Medicine, Faculty of
Obstetrics and Gynaecology, Department of
DSpace
UBCV
Kinshella, Mai-Lei Margaret
Doctor of Philosophy - PhD
University of British Columbia
Pre-eclampsia and other hypertensive disorders of pregnancy are the second leading cause of maternal mortality in sub-Saharan Africa, where they account for 22% of maternal deaths. Nutritious and diverse foods during pregnancy have vital roles to play in maternal and child health. The objectives of the work presented in this Dissertation are to: 1) systematically evaluate the current evidence for the influence of maternal diets on pregnancy hypertension in resource-constrained settings, 2) understand maternal diets and influencing factors from community perspectives in sub-Saharan Africa, and 3) investigate associations between nutritious and diverse maternal diets and pregnancy hypertension among women living in three geographical settings in sub-Saharan Africa. This study used quantitative data from the PRECISE Network, a prospective cohort that enrolled women in Kenya, Mozambique and The Gambia between June 2019 and December 2022. Based on foods consumed in the previous 24-hours, Minimum Dietary Diversity for Women (MDD-W) was assessed among women participating in PRECISE. Quantitative research was accompanied by qualitative community-based research in PRECISE study communities to understand local perspectives. The systematic review was the first to focus on dietary patterns and pregnancy hypertension in low- and middle-income countries and found substantially lower odds of pre-eclampsia associated with fruits or vegetables consumption at least once per week. Through qualitative interviews, community members shared that diverse meals were valued to support pregnancy health, but maternal diets did not substantially differ from typical household meals, especially due to affordability constraints. This was confirmed in the quantitative data that found pregnant women had slightly higher rates of meeting MDD-W, but the MDD-W was only met by less than half the population (48.4% pregnant vs 45.6% non-pregnant women). Among women with lower frequency of unhealthy food group consumption, meeting MDD-W was associated with reduced rates of gestational (aOR 0.84, 95% CI: 0.72-0.97) or any pregnancy hypertension (aOR 0.86, 95% CI: 0.75-0.99). The effect was not significant among women with higher unhealthy food consumption patterns. Findings support efforts to strengthen nutrition guidance to improve maternal health in sub-Saharan Africa.
MATERNAL DIETS AND DIETARY DIVERSITY IN RELATION TO PREGNANCY HYPERTENSION IN SUB-SAHARAN AFRICA by Mai-Lei Margaret Kinshella M.A., The University of British Columbia, 2012 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Women+ and Children’s Health Sciences) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) July 2024 © Mai-Lei Margaret Kinshella, 2024 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Maternal diets and dietary diversity in relation to pregnancy hypertension in sub-Saharan Africa submitted by Mai-Lei Margaret Kinshella in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Women+ and Children’s Health Sciences Examining Committee: Dr Rajavel Elango, Associate Professor, School of Population and Public Health, Department of Pediatrics, University of British Columbia Co-supervisor Dr Sophie E Moore, Professor of Global Women & Children's Health, Department of Women & Children's Health, King’s College London Co-supervisor Dr Sarka Lisonkova, Associate Professor, Department of Obstetrics and Gynaecology, University of British Columbia Supervisory Committee Member Dr Rachel Murphy, Associate Professor, School of Population and Public Health, University of British Columbia University Examiner Dr Annalijn I. Conklin, Associate Professor, Faculty of Pharmaceutical Sciences, University of British Columbia University Examiner Additional Supervisory Committee Members: Dr Patricia Janssen, Professor, School of Population and Public Health, University of British Columbia Supervisory Committee Member Dr Laura Magee, Professor of Women's Health, Department of Women & Children's Health, King’s College London Supervisory Committee Member iii Abstract Pre-eclampsia and other hypertensive disorders of pregnancy are the second leading cause of maternal mortality in sub-Saharan Africa, where they account for 22% of maternal deaths. Nutritious and diverse foods during pregnancy have vital roles to play in maternal and child health. The objectives of the work presented in this Dissertation are to: 1) systematically evaluate the current evidence for the influence of maternal diets on pregnancy hypertension in resource-constrained settings, 2) understand maternal diets and influencing factors from community perspectives in sub-Saharan Africa, and 3) investigate associations between nutritious and diverse maternal diets and pregnancy hypertension among women living in three geographical settings in sub-Saharan Africa. This study used quanitative data from the PRECISE Network, a prospective cohort that enrolled women in Kenya, Mozambique and The Gambia between June 2019 and December 2022. Based on foods consumed in the previous 24-hours, Minimum Dietary Diversity for Women (MDD-W) was assessed among women participating in PRECISE. Quantitative research was accompanied by qualitative community-based research in PRECISE study communities to understand local perspectives. The systematic review was the first to focus on dietary patterns and pregnancy hypertension in low- and middle-income countries and found substantially lower odds of pre-eclampsia associated with fruits or vegetables consumption at least once per week. Through qualitative interviews, community members shared that diverse meals were valued to support pregnancy health, but maternal diets did not substantially differ from typical household meals, especially due to affordability constraints. This was confirmed in the quantitative data that found pregnant women had slightly higher rates of meeting MDD-W, but the MDD-W was only met by less than half the population (48.4% pregnant vs 45.6% non-pregnant women). Among women with lower frequency of unhealthy food group consumption, iv meeting MDD-W was associated with reduced rates of gestational (aOR 0.84, 95% CI: 0.72-0.97) or any pregnancy hypertension (aOR 0.86, 95% CI: 0.75-0.99). The effect was not significant among women with higher unhealthy food consumption patterns. Findings support efforts to strengthen nutrition guidance to improve maternal health in sub-Saharan Africa. v Lay Summary High blood pressure during pregnancy is a leading cause of maternal death in Africa. Eating healthy and diverse foods during pregnancy is important for both mother and her growing baby. Based in the large PRECISE Network study in Kenya, Mozambique and The Gambia, this research used multiple methods (systematic review, quantitative survey data, and community-based qualitative research) to explore the pathways between maternal diets and risk of developing high blood pressure during pregnancy. Overall, the study found that community members largely had knowledge about the importance of healthy and diverse foods during pregnancy, but they described challenges in access to healthy foods. Survey results found that less than half of the women had adequately diverse diets. Women with dietary diversity, alongside lower consumption of unhealthy food groups, had lower rates of high blood pressure during pregnancy. These study findings can support efforts aimed at improving maternal health in Africa. vi Preface The work presented in this Dissertation was designed, conducted, analyzed, and written by Mai-Lei Woo Kinshella (M.W.K.) under the supervision of Dr Rajavel Elango (R.E.) and Dr Sophie E. Moore (S.E.M.), the supervisory committee comprised of Dr Sarka Lisonkova (S.L.), Dr Patricia Janssen (P.J.) and Dr Laura A. Magee (L.A.M.), and in partnership with colleagues and research staff with the PRECISE Network in the United Kingdom, Kenya, Mozambique and The Gambia. A version of “Safe Motherhood Initiative principals” in Chapter 1 has been published in “Kinshella, M.W., Moore, S.E., and Elango R. (2021) The missing focus on women's health in the First 1,000 days approach to nutrition. Public Health Nutrition. 24 (6):1526-1530.” M.W.K conceptualized, conducted the review, and wrote the first draft of the manuscript. S.E.M. and R.E. reviewed all versions of the paper and contributed to the interpretation and the structure of the paper. All authors read and approved the final published version. A version of Chapter 2 has been published. “Kinshella, M.W., Omar, S., Scherbinsky, K., Vidler, M., Magee, L.A., von Dadelszen, P., Moore, S.E., Elango, R. and the PRECISE Conceptual Framework Working Group. (2022) Maternal nutritional risk factors for pre-eclampsia incidence: findings from a narrative scoping review. Reproductive Health. 5;19 (1):188.” M.W.K conceptualized and developed the scoping review methodology for the manuscript, screened and analyzed abstracts and full texts with S.O. and K.S. Analyses and the first draft of the manuscript was written by M.W.K, which was reviewed and refined with the support of M.V., L.A.M., P.vD., S.E.M., R.E. All authors read and approved the final published version. vii A version of Chapter 3 has been published. “Kinshella, M.W., Omar, S., Scherbinsky, K., Vidler, M., Magee, L.A., von Dadelszen, P., Moore, S.E. and Elango, R. (2021) Maternal Dietary Patterns and Pregnancy Hypertension in Low- and Middle-Income Countries: A Systematic Review and Meta-analysis. Advances in Nutrition. 12 (6):2387-2400.” For this manuscript, M.W.K. conceptualized and created a plan for the systematic literature review, screened and analyzed abstracts and full texts with S.O. and K.S. M.W.K conducted the formal analyses and wrote the first draft of the manuscript. M.V., L.A.M., P.vD., S.E.M., R.E. reviewed all versions of the paper and contributed to the interpretation and the structure of the paper. All authors read and approved the final published version. For Chapters 4, 5, 6, and 7, M.W.K. independently developed a research plan, which was conducted and analyzed in partnership with PRECISE Network collaborators. A Kenyan research assistant, S.D., supported in piloting the qualitative coding framework. M.W.K. led the writing of the chapters. All chapters were supported and reviewed by supervisors, the supervisory committee, and global PRECISE Network collaborators. While currently being prepared for submission, Chapters 4, 5, 6 and 7 have not yet been published. For a list of other PhD publications and presentations (all-encompassing), please see Appendix A. The study received ethics approval from the University of British Columbia (H20-00143), the Aga Khan University Nairobi (2021/IERC-159), The Gambia Government/Medical Research Council The Gambia (MRCG) Joint Ethics Committee (26342), and the Centro de Investigação em Saúde de Manhiça (CIBS-CISM/034/2022). viii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ....................................................................................................................... viii List of Tables ............................................................................................................................. xvii List of Figures ........................................................................................................................... xviii List of Abbreviations ...................................................................................................................xx Glossary .................................................................................................................................... xxiii Acknowledgements ....................................................................................................................xxv Dedication ................................................................................................................................ xxvii Chapter 1: Introduction ................................................................................................................1 1.1 Maria’s story ................................................................................................................... 1 1.2 Background and rationale ............................................................................................... 3 1.3 Research paradigm and approach ................................................................................... 6 1.3.1 Human Rights Based Approach .................................................................................. 6 1.3.2 Safe Motherhood Initiative principles ........................................................................ 8 1.4 Research objectives ......................................................................................................... 9 1.5 Research setting and methods ......................................................................................... 9 1.5.1 The PRECISE Network .............................................................................................. 9 1.5.2 Research setting ........................................................................................................ 10 1.5.3 Study design .............................................................................................................. 10 ix 1.5.4 The PRECISE Network prospective cohort study .................................................... 11 1.5.4.1 Study participants and recruitment ................................................................... 11 1.5.4.2 Data collection methods .................................................................................... 12 1.5.4.3 Minimum dietary diversity for women ............................................................. 12 1.5.5 Focused ethnography ................................................................................................ 14 1.5.5.1 Qualitative approach ......................................................................................... 14 1.5.5.2 Study participants and recruitment ................................................................... 15 1.5.5.3 Data collection methods .................................................................................... 16 1.5.6 Ethics considerations ................................................................................................ 17 1.6 Chapter breakdown ....................................................................................................... 18 Chapter 2: Maternal nutritional risk factors for pre-eclampsia incidence: findings from a narrative scoping review .............................................................................................................21 2.1 Introduction ................................................................................................................... 21 2.2 Methodology ................................................................................................................. 23 2.3 Results ........................................................................................................................... 25 2.3.1 Poor placentation, immune response and inflammation ........................................... 28 2.3.2 Oxidative stress ......................................................................................................... 30 2.3.3 Maternal endothelial dysfunction ............................................................................. 34 2.3.4 High blood pressure .................................................................................................. 37 2.4 Discussion ..................................................................................................................... 39 2.5 Conclusion .................................................................................................................... 42 Chapter 3: Maternal dietary patterns and pregnancy hypertension in low- and middle-income countries: a systematic review and meta-analysis .......................................................44 x 3.1 Introduction ................................................................................................................... 44 3.2 Methods......................................................................................................................... 45 3.3 Results ........................................................................................................................... 48 3.3.1 Characteristics of included studies............................................................................ 49 3.3.2 Quality assessment .................................................................................................... 55 3.3.3 Healthy dietary patterns ............................................................................................ 56 3.3.4 Vegetable dietary pattern .......................................................................................... 57 3.3.5 Fruit dietary pattern ................................................................................................... 59 3.3.6 Other dietary patterns ................................................................................................ 61 3.3.7 Factors associated with dietary patterns ................................................................... 62 3.4 Discussion ..................................................................................................................... 63 3.5 Conclusion .................................................................................................................... 67 Chapter 4: Community perspectives on maternal diets and dietary diversity in rural Kenya, Mozambique and The Gambia: a qualitative study ....................................................69 4.1 Introduction ................................................................................................................... 69 4.2 Methods......................................................................................................................... 70 4.2.1 Study design and research setting ............................................................................. 70 4.2.2 Recruitment and selection ......................................................................................... 70 4.2.3 Data collection .......................................................................................................... 71 4.2.4 Data analysis ............................................................................................................. 72 4.2.5 Reflexivity................................................................................................................. 73 4.3 Findings......................................................................................................................... 74 4.3.1 Participant characteristics ......................................................................................... 74 xi 4.3.2 Typical dietary patterns ............................................................................................. 75 4.3.3 Perceptions of dietary diversity ................................................................................ 77 4.3.4 Perceptions of influencing factors ............................................................................ 79 4.3.5 Thematic map............................................................................................................ 83 4.4 Interpretation ................................................................................................................. 85 4.4.1 Summary of findings in comparison to the literature ............................................... 85 4.4.2 Implications for research and policy ......................................................................... 87 4.4.3 Strengths and limitations........................................................................................... 88 4.5 Conclusion .................................................................................................................... 90 Chapter 5: Prevalence and associated factors of meeting minimum dietary diversity among pregnant and non-pregnant women of reproductive age in three sub-Saharan African countries ........................................................................................................................................91 5.1 Introduction ................................................................................................................... 91 5.2 Methods......................................................................................................................... 92 5.2.1 Study design, setting, and participants ...................................................................... 92 5.2.2 Study variables and outcome .................................................................................... 92 5.2.3 Data collection and analysis ...................................................................................... 93 5.3 Results ........................................................................................................................... 94 5.3.1 Participant characteristics ......................................................................................... 94 5.3.2 Dietary diversity........................................................................................................ 97 5.3.3 Correlates of meeting minimum dietary diversity .................................................... 99 5.4 Discussion ................................................................................................................... 102 5.4.1 Comparison with the literature ................................................................................ 102 xii 5.4.2 Strengths and limitations......................................................................................... 106 5.5 Conclusion .................................................................................................................. 107 Chapter 6: Characterizing dietary diversity patterns among pregnant women in Kenya, Mozambique and The Gambia: A mixed methods latent class analysis and qualitative content analysis ..........................................................................................................................108 6.1 Introduction ................................................................................................................. 108 6.2 Methods....................................................................................................................... 109 6.2.1 Study design and setting ......................................................................................... 109 6.2.2 Quantitative data collection and analysis ................................................................ 110 6.2.3 Qualitative data collection and analysis .................................................................. 111 6.3 Results ......................................................................................................................... 111 6.3.1 Participant characteristics ....................................................................................... 111 6.3.2 Overall food groups consumed yesterday ............................................................... 112 6.3.3 Dietary pattern analyses .......................................................................................... 115 6.3.3.1 Kenya .............................................................................................................. 116 6.3.3.2 Mozambique ................................................................................................... 116 6.3.3.3 The Gambia ..................................................................................................... 117 6.3.4 Qualitative results ................................................................................................... 119 6.3.4.1 Staple foods ..................................................................................................... 119 6.3.4.2 Luxury foods and special occasion foods ....................................................... 122 6.3.4.3 Local food conceptualizations ........................................................................ 123 6.3.4.4 Unhealthy foods .............................................................................................. 124 6.4 Discussion ................................................................................................................... 126 xiii 6.4.1 Summary of findings............................................................................................... 126 6.4.2 Nutritional implications .......................................................................................... 128 6.4.3 Implications for research and policy ....................................................................... 130 6.4.4 Strengths and limitations......................................................................................... 131 6.5 Conclusion .................................................................................................................. 131 Chapter 7: Associations between maternal dietary diversity status and pregnancy hypertension in Kenya, Mozambique and The Gambia ........................................................133 7.1 Introduction ................................................................................................................. 133 7.2 Methods....................................................................................................................... 134 7.2.1 Study design and population ................................................................................... 134 7.2.2 Exposure assessment ............................................................................................... 135 7.2.3 Outcome assessment and sample size ..................................................................... 135 7.2.4 Covariates assessment ............................................................................................. 136 7.3 Results ......................................................................................................................... 137 7.3.1 Participant characteristics ....................................................................................... 137 7.3.2 Dietary diversity status and prevelances of pregnancy hypertension ..................... 139 7.3.3 Meeting minimum dietary diversity for women and pregnancy hypertension ....... 140 7.4 Discussion ................................................................................................................... 141 7.4.1 Summary of findings............................................................................................... 141 7.4.2 Comparisons to the literature .................................................................................. 142 7.4.3 Implications for research and practice .................................................................... 143 7.4.4 Strengths and limitations......................................................................................... 145 7.5 Conclusion .................................................................................................................. 146 xiv Chapter 8: Summary and recommendations ..........................................................................147 8.1 Overview ..................................................................................................................... 147 8.2 Summary of objectives and findings........................................................................... 148 8.2.1 Objective 1 .............................................................................................................. 148 8.2.2 Objective 2 .............................................................................................................. 148 8.2.3 Objective 3 .............................................................................................................. 149 8.2.4 Mapping the pathways of risk between meeting MDD-W and pregnancy hypertension and the complex involvement of socio-economic status ............................... 151 8.3 Unique contributions and limitations .......................................................................... 152 8.3.1 Critical evaluation of the influential First 1,000 Days and advancing women-centered maternal nutrition research approaches ................................................................ 152 8.3.2 Mixed-methods study design engaged multiple perspectives ................................. 154 8.3.3 Expanding the scope of the MDD-W tool .............................................................. 155 8.3.3.1 Advanced latent class analysis for maternal dietary patterns research ........... 156 8.3.3.2 Developed a modified MDD-W methodology that incorporated unhealthy food group intake .................................................................................................................... 157 8.3.4 Pathways of risk between dietary diversity and pregnancy hypertension grounded in evidence of potential biological mechanisms ..................................................................... 157 8.4 Application of research findings ................................................................................. 158 8.4.1 Global health implications and recommendations .................................................. 158 8.4.2 Strengthening maternal nutrition in Kilifi, Kenya: A knowledge mobilization workshop with Kenyan Department of Health ................................................................... 159 8.4.3 Recommendations for future research .................................................................... 162 xv 8.5 Conclusions ................................................................................................................. 164 Bibliography ...............................................................................................................................165 Appendices ..................................................................................................................................205 ............................................................................................................................. 205 A.1 List of other PhD publications and presentations (all-encompassing) .................... 205 Chapter 1 appendix for the introduction and methods ....................................... 210 B.1 Semi-structured interview guide for in Swahili for Kenya ..................................... 210 B.2 Semi-structured interview guide in Portuguese for Mozambique .......................... 219 B.3 Semi-structured interview guide in English for The Gambia ................................. 223 Chapter 2 appendix for the maternal nutritional risk factors for pre-eclampsia incidence scoping review ........................................................................................................ 228 C.1 Search terms ............................................................................................................ 228 C.2 Excluded studies ..................................................................................................... 229 Chapter 3 appendix for the systematic review on maternal diet and pregnancy hypertension in low- and middle-income countries ................................................................ 232 D.1 Systematic review search strategy .......................................................................... 232 D.2 Excluded studies ..................................................................................................... 235 D.3 Dietary pattern classifications from each study ...................................................... 238 D.4 Outcome definitions by study ................................................................................. 240 D.5 Reported outcomes by study ................................................................................... 242 D.6 ROBINS-I Risk of Bias quality assessment ........................................................... 251 D.7 Summary risk of bias .............................................................................................. 251 D.8 Adjustment factors in multivariable analyses ......................................................... 252 xvi Chapter 4 appendix for the community perspectives qualitative study .............. 256 E.1 Qualitative analysis coding framework .................................................................. 256 E.2 Frequency of reported themes ................................................................................. 257 E.3 Frequency of themes reported by participant group and number of participants ... 258 E.4 Community perspectives on influencing factors by country .................................. 259 Chapter 5 appendix for the prevalence and factors of meeting minimum dietary diversity for women study ...................................................................................................... 262 F.1 Literature review of sub-Saharan African studies reporting determinants of dietary diversity among women ...................................................................................................... 262 F.2 Model selection for determinants of meeting MDD-W .......................................... 270 Chapter 6 appendix for the mixed methods study on characterizing dietary diversity patterns ..................................................................................................................... 273 G.1 Qualitative content analysis coding framework from Nvivo .................................. 273 G.2 Consumption patterns of meat, poultry and fish by sub-groups ............................. 274 G.3 Model-fit statistics for latent class analysis ............................................................ 274 G.4 Food group consumption patterns across latent classes in Kenya, Mozambique and The Gambia ......................................................................................................................... 275 G.5 Summary of main foods consumed in each food group ......................................... 276 G.6 Illustrative quotes about food groups by country ................................................... 279 Chapter 7 appendix for the association between maternal dietary diversity and pregnancy hypertension study ................................................................................................. 295 H.1 Model selection ....................................................................................................... 295 xvii List of Tables Table 2.1 Role of maternal dietary components in the development of pre-eclampsia ................ 27 Table 3.1 Eligibility criteria .......................................................................................................... 47 Table 3.2 Characteristics of included studies ............................................................................... 51 Table 4.1 Demographic characteristics of interview participants ................................................. 74 Table 4.2 Typical meals among maternal and general populations in Kenya, Mozambique and The Gambia ................................................................................................................................... 76 Table 5.1 Demographics of PRECISE participants included in nutrition analyses ...................... 95 Table 5.2 Dietary diversity scores and prevalence of meeting minimum dietary diversity for women ........................................................................................................................................... 98 Table 5.3 Correlates of meeting minimum dietary diversity for women .................................... 100 Table 5.4 Correlates of higher dietary diversity from the PRECISE cohort compared to other dietary diversity studies from sub-Saharan Africa ...................................................................... 105 Table 6.1 Characteristics of pregnant women in the PRECISE cohort ...................................... 112 Table 6.2 Food groups consumed in the previous 24 hours by country and overall .................. 114 Table 6.3 Interview participants by country and population group ............................................ 119 Table 6.4 Summary of key converging quantitative and qualitative findings ............................ 127 Table 7.1 Participant characteristics ........................................................................................... 138 Table 7.2 Prevelances of gestational hypertension and any pregnancy hypertension by dietary diversity status ............................................................................................................................ 140 Table 7.3 Associations between dietary diversity status with gestational and any pregnancy hypertension ................................................................................................................................ 141 xviii List of Figures Figure 2.1 PRISMA flow diagram for the maternal nutritional risk factors for pre-eclampsia incidence scoping review .............................................................................................................. 26 Figure 3.1 PRISMA flow diagram for the systematic review on maternal dietary patterns and pregnancy hypertension in low- and middle-income countries .................................................... 49 Figure 3.2 (A) Adequate consumption of vegetables compared with low or no consumption for the risk of developing pre-eclampsia in low- and middle-income countries; (B) Sensitivity analysis excluding studies classed as serious risk of bias ............................................................. 59 Figure 3.3 (A) Adequate consumption of fruits compared with low or no consumption for the risk of developing pre-eclampsia in low and middle-income countries; (B) Sensitivity analysis excluding studies classed as serious risk of bias ........................................................................... 60 Figure 3.4 Alcohol use during pregnancy and risk of pre-eclampsia in low- and middle-income countries ........................................................................................................................................ 62 Figure 4.1 Frequency map of reported themes for dietary diversity influencing factors ............. 80 Figure 4.2 Thematic map of community perspectives on dietary diversity among maternal and general populations ....................................................................................................................... 84 Figure 5.1 Profile of PRECISE participants in the nutrition analyses .......................................... 95 Figure 6.1 Food groups consumed in the previous 24 hours by country and overall ................. 113 Figure 6.2 Dietary patterns among pregnant women in Kenya, Mozambique and The Gambia 115 Figure 6.3 Dietary diversity patterns identified by latent class analysis in (A) Kenya, (B) Mozambique, and (C) The Gambia ............................................................................................ 118 Figure 8.1 Pathways of risk between meeting minimum dietary diversity for women and pregnancy hypertension in sub-Saharan Africa .......................................................................... 152 xix Figure 8.2 Integrating four approaches to strengthen research on maternal diets and pregnancy hypertension prevention .............................................................................................................. 153 Figure 8.3 Participants of the Maternal Nutrition Stakeholders Meeting held in Kilifi, Kenya on July 18th 2023 .............................................................................................................................. 160 Figure 8.4 Community Health Promoters Open Forum in Mariakani on Feb 23rd 2024 ........... 161 xx List of Abbreviations AIC – Akaike Information Criterion AJOL – African Journals Online database ANC – antenatal care aOR – adjusted odds ratio BIC – Bayesian Information Criterion BMI – body mass index CEDAW – Convention on the Elimination of All Forms of Discrimination Against Women CENTRAL – Cochrane Central Register of Controlled Trials database CI – confidence interval CINAHL – Cumulative Index to Nursing and Allied Health database CH – chronic hypertension CHP – community health promoters cOR – crude odds ratio COREQ - Consolidated Criteria for Reporting Qualitative Research DASH - Dietary Approaches to Stop Hypertension DDS – dietary diversity score DHS – Demographic and Health Surveys FAO – Food and Agricultural Organization of the United Nations FFQ – food frequency questionnaire g – gram GH – gestational hypertension HDP – hypertensive disorders of pregnancy HICs – high-income countries xxi HR(S)– hour(s) HRBA – human rights based approach ICCPR – International Covenant on Civil and Political Rights ICESCR – International Covenant on Economic, Social and Cultural Rights IDI – in-depth interview IQR – interquartile range L – litre LCA – latent class analysis LMICs – low- and middle-income countries MCH – maternal and child health MDD-W – minimum dietary diversity for women MDG(s) - Millennium Development Goal(s) mg – milligram M-H – Mantel-Haeszel statistical method mL– milliliter MMR – maternal mortality ratio NA – not available NCD(s) – non-communicable disease(s) NS – not significant OR – odds ratio PCA – principal component analysis PE – pre-eclampsia PIH – pregnancy-induced hypertension PRECISE – PREgnancy Care Integrating translational Science, Everywhere xxii PRISMA – Preferred Reporting Items for Systematic Reviews and Meta-Analysis PRISMA-ScR – Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews PTH – parathyroid hormone PUFA - polyunsaturated fatty acids RCT – randomized controlled trials RoB – risk of bias RR – risk ratio SD – standard deviation SDG(s) – Sustainable Development Goal(s) SES – socio-economic status SIP – superimposed pre-eclampsia SMD – standardized mean difference SMI – Safe Motherhood Initiative uNK - uterine natural killer cells VEGF - vascular endothelial growth factor VIF – variance inflation factor WHO – World Health Organization WRA – woman of reproductive age YRS – years xxiii Glossary Chronic hypertension – Hypertension detected pre-pregnancy or before 20 weeks of gestation. First 1000 Days – An approach to nutrition that emphasizes early life nutrition between conception to a child’s second birth as the most critical period of growth and development in a child’s life, with far-reaching effects on capacities to work and learn, and intergenerational effects on their own children. Adequate early life nutrition is seen as essential to global health and development. Gestational hypertension – Novel hypertension arising at or after 20 weeks’ gestation in the absence of proteinuria, maternal end-organ dysfunction or uteroplacental dysfunction. Human Rights Based Approach (HRBA) – Emphasizes health as a human right through attention to the social determinants of health and the principles of availability, accessibility, acceptability and quality of facilities and services, participation, equality and non-discrimination, and accountability. Hypertensive disorders of pregnancy – Diagnosis of systolic blood pressure ≥140 and/or diastolic blood pressure ≥90 mmHg during gestation and/or postpartum. Minimum Dietary Diversity for Women (MDD-W) – Population-level indicator of micronutrient adequacy among women of reproductive age based on at least five out of ten healthy food groups consumed in the previous 24-hours. Pre-eclampsia – Novel hypertension arising at or after 20 weeks’ gestation with proteinuria, maternal end-organ dysfunction and/or uteroplacental dysfunction. Superimposed pre-eclampsia xxiv is a subset of pre-eclampsia that involves the development of proteinuria, maternal end-organ dysfunction and/or uteroplacental dysfunction among women with chronic hypertension. Safe Motherhood Initiative (SMI) – An initiative launched in 1987 to ensure all women receive the care they need to be safe and healthy throughout pregnancy and childbirth. xxv Acknowledgements I would like to express my deepest gratitude to my supervisors, Dr Rajavel Elango and Dr Sophie Moore, for their unwavering support, guidance, and mentorship throughout this journey. Their expertise, encouragement, and constructive feedback have been invaluable in shaping this Dissertation and my professional, academic and personal growth. They have kept me focused on my PhD – a momentous task – while nurturing my initiative to grow my skills and knowledge. I am also indebted to my dissertation committee members, Dr Sarka Lisonkova, Dr Patti Janssen, and Dr Laura Magee, for their insightful comments, suggestions, and expertise, which have enriched the quality of this work. I would also like to thank my dissertation committee chair, Dr Angela Devlin, who kept us on track and shared invaluable insights into my research beyond the roles of a typical chair. To my supervisors and committee members, thank you so much for making the time to meet across global timezones. Thank you to the Canadian Institutes of Health Research for supporting my research through the Vanier Canadian Graduate Scholarship and the Michael Smith Foreign Study Supplement, to the Friedman Award for Scholars in Health to support my study abroad at King’s College London, to the University of British Columbia for continued support through the President’s Academic Excellence Initative PhD Award and the Four Year Fellowship. I am grateful for UBC Public Scholars Initiative for the inspiration, connections and support in becoming a public scholar and for the Emerging Voices in Global Health program in connecting me to the vibrant network of movers and shakers from around the world. xxvi Thank you to the Institute of Global Health, BC Children’s Hospital Research Institute, the UBC Women’s Health Research Cluster for being my academic home these past years. To Natalie Towhey and all of the amazing leadership with the Women+ and Child Health Sciences program, thank you so much for your continued support during my PhD journey. I am grateful to fellow students in WACH, the Elango Lab and the Global Health Nutrition group at King’s College London, whose friendship and encouragement have been a source of strength, inspiration and much needed laughs. I want to also thank the PRECISE Network and the inspiring leadership by Dr Peter von Dadelszen, Dr Laura Magee, Dr Marleen Temmerman, Dr Esperança Sevene, Dr Anna Roca, Dr Umberto D'Alessandro and Dr Marianne Vidler. I am eternally grateful to have the opportunity to work with and learn from the PRECISE research teams in Kenya, Mozambique and The Gambia, including Dr Angela Koech, Onesmus Wanje, Helena Boene, Anifa Vala, Hawanatu Jah, Yahaya Idris, and countless others. To Shilla Dama, Rosa Pires, Papa Jagne, and Alpha Jallow, I will always remember our times in the field – the struggles and the laughs as we cooked, cleaned and chatted with community members. To the women, their families and community leaders, thank you so much for sharing your stories and experiences. This research would not have been possible without you. Asante sana! Obrigada! Khanimambo! Jera-jef! Abaraka bakeh! Jarama! Last but not least, I want to thank my family for their unconditional love, encouragement, and support, especially my husband Bryan Kinshella whose unwavering belief in me has been a driving force behind my accomplishments. xxvii Dedication This Dissertation is dedicated to my son, Kodiak Woo Kinshella, who was born during my PhD journey and joined me on three months of fieldwork in sub-Saharan Africa starting when he was 10 months old. 1 Chapter 1: Introduction 1.1 Maria’s story A 32-year old woman whom I call Maria (a pseudonym) was standing over a fire, bending over to cook, when I first met her during my fieldwork in Mozambique. This was impressive because she was nine months pregnant . Maria lived at her small home, made of sticks and wood with a corrugated tin roof, down a long sandy road from the town centre. Her husband was away in South Africa for work, and though she was living with her brother’s family, she was essentially a single mother. She cooked for herself, ground maize kernels into flour on her own and went out to the fields in the morning. Today, she made a stew from sweet potato leaves cooked with cherry tomatoes and a small onion, then we went outside to grind fermented maize bran and maize kernel for xima – a stiff porridge that formed a starchy base of meals. Green leafy vegetables and xima was a local staple and considered healthy to eat, especially for pregnant women. A slightly sour smell from the fermented grain filled the air as beads of sweat formed on our foreheads when we took turns grinding. The pestle was heavy; it was not easy work. Maria’s maternity experience highlights her strength, yet vulnerability. The next time we visited Maria five days later, she had given birth to a beautiful and healthy baby girl weighing 2900 grams and was heartily devouring xima and green leafy vegetables cooked with coconut milk. The critical impact of nutrition during pregnancy has been highlighted by the influential First 1,000 Days approach to nutrition, which emphasizes the importance of adequate nutrition between a woman’s pregnancy and her child’s second birthday as the most critical period of growth and development in a child’s life, with far-reaching effects on capacities to work and learn, and intergenerational effects on their own children (1–5). However, outcomes tend to be 2 focused on fetal and infant growth and development. With Maria, for example, an adequate diet during pregnancy may have supported her to deliver an infant within the normal weight range (2500-4000g), which reduces the risk of neonatal mortality, childhood stunting, and poor cognitive development (6,7). While the beneficial effects on child health are invaluable, there is a gap in the literature on practice around the impact of nutrition during pregnancy on maternal health. While maternal mortality decreased globally by 44% between 1990-2015 during the Millennium Development Goals (MDGs), there is an urgent need for continued focus on improving maternal health outcomes around the world (8,9). Progress towards the Sustainable Development Goal (SDG) 3.1 to reduce the global maternal mortality ratio (MMR) to less than 70 per 100 000 live births has stagnated, especially in low-income countries (8,9). The World Health Organization (WHO) reported an MMR of 531 per 100 000 live births in the African region in 2020, which accounted for 69% of the total global burden of maternal deaths (10). Hypertensive disorders of pregnancy (HDP) was a leading cause of maternal deaths in Africa, and contribute to 22.1% of maternal deaths (10,11). Globally, the incidence of HDPs increased by 10.9% between 1990 and 2019, with highest incidences in 2019 recorded in Western and Eastern sub-Saharan Africa (12). Returning to Maria’s story, a study of 4253 pregnant women from Southern Mozambique found that HDP occurred in 10.9% of pregnancies , suggesting that about one in ten women experience hypertension during pregnancy (13). For Maria and other women across sub-Saharan Africa, did their ability to obtain nutritious and diverse foods during pregnancy impact their likelihood of experiencing an HDP and other adverse maternal outcomes? This Dissertation will primarily 3 focus on women in sub-Saharan Africa, their diet, hypertensive disorders, and local contextual characteristics. 1.2 Background and rationale HDPs are the second leading direct cause of maternal deaths worldwide (14,15). Pre-eclampsia, the most serious form of HDP, is characterized by new onset hypertension (≥140/90 mmHg) after 20 weeks gestation with proteinuria, maternal end-organ involvement, and/or uteroplacental dysfunction (16,17). HDPs also include chronic hypertension (hypertension that predates the pregnancy or is diagnosed early before 20 weeks gestation), gestational hypertension (hypertension after 20 weeks without signs of organ damage), and superimposed pre-eclampsia (chronic hypertension that develops signs of organ damage) (17). Together, HDPs complicate 5-10% of pregnancies, including 2-4% with pre-eclampsia, according to global estimates (13,18). Pre-eclampsia is estimated to contribute up to a third of all cases of serious maternal morbidity, with approximately 5% of women with pre-eclampsia requiring admission to intensive care, and is associated with development of non-communicable diseases such as cardiovascular disease, type II diabetes and renal impairment in the long-term (14,19). Pre-eclampsia is closely associated with low birthweight (<2500g), and a contributing factor in 12% of infants born with intrauterine growth restriction and 19% of preterm birth (19–22). Pre-eclampsia is a complex pregnancy-specific inflammatory disorder that involves inadequate placentation, maternal inflammatory response, generalized endothelial dysfunction and hypertension (23,24). Nutrition plays an important role in placentation and certain micronutrients have clinical antioxidant, anti-inflammatory and blood pressure regulating properties; consequently, nutritional factors may trigger or exacerbate the development of pre-eclampsia 4 (25–27). While placental disorders of pregnancy, including pre-eclampsia, are well investigated in high-income countries (HICs), current limitations of the evidence base include inadequate research conducted in low- and middle-income countries (LMICs) (28). This has led to a gap in knowledge as there are likely different pathways of risk in resource-constrained settings, including an overall higher prevalence and different prevalent forms of malnutrition compared to HICs (28). A recent umbrella review of maternal nutritional supplementation and dietary intervention trials found that vitamin D and/or calcium supplementation (given after 20 weeks gestation in most studies) were promising interventions to help prevent pre-eclampsia but many single micronutrient interventions did not result in significant effects (29). This may point to a need to look more broadly at maternal dietary patterns, particularly in resource-constrained settings where someone who has a low dietary intake of one nutrient may also experience low intakes of other nutrients as well. A meta-analysis of four observational studies found that a healthy dietary pattern characterized by high consumption of fruits, vegetables, legumes, whole grains and fish may reduce the odds of pre-eclampsia by 22% (30). However, the review only included studies conducted in HICs (30). Dietary research in all settings, but especially in LMICs, is challenged by the need for highly trained data collectors, resource-intensive and time-consuming data collection, and availability of complete food composition tables in many dietary assessment methodologies (31,32). Additionally, some methods such as weighted food records require respondents to have literacy and numeracy skills (31,32). Dietary diversity scores, which count the number of food groups consumed over a given period as a proxy measure of diet quality, is a simple and practical 5 dietary assessment method that the Food and Agricultural Organization of the United Nations (FAO) describes as feasible for contexts where resource and capacity constraints might restrict the use of more detailed dietary assessment methods (31). Developed by the FAO, the Minimum Dietary Diversity for Women (MDD-W) has been validated to reflect adequacy across 11 micronutrients (vitamin A, thiamine, riboflavin, niacin, vitamin B6, folate, vitamin B12, vitamin C, calcium, iron and zinc) as a simple yet accurate population-level overview of diet quality among women of reproductive age in resource-limited settings (33,34). The MDD-W indicator was especially designed for settings where weighted food records and other dietary assessment methods that measure the specific types and amounts of food consumed are unfeasible (32) and is now widely used by international and national organizations for nutritional status tracking (35). However, though the MDD-W was constructed for women, reports of health outcomes associated with MDD-W among women are scarce, with the exception of a protective effect of diverse diets during pregnancy on maternal anemia (36–38). Reported adverse pregnancy outcomes largely focused on reduced risk of small-for-gestational-age, preterm delivery, and low birthweight infants (39–42), with lasting effects on reduced childhood stunting (43–45). Only four studies globally have reported dietary diversity scores in association with pregnancy hypertension or self-reported symptoms suggestive of pre-eclampsia (46–49). Of these four studies, there was a large (N= 19,917) retrospective cohort study from the United States (48) and a smaller case-control study (N=340) from Ethiopia (49) that specifically used MDD-W, which resulted in conflicting findings on pregnancy hypertension (48,49). There is a need for high-quality research to understand the potential impacts of nutritious and diverse maternal diets on pregnancy hypertension in resource-constrained settings where there 6 are disproportionate burdens of adverse maternal outcomes (50), and maternal diets are often inadequate (51). There are research gaps especially in rural areas of low-income countries where resources are most constrained and there is a higher risk of adverse outcomes associated with HDPs (52,53). The development of appropriate and effective interventions for HDP requires further understanding of the pathways of risk. 1.3 Research paradigm and approach 1.3.1 Human Rights Based Approach This research uses a Human Rights Based Approach (HRBA) to frame research questions in the exploration of the First 1000 Days approach to nutrition, maternal diet and pregnancy hypertension. HBRA is strongly supported by United Nations organizations, including the WHO, that recognizes that human rights underpin their work (54). As described by the WHO, “A human rights-based approach aims to support better and more sustainable development outcomes by analyzing and addressing the inequalities, discriminatory practices and unjust power relations which are often at the heart of development problems” (55). Within a rights-based approach, health is a Human Right. The basis of human rights is equal dignity for all human beings, which is recognized in the International Covenant on Civil and Political Rights (ICCPR) (56) and the International Covenant on Economic, Social and Cultural Rights (ICESCR) (57). This means that each person is considered an “ends” in themselves with intrinsic worth, and not treated as a “means” to further another goal (58). Consequently, this research aims to expand on the First 1,000 Days approach to nutrition where the primary focus is on child health outcomes and the mother serves as a means to that end (59,60). While maternal 7 diet is an important way of targeting fetal growth, there is a lack of focus on the mother herself and maternal nutrition interventions have rarely focused on women as the direct beneficiaries (2,61,62). Even in the ICESCR where the Right to Health is covered in Article 12 as “the right of everyone to the enjoyment of the highest attainable standard of physical and mental health”, maternal health is considered within steps towards “the provision for the reduction of the stillbirth-rate and of infant mortality and for the healthy development of the child” (Article 12.2.a) (57), and clearly highlights the systematic neglect of maternal health as intrinsically valuable even in fundamental human rights covenants. Maternal mortality or maternal health in general is not mentioned in the ICESCR (57). The Convention on the Elimination of All Forms of Discrimination Against Women (CEDAW) more explicitly states that appropriate measures to eliminate discrimination against women include ensuring “appropriate services in connection with pregnancy, confinement and the post-natal period, granting free services where necessary, as well as adequate nutrition during pregnancy and lactation” (Article 12.2) (63). Employing HRBA, the missing focus on health outcomes in women within the First 1000 days approach to nutrition is an injustice and this research aims to center women in the research and research process, recognizing that maternal dietary interventions are important to the health and lives of women. Human rights-based approaches to health highlight underlying social determinants of health, the availability, accessibility, acceptability of services, transparency, accountability, meaningful participation, and the principles of equality and non-discrimination (64,65). Research that uses a HRBA amplifies the voices of women, their families and communities to emphasize their lived experiences at the core of this study. 8 1.3.2 Safe Motherhood Initiative principles Concerns about the missing focus on maternal health outcomes builds on concepts brought up by the Safe Motherhood Initiative (SMI). In the seminal paper by Rosenfield and Maine in 1985, the question of where is the “M” (mother) in “MCH” (maternal and child health) was posed to highlight the missing focus on interventions that specifically targeted maternal health outcomes, such as strengthening emergency obstetrical care at referral health facilities (66). Launched in 1987, SMI was developed to counter the relative neglect of women’s health within the attention on child survival and the failure to address maternal health as intrinsically valuable beyond its impact on child health (67,68). Obstetrician Mahmoud Fathalla wrote, “Women are not dying during pregnancy and childbirth because of conditions that are difficult to manage. They are dying because the societies in which they live did not see fit to invest what is needed to save their lives. It is a question of how much the life of a woman is considered to be worth…Even with the tragedy of maternal mortality, a justification sometimes put forward for investment in keeping mothers alive is that their survival is critical for the survival of the children. Resources allocated for maternal health are generally grouped together with resources for child health in a ‘mother and child health (MCH)’ package” (69). Described as a “measurement trap”, quality maternal health data is required to establish levels and trends, identify determinants of risk, and evaluate the effectiveness of maternal health programming (70). A lack of quality maternal health data is both a result and contributor to the neglect of maternal health as a priority topic. Taken in the context of maternal and child nutrition, the relative gap in knowledge on women’s health outcomes in maternal dietary 9 interventions contributes to lower prioritization and less research. Research on the impact of maternal nutrition on her health and understanding the contexts of food and nutritional security within women’s lived experiences is needed to help fill the current research-advocacy gap. 1.4 Research objectives The purpose of the research presented in this Dissertation is to map the pathways of risk between the ability to obtain nutritious and diverse maternal diets with pregnancy hypertension among women in sub-Saharan Africa, and investigate contextual risk factors. This is divided into three primary objectives: Objective 1: To evaluate the current evidence for the influence of maternal diets on pregnancy hypertension in resource-constrained settings. Objective 2: To understand maternal diets and influencing factors from community perspectives in sub-Saharan Africa. Objective 3: To investigate associations between nutritious and diverse maternal diets and pregnancy hypertension among women in the PRECISE Network cohort in Kenya, Mozambique and The Gambia. Meeting Minimum Dietary Diversity for Women is hypothesized to be associated with reduced odds of pregnancy hypertension. 1.5 Research setting and methods 1.5.1 The PRECISE Network The PRECISE (PREgnancy Care Integrating translational Science, Everywhere) Network is an interdisciplinary group of research scientists and health advocates from sub-Saharan Africa, Europe, Canada and the USA investigating placental disorders and other complications of 10 pregnancy in sub-Saharan Africa, primarily through a prospective pregnancy cohort study in Kenya, Mozambique and The Gambia, as well as through subsidiary studies such as the maternal diets qualitative study for this Dissertation (71). Most research on the pathways to disease for placental disorders are conducted in HICs, while LMIC-based research is under-represented. Pathways of disease within resource-constrained sub-Saharan African settings may not be fully captured by research from HICs, such as interconnected challenges of malnutrition, rural settings with limited transport and health infrastructure, and other inequities in social determinants (71). The PRECISE research programme emphasizes a 360° approach that situates women in their social, geographic, health services, nutritional, and chronic disease contexts, alongside collecting biophysical and biomarker data to better understand placental disorders and other complications of pregnancy in sub-Saharan Africa (72). 1.5.2 Research setting PRECISE was conducted in Kilifi County in the coastal region of Kenya, Manhiça District in Maputo Province in the Southern region of Mozambique, and the North Bank (also known as the Kerewan Local Government Area) in The Gambia to represent Eastern, Southern and Western Africa, respectively. PRECISE study sites included both rural (Rabai Hospital in Kenya, Xinavane Hospital in Mozambique, Illiasa and Ngayen Sanjal Health Centres in The Gambia) and periurban (Mariakani Hospital in Kenya, Manhiça Hospital in Mozambique, Farafenni Hospital in The Gambia) locations. 1.5.3 Study design Following the comprehensive approach of the PRECISE Network, this research examined maternal diet and pregnancy hypertension in terms of community perspectives, clinical findings, 11 and grounded in an understanding of potential biological pathways. The study design employed three main methodologies: i) literature reviews of current evidence following PRIMSA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines for scoping and systematic reviews, ii) assessment of the association between dietary diversity and pregnancy hypertension in the the PRECISE Network prospective cohort study, and iii) a focused ethnography in PRECISE study communities to understand maternal dietary patterns from the perspectives of women, their families and influential members of their communities. A convergent mixed method was employed, which consists of separate quantitative and qualitative data collection approaches, mixing them at the point of interpretation to highlight the areas where the two data sets converge or diverge (73). Overall quantitative and qualitative data collection methods are presented below, with details briefly stated in each of the subsequent Chapters, especially regarding unique methodological features and analysis methods contained in the specific Chapter. 1.5.4 The PRECISE Network prospective cohort study 1.5.4.1 Study participants and recruitment Quantitative data were obtained from the PRECISE Network prospective cohort study (October 2023 dataset), which included 8757 women recruited across Kenya, Mozambique and The Gambia between June 2019 and December 2022. As a pregnancy cohort, the study primarily recruited pregnant women presenting at health facilities in each of the study sites. A smaller sample of non-pregnant women of reproductive age (WRA), defined as age 16 to 49 years in Kenya and The Gambia, and age 15 to 49 years in Mozambique, presenting at the same health facilities were also recruited to better understand similarities and differences in experiences and 12 outcomes between pregnant and non-pregnant populations. Women were recruited when presenting to health facilities for their own care (i.e. antenatal care or family planning clinic) or for the care of others (i.e., child immunizations) (74). Pregnant women who did not plan to deliver in study health facilities were excluded. Women recruited for PRECISE were largely representative of the local population as institutional birth rates were high in study regions (85% in Kilifi County, Kenya, 90% in Kerewan, The Gambia, and 97% in Maputo Province, Mozambique)(75–77). 1.5.4.2 Data collection methods Trained data collectors administered face-to-face clinical surveys after obtaining written informed consent. PRECISE surveys collected information on demographics, dietary assessment, and medical histories over four visits (two antenatal, one antepartum, and one postpartum visit). The dietary questionnaire was conducted at the first antenatal visit (typically between 24-27 weeks gestation), while physiological assessments such as the assessment of blood pressure was tracked across the four study visits (first ANC clinic, during the third trimester, a visit during delivery, clinic visit between 6 weeks to 6 months postpartum). Utilizing a food list-based approach, women responded yes or no to consuming local foods corresponding to food groups in the previous 24-hours (35). 1.5.4.3 Minimum dietary diversity for women Dietary diversity indicators summarize the number of foods or food groups consumed over a reference period as a proxy for nutritional adequacy, with instruments ranging in complexity levels in terms of number of food groups considered, food group classifications, length of reference periods and consideration of the number of servings (78,79). Due to their simplicity, 13 single food group counts are popular measurement approaches in resource-limited settings and since its launch in 2015, MDD-W is now widely used by United Nations agencies, the Demographic and Health Surveys (DHS) Program, and national governments for nutritional tracking (52). Across the globe, 55 countries have collected MDD-W data for research and/or impact evaluations (80). The MDD-W is a simple, food-based, dichotomous indicator validated for resource-limited settings to assess adequate dietary diversity consisting of 10 main healthy food groups: • Grains, white roots and tubers, and plantains • Pulses (beans, peas, and lentils) • Nuts and seeds • Milk and milk products • Meat, poultry, and fish • Eggs • Dark green leafy vegetables • Other vitamin A-rich fruits and vegetables (dark-yellow or orange-fleshed fruits and vegetables) • Other vegetables • Other fruits. There were also three main unhealthy food groups measured: • Fried and salty foods • Sweet foods • Sweetened beverages Utilizing a food-list approach, PRECISE participants responded yes or no to consuming various foods associated with the food groups in the MDD-W tool. Intakes of less than 15g (approximately a tablespoon for most foods) were not counted towards a food group, following the FAO guideline (35). The dietary diversity score described the median number of healthy food groups consumed in the population, while meeting minimum dietary diversity was defined as a 14 dietary diversity score of at least five (35). Consumption of unhealthy food groups were collected but did not contribute to the DDS or MDD-W. MDD-W combines a number of FAO food groups and sub-groups in its main 10 food groups (81). For example, cereals are combined with roots, tubers and plantains for a count of one food group in the dietary diversity score. Fish and shellfish are combined with meat and meat products as one food group in the dietary diversity score, and the milk and milk products food group combines milk, fermented milk products (i.e. yogurt), cheese and other milk products . In contrast, fruit and vegetable sub-groups (leafy green vegetables, yellow and orange fruits and vegetables, other vegetables, other fruit) are individual food groups in the MDD-W tool. This highlights an emphasis on a diversity of fruits and vegetables in the MDD-W instrument. Though recommended by the FAO as an indirect measure for diet quality in resource-limited settings (31), the MDD-W is still a limited tool in the ability to measure nutrient, and food intake accurately. It is recognized that the tool does not measure macro-nutrient intakes, is less detailed to measure food sources or frequency of intake, and could be biased to more recent food intakes. Based on food group counts, the MDD-W is limited in its ability to measure all aspects of food and nutrient intakes. 1.5.5 Focused ethnography 1.5.5.1 Qualitative approach Qualitative research can be used to understand women’s perceptions of maternal diets, including concerns, attitudes, beliefs and food taboos as well as barriers in availability and access (82–85). Qualitative research took place in PRECISE study communities to understand local contexts of 15 maternal diets experienced by pregnant women and their families and social determinants of health, which complement the quantitative data collected in PRECISE (74,86). The qualitative community-based research followed a focused ethnographic approach, an applied exploratory methodology emphasizing rich descriptions focused on an area of interest and a combination of qualitative methodologies (in-depth interviews (IDIs), participant observation, photovoice) to understand participant experiences (87–89). IDI findings were triangulated with other qualitative methodologies. 1.5.5.2 Study participants and recruitment PRECISE study communities included in the qualitative study included Mariakani and Rabai in Kenya, Illiasa in The Gambia, and Xinavane in Mozambique. Communities were predominantly rural, with the exception of Mariakani. The sample was purposively drawn to include pregnant and recent mothers who had delivered in the previous two years, their family members including male and female relatives, and community members. Decisions about household spending and access to pregnancy care are influenced by family and community dynamics. Previous reviews have found that decision-making on maternity health services in LMICs were low. In particular, rural women with lower education and income have lower decision-making autonomy (90,91). Consequently, we recruited family members and community leaders in the qualitative study, who would be influential on household decisions around maternal diets and health care access. As household decision-makers, mothers-in-law were prioritized for female relatives, and husbands and partners for male relatives where possible. Community leaders included village elders, religious leaders 16 chiefs/assistant chiefs, traditional birth attendants and others considered an opinion leader in the community. Participants were required to be a resident in the study communities. A PRECISE Network study team member approached potential participants in person or by phone to discuss the maternal diets qualitative sub-study. A sample size of 12-18 interviews in each country was estimated to reach data saturation with a variety of perspectives (92). Additionally, three further pregnant or recent mothers for participant observation and five to ten pregnant or recent mothers for photovoice were recruited in each country to confirm data saturation (93). We oversampled pregnant and recent mothers to ensure inclusion of their perspectives. Literature has shown that young women’s voices can be marginalized in patriarchal societies particularly where married couples reside in extended households such as traditionally practiced within the communities in this study (94). 1.5.5.3 Data collection methods Qualitative fieldwork took place between May and October 2022. Local data collectors from Kenyan, Gambian and Mozambican PRECISE field teams (five female, six male) underwent an intensive training led by M.W.K. on qualitative methods and data collection materials prior to conducting interviews. Following a semi-structured topic guide piloted with local PRECISE staff (Tables A.1, A.2, and A.3), data collectors conducted 45 minute to two hour long face-to-face interviews at a location of participants’ preferences, usually a secluded place within the participant’s household. Interviews were conducted in the participants’ preferred language. Data collectors were fluent in local tribal languages and national languages, which included Giriama and Swahili in Kenya, Mandinka, Fula and Wolof in The Gambia, and Changana and Portuguese in Mozambique. Participant observation involved nine women (three each in Kenya, The Gambia 17 and Mozambique) conducted by M.W.K and a local field team member. With each woman, researchers spent one to two full days to shadow her daily food provisioning activities. Fieldnotes were compiled during and after each participant observation session. Photovoice was conducted with 20 women (five each in Mariakani and Rabai; five in Illiasa; five in Xinavane). Digital cameras were distributed to women with training and collected approximately four days later. Photographs were used as prompts during in-person discussions either with each woman individually (The Gambia) or in a 90-minute focus group discussion (Kenya and Mozambique), as directed by local staff to be culturally appropriate in each country. Interviews and focus group discussions were audio recorded with participant permission, then translated and transcribed in verbatim. Findings were largely reported from the interview dataset; however, themes elicited from interview participants were triangulated with field notes from participant observation and photovoice discussions to support credibility of findings (95,96). Overall, there were no refusals to participate and no repeat interviews were conducted. 1.5.6 Ethics considerations The study received ethics approval from the University of British Columbia (H20-00143), the Aga Khan University Nairobi (2021/IERC-159), The Gambia Government/Medical Research Council The Gambia (MRCG) Joint Ethics Committee (26342), and the Centro de Investigação em Saúde de Manhiça (CIBS-CISM/034/2022). The PRECISE dataset was de-identified through the use of participant codes. The qualitative dataset also used participant codes or pseudonyms and aggregated demographic features to ensure confidentiality. 18 1.6 Chapter breakdown This six-paper Dissertation, which includes six stand-alone empirical Chapters, is organized into eight chapters. Chapter 1 introduces the overall research problem to be addressed, the research approaches and objectives, and the research sites and methodologies that underpin the Dissertation. Chapter 2 is the first paper titled, “Maternal nutritional risk factors for pre-eclampsia incidence: findings from a narrative scoping review.” Previous reviews on nutritional approaches to pre-eclampsia prevention have largely focused on supplementation trials with insufficient attention to underlying maternal nutritional exposures. This chapter systematically reviews 58 studies to summarize existing evidence about the interaction between maternal nutritional deficiencies and components of the pathophysiology of pre-eclampsia. Results were considered in terms of their biological plausibility, consistency of evidence and effect sizes. Chapter 3 is the second paper titled, “Maternal Dietary Patterns and Pregnancy Hypertension in Low- and Middle-Income Countries: A Systematic Review and Meta-analysis.” Previous reviews focused on large cohort studies from HICs, and there was a gap in understanding literature from LMICs. The chapter narratively synthesized 13 studies of maternal dietary patterns and pregnancy hypertension conducting in LMICs, with five studies included in the meta-analysis. Chapter 4 is the third paper titled, “Community perspectives on maternal diets and dietary diversity in rural Kenya, Mozambique and The Gambia: a qualitative study”. Drawing from interviews from community members, this chapter provides an overview of dietary patterns and 19 practices typically found in rural Kenya, Mozambique and The Gambia among general and maternal populations. The chapter covers community perceptions of nutritious and diverse maternal dietary patterns and the major and minor influencing factors of obtaining healthy maternal diets. Chapter 5 is the fourth paper titled, “Prevalence and associated factors of meeting minimum dietary diversity among pregnant and non-pregnant women of reproductive age in three sub-Saharan African countries”. The chapter evaluates the proportion of women in the PRECISE cohort who met minimum dietary diversity for women and explores the determinants of adequate dietary diversity. Resulting correlates of dietary diversity were considered in the statistical models for the association between maternal diets and pregnancy hypertension covered in Chapter 7. Chapter 6 is the fifth paper titled, “Characterizing dietary diversity patterns among pregnant women in Kenya, Mozambique and The Gambia: A mixed methods latent class analysis and qualitative content analysis”. This chapter explores the food groups included in the Minimum Dietary Diversity for Women tool in more depth, including both the ten healthy food groups and the three unhealthy food groups. This chapter utilizes latent class analysis to explore dietary patterns distinguished by dietary diversity among pregnant women in the PRECISE cohort and qualitative content analysis to explore community perceptions of each of the food groups. This chapter also discusses implications for nutrition of the dietary patterns identified. Latent class analysis results informed development of the novel modified MDD-W criteria explored in the next chapter. 20 Chapter 7 is the sixth paper titled, “Associations between maternal dietary diversity status and pregnancy hypertension in Kenya, Mozambique and The Gambia”. Using dietary diversity data from the PRECISE cohort, this chapter evaluates the association between meeting minimum dietary diversity for women and their risk of gestational hypertension and any pregnancy hypertension. This chapter investigates the standard MDD-W criteria, which only considers healthy food group consumption patterns, as well as the novel modified MDD-W criteria that also incorporates unhealthy food group consumption patterns. Chapter 8 is an integrated discussion that summarizes key findings of the six papers. This chapter highlights the unique contributions, limitations, knowledge translation activities, and implications for future research and practice. 21 Chapter 2: Maternal nutritional risk factors for pre-eclampsia incidence: findings from a narrative scoping review 2.1 Introduction Pre-eclampsia is a pregnancy-specific inflammatory disorder with two major pathways of pathophysiology (23). Placental pre-eclampsia, generally developing < 34 weeks gestation, arises from abnormal vascular development of the placenta and inadequate transformation of the maternal spiral arteries to adequately supply nutrients to the placenta and fetus (23,25). Reduced uteroplacental blood supply results in a greater demand than supply and leads to the release of placental syncytiotrophoblast stress–derived factors and an imbalance in circulating pro-/anti-angiogenic factors, which exacerbates oxidative stress, systemic inflammation and endothelial dysfunction in the maternal system (16). Maternal pre-eclampsia, generally developing ≥34 weeks and postpartum, arises from interactions between a normal placenta and maternal cardiovascular risk factors such as hypertension, renal disease, overweight, and diabetes (23). Pre-eclampsia of maternal or placental origin are not mutually exclusive and there is an overlap in influencing factors (23). Certain micronutrients have antioxidant and anti-inflammatory properties, and dietary deficiencies may contribute to poor placentation. Adaptive responses to maternal malnutrition include the regulation of specific nutrient transporters and blood flow, and thus maternal nutrition is hypothesized to be associated with the development of pre-eclampsia (19,20,25,26). While a proposed role for diet in the origins of pre-eclampsia is well-established (25–27), evidence from nutritional supplementation trials remains elusive (25,27). Although micronutrients are good candidates for pre-eclampsia prevention due to their antioxidant, anti-22 inflammatory or vasoactive proprieties, current evidence does not support routine supplementation of vitamins C, D or E for the prevention or treatment of pre-eclampsia (25). High-dose calcium (i.e., at least 1g/day) may reduce the risk of pre-eclampsia in women with low dietary calcium intake (25). While supplementation in the latter half of pregnancy may reduce high blood pressure, this timing may be too late to influence placental development largely occurring in early gestation (97). A multi-country placebo-controlled trial evaluating low-dose calcium replacement (500 mg/day) given preconception and in early pregnancy to women with a history of severe pre-eclampsia and low dietary intake (women in both arms receiving open label 1500 mg/day from 20 weeks) observed a marginal effect on the incidence of pre-eclampsia in a subsequent pregnancy amongst women who were compliant with the intervention (98). However, the efficacy of supplementation is conceptually a different research question than understanding the association between nutritional deficiencies and risk of pre-eclampsia; the first emphasizes modifiability of specific dietary components related to the condition and involves consideration of the intervention implementation process, while the latter focuses on underlying nutritional deficiencies observed in populations. A 2014 review of dietary factors in the prevention of HDP that excluded purely supplement-based studies yielded more promising results (99). Higher total energy and lower magnesium and calcium intake during pregnancy were associated with HDP incidence, while maternal diets rich in fruits and vegetables may be beneficial in reducing pre-eclampsia (99). An updated review is needed, particularly a scoping review of observational studies separated from intervention trials evaluated through the lens of consistency in associations and etiology. 23 Conventional systematic reviews that value randomized controlled trials (RCTs) as the gold standard of study design and a rigorous criteria for evaluating evidence may not always capture the bigger picture in nutritional epidemiology (100). This is because diet-related diseases may take time to develop and manifest chronic symptoms, RCTs may not be ethically feasible with dietary deficiencies known to have adverse effects on human health, and dietary modification involves behavioural change inadequately detected in trials with insufficient follow-up time (100). Therefore, in nutritional epidemiology, it is important to triangulate a) biological plausibility in association with literature related to physiological mechanisms, b) consistency of the evidence across study designs and populations, and c) consideration that small effects for individuals may have a large impact on populations (100). We performed a scoping review according to the methods described by Arksey and O’Malley (101) to address the research question: What is known from the existing literature about the interaction between maternal nutritional deficiencies and risk of developing pre-eclampsia? 2.2 Methodology The review is reported according to Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) (102) and took an pragmatic approach, as recommended for scoping reviews (101,103). Relevant studies were identified in an iterative two-stage process conducted from database inception to January 2021. First, electronic database searches were conducted on Medline Ovid, EMBASE, Cumulative Index to Nursing & Allied Health Literature, Web of Science, JBI Database of Systematic Reviews and Implementation Reports, Database of Abstracts of Reviews of Effects and EBM reviews. EBM reviews includes the Cochrane Database of Systematic Reviews, ACP Journal Club, Clinical Evidence, Evidence-24 based Mental Health, Evidence-based Nursing, Evidence report/Technology assessment. Registers, including PROSPERO, Cochrane Central Register of Controlled Trials (CENTRAL), ClinicalTrials.gov and ICTRP Search Portal of the World Health Organization were also scanned. Two reviewers (M.W.K and S.O.) independently reviewed titles, abstracts and full texts with reflexive discussion with a third independent reviewer (K.S.) at each phase to resolve any disagreements. Existing reviews were prioritized where available and studies were considered if they investigated maternal nutrition and diets, if they examined underlying nutritional status and deficiencies and/or if they discussed biological plausibility that linked nutritional deficiencies with hypotheses of the etiology of pre-eclampsia. Nutritional supplementation trials raise questions about compliance and adherence to the intervention protocol as well as duration, dosage and timing of intervention delivery, factors that would be more appropriately evaluated in a systematic review. In contrast, this scoping review seeks more broadly to understand maternal nutritional status and nutritional deficiencies as exposures on the outcome of pre-eclampsia and other hypertensive disorders of pregnancy. Consequently, our scoping review focused on observational studies and reviews of observational studies. In the second stage of the search process, the first reviewer (M.W.K) reviewed the studies compiled, reviewed reference lists, snowball searched related articles on Google Scholar and PubMed, and consulted with experts in the field. Over the two stages of this process, search terms broadly included pregnancy hypertension, pregnancy-induced hypertension, gestational hypertension, pre-eclampsia, eclampsia, HELLP syndrome, pregnancy complications, micronutrients, vitamins, minerals, macronutrients, nutritional deficiencies and serum levels (Table B.1). Categories of nutritional deficiencies were explored with more sensitive searches in the expanded second stage (e.g., low 25 calcium levels, serum calcium, calcium deficiency and Mediterranean diet), as familiarity with the literature increased. Data were charted by sifting, sorting and extracting material according to key issues and themes (101). M.W.K. completed primary data charting and collated summaries of findings, which were then discussed iteratively with the reviewer team to review results, identify gaps and consolidate interpretation in reporting until consensus was achieved. Results were considered in terms of their biological plausibility, consistency of evidence and effect sizes as recommended (100,104). Biological plausibility refers to the potential biological role the nutrient has in the pathophysiology of pre-eclampsia. Consistency of evidence in nutritional epidemiology considers the direction of association across populations, study designs and statistical methods. Similar direction of association in a majority of high quality studies is recommended for consistency of evidence (104). Effect sizes in nutritional epidemiology are frequently smaller at around 0.8-1.2, but these may still have large public health effects at a population level. Strong associations over 4.0 are viewed with caution unless corroborated by other studies (104). 2.3 Results Searches identified 6572 records, of which 58 were included in the review (Figure 2.1; see Table B.2 for the excluded studies). 26 Figure 2.1 PRISMA flow diagram for the maternal nutritional risk factors for pre-eclampsia incidence scoping review Results are presented according to the following components in the development of pre-eclampsia where literature found that maternal nutritional inadequacies may contribute to proper placentation, regulation of placental inflammation and immune system, oxidative stress maternal endothelial dysfunction and high blood pressure (Table 2.1). Within each section, key themes from the reviewed material are presented. 27 Table 2.1 Role of maternal dietary components in the development of pre-eclampsia Pathophysiology of pre-eclampsia Dietary components and mechanism Poor placentation Maternal syndrome with clinical signs of pre-eclampsia Defective trophoblast invasion leading to reduced utero-placental blood flow and inflammatory response Vitamin D • Regulates inflammation in maternal uterine natural killer cells,which supports extravillous trophoblast invasion• Regulates angiogenesis through stimulating VEGFVitamin B9 (folate) and B12 • Regulates homocysteine concentrations, which damages endothelialcells and increases trophoblast apoptosisOxidative stress Vitamin C and E • Important antioxidants that scavenges oxygen radicals in aqueousphase (C) and in cell membranes (E)• Vitamin C involved in uptake of free iron in plasmaEssential trace elements • Zinc, copper and selenium as components of important antioxidants(superoxide dismutase and glutathione peroxidase)• Free iron and copper in plasma are pro-oxidative transition metalsEndothelial dysfunction and systemic inflammatory response Omega 3 long-chain polyunsaturated fatty acids • Regulates oxidative stress, inflammation and lowers triglycerideconcentrations by reducing free fatty acid availability, increasingphospholipid synthesis and decreasing triglyceride-synthesizingenzyme activity• Increased concentration of circulating lipids accumulate inendothelial cells, which decreases release of prostacyclin (anendothelium-derived vasodilator) and results in endothelialdysfunctionHealthy dietary patterns • Maternal metabolic or insulin resistance syndromes associated withendothelial dysfunction or sensitivity• Diets characterized by high consumption of fruits, vegetables andwhole grains, fish and seafood high in omega-3 fatty acids,monounsaturated vegetable oils, and low in added sugar areprotective against cardiovascular diseases and metabolic syndromesHigh blood pressure Vitamin D and calcium • Low serum calcium triggers increased secretion of PTH, whichstimulates release calcium stores from bone reservoirs, openscalcium channels to increase intracellular calcium, which leads tovasoconstriction and high blood pressure• PTH stimulates calcitriol production and calcitriol increases calciumabsorption from the intestine• PTH activates the renin–angiotensin–aldosterone signaling pathway,which increases the vascular volume though sodium and waterreabsorptionPTH – parathyroid hormone; VEGF - vascular endothelial growth factor 28 2.3.1 Poor placentation, immune response and inflammation Poor placentation is characteristic in the pre-clinical stage of early-onset/placental pre-eclampsia where shallow cytotrophoblast invasion results in defective remodelling of the maternal spiral arteries (23,25). The under-perfused placenta creates angiogenic imbalance in the maternal blood stream and activates maternal inflammatory response (4,10,13). Vitamin D is a fat-soluble vitamin with two major physiological forms, ergocalciferol (D2), which is mainly obtained from plant and vegetable sources, and cholecalciferol (D3), which is mainly synthesized in the skin from 7 dehydrocholesterol with exposure to UVB radiation from sunlight (105). Vitamins D2 and D3 are prohormones first hydroxylated in the liver to produce calcidiol (25-hydroxycholecalciferol, 25OHD), which is frequently used as the best stable and circulating biomarker for vitamin D status (106–108). 25OHD is further hydroxylated in the kidneys to produce calcitriol (1,25 dihydroxycholecalciferol), which is the active form of the hormone used by the body (105). Calcitriol synthesis has also been demonstrated in decidua and placenta, and calcitrol has important roles in hormonogenesis and overall placental physiology including stimulating endometrial decidualization and synthesis of vital hormones (estradiol, progesterone, human chorionic gonadotrophin, human placental lactogen) in pregnancy (105,109). Calcitriol regulates placental immune response and inflammation in maternal uterine natural killer (uNK) cells by inhibiting inflammatory cytokines (TNF-α, IL-6) produced by trophoblast cells to reduce inflammation and produced by decidual cells in the maternal endometrium for immunosuppression as well as promoting the release of antimicrobial peptides (hCTD, HBD2, HBD3) to restrain infection (105). uNK cells in turn regulate extravillous trophoblast invasion of the decidua and maternal spiral arteries that is characteristic of poor 29 placentation in pre-eclampsia (105,110,111). In addition, in vitro studies have demonstrated a direct pro-invasive effect of calcitriol on the extravillous trophoblast (110). Calcitriol is also involved in regulating angiogenesis through stimulating the expression of pro-angiogenic signaling protein, VEGF, in vascular smooth muscle cells (112,113). Women with pre-eclampsia had significantly lower 25OHD serum concentrations in comparison with normotensive pregnant women (114,115). Most meta-analyses on vitamin D insufficiency (25OHD <75 nmol/L) and deficiency (25OHD <50 nmol/L) reported significantly increased odds of pre-eclampsia (insufficiency: odds ratio (OR) 2.11, 95% CI: 1.36-3.27, I2 0%, 5 studies (114) / deficiency: OR 1.27, 95% CI: 0.67-2.42, I2 0%, 2 studies (114); OR 1.54, I2 58%, otherinformation not reported (115); OR 1.62, 95% CI: 1.36–1.94, I2 50%, 21 studies (116)). However, a recent meta-analysis found that associations were not significant under a random effects model (insufficiency: OR 1.26, 95% CI: 0.97-1.82, I2 78%, 11 studies / vitamin D deficiency: OR 1.42, 95% CI: 0.99-2.04, I2 83%, 11 studies) highlighting high heterogeneity due to differences in study design and gestational age at time of sampling (117). A European nested case-controlled study in 83 women with pre-eclampsia matched with 319 normotensive controls found that adequate plasma vitamin D concentration in the third trimester was significantly protective while not significant in first trimester alone (118). The strongest effect was among women with sufficient vitamin D in both first and third trimesters, which was related to lower odds of pre-eclampsia compared with women who had low vitamin D in the same periods (OR 0.34, 95% CI: 0.13-0.86, p=0.02)(118). This may suggest that while vitamin D is involved in proper placentation, a further role of vitamin D in calcium homeostasis may be for blood 30 pressure regulation in late gestation, which may play a major part in the linkage between its deficiency and increased risk of pre-eclampsia. This is further discussed below. In addition to its essential roles in nucleotide synthesis, cell growth and proliferation, and DNA methylation during pregnancy (119), folate/folic acid and vitamin B12 are regulators of plasma homocysteine concentrations (25,120). Elevated homocysteine concentrations may cause direct damage to endothelial cells and increase cellular destruction (apoptosis) of trophoblast cells leading to poor placentation (120,121). A meta-analysis did not find a significant association between maternal folate deficiencies and pre-eclampsia incidence (122); however, two large studies with over 1000 participants each (China (120), the Netherlands (121)) highlighted that low plasma folate and high homocysteine concentrations were particularly associated with incidence of pre-eclampsia during early pregnancy when measured around 11-13 weeks gestation (120,121). Both studies found strong effect sizes comparing women with the lowest folate concentrations to highest concentrations on pre-eclampsia incidence (Q1 vs Q4 OR 2.27, 95% CI: 1.56-3.33, p < 0.001 (120); Q1 vs Q5 adjusted odds ratio (aOR) 2.10, 95% CI: 1.05-4.20, p=0.04 (121)). 2.3.2 Oxidative stress Poor placentation in the pre-clinical stage progresses to the clinical symptoms of the syndrome in the second stage (20,23,26). However, reduced placental perfusion alone is not considered sufficient to explain pre-eclampsia since other conditions such as intrauterine growth restriction and preterm birth are also associated with poor placental development. Increased oxidative stress resulting from an under-perfused placenta has been proposed as the linkage between the two stages of pre-eclampsia (20,26). Oxidative stress occurs when there is an accumulation of free 31 radicals (substances with one or more unpaired electrons) that exceeds the capacity of antioxidant defense mechanisms to mitigate against the harmful effects of free radicals, including damage of cells, lipids and proteins (20,26,123–125). An imbalance between the production of free radicals and antioxidants triggers oxidative stress, which contributes to maternal endothelial cell activation, destruction of trophoblast cells and vasoconstriction that are characteristic of pre-eclampsia (20,123,125). An increased rate of destruction (aponecrosis) of syncytiotrophoblast leads to higher concentration of trophoblast debris in maternal circulation, which subsequently increases systemic inflammatory responses (20,126,127). Vitamin C and E are important antioxidants in humans obtained through dietary intake that help protect against oxidative stress (25,124,128). Vitamin C (ascorbic acid, ascorbate) is an essential hydrophilic micronutrient that scavenges oxygen radicals in the aqueous phase, while vitamin E is the major lipid-soluble micronutrient (tocopherols and tocotrienols) that scavenges oxygen radicals within cell membranes (26,124,129). Vitamin C is considered the “linchpin” antioxidant in humans to replenish vitamin E and is proposed to be the first antioxidant defense mechanism damaged in women with pre-eclampsia as no other antioxidants are reduced prior to vitamin C being depleted (26,124,129). A meta-analysis found that women with pre-eclampsia had significantly lower third trimester concentrations of vitamin C and E in comparison with normotensive pregnancies (vitamin C standardized mean difference (SMD) -0.56, 95% CI: -0.83 to -0.28, I2 91%, 29 studies; vitamin E SMD -0.42, 95% CI: -0.72 to -0.13, I2 93%, 34 studies) (130). While the meta-analysis reported high heterogeneity, there was a consistent direction of effect in the high quality studies (studies with sample sizes over 50 participants), especially with vitamin C (130). Of the 6 high quality studies, five case-control studies in Spain (131), Nigeria 32 (132), Uganda (133), Peru (134), and United States (128) found that pre-eclampsia was associated with significant reductions of vitamin C and/or E. Both low dietary intake of vitamin C and low plasma vitamin C concentration were associated with over two-fold higher odds of pre-eclampsia incidence in comparison with pregnant women with adequate vitamin C (dietary intake <85mg/day OR 2.1, 95% CI: 1.1-3.9 (128); vitamin C concentration <2.0x103μg/L OR 2.9, 95% CI: 1.56-5.44 (133)). A Bangladeshi case-controlled study with 150 pre-eclampsia cases and 174 healthy pregnant controls found significantly lower concentrations of serum vitamin C among cases combined with elevated levels of lipid peroxidation (p<0.05) (135). Another recent Canadian nested case-controlled study with 111 pre-eclampsia cases and 441 normotensive controls observed that antioxidants have potentially stronger associations for early-onset (generally placental) rather than late-onset (generally maternal) pre-eclampsia suggesting the role of oxidative stress in the pathophysiology of placental pre-eclampsia (136). Essential trace elements including zinc, copper and selenium are vital components for antioxidants synthesized in the body. Zinc and copper are essential components for superoxide dismutase (SOD), while selenium is vital for proper functioning of selenoenzymes, such as glutathione peroxidase (GPx) (25,137–140). SOD and GPx are both considered “first line” antioxidants and indispensable to the body’s defense against oxygen radicals (141). Two meta-analyses found that women with pre-eclampsia had significantly lower concentration of serum zinc (SMD -0.587, 95% CI: -0.963 to -0.21 I 2 88%, 14 studies (142); SMD −0.61, 95 % CI:-0.74 to -0.48, I2 88.5%, 3 studies (143)). A third review found evidence supporting an association between low maternal dietary zinc intake and low birthweight infants (10 out of 16 studies) and severe pre-eclampsia (16 out of 33 studies), but not preterm birth and gestational diabetes (137). 33 However, there were high rates of heterogeneity among three systematic reviews investigating association between maternal zinc concentrations and pre-eclampsia (137,142,143), which may be driven by gestational age of measurement (144). Evidence for selenium was limited; a UK study indicated mixed results (145) and an Iranian study reported a strong effect between women with low selenium concentration and pre-eclampsia compared to women with high concentration (OR 9.14, 95% CI: 2.25–37.01) (140). Such findings from single trials, however, require further corroboration. A meta-analysis found significantly higher serum copper concentrations among women with pre-eclampsia in comparison to normotensive controls (SMD 0.69, 95% CI: 0.54–0.8, I2 97%, 12 studies) (138), likely because free copper in the plasma is pro-oxidant (139). In addition, vitamin C is actively involved in the uptake of free iron in the plasma (non-transferrin bound iron) and is consequently important for iron homeostasis (146). While the reactive oxygen species are insufficient to initiate cellular damage directly, transitional metal ions (e.g., free iron) in plasma in particular are a necessary co-factor in the production of the highly reactive hydroxyl radicals that may initiate the process of lipid peroxidation and subsequent endothelial cell damage (147–149). In the current review, iron was a dietary factor with significant heterogeneity across studies in part due to the number of different indicators associated with iron status, including serum iron concentration but also maternal anemia measured as low hemoglobin concentrations. Two meta-analyses found that women with pre-eclampsia had significantly higher serum iron concentrations (SMD 0.28, 95% CI: 0.11–0.44 (150); SMD 1.27, 95% CI: 0.76-1.78 (151)). Another meta-analysis found a significant association between maternal anemia (hemoglobin <11 g/dL) and pre-eclampsia odds in the first (OR 1.55, 95% CI: 1.15−2.10) but not in the second or third trimesters (152). Another meta-34 analysis found a dose-response with both low maternal hemoglobin (< 110 g/L) and high maternal hemoglobin (> 130 g/L) significantly associated with higher PE odds (low Hb OR 1.84, 95%CI: 1.31-2.59, high Hb OR 1.48, 95% CI: 1.10-2.01) (153). 2.3.3 Maternal endothelial dysfunction The stressed placenta triggers endothelial dysfunction and increases systemic inflammatory responses (154). Dietary components may also contribute. Increased concentrations of circulating lipids may accumulate within endothelial cells, which triggers a decreased release of prostaglandins, specifically prostacyclin (155–157). Prostacyclin is an effective vasodilator and inhibits platelet aggregation. Reduced prostacyclin levels results in endothelial dysfunction with exacerbated oxidative stress and maternal inflammation (156–158). While maternal metabolism changes during normal uncomplicated pregnancies, especially in late gestation to meet the needs of the growing fetus (157–160), women with pre-eclampsia a tend to experience greater changes in lipid metabolism. Three meta-analyses (156,160,161) found that women with pre-eclampsia have consistently higher serum triglycerides concentrations, compared with normotensive pregnant controls, even after adjusting for maternal body mass index (BMI) (156). Triglycerides were significantly elevated in first and second trimesters before onset of pre-eclampsia in women who developed the condition (156,160). Long chain polyunsaturated fatty acids (PUFA) are significantly associated with lower triglyceride concentrations (162). For example, omega-3 fatty acids can help reduce triglyceride concentration by reducing free fatty acid availability, increasing phospholipid synthesis and decreasing triglyceride-synthesizing enzyme activity (163). Omega-3 fatty acids must be obtained from the diet, mainly from fish and marine sources or as α-linolenic acid from vegetable oils (164). However, the evidence on the association 35 between omega-3 dietary intake and lower risk of pregnancy hypertension from observational studies is inconsistent, with studies in populations with traditionally higher omega-3 intakes reporting significant associations (165–167), but not among populations with low intakes (168,169). An observational study from Iceland also cautioned that supplementation alongside traditional fish and cod-liver oil consumption may result in overly high intake of omega-3, with increased the risk of developing HDPs (170). Pregnancy places stress on maternal cardiovascular and metabolic systems and there is a decrease in insulin sensitivity during gestation to allow the maternal metabolism to meet fetal demands for glucose (171,172). Pregnancy may be considered a metabolic and vascular “stress test” (20). Maternal metabolic or insulin resistance syndromes such as chronic hypertension, dyslipidemia, insulin resistance, diabetes, adiposity, and hemostatic disturbances are associated with endothelial cell dysfunction, which increases sensitivity to placental factors and increases the risk of developing pre-eclampsia (173). A case-controlled study with 259 women with pre-eclampsia and 297 normotensive controls in the United States found that women with a higher metabolic score based on the WHO and the National Cholesterol Education Program (NCEP-ATP III) diagnostic criteria was independently associated with developing pre-eclampsia (174). Healthy dietary patterns emphasizing high consumption of fruits, vegetables, whole grains, and limited consumption of saturated fats, sodium, red meat, and sweets, such as the Mediterranean, Nordic and Dietary Approaches to Stop Hypertension (DASH) diets, have been shown to be protective against cardiovascular diseases and metabolic syndromes (30,175–179). Olive oil is traditional to the Mediterranean region and a staple component of the Mediterranean diet, while the Nordic diet emphasizes locally sourced foods in modern-day Scandinavia and includes 36 rapeseed (canola) oil (179). Mediterranean and Nordic diets are recommended by the WHO for their protective benefits against cardiovascular diseases and type 2 diabetes (179). Cohort studies in Greece (180), Netherlands (181) and Australia (182) found that high adherence to a Mediterranean type diet was protective against HDPs. The Generation R cohort study with 3,187 pregnant women found that low adherence to a Mediterranean dietary pattern was associated with higher systolic and diastolic blood pressure in pregnancy, though not significantly associated with gestational hypertension or pre-eclampsia incidence (181). A 9 year follow-up of 3,582 women in the Australian Longitudinal Study on Women's Health found that high adherence to a Mediterranean dietary pattern was significantly associated 42% reduced risk (RR 0.58, 95% CI: 0.42-0.81) of developing HDPs in comparison with those with low adherence (182). The association may be stronger among high-risk women. A cohort of 82 women with early preterm singleton births (≤ 34 weeks) found that low adherence to a Mediterranean diet was associated with an almost four-fold increased odds (OR 3.8, 95% CI: 1.3-11.4) of developing gestational hypertension or pre-eclampsia (180). High adherence to the Nordic diet was significantly associated with lower odds of any pre-eclampsia (OR 0.86, 95 % CI: 0.78-0.95) and early onset pre-eclampsia (OR 0.71; 95% CI: 0.52-0.96) in comparison to low adherence among the 72,072 women from the Norwegian Mother and Child Cohort Study (MoBa) (183). In contrast, two large cohort studies from the United States (Project Viva) and Denmark (Danish National Birth Cohort) did not find an association between the DASH diet and pre-eclampsia incidence (184,185). The protective benefit of Mediterranean and Nordic diets, which both feature low intake of foods with added sugar, corroborates with findings from two Norwegian cohort studies that reported 37 associations with high consumption of sugary drinks with increased risk of pre-eclampsia incidence (173,186). Women who drank 125ml or more a day of sugar-sweetened carbonated and non-carbonated beverages had 27% higher odds of developing pre-eclampsia (adjusted OR 1.27, 95% CI: 1.05-1.54), in comparison to women with no intake after controlling for potential confounders (186). However, high intake of fruit, though high in natural sugars, was protective against pre-eclampsia (186). 2.3.4 High blood pressure Vitamin D supports calcium homeostasis. Concentrations of maternal plasma calcitriol, a vitamin D metabolite, almost double by the end of the third trimester as calcium absorption and placental calcium transport needs intensify for adequate fetal bone mineralization (25,105). Calcium was identified early as a potential nutrients in relation to pre-eclampsia as Belizan and Villar observed an inverse relationship between low calcium intake with higher rate of eclampsia incidence in the 1980s (187). They observed low pre-eclampsia and eclampsia rates among groups in LMICs with traditional diets rich in calcium, such as among populations in Ethiopia and among Mayan Indians in Guatemala who traditionally soak their corn in lime prior to cooking and suggested that the association could not be wholly driven by socio-economic factors (187). Calcium plays an important role in muscle contraction and regulation of water balance in cells in the regulation of blood pressure (25,188,189). Low serum calcium concentrations trigger increases in the secretion of parathyroid hormone (PTH) by the parathyroid gland, which stimulates the release of calcium stores in bone reservoirs into the bloodstream and increases intracellular calcium in vascular smooth muscle cells by opening calcium channels (189–195). Increases in intracellular calcium can directly contribute to vasoconstriction and subsequent high 38 blood pressure. PTH also stimulates the production of 1alpha-hydroxylase, which catalyzes the synthesis of calcitriol that increases calcium absorption from the intestine (191,195). PTH indirectly contributes to high blood volume by activation of the renin–angiotensin–aldosterone signalling pathway, increasing vascular volume though sodium and water reabsorption (189,190,195). Calcitriol decreases renin activity and PTH secretion through negative feedback (195,196). Adequate serum calcium concentrations serve as a negative-feedback loop signalling decreased secretion of PTH, stabilizes vascular cell membranes and reduces vasoconstriction (191,193,195). Perhaps because calcium was identified early in the prevention of pre-eclampsia and supplementation trials commenced early, there is less attention to epidemiological studies investigating the association between calcium deficiencies and pre-eclampsia incidence. In contrast to numerous systematic reviews of observational studies with vitamin D on the topic, there was one meta-analysis found for calcium, which found a significant protective effect with an OR of 0.63 (95% CI: 0.41-0.97, I2 0%, 7 studies) for high calcium intake during pregnancy (>1600mg/day) in comparison with insufficient intake (<1000mg/day) on gestational hypertension (99). While the meta-analysis noted a consistent direction of higher calcium intake as protective (99), two subsequent cross-sectional studies from Haryana, India did not find a significant association between pre-eclampsia and hypocalcemia (serum calcium <9 mg/d) (197,198). However, the authors noted that while the majority of pregnant women had inadequate dietary calcium intakes, dietary intakes did not correspond with serum calcium concentration, which may be because serum calcium is highly homeostatically regulated. 39 Instead of investigating calcium concentrations in isolation, epidemiological studies more frequently examined calcium and magnesium concentrations together. Magnesium is a calcium channel blocker that reduces intracellular calcium and thus results in vasodilation and reduced blood pressure (193,199,200). While a meta-analysis found that women with HDP had significantly lower concentrations of magnesium (-8.0, 95% CI:-13.99 to -1.38, I2 0%, 7 studies) (99), the consistency of evidence was mixed. There was higher consistency in case-controlled studies with more than 100 participants (201–204) and less consistency in case-controlled studies with 100 participants or less (193,199,200,205,206). 2.4 Discussion The purpose of this narrative scoping review was to compile current evidence on the pathways that maternal nutritional deficiencies and imbalances may lead to the onset of pre-eclampsia from observational studies and reviews of observational studies. There were a number of promising maternal dietary factors associated with risk of pre-eclampsia incidence that aligned with current understandings of biological mechanisms, including vitamin C as an essential antioxidant and its relationship with iron status, and vitamin D for its roles in placental development and together with calcium for blood pressure regulation. While evidence on omega-3 long-chain PUFAs seemed inconsistent, diets protective against cardiovascular and metabolic syndromes were more promising, particularly when characterized by high consumption of fruits, vegetables and whole grains as well as fish and seafood high in omega-3 fatty acids and monounsaturated vegetable oils. Associations between added sugar intake and pre-eclampsia incidence may also be an area to further explore as evidence is limited, though reported associations are strong. In addition to added sugar, other current gaps include limited literature 40 regarding B vitamins, zinc and other essential trace elements, dietary diversity and recent studies on dietary calcium. With the exception of calcium, where decades of intervention trials corroborate with early epidemiological observations and understandings of biological mechanisms on evidence of a protective effect against pre-eclampsia, many potential maternal dietary factors are not supported by results of supplementation trials (29). For example, though maternal serum vitamin C (136), zinc (142) and iron (151) have strong associations with the development of pre-eclampsia and make biological sense, supplementation resulted in non-significant effects (29,207–209). Findings from this scoping review may help to shed light on the discrepancy. First, the relationship between dietary factors and maternal conditions may not be linear for certain nutrients. This was most clearly described with iron as both high and low hemoglobin levels were associated with higher risk of developing pre-eclampsia (153). A non-linear relationship omega-3 fatty acids was also suggested with increased risk at both high and low levels (170). Consequently, heterogeneity of results may in part be due a focus on nutritional deficiencies rather than also when concentrations are too high. Secondly, gestational age is an important modifying factor because dietary components may be involved in different processes and demands over the course of the pregnancy. Studies with iron and vitamin D demonstrate that effects may be time-dependent (118,152). Periconceptual nutrition from 14 weeks before conception to 10-12 weeks gestation when women may not be aware of their pregnancy status may be particularly important for placentation (210–212), though there remains a gap on understanding dietary components for that phase of disease development (26). Furthermore, interrelationships between dietary factors complicate the direct linkage between dietary intake 41 and its metabolism. Potential synergies of dietary factors, such as vitamin C and iron for oxidative stress and vitamin D, calcium and magnesium for regulation of blood pressure, may shed light onto why single supplement trials may not have been as effective as desired in pre-eclampsia prevention. Further research is recommended to investigate gestational age, potential non-linear relationships and interactions between dietary factors. A broader approach to explore interrelationships between dietary factors and considering balanced dietary intake supports the potential for healthy dietary patterns in the prevention of pre-eclampsia, as previously suggested and further strengthened in this review. The review by Schoenaker et al found a non-significant trend towards the protective effect of healthy dietary patterns high in fruits and vegetables (99). Since the 2014 Schoenaker et al review, there has been further evidence in cohort studies of the protective effect of Mediterranean and Nordic diets on lowering risk of pre-eclampsia incidence (180,182,183). However, two recent large cohort studies did not find a significant association between the DASH diet and risk of pre-eclampsia incidence (184,185). This suggests that healthy diets comprise of more than high intake of fruits, vegetables and whole grains, which the three diets have in common. The DASH diet aims to be low in total fat while Mediterranean and Nordic diets include fish and seafood (high in omega-3 long-chain PUFAs) as well as olive oil in the Mediterranean diet and rapeseed (canola) oil in the Nordic diet (both monounsaturated fats). Unlike the DASH diet, the Mediterranean and Nordic diets also emphasizes the cultural significance of these diets, including their linkages to identity, local food systems, and sociality of shared meals together with family and friends (179). Further research into the social and cultural contexts of meals and eating may complement our understandings of maternal dietary patterns and their associated maternal health risks. 42 Additionally, more research is needed to understand food groups and their combinations in association with pre-eclampsia incidence rates, particularly in LMICs. Cohort studies examining maternal dietary patterns are largely conducted in high-income countries and less is known in resource-limited settings. In contrast to other systematic reviews, the focus of this review is less on evaluation of effect sizes. A limitation is that this is not a systematic review and does not provide evidence towards clinical practice. Rather, the emphasis of this scoping review was to map the landscape of the epidemiological evidence. Significant results within diverse populations was emphasized as a strength. A strength of this review is its extensive and iterative search strategy that adapted to knowledge gained in the process. However, with our focus on observational studies, potential confounding by other nutrients and non-nutritional factors, such as access to health services, health seeking behaviour, educational attainment and other social determinants of health, is a limitation of this approach. 2.5 Conclusion The review finds a growing body of literature describing the associations between nutritional inadequacies and higher risk of pre-eclampsia potentially through oxidative stress, inflammation, maternal endothelial dysfunction and blood pressure in the pathophysiology of pre-eclampsia. On the one hand, these findings confirm our understandings of oxidative stress, inflammation, maternal endothelial dysfunction and blood pressure in the development of pre-eclampsia while on the other hand, reinforce the potential role of maternal dietary factors. Rather than examining individual macro- or micronutrients in isolation, findings from the review suggested looking broader to interactions between dietary factors, and shifting from a narrow focus on nutritional 43 deficiencies to wider discussions of nutritional homeostasis and healthy dietary patterns to reduce risk of HDPs. 44 Chapter 3: Maternal dietary patterns and pregnancy hypertension in low- and middle-income countries: a systematic review and meta-analysis 3.1 Introduction Sustainable Development Goal 3.1 aims to reduce the global MMR to 70 per 100,000 live births, but reaching this target will not be achieved without reducing the burden of maternal deaths in LMICs (213–215). In 2017, low-income countries had an MMR of 462 per 100,000 compared to 11 per 100,000 in HICs(213). More than half of all maternal deaths are associated with three leading direct causes: maternal haemorrhage (27%), hypertensive disorders (14%) and sepsis (11%) (216). While there have been dramatic decreases in haemorrhage- and sepsis-related maternal deaths, reductions in pregnancy hypertension-related deaths have been much slower (215,216). As a percentage of overall maternal deaths, the proportion of pregnancy hypertension-related deaths have remained relatively steady between 1990 and 2013 (216). HDPs are associated with an estimated 46,000 maternal deaths annually (14). Pre-eclampsia, the most serious of the HDP (7), is characterized by new-onset hypertension ≥20+0 weeks gestation with proteinuria and/or signs of organ damage, most commonly the liver and kidneys (7–9). It is a pregnancy-specific inflammatory disorder related to abnormal vascular development of the placenta or pre-existing maternal risk factors for cardiovascular disease such as hypertension, renal disease, overweight, or diabetes (23). Dietary intake during pregnancy has been proposed to influence the risk of pre-eclampsia, with micronutrients specifically implicated due to their anti-oxidant, anti-inflammatory or vasoactive properties (25). However, the evidence remains inconclusive (25), suggesting a need to look at overall dietary patterns. A systematic review found that healthy diet interventions reduced the 45 risk of pre-eclampsia by 33% (217) and a meta-analysis of four observational studies found that a healthy dietary pattern characterized by high intake of fruits, vegetables, whole-grain foods, fish and poultry was associated with lower likelihood of pre-eclampsia (30). However, all four of the studies included in the meta-analysis were from HICs, with three from Norway and one from the Netherlands. There is a need to explore the impact of maternal diet on pre-eclampsia risk in resource-constrained settings where there are high burdens of both maternal deaths and maternal undernutrition. The primary objective of this review was to evaluate the association between dietary patterns in pregnancy and hypertension for pregnant and postpartum women in LMICs. The secondary objective was to understand risk factors associated with maternal dietary patterns, including identifying barriers and facilitators to obtaining an adequate maternal diet. 3.2 Methods This review was been developed in accordance with the PRISMA checklist (218). A review protocol was registered to PROSPERO (CRD42020165154) prior to conducting the review. Searches were conducted on MEDLINE Ovid, EMBASE, Cumulative Index to Nursing and Allied Health (CINAHL), Web of Science, CENTRAL, African Journals Online (AJOL) and the WHO Regional Databases. WHO Regional Databases included African Index Medicus, Latin American and Caribbean Health Sciences Literature, Index Medicus for the Eastern Mediterranean Region, Index Medicus for the South-East Asian Region and Western Pacific Region Index Medicus. Additionally, searches were supplemented by reviewing ClinicalTrials.gov, ICTRP Search Portal (World Health Organization), Google Scholar and scanning reference lists. Searches were conducted from database inception to February 2020. Based on the PECOS research framework, search terms broadly included dietary diversity, 46 dietary pattern, diet quality, developing countries, resource-constrained, LMICs, maternal death, pregnancy hypertension, pregnancy induced hypertension, pre-eclampsia, gestational hypertension, chronic hypertension, and eclampsia (Appendix C.1). We used dietary patterns and outcomes definitions as defined by study authors. As the focus is on maternal dietary patterns as the exposure, searches primarily sought observational cohort studies but also included randomized controlled trials to identify interventions to improve maternal dietary diversity or patterns. After scoping searches, case-control studies were added to the full searches. Case-controlled studies are less expensive, quicker and simpler to facilitate (219,220), which may make them more feasible in resource-limited LMIC settings – a focus of this review. Studies without a comparison group or longitudinal follow-up, such as cross-sectional studies, were not included in the review to reduce potential risks of bias (219). Titles and abstracts were independently screened by two reviewers (M.W.K., S.O.) and discrepancies were resolved by discussion with a third reviewer (K.S.). Full-texts were independently assessed for their eligibility by the two reviewers (M.W.K., S.O.), with the third reviewer (K.S.) providing an independent assessment for discrepancies. Studies were screened for inclusion if they were studies with (i) primary data collection; (ii) women of reproductive age during periconception, pregnancy or postpartum; (iii) conducted in LMICs; and (iv) reported maternal dietary patterns in association with pregnancy hypertension outcomes (Table 3.1). Only English language articles were included due to capacities of the reviewer team. Search results were uploaded in Mendeley (Elsevier, London, UK) to remove duplicates, then the reference list was uploaded to Excel (Microsoft, Redmond, USA) for study selection. 47 Table 3.1 Eligibility criteria Inclusion Exclusion Population Studies with women of reproductive age (15-49 years) during pre-pregnancy, pregnancy or postpartum (up to 42 days after delivery) Studies with women outside 15-49 years. Studies with men, children or infants without separated outcomes for women Exposure Studies that report maternal dietary patterns such as food intake frequencies and diversity Studies that reported on nutritional status without discussion of food groups or items Context Studies conducted in one/more low- and middle-income countries (as classified by the World Bank) Excluded if study does not specify outcomes of interest specifically for low- and middle-income countries Outcomes Studies that report associations between maternal dietary patterns and pregnancy hypertension outcomes (chronic hypertension, gestational hypertension, pre-eclampsia, superimposed pre-eclampsia) Studies that report on infant or child health outcomes only. Studies that do not report on pregnancy hypertension outcomes Study design Case-controlled, cohort studies, randomized controlled trials. Studies with primary data collection. Cross-sectional surveys, uncontrolled pre-post studies and studies without primary data collection and sufficient methodological data, including reviews, commentaries and editorials, letters to the editor, study protocols, conference abstracts and proceedings. Language Studies published in the English language Excluded if not written in the English language Other No restrictions on the time of publication Details about study design, country, population characteristics, exclusion criteria, age of participants, dietary assessment, dietary patterns and food groups identified, outcome measured, 48 comparative risk, relative effect, and risk factors associated with pre-eclampsia incidence and dietary patterns were extracted into a data extraction sheet on Excel (Microsoft, Redmond, USA) with independent review by two reviewers. Potential confounding factors and co-interventions were also extracted in preparation for quality assessment. To access study quality, we evaluated each included study with the ROBINS-I risk of bias (RoB) tool, a conceptually rigorous tool for non-randomized studies that uses the Cochrane-approved RoB approach and focuses on internal validity (221). No studies were excluded from the narrative synthesis on the basis of their quality assessment. However, following the guidance for using ROBINS-I, studies with high RoB (critical risk of bias) were excluded from meta-analyses (222). Evidence from studies of similar design, data collection methodology, sample and outcomes reported was pooled using Review Manager (RevMan 5) and reported as odds ratios with 95% confidence intervals. Evidence was pooled according to Mantel-Haenzel random-effects model for analyses with substantial heterogeneity (I2>50%) and sensitivity analyses conducted to explore the impact of study quality on heterogeneity levels (223). Funnel plots to estimate publication bias were planned if there were more than 10 included studies in the meta-analysis. 3.3 Results A total of 4,993 records were identified from our database searches (2,648 from Medline, 1,801 from Embase, 446 from Web of Science, 14 from CINAHL, 1 from AJOL, 32 from WHO Regional Databases, 43 from Central, 6 from ClinicalTrials.Gov, and 2 from the ICTRP Search Portal) (Figure 3.1). Two additional unique records were located through Google Scholar and reference list searching. After removal of duplicates and screening against the eligibility criteria, 13 studies were included in the review. Forty-three full text articles were excluded. Reasons for 49 exclusion included that the study did not investigate the population (224–227), exposure (228–232), or outcome of interest (227,229,233–259), was not conducted in a LMIC (169,173,180), a conference abstract only (260), cross-sectional survey design (52,261), or were duplicates(245,262) (Appendix C.2). Figure 3.1 PRISMA flow diagram for the systematic review on maternal dietary patterns and pregnancy hypertension in low- and middle-income countries 3.3.1 Characteristics of included studies One article was published prior to 2000 (263), one between 2001-2010 (264), and 11 between 2011-2020 (265–275). Overall, there were seven studies from sub-Saharan Africa and six studies 50 from Asia and the Middle East. There were five studies from Ethiopia (266,267,269,271,275), which was the country with the most studies, followed by Iran with four studies (268,270,273,274). There was a study each from mainland China (272), Turkey (265), DR Congo (264) and Zimbabwe (263). All studies were prospective design with dietary intake data collected, pregnancy monitoring, and recording of morbidities. The most common study design was prospective case-controlled with seven unmatched (263,265–267,271,273,274) and three matched studies (268,269,275). In addition, there were two prospective cohort studies (264,270) and one secondary analysis of a randomized controlled trial (272). Nine studies reported pre-eclampsia as an outcome (263,265–268,271,273–275) while three studies reported both pre-eclampsia and gestational hypertension as study outcomes (264,270,272). One study reported HDPs, including pre-eclampsia, gestational hypertension or superimposed pre-eclampsia (269). For more information on study characteristics, see Table 3.2 (see Appendix C.3 for dietary pattern classifications from each included study, Appendix C.4 for outcome definitions from each included study, Appendix C.5 for reported study outcomes by study). 51 Table 3.2 Characteristics of included studies Reference Study design Country, N Cases, n Population characteristics Age (years) Dietary assessment method, period Dietary pattern Outcome Abbasi et al 2019 (273) Prospective unmatched case-controlled study Iran, 510 participants 170 cases, 340 controls Pregnant women visiting three hospitals, eleven urban and seven rural health care centres in Lorestan province between Aug 2015-2016 Cases: 24; controls: 26 (Median) 198-item FFQ, 20-40 weeks (Cases: 35 ±5 weeks; controls: 26 ±6 weeks) Healthy; Western; Iranian traditional PE Atkinson et al 1998 (263) Prospective unmatched case-controlled study Zimbabwe, 374 participants 180 cases, 194 controls Pregnant women delivering Harare Maternity Hospital or one of nine clinics in suburbs of Harare city, between Jun 1995 to Apr 1996 Cases: 25.6 ± 6.4; controls: 24.8 ± 7.9 (Mean +SD) Questionnaire, during postpartum hospital stay (retrospectively recall for the month prior to birth) Meat; poultry; fruit; fish; vegetables; and dairy PE Endeshaw et al 2015 (266) Prospective unmatched case-controlled study Ethiopia, 453 participants 151 cases, 302 controls Pregnant women attending antepartum or intrapartum care at any public health facility in Bahir Dar City between Jun-Sep 2014 Range: 25 to 29: 33% of case; 36% of controls Questionnaire, during pregnancy (20 weeks onwards) and delivery care for cases; during delivery care for controls Fruit; vegetable; animal product; coffee; alcohol PE 52 Grum et al 2017 (267) Prospective unmatched case-controlled study Ethiopia, 291 participants 97 cases, 194 controls Pregnant women delivering at Gandhi and Sewditu Memorial hospitals in Addis Ababa between Dec 2015-Feb 2016 25.42 ±5.33 (Mean + SD) Questionnaire, during delivery care services Fruit; alcohol; nutritional counselling during ANC PE Grum et al 2018 (271) Prospective unmatched case-controlled study Ethiopia, 243 participants 81 cases, 162 controls Pregnant women delivering at Gandhi and Sewditu Memorial hospitals in Addis Ababa between Dec 2015-Feb 2016 27.22 ±5.03 (Mean + SD) Questionnaire, during delivery care services Fruit; vegetable; coffee; nutritional counseling during ANC PE Gulsen et al 2012 (265) Prospective unmatched case-controlled study Turkey, 247 participants 92 cases, 155 controls Pregnant women from Konya and neighboring cities hospitalized with pre-eclampsia at the Selcuk University Meran Medical School clinic between Oct 2004-May 2005 Range: 20 to 34: 65% of cases; 88% of controls Questionnaire, 2nd-3rd trimester Milk; yogurt; yogurt drink; cheese; dairy desserts; egg; meat; chicken; meat product; fish; legumes; bread; PE 53 vegetables; fruit Hajianfar et al 2018 (270) Prospective cohort study Iran, 812 participants NA Healthy pregnant women in Isfahan referred to health centres during the first-trimester of pregnancy in 2015-2016 Range: 20-40 years 117-item FFQ, 8-16 weeks Western; traditional; healthy GH; PE Kahsay et al 2018 (269) Prospective matched case-controlled study Ethiopia, 330 participants 110 cases, 220 controls Pregnant women after 20 weeks gestation attending antenatal care clinics at seven public hospitals in Tigray region, between Jun-Nov 2017 Cases: 27.6 ±5.6; Controls: 26.7 ±5.8 (Mean + SD) 18-question FFQ, during pregnancy (20 weeks onwards) and delivery care Fruits; vegetables HDP (GH, PE, SIP) Longo-Mbenza et al 2008 (264) Prospective cohort study DR Congo, 238 participants PE: 7 (2.9%); GH: 4 (1.7%) Black pregnant women admitted to the rural Evangelical Hospital in Kimpese between Jan-Mar 2003 27 ± 6.4 (Mean +SD) Questionnaire, 1st trimester Vegetables; meat GH; PE Mekie et al 2020 (275) Prospective matched case-Ethiopia, 321 participants 107 cases, 214 controls Nulliparous women delivering at three high volume hospitals 22.92 ± 4.64 (Mean +SD) Questionnaire, during pregnancy Fruits; vegetables; coffee; alcohol; PE 54 controlled study in West Amhara between Jan-April 2018 nutritional counselling during ANC Mi et al 2019 (272) Randomized controlled trial (secondary analysis) China, 987 participants PE: 19 (1.9%) Pregnant women enrolled at preconception and prenatal care in three rural counties in Shaanxi Province between Dec 2015 and Feb 2018 25.3 ±4.2 (Mean +SD) 107-item FFQ, during pregnancy Vegetable; meat; fruit; snack; wheat staple GH; PE Sheikhi et al 2018 (268) Prospective matched case-controlled study Iran, 125 participants 62 cases, 63 controls Pregnant women attending Iman-Ali Hospital between Jun-Sep 2015. Cases: 29.3±6.7; controls: 25.8±6.2 (Mean +SD) 169-item FFQ, 30-36 weeks Meat, beans nuts and eggs; milk; grains; vegetables; fruit PE Zareei et al 2019 (274) Prospective unmatched case-controlled study Iran, 182 participants 82 cases, 100 controls Pregnant women referred to the Gynaecology Ward of vali-e-Asr Hospital in 2016 Cases: 28.96 ± 5.85; controls: 27.91 ±4.93 (Mean +SD) 169-item FFQ, during pregnancy Unhealthy; healthy PE ANC – antenatal care; CH – chronic hypertension; FFQ – food frequency questionnaire; GH – gestational hypertension; HDP – hypertensive disorders of pregnancy; PE – pre-eclampsia; SD – standard deviation; SIP – superimposed pre-eclampsia 55 3.3.2 Quality assessment Overall, seven studies were classed as moderate risk of bias, four as serious risk of bias, and two as critical risk of bias (see Appendix C.6 for ROBINS-I Risk of Bias quality assessment of each included study and Appendix C.7 for summary risk of bias). All but two studies adjusted for important baseline confounders (264,265). Over half of the studies controlled for maternal age (9/13, 69.2%) and a number of studies controlled for parity/gravidity (6/13, 46.2%), pre-pregnancy BMI (6/13, 46.2%) and family history of hypertension (4/13, 30.8%) (see Appendix C.8 for adjustment factors). The majority of studies also excluded women with a pre-pregnancy history of hypertension (7/13 excluded, 1/13 adjusted, 61.5% total). Based on a list of potential risk factors for pre-eclampsia described by Schoenaker and colleagues (99), a number of confounding variables were unaccounted for in all studies, including ethnicity, season of infant birth, maternal height, and smoking status. Some studies considered ethnicity in participant characteristics to understand the composition of study samples; however, no analyses adjusted for ethnicity. Few studies adjusted for socio-economic status, history of pregnancy hypertension, blood pressure in early pregnancy, gestational age, pregnancy interval, gestational weight gain, physical activity, total energy intake, and dietary supplement use (1-3 studies each). Some studies controlled for confounders beyond the list described by Schoenaker and colleagues (99), including rural/urban residence; educational level; occupation; cohabitation; family planning and whether the current pregnancy was planned; drug use; anemia; urinary tract infections; multiple pregnancy; antenatal care visits; differences in physical activities prior to, as opposed to during, the pregnancy; gestational diabetes; and history of miscarriage, stillbirth, and pregnancy termination. Due to the need for a clinical diagnosis for pre-eclampsia and other forms of pregnancy hypertension, 12 out of 13 studies recruited participants at a health facility; only the 56 randomized controlled trial also recruited in the community setting (272). Pregnancy hypertension was often diagnosed by clinicians external to the dietary study. All studies relied on self-report of dietary intake patterns through food frequency questionnaires (FFQs) facilitated by trained interviewers, of which six studies used validated FFQs (268–270,272–274). 3.3.3 Healthy dietary patterns Four studies employed principal component analysis (PCA) to elicit dietary patterns from habitual diets of study participants. Study participants were scored on consumption frequency of foods characterizing dietary patterns and divided into quartiles (270,272,274) or tertiles (273). High adherence to a dietary pattern included those in the fourth quartile (Q4) or third tertile (T3) while first quartile (Q1) or tertile (T1) were classified as low adherence. Three Iranian studies described a healthy dietary pattern characterized by frequent consumption of vegetables, fruit and dairy products, particularly low fat dairy (270,273,274). These studies found that women who scored higher on the healthy dietary pattern had lower odds of developing pre-eclampsia. Case-control studies (two studies) found that high adherence to a healthy dietary pattern significantly reduced the odds of pre-eclampsia (T3 vs T1 adjusted OR 0.13; 95% CI: 0.07, 0.22; P <0.001 (273), Q4 vs Q1 adjusted OR 0.22; 95% CI: 0.09, 0.53; P = 0.001 (274)) compared with low adherence. A prospective cohort study also found that high adherence to a healthy dietary pattern reduced the odds of pre-eclampsia (Q4 vs Q1 adjusted OR 0.49; 95% CI: 0.24,1.00; P =0.05) (270). A secondary analysis of a randomized controlled trial in China identified five main food patterns: vegetable, meat, fruit, snack and wheat staple (70). Women who scored high (Q4) in the vegetable dietary pattern characterized by frequent consumption of mushrooms, leafy and 57 cruciferous vegetables, root vegetables, melon vegetables and legumes had a 80% reduced risk of pre-eclampsia incidence (adjusted RR 0.20; 95% CI: 0.04, 0.98; P = 0.041) compared with those who scored low (Q1) (272). A higher vegetable dietary pattern score was associated with lower risk of proteinuria (adjusted RR Q4 vs Q1 0.44; 95% CI: 0.24, 0.80; P-trend=0.015). Vegetable dietary pattern was not associated with risk of gestational hypertension or proteinuria. Meat, fruit, snack and wheat staple dietary patterns were not associated with pre-eclampsia risk. In contrast, a case-control study in Iran found that high consumption of a Western dietary pattern characterized by red meat and/or processed meat, fried potatoes, pickles, sweets, pizza, and low intake of vegetables was associated with a four-fold increase in the odds of developing pre-eclampsia (adjusted OR 4.37; 95% CI: 3.04, 6.28; P <0.001) (273). An Iranian cohort study also found that a Western dietary pattern was associated with doubled the odds of developing pre-eclampsia (adjusted OR 2.08; 95% CI: 1.00, 4.36; P = 0.02) (270). Slightly different than in the case-control study, the cohort study defined a Western dietary pattern as high consumption of processed meats, fruits, fruit juice, citrus, nuts, fish, desserts and sweets, sugar, saturated fat, sweet fruit, potato, legumes, coffee, egg, pizza, high fat dairy, whole grain and soft drinks (270). A meta-analysis was not possible due to heterogeneity of study design and reporting formats. 3.3.4 Vegetable dietary pattern Among seven studies that examined frequency of vegetable consumption in association with risk of developing pregnancy hypertension, one Ethiopian study examining HDP (269) and two studies from Zimbabwe (263) and Iran (268) reporting pre-eclampsia outcomes did not find a significant association. Four studies found significant associations. Three case-control studies from Ethiopia reported that adequate vegetable consumption (at least one to three servings per 58 week) was associated with reduced odds of developing pre-eclampsia (adjusted OR 0.46; 95% CI: 0.24, 0.90; P =0.023 (266), adjusted OR 0.42; 95% CI: 0.22, 0.82; P <0.05 (275), daily vs no intake adjusted OR 0.95; 95% CI: 0.01, 0.71; P <0.05 (271)). One of these studies found that the relationship between adequate vegetable intake and pre-eclampsia incidence was only significantly protective after adjustment for daily but not one serving per week (271). Additionally, a prospective cohort study from DR Congo found that women with three daily servings of vegetables was associated with a 12% reduced risk of pre-eclampsia incidence (RR 0.88; 95% CI: 0.6, 0.98; P <0.01) (264). A meta-analysis pooled evidence from the four case-control studies that measured pre-eclampsia and could be grouped as dichotomous indicators resulted in a pooled OR 0.38 (95% CI: 0.18, 0.80; I2 85%; P = 0.01) for adequate consumption of vegetables compared with low or no consumption and risk of developing pre-eclampsia (Figure 3.2A). A sensitivity analysis excluding studies classed as serious risk of bias lowered the heterogeneity between studies without changing the direction of the effect (OR 0.29; 95% CI: 0.20, 0.43; I2 14%; P < 0.00001) (Figure 3.2B). One study with a serious risk of bias that defined low consumption as below 120 servings per month was responsible for a majority of the heterogeneity (263). The three remaining studies evaluated consumption of vegetables at least once per week (266,271,275). 59 Figure 3.2 (A) Adequate consumption of vegetables compared with low or no consumption for the risk of developing pre-eclampsia in low- and middle-income countries; (B) Sensitivity analysis excluding studies classed as serious risk of bias 3.3.5 Fruit dietary pattern Among seven studies that examined frequency of fruit consumption in association with risk of developing pregnancy hypertension, three studies from Zimbabwe (263), Iran (268) and Ethiopia(267) reporting pre-eclampsia outcomes did not find a significant association. Three studies fromEthiopia reported that adequate fruit consumption (at least one to three servings per week) was associated with reduced odds of developing pre-eclampsia (adjusted OR 0.51; 95% CI: 0.29, 0.91; P = 0.023 (266), adjusted OR 0.45; 95% CI: 0.24,0.87; P <0.05 (275), adjusted OR 0.23; 95% CI: 0.06, 0.91; P <0.05) (271)). A study from Ethiopia found that regular fruit consumption at least two to four times per week was associated with lower odds of developing HDP compared to a women with low consumption (adjusted OR 0.19; 95% CI: 0.09, 0.42; P <0.001) (269). 60 A meta-analysis of the five case-control studies that measured pre-eclampsia and could be grouped as dichotomous indicators found a pooled OR 0.42 (95% CI: 0.24, 0.71; I2 79%; P =0.001) (Figure 3.3A) for adequate consumption of fruits compared to low or no consumption for the risk of developing pre-eclampsia. A sensitivity analysis excluding studies with serious risk of bias lowered the heterogeneity between studies though the variability was still moderate (OR 0.34; 95% CI: 0.21, 0.54; I2 = 56%; P <0.00001) (Figure 3.3B). The three remaining studies also evaluated consumption of fruits at least once per week (266,271,275). The two studies with a serious risk of bias classified low consumption of fruit as 12 or less servings in the month before delivery (263) and no fruit intake during pregnancy (267). Figure 3.3 (A) Adequate consumption of fruits compared with low or no consumption for the risk of developing pre-eclampsia in low and middle-income countries; (B) Sensitivity analysis excluding studies classed as serious risk of bias 61 3.3.6 Other dietary patterns Other food groups, including meat, poultry, fish, dairy and other animal products, and grains dietary patterns, were inconsistently defined among studies. A study from Zimbabwe suggested that higher consumption of meat may be associated with risk for pre-eclampsia (adjusted OR 1.9; 95% CI: 1.5, 5.6 for women with 12-45 servings and adjusted OR 2.9; 95% CI: 0.8, 3.0 for women 45-72 servings, compared with ≤ 11 servings in the month before delivery; P-trend = 0.142), while poultry, fish, and dairy were not (263). A study from Ethiopia found that overall animal product intake was not associated with pre-eclampsia (266), while a study from Iran found that meat, beans, nuts, eggs and milk were not associated with pre-eclampsia (268). The same Iranian study found that higher consumption of grains was associated with a two-fold increase in the odds of developing pre-eclampsia (adjusted OR 2.00; 95% CI: 1.11, 3.61; P <0.05) (268). The association between coffee consumption and alcohol with risk of developing pre-eclampsia or HDPs was explored in five studies from Ethiopia (266,267,269,271,275). None of four studies looking at coffee consumption found a significant association (266,269,271,275). Three Ethiopian studies found that alcohol use during pregnancy was associated increased odds of developing pre-eclampsia (OR 2.36; 95% CI: 1.42, 3.92; I2 = 69%; P =0.001) (Figure 3.4), though two studies were not significant after adjusting for confounders (266,275). 62 Figure 3.4 Alcohol use during pregnancy and risk of pre-eclampsia in low- and middle-income countries3.3.7 Factors associated with dietary patterns Three studies from Ethiopia found that women who reported receiving dietary advice during antenatal care significantly reduced the odds of developing pre-eclampsia (adjusted OR 0.52; 95% CI: 0.29, 0.96; P < 0.05 (275), adjusted OR 0.22; 95% CI: 0.10, 0.48; P <0.001 (267), adjusted OR 0.17; 95% CI: 0.05, 0.60, P <0.05 (271)) Other studies highlighted the influence of socio-economic factors on dietary patterns(265,266,270,274). A study from Turkey found that low education and income was associated with lower quality maternal diets and observed that a majority of the women with pre-eclampsia tended to meet their protein needs with low quality and cheap vegetable protein products instead of animal products (265). A study from Iran found that women with high adherence to a healthy diet characterized by vegetables, fruits, low fat dairy, poultry and red meat were more likely to be employed, have graduated from university, and have husbands who were also employed (270). A study from Ethiopia reflected that due to poverty, “regular intake of green vegetables, fruit and animal products is impossible for most of the population, including pregnant women” (266). 63 3.4 Discussion To the best of our knowledge, this is the first review examining maternal dietary patterns in association with pregnancy hypertension specifically in LMICs. Three studies identified that a healthy dietary pattern characterized by high consumption of fruits, vegetables and low fat dairy products was associated with a significant reduction in odds of developing pre-eclampsia(270,273,274). Maternal diets with no or low consumption of vegetables was associated with 2.6 times the odds of developing pre-eclampsia compared with women who consumed vegetables during their pregnancies. Similarly, no or low consumption of fruit was associated with 2.3 times the odds of developing pre-eclampsia compared with women who consumed fruits during their pregnancies. Limited data were found to suggest that high consumption of meat (263), grains(268), a “Western” style diet characterized by foods with high sugar content, fried and/or processed (270,273) or alcohol consumption during pregnancy (267) may be associated with higher pre-eclampsia incidence rates; however, mixed results and inconsistent definitions between studies preclude conclusions. With 10 out of the 13 included studies published within the past decade, there has been growing interest in maternal dietary patterns as a risk factor for pre-eclampsia in LMICs. However, the literature available is mostly limited to two countries, Ethiopia and Iran; this limits the broader relevance of the observed findings. Moderate to serious risk of bias in a majority of studies limits the quality of the evidence, as shown by substantially reduced heterogeneity in pooled outcomes when studies with a serious risk of bias were excluded. Additionally, while the review was limited to cohort and case-control studies and randomized controlled trials, all of which have lower risk of bias than cross-sectional studies, the evidence is drawn mostly from case-control 64 studies with few large prospective cohort studies available. This weakness in the evidence base suggests a clear need for additional such studies to confirm the relationship to pre-eclampsia. Although the quality and completeness of current evidence is low, the association between healthy maternal dietary patterns with lower risk of pre-eclampsia incidence in LMICs is supported by the similar direction of evidence from HICs. A previous review including two case-control studies from the United States and two cohort studies from Norway suggested that maternal diets rich in fruits and vegetables had a beneficial effect on pre-eclampsia (99). A review with four publications based on cohort studies in Western Europe found a 22% lower odds of pre-eclampsia incidence among women who consumed a healthy dietary pattern characterized by high consumption of fruits, vegetables, whole-grain foods, fish and poultry (30). Three of these studies were based on the Norwegian Mother and Child Cohort (MoBa), which found a 28% reduced odds of developing pre-eclampsia among women with high adherence to a dietary pattern characterized by vegetables, plant foods and vegetable oils (T3 vs T1 OR 0.72; 95% CI: 0.62, 0.85; n=23,423) (276), particularly those who reported frequent consumption of organic vegetables (277). The New Nordic diet and the Mediterranean diet, characterized by the high intake of fruits and vegetables, whole grains, fish, legumes and vegetable oil, were associated with lower rates of pregnancy hypertension in cohort studies from Norway (MoBa)(183), the Netherlands (Generation R) (181), Greece (180) and Australia (the Australian Longitudinal Study on Women's Health) (182). The Project Viva cohort from the United States also found that women with higher consumption of vegetables, fruits, fibre and food rich in folate, calcium and iron, white compared to red meat and polyunsaturated compared to saturated 65 fatty acids/trans fats were 13% less likely to develop pre-eclampsia (OR 0.87; 95% CI: 0.76, 1.00; n= 1,777) (278). As in studies conducted in HICs, this review finds that healthy diets characterized by adequate consumption of fruits and vegetables are associated with lower risk of pre-eclampsia incidence. However, while the odds of developing pre-eclampsia was lowered by 13-28% by healthy maternal dietary patterns between five cohort studies in Western Europe and the United States(181,183,276–278), the potential risk reduction may be even larger in LMIC settings. Four studies from Iran and China reported that healthy maternal diets characterized by high intake of vegetables was associated with a 51-82% risk reduction in incidence of pre-eclampsia (270,272–274). This may be related to high rates of maternal malnutrition in LMICs, and the advantages offered by a diversified diet, rich in micronutrients (51). Maternal malnutrition, frequent in LMICs, is characterized by imbalanced macronutrients and inadequate micronutrient intakes, such as in iron, folate, calcium and zinc, and has been documented in a review of 62 studies (51). A multi-country study from Pakistan, DR Congo, Guatemala and India found that inadequate dietary diversity was found in upwards of 80% of poor, rural women during their first trimester and more than 80% had inadequate intakes of folate, vitamin B12 and choline (252). Researchers also found inadequate intake of calcium, thiamine, riboflavin, and vitamin B6 were common, but rates varied between countries (252). Additionally, a study in South Africa and Zimbabwe with women with a history of pre-eclampsia found high rates of overweight and obesity (74% from South Africa and 60% from Zimbabwe with BMI above normal) alongside high rates of undernutrition (235). Over 80 to 100% of women in the study had below recommended intake of calcium, iron, folate, magnesium, zinc 66 and selenium and a majority of women had lower protein intakes than the estimated average requirement (71% South Africa, 98% Zimbabwe) (235). Two Ethiopian studies included in the review also described heightened risk of pre-eclampsia incidence with increased mid-upper arm circumference while noting low overall consumption of fruits and/or vegetables (266,275). Higher rates of maternal malnutrition including both obesity and overweight alongside nutritional deficiencies in LMICs may highlight the importance of adequate diet for maternal health, and the potential impact of healthy maternal diets can have on reducing risk of pre-eclampsia and improving maternal outcomes in general. While not reporting specifically on pregnancy hypertension, cohort studies from Ethiopia and Nepal reported that consumption of dark green, leafy vegetables in particular were associated with lower odds of adverse pregnancy outcomes (279) and maternal mortality (254). While the current review suggests the potential for healthy maternal diets, it is likely that socio-economic status (SES) may play an important role and it is unclear whether access to fruits and vegetables on a regular basis is directly related to a lower incidence of pre-eclampsia or indirectly as access to higher quality maternal diets is representative of higher SES. A number of the included papers suggest the potential importance of SES, however the discussion was limited (265,266,270,274). Studies from rural Bangladesh examining determinants of improved household food security and dietary diversity identified household wealth and female literacy as important factors (256,259). Despite having knowledge about their importance during pregnancy, dietary diversity and consumption of micronutrient-rich foods was low among pregnant women of lower socio-economic status, (259). A Tanzanian cross-sectional survey found that higher dietary diversity was associated with HDP, but researchers highlighted that 67 may have been driven by urban residence, greater pre-pregnancy BMI, and HIV positive status(280). More research is needed to understand the influence of SES on the relationship between maternal diets and adverse pregnancy outcomes, such as pre-eclampsia, in LMICs. Strengths of our review include the use of multiple reviewers, a comprehensive search strategy employing multiple databases and grey literature, and use of quality assessments. A limitation of the current review is the exclusion of non-English language articles, which may have excluded some studies. Publication bias was not evaluated due to the relatively small number of studies included in the meta-analyses and there is potential of an increased risk of making a Type I error that results from testing multiple study outcomes in meta-analyses. Additionally, inconsistent definitions of dietary patterns limited the ability to pool evidence, particularly beyond frequency of fruit and vegetable consumption. Furthermore, while material dietary diversity was a focus outlined in the protocol, it remains a research gap in the literature. Studies tend to look at consumption of different food groups but not necessarily to see if the same woman is consuming multiple food groups. 3.5 Conclusion Maternal diet is increasingly recognized as critical to the health of the mother as well as to the healthy development of her child. Pre-eclampsia is the second leading direct cause of maternal deaths worldwide and there is evidence that healthy dietary patterns characterized by regular consumption of fruits and vegetables may be related to lower incidence of pre-eclampsia. This association was previously demonstrated in research conducted in HICs. The current review suggests that the association may also be found among women in LMICs, perhaps with an even stronger potential effect. However, the completeness and quality of evidence from LMICs is 68 currently low, with few large, prospective cohort studies investigating this topic. Further research with larger cohorts is needed to systematically evaluate the association, investigate deeper into dietary diversity and the consumption of different food groups and explore the potential interaction with socio-economic status. 69 Chapter 4: Community perspectives on maternal diets and dietary diversity in rural Kenya, Mozambique and The Gambia: a qualitative study 4.1 Introduction Dietary diversity is a key component of a quality diet. A varied diet increases the probability of nutrient adequacy and higher dietary diversity is associated with a decreased risk of all-cause mortality (281–283). Low diversity dietary patterns with insufficient intake of whole grains, fruits and vegetables have emerged as a leading contributor to morbidity and mortality around the world (284). In sub-Saharan Africa, an estimated 22.5% of the population faced hunger in 2022 (285). Due to high nutritional requirements during gestation to support a healthy pregnancy, pregnant and lactating women are especially vulnerable to nutrient inadequacies (286–291). However, dietary patterns of pregnant women in LMICs were frequently predominated by starchy foods and characterized by inadequate micronutrient intakes (292). A review found substantial rates of iron, vitamin A, iodine, zinc and folate deficiencies among pregnant and non-pregnant WRA across four countries in sub-Saharan Africa, including up to 61% of pregnant women deficient in iron and up to 76% deficient in zinc (293). Low maternal dietary diversity during pregnancy has been associated with a number of adverse pregnancy outcomes (294,39,295,37,296), as well as associated with increased rates of maternal depression and anxiety (297). Though dietary diversity is recommended by the WHO to be part of healthy eating counselling during antenatal care for all women (298), the literature on community knowledge and perceptions of dietary diversity is sparse. Limited previous qualitative studies in Tanzania (299,300), Uganda (301), and Nigeria (302) have often focused on agricultural and economic 70 factors and a gap remains on understanding local conceptualizations of dietary diversity within the context of maternal diets. The study explores community perceptions of dietary patterns and diversity during pregnancy and lactation, and their influencing factors in rural Kenya, Mozambique and The Gambia. 4.2 Methods 4.2.1 Study design and research setting This community-based qualitative study embedded within the PRECISE Network investigated local perspectives and experiences of dietary diversity and maternal diets in sub-Saharan Africa. Maternal diets were conceptualized as the food eaten during pregnancy and lactation. The study featured IDIs triangulated with participant observation and photovoice, and is reported based on the “Consolidated criteria for reporting qualitative research” (COREQ) (303). Qualitative research was conducted at PRECISE Network study sites Mariakani and Rabai in coastal Kenya, Xinavane in the Southern region of Mozambique, and Illiasa in the North Bank of The Gambia. Communities were predominantly rural; only Mariakani was periurban. 4.2.2 Recruitment and selection The study purposively drew a sample of pregnant and recent mothers who had delivered within the last two years, male and female family members from participating mothers’ households and community leaders. Potential participants were approached by a PRECISE Network study team member in person or by phone for individual study sensitization. A sample size of 12-18 interviews in each country was estimated to reach data saturation with a variety of perspectives (92). An additional three pregnant or recent mothers were recruited in each country for 71 participant observation and five-to-ten pregnant or recent mothers for photovoice to confirm data saturation (93). 4.2.3 Data collection Fieldwork took place between May and October 2022 with trained Kenyan, Mozambican and Gambian data collectors (five female, six male). Interviewers from each country were selected based on familiarity with national and ethnic languages in each study community, but did not know participants personally prior to the study. In-person interviews were conducted following a piloted semi-structured topic guide at secluded places within the participant’s household. Interviews were between 45 minutes to two hours in length, conducted in the participants’ preferred language. For participant observation, M.W.K and a local field team member in each country spent one to two full days to shadow each woman during her daily food provisioning activities in her household and community. Researchers participated in the process of obtaining food, such as from a store, garden or local market, then cooking and eating together. Fieldnotes were compiled during and after each participant observation session documenting informal conversations during observations on food provisioning, food preparation, meals, mealtime configurations within a family setting and overall conversations about maternal diets. Photovoice was conducted with an additional 20 women (five each in Mariakani and Rabai (Kenya); five in Illiasa (The Gambia); five in Xinavane (Mozambique). Digital cameras were distributed to women with training on how to use the cameras and take photographs, whilst maintaining privacy and participant safety. Cameras were collected by researchers approximately four days later. Photographs were used as prompts during in-person discussions either with each woman individually (The Gambia) or in a 90-minute focus group discussion (Kenya and Mozambique), 72 as directed by local staff to be culturally appropriate in each country. There were no refusals to participate and no repeat interviews were conducted. Debriefs with the data collectors during the data collection period ensured data quality and consistency. 4.2.4 Data analysis We employed a thematic approach in analyzing the data (304,305). Field notes and audios were recorded with permission, transcribed verbatim and translated into English. Transcripts were uploaded to NVivo software (Release 1.7.1; QSR International, Melbourne, Australia) for analysis. Participant characteristics were compiled from transcripts based on open-answered demographics questions in the interview guide. After familiarizing with the data, a coding framework was developed inductively from the data and deductively from research questions to cover maternal dietary patterns and dietary diversity, community knowledge of healthy maternal diets, food security and other (Table D.1). Six interviews were double coded by a Canadian (M.W.K) and Kenyan researcher (S.D.) to pilot the coding framework and ensure interrater reliability; the remaining interviews were coded by M.W.K. Two photovoice transcripts were reviewed in collaboration with Kenyan researchers with the coding framework; the remaining photovoice transcripts and fieldnotes from participant observation were coded by M.W.K. Themes were compared across methodologies and presented to the PRECISE Network consortium for discussion of key themes with researchers across all country sites. Themes were enumerated by coding frequency overall (Table D.2) and by country and participant group (Table D.3). Following a thematic analysis approach, frequency of occurrence in transcripts was not used to determine the themes itself but rather to explore patterns of meaning from participants’ perspectives (306). In other words, themes that were more frequently 73 mentioned across participant groups and countries may be considered more salient in participants’ lived experiences; infrequently mentioned themes were reported as minor themes. A tree map was used to visualize patterns of dietary diversity influencing factors relative to each other, with larger rectangles in the figure representing more frequent occurrence of the theme (Figure 4.1, based on numbers from Table D.2). A thematic map was also constructed to illustrate the relationships between themes and summarize overall community perspectives on dietary diversity (306). 4.2.5 Reflexivity Throughout the research process, I reflected on my positionality as an outsider in these communities, including as an Asian-Canadian female researcher from a high-income country. With awareness of my positionality, I involved clinician-scientists and PRECISE project coordinators from each country to ensure cultural appropriateness and contextualization of methods and interpretation of findings relevant to each study community. The process took years; discussions began with the development of the study design in 2019, and follow-up has continued into the year 2024. For research in maternal health and diets, my positionality as an outsider was also partly balanced through my positionality as a woman, as a new mother with a 10 month-old infant, my enthusiasm to participate in food preparation and consumption activities, and visiting communities with local data collectors who were fluent in local languages and often from the same ethnic group. 74 4.3 Findings 4.3.1 Participant characteristics There were 47 interviews in total; 18 from Kenya, 14 from Mozambique, and 15 from The Gambia (see Table 4.1). Overall, these included 17 pregnant or recent mothers, 10 male relatives, 9 female relatives and 11 community leaders. Male relatives included husbands and brothers-in-law and female relatives included mothers-in-law and sisters-in-law. Community leaders included traditional birth attendants, religious leaders, village elders and chiefs, as well as local government officials. Participants from The Gambia were largely reliant on farming, reporting that either they farmed or that they depended on the income of a family member who farmed. Participants from Kenya least frequently reported farming as their primary occupation and a third (33%; 6 of 18) reported engaging in small business. Table 4.1 Demographic characteristics of interview participants Kenya (n=18) Mozambique (n=14) The Gambia (n=15) Total (n=47) Participant group Pregnant or recent mother 7 (39%) 5 (36%) 5 (33%) 17 (36%) Husband or brother-in-law 4 (22%) 3 (21%) 3 (20%) 10 (21%) Mother-in-law or sister-in-law 3 (17%) 3 (21%) 3 (20%) 9 (19%) Community leader 4 (22%) 3 (21%) 4 (27%) 11 (24%) Sex Female 13 (72%) 9 (64%) 10 (67%) 32 (68%) Male 5 (28%) 5 (36%) 5 (33%) 15 (32%) Age 25 years old or younger 6 (33%) 1 (7%) 2 (13%) 9 (19%) 26 to 35 years old 3 (17%) 6 (43%) 6 (40%) 15 (32%) 36 to 45 years old 4 (22%) 2 (14%) 1 (7%) 7 (15%) 46 years or older 4 (22%) 5 (36%) 5 (33%) 14 (30%) Unknown 1 (6%) 0 (0%) 1 (7%) 2 (4%) Marital status Married or cohabitating 18 (100%) 14 (100%) 12 (80%) 44 (94%) Single 0 (0%) 0 (0%) 2 (13%) 2 (4%) 75 Widowed 0 (0%) 0 (0%) 1 (7%) 1 (2%) Number of children 0 to 1 child 4 (22%) 1 (7%) 2 (13%) 7 (15%) 2 to 4 children 11 (61%) 9 (64%) 4 (27%) 24 (51%) 5 or more children 3 (17%) 4 (29%) 9 (60%) 16 (34%) Highest level of education attained No formal education 3 (17%) 1 (7%) 13 (87%) 17 (36%) Some primary school 6 (33%) 5 (36%) 2 (13%) 13 (28%) Completed primary school 4 (22%) 8 (57%) 0 (0%) 12 (26%) Completed secondary school 1 (6%) 0 (0%) 0 (0%) 1 (2%) Post-secondary education 4 (22%) 0 (0%) 0 (0%) 4 (9%) Occupation Farming 1 (6%) 6 (43%) 7 (47%) 14 (30%) Small business 6 (33%) 3 (21%) 1 (7%) 10 (21%) Labourer, house help or informal work 3 (17%) 4 (29%) 0 (0%) 7 (15%) Professional or government employment 2 (11%) 0 (0%) 0 (0%) 2 (4%) Housewife 5 (28%) 0 (0%) 3 (20%) 8 (17%) Dependent on adult children 0 (0%) 0 (0%) 4 (27%) 4 (9%) Other 1 (6%) 1 (7%) 0 (0%) 2 (4%) 4.3.2 Typical dietary patterns Participants reported a starchy base, typically comprised of grains as fundamental to a meal. This was mainly a stiff porridge made of maize meal in Kenya and Mozambique called ugali or xima respectively, and “cous” grains comprised mainly of millet or sorghum in The Gambia (Table 4.2). Participants reported that rice was also frequently consumed across all three countries and was highly preferred by community members. The starchy base was served with a sauce/stew, commonly made from leafy greens, beans, or fish. Fish commonly consumed included omena (small dried fish) among Kenyan participants, carapau (horse mackerel fish) among Mozambican participants, and small fish from the river among Gambian participants. Participants across countries described regular consumption of sweetened tea and white bread or fried dough, as well as widespread availability of cheap candies in their communities. Across the 76 three countries, participants shared that maternal diets did not substantially differ from typical household meals. However, green leafy vegetables were emphasized as healthy for women to eat during pregnancy and lactation, as well as meat and fruit when possible. Typical diets for lactating mothers often included additional servings of starchy staples for energy and to help promote breastmilk production. Table 4.2 Typical meals among maternal and general populations in Kenya, Mozambique and The Gambia Kenya Mozambique The Gambia Typical household meals “It’s just ugali… Currently, we are lucky; because of the rains, we have some vegetables, but for the other days, it is ugali and omena… We buy kale, which is found in the market and helps us. But the food that is mostly eaten is ugali made of maize flour” Community leader “The thing most consumed here in the community is xima… We always pray that our fields will produce maize for us to make xima… We cook the xima, the beans, and when there is money we buy rice and we cook” Mother-in-law “The type of food we eat here mostly is rice, findi, and beans both during the day and during the night.” Spouse Typical meals during pregnancy “Most of the time when a woman is pregnant, she eats vegetables especially mchicha with ugali. Also, she can eat meat… [and] can also eat oranges” Pregnant woman “Pregnant women can eat one thing and another, but…the most important thing is to eat xitsakatu, because xitsakatu brings blood in the body” Pregnant woman Fruits, and vegetables, and greens…They are a very good source of blood. And for pregnant women, they need more blood for their own health and that of their unborn baby. Pregnant woman Typical meals after delivery and during lactation “During breastfeeding, there is not specific food that they have to eat. However, they prefer [maize meal] “Foods made with groundnuts and xima… you have to eat those foods to be able to have strength and for the “Things like green leaves, porridge with groundnut and the likes are a good source of vitamins… It will help 77 porridge in the morning so that the body may become warm and help produce breast milk” Spouse child to be able to have enough milk” Breastfeeding mother them maintain good health and provide them with healthy milk that is necessary for the child’s development.” Spouse Kenya: ugali – stiff maize meal porridge, omena - small dried fish, mchicha – amaranth leaves; Mozambique: xima – stiff maize meal porridge, xitsakatu - green leafy vegetable made with groundnuts; The Gambia: findi – a type of local millet 4.3.3 Perceptions of dietary diversity Overall, participants reported familiarity with dietary diversity, which was conceptualized as mixing different types of food either within a meal or between meals. Participants across the three countries and population groups shared that consuming a variety of foods was important for health, including for pregnant and lactating mothers (Table D.2). Unmarried men and older mothers-in-law from The Gambia commented less on maternal diets, though voiced the value of diverse diets for all people (Table D.3). While the participants felt consuming the starchy base was filling, additional ingredients cooked as a stew served on top or cooked with the grains were required to add nutrition, with the generalization that more ingredients equated to healthier meals. Healthy meals were conceptualized to be “complete” with the inclusion of multiple food groups, particularly both meat/fish/beans and green leafy vegetables as well as a piece of fruit accompanying the staple grains in Kenya and Mozambique. Participants from The Gambia described multiple “condiments” such as fish, chicken, garden vegetables such as eggplants, bitter tomatoes, cabbage and onions cooked in the stew as adding to the nutrition and taste of food. 78 “Meals become healthy when you mix different nutrients in it. Just like today, you would eat green vegetables, which have vitamins. Tomorrow you get some meat, which is protein, or mix the green vegetables with meat, boil and give that to the pregnant mother, then get some ugali (stiff maize meal porridge), which is carbohydrates. That is a balanced diet and that is what makes a meal complete.” Spouse, Kenya “Foods now are more delicious now…because it has more ingredients than that of the past… Pregnant women should eat things like meat, leafy greens, vegetables, and seafood like fish to help them become heathy…If pregnant women fail to get enough of these varieties of foods… they develop a lot of complications such as anemia etc.” Traditional birth attendant, The Gambia “It’s eating different things with vitamins… As soon as I am pregnant, I want fried carapau (horse mackerel fish) with onion rice, I want roast chicken… I have to eat fruit. I have to eat things from the farm (vegetables) to increase blood for the child to grow well” Pregnant woman, Mozambique Participants emphasized that additional food groups provided “vitamins”, which were especially important during pregnancy and lactation to support the growing baby and prevent complications such as anemia. In contrast, a lack of dietary diversity, described as eating only the staple foods or the same foods for multiple meals, was considered unhealthy for pregnant women. “If you are pregnant and you wake up early in the morning to eat leftover food from yesterday…dried fish with cold ugali (stiff maize meal porridge), that is not good 79 nutritious food and it can even kill you… Also… eating ugali with salt…is not allowed” Pregnant woman, Kenya “If they want to depend on only rice, it sometimes gives the problems…. For rice, people like it but is not a health-giving food. Just things that are put on top of the rice, which give vitamins, but not the rice… Types of food like “Nyankatang” (rice cooked with dried fish, groundnuts, beans, chili and tomato)….has multiple condiments… [I]t gives a lot of vitamins to a pregnant woman.” Community leader, The Gambia “The meat itself, but… don't miss small vegetables…don't miss an orange and banana… [T]ogether they make a healthy diet…. When they [pregnant women] consume meat with xima (stiff maize meal porridge) only…The meal is decent, but not nutritious” Community leader, Mozambique 4.3.4 Perceptions of influencing factors While dietary diversity was described as ideal for health, participants also frequently described a limited number of foods consumed on a regular basis. Affordability and seasonality were described as leading factors that influenced the types of food pregnant and lactating mothers consumed in their communities, followed by knowledge, gender norms and cravings (Figure 4.1). Traditional beliefs, religion, and rural residency were least frequently mentioned factors. All factors were reported across all groups (countries Table D.2; participant groups Table D.3), though the emphasis of certain factors varied. Irregular weather patterns, particularly drought, was especially a concern voiced by Kenyan participants. Gambian participants more frequently described a lack of certain foods in rural communities and less frequently reported cravings and traditional beliefs as drivers for the types of food pregnant women eat. The influence of 80 pregnancy food cravings on maternal diets was especially emphasized in Mozambique. Illustrative quotes across countries can be found in Table D.4. Figure 4.1 Frequency map of reported themes for dietary diversity influencing factors Affordability and seasonality, the most frequently mentioned factors, were especially challenging for pregnant and lactating women as participants shared that nutritious foods were often purchased or seasonal. Fruits and vegetables, particularly leafy greens and other vitamin A rich fruits and vegetables, were more available during the rainy season in each respective country, though vegetables were grown during the dry season in The Gambia by those with gardens. Kenyan participants emphasized the ongoing drought in their region as a driving factor for limiting the types of food consumed, highlighting crop failures of fruits, vegetables and legumes and reduced grazing for local cows to produce milk due to unreliable and reduced rains. 81 “There are specific types of food that pregnant women and lactating others should depend on but due to lack of affordability, we all depend entirely on rice and coos (millet)…” Spouse, The Gambia “In summer, we don't have vegetables… The months of April, May and June, those are the winter period….Until July, we still have something. In August, there is nothing in the farms” Mother-in-law, Mozambique “The problem is like now when there is drought. There is no rain at all there is no food in the shambas (farms) so you can not get healthy foods.” Spouse, Kenya Participants described seasonality as interconnected with affordability because out-of-season crops required more money to purchase. In comparison to the past, Gambian participants reported increasing accessibility to different types of food in part due to monetary remittances from family members working abroad. However, participants from Kenya and Mozambique described substantial affordability barriers to dietary diversity. “Kale is also eaten. It’s just expensive… [when] the person can no longer plant because it is already very hot, and when they buy, it is sometimes 50mt (Mozambican metical)… [and] there is no money to buy anything else...” Pregnant woman, Mozambique “[We are] helped by some of our children living abroad with some money to buy food stuff….It was very difficult in the past… because of poverty…. Now things have changed, you talk of affordability but not availability; you can buy anything you want if you have money” Community leader, The Gambia 82 “It is too expensive and very difficult to afford change of food aside from ugali (stiff maize meal porridge). We just eat ugali in the afternoon and in the evening…Affordability, affordability. I think you can see that things are not that easy. People do not have jobs, they are not employed and do not have even casual jobs. People are burdened.” Community leader, Kenya Other major influencing factors described by participants included knowledge of healthy foods during pregnancy and lactation, local gender norms about household decision-makers, and pregnancy food cravings. Clinics were described as a key source of information of healthy maternal diets, but many participants shared that their knowledge was largely from experience, either from their own pregnancies or from family members. In all three countries, men were conceptualized as the primary provider for the household and the types of food consumed by pregnant women relied on what their spouses brought home or provided funds for. Emphasizing cravings was a way for women to request certain foods during pregnancies, although participants sometimes discounted the food women wanted as unnecessary cravings. “Whenever you go to the hospital, the doctor advises to eat fruits, vegetables and soup this helps a lot with increasing blood and energy” Recent mother, Kenya “If available, they (women) eat and if not, they just sit and wait… That is it… It is your husband who feeds and protects you.” Traditional birth attendant, The Gambia “I have a daughter who during her pregnancy she didn't eat anything other than oranges…That's because it's not the woman's will…But…what she carries in her womb.” Community leader, Mozambique 83 Factors less frequently mentioned by participants included traditional beliefs about pregnancy food taboos, religion and a rural/urban divide. There were some reports about food that should be avoided during pregnancy, including eggs, bread, meat and seafood. However, participants frequently reported that these beliefs were changing with increasing education about healthy foods during pregnancy and witnessing positive pregnancy outcomes among women who consumed these foods in their communities. Mentions of religious food restrictions were rare and participants only described pork as prohibited among Muslims. Participants more frequently mentioned religious holidays and other major celebrations as occasions where meat and chicken were consumed. Some food items were also difficult to find in rural and remote communities. Fruit and meat were reported to be more widely available in urban and periurban centers. “What they said in the old days was myth… she can eat eggs…because it provides vitamins for the baby.” Mother-in-law, Mozambique “We eat meat during Eid because my husband’s family is Muslim and they celebrate Eid. For me, because I am Christian, I can cook chicken for Christmas.” Pregnant woman, Kenya “We do not have oranges here. If you go to the urban areas and you see it there, you [can] buy… Pregnant women, when they go for the antenatal clinics and see it being sold, they buy and eat.” Community leader, The Gambia 4.3.5 Thematic map Figure 4.2 illustrates the community perspectives and experiences of dietary diversity described by study participants, highlighting how dietary diversity was conceptualized as ideal for health, 84 but limited in practice. Local conceptualizations of meals and perceptions that “vitamins” were needed for a healthy pregnancy and infant growth contributed to the health value of dietary diversity perceived by participants. However, a number of factors contributed to the capacity to achieve diverse diets. Dietary diversity influencing factors were sometimes described as interconnected, such as affordability, seasonality and irregular weather patterns, as well as women’s food cravings negotiated through gender norms and the knowledge men had about healthy foods during pregnancy, and changing traditional beliefs with health education from clinics. Figure 4.2 Thematic map of community perspectives on dietary diversity among maternal and general populations 85 4.4 Interpretation 4.4.1 Summary of findings in comparison to the literature This research in three sub-Saharan African countries found that dietary diversity was well aligned with community members’ understanding of healthy meals. Dietary diversity was seen to be particularly valuable for pregnant and lactating mothers to prevent anemia and support healthy infant growth. In contrast to a previous study among farming households where dietary diversity was seen largely to promote the appeal of meals and increase appetite rather than for nutritive value (299), participants in this study frequently emphasized the importance of diverse diets to provide “vitamins”, likely building on maternal and child health education. Consequently, there may be heightened awareness about the importance of dietary diversity especially for pregnant and lactating mothers, yet community members reflected on significant barriers. Participants indicated limited accessibility due to a complex interplay of affordability, seasonality, gender norms, local knowledge and preferences. While dietary diversity was highly meaningful within local conceptualizations of meals hierarchies in the prioritization of various foods challenged the capacity for diverse maternal diets. High energy staples of lower nutritive value were prioritized as fundamental components of meals, in comparison to costly nutritious foods like fruit, eggs, meat and out-of-season vegetables. Affordability and seasonality were widely described as key challenges to the practice of dietary diverse meals, as was also found in Tanzania (299), Uganda (301), and Nigeria (302). Participants in our study highlighted that challenges with affordability limited the types of foods that households could access, rather than necessarily equated with hunger. This aligns with 86 research reporting fewer types of foods consumed with increasing food insecurity (307,308) and that food insecurity did not equate to lower energy intakes (309). Two large systematic reviews found that increasing food prices or falling income due to job instability created pressure to purchase foods that are lowest in cost, particularly in economically disadvantaged settings and incomes (310,311). Participants in this study highlighted an increasing emphasis on cash, which may reflect demographic and nutritional transitions in rural sub-Saharan Africa. Previous studies emphasized agriculture as the mainstay economic activity for rural sub-Saharan African households (300) and highlighted diversity in household food production for dietary diversity (299,301). However, less than a third of those interviewed here reported farming as their primary livelihood activity and rural residence was not described as a major influencing factor due to the growing availability of shops and vendors. The findings presented here align with reports on fast rural population growth in sub-Saharan Africa and its contribution to rapid urbanization, constrained access to farmland, and the growth of non-farming livelihoods even in rural areas (312). Our study reflects emerging findings in the State of Food Security and Nutrition in the World 2023 report of increasing access to a variety of food (including processed foods) in rural and remote global settings and that even rural populations purchase a majority of their food (285). While gender norms have been recognized to influence household nutrition and dietary diversity practices (301,313–316), a growing dependence on cash may shift household gender dynamics to further disadvantage diverse maternal diets. Because rural women are traditionally in charge of food crops for household consumption while men are more likely responsible for decisions regarding cash crops and other sources of income (300), an increased reliance on money may 87 deepen dependency on men as primary household providers and decision-makers for food and other essentials. A study from Nigeria found that women often required permission before purchasing costly food items (302), which may include nutrient dense foods during pregnancy and lactation. 4.4.2 Implications for research and policy Dietary diversity recommendations during pregnancy resonate with local knowledge about healthy eating, which supports nutrition counselling during antenatal care. However, this research highlights the contribution of gender norms and family dynamics to maternal diets, with a complex interplay between the types of food women wanted during pregnancy and lactation, economic constraints, gender roles, and knowledge. These findings support the need for further research and policies to engage men in maternal nutrition education (317,318) and the economic empowerment of women (302,316,319–321). While women’s empowerment has been shown to improve dietary diversity among children (322,323), women’s empowerment is often described within a limiting lens of helping women better care for their children within the First 1000 Days approach to nutrition; again, this is an influential movement that emphasizes the importance of early life nutrition for child survival, growth and development (60). Within a Human Rights Based Approach that emphasizes the intrinsic value and equal dignity of women, adequate nutrition during pregnancy and lactation is part of the Right to Health enshrined in the Convention on the Elimination of All Forms of Discrimination Against Women (CEDAW Article 12.2) (63). Study findings reaffirm the call of CEDAW Articles 11 and 13 to strengthen women’s rights to employment and economic and social activities, as well as to engage women, men, and community leaders to work together to 88 eliminate "prejudices and customary and all other practices which are based on the idea of the inferiority or the superiority of either of the sexes or on stereotyped roles for men and women" (CEDAW Article 5) (63). Engaging men and communities in maternal nutrition education may be a pathway towards the modification of discriminatory social and cultural patterns. Additionally, local conceptualizations of more ingredients equating to healthier meals is complicated by the surge of processed foods in sub-Saharan Africa even in rural communities (285,324–326). There is a concern that higher dietary diversity may be associated with more frequent consumption of low nutrient-dense foods (327–330) and more research is needed to understand dietary diversity in sub-Saharan Africa with the local context to ensure optimal dietary counselling. The emphasis on cash to purchase foods, increased availability of food products even in rural areas, and concerns about irregular weather patterns highlights the need for further research on determinants of diet diversity within global food system transitions (331), climate change and sustainable food systems (332). 4.4.3 Strengths and limitations Strengths of this study include prolonged engagement with multiple qualitative methods for researchers to become more familiar with the setting and context, utilization of a reporting checklist to ensure dependability, use of a clear coding framework, and engagement of local and international field experts in analysis, and interpretation to support confirmability. Based on the discussions of trustworthiness in qualitative research by Lincoln and Guba, data triangulation with multiple data sources across various spaces and persons support the credibility of findings (96,333,334). Our research in three countries and multiple population groups strengthened our capacity to explore overarching common themes and topic areas where each location may be 89 unique. A limitation of our study was the focus on interview data in analysis, with other qualitative methodologies were utilized to confirm data saturation and key themes. Consequently, findings from photovoice and participant observation were not fully covered in the current chapter. Furthermore, understanding community perspectives of the impact of food systems and public policies was not well elucidated in the study and represents a limitation in this research. Other limitations include potential sampling bias, as participants were recruited from PRECISE study communities where they may be more familiar with research compared to other populations, and observation bias, when people behave differently when they know they are observed. Observation bias is especially a challenge with short periods of participant observation. Our study attempted to mitigate observation bias through detailed discussions during the informed consent process to emphasize how researchers wanted to experience typical meals and food provisioning activities, but there was potential that some observation bias remained. Researchers’ positionality can also exert influence on the data collected and interpretations of findings. For example, participants may feel less comfortable to openly share perspectives with a foreign researcher, female participants may feel less comfortable to discuss maternal health and diet concerns with male data collectors, or conversely share less with female data collectors whom they assume to have similar perspectives and experiences. My outsider position as a foreign researcher may have been partly mitigated by my insider position as a woman and a mother. The influence of insider/outsider positionality characteristics were also partly mitigated through investigator triangulation, which included the utilization of data collectors of both genders, regular debriefs with data collectors to ensure data consistency and elicit preliminary emergent themes, and discussions with qualitative experts, clinician-scientists and project coordinators from each country in the development of the qualitative methodology, 90 coding framework and interpretation of findings. Investigator triangulation using two or more researchers to make coding, analysis and interpretation decisions supports credibility of findings (96,333,334). 4.5 Conclusion Our research in Kenya, Mozambique and The Gambia found that meals were predominantly grain-based, typically served with a sauce made from leafy greens, beans, or small local fish. Dietary diversity was considered especially important for maternal diets but meals for pregnant and lactating mothers were usually similar to their households. Adequate nutrition knowledge and accessibility are both needed to ensure women have adequate diverse maternal diets. More research is needed on adequate maternal diets within the context of nutritional transitions. 91 Chapter 5: Prevalence and associated factors of meeting minimum dietary diversity among pregnant and non-pregnant women of reproductive age in three sub-Saharan African countries 5.1 Introduction An estimated 262 million people in sub-Saharan Africa were undernourished in 2022, equating to 22.5% of the population, with higher rates in East Africa (28.5%) compared to West (14.6%) and Southern Africa (11.1%) (285). All WRA are vulnerable to gender inequities in poverty. For WRA who become pregnant, they are doubly burdened with higher nutritional requirements during pregnancy and lactation (286,335,336). Previous qualitative work in Kenya, Mozambique and The Gambia found that community members identified diverse dietary patterns as nutritious for pregnant women but described barriers in practice (see Chapter 4). Eating a variety of foods is a key component of diet quality and higher dietary diversity is associated with better micronutrient adequacy (337–339). Almost all micronutrients must be obtained from the diet and are critical to human health and development, particularly during pregnancy where micronutrient deficiencies have been associated with pregnancy loss, preterm delivery, small birth size, birth defects and metabolic abnormalities (287). The MDD-W indicator summarizes micronutrient adequacy among WRA (33,34). Assessments among pregnant and non-pregnant WRA in sub-Saharan Africa have reported low dietary diversity, with rates of meeting MDD-W typically between 20-50% of the population (300,307,315,340–345), though some report as low as 2.8% (40). However, representiveness of the evidence is challenged by limited coverage across sub-Saharan Africa with a majority of 92 studies conducted in Ethiopia (315,342,344,346,347) and fewer studies from Southern (307,341) and Western Africa (343,348). Many employed cross-sectional study designs (300,315,340,341,344,345,347,348) and did not perform multivariable analyses (40,307,315,342,343). The objective of this study was to assess the prevalence of meeting MDD-W among women enrolled in the PRECISE Network prospective cohort study in Kenya, Mozambique and The Gambia and explore potential factors associated with meeting MDD-W. 5.2 Methods 5.2.1 Study design, setting, and participants This study is part of the PRECISE Network prospective cohort study, conducted between June 2019 and December 2022 in Kenya, Mozambique and The Gambia (74). PRECISE primarily recruited pregnant women presenting at health facilities in each of the rural and periurban study sites, with a smaller sample of non-pregnant WRA presenting at the same health facilities recruited. 5.2.2 Study variables and outcome Correlates explored in this study were drawn a literature review of dietary diversity studies from sub-Saharan Africa. Correlates from the literature review that were available in the PRECISE Network database included age (40,315,340,341), rural residency (307,343), parity (344), woman’s educational status (40,315,340,342–344,349–351), women’s occupation/employment status (351), women’s autonomy in decision-making (315,349), gender of household head (340,341,344,347,348) and household size (333,334,337,340,341). Additionally, correlates investigated were informed by qualitative research within study communities (see Chapter 4) and community perceptions on factors that influenced maternal dietary diversity, including PRECISE 93 Network indicators for socio-economic status (women’s education and occupation), women’s autonomy (decision-making for household spending), and household composition (gender of primary decision-maker for household spending, living arrangements and household size). Knowledge of healthy foods during pregnancy and seasonality were not available in the PRECISE database. Country, cohort status, and rural/periurban residence were categorical variables based on the health facility women were recruited into the PRECISE cohort. Age, parity and household size were continuous variables, while marital status, highest educational level attained, occupation, decision-making about household spending, primary household decision-maker, and living arrangements were categorical variables self-reported by women in PRECISE surveys. The primary study outcome was meeting MDD-W, based on the DDS. The DDS is a count of the MDD-W main food groups that a woman has consumed during the previous 24 hours. There areten MDD-W main food groups: (i) grains, white roots and tubers, and plantains, (ii) pulses, (iii) nuts and seeds, (iv) milk and milk products, (v) meat, poultry and fish, (vi) eggs, (vii) dark green leafy vegetables, (viii) other vitamin A-rich fruits and vegetables, (ix) other vegetables, and (x) other fruits. The DDS ranges from 0 (no food groups consumed) to 10 (all food groups consumed). Meeting minimum dietary diversity for women is defined as consuming at least five of the ten healthy food groups in the previous 24 hours (minimum DDS of 5) (35). 5.2.3 Data collection and analysis Trained data collectors administered face-to-face PRECISE Network surveys after obtaining written informed consent, which included collecting demographics, dietary data, and medical histories over four visits during gestation and postpartum. For the assessment of MDD-W, 94 women responded yes or no to consuming local foods corresponding to ten food groups in the previous 24 hours (35). Descriptive statistics summarized demographic characteristics, DDS, and the proportions of pregnant and non-pregnant WRA in the PRECISE cohort that met MDD-W by country and overall. As an ordinal food group diversity score (32,34), median DDS along with interquartile ranges (IQR) were reported. Multivariable regression models were performed to evaluate determinants of meeting MDD-W reported as odds ratios (ORs) with their corresponding 95% confidence intervals. Covariables in the model were based on qualitative research in PRECISE communities (see Chapter 4 of the Dissertation), a literature review (Table E.1) and model fit was evaluated using the Akaike Information Criterion (AIC) (Table E.2). Multicollinearity was assessed using variance inflation factor (VIF), with VIF values above 5 removed from the model (352). No variables were removed due to multicollinearity. The final model adjusted for basic demographics (country of residence, pregnant/non-pregnant status, rural/periurban residence, age at enrollment, parity, marital status), socio-economic status (highest education attained and occupation), women’s autonomy (decision-making for household spending), and household composition (gender of primary decision-maker for household spending, living arrangements and household size). All demographic characteristics were self-reported. All analyses were performed on R Studio (version 4.2.3). 5.3 Results 5.3.1 Participant characteristics Of the 8757 women from PRECISE, there were 7715 women with complete dietary data and 1042 women excluded due to incomplete data (Figure 5.1). Of the 7715 women included, there 95 were 3209 from Kenya, 2660 from Mozambique, and 1846 from The Gambia. There were 1549 non-pregnant women of reproductive age and 6166 pregnant women included in the analyses; their demographic characteristics are reported in Table 5.1. Figure 5.1 Profile of PRECISE participants in the nutrition analyses Table 5.1 Demographics of PRECISE participants included in nutrition analyses Kenya (n=3209) Mozambique (n=2660) The Gambia (n=1846) Total (n=7715) Cohort Non-pregnant 353 (11%) 594 (22%) 602 (33%) 1549 (20%) Pregnant 2856 (89%) 2066 (78%) 1244 (67%) 6166 (80%) Residence Rural 1408 (44%) 864 (32%) 990 (54%) 3262 (42%) Periurban 1801 (56%) 1796 (68%) 854 (46%) 4451 (58%) Missing 0 (0%) 0 (0%) 2 (<1%) 2 (<1%) Age Median [IQR] 26 yrs [23, 31] 24 yrs [20, 30] 27 yrs [22, 32] 26 yrs [21, 31] Range 16 to 49 yrs 15 to 49 yrs 16 to 49 yrs 15 to 49 yrs 15-19 years 211 (7%) 599 (23%) 221 (12%) 1031 (13%) 20-24 years 989 (31%) 757 (28%) 475 (26%) 2221 (29%) 96 25-34 years 1587 (49%) 968 (36%) 789 (43%) 3344 (43%) ≥35 years 421 (13%) 336 (13%) 346 (19%) 1103 (14%) Missing 1 (<1%) 0 (0%) 15 (1%) 16 (<1%) Parity Median [IQR] 1 [0,3] 1 [0,3] 2 [1,5] 1 [0,3] Range 0 to 12 0 to 8 0 to 14 0 to 14 0 previous births 844 (26%) 882 (33%) 407 (22%) 2133 (28%) 1-4 previous births 2080 (65%) 1637 (62%) 968 (52%) 4685 (61%) 5 or more previous births 285 (9%) 141 (5%) 471 (26%) 897 (12%) Marital status Single 225 (7%) 1177 (44%) 118 (6%) 1520 (20%) Married/Co-habiting 2703 (84%) 1450 (55%) 1078 (58%) 5231 (68%) Polygamous marriage 200 (6%) 5 (<1%) 628 (34%) 833 (11%) Separated/Divorced/Widowed 81 (3%) 28 (1%) 22 (1%) 131 (2%) Socio-economic status Highest school level attended None 307 (10%) 172 (6%) 1163 (63%) 1642 (21%) Primary school 1681 (52%) 952 (36%) 265 (14%) 2898 (38%) Secondary school 826 (26%) 1507 (57%) 314 (17%) 2647 (34%) Higher education 395 (12%) 29 (1%) 104 (6%) 528 (7%) Occupation Housewife 1742 (54%) 1857 (70%) 1541 (83%) 5140 (67%) Student 69 (2%) 411 (15%) 73 (4%) 553 (7%) Market trader 319 (10%) 166 (6%) 73 (4%) 558 (7%) Laborer (factory, large scale agriculture, construction) 55 (2%) 53 (2%) 15(1%) 123 (2%) Professional 164 (5%) 79 (3%) 36 (2%) 279 (4%) Other/ Missing 860 (27%) 94 (4%) 108 (6%) 1062 (14%) Women’s autonomy Decision-maker for pregnancy care Husband/Partner 1885 (59%) 1501 (56%) 1086 (59%) 4472 (58%) Father/Father-in-law 43 (1%) 135 (5%) 30 (2%) 208 (3%) Mother/Mother-in-law 116 (4%) 219 (8%) 86 (5%) 421 (5%) Participant 819 (26%) 118 (7%) 21 (1%) 1028 (13%) Other/ Missing 346 (11%) 617 (23%) 623 (34%) 1586 (21%) Decision-maker for household spending Husband/Partner 2289 (71%) 1473 (55%) 1380 (75%) 5142 (67%) Father/Father-in-law 100 (3%) 452 (17%) 237 (13%) 789 (10%) Mother/Mother-in-law 127 (4%) 366 (14%) 92 (5%) 585 (8%) Participant 633 (20%) 282 (11%) 25 (1%) 940 (12%) Other / Missing 60 (2%) 87 (3%) 112 (6%) 259 (3%) Women’s autonomy for decision-making in household spending No 2576 (80%) 2378 (89%) 1821 (99%) 6775 (88%) Yes 633 (20%) 282 (11%) 25 (1%) 940 (12%) 97 Household composition Gender of household money decision-makerMale headed household* 2414 (75%) 1967 (74%) 1716 (93%) 6097 (79%) Female headed household† 782 (24%) 683 (26%) 125 (7%) 1590 (21%) Not sure 113(<1%) 10 (<1%) 5 (<1%) 28 (<1%) Living arrangements Lives alone 182 (6%) 74 (3%) 129 (7%) 385 (5%) Lives with husband or partner 2005 (62%) 1189 (45%) 407 (22%) 3601 (47%) Extended household with in-laws 627 (20%) 475 (18%) 1026 (56%) 2128 (28%) Lives with parents or relatives 126 (8%) 733 (28%) 250 (14%) 1252 (16%) Other 126 (4%) 189 (7%) 34 (2%) 349 (5%) Household size Median [IQR] 4 [3,6] 5 [4,7] 9 [7,9] 5 [3,9] Range 1 to 9 people 1 to 9 people 1 to 9 people 1 to 9 people Small household (1-3 people) 1327 (41%) 634 (24%) 96 (5%) 2057 (27%) Medium household (4-6 people) 1172 (37%) 1319 (50%) 275 (15%) 2766 (36%) Large household (7-9 people) 710 (22%) 704 (26%) 1475 (80%) 2889 (37%) Missing 0 (0%) 3 (<1%) 0 (0%) 3 (<1%) IQR – interquartile range; yrs – years * Male headed household defined by household decision-maker for money as husband, male partner, father, father-in-law, brother or brother-in-law† Female headed household defined by household decision-maker for money as mother, mother-in-law, sister, sister-in-law, or participant herself5.3.2 Dietary diversity Women in the PRECISE cohort had a median DDS of four [IQR 3, 6], with the full range from zero to ten food groups reported. Overall, 47.7% across the cohort met MDD-W, including 45.0% of women from Kenya, 39.2% of women from Mozambique, and 65.1% from The Gambia (Table 5.2). Pregnant and non-pregnant women both had a median DDS of four [IQR 3, 6], but pregnant women had a slightly higher proportion of meeting MDD-W (48.4% pregnant vs 45.6% non-pregnant). 98 Table 5.2 Dietary diversity scores and prevalence of meeting minimum dietary diversity for women Dietary diversity score (median [IQR]) Met minimum dietary diversity No (<5 DDS) Yes (≥5 DDS) Total (n=7715) 4 (IQR 3, 6) 4026 (52%) 3689 (48%) Country Kenya (n=3209) 4 (IQR 3, 6) 1764 (55%) 1445 (45%) Mozambique (n=2660) 4 (IQR 3, 6) 1617 (61%) 1043 (39%) The Gambia (n=1846) 5 (IQR 4, 6) 645 (35%) 1201 (65%) Cohort Non-pregnant (n=1549) 4 (IQR 3, 6) 843 (54%) 706 (46%) Pregnant (n=6166) 4 (IQR 3, 6) 3183 (52%) 2983 (48%) Residence Rural (n=3262) 5 (IQR 3, 6) 1604 (49%) 1658 (51%) Periurban (n=4451) 4 (IQR 3, 6) 2420 (54%) 2031 (46%) Age 15-19 years (n=1031) 4 (IQR 3, 6) 581 (56%) 450 (44%) 20-24 years (n=2221) 4 (IQR 3, 6) 1169 (53%) 1052 (47%) 25-34 years (n=3344) 4 (IQR 3, 6) 1705 (51%) 1639 (49%) ≥35 years (n=1103) 4 (IQR 3, 6) 565 (51%) 538 (49%) Parity 0 (n=2133) 4 (IQR 3, 6) 1139 (53%) 994 (47%) 1-4 (n=4685) 4 (IQR 3, 6) 2446 (52%) 2239 (48%) 5 or more (n=897) 5 (IQR 3, 6) 441 (49%) 456 (51%) Marital status Single (n=1520) 4 (IQR 3, 6) 837 (55%) 683 (45%) Married/Co-habiting (n=5231) 4 (IQR 3, 6) 2770 (53%) 2461 (47%) Polygamous marriage (n=833) 5 (IQR 4, 6) 344 (41%) 489 (59%) Separated/Divorced/Widowed (n=131) 4 (IQR 3, 6) 75 (57%) 56 (43%) Education None (n=1642) 5 (IQR 3, 6) 714 (43%) 928 (57%) Primary school (n=2898) 4 (IQR 3, 5) 1732 (60%) 1166 (40%) Secondary school (n=2647) 4 (IQR 3, 6) 1392 (53%) 1255 (47%) Higher education (n=528) 5 (IQR 4, 6) 188 (36%) 340 (64%) Occupation Housewife (n=5140) 4 (IQR 3, 6) 2759 (54%) 2381 (46%) Student (n=553) 4 (IQR 3, 6) 300 (54%) 253 (46%) Market trader (n=558) 4 (IQR 3, 6) 312 (56%) 246 (44%) Laborer (n=123) 5 (IQR 3, 6) 56 (46%) 67 (54%) Professional (n=279) 5 (IQR 4, 6) 117 (42%) 162 (58%) Women’s autonomy for decision-making about household spending No (n=6775) 4 (IQR 3, 6) 3504 (52%) 3271 (48%) 99 Yes (n=940) 4 (IQR 3, 6) 522 (56%) 418 (44%) Gender of primary household decision-maker Male (n=6097) 4 (IQR 3, 6) 3122 (51%) 2975 (49%) Female (n=1590) 4 (IQR 3, 6) 896 (56%) 694 (44%) Living arrangements Lives alone (n=385) 5 (IQR 3, 6) 176 (46%) 209 (54%) Husband or partner (n=3601) 4 (IQR 3, 6) 1918 (53%) 1683 (47%) Extended household with in-laws (n=2128) 5 (IQR 3, 6) 1033 (49%) 1095 (51%) Natal parents or relatives (n=1252) 4 (IQR 3, 6) 688 (55%) 564 (45%) Household size Small household (n=2057) 4 (IQR 3, 6) 1063 (52%) 994 (48%) Medium household (n=2766) 4 (IQR 3, 6) 1597 (58%) 1169 (42%) Large household (n=2889) 5 (IQR 3, 6) 1365 (47%) 1524 (53%) DDS – dietary diversity score; IQR – interquartile range; SD – standard deviation 5.3.3 Correlates of meeting minimum dietary diversity In multivariable analyses, country of residence was a significant determinant of meeting MDD-W (Table 5.3). There was no significant difference between Kenyan and Mozambican women in the rate of meeting MDD-W, but Gambian women had increased odds of meeting MDD-W (aOR 3.13, 95% CI: 2.64-3.71) in comparison to Kenyan women. Overall, pregnant women across the PRECISE cohort had higher 42% higher odds of minimum dietary diversity compared to non-pregnant women of reproductive age (aOR 1.42, 95% CI: 1.25-1.61) as did parous women with one to four previous births compared to nulliparous women (aOR 1.18, 95% CI: 1.03-1.36). Parous women with five or more previous births did not significantly vary from nulliparous women. Age was not found to be significantly associated with meeting MDD-W. Women with secondary or post-secondary education had significantly higher odds of meeting MDD-W compared to women with no formal education (secondary school aOR 1.28, 95% CI:100 1.09-1.51); higher education aOR 2.01, 95% CI: 1.57-2.58). Women with primary education did not significantly vary from women with no education. Paid employment as a labourer (aOR 1.68, 95% CI: 1.15-2.45) or professional (aOR 1.35, 95% CI: 1.03-1.77) was associated with higher odds of meeting MDD-W. Informal work as a market trader or being a student did not significantly vary from women who reported being housewives. Lower odds of meeting MDD-W was associated with women with a periurban residence compared with rural residence (aOR 0.84, 95% CI: 0.77-0.93) and residing with natal parents or relatives compared to living with a husband or partner (aOR 0.77, 95% CI: 0.63-0.95). Compared to small households, medium-sized households also had lower odds of meeting MDD-W(aOR 0.85, 95% CI: 0.75-0.97). Women’s autonomy in decision-making for household purchases and the gender of the primary household decision-maker were not significantly associated with MDD-W status. Table 5.3 Correlates of meeting minimum dietary diversity for women Unadjusted odds ratios (95% CI) Adjusted odds ratios* (95% CI) Country Kenya ref ref Mozambique OR 0.79 (0.71-0.87)† aOR 0.88 (0.77-1.00) The Gambia OR 2.27 (2.02-2.56) † aOR 3.13 (2.64-3.71) † Cohort Non-pregnant ref ref Pregnant OR 1.12 (1.00-1.25) † aOR 1.42 (1.25-1.61) † Residence Rural ref ref Periurban OR 0.81 (0.74-0.89) † aOR 0.84 (0.77-0.93) † Age 15-19 years OR 0.81 (0.70-0.93) † aOR 0.90 (0.75-1.08) 20-24 years OR 0.94 (0.84-1.04) aOR 0.98 (0.86-1.11) 25-34 years ref ref ≥35 years OR 0.99 (0.86-1.14) aOR 1.06 (0.91-1.24) 101 Parity 0 previous births ref ref 1-4 previous births OR 1.05 (0.95-1.16) aOR 1.18 (1.03-1.36) † 5 or more previous births OR 1.18 (1.01-1.39)† aOR 1.06 (0.85-1.32) Marital status Single OR 0.92 (0.82-1.03) aOR 1.51 (1.25-1.81) † Married/Co-habiting ref ref Polygamous marriage OR 1.60 (1.38-1.86) † aOR 0.96 (0.81-1.14) Separated/Divorced/Widowed OR 0.84 (0.59-1.19) aOR 1.14 (0.76-1.69) Education None ref ref Primary school OR 0.52 (0.46-0.59) † aOR 0.93 (0.80-1.09) Secondary school OR 0.69 (0.61-0.79) † aOR 1.28 (1.09-1.51) † Higher education OR 1.39 (1.14-1.71) † aOR 2.01 (1.57-2.58) † Occupation Housewife ref ref Student OR 0.98 (0.82-1.17) aOR 1.12 (0.91-1.38) Market trader OR 0.91 (0.77-1.09) aOR 1.05 (0.87-1.27) Laborer OR 1.39 (0.97-1.99) aOR 1.68 (1.15-2.45) † Professional OR 1.60 (1.26-2.05) † aOR 1.35 (1.03-1.77) † Women’s autonomy for decision-making on household spending No ref ref Yes OR 0.86 (0.75-0.98) † aOR 1.07 (0.85-1.35) Gender of primary household decision-maker Male-headed household ref ref Female-headed household OR 0.81 (0.73-0.91) aOR 0.89 (0.73-1.08) Living arrangements Lives alone OR 1.35 (1.10-1.67) † aOR 0.91 (0.72-1.15) Husband or partner ref ref Lives with in-laws OR 1.21 (1.09-1.34) † aOR 0.90 (0.78-1.03) Natal parents or relatives OR 0.93 (0.82-1.06) aOR 0.77 (0.63-0.95) † Household size Small household ref ref Medium household OR 0.78 (0.70-0.88) † aOR 0.85 (0.75-0.97) † Large household OR 1.19 (1.07-1.34) aOR 0.91 (0.78-1.06) aOR – adjusted odds ratio; OR – odds ratio; ref – reference category *Adjusted for basic demographics (country, cohort, residency, age, parity, marital status), social-economic status (education and occupation), women’s autonomy (decision-making), and household composition (gender of primary household decision-maker, living arrangements, household size) † p <0.05 102 5.4 Discussion The majority of women in the PRECISE cohort did not meet minimum dietary diversity for women. Sub-optimal prevelance of meeting MDD-W among non-pregnant women suggests that many women are not starting their pregnancies with adequate micronutrient status. While being pregnant was associated with higher odds of adequate dietary diversity, continued sub-optimal prevelance of achieving MDD among pregnant women highlights that dietary diversity does not substantially improve during pregnancy. However, there was a range in dietary diversity scores highlighting variation within the population and the importance of understanding determinants of dietary diversity, especially socio-economic indicators. 5.4.1 Comparison with the literature Our overall prevelance of meeting MDD-W at 47.7% of women in the PRECISE cohort is in line with a systematic review from Ethiopia that found a pooled rate of 41% (342). Higher prevalence of meeting MDD-W among Gambian women likely drove the overall higher rates in the PRECISE cohort, which aligns with regional differences in undernourishment reported in the 2023 The State of Food Security and Nutrition in the World report (285). Table 5.4 summarizes dietary diversity correlates from PRECISE in comparison with 17 other studies of dietary diversity among pregnant or non-pregnant women of reproductive age from sub-Saharan Africa (see Table E.1 for other studies’ details). Our study adds to the literature by highlighting regional variability in dietary diversity status across Western, Eastern and Southern Africa, collected by the same dietary assessment methodology, and that pregnancy status was positively associated with meeting MDD-W. While previous studies have examined urban compared to rural residency (307,343), our findings highlight heightened risk of inadequate 103 dietary diversity in periurban areas, where recent reports have noted food insecurity challenges (285,353). An emphasis on access to agricultural resources found in studies conducted in rural areas with largely subsistence farming households (300,341,346) may not fully represent experiences of vulnerable periurban households. Women’s education and occupationemerged as strong influencing factors of dietary diversity after controlling for other variables. A larger effect size for higher education compared to secondary education in our study may indicate a potential dose response of women’s education. Other studies from sub-Saharan Africa also found women’s education (40,315,340,342–344,349–351) and occupation (351), and household income or wealth ranking (40,307,341,342,344,347–351) to be positively associated with higher dietary diversity among women; however, definitions varied between studies. Higher or richest household income or wealth ranking were also frequently found to be strong correlates of higher dietary diversity across settings, while middle- compared to low-income or wealth ranking were frequently found to be not significantly associated (40,307,341,342,347–351,354–359). Perhaps due to various occupational categories being compared, some found a significant association between women’s employment status and higher dietary diversity (351,359) and others not (343,345,349,356,357,360,361). Overall, women’s paid employment appears to be associated with higher dietary diversity, whereas informal work may not significantly vary from being a housewife or unemployed (351,359), similar to the findings presented here. However, employment status may be contextual to local gender norms and practices; for example, being a housewife had a higher social status compared to being a labourer from an Indian study (358). While socio-economic indicators were strongly associated with dietary diversity among women, 104 variations in measurement and implications of educational and wealth hierarchies within different contexts may contribute to the heterogeneity in findings across the literature. Other major determinants of dietary diversity among women from sub-Saharan African studies included smaller household size (340,341,344,347,348), which was also found in our study, and women’s nutrition knowledge (315,342,345,350), which was not quantitatively explored in our study. Previous PRECISE qualitative research found community knowledge of dietary diversity and its value during pregnancy (see Chapter 4 in this Dissertation). However, the practice of dietary diversity was constrained by affordability and household gender dynamics in decision-making. Perhaps due to systematic gender inequities that may disadvantage female-headed households within patriarchal societies (362), we did not find significant associations for women’s autonomy or gender of household primary decision-maker on meeting MDD-W. Previous studies of indicators of women’s empowerment have been mixed with reports of significant (315,349,359) and non-significant associations with dietary diversity (321,354,357). Gender of household head in previous studies have either favoured male-headed households (300,340) or reported non-significant associations with women’s dietary diversity (341,349,351,359). The overall low rates in our study communities raises reflection on whether women’s autonomy decision-making may indicate an absentee husband or partner. Our study found that women residing with their natal parents or relatives had a lower likelihood of meeting MDD-W, which has not been previously evaluated as a determinant of MDD-W to the best ofour knowledge. The counter-intuitive finding that single status was beneficial appears to be largely driven by women from Mozambique, where many men in the region migrate to South 105 Africa for work, and single and separated women from rural Southern Mozambique have high rates of engaging in paid employment (363). Table 5.4 Correlates of higher dietary diversity from the PRECISE cohort compared to other dietary diversity studies from sub-Saharan Africa Determinants PRECISE cohort Other studies Country of residence ✔ NA Pregnancy status ✔ NA Periurban residency (vs rural)* ✔ NA Urban residency (vs rural) NA (307,343) Older maternal/women’s age NS (40,315,340,341) Parous (vs nulliparity) ✔ (344) Single status (vs married) ✔ NA Polygamous marriage* NS (349) Socio-economic status Women’s education ✔ (40,315,340,342–344,349–351) Women’s occupation/ employment ✔ (351) Husband or partner's education/occupation NA (315,347,350) Household wealth ranking/ income NA (40,307,341,342,344,347–351) Women’s autonomy Women’s autonomy/ decision-making NS (315,349) Household composition Male-headed household NS (300,340) Lives with natal parents or relatives (vs husband/partner)* ✔ NA Smaller household size ✔ (340,341,344,347,348) Other Women’s knowledge about nutrition and/or dietary diversity NA (315,342,345,350) Agricultural resources (land, livestock, crops grown, participation in agricultural development project) NA (300,341,346) NA – not available; NS – not significant *As a risk factor106 5.4.2 Strengths and limitations The current analysis utilized the standardized MDD-W instrument, which has been validated in resource-limited settings, and included non-pregnant women of reproductive age and pregnant women from the same communities and time-period in the study cohort to enable comparisons between the two groups. Dietary assessments were conducted across the three countries with women over the span of two and a half years with a large sample size. Strengths include the use of culturally-adapted food lists and reduced potential recall bias in the 24-hour recall method compared to other food frequency questionnaires that request recall over longer periods of time. However, dietary data were collected at one time point from each woman, which heightens concern for potential seasonal bias as some foods may vary by season and represents a key study limitation that warrants further research to confirm findings. Certain indicators were unavailable in the PRECISE dataset, including seasonality, husband/partners’ education or occupation, women’s nutrition knowledge and agricultural resources, and the complexity of women’s autonomy and gender equity may not be adequately captured in our study. The potential for residual confounding from unmeasured or inadequately measured variables is particularly a concern for smaller effect sizes (RR<2.0) (364), which represents most of the associations in our study. Due to self-reported dietary data, there is potential for measurement error from social desirability bias where participants report consuming food items they understand to be healthy. Previous qualitative research in study communities (see Chapter 4) documented local knowledge about the benefits of dietary diversity and green leafy vegetables, fruits and meat during pregnancy, which may lead to overestimating these food groups and overall dietary diversity. Over-reporting of beans and peas, dark green leafy vegetables, vitamin A-rich fruit and vegetables, and other fruits has been previously documented with the MDD-W tool (365). 107 Furthermore, PRECISE recruited women from a single region in each country and is not nationally representative. Analyses do not consider potential regional differences within countries, which may limit external validity and the generalizability of study findings. 5.5 Conclusion Our assessment found 52.3% of women in the PRECISE cohort across Kenya, Mozambique and The Gambia did not meet MDD-W, suggesting sub-optimal micronutrient adequacy among these populations. Our findings highlight important differences between the African regions studied, such as Western Africa compared to Eastern and Southern Africa; and, within populations including by pregnant status, marital status, household composition, education and occupation, that warrant further investigation. While socio-economic factors emerged as overall key determinants of dietary diversity both in our study and across the literature, factors need to be contextualized to local settings, norms and practices. 108 Chapter 6: Characterizing dietary diversity patterns among pregnant women in Kenya, Mozambique and The Gambia: A mixed methods latent class analysis and qualitative content analysis 6.1 Introduction Inadequate nutritional intake during pregnancy contributes to adverse health outcomes (291,366–369). Dietary diversity supports adequate micronutrient status, with more food groups consumed associated with higher micronutrient intake. However, a growing body of research finds low dietary diversity among women in resource-limited countries, particularly in sub-Saharan Africa (32,40,307,340,342) including 52.3% of 7715 pregnant and non-pregnant WRA in the PRECISE cohort across Kenya, Mozambique and The Gambia who did not meet MDD-W (see Chapter 5 of this Dissertation) MDD-W is a simple but powerful tool for highlighting the proportion of WRA who met or didnot meet minimum dietary diversity to shed light on population-level nutritional inadequacies (33,35), but more is needed to understand underlying dietary patterns. Characterizing food groups emphasized or frequently missed in different dietary patterns can support meaningful knowledge mobilization and consideration of nutritional implications, particularly during pregnancy. Additionally, developing dietary patterns from MDD-W food groups extends the capacity of the tool. Latent class analysis (LCA) is a data-driven, person-oriented method to identify distinct subgroups within a population frequently used in social sciences (370–373). LCA has been used to explore patterns of health behaviours (374–376), with growing application in medicine to 109 identify clinically important patient subgroups (377,378). To date, LCA has not been adequately used to explore dietary patterns and though LCA is a recommended approach to classify dietary subgroups among pregnant women (379), dietary studies with maternal populations using LCA have been limited (380,381). A previous Kenyan study performed LCA on MDD-W food groups to identify dietary patterns distinguished by dietary diversity among school-aged children (382), but has not yet been applied to pregnant women. The purpose of this study was to identify dietary patterns among pregnant women in Kenya, Mozambique and The Gambia using LCA, describe similarities and differences between countries, and their convergence with community perspectives of various food groups. 6.2 Methods 6.2.1 Study design and setting We conducted a convergent mixed methods study comprised of latent class analysis of dietary patterns and qualitative interviews to elicit community perspectives on maternal diets. A convergent mixed methods approach involves separate quantitative and qualitative data collection and integration at the point of interpretation (383). The study is part of the larger PRECISE Network prospective cohort study that recruited pregnant and non-pregnant women of reproductive age from Kenya, Mozambique and The Gambia (74). Women were recruited between June 2019 and December 2022. For the current study on dietary patterns, we included data from pregnant women and excluded non-pregnant women of reproductive age. Qualitative research was conducted between April and October 2022 in the communities serving study hospitals. 110 6.2.2 Quantitative data collection and analysis Data collection as part of PRECISE has been described in detail elsewhere (see Section 1.5.4). Briefly, trained data collectors administered clinical surveys as part of PRECISE, which included demographics, dietary assessment using the MDD-W index and medical histories. The dietary assessment was conducted at the first antenatal visit. The MDD-W included 10 healthy food groups: i) grains, white roots and tubers, and plantains, ii) pulses (beans, peas, and lentils), iii) nuts and seeds, iv) milk and milk products, v) fish, poultry and meat (flesh foods), vi) eggs, vii) dark green leafy vegetables, viii) other vitamin A-rich fruits and vegetables, ix) other vegetables, and x) other fruits. Additionally, there were three unhealthy food groups: i) fried and salty foods (deep-fried foods, packaged salty snacks, take-away/fast food), ii) sweet foods (candy, cake, biscuits), and iii) sweetened beverages (sodas, juices and sweet tea). We tabulated descriptive statistics of food group consumption by country and overall, then conducted LCA to identify dietary patterns by country and assign individuals to their most likely dietary pattern. To characterize dietary patterns, high intake of a food group was classified as consumption by at least 75% of the women and moderate intake as consumption by at least 50% of the women in each country. We fitted models with one to seven latent classes. The best number of patterns to fit was determined based on the Bayesian Information Criterion (BIC) and model characteristics, including number of classes, the size of the smallest class and class separation (378,384–387). For consistency between countries, we selected a similar number of latent classes in final models for each country. LCA was performed using the poLCA package (387) and all other analyses in R Studio (version 4.2.3).111 6.2.3 Qualitative data collection and analysis This study was a secondary analysis of a qualitative dataset collected as part of a larger PRECISE sub-study on community perceptions of maternal diets, of which the methodology was described in Sections 1.5.5 and 4.2. In brief, pregnant and recent mothers who delivered within the past two years, her female and male relatives, and community leaders were purposively sampled and approached by PRECISE study staff to explain the qualitative study. IDIs were facilitated in-person by trained local research assistants using a semi-structured topic guide in the participant’s language of preference. Interviews were digitally recorded with permission, transcribed in verbatim, translated into English by local translation specialists and transcripts uploaded into Nvivo (version R.1) for analysis. Qualitative content analysis was employed using the MDD-W food groups as the coding framework (388) (Table F.1). 6.3 Results 6.3.1 Participant characteristics Of the 8757 total women in PRECISE, there were 7715 with compete dietary data. Of these, there were 6166 pregnant women, including 2856 from Kenya, 2066 from Mozambique, and 1244 from The Gambia. Women had a median age of 25 years, most were parous (69.6%), and a majority (57.2%) had only primary or no formal education. The median BMI was 23.8kg/m2, with an interquartile range of 21.3 to 27.1kg/m2. Participant characteristics are reported by country in Table 6.1 112 Table 6.1 Characteristics of pregnant women in the PRECISE cohort Kenya (n=2856) Mozambique (n=2066) The Gambia (n= 1244) Total (n=6166) Median age [IQR] 26 years [23, 31] 23 years [19, 29] 26 years [22, 31] 25 years [21, 30] Parity (≥1) 2035 (71.3%) 1244 (60.2%) 1010 (81.2%) 4289 (69.6%) Highest education None 273 (9.6%) 107 (5.2%) 794 (63.8%) 1174 (19.0%) Primary 1469 (51.4%) 692 (33.5%) 196 (15.8%) 2357 (38.2%) Secondary 765 (26.8%) 1242 (60.1%) 197 (15.8%) 2204 (35.7%) Post-secondary 349 (12.2%) 25 (1.2%) 57 (4.6%) 431 (7.0%) Median BMI [IQR] 24.2 kg/m2 [21.6, 28.0] 24.2 kg/m2 [22.0, 27.0] 22.0 kg/m2 [19.8, 24.8] 23.8 kg/m2 [21.3, 27.1] BMI – body mass index; IQR – interquartile range 6.3.2 Overall food groups consumed yesterday Figure 6.1 shows grains and white roots, flesh foods, and leafy green vegetables were the most regularly consumed food groups overall. Eggs, nuts and pulses were the least reported consumed, though there was variation between countries. 113 Figure 6.1 Food groups consumed in the previous 24 hours by country and overallAlmost all (93.1%) pregnant women reported consuming grains and white roots in the previous 24 hours (Table 6.2). Flesh foods and dark green leafy vegetables were reported by 62% and 60% of women respectively. Consumption of flesh foods was largely driven by seafood; 44% reported eating seafood yesterday compared 30% for poultry and meat and 16% for organ meats (Table F.2). The least frequently reported healthy food group was eggs, reported by 23% of women. Overall, 87% of women reported consuming at least one type of fruits and vegetables yesterday, with prevelance similar across countries. Almost two-thirds of women also reported consuming unhealthy foods yesterday, with higher prevelance in Kenya and The Gambia compared to Mozambique. Gambian women reported high prevelance of consuming nuts, flesh foods, and other vegetables in comparison to Kenya and Mozambique. Kenyan and Mozambican women more frequently reported consuming dark green leafy vegetables. Kenyan women 114 reported particularly low consumption of nuts and eggs, and Mozambican women were least likely to report milk and milk product consumption. Table 6.2 Food groups consumed in the previous 24 hours by country and overall Kenya (n=2856) Mozambique (n=2066) The Gambia (n= 1244) Total (n=6166) Healthy foods Grains and white roots 2548 (89.2%) 1992 (96.4%) 1198 (96.3%) 5738 (93.1%) Beans, peas & lentils (pulses) 1084 (38.0%) 660 (31.9%) 334 (26.8%) 2078 (33.7%) Nuts 363 (12.7%) 974 (47.1%) 722 (58.0%) 2059 (33.4%) Milk & milk products 1287 (45.1%) 441 (21.3%) 600 (48.2%) 2328 (37.8%) Fish, poultry & meat (flesh foods) 1670 (58.5%) 1124 (54.4%) 1015 (81.6%) 3809 (61.8%) Eggs 465 (16.3%) 642 (31.1%) 316 (25.4%) 1423 (23.1%) Dark green leafy vegetables 1721 (60.3%) 1547 (74.9%) 451 (36.3%) 3719 (60.3%) Other vitamin A fruits & vegetables 1450 (50.8%) 1123 (54.4%) 717 (57.6%) 3290 (53.4%) Other vegetables 811 (28.4%) 609 (29.5%) 727 (58.4%) 2147 (34.8%) Other fruit 1213 (42.5%) 692 (33.5%) 403 (32.4%) 2308 (37.4%) Unhealthy foods Fried & salty foods 1135 (39.7%) 543 (26.3%) 422 (33.9%) 2100 (34.1%) Sweets and bakery goods 1000 (35.0%) 568 (27.5%) 588 (47.3%) 2156 (35.0%) Sweet beverages 1205 (42.2%) 580 (28.1%) 395 (31.8%) 2180 (35.4%) Composite categories Any fruits and vegetables yesterday* 2501 (87.6%) 1801 (87.2%) 1089 (87.5%) 5391 (87.4%) Any unhealthy foods yesterday† 2016 (70.6%) 930 (45.0%) 877 (70.5%) 3823 (62.0%) * Any dark green leafy vegetables, other vitamin A fruits & vegetables, other vegetables, and/or other fruitconsumed in the previous 24 hours† Any fried & salty foods, sweets and bakery goods, and/or sugar added beverages in the previous 24 hours115 6.3.3 Dietary pattern analyses Based on the BIC, there was more diversity in dietary pattern in Mozambique (6 latent classes), compared to Kenya (3 latent classes) and The Gambia (2 latent classes) (Table F.3). In conjunction with model characteristics, we chose the model with three patterns as the final model for classifying dietary patterns among pregnant women in each country. The three dietary patterns were distinguished by food group diversity (most, moderately and least diverse) (Figure 6.2). Figure 6.2 Dietary patterns among pregnant women in Kenya, Mozambique and The Gambia *Vegetables and fruit including leafy green vegetables, other vitamin A-rich fruits and vegetables, other fruits andvegetables. Lower leafy green and other fruit consumption patterns among pregnant women in The Gambia† Lower leafy green consumption patterns in The Gambia‡ Lower nut consumption patterns in Kenya116 6.3.3.1 Kenya Representing 4.6% (n=131) of the pregnant women in our study from Kenya, the most diverse dietary pattern was characterized by high consumption of all food groups except eggs and nuts (Figure 6.3A, see also Table F.4). We found 57.3% (n=1637) had the moderately diverse pattern, which was characterized by high consumption of grains and white roots and moderate consumption of milk, flesh foods, leafy green vegetables, other vitamin A-rich fruits and vegetables, other fruit and sweetened beverages. We found 38.1% (n=1088) had the least diverse pattern, which was characterized by high consumption of grains and white roots only and low consumption of all other food groups. Moderate and least diverse patterns differed from most diverse patterns particularly with beans, nuts, milk, eggs, other vitamin A-rich fruits and vegetables, other fruit and vegetables, and unhealthy foods. 6.3.3.2 Mozambique Representing 15.8% (n=326) of the pregnant women from Mozambique, the most diverse dietary pattern was characterized by high consumption of all food groups (Figure 6.3B, see also Table F.4). We found 31.9% (n=659) had the moderately diverse dietary pattern, which wascharacterized by a high consumption of grains and white roots, and leafy green vegetables, as well as moderate consumption of flesh foods, other vitamin A-rich fruits and vegetables, and other fruit. Over half (52.3%, n=1081) of the Mozambican pregnant women in our study had the least diverse diet, which was characterized by high consumption of grains and white roots and a moderate consumption of leafy green vegetables. Moderate and least diverse patterns differed from most diverse patterns in Mozambique in consumption of beans, nuts, milk, eggs, other vitamin A-rich fruits and vegetables, other fruit and vegetables, and unhealthy foods. 117 6.3.3.3 The Gambia Representing 12.7% (n=158) of the pregnant women from The Gambia, the most diverse dietary pattern was characterized by high consumption of all food groups except moderate consumption of beans, eggs, leafy greens, other fruit, and sweetened beverages (Figure 6.3C, see also Table F.4). About half (50.6%, n=630) had the moderately diverse pattern, which was characterized byhigh consumption of grains and white roots, and flesh foods, as well as moderate consumption of nuts, milk, other vitamin-A fruits and vegetables, other vegetables, and sweets. We found 36.7% (n=456) had the least diverse, which was characterized by high consumption of grains and white roots, and moderate consumption of nuts and flesh foods. In comparison to most diverse patterns, least and moderately diverse patterns differed in consumption of beans, eggs, leafy greens, other fruit and unhealthy foods. 118 Figure 6.3 Dietary diversity patterns identified by latent class analysis in (A) Kenya, (B) Mozambique, and (C) The Gambia 1 – Grains and white roots; 2 - Beans, peas & lentils; 3 – Nuts; 4 – Milk & milk products; 5 – Fish, poultry & meat; 6 – Eggs; 7 – Leafy greens; 8 – Other vitamin A-rich fruits & vegetables; 9 – Other vegetables; 10 – Other fruit; 11 – Fried and salty foods; 12 – Sweets; 13 – Sweetened beverages119 6.3.4 Qualitative results There were 47 interviews conducted across the three countries (18 from Kenya, 14 from Mozambique and 15 from The Gambia). Table 6.3 reports interview participants by country and population group. Main food items described by participants in each food group are reported in Table F.5. Participants distinguished between widely consumed household staples included as part of regular household expenses, luxury that were not budgeted but eaten when there was money or for a special occasion, and certain foods not locally conceptualized as meals. Additionally, community perceptions on salty and fried foods, sugary foods, and sweetened beverages were compiled. A summary of qualitative results are presented in Table F.6. Table 6.3 Interview participants by country and population group Kenya (n=18) Mozambique (n=14) The Gambia (n=15) Total (n=47) Pregnant or recent mother 7 (38.8%) 5 (35.7%) 5 (33.3%) 17 (36.2%) Mother-in-law or sister-in-law 3 (16.7%) 3 (21.4%) 3 (20.0%) 9 (19.1%) Spouse or brother-in-law 4 (22.2%) 3 (21.4%) 3 (20.0%) 10 (21.3%) Community leader 4 (22.2%) 3 (21.4%) 4 (26.7%) 11 (23.4%) 6.3.4.1 Staple foods Participants highlighted grains as a fundamental staple food, including a stiff porridge from maize in Mozambique and Kenya, or a porridge made from millet in The Gambia. All three countries described increasing consumption of bread for breakfast and rice for subsequent meals 120 in the day. Some participants shared that they consumed more staple grains, so food expenses could be reduced. Participants described less frequent consumption of white roots and plantains, as cassava was seasonal and vulnerable to irregular rains, and potatoes and green bananas often needed to be bought and was considered a luxury food item by some “The food that is mostly eaten is ugali (stiff maize meal porridge) made of maize flour” Community leader from Kenya “For us, we depend almost entirely on rice and coos (pearl millet)… We normally cook [coos] porridge in the morning as our breakfast. Rice as lunch and dinner…” Brother-in-law from The Gambia “We eat more xima (stiff maize meal porridge), so the expense of buying food is reduced” Mother-in-law Participants also described fish as a staple food. Kenyan and Mozambican participants in particular highlighted consumption of small fish. In Kenya, small dried fish was often eaten, while fresh fish was very expensive and rarely consumed. In Mozambique, participants distinguished between affordable small freshwater fish with darker flesh and the more preferred horse mackerel, tilapia and other types of fish. “What we often eat as meat is horse mackerel and tilapia fish… They are consumed throughout the year… Fish is our everyday meat” Community leader from Mozambique “Fish is eaten every day. If it is not caught from the river, people bring it for sale and we buy. I can say it is eaten 4 times in a week” Community leader from The Gambia 121 “Due to poverty and not having money, people eat the small fish… There are saltwater fish…[but] they are more expensive than meat… [I]t depends if someone can afford it” Spouse from Kenya Leafy green vegetables and pulses were described as staple foods with irregular consumption due to seasonality and affordability challenges. Leafy green vegetables grew abundantly during rainy season, including wild leafy greens, but required access to gardens or money to purchase during the dry season. Beans were the most commonly eaten pulse across the three countries and participants reported consumption of some cowpeas and lentils. These were highly seasonal when grown and most families had to buy dried beans. Beans were more expensive than green leafy vegetables or small dried fish. Some Kenyan and Mozambican participants described beans as a “drought” food when other vegetables were not available. “We eat greens both wild and the ones we cultivate in our gardens. The wild leaves are mostly available during the rainy season but other greens we cultivate are also available during certain time of the dry season too…” Spouse from The Gambia “When it rains, there are green leafy vegetables and when there is no rain, then we eat sardines… unless you get money to buy beans, but when you do not have enough money to buy beans, then you would buy sardines and fry.” Mother-in-law from Kenya “Now that it doesn't rain, what is cooked frequently is beans… I don't like beans… [but] I can't get something else I can cook at home so I cook...” Pregnant woman from Mozambique 122 6.3.4.2 Luxury foods and special occasion foods Meat, poultry and certain types of fish (i.e. larger fish, fresh fish, saltwater fish), as well as fruits were often highly desired but mostly purchased and considered luxury foods not included in the household budget. Meat typically referred to beef or goat, though also included pork among Mozambican respondents (see Table F.5). Mozambican and Gambian participants highlighted more vendors selling parts (i.e., chicken legs), making it more feasible to eat chicken more regularly. Orange- and dark yellow-fleshed fruits and vegetables high in vitamin A, other vegetables and milk were seasonal, and expensive to purchase out of season. Overall, participants shared that these foods were often eaten only during special occasions for a majority of families in their community. “As of now milk has become expensive. A packet of milk is sold at 80 Ksh (Kenyan Shilling). If I get 100 Ksh and take 80 Ksh to buy milk, I will remain with only 20 Ksh and I have not yet bought sugar or bread. I would rather just buy the sugar and bread.” Mother from Kenya “People perceive meat to be expensive…Mostly it’s during Christmas celebrations, New Year, that’s when you will see people eating chicken but it’s not a common thing to see a person slaughtering a chicken for family to just eat… Meat, if it were affordable, they (people) would… eat every day” Community leader from Kenya “Nowadays it is easy, because chicken is sold in pieces (laughs), the legs are components of the chicken... The wings are also components of the chicken, so you will have eaten meat” Mother-in-law from Mozambique 123 6.3.4.3 Local food conceptualizations Participants shared that eggs from chickens were not usually seen as food, as they wanted the eggs to hatch into chickens. Consequently, though many households raised chickens, eggs had to be bought for consumption and were often seen as a luxury food not budgeted for. “[We] do not keep chicken for eggs…they want the chicken to hatch the eggs and get chicks hence…the eggs are not eaten often” Mother from Kenya “Sometimes we do have our local chickens which lay eggs but usually we do not dare to touch the eggs… so we allow it to hatch them itself.” Community leader from Mozambique “The eggs that hens lay are not always eaten, but only from time to time” Mother-in-law from The Gambia Nuts were conceptualized as a snack food in Kenya, which meant they were neither considered a meal nor budgeted for. Mozambican and Gambian participants considered nuts as a main ingredient in meals, cooked into dishes or used as an affordable and/or healthier oil alternative. “Truth is, they (groundnuts) are very rare. Maybe on a personal level, if someone wants to eat them… they can be found on the roadside…for 5 Ksh or 10 Ksh. They just like a snack” Community leader from Kenya “We use groundnuts a lot…Because groundnuts are not expensive compared to oil” Mother from Mozambique 124 “Groundnut is part of our daily meal because it is produced by us…. We always eat groundnut…. We keep eating groundnut soup throughout the year.” Mother-in-law from The Gambia 6.3.4.4 Unhealthy foods Salty and fried foods, sugary foods, and fizzy drinks were described as luxury foods purchased by families who could afford it, special occasion foods enjoyed at celebrations, and as snack foods. Sweets and packaged biscuits in particular were cheap and widely available in small neighbourhood shops across the three countries, and perceived to be snacks for children but also consumed by pregnant women when they had cravings. Mozambican and Gambian participants rarely described cake, which Kenyan participants described for celebrations. Kenyan and Mozambican participants more frequently described consumption of packaged potato or cassava crisps, fried bread products, fried potatoes, samosas and roasted portions of chicken or meat. Fast foods and street foods were not available in some remote rural neighbourhoods but women accessed them at nearby main roads and towns when they went shopping or to the clinic. “We eat sweets always because it’s always available… If you don’t eat it in the morning, you can eat them in the evenings…They (pregnant women) do [eat sweets]… because it gives them appetite.” Mother from The Gambia “She eats fried potatoes, sambusa (samosa)… anytime she feels like eating them, she goes to eat when there is money” Spouse from Kenya “These fried things are much more on the weekends… [O]n normal days, they (pregnant women) eat beans and vegetables, but when the weekend comes here, life is 125 different….you have to get this meat…They like to eat roasted beef.” Spouse from Mozambique Across the three countries, participants described frequent consumption of sweetened drinks by both pregnant and general populations, especially sweetened tea. Participants often considered sweetened tea a staple for breakfast. Gambian participants shared having sweetened green tea potentially multiple times a day. “For attaya (sweetened green tea)… some drink it in the morning, afternoon, and evening…some pregnant women drink it a lot.” Community leader from The Gambia “You can take it today and take it tomorrow as I am addicted to tea…. Tea, when we put it on the table for everyone to drink, there's one who puts 2 spoons [of sugar], there's one who puts 4 spoons and…even putting 5 little spoons in the cup to take tea…. there are those who like sweet things” Mother-in-law from Mozambique “I use sugar in my tea or make juice and add sugar to it to make it sweet.” Mother from Kenya While some participants described fried and salty foods, sugary foods and sweetened drinks as unhealthy, affordability was the main barrier to frequent consumption and participants shared that people bought these foods whenever they had money. Participants sometimes perceived certain sweetened drinks, such as juice and orange sodas, to be healthy due to their association with fruits. 126 [Regarding sweet foods and drinks] “They are consumed, but require great care… Because it can cause diabetes, you have to eat very cautiously. Even when you drink tea, you can't fill too much sugar… And so can soft drinks, they can cause diseases… While there are people who like it, not having money, they have no way to do anything” Mother-in-law from Mozambique “If they (pregnant women) have money, they can consume three times per week…The Fanta, it's almost orange isn't it, so … it's part vitamin.” Spouse from Mozambique “If it comes to juice, sometimes we can drink it three times in a day… For juice, I know it gives the body water” Mother-in-law from The Gambia “For Afya drink (commercial sweetened fruit juice), it strengthens because it is a fruit drink… They (pregnant women) drink Afya because it increases blood circulation as it is made of fruits.” Mother from Kenya 6.4 Discussion 6.4.1 Summary of findings Our study found three distinct dietary patterns across countries distinguished by dietary diversity. The most diverse dietary pattern represented about one in ten pregnant women across the PRECISE study (608 of 6166; 9.9%) and was characterized by high prevelance of intake of all food groups in the previous 24-hours. The moderate diversity dietary pattern represented 47.5% (2926 of 6166) of women across the three PRECISE countries, and was characterized by high consumption of grains and white roots with moderate to high consumption of flesh foods, and vitamin A-rich fruits and vegetables, including leafy greens. The least diverse pattern represented 127 42.6% (2625 of 6166) of women across the three PRECISE countries, and was characterized by a predominance of grains. The most diverse and least diverse patterns were similar across the three countries, with more differences between countries for moderately diverse patterns. Overall, dietary patterns prioritized grains and flesh foods, especially fish, which aligned with qualitative findings that these were perceived as staple foods across the three countries (Table 6.4). Consumption patterns of beans were surprisingly low with a relatively higher prevelance of consuming flesh foods even in moderate and least diverse patterns. Qualitative data suggests that meat, poultry and fish were preferred, purchased when the household could afford to, and thus a marker of social status and a rich life. Qualitative findings suggest affordability was the major driver of dietary patterns, influenced by local conceptualizations and preferences of various food groups. Table 6.4 Summary of key converging quantitative and qualitative findings Quantitative findings Qualitative findings • High consumption of grains and whiteroots across all three dietary patterns• Grains considered a staple food and thebase of meals• Consumption patterns of meat, poultryand fish were lower among moderate andleast diverse patterns but relatively highwithin each dietary pattern• Fish, especially small fish, was considereda staple food across the three countries• Meat and poultry seen as luxury foods orspecial occasion foods that are regularlyconsumed by people who can afford topurchase• Compared to the most diverse dietarypattern, moderate and least diversepatterns were characterized by lowerdiversity in fruits and vegetables• Green leafy vegetables were considered astaple food, especially in Kenya andMozambique• Orange- and dark yellow-fleshed fruitsand vegetables high in vitamin A, othervegetables and fruits were highly seasonaland seen as luxury foods regularly128 consumed by people who can afford to purchase • The most diverse dietary pattern wascharacterized by consumption ofunhealthy foods (fried and salty foods,sweet foods and drinks)• Many unhealthy foods were often seen asluxury foods or special occasion foodsthat are regularly consumed by peoplewho can afford to purchase6.4.2 Nutritional implications Compared to least diverse dietary patterns, the moderate and most diverse patterns featured higher intake of a variety of animal source foods, fruits, and vegetables. In particular, the most diverse dietary pattern had higher intakes of beans, milk and milk products and eggs. Women with the least diverse dietary pattern may be challenged in obtaining adequate intakes of high-quality protein and bioavailable micronutrients such as iron, zinc, calcium, vitamin A and vitamin B12. Additionally, certain micronutrients such as zinc and iron are more bioavailable in flesh foods (389,390). Though cereals are a source of zinc, high phylate content in cereals inhibit zinc absorption (389). Calcium from dairy products and vitamin A from orange- and dark yellow-fleshed fruits and vegetables are also more bioavailable than these micronutrients from dark green leafy vegetables (389,390). Vitamin B12 is only naturally found in animal food products (390). These nutrients are important for a healthy pregnancy. Low iron and vitamin B12 increases the risk of anemia, which is associated with higher risk of postpartum hemorrhage, hypertensive disorders of pregnancy, preterm delivery and low birth weight infant (391–393,368). Lower maternal calcium, zinc and vitamin B12 levels have been associated with higher risk of pre-eclampsia (368,394). Furthermore, supplementation trials have generally found 129 protective effects of calcium and zinc on reducing low birth weight and preterm delivery (395,396). While MDD-W has only been validated for micronutrient adequacy, an examination of food group patterns revealed probable macronutrient imbalances with the emphasis on grain-based meals. While protein may be obtained from other foods, flesh foods and dairy are important sources of high-quality protein providing all essential amino acids. Rice and maize, which many participants described regularly consuming across the three countries, is low in the essential amino acid lysine, which limits the total utilization of protein (397,398). Furthermore, only 71% of the available lysine in white African maize is bioavailable when prepared in a stiff maize porridge, further reducing the protein quality value (398). Adequate protein during pregnancy is crucial to support fetal growth and development as well as maintaining maternal health, and recent studies have shown increased protein requirements during pregnancy, especially in late gestation (399,400). Lysine requirements are higher during late gestation compared to early gestation (401), which can be particularly challenging in low diversity, grain-based dietary patterns found in our study. While low intake of consumption of poultry and meat were found in low diversity dietary patterns, quantitative and qualitative findings in our study both highlighted fish as a key animal food source in all three dietary patterns, which aligns with previous studies in sub-Saharan Africa (402–406). While small fish cooked as a stew shared among the entire household raises concern about inadequate protein intake at an individual level, even small amounts of fish may play an important role in predominantly grain-based diets. As a source of all essential amino acids, with a particularly high concentration of lysine, consumption of fish may help compensate 130 for the small amount of lysine in rice and maize (407). Additionally, small fish is a valuable source of bioavailable vitamin A, iron and zinc, though fish species, preparation methods, and consumption practices can influence nutritional content (405,408,407,409). For example, freshwater fish may be high in less bioavailable forms of vitamin A (3,4-dehydroretinol) and preparation methods such as drying and boiling can destroy substantial vitamin A content (407). Consuming small fish along with their bones, as with sardines and other small dried fish in Kenya, is a valuable source of calcium and B-vitamins such as folate and vitamin B12 (403,405). 6.4.3 Implications for research and policy WHO antenatal guidelines recommend healthy dietary counselling during pregnancy to support adequate maternal nutrition (298). However, this study has shown that accessing certain nutritious food groups was a challenge for substantial proportions of the population and innovative solutions are needed to close the gap in meeting nutrition needs. While research is moving forward to evaluate the efficacy and feasibility of multiple micronutrient supplementation during pregnancy (410), macronutrient imbalances and essential amino acid requirements warrant further consideration. More research is needed to understand the role of small fish to support protein requirements in sub-Saharan Africa. Our findings of a high diversity dietary patterns characterized by high intake of unhealthy foods in the same communities as low diversity dietary patterns highlight the growing concern about a triple burden of malnutrition (over- and under-nutrition, micronutrient deficiencies) in sub-Saharan Africa (411–413). To the best of our knowledge, our study is the first to report high intake of MDD-W unhealthy food groups alongside high dietary diversity patterns among pregnant populations in Africa, where the emphasis is usually focused on unmet minimum 131 dietary diversity. However, our findings align with other studies from sub-Saharan Africa documenting rapid nutritional transition even in rural areas, and the emerging prominence of dietary patterns characterized by purchasing highly processed foods (414). Our findings suggest the need to i) strengthen health education about unhealthy foods, such as to dispel misconceptions about health benefits of sugar sweetened fruit drinks and increase awareness about sweetened tea, and ii) consider subgroups within women with adequate dietary diversity depending on intake of unhealthy foods. The latter may be especially important when investigating associations between dietary diversity and health outcomes. 6.4.4 Strengths and limitations Our study is strengthened by the triangulation of quantitative and qualitative methodologies and multi-country research utilizing the same research procedures. Strengths of the 24-hour recall method include reduced recall bias compared to longer timeframes for other dietary methodologies. However, the self-reported nature of the recall method is limited by potential social desirability biases (415) as well as misunderstandings of food groups classifications (32). Additionally, the study is limited by a single food recall conducted with each woman. Furthermore, while data-driven approaches generate relevant dietary patterns for study samples, patterns are not generalizable to other settings. 6.5 Conclusion Pregnant women in Kenya, Mozambique and The Gambia with least diverse dietary patterns have largely grain-based diets and face challenges in accessing high quality sources of protein, iron, zinc, calcium, vitamin A and vitamin B12, which have important roles in human health and fetal development. On the other hand, women with the most diverse pattern had the highest 132 intake of unhealthy foods, which has been associated in the literature with increased risk of non-communicable diseases. The moderately diverse pattern may be the most beneficial for health, which can be further explored in future research and targeted in health education programming. 133 Chapter 7: Associations between maternal dietary diversity status and pregnancy hypertension in Kenya, Mozambique and The Gambia 7.1 Introduction Dietary diversity, when a range of different foods are consumed ensuring nutrient balance, is a critical component of good nutrition (416) and evidence suggest that when maternal diets are diverse, there are lower risks of maternal anemia and small vulnerable newborns (417,40,418,419), with lasting effects on reduced childhood stunting (43–45). However, though the MDD-W is a widely used indicator for WRA (35), less is known about the impact of dietary diversity during pregnancy on women’s health outcomes beyond maternal anemia. Only two studies globally have investigated the association between MDD-W and pregnancy hypertension, resulting in conflicting findings (48,49). HDPs are a leading cause of maternal mortality and morbidity globally, with a disproportionate burden in LMICs (12,420). HDPs account for 16% of the maternal deaths in sub-Saharan Africa (420), where the prevalence of HDPs is 8% of all pregnancies and associated with adverse pregnancy outcomes including higher risk of caesarean deliveries, preterm birth, low birth weight infants and perinatal mortality (421). There is growing concern about increasing incidence of HDP in resource-limited sub-Saharan African settings, where fragile health systems can compromise timely diagnosis and care, and risk factors are not contextualized to African settings, including a high prevalence of undernutrition (12,71,422,423). Among populations with low dietary calcium, calcium supplementation is recommended by the WHO to help prevent pre-eclampsia (298), though other micronutrient deficiencies can also increase the risk of pre-eclampsia and other HDPs (394). 134 Additionally, previous work presented in this Dissertation found that maternal dietary patterns with the most dietary diversity also feature high consumption of unhealthy foods (see Chapter 6). Unhealthy foods groups described by MDD-W include highly processed and nutrient poor fried and salty snacks, sweets, and sweetened beverages, which are important risk factors for non-communicable diseases such as cardiovascular disease, diabetes and cancer (424–427). However, while data on unhealthy foods are collected during the assessment of MDD-W, they are not considered as part of dietary diversity status and only descriptively reported following the indicator guidelines (35). While MDD-W is often used to understand population-level nutritional status among WRA, there is limited knowledge on the association between dietary diversity and HDPs, and the additional involvement of consumption of unhealthy food groups. Consumption of unhealthy food groups may complicate the relationship between dietary diversity and health outcomes if not adequately considered. The objective of this study was to assess the association between maternal dietary diversity status and HDPs in sub-Saharan Africa, and investigate the potential influence of high unhealthy food consumption. 7.2 Methods 7.2.1 Study design and population This study is part of the PRECISE Network, a prospective cohort that enrolled women in Kenya, Mozambique and The Gambia between June 2019 and December 2022, described previously in Section 1.5.4. For the present analysis, we included women who reported a singleton pregnancy. Non-pregnant women of reproductive age and women with multiple pregnancies were excluded. The median gestational age at enrollment into PRECISE was 20.9 weeks [IQR 16.0, 25.6]. 135 7.2.2 Exposure assessment All dietary diversity indicators were based on consumption of MDD-W food groups in the previous 24-hours. The MDD-W includes ten main healthy food groups and three main unhealthy food groups (see Section 1.5.4.3 for more detail on the food groups). The standard criteria for meeting MDD-W was five or more food groups out of ten healthy food groups (428,429). We also explored modified criteria that classified women as unmet MDD-W (<5 healthy food groups), met MDD-W with lower unhealthy intake (≥5 healthy food groups and <3 unhealthy food groups), and met MDD-W with higher unhealthy intake (≥5 healthy food groups and 3 unhealthy food groups). High intake of unhealthy foods was defined in our study as consumption of all three unhealthy food groups (fried and salty foods, sweet foods, sweetened beverages). High intake of healthy foods was defined as consumption of all four fruit and vegetable food groups (green leafy vegetables, other vitamin-A rich fruits and vegetables, other fruits, other vegetables). 7.2.3 Outcome assessment and sample size The primary outcome for this study was gestational hypertension, defined as 140/90 mmHg arising at ≥20 weeks’ gestation. Gestational hypertension excluded women with chronic hypertension, defined as high blood pressure detected pre-pregnancy or before 20 weeks’ gestation. The outcome, ‘any pregnancy hypertension’, included women with hypertension diagnosed anytime during pregnancy (gestational or chronic hypertension). Pre-pregnancy hypertension was self-reported in surveys through asking women if they had high blood pressure, or hypertension, or if they were currently taking blood pressure medication. During pregnancy, clinical study staff took blood pressure measurements at each study visit. 136 Following International Society for the Study of Hypertension in Pregnancy (ISSHP) guidelines (17), hypertension was diagnosed based on two readings, averaged to reflect the blood pressure for the visit. If the first two readings differed >10 mmHg, a third measurement was taken and the average of the second and third readings used. The sample size calculation for this study was based on estimates that pregnancy hypertension complicates about 10% of pregnancies in LMICs (13) and a previous study found that meeting MDD-W may be associated with an odds ratio of 0.45 for HDP incidence (49). A sample size of435 per study group was required to detect an odds ratio of 0.5 from a 10% expected incidence with a type I (two-sided) error of 5% and a type II error of 80% (430). 7.2.4 Covariates assessment Country and rural/periurban residence were based on the health facility women were recruited into the PRECISE cohort. Age, parity, marital status, pre-gestational diabetes and HIV status were self-reported by women in the PRECISE surveys. BMI was calculated as a woman’s weight divided by the square of her height, measured at the first study visit (at enrollment). Maternal weight was an average of three weight readings and maternal height was an average of two height readings. Seca adult scales were used to measure weight and Seca adult stadiometers were used to measure height. Measurements were completed by trained nurses.Statistical analysis Analyses were performed using RStudio (version 4.2.3). Descriptive statistics tabulated frequency of demographic, clinical and dietary background characteristics by country and overall. The prevelances of gestational hypertension and any pregnancy hypertension were summarized by country and dietary diversity status (standard and modified MDD-W). Logistic regression models were performed for gestational hypertension and any pregnancy hypertension 137 to evaluate the effect of dietary diversity indicators. Model-fit was selected based on the AIC (29) (Appendix H.1). The final model adjusted for country, rural/periurban residence, age,parity, marital status, BMI, HIV, and pre-gestational diabetes. Odds ratios (ORs) with their corresponding 95% confidence intervals were calculated with pregnant women with unmet MDD-W as the reference categories. High intakes of fruits and vegetables and high intakes ofunhealthy foods were compared to women with lower intake in each indicator. Both crude ORs and adjusted ORs are reported. Statistical significance was evaluated as p ≤0.05. 7.3 Results 7.3.1 Participant characteristics Of the 8,757 women enrolled in PRECISE across the three countries, 7,715 contributed dietary assessments, including 6,166 pregnant women. Among pregnant women, there were 6,074 singleton pregnancies, including 2,812 from Kenya, 2,048 from Mozambique and 1,214 from The Gambia. Overall, participants had a median age of 25 years, with 11.4% of women aged 35 years or older (Table 7.1). Most women were parous, married or cohabiting with their partner, and 57.1% had primary education or less. A majority (67.5%) of women self-identified as housewives as their occupation without independent sources of income. Over half (59.4%) of the women were recruited from periurban health facilities. Women had a median BMI of 23.8kg/m2, with 5.0% classified as underweight, 26.0% overweight and 12.4% obese. Self-reported pre-gestational diabetes and chronic hypertension was low, at 0.6% and 1.7% of the women respectively. Overall, 5.7% of women reported they were HIV positive, with the highest prevelance in Mozambique (11.6%). Within our sample, women had a median DDS of four, with an interquartile range of three to six healthy food groups consumed in the previous 24-hours, and 138 48.3% met minimum dietary diversity for women. There were 11.6% with high fruit and vegetable intake, and 10.9% with high intake of unhealthy food groups. Table 7.1 Participant characteristics Kenya (n=2812) Mozambique (n=2048) The Gambia (n=1214) Total (n=6074) Demographics Residence Rural 1222 (43.5%) 629 (30.7%) 613 (50.5%) 2464 (40.6%) Periurban 1590 (56.5%) 1419 (69.3%) 600 (49.5%) 3609 (59.4%) Maternal age Median [IQR] 26.0 [23.0, 31.0] 23.0 [19.0, 29.0] 26.0 [22.0, 31.0] 25.0 [21.0, 30.0] ≥35 years 339 (12.1%) 186 (9.1%) 169 (13.9%) 694 (11.4%) Parity 0 previous births 809 (28.8%) 817 (39.9%) 229 (18.9%) 1855 (30.5%) 1-4 previous births 1790 (63.7%) 1174 (57.3%) 699 (57.6%) 3663 (60.3%) 5 or more previous births 213 (7.6%) 57 (2.8%) 286 (23.6%) 556 (9.2%) Marital status Single 186 (6.6%) 881 (43.0%) 22 (1.8%) 1089 (17.9%) Married/Co-habiting 2400 (85.3%) 1151 (56.2%) 776 (63.9%) 4327 (71.2%) Polygamous marriage 174 (6.2%) 4 (0.2%) 411 (33.9%) 589 (9.7%) Separated/ Divorced/Widowed 52 (1.8%) 12 (0.6%) 5 (0.4%) 69 (1.1%) Education None 269 (9.6%) 107 (5.2%) 772 (63.6%) 1148 (18.9%) Primary school 1443 (51.3%) 683 (33.3%) 193 (15.9%) 2319 (38.2%) Secondary school 758 (27.0%) 1233 (60.2%) 192 (15.8%) 2183 (35.9%) Higher education 342 (12.2%) 25 (1.2%) 57 (4.7%) 424 (7.0%) Occupation Housewife 1547 (55.0%) 1486 (72.6%) 1068 (88.0%) 4101 (67.5%) Student 55 (2.0%) 342 (16.7%) 12 (1.0%) 409 (6.7%) Market trader 278 (9.9%) 87 (4.2%) 46 (3.8%) 411 (6.8%) Laborer (factory, large scale agriculture, construction) 47 (1.7%) 35 (1.7%) 9 (0.7%) 91 (1.5%) Professional 148 (5.3%) 59 (2.9%) 20 (1.6%) 227 (3.7%) Other/ Missing 737 (26.2%) 39 (1.9%) 59 (4.9%) 835 (13.7%) Medical conditions BMI kg/m2 139 Median [IQR] 24.2 [21.6, 27.9] 24.2 [22.0, 27.0] 22.0 [19.75, 24.8] 23.8 [21.3, 27.1] Underweight (<18.5 kg/m2) 106 (3.8%) 38 (1.9%) 162 (13.3%) 306 (5.0%) Normal weight (18.5-24.9 kg/m2) 1475 (52.5%) 1153 (56.3%) 771 (63.5%) 3399 (56.0%) Overweight (25.0-29.9 kg/m2) 736 (26.2%) 643 (31.4%) 203 (16.7%) 1582 (26.0%) Obese (≥30.0 kg/m2) 462 (16.4%) 214 (10.4%) 78 (6.4%) 754 (12.4%) Pre-gestational diabetes 26 (0.9%) 3 (0.1%) 8 (0.7%) 37 (0.6%) HIV+ 88 (3.1%) 238 (11.6%) 19 (1.6%) 345 (5.7%) Chronic hypertension 66 (2.3%) 22 (1.1%) 14 (1.2%) 102 (1.7%) Dietary diversity Median DDS [IQR] 4 [3, 6] 4 [3, 6] 5 [4, 6] 4 [3, 6] Unmet MDD-W (<5 healthy food groups) 1550 (55.1%) 1170 (57.1%) 421 (34.7%) 3141 (51.7%) Met MDD-W (≥5 healthy food groups) 1262 (44.9%) 878 (42.9%) 793 (65.3%) 2933 (48.3%) Met MDD-W with lower unhealthy intake* 1045 (37.2%) 642 (31.3%) 705 (58.1%) 2392 (39.4%) Met MDD-W with higher unhealthy intake† 217 (7.7%) 236 (11.5%) 88 (7.2%) 541 (8.9%) High intake of fruits and vegetables‡ 233 (8.3%) 375 (18.3%) 96 (7.9%) 704 (11.6%) High intake of unhealthy foods† 304 (10.8%) 253 (12.4%) 105 (8.6%) 662 (10.9%) IQR – interquartile range; DDS – dietary diversity score; MDD-W – minimum dietary diversity for women *Less than three unhealthy food groups consumed in the previous 24-hours (fried and salty foods, sweets, sweetenedbeverages)†All three unhealthy food groups consumed in the previous 24-hours‡Reported consumption of all four fruit and vegetable food groups in the previous 24-hours (green leafy vegetables,other vitamin-A rich fruits and vegetables, other fruits, other vegetables)7.3.2 Dietary diversity status and prevelances of pregnancy hypertension There were 1068 cases of gestational hypertension and 1170 of any pregnancy hypertension among our cohort of singleton pregnancies, resulting in prevelances of 17.6% and 19.3% gestational and any pregnancy hypertension, respectively. The prevelance of gestational hypertension was 17.2% among women with unmet MDD-W and 18.0% among women who 140 met MDD-W. Among women who met MDD-W with higher unhealthy foods intake, 20.3% had gestational hypertension and 22.2% had any pregnancy hypertension (Table 7.2). Table 7.2 Prevelances of gestational hypertension and any pregnancy hypertension by dietary diversity status Gestational hypertension Any pregnancy hypertension* Overall 17.6% (1068 of 6074) 19.3% (1170 of 6074) Kenya 16.7% (471 of 2812) 19.1% (537 of 2812) Mozambique 13.3% (272 of 2048) 14.4% (294 of 2048) The Gambia 26.8% (325 of 1214) 27.9% (339 of 1214) Standard MDD-W Unmet MDD-W 17.2% (539 of 3141) 18.8% (589 of 3141) Met MDD-W 18.0% (529 of 2933) 19.8% (581 of 2933) Modified MDD-W Unmet MDD-W 17.2% (539 of 3141) 18.8% (589 of 3141) Met MDD-W with lower unhealthy intake† 17.5% (419 of 2392) 19.3% (461 of 2392) Met MDD W with higher unhealthy intake‡ 20.3% (110 of 541) 22.2% (120 of 541) MDD-W – minimum dietary diversity for women*Any pregnancy hypertension includes both gestational and chronic hypertension†With less than three unhealthy food groups consumed in the previous 24-hours (fried and salty foods, sweets,sweetened beverages)‡With all three unhealthy food groups consumed in the previous 24-hours7.3.3 Meeting minimum dietary diversity for women and pregnancy hypertension Meeting minimum diversity for women was not associated with gestational hypertension or any pregnancy hypertension in neither the crude nor adjusted models (Table 7.3). After adjusting for confounders, we found that women who met MDD with lower unhealthy intake had lower odds of gestational hypertension (aOR 0.84, 95% CI: 0.72-0.97, p= 0.0198) and any pregnancy hypertension (aOR 0.86, 95% CI: 0.75-0.99, p= 0.0399) compared to women with unmet MDD. The protective effect of meeting MDD was not found among those with higher unhealthy intake. 141 Neither examining high intake of unhealthy foods or diverse fruits and vegetables on their own were significantly associated with gestational hypertension or any pregnancy hypertension. Table 7.3 Associations between dietary diversity status with gestational and any pregnancy hypertension Gestational hypertension Any pregnancy hypertension* cOR (95% CI) aOR† (95% CI) cOR (95% CI) aOR† (95% CI) Met MDD-W‡ 1.06 (0.93-1.21) 0.89 (0.78-1.03) 1.07 (0.94-1.22) 0.91 (0.80-1.04) Met MDD-W with lower unhealthy intake‡§ 1.03 (0.89-1.18) 0.84 (0.72-0.97)** 1.23 (0.99-1.54) 0.86 (0.75-0.99)** Met MDD-W with higher unhealthy intake‡¶ 1.23 (0.98-1.54) 1.16 (0.91-1.47) 1.03 (0.90-1.18) 1.17 (0.92-1.47) High intake of unhealthy foods¶ 1.17 (0.95-1.43) 1.20 (0.97-1.48) 1.15 (0.94-1.40) 1.18 (0.96-1.45) High intake of fruits and vegetables# 1.01 (0.82-1.24) 1.14 (0.92-1.41) 1.04 (0.85-1.26) 1.17 (0.95-1.44) cOR –crude odds ratios; aOR – adjusted odds ratios; CI – confidence intervals; MDD-W – minimum dietary diversity for women *Any pregnancy hypertension includes both gestational and chronic hypertension†Adjusted for country, rural/periurban residence, age, parity, marital status, BMI, pre-gestational diabetes and HIV‡Compared to unmet MDD-W§Less than three unhealthy food groups consumed in the previous 24-hours (fried and salty foods, sweets, sweetenedbeverages)¶All three unhealthy food groups consumed in the previous 24-hours#Reported consumption of all four fruit and vegetable food groups in the previous 24-hours (green leafy vegetables,other vitamin-A rich fruits and vegetables, other fruits, other vegetables)** p ≤0.057.4 Discussion 7.4.1 Summary of findings The key findings are that, meeting minimum dietary diversity for women was associated with lower odds of gestational and any pregnancy hypertension only among those with lower 142 unhealthy foods intake. These results suggested that eating a diversity of different foods is beneficial for health only when accompanied by lower intake of unhealthy food groups. Adequate levels of dietary diversity, even high consumption patterns of diverse fruits and vegetables, are not sufficient on their own if unhealthy food consumption patterns are not taken into account. 7.4.2 Comparisons to the literature A systematic review of maternal dietary patterns and pregnancy hypertension in LMICs (see Chapter 3 of the Dissertation) previously found reduced risk of pre-eclampsia among women with regular consumption of fruits and vegetables (431). In contrast, our study found that examining high intake patterns of fruits and vegetables or those with high intake patterns of unhealthy food groups on their own both trended towards higher odds of pregnancy hypertension. The women with ability to obtain diverse types of fruits and vegetables may overlap with those who obtained unhealthy foods more regularly and highlights the need to consider intake patterns of healthy and unhealthy food groups together. Our results build on previous findings from the Nurses' Health Study II cohort in the United States with 19,917 singleton pregnancies that also did not find a significant association between the standard definition of meeting MDD-W and reduced HDPs rates (48). Their definition of HDP excluded chronic hypertension, which was similar to our study definition of gestational hypertension. Our study reported similar point estimates for meeting MDD-W (RR 0.92, 95% CI: 0.75-1.12 Nurses' Health Study II cohort vs aOR 0.89, 95% CI: 0.78-1.03 PRECISE cohort). In contrast, a smaller case-control study from Ethiopia with 340 pregnancies found substantially lower odds of HDPs among women who met MDD-W (aOR 0.45, 95% CI:0.21-0.93) (49). 143 Conflicting findings from the two previous studies align with a recent review that concluded there are inconsistent effects of high dietary diversity status on a broad range of health outcomes (79). However, our study findings may help to bring these two divergent findings together by highlighting the importance of local dietary patterns, especially in the consumption patterns of fried and salty foods, and sweetened foods and beverages. Highlighting consumption patterns of unhealthy foods is in line with a meta-analysis of four cohort studies that found increased odds of pre-eclampsia (OR 1.28; 95% CI: 1.15-1.42) with maternal diets high in ultra-processed foods (432), especially sweetened beverages (433,434). However,our findings suggested the need also for adequate dietary diversity in resource-limited settings, at least for gestational hypertension. Previous studies from Ethiopia and other LMICs have highlighted higher intakes of dairy, fruits and vegetables on reduced adverse pregnancy outcomes, including pre-eclampsia (435–438,431). 7.4.3 Implications for research and practice Our findings supported evidence for Mediterranean and Nordic diets (high consumption of fruits, vegetables, whole grains, fish and poultry, limited saturated fats, red meat and sweets) as protective against the development of pre-eclampsia and other adverse pregnancy outcomes (368,394,439–441). However, the cultural significance of Mediterranean and Nordic diets (441) and limited evidence from LMICs (431) suggests that they may not translate well to other cultural contexts, especially in resource-limited global settings. MDD-W, on the other hand, was developed by the FAO for use in LMICs and is widely used by United Nations agencies, in Demographic and Health Surveys and national governments for nutritional tracking (35). The earlier qualitative research presented in this Dissertation has shown that the concept of dietary diversity resonated with local knowledge about healthy eating, especially during pregnancy, in 144 Kenya, Mozambique and The Gambia, but there were potential misunderstandings about unhealthy foods (see Chapter 6 in the Dissertation). Further research can explore the feasibility, acceptability and effectiveness of raising awareness of unhealthy food groups alongside the benefits of increased dietary diversity during antenatal care, especially given the rapid growth of processed foods in rural and periurban Africa (324,326,442). The importance of both adequate micronutrient status, represented by meeting MDD-W, and lower intake of unhealthy food groups speaks to findings of our scoping review (Chapter 2 of the Dissertation) that discussed how maternal nutrient factors may be involved in the physiology of pre-eclampsia development. Micronutrients had key roles in placental development, and the regulation of oxidative stress and hypertension, while dietary patterns high in added sugar, sodium and saturated fats were associated with maternal endothelial dysfunction and systemic inflammatory response (394). Evaluating biomarkers can clarify pathways between diet, nutrients and disease risk and further research is recommended into biomarkers of diet intake associated with the development of HDPs in resource-limited settings. Lastly, more research is recommended to evaluate the association between the modified MDD-W, which incorporates unhealthy food group intake and other health outcomes, especially in resource-limited settings. The WHO Non-Communicable Diseases (NCDs) Progress Monitor Report 2022 highlighted cardiovascular diseases, cancer, diabetes and chronic respiratory diseases as the leading causes of deaths globally and the heavy burden particuarly in LMICs where 75% of these deaths occur (443). Unhealthy diets characterized by foods and beverages high in saturated fats, transfatty acids, free sugars, or salt was a key modifiable risk factor for NCDs (443). Women who develop gestational hypertension and pre-eclampsia have higher risk 145 of developing NCDs later in life, including cardiovascular disease and type II diabetes (444–446). Futher research evaluating the modified MDD-W criteria with other health outcomes in women can contribute to the literature on NCDs in resource-limited settings, as well as explore whether dietary patterns may mediate the association between HDPs and higher risk of NCDs later in life. 7.4.4 Strengths and limitations Chronic hypertension and pre-gestational diabetes were based on self-report in this study, which may be underdiagnosed. Additionally, because chronic hypertension was measured at the first PRECISE study visit along with the dietary questionnaire, the direction of causality is unclear. Also, the study is limited by potential recall and social desirability biases (415) and misunderstandings of food groups classifications (32) previously documented with list-based 24-hour food recalls. Social desirability bias may lead to selective under-reporting of food items that are known to be unhealthy particularly among sub-groups with high BMI (447), which may underestimate the prevalence of high unhealthy food intake and lead to groups seeming more similar than they actually are; this would bias results towards the null. Misunderstandings of food groups classifications may over- or under-estimate dietary diversity depending on the specific misunderstanding. The MDD-W indicator also did not collect information on food quantities, thus caloric intake or nutrient quantities cannot be calculated and there is unmeasured confounding from the lack of data on quantity for adjustment. Collecting dietary data over multiple countries in sub-Saharan Africa were strengths of our study. 146 7.5 Conclusion Pregnant women in resource-limited settings in sub-Saharan Africa require both higher diversity in healthy food groups and lower consumption of unhealthy food groups to reduce the risk of developing gestational hypertension and other HDPs. The current MDD-W criteria does not adequately consider unhealthy food groups, which need to be incorporated into the assessment of dietary diversity status. We have developed a method using existing data collected in the tool to strengthen capacity of understanding subgroups among women who met MDD-W distinguished by higher unhealthy foods consumption, which can be further explored in future research. 147 Chapter 8: Summary and recommendations 8.1 Overview Nutritious and diverse foods during pregnancy plays important roles in supporting maternal and child health, but maternal nutritional interventions tend to focus on reporting fetal and infant outcomes and health outcomes for women specifically have been under-reported. While healthy maternal dietary patterns may help to prevent pre-eclampsia and other HDPs, research summarized in systematic reviews often included only studies conducted in HICs, not in resource-limited settings where there are disproportionate burdens of both maternal mortality and maternal undernutrition. Thus, this Dissertation sought to map the pathways of risk between maternal diets and pregnancy hypertension, using the MDD-W tool to advance women-centered maternal nutrition in sub-Saharan Africa. This Dissertation included a series of studies that summarized existing literature and used mixed-methods research to generate novel findings in an area of clinical relevance, grounded in community perspectives and biological mechanisms. Findings raised important issues about how dietary diversity was perceived by the community members, the interplay of socio-demographic determinants, dietary diversity patterns and their implications for nutrition, and changing nutritional landscapes in rural Africa. In this final chapter, I summarize the main research objectives and findings, and discuss the unique contributions of this work, its limitations and global health implications, as well as knowledge translation activities and recommendations for future research and policy. 148 8.2 Summary of objectives and findings 8.2.1 Objective 1 This Dissertation systematically reviewed the literature for current evidence on the influence of maternal diets on pregnancy hypertension in resource-constrained settings, which resulted in two reviews that have been published in BMC Reproductive Health (394) and Advances in Nutrition (431). The scoping review found associations between nutritional inadequacies and higher risk of pre-eclampsia through poor placentation (vitamins D, B9, B12), oxidative stress (vitamins C and E, zinc, copper, selenium as antioxidants; free iron and copper as pro-oxidative transition metals), maternal endothelial dysfunction and systemic inflammatory response (healthy maternal dietary patterns, low in added sugar), and hypertension (vitamin D and calcium). The systematic review on dietary patterns and pregnancy hypertension in LMICs was the first to explicitly focus on resource-limited global settings, and found that healthy maternal diets may have a substantial protective effect on reduced rates of pre-eclampsia, but more research with high quality prospective cohort studies was needed to support the evidence. 8.2.2 Objective 2 Based on 47 interviews triangulated with findings from participant observation and photovoice, this research found that dietary diversity was well-aligned with local perceptions of healthy meals. Community members differentiated between starchy staple grains as the filling foods and additional foods served in a sauce or stew to provide nutrients. While diverse meals were valued for pregnant and lactating mothers, participants across the three countries shared that maternal diets did not differ substantially from typical household meals, and that diverse diets were not assessible for many in their communities, due to challenges in affordability, seasonality, gender 149 norms, knowledge and preferences. Factors elicited in the qualitative study were futher assessed in objective 3 as determinants of dietary diversity. 8.2.3 Objective 3 Assessments of dietary diversity in the PRECISE cohort found that only 47.7% met MDD-W, which confirmed qualitative findings that diverse dietary patterns were not feasible for a majority of women in our study settings. Pregnant women had slightly higher rates of meeting MDD-W compared to non-pregnant WRA, but still below half of the population (48.4% pregnant vs 45.6% non-pregnant women in the PRECISE cohort), which aligned with qualitative findings that diverse diets were valued for pregnant women, but did not frequently translated into practice. The strongest associations with meeting MDD-W were seen with country (The Gambia compared to Kenya in our study), higher levels of education and paid employment. Periurban residency, living with natal family and medium (compared to small) household sizes were associated with unmet MDD-W. Conversely, no associations were observed with women’s autonomy and the gender of household head. Significant dietary diversity determinants with evidence of an association with pre-eclampsia (i.e. country, rural/periurban residence, parity, marital status), were considered as potential confounding variables in the statistical models for pregnancy hypertension. Using latent class analysis, I found three distinct dietary patterns across countries. Of note, a substantial portion of the population (42.6%) had the least diverse dietary pattern, which aligned with MDD-W and qualitative results. The inclusion of both dietary patterns and community perspectives is particularly unique, as no study to our knowledge has elaborated on local meanings of food groups to explain dietary patterns characterized by diversity among pregnant 150 women. Staple foods were regularly budgeted for, while luxury, special occasion and snack foods were only regularly consumed by those who could afford them. Unhealthy foods were often grouped within luxury, special occasion foods. These findings provided insight into the least diverse diets characterized by a predominance of staple grains, as well as high intake patterns of unhealthy foods among women with the most diverse diets. Simply reporting met or unmet minimum dietary diversity highlights concerns about undernutrition among WRA in resource-limited settings but neglects the frequency of unhealthy food group consumption. By understanding the patterns of food groups underlying dietary diversity, our study was the first to report high intake of MDD-W unhealthy food groups among pregnant populations with high dietary diversity in Africa. Understanding dietary patterns characterized by diversity led to the incorporation of unhealthy food groups in analyses assessing the association between MDD-W and pregnancy hypertension. While there was no significant difference between women who met or did not meet MDD-W, women who met MDD-W with lower intake patterns of unhealthy foods had reduced odds of gestational hypertension and any pregnancy hypertension. Findings that pregnant women in sub-Saharan Africa would benefit from both higher diversity in healthy food groups and lower consumption of unhealthy food groups aligns with results of the scoping review. Women with low dietary diversity may face challenges in obtaining adequate and bioavailable intake of zinc, calcium, and vitamin B12, which the review in Chapter 2 found was implicated in the development of pre-eclampsia. Additionally, the review found that dietary patterns characterized by high intake of sugar-added foods was also associated with pre-eclampsia (394). 151 8.2.4 Mapping the pathways of risk between meeting MDD-W and pregnancy hypertension and the complex involvement of socio-economic status In summary, this research has provided novel evidence of a protective pathway between meeting MDD-W and reduced risk of pregnancy hypertension, but only among those with lower intakepatterns of unhealthy food groups, as illustrated in Figure 8.1. Socio-economic indicators assessed in PRECISE (educational attainment, occupation) emerged as strong determinants of meeting minimum dietary diversity, which aligns with community perceptions that affordability was a key influencing factor for diverse dietary patterns. However, effects of socio-economic status was complicated by the finding that pregnant women with the most diverse diet had high intake patterns of all food groups, including both healthy and unhealthy MDD-W food groups, which reflected perceptions that luxury foods would be consumed regularly if a woman could afford it. Eating a diverse range of foods was seen to be nourishing for pregnancies, but also a social status marker of a healthful and successful life, where more food groups were often seen as simply better, without distinguishing between healthy and unhealthy foods. These community perceptions around food and health frame the study’s findings on the pathways of risk between meeting MDD-W and pregnancy hypertension in sub-Saharan Africa. 152 Figure 8.1 Pathways of risk between meeting minimum dietary diversity for women and pregnancy hypertension in sub-Saharan Africa 8.3 Unique contributions and limitations 8.3.1 Critical evaluation of the influential First 1,000 Days and advancing women-centered maternal nutrition research approaches A strength of this Dissertation is the strong engagement of maternal health and nutrition approaches. The First 1,000 Days approach emphasizes the importance of adequate nutrition in early life between conception to a child’s second birthday for optimal growth and development throughout their lives (448). However, my research identified a critical gap for maternal health, beyond child health outcomes, and pioneered conceptualizing the systematic neglect of maternal health as an ends in itself within Safe Motherhood Initiative (SMI) principles and a Human 153 Rights Based Approach (HRBA) to health (59,60). This research advanced women-centered maternal nutrition research approaches through the innovative integration of HRBA, SMI, the First 1000 Days, and the MDD-W tool (Figure 8.2). Figure 8.2 Integrating four approaches to strengthen research on maternal diets and pregnancy hypertension prevention HRBA – Human Rights Based Approach; LMIC – low- and middle-income countries; MDD-W – Minimum Dietary Diversity for Women SMI – Safe Motherhood InitiativeAt the intersection between SMI and HRBA is valuing women’s health as intrinsically important. In this research, I built on SMI principles within the field of global maternal and child nutrition, by expanding the First 1000 Days approach to nutrition, and overcoming a research-advocacy gap where limited evidence on the impacts of maternal dietary interventions on women reinforced the lower prioritization of women’s health in nutrition research and recommendations. Bringing together principles of HRBA, SMI and the First 1000 Days, I called for the need to report women’s health outcomes in maternal nutrition research and interventions (59). 154 MDD-W intersects with the First 1000 Days in their shared focus on the importance ofpregnancy nutrition (449). Widely used in resource-limited global health settings, MDD-W within a rights-based lens can support reducing health inequities through strengthening data on nutritional status of WRA in LMICs. However, informed by SMI principles, the impacts of dietary diversity on women’s health has been under-represented. Bringing together MDD-W with the First 1000 Days and principles of SMI highlights the potential impacts of dietary diversity on maternal health and wellbeing. Overall, the principles of HBRA and SMI were leveraged in my research to expand the scope of the First 1000 Days and advance women-centered maternal nutrition research through use of the MDD-W tool. 8.3.2 Mixed-methods study design engaged multiple perspectives Analyses on the association between dietary diversity and pregnancy hypertension may be limited by potential measurement errors in self-reported variables, including demographics (i.e. maternal age), clinical histories (i.e. pre-gestational diabetes, chronic hypertension), and diet (i.e. reported food group consumption). Measurement errors may be random, such as when certain food groups are misunderstood across participant groups. One example is the misclassification of cabbages as a leafy green vegetable. However, there may also be differential measurement error within dietary data when groups with higher BMI under-report unhealthy food group intake due to social desirability bias. However, qualitative findings suggest that the lack of affordability was a key driver of low unhealthy food group intake, rather than avoidance of adverse health outcomes, which suggest less potential social desirability bias in this instance. Certain variables were not available in the PRECISE database at the time of analysis, including seasonality and household poverty, which result in unmeasured confounding. These measurement errors may 155 lead to groups seeming more similar than they actually are and potentially underestimate effects of nutritional exposures on study outcomes. Additionally, a limitation of the study is the potential lack of representativeness of study populations in comparison to national populations, as PRECISE Network research was conducted in specific regions in each countries and the influence of ethnicity was not taken into account in current analyses. The use of mixed-methods positioned this Dissertation to comprehensively explore maternal diet and pregnancy hypertension from a wide range of perspectives across three countries in three different regions in sub-saharan Africa. The involvement of local researchers from each of the three sub-Saharan African sites from the beginning with study design to interpretation of findings and incorporation of qualitative methods allowed for greater contextual understanding of dietary diversity results in study settings. Qualitative methods also supported better understanding of meal compositions and food intake quantities. These may partly compensate for some limitations in the MDD-W tool, which included potential social desirability bias in responses, not quantifying food intake, and limited information on the types of foods consumed in each food group. The MDD-W tool also assumed that food groups are equal in contribution, that any five food group combination is nutritionally equivalent. This Dissertation included dietary pattern analysis to understand food groups frequently missed. 8.3.3 Expanding the scope of the MDD-W tool MDD-W is widely used by national and international organizations. However, it is of note thatMDD-W privileges the diversity of certain food groups, particularly fruits and vegetables, whereFAO food sub-groups are considered individual food groups in the dietary diversity score (78). For example, green leafy vegetables is differentiated from other vitamin A-rich fruits and 156 vegetables as separate DDS food groups, which prioritizes vitamin A in the index. The main 10 food groups in MDD-W are designed to be sensitive to micronutrient adequacy, but limited in its consideration of macronutrients. Tabulating intake of each food group and exploring dietary diversity patterns can suggest macronutrient imbalances to be further explored. This Dissertation demonstrated the potential for expanded use of data already collected by the MDD-W tool, including exploring dietary patterns using latent class analysis and modifiedcriteria that incorporated unhealthy food consumption patterns. 8.3.3.1 Advanced latent class analysis for maternal dietary patterns research LCA has been described as a useful method for identifying dietary patterns among pregnant women (379,381). However, to our knowledge, this Dissertation is the first to use LCA to derive dietary diversity patterns among pregnant populations to date. LCA infers subgroups from patterns of observed variables, comprised of categorical or a mixture of categorical and continuous variables (378). There is growing interest in LCA in clinical medicine to identify phenotypes within complex medical conditions to better deliver effective and targeted therapy (378). Through rarely used for dietary pattern research, LCA is particularly suited for identifying dietary patterns related to dietary diversity (382,450–452). While PCA is frequently used as a data-driven method of deriving dietary patterns, PCA is best suited for continuous variables and reducing dimensionality by identifying axes of variation (453). PCA is not well-suited for dietary diversity data, which i) has categorical variables, such as yes/no responses to MDD-W food groups, and ii) patterns that are not entirely distinct from one another (453). For example, LCA identified high consumption patterns of grains across all three dietary patterns, which aligned with community conceptualizations of staple foods. However, because grains were not unique to 157 a single dietary pattern, it would not be considered as a principal component and grains, as a staple food, would not be identified by PCA. 8.3.3.2 Developed a modified MDD-W methodology that incorporated unhealthy food group intake The standard MDD-W criteria only summarize consumption patterns of the ten main healthy food groups. While three main unhealthy food groups were collected, MDD-W guidelines recommend only a descriptive summary of these items. This represents a limitation of the MDD-W tool and other dietary diversity instruments that do not include unhealthy food items, especially when analyses do not adjust for quantity or total energy intake, which has led to concern about potential associations between higher dietary diversity and risk of obesity and diabetes (328,329,454). This Dissertation developed a simple method using existing data collected in the MDD-W tool to incorporate unhealthy food group consumption. An assumption of this modified MDD-W methodology is that women who consume all three unhealthy food groups during the previous 24-hours have higher intake patterns than women who consumed two or less unhealthy food groups. More research is needed to evaluate this assumption and assess its association with BMI status and other health outcomes. 8.3.4 Pathways of risk between dietary diversity and pregnancy hypertension grounded in evidence of potential biological mechanisms Previous nutritional interventions to reduce pre-eclampsia incidence have largely focused on single micronutrient supplements, with many resulting in inconsistent or no significant effects (395,455). This may in part be explained by i) multiple potential nutrient-related physiological pathways described in the scoping review in Chapter 2, and ii) women with low intake in one 158 nutrient may also have low intake in other key nutrients identified in dietary patterns in Chapter 6. Women with the least diverse dietary patterns systematically missed food groups that werekey sources of vitamin B12, zinc, and calcium, of which low maternal levels have been associated with poor placental development, oxidative stress, and increased risk of hypertension. On the other hand, women with the most diverse dietary patterns were also characterized by higher consumption of fried, salty and sweetened foods and beverages, which has been associated with endothelial dysfunction and systemic inflammatory response in the development of pre-eclampsia. Moreover, as described in Chapter 7, lower rates of HDPs was only significantly associated with women who met MDD-W and had lower unhealthy food consumption, which is suggestive of multiple roles of nutrition in the progression of the pathophysiology of pre-eclampsia. To effectively reduce risk, optimal maternal diets may be protective in multiple components in the development of pre-eclampsia. While there is growing interest in dietary patterns to reduce the risk of HDPs (438,439), this research contributes to the literature by grounding its findings within current evidence of potential nutrient-related physiological pathways. 8.4 Application of research findings 8.4.1 Global health implications and recommendations While research implications and recommendations have been discussed throughout the Dissertation, in each chapter, overarching themes include: • The potential for promotion of dietary diversity in resource-limited settings, to helpprevent pregnancy hypertension,159 • Effective promotion will require context-specific strategies that include adequate accessto nutritious foods, and• Attention is needed to raising awareness about unhealthy foods.8.4.2 Strengthening maternal nutrition in Kilifi, Kenya: A knowledge mobilization workshop with Kenyan Department of Health Application of research findings was demonstrated by knowledge translation and mobilization activities within this Dissertation. Working with the PRECISE Kenyan team and Kilifi County Department of Health partners, we planned the Maternal Nutrition Stakeholders Meeting in Kilifi, Kenya on July 18th 2023. The meeting aimed to disseminate findings from this thesis work and provide a space for discussions around how the results could be applied in their work. Key components of the workshop included: • Meeting leadership by Kilifi Department of Health officials to emphasize localownership. The meeting was chaired by the Kilifi County Nutrition Coordinator, andSub-County Community Health Strategy Focal Person.• Targeted engagement of Sub-County Department of Health officers to highlight regionalcontext and strategies. The workshop convened 18 Department of Health officials,including Medical Officers of Health, Community Health Strategy Focal Persons, PublicHealth Officers, Health Promotion Officers, Health Records and Information Officers,Public Health Nurses, Nutrition Coordinators and Reproductive Health Coordinatorsfrom each of the two sub-counties (Figure 8.3).160 • Unique dissemination meeting format where participants spent the majority of the day indiscussion. After presentation of the results, participants discussed key findings relevantto their portfolios and potential strategies that could be incorporated into existingprogramming in small groups. The feasibility of each strategy was then discussed in thelarge group. Finally, ideas were ranked in terms of implementation and impact potentialusing an audience interaction platform (Sli.do).Figure 8.3 Participants of the Maternal Nutrition Stakeholders Meeting held in Kilifi, Kenya on July 18th 2023 Outputs of the workshop included health officials taking ownership of findings and implementing a small intervention to promote maternal nutrition through Maternity Open Days. The intervention leveraged existing Department of Health programs and their networks of community health promoters (CHPs). 161 The intervention had two phases: 1. An open forum for community health promoters in Mariakani, Kenya on Feb 23, 2024and attended by 42 CHPs (Figure 8.4). The forum included pregnancy nutritioneducation for CHPs and engaging CHPs to map pregnant mothers in their catchment area.Pregnant mothers would then be mobilized by CHPs to attend to Maternity Open Days.2. Two Maternity Open Days in Rabai and Mariakani Hospitals in March 2024 that includenutritional counselling and education, as well as maternity facilities tours to familiarizewomen with local services and healthcare providers, and the "Linda Mama" freematernity program.Figure 8.4 Community Health Promoters Open Forum in Mariakani on Feb 23rd 2024 162 8.4.3 Recommendations for future research This Dissertation has highlighted the potential protective effect of meeting MDD-W alongside lower consumption patterns of unhealthy food groups on reducing risks of pregnancy hypertension. Future research should consider the potential relationship with various forms of malnutrition, explore early and late onset of pre-eclampsia and identify biomarkers for nutrient-related pathways of risk. There is growing concern about a triple burden of malnutrition among women of reproductive age (411–413). The co-existence of under- and overnutrition alongside micronutrient deficiencies was suggested in dietary pattern analysis in this Dissertation, which aligns with reports of underweight in 10% of women in sub-Saharan Africa, overweight/obese in 21%, anemia in 41% and all three forms of malnutrition together in 5% of households (413). Malnutrition disproportionately impacts women in sub-Saharan Africa, where it widens the gender and socio-economic health gap (458). A 2018 publication of pregnant women in South Africa and Zimbabawe at high risk of pre-eclampsia found a high prevalence of overweight and obesity alongside inadequate micronutrient intakes (459), but literature continues to be limited. Evidence around nutritional approaches for pre-eclampsia prevention have not frequently differentiated between early (<34 weeks gestation/preterm) and late (≥34 weeks gestation/term) forms of pre-eclampsia or investigated postpartum pre-eclampsia, which may be differently impacted by various forms of malnutrition. Certain micronutrient deficiencies may have a greater impact on abnormal placental development, as frequently found in early onset pre-eclampsia, while obesity may exacerbate maternal cardiovascular factors that increase the likelihood of late 163 onset pre-eclampsia (394,460). The rising rates of obesity across sub-Saharan Africa (461–463) highlights the need to examine different forms of pre-eclampsia and other HDPs. Evaluating biomarkers may clarify nutrient-related pathways of risk within the context of various forms of malnutrition and pre-eclampsia, as well as how pre-eclampsia may connect to other placental disorders of pregnancy, including fetal growth restriction, preterm birth and stillbirth. There is currently limited literature on the association between dietary diversity status and nutritional biomarkers. To date, there is a study from Mozambique with non-pregnant adolescent girls that evaluated circulating hemoglobin, serum ferritin, serum zinc, serum folate, and plasma retinol, and found that low serum zinc was associated with low dietary diversity status at certain times of the year (464). Another study from India with adolescent boys and girls assessed dietary diversity in association with hemoglobin, plasma vitamin B12 and plasma folate, and found that unmet minimum dietary diversity was associated with low vitamin B12 (465). However, associations between dietary diversity status and nutritional biomarkers among maternal populations is a current gap in the literature. An evidence review found maternal serum concentrations of 25(OH)D (as a marker of vitamin D status), iron (iron, ferritin, and transferrin as markers of iron status), zinc, selenium, vitamin C, E and B12 were associated with the development of pre-eclampsia (368). Improved understanding of biomarkers may support resolving uncertainty posed by differing results across nutrition and pre-eclampsia studies (368,394,395), and facilitate prediction and preventation of various forms of pre-eclampsia. Understanding of overall biomarkers for late-onset pre-eclampsia, including diet-related biomarkers, is currently very limited (466). Further research into biomarkers of dietary intake 164 may improve the effectiveness and precision of nutritional interventions for pre-eclampsia in resource-limited settings. 8.5 Conclusions This Dissertation has highlighted the significance of maternal nutrition for women's health outcomes, and expands beyond the conventional focus on child health outcomes in the First 1000 Days approach to nutrition for pregnant populations and young children. Recognizing local cultural contexts where preparing food for the household is considered women’s domain, efforts to strengthen maternal diets may be a way for transformative women’s empowerment. Insights into the specific pathways linking nutrition to pregnancy hypertension in sub-Saharan Africa and working with local health officials to develop strategies for knowledge mobilization has the potential to reduce maternal mortality and morbidity in a region disproportionately affected by this condition. 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Am J Obstet Gynecol. 2019Dec;221(6):563–76.469. Cai C, Vandermeer B, Khurana R, Nerenberg K, Featherstone R, Sebastianski M, et al.The impact of occupational activities during pregnancy on pregnancy outcomes: a systematicreview and metaanalysis. Am J Obstet Gynecol. 2020 Mar;222(3):224–38.205 Appendices A.1 List of other PhD publications and presentations (all-encompassing) Refereed publications 1. Elawad T, Scott G, Bone JN, Elwell H, Lopez CE, Filippi V, Green M, Khalil A, Kinshella ML, Mistry HD, Pickerill K, Shanmugam R, Singer J, Townsend R, Tsigas EZ, Vidler M, Volvert ML, von Dadelszen P, Magee LA; PRECISE Network. Risk factors for pre‐eclampsia in clinical practice guidelines: Comparison with the evidence. BJOG: An International Journal of Obstetrics & Gynaecology. 2024 Jan; 131 (1): 46-62. https://doi.org/10.1111/1471-0528.17320 2. Kinshella ML, Pickerill K, Bone JN, Prasad S, Campbell O, Vidler M, Craik R, Volvert ML, Mistry HD, Tsigas E, Magee LA. An evidence review and nutritional conceptual framework for pre-eclampsia prevention. British Journal of Nutrition. 2023 Sep 28;130(6):1065-1076 https://doi.org/10.1017/S0007114522003889 3. Kinshella ML, Sarr C, Sandhu A, Bone JN, Vidler M, Moore SE, Elango R, Cormick G, Belizan JM, Hofmeyr GJ, Magee LA. Calcium for pre‐eclampsia prevention: A systematic review and network meta‐analysis to guide personalised antenatal care. BJOG: An International Journal of Obstetrics & Gynaecology. 2022 Oct; 129: 1833– 1843. https://doi.org/10.1111/1471-0528.17222 4. Kinshella ML, Omar S, Scherbinsky K, Vidler M, Magee LA, von Dadelszen P, Moore SE, Elango R, PRECISE Conceptual Framework Working Group. Effects of maternal nutritional supplements and dietary interventions on placental complications: an umbrella review, meta-analysis and evidence map. Nutrients. 2021 Jan; 13(2):472. https://doi.org/10.3390/nu13020472 5. Kinshella ML, Moore S, Elango R. Beyond reproduction: The First 1,000 Days approach to nutrition through a gendered rights-based lens. Health and Human Rights. 2020 Dec; 22(2):113-123. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7762907/ 6. Donnay F, Kinshella ML, Flint-O’Kane M, von Dadelszen P, Magee L, Vidler M. Investigating placental disorders of pregnancy in sub-Saharan Africa: addressing the gap in a neglected area of research. Reproductive Health. 2020 Apr;17(Suppl 1):53. https://doi.org/10.1186/s12978-020-0871-x Non-refereed publications 1. Kinshella ML. What do we know? Creating an effective understanding of nutrition and preeclampsia. Pre-eclampsia Foundation. 2023, Mar 23. Available from: 206 https://www.preeclampsia.org/the-news/health-information/what-do-we-know-creating-an-effective-understanding-of-nutrition-and-preeclampsia 2. Cormick G, Hofmeyr GJ, Kinshella ML, Von Dadelszen P, Belizán JM, Magee LA. Saving lives and promoting health equity: an urgent call to action for universal mandatory food fortification with calcium. The Lancet Global Health. 2022 Oct; 10 (10): E1393. https://doi.org/10.1016/S2214-109X(22)00383-7 3. Kinshella ML, Rogers C, Poye L. Could vitamin B12 deficiency and preeclampsia/HELLP syndrome be related? Pre-eclampsia Foundation. 2021, Jun 14. Available from: https://preeclampsia.org/the-news/ask-an-expert/could-vitamin-b12-deficiency-and-preeclampsiahellp-syndrome-be-related 4. Kinshella ML. Reflections on Women Deliver 2019: It’s time to move beyond individualistic gender empowerment. International Health Policies Blog. 2019, Jun 13. Available from: https://www.internationalhealthpolicies.org/blogs/reflections-on-women-deliver-2019-its-time-to-move-beyond-individualistic-gender-empowerment/ Oral presentations 1. Kinshella ML, Koech A, Boene H, Jah H, Sandu A, Bone JN, Craik R, Volvert ML, Mistry HD, Temmerman M, Sevene E, Roca A, D’Alessandro U, von Dadelszen P, Magee LA, Vidler M, Moore SE, Elango R, the PRECISE Network. Pregnancy hypertension and maternal dietary diversity among women in Kenya, Mozambique and The Gambia: A PRECISE Network study. Presented at: Perinatal Child Health Research Annual Meeting (CNRPM 2024), 2024 June 2-7; Vancouver, Canada 2. Kinshella ML. Pregnancy hypertension and maternal dietary diversity in three sub-Saharan African countries: the importance of considering unhealthy food group consumption patterns. Presented at: UBC Obstetrics and Gynaecology Research Day; 2024 May 8; Vancouver, Canada 3. Kinshella ML, Maternal diet and pregnancy hypertension in sub-Saharan Africa. Invited presentation at: Women+ and Child Health Research Day; 2024, April 16; Vancouver, Canada 4. Kinshella ML. Strengthening maternal nutrition in Kilifi, Kenya: A knowledge mobilization workshop with Kenyan Department of Health. Presented at: Women’s Health Research Cluster Trainee Research Presentations; 2024 March 27; Vancouver, Canada. 5. Kinshella ML. Dietary diversity among pregnant and non-pregnant women of reproductive age in Kenya, The Gambia, and Mozambique: a mixed methods study. Invited presentation at: The Rank Symposium on The Impact of Nutrition During Pregnancy on Maternal Health; 2023 July 10-13; Grasmere, United Kingdom. 207 6. Kinshella ML, Koech A, Wanje O, Mwashigadi G. Maternal Nutrition Stakeholders Meeting. Stakeholders presentation to Kenyan Department of Health; 2023 Jul 18; Kilifi, Kenya. 7. Wanje O, Kinshella ML, Koech A, Mwashigadi G, Naanyu V, Elango R, Moore SE, Temmerman M, PRECISE Network. Barriers and facilitators to an adequate maternal diet in Kilifi County: Amplifying the voices of women through photovoice. Presented at: 2nd Kilifi County Scientific Symposium; 2023 Nov 16-17; Kilifi, Kenya. 8. Kinshella ML. Investigating the relationship between maternal diets and pregnancy hypertension in sub-Saharan Africa. Invited presentation at: PRECISE Network Retreat; 2023 March 13-15; London, UK 9. Kinshella ML, Pickerill K. A conceptual framework for the determinants of pre-eclampsia. Invited presentation at: PRECISE Network Retreat; 2023 March 13-15; London, UK. 10. Kinshella ML. A mixed methods approach to investigating maternal diet and pregnancy hypertension in sub-Saharan Africa. Presented at: Origins of Child Health and Disease Work in Progress Seminar, BC Children’s Hospital Research Institute; 2023 January 11; Vancouver, Canada. 11. Pickerill K, Ard Q, Elia A, Reyes S, Viray C, Witmer C, Mateljan V, Nelson K, Rogers C, Kinshella ML, Craik R, Elwad T, Hiten M, Volvert ML, von Dadelszen P, Magee LA, Vidler M, Tsigas E. The social determinants of health as risk factors for pre-eclampsia: Evidence from a pre-eclampsia conceptual framework. Presented at: 23rd World Congress of the International Society for the Study of Hypertension in Pregnancy (ISSHP); 2022, August 28-31; Montpellier, France. 12. Kinshella ML, Wanje O, Dama S, Koech A. Barriers and facilitators to an adequate maternal diet: Preliminary findings from the PRECISE Nutrition Qualitative Sub-Study in Kenya; Presented at: PRECISE Network Symposium; 2022 Jun 17; virtual. 13. Kinshella ML. PRECISE Network: maternal diet and pre-eclampsia. Presented at: PRECISE Network Symposium; 2022 March 22; virtual. 14. Kinshella ML. A human rights-based lens to exploring conceptualizations of gender and motherhood within the First 1,000 Days approach to nutrition. Presented at: Women’s Health Research Institute Research Trainee Seminar; 2020 August 20; Virtual, based in Vancouver, Canada. 15. Kinshella ML. Maternal dietary patterns and risk of pregnancy hypertension in low- and middle-income countries (LMICs): A systematic review in progress. Presented at: 208 Origins of Child Health and Disease Work in Progress Seminar, BC Children’s Hospital Research Institute; 2020 June 16; Vancouver, Canada. 16. Kinshella ML. Beyond reproduction: The First 1,000 Days approach to nutrition through a gendered rights-based lens. Presented at: 2020 Conference of the Society for Medical Anthropology; 2020 March 9-12; Havana, Cuba. 17. Kinshella ML. The First 1,000 Days approach to nutrition through a rights-based lens: gaps and opportunities for gender and health equity. Presented at: 25th Canadian Conference on Global Health; 2019 October 17-19; Ottawa, Canada. 18. Kinshella ML. Maternal diet and pre-eclampsia risk in global health settings: a scoping review. 2019 GLOW (Global Women's Research Society) Conference; 2019 September 10; London, UK Poster presentations 1. Kinshella ML, Koech A, Boene H, Jah H, Sandu A, Bone JN, Craik R, Volvert ML, Mistry HD, Temmerman M, Sevene E, Roca A, D’Alessandro U, von Dadelszen P, Magee LA, Vidler M, Moore SE, Elango R, the PRECISE Network. Considering intake of unhealthy foods within the Minimum Dietary Diversity for Women (MDD-W) index: examining the association between maternal dietary diversity and pregnancy hypertension in sub-Saharan Africa. Poster presented at: Canadian Nutrition Society Annual Conference; 2024, May 2-4; Edmonton, Canada 2. Kinshella ML, Moore SE, Elango R. Determinants of dietary diversity among pregnant and non-pregnant women of reproductive age in sub-Saharan Africa. Poster presented at: Healthy Starts Research Day, BC Children’s Hospital Research Institute; 2024 February 1; Vancouver, Canada 3. Kinshella ML, Koech A, Wanje O, Mwashigadi G, Naanyu V, Elango R, Moore S and Temmerman M. Community perspectives of healthy diets for pregnant women and influencing factors: A PRECISE qualitative study in Kilifi, Kenya. Poster presented at: The Aga Khan University PRECISE Network Dissemination Meeting; 2023 February 14; Kilifi, Kenya. 4. Kinshella ML, Sarr C, Sandhu A, Bone J, Vidler M, Moore SE, Elango R, Cormick G, Belizan J, Hofmeyr GJ, von Dadelszen P, Magee LA and the PRECISE Conceptual Framework Working Group. Systematic review and network meta-analysis on calcium for pre-eclampsia prevention. Poster presentation at: XXIII FIGO (The International Federation of Gynecology and Obstetrics) World Congress of Gynecology and Obstetrics; 2021 October 21-28; virtual. 209 5. Kinshella ML, Omar S, Scherbinksy K, Vidler M, Magee L, von Dadelszen P, Moore SE, Elango R. Maternal dietary patterns and pregnancy hypertension in low- and middle-income countries: a systematic review and meta-analysis. Poster presentation at: Global Health Conference; 2021 January 28; Vancouver, Canada. 6. Kinshella ML, Omar S, Scherbinksy K, Vidler M, Magee L, von Dadelszen P, Moore SE, Elango R. Do maternal dietary patterns influence women’s risk of pre-eclampsia in low- and middle-income countries? A systematic review. Poster presentation at: Keystone Symposia: Optimizing Nutrition for Maternal, Newborn and Child Health; 2020 October 23; virtual/Denver, United States. 7. Kinshella ML, Moore S, Elango R. Missing focus on mothers in the First 1000 Days approach to nutrition. Poster presentation at: Healthy Starts Research Day, BC Children’s Hospital Research Institute; 2020 February 5; Vancouver, Canada. 8. Kinshella ML. Global health, maternal nutrition and risk of pre-eclampsia: a literature review. Poster presentation at: Building the Future: Faculty of Medicine Research Trainee Day & Lecture Series; 2019 April 3; Vancouver, Canada 210 Chapter 1 appendix for the introduction and methods B.1 Semi-structured interview guide for in Swahili for Kenya Demographic and opening questions Maswali tangulizi 1. Do you have any children? Je una watoto wowote? - Boys? Girls? How old are they? - Wavulana? Wasichana? Wana umri gani? 2. Did you grow up in this community? Je ulikua katika jamii hii? - Do you have family members in this community? - Je una wanafamilia katika jamii hii? - For those not born in the community: When did you come here? Why did you move here? (i.e. marriage, economic opportunity, family etc.) Kwa wale ambao hawakuzaliwa kwa jamii hii: je ulihamia hapa lini? Kwa nini ulihamia hapa? ( ndoa, fursa ya kiuchumi, familia na mengineo.) 3. What is your ethnic background? Wewe ni wa asilia gani? 4. How old are you? Una umri gani? 5. Did you attend any schooling? Je ulihudhuria shule yoyote? - If so, how many years of school did you complete? - Ikiwa ni hivyo, ulikamilisha miaka ngapi ya shule. 6. What do you do for a living? Unafanya kazi gani? - How much do you typically earn in a day? - Unapokea malipo/mapato kiasi gani kwa siku? 7. Are you currently married? Je Umeoa kwa sasa? - If not: single, unmarried partner, divorced, widowed? - Ikiwa sivyo, hujaoa, uko na mpenzi, talaka, mjane? - If married: what does your spouse do for a living? How much do they typically earn in a day? Do they work in the community or have to travel away for work? - Ikiwa umeolewa: je mwenzi wako anafanya kazi gani? Unapata kiasi gani kwa siku? Anafanya kazi katika jamii au lazima wasafiri kwenda kazini? 8. Can you describe a typical day for you? Unaweza kuelezea siku ya kawaida kwako? Local diets and food patterns Mfumo wa lishe na vyakula 211 9. Please tell me about the typical meals people eat in this community Tafadhali nieleze kuhusu chakula cha kawaida ambacho watu hula katika jamii hii - What meals do people usually eat everyday in the morning, afternoon and evening? - Ni chakula gani watu hula kila siku asubui, mchana na jioni - Are different foods and meals people eat at different times of the year? - Kuna vyakula na milo tofauti watu hula kwa nyakati tofauti za mwaka. - Are there any foods or meals that women eat especially during pregnancy, delivery, when they are breastfeeding? - Kuna chakula chochote ama milo ambayo wamama hula hasa wakati wa ujauzito, kujifungua, wakati wanapo nyonyesha? I’m going to go through a list of different food groups and I would like you to tell me what foods are commonly eaten in this community: Nitapitia orodha ya aina tofauti ya chakula na ningependa uniambie ni vyakula gani kawaida huliwa katika jamii hii: 10. Are eggs eaten here? Je mayai huliwa hapa? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au hailiwi mara kwa mara (chini ya mara moja kwa wiki)? - Do you eat more eggs in certain months or are they eaten around the year? If in certain months, which months? - Unakula mayai Zaidi katika miezi Fulani au huliwa karibu mwaka mzima? Ikiwa katika miezi fulani ni miezi ipi? - Do pregnant women eat these foods? Why or why not? - Je akina mama wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 11. Is meat and chicken eaten here, including organ meats? What types? Je nyama na kuku huliwa hapa, pamoja na nyama ya viungo? Aina gani? - How frequently for red meats (i.e. Beef, pork, lamb, goat, rabbit, wild game meat), organ meats (i.e. kidney, liver), and poultry (i.e. chicken, duck, any birds)? Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Ni mara ngapi kwa nyama nyekundu( mfano nyama ya ng’ombe, nguruwe, mwana kondoo, mbuzi,sungura, nyama ya porini), nyama ya viungo( figo, ini), na ndege ( mfano kuku, bata, ndege yoyote)? Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya wiki moja)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Unakula Zaidi ya vyakula hivi katika miezi fulani au huliwa karibu mwaka mzima? Ikiwa katika miezi fulani ni miezi ipi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 12. Is fish and other seafood eaten here? What types? Je samaki na wanyama wengine wa baharini huliwa hapa? Aina gani? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? 212 - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki) - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Unakula Zaidi ya vyakula hivi katika miezi fulani au huliwa karibu mwaka mzima? Ikiwa katika miezi fulani ni miezi ipi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 13. Is low fat-fat dairy like milk, cheese, yoghurt or other milk products (NOT butter, cream or sour cream) eaten here? What types? Je, vyakula vinavyotokana na maziwa lakini vyenye kiasi kidogo tu cha mafuta kama vile: maziwa, jibini, mgando (maziwa mala/ maziwa lala) au bidhaa zingine za maziwa (sio siagi, siki au krimu iliyoganda) huliwa hapa? Aina gani? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki) - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Unakula Zaidi ya vyakula hivi katika miezi fulani au huliwa karibu mwaka mzima? Ikiwa katika miezi fulani ni miezi ipi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 14. Are nuts and seeds like, ground nut, peanut, cashew nuts or certain seeds or nut/seed "butters" or pastes eaten here? What types? Je karanga na mbegu kama njungu, karanga, korosho au mbegu fulani au karanga/siagi za mbegu au pastes huliwa hapa? Aina gani? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki) - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Unakula Zaidi ya vyakula hivi katika miezi fulani au huliwa karibu mwaka mzima? Ikiwa katika miezi fulani ni miezi ipi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 15. Are peas, green grams, lentils and beans eaten here? What types? Je njegere, pojo, mbaazi , lenti na maharagwe huliwa hapa? Aina gani? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki) - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Unakula Zaidi ya vyakula hivi katika miezi fulani au huliwa karibu mwaka mzima? Ikiwa katika miezi fulani ni miezi ipi? - Do pregnant women eat these foods? Why or why not? 213 - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 16. Are cruciferous vegetables like cabbage and kale and dark green leafy vegetable eaten here? What types? Je mboga kama kabichi na sukumawiki, mchicha na mboga za kijani kibichi, huliwa hapa? Aina gani? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Unakula Zaidi ya vyakula hivi katika miezi fulani au huliwa karibu mwaka mzima? Ikiwa katika miezi fulani ni miezi ipi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 17. Are white roots and tubers like Cassava, sweet potatoes, Irish potatoes, arrow roots) or plantains eaten here? What types? Je, vyakula vya mizizi mieupe (kama mihogo, viazi vitamu, viazi irish, nduma) au ndizi ya kupikwa huliwa hapa? Aina gani? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Unakula Zaidi ya vyakula hivi katika miezi fulani au huliwa karibu mwaka mzima? Ikiwa katika miezi fulani ni miezi ipi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 18. Are vegetables or roots that are orange-coloured inside like carrots pumpkin, squash and sweet potatoes eaten here? What types? Je mboga au mizizi ambayo ina rangi ya machungwa ndani kama karoti, malenge, ‘butternut’ na viazi vitamu (vya manjano) huliwa hapa? Aina gani? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Unakula Zaidi ya vyakula hivi katika miezi fulani au huliwa karibu mwaka mzima? Ikiwa katika miezi fulani ni miezi ipi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 19. Any other types of vegetables are eaten here that we have not mentioned? Aina nyingine yoyote ya mboga huliwa hapa ambayo hatujataja. - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki)? 214 - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Unakula Zaidi ya vyakula hivi katika miezi fulani au huliwa karibu mwaka mzima? Ikiwa katika miezi fulani ni miezi ipi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 20. Are other fruits that are dark yellow or orange eaten here? like ripe mango, ripe papaya What types? Aina nyingine yoyote ya matunda ambayo yako rangi ya manjano/chungwa iliyokolea huliwa hapa? Kama embe iliyoiva, papai iliyoiva. Aina gani? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Unakula Zaidi ya vyakula hivi katika miezi fulani au huliwa karibu mwaka mzima? Ikiwa katika miezi fulani ni miezi ipi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 21. Any other types of fruits are eaten here that we have not mentioned? Aina nyingine yoyote ya matunda huliwa hapa ambayo hatujataja - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Unakula Zaidi ya vyakula hivi katika miezi fulani au huliwa karibu mwaka mzima? Ikiwa katika miezi fulani ni miezi ipi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 22. What kinds of sweets are eaten here, if any? Ni aina gani ya peremende (au vyakula vyenye sukari) huliwa hapa, ikiwa ipo? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki)? - When would people eat these foods? - Ni lini watu wangekula vyakula hizi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 23. Fried snacks and savoury snacks in packets, fast/street foods like potato crisps, Lays, Kachiri Vitafunio vya kukaanga na vitafunio vitamu kwenye pakiti, vyakula vya haraka/vya barabarani kama kachiri ya viazi - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki)? 215 - When would people eat these foods? - Ni lini watu wangekula vyakula hizi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 24. Refined grains and baked goods like cake, biscuits, puffs Nafaka iliyosafishwa na bidhaa zilizooka kama keki, biskuti - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki)? - When would people eat these foods? - Ni lini watu wangekula vyakula hizi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 25. Sugar-sweetened fizzy drinks? Like Coca Cola, Fanta, afya drink, club soda Vinywaji vya sukari vya kupendeza? Kama cocacola, fanta, kinywaji cha afya,club soda - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki)? - When would people eat these foods? - Ni lini watu wangekula vyakula hizi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? 26. Any other foods people eat here that we have not mentioned? Chakula kingine chochote watu hula hapa ambacho hatujataja? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Huliwa mara kwa mara (angalau mara moja kwa wiki) au si mara nyingi (chini ya mara moja kwa wiki)? - When would people eat these foods? - Ni lini watu wangekula vyakula hizi? - Do pregnant women eat these foods? Why or why not? - Je wanawake wajawazito hula chakula hizi? Kwanini au kwanini sivyo? Food provisioning and meals Upeanaji wa vyakula na mlo 27. Where do you get your food from? How far do you have to travel to get your food? Unatoa wapi chakula chako? Una safiri kwa umbali gani ili kupata chakula chako? - Who goes to get the food items in your family and how far do they have to travel for it? Are there different places for different types of food? Nani huendea vyakula katika familia yako na huviendea kwa umbali gani? Je kuna mahali tofauti kwa vyakula tofauti - How do you/people in this community store food? Je! Wewe au watu katika jamii hii mnahifadhi kivipi chakula? 216 - How many hours of your day do you (or your family member) spend getting, preparing and cooking food and cleaning after meals? Je! Wewe (au mwanafamilia wako) unatumia masaa mangapi ya siku yako kupata, kutayarisha na kupika chakula na kusafisha baada ya kula? - Does any of these daily activities change when a woman is pregnant or caring for a young infant? Je! Kuna mabadiliko ya shughuli zozote za kila siku pindi mwanamke anakua mjamzito au analea mtoto mchanga? 28. Please share how meals are eaten in your family Tafadhali eleza jinsi chakula huliwa katika familia yako. - Where does your household eat meals? Does everyone eat together? Je! Jamii yako hula chakula wapi? Je! Kila mtu hula pamoja? - Do certain family members eat first? Je! Kuna baadhi wa wanafamilia wanaotangulia kula baada ya wengine? - Does everyone in the family eat the same meal? If not, how does it differ and for who? Je Kila mtu katika familia hula chakula sawa? Ikiwa si hivyo, kinatofautiana vipi na kwa nani? 29. Has food and food related activities changed in your lifetime? Je! Chakula na shughuli zinazohusiana na chakula na zimebadilika katika maisha yako? - Do you eat the same food as your parents? Your grandparents? If not, what has changed and why. Je unakula chakula sawa na wazazi wako? Babu au Bibi yako? Ikiwa sivyo, nini kimebadilika na kwanini? - Has anything changed in where you get your food, how you store your food items and how you cook? When has these changes happened and why? Kuna chochote kimebadilika mahali ambapo unapata chakula chako, jinsi unahifadhi chakula chako na jinsi unapika? Je! Mabadiliko haya yametokea lini na kwanini? Local perspectives on food and healthy diets Mitazamo ya kienyeji juu ya chakula na lishe bora 30. Are there any foods or meals that are associated to your ethnic group? Je! Kuna vyakula ambavyo vinahusishwa na kabila lako au watu wa asilia yako? - What are your traditional foods that people eat in your community? Do people still eat this? If not, why? Je! Ni vyakula gani vya kitamaduni ambavyo watu hula katika jamii yako? Je! Watu bado wanakula hivi? Ikiwa sivyo, kwa nini? - What are favourite foods or meals that people in this community would eat everyday if they could? Je! Ni vyakula gani pendwa ambavyo watu katika jamii hii wangekula kila siku ikiwa wangeweza? - Are there any foods that people in this community do not eat? Why? (if they simply reply that it’s culture, try to probe deeper) Je, kuna vyakula vyovyote ambavyo haviliwi na watu katika jamii hii? Mbona? (Wakipeana sababu kuwa ni kwa ajili ya mila, uliza Zaidi) 217 - Are there any stories or beliefs in this community about foods that pregnant and/or lactating mothers should eat? Why? Je! Kuna hadithi au imani yoyote katika jamii hii juu ya vyakula ambavyo mama wajawazito na / au wanaonyonyesha wanapaswa kula? Mbona? - Are there any stories or beliefs in this community about foods that pregnant and/or lactating mothers should not eat? Why? Je! Kuna hadithi au imani yoyote katika jamii hii juu ya vyakula ambavyo mama wajawazito na / au wanaonyonyesha hawapaswi kula? Mbona? 31. What does a healthy meal mean to you? What makes a meal healthy? Why? Je! Lishe bora ina maana gani kwako? Ni nini hufanya lishe kuwa bora? Kwa nini? - What is needed to make a meal considered complete? (i.e. if this food item is missing, then the meal is not complete) Je! Ni nini kinachohitajika ili kufanya mlo uzingatiwe kuwa kamili? (yaani ikiwa chakula hiki hakipo, basi chakula hakijakamilika) 32. What foods/meals do you think is healthy for pregnant women to eat? Why? Where did you learn this from? Je! Unadhani ni vyakula / mlo gani bora kuliwa na wanawake wajawazito? Kwa nini? Ulijifunza hii kutoka wapi? 33. What foods/meals do you think is healthy for a woman who is breastfeeding to eat? Why? Where did you learn this from? Je! Unadhani ni vyakula / mlo gani bora kuliwa na wanawake wanaonyonyesha? Kwa nini? Ulijifunza hii kutoka wapi? Barriers and facilitators to adequate maternal diets and health Vizuizi na wawezeshaji kwa lishe ya kutosha ya mama na afya 34. In your opinion, do you think pregnant and breastfeeding women in this community are able to eat enough food? Eat enough healthy meals? Why or why not? Kwa maoni yako, unafikiri wanawake wajawazito na wanaonyonyesha katika jamii hii wanaweza kula chakula cha kutosha? Kula lishe bora ya kutosha? Kwanini au kwanini isiwe? - What do you think are the key problems that happen when women do not get enough healthy food to eat? Unafikiria ni shida gani kuu zinazotokea wakati wanawake hawapati kula lishe bora na ya kutosha? - In your opinion, is there a relationship between the food a woman eats and getting high blood pressure during pregnancy? Kwa maoni yako, kuna uhusiano wowote kati ya chakula anachokula mama na kupata shinikizo la damu wakati wa ujauzito? 35. During the last 12 months, was there a time when, because of lack of money or other resources (probe for examples and stories if possible) Katika miezi 12 iliyopita, kulikuwa na wakati ambapo, kwa sababu ya ukosefu wa pesa au rasilimali zingine (tafuta mifano na hadithi ikiwezekana) - You were worried you would not have enough food to eat? Ulikuwa na wasiwasi hautakuwa na chakula cha kutosha kula? - You were unable to eat healthy and nutritious food? Haukuweza kula lishe bora na chakula chenye afya? 218 - You ate only a few kinds of foods? Ulikula aina chache tu za vyakula? - You had to skip a meal? Ilibidi ukose kula? - You ate less than you thought you should? Ulikula kidogo ya ulivyodhania? - Your household ran out of food? Nyumbani kwako kulikosa chakula? - You were hungry but did not eat? Ulikuwa na njaa lakini haukula? - You went without eating for a whole day? Ulienda bila kula kwa siku nzima? 36. What do women do when there is not enough food in their homes? Je! Wanawake hufanya nini wakati hakuna chakula cha kutosha majumbani mwao? - Do mothers change their eating (i.e. eat less) so other people in their families can eat more? Prioritize food for which family members? Je! Akina mama hubadilisha ulaji wao (yaani kula kidogo) ili watu wengine katika familia zao waweze kula zaidi? Hupa kipaumbele chakula kwa wanafamilia gani? - What coping strategies employed? Je! Kuna mikakati gani ya kukabiliana? - Do people gossip and talk bad about women/ households if they know a household cannot get enough food or if a child looks hungry? Je! Watu husengenya na kusema vibaya juu ya wanawake / nyumba ikiwa wanajua nyumba haiwezi kupata chakula cha kutosha au ikiwa mtoto anaonekana ana njaa? 37. In your opinion, what helps women have enough food? Kwa maoni yako, nini husaidia wanawake kupata chakula cha kutosha? - For their household Kwa nyumba zao - For themselves Kwao wenyewe 38. In your opinion, what helps women to have good health during their pregnancy, delivery and caring for their young infant? Kwa maoni yako, ni nini kinachosaidia wanawake kuwa na afya nzuri wakati wa uja uzito wao, kujifungua na kulea watoto wao wachanga? Closing Kufunga 39. Is there anything else you would like to tell me that we have not already discussed? Je! Kuna kitu kingine chochote ungependa kuniambia ambacho hatujazungumzia tayari? Thank participants for their contribution. Shukuru washiriki kwa mchango wao. 219 B.2 Semi-structured interview guide in Portuguese for Mozambique Perguntas demográficas e de abertura 1. Você tem filhos? - Meninos? Meninas? Quantos anos têm? 2. Você cresceu nessa comunidade? - Você tem familiares na comunidade? - Para aqueles que não nasceram aqui: Quando se mudou? Por que se mudou? (Por exemplo, casamento, oportunidades econômicas, família, etc.) 3. Qual sua origem étnica? 4. Quantos anos tens? 5. Frequentou a escola? - Se sim, quantos anos completou? 6. Com o que trabalha? - Quanto, em média, ganha em um dia? 7. Você está casado? - Se não: solteiro, tem parceiro mas não está casado, separado, viúvo? - Se sim, com o que seu cônjuge trabalha? Quanto, em média, ele ganha em um dia? 8. Descreva um dia típico para você. Nutrição local e padrões alimentícios 9. Fale um pouco sobre pratos típicos desta comunidade. - O que as pessoas costumam comer de manhã, de tarde e de noite? - Há comidas e pratos diferentes em diferentes partes do ano? - Há comidas ou pratos que mulheres grávidas comem especialmente durante a gestação, parto ou amamentando? Agora, vou perguntar sobre alguns grupos alimentícios e gostaria que me dissesse quais deles são frequentemente consumidos 10. Ovos. São consumidos? - Com que frequência (pelo menos uma vez por semana) ou menos que uma vez por semana? - Comem mais ovos em certos meses ou são consumidos no ano inteiro? Se em meses específicos, quais meses? - Mulheres grávidas consomem ovos? Por que ou por que não? 11. São consumidas carne de boi e de frango, incluindo órgãos? Que tipos? - Com que frequência carnes vermelhas (por exemplo porco, gado, cordeiro, bode, cabra, coelho ou animais selvagens), órgãos (rim ou fígado, por exemplo), ou aves(frango, pato ou outros)? Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Esses alimentos são consumidos em meses específicos ou no ano inteiro? Em quais meses? - Grávidas costumam comer esse tipo de alimento? Por quê? 12. Peixes e frutos do mar são consumidos? Quais tipos? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Esses alimentos são consumidos em meses específicos ou no ano inteiro? Em quais meses? 220 - Grávidas costumam comer esse tipo de alimento? Por quê? 13. São consumidos laticínios de baixa gordura, como por exemplo leite, queijo, iogurte e outros produtos derivados do leite (sem contar manteiga, creme de leite ou nata). Que tipos? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Esses alimentos são consumidos em meses específicos ou no ano inteiro? Em quais meses? - Grávidas costumam comer esse tipo de alimento? Por quê? 14. Nozes, frutos secos, amendoins, sementes e nozes/sementes em cremes ou pastas, são consumidos? Que tipos? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Esses alimentos são consumidos em meses específicos ou no ano inteiro? Em quais meses? - Grávidas costumam comer esse tipo de alimento? Por quê? 15. Ervilhas, lentilhas feijões são consumidos? Que tipos? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Esses alimentos são consumidos em meses específicos ou no ano inteiro? Em quais meses? - Grávidas costumam comer esse tipo de alimento? Por quê? 16. Vegetais como repolho, couve e vegetais de folhas verde escuro são consumidos? Que tipos? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Esses alimentos são consumidos em meses específicos ou no ano inteiro? Em quais meses? - Grávidas costumam comer esse tipo de alimento? Por quê? 17. Raízes brancas, tubérculos ou bananas-da-terra são consumidos? Que tipos? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Esses alimentos são consumidos em meses específicos ou no ano inteiro? Em quais meses? - Grávidas costumam comer esse tipo de alimento? Por quê? 18. Vegetais ou raízes de cor alaranjada, como cenoura ou batata doce, são consumidos? Que tipos? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Esses alimentos são consumidos em meses específicos ou no ano inteiro? Em quais meses? - Grávidas costumam comer esse tipo de alimento? Por quê? 19. Algum outro tipo de vegetal é consumido, que não foi mencionado anteriormente? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Esses alimentos são consumidos em meses específicos ou no ano inteiro? Em quais meses? - Grávidas costumam comer esse tipo de alimento? Por quê? 20. Frutas amarelas ou cor-de-laranja são consumidas? Quais tipos? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Esses alimentos são consumidos em meses específicos ou no ano inteiro? Em quais meses? 221 - Grávidas costumam comer esse tipo de alimento? Por quê? 21. Algum outro tipo de fruta é consumido? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Esses alimentos são consumidos em meses específicos ou no ano inteiro? Em quais meses? - Grávidas costumam comer esse tipo de alimento? Por quê? 22. Costumam comer doces? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Em quais ocasiões são consumidos? - Grávidas costumam comer esse tipo de alimento? Por quê? 23. Lanches fritos e salgados pré embalados, fast-food ou comidas de rua? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Em quais ocasiões são consumidos? - Grávidas costumam comer esse tipo de alimento? Por quê? 24. Grãos refinados, farináceos ou produtos assados? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Em quais ocasiões são consumidos? - Grávidas costumam comer esse tipo de alimento? Por quê? 25. Refrigerantes com açúcar? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Em quais ocasiões são consumidos? - Grávidas costumam comer esse tipo de alimento? Por quê? 26. Algum outro tipo de alimento que não foi mencionado? - Consumidos com frequência (pelo menos uma vez por semana) ou menos que isso? - Em quais ocasiões são consumidos? - Grávidas costumam comer esse tipo de alimento? Por quê? Refeições e alimentos 27. De onde você obtém seus alimentos? Precisa ir para longe para conseguir seus alimentos? - Quem vai buscar os alimentos na sua família e quão longe eles precisam viajar para obtê-lo? São locais diferentes para diferentes tipos de comida? - Como você/pessoas na sua comunidade armazenam os alimentos? - Quantas horas por dia você(ou familiar) gasta obtendo, preparando, cozinhando e limpando depois das refeições? - Alguma dessas atividades diárias muda quando há uma mulher grávida ou cuidando de um bebê? 28. Por favor, fale um pouco sobre como refeições são feitas na sua família. - Onde as refeições são feitas? Todos comem juntos? - Algum membro da sua família come primeiro? - Todos comem as mesmas comidas? Se não, como é diferente e para quem? 29. A comida/atividades relacionadas à alimentação mudou durante a sua vida? - Ainda come as mesmas comidas que seus pais? Seus avós? Se não, o que mudou e por quê? - Algo mudou no modo como você consegue seus alimentos, os armazena ou cozinha? Quando essas mudanças ocorreram e por quê? Perspectivas locais sobre alimentos e alimentação saudável 222 30. Há algum alimento ou prato associado à sua origem étnica? - Quais são comidas tradicionais que pessoas comem na sua comunidade? Esses alimentos ainda são consumidos? Se não, por quê? - Quais são alimentos ou pratos que as pessoas comeriam todos os dias se pudessem? - Há algum alimento que as pessoas não comem? Por quê? (Se responderem somente que é cultura/tradição, tente fazer perguntas/investigar). - Há histórias ou crenças sobre alimentos que grávidas ou mães lactantes devem comer? Por quê? - Há histórias ou crenças sobre alimentos que grávidas ou mães lactantes não devem comer? Por quê? 31. O que significa uma refeição saudável para você? O que faz uma refeição ser saudável? Por quê? - O que é necessário para uma refeição ser completa? (por exemplo, uma refeição sem um alimento específico não é completa.) 32. Quais alimentos/pratos você considera saudáveis para mulheres grávidas? Por quê? Como você aprendeu isso? 33. Quais alimentos/pratos você considera saudáveis para mulheres lactantes? Por quê? Como você aprendeu isso? Barreiras ou facilidades para nutrição e saúde materna adequada. 34. Na sua opinião, você acha que mulheres grávidas ou lactantes têm acesso à alimentação suficiente? Elas comem refeições saudáveis? Por quê? - Quais você acha que são os problemas chave para mulheres não conseguirem alimentos saudáveis? - Na sua opinião, existe relação entre a alimentação que a mulher ingere e a hipertensão durante a gravidez? 35. Durante os últimos 12 meses, houve um período que, por causa de falta de dinheiro ou outros recursos: (Tente ouvir histórias e exemplos se possível) - Você se preocupou que não teria suficiente para comer? - Não conseguiu comer alimentos saudáveis/nutritivos? - Comeu somente alguns tipos de alimentos? -Teve que pular refeições? - Comeu menos que você achava que deveria? - Acabou a comida da sua casa? - Você esteve com fome, mas não comeu? - Você ficou sem comer por um dia inteiro? 36. O que mulheres fazem quando não há comida suficiente em suas casas? - Mães mudam seus hábitos alimentares (por exemplo comer menos) para que pessoas nas suas famílias possam comer mais? Há algum tipo de alimento que vai para algum membro específico? - Quais mecanismos são utilizados? - É feita chacota/zombaria/fofoca com mulheres que não possuem alimentos suficientes ou com crianças que parecem ter fome? 37. Na sua opinião, o que ajuda mulheres a terem comida - Para suas casas: - Para elas mesmas: 223 38. Na sua opinião, o que ajuda mulheres a manterem boa saúde durante a gravidez, parto e cuidados de filhos pequenos? Encerramento 39. Há algo que não discutimos que você gostaria de falar sobre? Algo que quer me contar? Agradeça o participante pela sua contribuição. B.3 Semi-structured interview guide in English for The Gambia (Verbally translated into local languages, since they do not have an established written language) Demographic and opening questions 1. Do you have any children? - Boys? Girls? How old are they? 2. Did you grow up in this community? - Do you have family members in this community? - For those not born in the community: When did you come here? Why did you move here? (i.e. marriage, economic opportunity, family etc.) 3. What is your ethnic background? 4. How old are you? 5. Did you attend any schooling? - If so, how many years of school did you complete? 6. What do you do for a living? - How much do you typically earn in a day? 7. Are you currently married? - If not: single, unmarried partner, divorced, widowed? - If married: what does your spouse do for a living? How much do they typically earn in a day? Do they work in the community or have to travel away for work? 8. Can you describe a typical day for you? Local diets and food patterns 9. Please tell me about the typical meals people eat in this community - What meals do people usually eat everyday in the morning, afternoon and evening? - Are different foods and meals people eat at different times of the year? - Are there any foods or meals that women eat especially during pregnancy, delivery, when they are breastfeeding? I’m going to go through a list of different food groups and I would like you to tell me what foods are commonly eaten in this community: 10. Are eggs eaten here? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? 224 - Do you eat more eggs in certain months or are they eaten around the year? If in certain months, which months? - Do pregnant women eat these foods? Why or why not? 11. Is meat and chicken eaten here, including organ meats? What types? - How frequently for red meats (i.e. Beef, pork, lamb, goat, rabbit, wild game meat), organ meats (i.e. kidney, liver), and poultry (i.e. chicken, duck, any birds)? Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Do pregnant women eat these foods? Why or why not? 12. Is fish and other seafood eaten here? What types? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Do pregnant women eat these foods? Why or why not? 13. Is low fat-fat dairy like milk, cheese, yoghurt or other milk products (NOT butter, cream or sour cream) eaten here? What types? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Do pregnant women eat these foods? Why or why not? 14. Are nuts and seeds like Tree nut, ground nut, peanut or certain seeds or nut/seed "butters" or pastes eaten here? What types? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Do pregnant women eat these foods? Why or why not? 15. Are peas, lentils and beans eaten here? What types? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Do pregnant women eat these foods? Why or why not? 16. Are cruciferous vegetables like cabbage and kale and dark green leafy vegetable eaten here? What types? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Do pregnant women eat these foods? Why or why not? 17. Are white roots and tubers or plantains eaten here? What types? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Do pregnant women eat these foods? Why or why not? 18. Are vegetables or roots that are orange-coloured inside like carrots and sweet potatoes eaten here? What types? 225 - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Do pregnant women eat these foods? Why or why not? 19. Any other types of vegetables are eaten here that we have not mentioned? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Do pregnant women eat these foods? Why or why not? 20. Are other fruits that are dark yellow or orange eaten here? What types? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Do pregnant women eat these foods? Why or why not? 21. Any other types of fruits are eaten here that we have not mentioned? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - Do you eat more of these foods in certain months or are they eaten around the year? If in certain months, which months? - Do pregnant women eat these foods? Why or why not? 22. What kinds of sweets are eaten here, if any? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - When would people eat these foods? - Do pregnant women eat these foods? Why or why not? 23. Fried snacks and savoury snacks in packets, fast/street foods - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - When would people eat these foods? - Do pregnant women eat these foods? Why or why not? 24. Refined grains and baked goods - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - When would people eat these foods? - Do pregnant women eat these foods? Why or why not? 25. Sugar-sweetened fizzy drinks? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - When would people eat these foods? - Do pregnant women eat these foods? Why or why not? 26. Any other foods people eat here that we have not mentioned? - Eaten regularly (at least once a week) or not eaten often (less than once a week)? - When would people eat these foods? - Do pregnant women eat these foods? Why or why not? Food provisioning and meals 27. Where do you get your food from? How far do you have to travel to get your food? - Who goes to get the food items in your family and how far do they have to travel for it? Are there different places for different types of food? 226 - How do you/people in this community store food? - How many hours of your day do you (or your family member) spend getting, preparing and cooking food and cleaning after meals? - Does any of these daily activities change when a woman is pregnant or caring for a young infant? 28. Please share how meals are eaten in your family - Where does your household eat meals? Does everyone eat together? - Do certain family members eat first? - Does everyone in the family eat the same meal? If not, how does it differ and for who? 29. Has food and food related activities changed in your lifetime? - Do you eat the same food as your parents? Your grandparents? If not, what has changed and why. - Has anything changed in where you get your food, how you store your food items and how you cook? When has these changes happened and why? Local perspectives on food and healthy diets 30. Are there any foods or meals that are associated to your ethnic group? - What are your traditional foods that people eat in your community? Do people still eat this? If not, why? - What are favourite foods or meals that people in this community would eat everyday if they could? - Are there any foods that people in this community do not eat? Why? (if they simply reply that it’s culture, try to probe deeper) - Are there any stories or beliefs in this community about foods that pregnant and/or lactating mothers should eat? Why? - Are there any stories or beliefs in this community about foods that pregnant and/or lactating mothers should not eat? Why? 31. What does a healthy meal mean to you? What makes a meal healthy? Why? - What is needed to make a meal considered complete? (i.e. if this food item is missing, then the meal is not complete) 32. What foods/meals do you think is healthy for pregnant women to eat? Why? Where did you learn this from? 33. What foods/meals do you think is healthy for a woman who is breastfeeding to eat? Why? Where did you learn this from? Barriers and facilitators to adequate maternal diets and health 34. In your opinion, do you think pregnant and breastfeeding women in this community are able to eat enough food? Eat enough healthy meals? Why or why not? - What do you think are the key problems that happen when women do not get enough healthy food to eat? - In your opinion, is there a relationship between the food a woman eats and getting high blood pressure during pregnancy? 227 35. During the last 12 months, was there a time when, because of lack of money or other resources (probe for examples and stories if possible) - You were worried you would not have enough food to eat? - You were unable to eat healthy and nutritious food? - You ate only a few kinds of foods? - You had to skip a meal? - You ate less than you thought you should? - Your household ran out of food? - You were hungry but did not eat? - You went without eating for a whole day? 36. What do women do when there is not enough food in their homes? - Do mothers change their eating (i.e. eat less) so other people in their families can eat more? Prioritize food for which family members? - What coping strategies employed? - Do people gossip and talk bad about women/ households if they know a household cannot get enough food or if a child looks hungry? 37. In your opinion, what helps women have enough food? - For their household - For themselves 38. In your opinion, what helps women to have good health during their pregnancy, delivery and caring for their young infant? Closing 39. Is there anything else you would like to tell me that we have not already discussed? Thank participants for their contribution. 228 Chapter 2 appendix for the maternal nutritional risk factors for pre-eclampsia incidence scoping review C.1 Search terms Search strategy for Medline Ovid 1. Nutrit* supplement or vitamin* or mineral* or micronutrit* 2. (Minerals/ or Micronutrients/ or Vitamins/ or exp Diet/) and Humans/ 3. (Dietary Proteins/ or Potassium, Dietary/ or Dietary Exposure/ or Dietary Sucrose/ or Dietary Carbohydrates/ or Sodium, Dietary/ or Dietary Sugars/ or Dietary Fats/ or Cholesterol, Dietary/ or Calcium, Dietary/ or Plant Proteins, Dietary/ or Sodium Chloride, Dietary/ or Dietary Fiber/ or Fatty Acids/) and Humans/ 4. Diet* or diet* qualit* or health* diet* or diet* intervention* or Mediterranean diet* or Mediterranean style diet* or Mediterranean type diet* or Dietary approaches to stop hypertension or DASH diet* 5. Diet, Fat-restricted/ or Diet, High-protein/ or diet, Mediterranean/ or Diet, Reducing/ or Diet, Sodium-restricted/ or Diet, Vegetarian/ or Dietary Approaches to Stop Hypertension/ or Healthy diet/ 6. Diet* pattern* or Eat* pattern* or Diet* habit or Diet* guideline* or Diet* adhere* or Diet* complian* or Nutrition* adhere* or Nutrition* complian* or Diet* score* or Diet* index* or Diet* indices 7. 1 or 2 or 3 or 4 or 5 or 6 8. Pregnan* or Pregnan* complicat* or Placenta* pathology or Birth outcome* or Obstetric* outcome* 9. Pregnancy/ or Pregnancy Complications/ or Pregnancy Outcome/ or Maternal Nutritional Physiological Phenomena/ or Prenatal Nutritional Physiological Phenomena/ 10. Matern*mortality or Matern* death* or pregnancy death* or motherhood death* or women death* 11. Maternal Mortality/ or Maternal Death/ 229 12. Pregnan* hypertension or gestational hypertension or chronic hypertension or pre-eclampsia or preeclampsia or toxemia or eclampsia or HEELP syndrome 13. Hypertension/ or Hypertension, Pregnancy-Induced/ or Pregnancy Complications, Cardiovascular/ or Pre-Eclampsia/ or HELLP Syndrome/ 14. 8 or 9 or 10 or 11 or 12 or 13 15. 7 and 14 C.2 Excluded studies Reference Article title Reason for exclusion Abu-Saad and Fraser 2010 Maternal nutrition and birth outcomes. Did not cover outcome of interest (pre-eclampsia) Attree 2005 Low-income mothers, nutrition and health: a systematic review of qualitative evidence Did not cover outcome of interest (pre-eclampsia) Bulloch et al 2018 Maternal folic acid supplementation for the prevention of preeclampsia: A systematic review and meta-analysis Wrong study design (supplementation or fortification studies) Chia et al 2019 Maternal Dietary Patterns and Birth Outcomes: A Systematic Review and Meta-Analysis. Did not cover outcome of interest (pre-eclampsia) Doyle et al 2017 Determinants of dietary patterns and diet quality during pregnancy: a systematic review with narrative synthesis Did not cover outcome of interest (pre-eclampsia) Drueke 1999 Dietary calcium and blood pressure Wrong population (not in pregnancy) Fang et al 2021 Maternal vitamin D deficiency during pregnancy and low birth weight: a systematic review and meta-analysis Did not cover outcome of interest (pre-eclampsia) Harika et al 2017 Micronutrient Status and Dietary Intake of Iron, Vitamin A, Iodine, Folate and Zinc in Women of Reproductive Age and Pregnant Women in Ethiopia, Kenya, Did not cover outcome of interest (pre-eclampsia) 230 Nigeria and South Africa: A Systematic Review of Data from 2005 to 2015 Hu et al 2018 Maternal Vitamin D Deficiency and the Risk of Small for Gestational Age: A Meta-analysis Did not cover outcome of interest (pre-eclampsia) Kjollesdal and Holmboe-Ottesen 2014 Dietary Patterns and Birth Weight-a Review Did not cover outcome of interest (pre-eclampsia) Lewis et al 1998 Drug and environmental factors associated with adverse pregnancy outcomes. Part III: Folic acid: pharmacology, therapeutic recommendations, and economics Did not cover outcome of interest (pre-eclampsia); Wrong study design (supplementation or fortification studies) Mantovani et al 2014 Folic acid supplementation and preterm birth: results from observational studies Did not cover outcome of interest (pre-eclampsia); Wrong study design (supplementation or fortification studies) Murphy et al 2014 Associations of consumption of fruits and vegetables during pregnancy with infant birth weight or small for gestational age births: a systematic review of the literature Did not cover outcome of interest (pre-eclampsia) Ponzetto et al 2019 Prepregnancy calcium supplementation and pre-eclampsia Wrong study design (supplementation or fortification studies) Qin et al 2016 Does Maternal Vitamin D Deficiency Increase the Risk of Preterm Birth: A Meta-Analysis of Observational Studies Did not cover outcome of interest (pre-eclampsia) Raghavan et al 2019 Dietary patterns before and during pregnancy and birth outcomes: a systematic review Did not cover outcome of interest (pre-eclampsia) Rogne et al 2014 Associations of Maternal Vitamin B12 Concentration in Pregnancy With the Risks of Preterm Birth and Low Birth Weight: A Systematic Review and Meta-Analysis of Individual Participant Data Did not cover outcome of interest (pre-eclampsia) 231 Rogozinska et al 2014 Variation in outcomes in trials reporting effects of diet and lifestyle based intervention on pregnancy outcomes: a systematic review. Wrong study design (supplementation or fortification studies) van Uitert et al 2013 Influence of maternal folate status on human fetal growth parameters. Did not cover outcome of interest (pre-eclampsia) Wen and Walker 2005 An exploration of health effects of folic acid in pregnancy beyond reducing neural tube defects Did not cover outcome of interest (pre-eclampsia) Yang et al 2016 Periconceptional folic acid fortification for the risk of gestational hypertension and pre-eclampsia: a meta-analysis of prospective studies. Wrong study design (supplementation or fortification studies) Zerfu and Ayele 2013 Micronutrients and pregnancy; effect of supplementation on pregnancy and pregnancy outcomes: a systematic review Wrong study design (supplementation or fortification studies) Zhang et al 2017 Effect of folic acid supplementation on preterm delivery and small for gestational age births: A systematic review and meta-analysis Did not cover outcome of interest (pre-eclampsia); Wrong study design (supplementation or fortification studies) 232 Chapter 3 appendix for the systematic review on maternal diet and pregnancy hypertension in low- and middle-income countries D.1 Systematic review search strategy 1. Diet* diversity or diet* qualit* or diet* pattern* or Eat* pattern* or Diet* score* or Diet* index* or Diet* indices 2. (Diet/ or Nutritional Status/ or Dietary exposure/) and Humans/ 3. Malnutrition/ and (Maternal Health/ or Maternal Exposure/) 4. 1 or 2 or 3 5. Developing countries/ 6. Resource-constrain* or resource constrain* or resource-limit* or resource limit* or low resource or low-resource or remote or rural 7. Afghanistan or Albania or Algeria or Angola or Antigua or Barbuda or Argentina or Armenia or Armenian or Aruba or Azerbaijan or Bahrain or Bangladesh or Barbados or Benin or Byelarus or Byelorussian or Belarus or Belorussian or Belorussia or Belize or Bhutan or Bolivia or Bosnia or Herzegovina or Hercegovina or Botswana or Brasil or Brazil or Bulgaria or Burkina Faso or Burkina Fasso or Upper Volta or Burundi or Urundi or Cambodia or Khmer Republic or Kampuchea or Cameroon or Cameroons or Cameron or Camerons or Cape Verde or Central African Republic or Chad or Chile or China or Colombia or Comoros or Comoro Islands or Comores or Mayotte or Congo or Zaire or Costa Rica or Cote d'Ivoire or Ivory Coast or Croatia or Cuba or Cyprus or Czechoslovakia or Czech Republic or Slovakia or Slovak Republic or Djibouti or French Somaliland or Dominica or Dominican Republic or East Timor or East Timur or Timor Leste or Ecuador or Egypt or United Arab Republic or El Salvador or Eritrea or Estonia or Ethiopia or Fiji or Gabon or Gabonese Republic or Gambia or Gaza or Georgia Republic or Georgian Republic or Ghana or Gold Coast or Greece or Grenada or Guatemala or Guinea or Guam or Guiana or Guyana or Haiti or Honduras or Hungary or India or Maldives or Indonesia or Iran or Iraq or Isle of Man or Jamaica or Jordan or Kazakhstan or Kazakh or Kenya or Kiribati or Korea or Kosovo or Kyrgyzstan or Kirghizia or Kyrgyz Republic or Kirghiz or Kirgizstan or Lao PDR or Laos or Latvia or Lebanon or Lesotho or Basutoland or Liberia or Libya or Lithuania or Macedonia or Madagascar or Malagasy Republic or Malaysia or Malaya or Malay or Sabah or Sarawak or Malawi or Nyasaland or Mali or Malta or Marshall Islands or Mauritania or Mauritius or Agalega Islands or Mexico or Micronesia or Middle East or Moldova or Moldovia or Moldovian or Mongolia or Montenegro or Morocco or Ifni or Mozambique or Myanmar or Myanma or Burma or Namibia or Nepal or Netherlands Antilles or New Caledonia or Nicaragua or Niger or Nigeria or Northern 233 Mariana Islands or Oman or Muscat or Pakistan or Palau or Palestine or Panama or Paraguay or Peru or Philippines or Philipines or Phillipines or Phillippines or Poland or Portugal or Puerto Rico or Romania or Rumania or Roumania or Russia or Russian or Rwanda or Ruanda or Saint Kitts or St Kitts or Nevis or Saint Lucia or St Lucia or Saint Vincent or St Vincent or Grenadines or Samoa or Samoan Islands or Navigator Island or Navigator Islands or Sao Tome or Saudi Arabia or Senegal or Serbia or Montenegro or Seychelles or Sierra Leone or Slovenia or Sri Lanka or Ceylon or Solomon Islands or Somalia or South Africa or Sudan or Suriname or Surinam or Swaziland or Syria or Tajikistan or Tadzhikistan or Tadjikistan or Tadzhik or Tanzania or Thailand or Togo or Togolese Republic or Tonga or Trinidad or Tobago or Tunisia or Turkey or Turkmenistan or Turkmen or Uganda or Ukraine or Uruguay or USSR or Soviet Union or Union of Soviet Socialist Republics or Uzbekistan or Uzbek or Vanuatu or New Hebrides or Venezuela or Vietnam or Viet Nam or West Bank or Yemen or Yugoslavia or Zambia or Zimbabwe or Rhodesia 8. (developing or less* developed or under developed or underdeveloped or middle income or low* income) adj (economy or economies) 9. low* adj (gdp or gnp or gross domestic or gross national) 10. low adj3 middle adj3 countr* or transitional countr* 11. lmic or lmics or "third world" or "lami country" or "lami countries" 12. 5 or 6 or 7 or 8 or 9 or 10 or 11 13. Maternal Nutritional Physiological Phenomena/ or Prenatal Nutritional Physiological Phenomena/ 14. Matern*mortality or Matern* death* or pregnancy death* or motherhood death* or women death* 15. Maternal Mortality/ or Maternal Death/ 16. Pregnan* hypertension or gestational hypertension or chronic hypertension or pre-eclampsia or preeclampsia or toxemia or eclampsia or HEELP syndrome 17. Hypertension/ or Hypertension, Pregnancy-Induced/ or Pregnancy Complications, Cardiovascular/ or Pre-Eclampsia/ or HELLP Syndrome/ 18. Risk factor* or risk* 19. Exp Risk/ 20. 13 or 14 or 15 or 16 or 17 or 18 or 19 234 21. Exp cohort studies/ 22. cohort$.tw. 23. controlled clinical trial.pt. 24. epidemiologic methods/ 25. limit 24 to yr= 1966-1989 26. exp case-control studies/ 27. (case$ and control$).tw. 28. or/21-23,25-27 29. randomized controlled trial.pt. 30. (random$ or placebo$ or single blind$ or double blind$ or triple blind$).ti,ab. 31. (retraction of publication or retracted publication).pt. 32. or/29-31 33. (animals not humans).sh. 34. ((comment or editorial or meta-analysis or practice-guideline or review or letter) not “randomized controlled trial”).pt. 35. (random sampl$ or random digit$ or random effect$ or random survey or random regression).ti,ab. not “randomized controlled trial”.pt. 36. 32 not (33 or 34 or 35) 37. 28 or 36 38. 4 and 12 and 20 and 37 235 D.2 Excluded studies Reference Reason for exclusion Description Agbozo et al 2017, Agbozo et al 2020 Did not measure outcome of interest Examined PE as a risk factor for anemia Agrawal et al 1998 Did not measure outcome of interest Examined socio-demographic factors but not in association with HDP Agrawal et al 2015, Agrawal et al 2014 Study design did not meet eligibility criteria Cross-sectional survey Ahmed et al 2018 Did not measure outcome of interest HDP reported for cases and controls of mothers who delivered low birth weight babies but not related to dietary diversity Alaofe et al 2017, Alaofe et al 2019 Did not measure outcome of interest Anemia and maternal micronutrient status were outcomes measured, not HDP Arredondo et al 2019 Not exposure of interest HDP is associated with obesity, not dietary patterns Babaei and Banaem 2018 Not exposure of interest Examined micro and macronutrient statuses, not dietary patterns Chomat et al 2015 Did not measure outcome of interest Did not look at dietary diversity and pregnancy hypertension together Christian et al 2008 Did not measure outcome of interest Both PE and dietary patterns related to pregnancy-related mortality risk but not in association with each other Clausen et al 2001 Research not conducted in LMIC Research based in Norway Cormick et al 2018 Did not measure outcome of interest Study looking at current nutritional status in women who previously had PE; did 236 not examine PE as an outcome of dietary patterns in current pregnancy Desalegn et al 2018 Not population or outcome of interest Lactating mothers, which extends past the postpartum period and does not mention hypertension in the study Gomes et al 2019 Did not measure outcome of interest PIH excluded in eligibility criteria Hajianfar, et al 2018 Duplicate Duplicated in the search results Harding et al 2017 Did not measure outcome of interest Weight gain was the outcome measured Harris-Fry et al 2015 Did not measure outcome of interest Dietary diversity as outcome, not exposure; looked at determinants of dietary diversity Huang et al 2019 Did not measure outcome of interest, was also duplicated in the search results Did not separate outcomes for HDP from other adverse maternal outcomes Lander et al 2019 Did not measure outcome of interest Surveyed dietary intakes but not in association with HDP Lu et al 2018 Did not measure outcome of interest Measured preterm delivery as the study outcome, did not explore associations with HDP Lukmanji et al 2013 Did not measure outcome of interest Examine sociodemographic characteristics of dietary patterns but not its association with HDP Martins et al 2003 Not exposure of interest Examined caloric intake, not dietary diversity. Also, not in English 237 Mridha et al 2018 Did not measure outcome of interest Study focused on nutritional status, does not mention hypertension Na et al 2016 Did not measure outcome of interest Examined nutritional status and consumption only without association with HDP Nguyen et al 2017 Did not measure outcome of interest Discussed increased number of food groups eaten after counselling but not the effects on maternal health/ HDP Nucci et al 2001 Not exposure of interest Examined underweight, obesity, not dietary patterns O’Sullivan et al 2015 Sufficient methodological data available Conference abstract only Oken et al 2007 Research not conducted in LMIC Research from Massachusetts, United States Parlapani et al 2019 Research not conducted in LMIC Based on research in Greece Ravaoarisoa et al 2019 Did not measure outcome of interest Study focused on nutritional status, does not mention hypertension Safdar et al 2013, Safdar et al 2015 Not population of interest Study population included urban adults, separated results for pregnant women not provided Savy et al 2008 Not population of interest Included women 20-59 years, not pregnant and postpartum women Shamim et al 2016 Did not measure outcome of interest Examined factors associated with dietary diversity but not in association with clinical outcomes including HDP Teixeira et al 2018 Did not measure outcome of interest Examined socio-demographic factors associated with 238 dietary patterns but not its association with HDP Todd et al 2019 Did not measure outcome of interest Pre-eclampsia and dietary diversity outcomes reported separately by intervention and control group, not directly associated with each other Tran et al 2019 Not exposure of interest, not outcome of interest Examined nutritional status, not dietary patterns. Also explored birth outcomes but did not mention hypertension. Wesolowska et al 2019 Did not measure outcome of interest Pregnancy symptoms and complications as a general composite outcome Workicho et al 2019 Did not measure outcome of interest Examined determinants of maternal undernutrition among young pregnant women but not its association with HDP Zerfu et al 2016 Did not measure outcome of interest Investigated maternal anemia, preterm delivery and low birthweight as outcomes, did not explore HDP Zerfu et al 2019 Did not measure outcome of interest Measured dietary fibre consumption as study outcome HDP – hypertensive disorders of pregnancy; LMIC – low and middle-income country; PE – pre-eclampsia; PIH – pregnancy-induced hypertension D.3 Dietary pattern classifications from each study Reference Dietary patterns/ food groups identified Abbasi et al 2019 (70) Healthy: high consumption of fruits, low-fat dairy, dried fruits, nuts, vegetables, fruit juice, liquid oil, tomatoes, butter, and honey and low consumption of broth, refined grains, and solid oils 239 Western: high consumption of red meat and/or processed meat, fried potatoes, pickles, sweets, pizza, and low consumption of vegetables Iranian traditional: high consumption of eggs, potatoes, legumes, high-fat dairy, tea and low consumption of olives, snacks, beverages, and poultry Atkinson et al 1998 (59) Meat, poultry, fruit, fish, vegetables, and dairy Endeshaw et al 2015 (62) Fruit, vegetable, animal product, coffee and alcohol - adequate intake defined as at least three times per week since identification of last pregnancy Gulsen et al 2012 (61) Daily consumption of 14 food groups: milk (mL), yogurt (g), yogurt drink (mL), cheese (g), dairy desserts (g), egg (g), meat (g), chicken (g), meat product (g), fish (g), legumes (g), bread (g), vegetables(g) and fruit (g) Grum et al 2018 (68) Fruit intake, vegetable intake, coffee intake - no, daily, at least once per week Nutritional counseling during ANC – received yes/no Grum et al 2017 (64) Fruit intake, alcohol intake and received nutritional counselling during ANC – yes/no Hajianfar et al 2018 (67) Western: high consumption of processed meats, fruits, fruit juice, citrus, nuts, fish, desserts and sweets, sugar, saturated fat, sweet fruit (melon, persimmon, date, fig, grapes, raisins, berries that have high glycemic index), potato, legumes, coffee, egg, pizza, high fat dairy, whole grain and soft drinks) Traditional: high in refined grains, coloured vegetables, olive, sugar, salt, spices, unsaturated fat, garlic, onion and tea Healthy: high in green vegetables, leafy vegetables, coloured vegetables, fruits, low fat dairy, poultry, bulky vegetables, red meat, citrus, nuts, fish, olive, marinades, sweet fruit, egg and unsaturated fat Kahsay et al 2018 (66) Fruits and vegetables - consumption of more than 2-4 times per week were considered regular consumers 240 Longo-Mbenza et al 2008 (60) Vegetables and meat – 3 or more daily servings considered often, less than 3 daily servings considered rare Mekie et al 2020 (63) Fruits and vegetables - at least one serving per week was considered as vegetable and fruit consumption Coffee per day - less than 4 cups, 4 or more Alcohol use – yes/no Nutritional counselling during ANC – yes/no Mi et al 2019 (69) Vegetable dietary pattern: high consumption of mushrooms, leafy and cruciferous vegetables, root vegetables, melon vegetables and legumes Meat dietary pattern: high consumption of beef, mutton, poultry, fish, and pork Fruit dietary pattern: high consumption of cantaloupes, pineapples, muskmelons, watermelons, and grapes Snack dietary pattern: high consumption of breads, cakes, biscuits and Chinese snacks Wheat staple dietary pattern: high consumption of noodles and Liangpi (cold skin noodles) Sheikhi et al 2018 (65) Meat, beans nuts and eggs; Milk; Grains; Vegetables; Fruit Zareei et al 2019 (71) Unhealthy: high in mayonnaise, pizza, fries, red meat, soft drinks, snacks, sweets and dessert, refined cereal, hydrogenated oils Healthy: high in fruits, vegetables, dairy products ANC – antenatal care; mL – millilitre; g – gram D.4 Outcome definitions by study Reference Outcome Definition Abbasi et al 2019 (70) PE >140/90mmHg, a 24-hr proteinuria >300 mg, and a health and hospital record confirmed by a gynecologist in case of hospitalization; control group followed throughout their pregnancy to ensure they did not develop PE 241 Atkinson et al 1998 (59) PE >140/90mmHg or rise of at least 30/15mmHg after 20 weeks pregnancy, a 24-hour proteinuria >300 mg or 0.1g/l in at least 2 random specimens at least 6 hrs apart and/or eclampsia Endeshaw et al 2015 (62) PE ≥140/90mmHg starting at or after 20 weeks measured at least twice at 4 hr intervals and protein in their urine confirmed by laboratory test, diagnosis by obstetrician Gulsen et al 2012 (61) PE as diagnosed by clinicians Grum et al 2018 (68) PE >140/90 mmHg and presence of protein in urine Grum et al 2017 (64) PE ≥ 140 mmHg systolic or ≥90 mmHg diastolic on two separate readings taken at least four hours apart with previously normal blood pressure and when proteinuria is greater than or equal to 300 mg per 24-h urine collection or dipstick, diagnosed by physician Hajianfar et al 2018 (67) GH ≥140/90mmHg during or after the 20th week of amenorrhea PE ≥140/90mmHg on at least two occasions and at least 4-6 hrs apart after the 20 weeks of gestation in women known to be normotensive beforehand, with proteinuria 300 mg/L or more in a 24 hr urine sample Kahsay et al 2018 (66) HDP = GH, PE or SIP, CH excluded GH: 140/90 mmHg measured on two occasions at least 4 h apart after 20 weeks of gestation in the absence of proteinuria or other systemic symptoms; PE: GH with proteinuria or other manifestations such thrombocytopenia, impaired liver function, the new development of renal insufficiency, pulmonary edema, or new onset cerebral or visual disturbances, or eclampsia; SIP: mothers known to have hypertension before pregnancy or before 20 weeks of gestation and who had developed signs of preeclampsia after 20 weeks of gestation Longo-Mbenza et al 2008 (60) GH Definitions unclear - "defined accordingly to the American College of Obstetricians and Gynaecologists" but not defined in text. Assessment procedures not described. PE Definitions unclear - "defined accordingly to the American College of Obstetricians and Gynaecologists" but not defined in text. Assessment procedures not described. Mekie et al 2020 (63) PE ≥140/90 mmHg on two separate readings taken at least four hours apart or a single BP measurement of≥ 160/110 mmHg and a proteinuria ≥ 300 mg per 24-hr urine collection or a dipstick reading of 1+ occurred after 20 weeks of gestation among 242 previously normotensive women Mi et al 2019 (69) GH ≥140/90mmHg starting at or after 20 weeks among women with normal blood pressure in first 20 weeks PE Gestational hypertension with proteinuria ≥1 on dipstick Sheikhi et al 2018 (65) PE ≥140/ ≥90 mmHg on two occasions more than 4 hrs apart after 20 weeks and proteinuria ≥300 mg protein in 24-hr urine collection Zareei et al 2019 (71) PE ≥140/ ≥90 mmHg after 20 weeks and proteinuria ≥300 mg protein in 24-hr urine collection CH – chronic hypertension; g – gram; GH – gestational hypertension; HDP – hypertensive disorders of pregnancy; hr(s) – hour(s); L – litre; mg – milligram; PE – pre-eclampsia; SIP – superimposed pre-eclampsia D.5 Reported outcomes by study Reference Illustrative comparative risk Relative effect (95% CI) Assumed risk of PE-associated dietary patterns Corresponding risk of comparison dietary patterns Crude Adjusted (for the maximum number of covariables) Abbasi et al 2019 (69) Factor scores of Western DP significantly higher among cases (mean rank 325.69 cases vs 220.40 control, p<0.001) Factor scores of healthy DP (mean rank 142.40 cases vs 312.05 control, p<0.001) and Iranian traditional DP (201.36 cases vs 282.57 control, p<0.001) significantly higher among control Healthy - cOR 0.129 (95%CI: 0.86 - 0.194, p <0.001) Western - cOR 4.42 (95%CI: 3.09- 6.31, p <0.001) Iranian traditional - OR 0.281 (95%CI: 0.182 - 0.375, p <0.001) Healthy - aOR 0.125 (95%CI: 0.070 - 0.22, p <0.001) Western - aOR 4.37 (95%CI: 3.04-6.28, p <0.001) Iranian traditional - aOR 0.183 (95%CI: 0.109 - 0.308, p <0.001) 243 Atkinson et al 1998 (59) Meat: 23/180 (12.8%) 11 or less servings per month, 63/180 (35.0%) 12-45 servings, 58/180 (32.2%) 48-72 servings, 36/180 (20.0%) 73 servings or more Poultry (chicken): 49/180 (27.2%) 1 or less servings chicken per month, 42/180 (23.3%) 2-6 servings, 38/180 (21.1%) 7-10 servings, 51/180 (28.3%) 11 servings or more Fruit (total): 48/180 (26.7%) 12 or less servings per month, 30/180 (16.7%) 13-30 servings, 62/180 (34.4%) 31-84 servings, 32/180 (17.8%) 85 or more servings Fish (kapenta -small white fish): 103/180 (57.2%) 0 servings per month, 26/180 (14.4%) 1-6 servings, 51/180 (28.3%) 7 or more servings Meat: 46/194 (23.7%) 11 or less servings per month, 63/194 (18.6%) 12-45 servings, 39/194 (20.1%) 48-72 servings, 46/194 (23.7%) 73 servings or more Poultry (chicken): 55/194 (28.4%) 1 or less servings chicken per month, 47/194 (24.2%) 2-6 servings, missing data 7-10 servings (estimated 33/194 (17.0%)), 59/194 (30.4%) 11 servings or more Fruit (total): 59/194 (30.4%) 12 or less servings per month, 40/ 194 (20.6%) 13-30 servings per month, 65/194 (33.5%) 31-84 servings, 30/194 (15.5%) 85 or more servings Fish (kapenta -small white fish): 107/194 (55.2%) 0 servings per month, 18/194 (9.3%) 1-6 servings, 69/194 (35.5%) 7 or more servings Meat: cOR 2.0 (1.1-3.7) 12-45 servings, cOR 3.0 (1.6-5.7) 45-72 servings, cOR 1.6 (0.6-1.7) compared to 11 or less servings Poultry (chicken): cOR 1.0 (0.6-1.8) 2-6 servings, cOR 1.3 (0.7-2.4) 7-10 servings, cOR 1.0 (0,6-1.7) compared to 1 or less servings Fruit (total): cOR 1.2 (0.7-2.1) 13-30 servings, cOR 1.2 (0.7-2.0) 31-84 servings, cOR 1.3 (0.7-2.5) 85 or more servings, compared 12 or less servings Fish (kapenta -small white fish): cOR 1.5 (0.8-2.9) 1-6 servings, cOR 0.8 (0.5-1.2) 7 or more servings, compared to 0 servings Vegetables (total): cOR 1.2 (0.7-1.9) 121-179 servings, cOR 0.8 (0.5-1.5) 180-239 servings, cOR 0.9 (0.5-1.6) 240 servings or more, compared to Meat: aOR 1.9 (1.5-5.6) 12-45 servings, aOR 2.9 (0.8-3.0) 45-72 servings compared to 11 or less servings Fish (kapenta -small white fish): aOR 1.4 (0.7-2.7) 1-6 servings, aOR 0.8 (0.5-1.2) 7 or more servings, compared to 0 servings Vegetables (total): aOR 1.2 (0.7-1.9) 121-179 servings, aOR 0.8 (0.5-1.6) 180-239 servings, aOR 0.8 (0.5-1.5) 240 servings or more, compared to 120 servings or less Dairy (total): aOR 0.9 (0.5-1.7) 4-11 servings, aOR 0.8 (0.4-1.5) 12-27 servings, aOR 0.9 (0.5-1.7) 28 or more servings, compared to 3 or less servings 244 Vegetables (total): 58/180 (32.2%) 120 servings or less, 63/180 (35.0%) 121-179 servings, 29/180 (16.1%) 180-239 servings, 30/180 (16.7%) 240 servings or more; Dairy (total): 40/180 (22.2%) 3 servings or less, 47/180 (26.1%) 4-11 servings, 37/180 (20.6%) 12-27 servings, 56/180 (31.1%) 28 or more servings Vegetables (total): 62/194 (32.0%) 120 servings or less, 58/194 (30.0%) 121-179 servings, 37/194 (19.1%) 180-239 servings, 37/194 (19.1%) 240 servings or more Dairy (total): 38/194 (20.1%) 3 servings or less, 49/194 (25.3%) 4-11 servings, 47/194 (24.2%) 12-27 servings, 58/194 (29.9%) 28 or more servings 120 servings or less Dairy (total): cOR 1.0 (0.5-1.7) 4-11 servings, cOR 0.9 (0.4-1.5) 12-27 servings, cOR 1.0 (0.5- 1.7) 28 or more servings, compared to 3 or less servings; Endeshaw et al 2015 (62) Inadequate fruit intake (less than three times per week): 59/151 cases (39.1%) vs 55/302 controls (18.2%) Inadequate vegetable intake (less than three times per week): 46/151 cases (30.5%) vs 36/302 controls (11.9%) Inadequate animal product intake (less than three times per week): 8/151 cases Adequate fruit intake (at least three times per week): 92/151 cases (60.9%) vs 247/302 controls (81.8%) Adequate vegetable intake (at least three times per week): 105/151 cases (69.5%) vs 266/302 controls (88.1%) Adequate animal product intake (at least three times per week): 143/151 cases Adequate fruit intake vs inadequate cOR 0.34 (0.22 - 0.54) Adequate vegetable intake vs inadequate cOR 0.31(0.19 - 0.50) Adequate vs inadequate animal product intake cOR 1.34 (0.58- 3.10) Daily versus no coffee intake - cOR 2.41(1.49 -3.90) Adequate fruit intake vs inadequate: aOR 0.51(0.29-0.91) Adequate vegetable intake vs inadequate: aOR 0.46 (0.24-0.90) Coffee intake: aOR 1.78(1.20-3.05) 245 (5.3%) vs 21/302 controls (7.0%) Daily coffee intake: 124/151 cases (81.1%) vs 198/302 controls (65.6%) Consumed alcohol: 80/151 cases (53.0%) vs 122/302 control (40.4%) (94.7%) 281/302 controls (93.0%) No coffee: 27/151 cases (17.9%) vs 104/302 controls (34.4%) No alcohol: 71/151 cases (47.0%) vs 180/302 controls (59.6%) Alcohol intake cOR c1.66 (1.12-2.46); Gulsen et al 2012 (61) (Mean ± SE) Legumes (g): 22.75 ±2.120 cases vs 14.74±0.950 controls, p<0.0001 Bread (g): 414.13 ±19.03 cases vs 269.03± 11.46 controls, p<0.0001 (Mean ± SE) Milk (mL): 73.4±11.29 cases vs 183.04±12.11 controls, p<0.0001 Yogurt (mL): 44.77±4.830 cases vs 84.61±3.590 controls, p<0.0001 Yogurt drink (mL): 10.74±2.410 cases vs 29.88±3.100 controls, p<0.0001 Cheese (g): 16.96±1.520 cases vs 34.07±1.370 controls, p<0.0001 Dairy desserts (g): 9.09±1.190 cases vs 12.04±0.720, p<0.03 Egg (g): 17.53±2.110 cases vs 29.19±1.81 controls, p<0.0001 NA NA 246 Meat (g): 41.85±4.270 cases vs 92.40±1.780 controls, p<0.0001 Chicken (g): 6.18±0.850 cases vs 12.26±1.290 controls, p<0.0001 Meat product (g): 3.69±0.990 cases vs 13.72 ±1.370 controls, p<0.0001; Fish (g): 5.80 ±0.580 cases vs 8.53±0.480 controls, p<0.001 Vegetable (g): 74.46±3.770 cases vs 97.51±3.560 controls, p<0.0001 Fruit (g): 232.61±12.47 cases vs 360.00±14.35 controls, p<0.0001 Grum et al 2018 (63) No fruit intake: 22/81 cases (27.2%) vs 10/162 controls (6.2%) No vegetable intake: 15/81 cases (18.5%) vs 5/162 controls (3.1%) Coffee intake: daily 32/81 cases (39.5%) vs 84/162 controls (81.9%), Fruit intake: daily 15/81 cases (18.5%) vs 41/162 controls (25.3%), at least once per week 44/81 cases (7.4%) vs 111/162 controls (21.6%) Vegetable intake: daily 6/81 cases (7.4%) vs 35/162 controls (21.6%), at least once per week 60/81 cases Fruit intake: daily cOR 0.17 (0.06-0.43), at least once per week cOR 0.18 (0.09-0.41) Vegetable intake: daily cOR 0.57 (0.02-0.22), at least once per week at least once per week cOR 0.164 (0.06 -0.47) Fruit intake: daily aOR 0.94 (0.20-4.32, p<0.05), at least once per week aOR 0.23 (0.06- 0.91, p<0.05) Vegetable intake: daily aOR 0.95 (0.01- 0.71, p<0.05), at least once per week aOR 0.25 (0.05 -1.37) 247 at least once per week 26/81 cases (32.1%) vs 52/162 controls (32.1%) Did not receive nutritional counselling during ANC 32/81 (43.2%) vs 17/162 (10.9%) (74.1%) vs 122/162 controls (75.3%) No coffee intake: 23/81 cases (28.4%) vs 84/162 controls (81.9%) Received nutritional counselling during ANC 42/81 cases (56.8%) vs 139/162 (89.1% control) Coffee intake: daily cOR 4.5 (2.25-9.0), at least once per week cOR 1.83 (0.95- 3.53) Received nutritional counselling during ANC cOR 0.16 (0.08 -0.32) Coffee intake: daily aOR 3.26 (0.42 - 25.36), at least once per week aOR 5.09 (0.93 - 27.97) Received nutritional counselling during ANC aOR 0.17 (0.05 -0.6, p<0.05) Grum et al 2017 (67) No fruit intake: 15/95 cases (15.8%) vs 11/190 controls (5.8%) Yes alcohol intake: 33/95 cases (34.7%) vs 21/190 controls (11.1%) Did not receive nutritional counselling during ANC 34/85 cases (40.0%) vs 23/183 (12.6%) Yes fruit intake: 80/95 cases (84.2%) vs 179/190 controls (94.2%) No alcohol intake: 62/95 cases (65.3%) vs 169/190 controls (89.0%) Received nutritional counselling during ANC: 51/85 cases (60.0%) vs 160/183 controls (87.4%) Fruit intake: cOR 3.05(1.34 -6.94) Alcohol intake cOR 4.28(2.3 -7.9) Received nutritional counselling during ANC: cOR 0.22(0.12, 0.4) Fruit intake: aOR 1.57 (0.47- 5.26) Alcohol intake: aOR 3.97(1.8- 8.75, p<0.05) Received nutritional counselling during ANC: aOR 0.22 (0.1-0.48, p<0.001) Hajianfar et al 2018 (66) NA NA Healthy: cOR 0.73 (0.44–1.20, p= 0.04) Western: cOR 1.31 (0.78-2.21, p=0.21) Healthy: aOR 0.49 (0.24–1.00, p=0.05) Western: aOR 2.08 (1.00–4.36, p=0.02) 248 Traditional: cOR 1.24 (0.76-2.02, p=0.80 Traditional: aOR 1.25 (0.63-2.49, p=0.80) Kahsay et al 2018 (65) Low fruit consumption (less than 2-4 times per week): 50/110 cases (45.5%) vs 27/220 controls (12.3%) Low vegetable consumption (less than 2-4 times per week): 63/110 cases (57.3%) vs 87/220 controls (39.6%) Coffee during pregnancy: 93/110 cases (84.5%) vs 149/220 controls (67.7%) Regular fruit consumption (2-4 times per week or more): 60/110 cases (54.5%) vs 193/220 controls (87.7%) Regular vegetable consumption (2-4 times per week or more): 47/110 cases (42.7%) 133/220 controls (60.4%) No coffee during pregnancy: 17/110 cases (15.5%) vs 71/220 controls (32.3%) Low fruit consumption: cOR 5.3 (3.0-9.4, p<0.01) Low vegetable consumption: cOR 2.08(1.3- 3.3, p<0.01) Coffee during pregnancy: cOR 3.08 (1.6-5.9, p<0.01) Low fruit consumption: aOR 5.1 (2.4-11.15, <0.001) Low vegetable consumption: aOR 1.2(0.6- 2.3) Coffee during pregnancy: aOR 1.9 (0.8- 4.4) Longo-Mbenza et al 2008 (60) Rare daily servings of vegetables (less than 3): 33.3% PE incidence Meat not reported Often daily servings of vegetables (3 or more): 3.7% PE incidence Meat not reported 3 daily servings of vegetables: RR 0.88 (0.6-0.98, p<0.01) Mekie et al 2020 (71) No fruit consumption: 57/107 cases (53.3%) vs 76/214 controls (35.5%) No vegetable consumption: 34/107 cases (31.8%) vs 30/214 controls (14.0%) Fruit consumption (at least one serving per week): 50/107 cases (46.7%) vs 138/214 controls (64.5%) Vegetable consumption (at least one serving per week): 73/107 cases (68.2%) vs Fruit consumption: cOR 0.62 (0.42- 0.91) Vegetable consumption: cOR 0.53 (0.35-0.80) More than 4 cups coffee per day: cOR 1.96 (1.14-3.37) Fruit consumption: aOR 0.45 (0.24- 0.87, p<0.05) Vegetable consumption: aOR 0.42 (0.22- 0.82, p<0.05) More than 4 cups coffee per day: 249 More than 4 cups coffee per day: 17/107 cases (19.3%) vs 10/214 controls (6.3%) Alcohol use: 47/107 cases (43.9%) vs 58/214 controls (27.1%) No nutritional counselling at ANC: 28/72 cases (38.9%) vs 25/188 control (13.3%) 184/214 controls(86.0%) 4 cups of coffee per day or less: 71/107 cases (80.7%) vs 149/214 controls (93.7%) No alcohol: 60/107 cases (56.1%) vs 156/214 controls (72.9%) Nutritional counselling at ANC: 44/72 cases (61.1%) vs 163/188 control (86.7%) Alcohol use during pregnancy: cOR 1.65 (1.12-2.43) Nutritional counselling during ANC: cOR 0.45 (0.27- 0.73) aOR 1.67 (0.69-4.05) Alcohol use during pregnancy: aOR 1.29 (0.72-2.34) Nutritional counselling during ANC aOR 0.52 (0.29- 0.96, p<0.05) Mi et al 2019 (68) Meat (quartile 1 vs quartile 4): 2 PE cases/246 (0.8%) vs 4 PE cases/247 (1.6%) Wheat staple (quartile 1 vs quartile 4): 4 PE cases/246 (1.6%) vs 6 PE cases /247 (2.4%) Vegetable (quartile 1 vs quartile 4): 9 PE cases/246 (3.7%) vs 2 PE cases/247 (0.8%), 35 proteinuria/246 (14.2%) vs 19 proteinuria /247 (7.7%), 32 GH/ 246 (13.0%) vs 29 GH/247 (11.7%) Fruit (quartile 1 vs quartile 4): 3 PE cases/246 (1.2%) vs 3 PE cases/247 (1.2%) Snack (quartile 1 vs quartile 4): 4 PE cases/246 Vegetable (quartile 1 vs quartile 4): unadjusted RR 0.20 (0.04–0.97, p=0.035) Meat (quartile 1 vs quartile 4): unadjusted RR 2.00 (0.36–11.01, p=0.74) Fruit (quartile 1 vs quartile 4): unadjusted RR 1.08 (0.21–5.52, p=0.99) Snack (quartile 1 vs quartile 4): unadjusted RR 0.25 (0.03–2.27, p=0.39) Vegetable (quartile 1 vs quartile 4): adjusted RR for PE 0.20 (0.04–0.98, p=0.041), adjusted RR for proteinuria 0.44 (0.24–0.80, p=0.015), adjusted RR for GH 0.88 (0.50–1.53, p=0.35) Meat (quartile 1 vs quartile 4): aOR 2.01 (0.35–11.67, p=0.72) Fruit (quartile 1 vs quartile 4): aOR 1.03 (0.18–5.76, p=0.96) 250 (1.6%) vs 1 PE cases /247 (0.4%) Wheat staple (quartile 1 vs quartile 4): unadjusted RR 1.49 (0.41–5.36, p=0.71) *note all PE as outcome Snack (quartile 1 vs quartile 4): aOR 0.33 (0.03–3.35, p=0.72) Wheat staple (quartile 1 vs quartile 4): aOR 1.58 (0.41–6.08, p=0.69) Sheikhi et al 2018 (64) (Mean +SD) Milk (cup): 2.3±1.4 cases vs 2.2±1.2 control, p= 0.86 Grains: 18.4±6.5 cases vs 15.8±14.3 control, p=0.008 (Mean+SD) Meat, beans, nuts and egg (ounces): 3.4 ±2.4 cases vs 4.5±3.2 control, p= 0.02 Vegetables (cup): 2.5±1.5 cases vs 3.5±1.9 control, p= 0.001 Fruit (cup): 2.7±2.3 cases vs 3.4±2.5 control, p=0.09 Meat, beans nuts and egg:cOR 0.92(0.39-2.15) Milk: cOR 1.31(0.23-7.40) Grains: cOR 2.02(1.13-3.62, p<0.05) Vegetables: cOR 1.08(0.68-1.71) Fruit: cOR 1.83(0.95-3.52) Meat, beans nuts and egg:aOR 0.92(0.39-2.15) Milk: aOR 1.33(0.20-8.59) Grains: aOR 2.00(1.11-3.61, p<0.05) Vegetables: aOR 1.03(0.64-1.65) Fruit: aOR 1.76(0.88-3.53) Zareei et al 2019 (70) NA NA Unhealthy dietary pattern (quartile 1 vs quartile 4): cOR 0.768 (0.337-1.75, p=0.529) Healthy dietary pattern (quartile 1 vs quartile 4): cOR 0.219 ( 0.090 - 0.528, p = 0.001) Unhealthy dietary pattern (quartile 1 vs quartile 4: aOR 1.381 (0.462-4.126, p=0.564) Healthy dietary pattern (quartile 1 vs quartile 4): aOR 0.178 (0.059 - 0.530, p= 0.002) ANC – antenatal care; aOR – adjusted odds ratio; CI – confidence interval; cOR – crude odds ratio; g – gram; NA – not available; PE – pre-eclampsia; RR – risk ratio 251 D.6 ROBINS-I Risk of Bias quality assessment D.7 Summary risk of bias 252 D.8 Adjustment factors in multivariable analyses Reference Confounding factors controlled (99) Socio-demographic factors Reproductive factors Lifestyle factors Other factors Maternal age Ethnicity SES Family history of hypertension History of hypertension History of PIH Early pregnancy blood pressure Season of childbirth Gestational age Parity / gravidity Pregnancy interval Pre-pregnancy BMI Height Gestational weight gain Smoking Physical activity Total energy intake Dietary supplement use Other nutrients/ foods/ pattern Abbasi et al 2019 (69) Y Ex Ex Y Y Y Y History of miscarriage, drug use, differences in physical activities prior as opposed to during the pregnancy Atkinson et al 1998 (59) Y Ex Ex 253 Endeshaw et al 2015 (62) Y Y Y Y Rural/urban residence, anemia Grum et al 2017 (63) Y Ex Y Y Y Martial status, pregnancy multiplicity Grum et al 2018 (67) Ex Y Y Y Y Nutritional counselling during ANC, pregnancy planning and contraceptive use, nutritional counseling during ANC Gulsen et al 2012 (61) Hajianfar et al 2018 (66) Y Y Y Y Kahsay et al 2018 (65) Y Y Ex Y Y Y Y Rural residence, gestational diabetes mellitus and pre-pregnancy oral contraceptive use 254 Longo-Mbenza et al 2008 (60) Ex Mekie et al 2020 (71) Y Y Ex Y Y UTI, family planning, multiple pregnancy, nutritional counselling at ANC, number of ANC visits, planned pregnancy, education status, cohabitation duration Mi et al 2019 (68) Y Y Y Y Y Y Intervention group assignment in the trial, educational level, occupation Sheikhi et al 2018 (64) Y Ex Y Y Y 255 Zareei et al 2019 (70) Y Ex Y Y Y Y Educational level, gestational diabetes in previous pregnancy, occupational status Y – Controlled factor in multivariable analyses due to adjustment or matching; Ex – Excluded in recruitment256 Chapter 4 appendix for the community perspectives qualitative study E.1 Qualitative analysis coding framework Codes Sub-codes Description Maternal dietary patterns and dietary diversity Typical meals Typical meals for breakfast, lunch, and dinner Special diets for pregnant and lactating women Mentions of foods especially eaten during pregnancy, delivery and breastfeeding Consumption patterns Staple foods, luxury foods, seasonal foods, special occasion foods, snacks and non-nutritive foods for children, other Influencing factors Descriptions of factors that impact the type of foods pregnant women are able to eat Community knowledge of healthy maternal diets Healthful foods Foods that are described as healthy for pregnant and lactating mothers Unhealthy foods Foods that are described as unhealthy for pregnant and lactating mothers Beliefs about maternal diets Reasons why for eating or avoiding certain foods Associations between maternal diets and health Local conceptualizations on how maternal diets connect with maternal health, sources of information and knowledge gaps Food security Experiences of food insecurity Descriptions of food insecurity, including worry, few foods, unable to get healthy foods, ate less, skipped meals, household ran out of food, hungry but did not eat, did not eat for a whole day Experiences of food security Descriptions of feeling food security in their household Coping mechanisms Methods for coping with food insecurity Barriers and facilitators Factors that impacted availability, accessibility, use/utilization and stability of household food supply Other Other Other topics that did not fit existing codes 257 E.2 Frequency of reported themes Number of participants Number of references coded Kenya (n=18) The Gambia (n=15) Mozambique (n=14) Total (n=47) Kenya The Gambia Mozambique Total Staple foods 17 (94%) 11 (73%) 13 (93%) 41 (87%) 41 22 35 98 Special foods for pregnancy 18 (100%) 15 (100%) 14 (100%) 47 (100%) 68 90 49 207 Special foods around delivery 14 (78%) 0 (0%) 8 (57%) 22 (47%) 30 0 15 45 Special foods for lactation 16 (89%) 12 (80%) 13 (93%) 41 (87%) 32 18 33 83 Value of dietary diversity overall 16 (83%) 10 (67%) 11 (79%) 37 (79%) 32 15 33 80 Maternal dietary diversity 14 (78%) 10 (67%) 10 (71%) 34 (72%) 40 21 16 77 Feasibility of diverse meals 11 (61%) 14 (93%) 12 (86%) 37 (79%) 22 33 29 84 Influencing factors Affordability 18 (100%) 15 (100%) 13 (93%) 46 (98%) 162 77 90 329 Seasonality 17 (94%) 15 (100%) 13 (93%) 45 (96%) 73 92 83 248 Droughts/storms 12 (67%) 3 (20%) 3 (21%) 18 (38%) 38 3 11 52 Gender norms 18 (100%) 12 (80%) 10 (71%) 40 (85%) 82 44 23 149 Knowledge 18 (100%) 15 (100%) 14 (100%) 47 (100%) 61 56 44 161 Cravings 17 (94%) 9 (60%) 14 (100%) 40 (85%) 60 15 68 143 Traditional beliefs 17 (94%) 10 (67%) 13 (93%) 40 (85%) 58 22 25 105 Religion and celebrations 16 (89%) 8 (53%) 10 (71%) 34 (72%) 57 12 16 85 Rural residence 8 (44%) 12 (80%) 4 (29%) 24 (51%) 16 33 12 61 258 E.3 Frequency of themes reported by participant group and number of participants Kenya The Gambia Mozambique Overall PW/ RM (n=7) MR (n=4) FR (n=3) CL (n=4) PW/ RM (n=5) MR (n=3) FR (n=3) CL (n=4) PW/ RM (n=5) MR (n=3) FR (n=3) CL (n=3) PW/ RM (n=17) MR (n=10) FR (n=9) CL (n=11) Staple foods 6 4 3 4 4 2 2 3 4 3 3 3 14 9 8 10 Special foods for pregnancy 7 4 3 4 5 3 3 4 5 3 3 3 17 10 9 11 Special foods around delivery 4 3 3 4 0 0 0 0 2 1 2 3 6 4 5 7 Special foods for lactation 5 4 3 4 5 2 3 3 5 2 3 3 15 8 9 10 Value of dietary diversity overall 5 4 3 4 3 2 2 3 3 2 3 3 11 8 8 10 Maternal dietary diversity 5 3 2 4 5 1 0 4 4 2 3 1 14 6 5 9 Feasibility of diverse meals 3 3 1 4 4 3 3 5 4 2 3 3 11 8 7 11 Influencing factors Affordability 7 4 3 4 5 3 3 4 4 3 3 3 16 10 9 11 Seasonality 6 4 3 4 5 3 3 4 4 2 3 3 15 9 9 11 Droughts/storms 3 4 1 4 2 0 0 1 1 1 1 0 6 5 2 5 Gender norms 7 4 3 4 2 3 3 4 2 3 2 3 11 10 8 11 Knowledge 7 4 3 4 5 3 3 4 5 3 3 3 17 10 9 11 Cravings 6 4 3 4 4 1 2 1 5 3 3 3 15 8 8 8 Traditional beliefs 6 4 3 4 4 1 1 4 4 3 3 3 14 8 7 11 Religion and celebrations 7 3 2 4 2 2 1 3 3 1 3 3 12 6 6 10 Rural residence 2 2 2 2 2 3 3 4 1 1 1 1 5 6 6 7 259 PW/RM – pregnant woman or recent mother; MR – male relative (husband or brother-in-law); FR – female relative (mother-in-law or sister-in-law); CL – community leader (village elder, village leader, religious leader, traditional birth attendant) E.4 Community perspectives on influencing factors by country Kenya The Gambia Mozambique Affordability “I did not have money [in my last pregnancy] and the food I had was only one type. I would always eat ugali (stiff maize porridge) and omena (small dried fish)” Recent mother “There are specific types of food that pregnant women and lactating others should depend on but due to lack of affordability, we all depend entirely on rice and coos (millet)…” Spouse “She doesn't have because it can be those such things, those vegetables happen that one has to buy while one has no money.” Recent mother Seasonality “During the rainy season, we have many green vegetables and eat a lot of greens…There are also guavas and other trees that produce fruits. You can just grab them while passing by and eat.” Recent mother “At this moment, it is not easy [to get] food as it is rainy season. You can see some have coos (millet), some groundnuts but others don’t have anything. For some they must buy before they can eat, which is not easy.” Recent mother “In summer, we don't have vegetables… The months of April, May and June, those are the winter period….Until July, we still have something. In August, there is nothing in the farms” Mother-in-law Irregular weather “The problem is like now when there is drought. There is no rain at all there is no food in the shambas (farms) so you can not get healthy foods.” Spouse “Today my biggest constraint is this house because last year’s storm destroyed part of it” Community leader “Because there is no rain and there is drought, so much so that now we [just] eat beans” Mother-in-law Gender norms “For fish, they have to be brought for her (pregnant woman) to eat…When it is not brought, it's just like that. Poor her if it is not brought. She will “If available, they (women) eat and if not, they just sit and wait… That is it… It is your husband who feeds “There's no money to buy those foods… I only have money at the end of the month… when my husband gives it for the household…. 260 completely not get (any fish).” Community leader and protects you.” Traditional birth attendant It's not always that he gives me money to buy curry (stew)” Recent mother Knowledge “Whenever you go to the hospital, the doctor advices to eat fruits, vegetables and soup this helps a lot with increasing blood and energy” Recent mother “As a woman, I am talking from experience. I have also gone through the same experience before. I know the type of foods I use to eat during pregnancy.” Mother-in-law “I didn't learn it anywhere. I just have knowledge, and I know that those foods are good for pregnant women and I, in particular, ate those foods when I was pregnant” Community leader Cravings “For pregnant women, you cannot choose for them food. They are sometimes picky and would only eat what they crave for.” Spouse “My mind used to urge me to eat sweets” Pregnant woman “I have a daughter who during her pregnancy she didn't eat anything other than oranges…That's because it's not the woman's will…But…what she carries in her womb.” Community leader Traditional beliefs “A pregnant woman should not eat eggs because they will give birth to a big baby.” Community leader “Many pregnant women are afraid to eat much bread … It makes the baby too big in the womb, yes” Brother-in-law “What they said in the old days was myth… she can eat eggs…because it provides vitamins for the baby.” Mother-in-law Religion and celebrations “We eat meat during Eid because my husband’s family is Muslim and they celebrate Eid. For me because I am Christian I can cook chicken for Christmas.” Pregnant woman “Well [it] is only during feasts such as Tobaski that people usually have enough meat to eat.” Brother-in-law “Pork and cow are things that are consumed a lot when the end of the year comes or on holidays” Spouse Rural/urban residence “It is not easy to find…unless you come to Mariakani (town)” Mother-in-law “We do not have oranges here. If you go to the urban areas and you see it there, you [can] buy… Pregnant “Fruits are consumed but… the trucks park in the village [sell]… a bowl at 50 meticais [and] when 261 women, when they go for the antenatal clinics and see it being sold, they buy and eat.” Community leader someone buys to resells here, an orange is 10 meticais. So for you to buy an orange is difficult.” Spouse ` 262 Chapter 5 appendix for the prevalence and factors of meeting minimum dietary diversity for women study F.1 Literature review of sub-Saharan African studies reporting determinants of dietary diversity among women Reference Country Participants Study design Outcome Determinants of higher dietary diversity Limitations Agyei et al 2021 (356) Ghana 130 pregnant women from rural district Hospital-based cross-sectional study (Feb-Mar 2020) MDD-W (≥5 out of 10 healthy food groups) - 74.6% • Monthly income ≥GHC 500 (vs <GHC 500, US$ 86) (p < 0.001) • Single period • Recruitment at single antenatal clinic • Analyzed dietary diversity as continuous variable rather than ordinal scale • Unclear reporting Alamirew et al 2023 (315) Ethiopia 421 women aged 15–49 years Community-based cross-sectional study (Apr-Aug 2019) MDD-W (≥5 out of 10 healthy food groups) - 26.8% • Age (33-38 years vs other ages) (p < 0.01) • Primary or more education (vs no education) (p < 0.01) • Knowledge of dietary diversity (p < 0.01) • Husband has primary or more education (vs no education) (p < 0.01) • Decision-making power on food purchasing and consumption (p < 0.01) • Single period (after harvest season) • Single region in Ethiopia • Did not adjust for potential confounders 263 • Cultural beliefs and practices associated with gender inequality (Prioritize husbands for food consumption, women should not eat in public or eat much food, gendered food restrictions (p < 0.01) • Food intake after serving family (p < 0.05) Amugsi et al 2016 (349) Ghana 2262 women aged 15–49 years National community-based cross-sectional study (Sep-Nov 2008; Ghana Demographic and Health Survey) DD≥5 on WDDS (9 healthy food groups) - 43.1% • Decision-making regarding household purchases (vs no decision-making OR 1.74, 95% CI: 1.24-2.42) • Secondary level or higher maternal education (vs no education OR 1.57, 95% CI: 1.12-2.20) • Monogamous households (vs polygamous households OR 1.42, 95% CI: 1.04-1.93) • Higher household wealth (Richer Q4 vs poorest Q1 OR 1.68, 95% CI: 1.07-2.64; richest Q5 vs poorest Q1 OR 1.81, 95% CI: 1.05-3.14) • Single period • Earlier measure of dietary diversity (organ meats was its own food group) Anyanwu et al 2021 (346) Ethiopia 4680 pregnant women followed to 1 year postpartum Prospective pregnancy cohort (2014-2016; - ENGINE USAID study MDD-W (≥5 out of 10 healthy food groups) – 13-17% • Agricultural land (per one unit increase, aOR 1.10, 95% CI: 1.01-1.19) • Farm equipment (per one additional piece of equipment, aOR 1.23, 95% CI: 1.10-1.38) • Food crops (per one additional type grown, aOR 1.13, 95% CI: 1.09-1.18) • Unclear reporting of MDD-W during pregnancy vs postpartum • Analyzed dietary diversity as 264 • Nonfood crops (per one additional type grown, aOR 1.36, 95% CI: 1.21-1.52) • Livestock (per one additional type raised, aOR 1.15, 95% CI: 1.11-1.20) continuous variable rather than ordinal scale Azene et al 2021 (342) Ethiopia 10,780 pregnant women Systematic review and meta-analysis of 23 studies MDD-W (≥5 out of 10 healthy food groups) -41% • Primary or more maternal education (vs no education, OR 2.11, 95% CI: 1.10-4.05) • Had nutritional information (vs no information, OR 4.1, 95% CI: 2.10-7.99) • Knowledge about dietary diversity (vs no knowledge, OR 3.4, 95% CI: 2.73- 4.73) • High wealth index (vs low wealth index, OR 3.45, 95% CI: 1.19-10.01) • Asymmetrical funnel plot suggest potential publication bias • High heterogeneity Chakona and Shackleton 2017 (307) South Africa 554 women aged 15–49 years Prospective cohort study Visited twice (Oct-Nov 2014 pre-harvest and Jun 2015 post-harvest) MDD-W (≥5 out of 10 healthy food groups) - 25% • Urban vs rural (p<0.05) • Higher wealth and food expenditure (p<0.05) • Did not adjust for potential confounders • Unclear generalizability beyond the three towns analyzed in study Delil et al 2021 (350) Ethiopia 303 pregnant women Hospital-based cross-sectional MDD-W (≥5 out of 10 healthy • High household income (≥2000 Ethiopian birr monthly vs low <1000 birr; aOR 1.62, 95%CI:1.19–2.85) • Single period • Recruitment at a single antenatal clinic 265 study (May-Jun 2019) food groups) -42.6% • Maternal higher education (vs no education, aOR 2.50, 95% CI: 1.05–6.12) • Educational status of partner (vs no education, aOR 2.45, 95% CI:1.20, 9.57) • Husband’s occupation as a salaried government employee (vs day labourer, aOR 4.0, 95% CI:2.18–7.21) • Nutritional information (vs no information, aOR 1.35, 95% CI: 3.39–6.94) at a large referral hospital Getahun et al 2023 (344) Ethiopia 594 pregnant women Community-based cross-sectional study (Aug-Sep 2021) MDD-W (≥5 out of 10 healthy food groups) – 59.9% Odds of unmet MDD-W: • No formal education (vs high school or higher; aOR 3.46, 95% CI: 1.99-5.66] • Poor by the wealth index (vs wealthy; aOR 2.23, 95% CI:1.33-3.73) • Having five or more children (vs less than 5; aOR 1.75, 95% CI:1.14-2.71) • Multigravida (vs gravida 1; aOR 2.18, 95% CI:1.34-3.56) • Male-headed households (vs female headed; aOR 4.46, 95% CI: 2.86-6.94) • Single period 266 Gitagia et al 2019 (340) Kenya 384 women aged 18–49 years Community-based cross-sectional study in a high vs low agro-biodiversity area (Mar-Apr 2016 MDD-W (≥5 out of 10 healthy food groups) -22% in high /16% in low agro-diverse areas • High maternal education (vs low, in both low and high agricultural potential areas aOR 3.65, 95% CI: 1.21–10.9; aOR 5.32, 95% CI: 2.27–12.46) • Male headed household (vs female, in high agricultural potential areas aOR 4.15, 95% CI:1.16–14.86) • Older maternal age (in high agricultural potential areas aOR 1.13, 95% CI: 1.07–1.18) • Smaller households (vs larger households, in high agricultural potential areas, aOR 1.30, 95% CI: 1.05-1.61) • Single period (during rainy season) Gyimah et al 2021 (343) Ghana 416 pregnant adolescents aged 13–19 years Prospective cohort (May 2018-Jul 2019) MDD-W (≥5 out of 10 healthy food groups) -44% • Higher proportion of rural than urban had low dietary diversity (p = 0.008) • Higher proportion of lower education had low dietary diversity (p = 0.031) • Did not analyze determinants of minimum or higher DD • Did not adjust for potential confounders • Adolescent population only Kassahun et al 2023 (347) Ethiopia 471 pregnant women Health facility-based cross sectional MDD-W (≥5 out of 10 healthy food • Rural residence (vs urban, aOR 12.5, 95% CI: 3.03-50.0) • Smaller household size <3 (vs larger household, aOR 7.28, 95% CI: 3.25-16.28) • Single period • Single region in Ethiopia (one city) 267 study (Jan-Mar 2018) groups) -52.7% • Husband occupation in business (vs non-business, aOR 2.55, 95% CI: 1.39-4.6) • Husband support (vs lack of support, aOR 3.85, 95% CI: 1.23 -12.02) • House size more than 1 room (vs 1 room, aOR 5.7, 95% CI: 2.32-13.8) • Higher household wealth (Medium T2 aOR 1.93, 95% CI: 1.1-3.39, Rich T1 aOR 2.12, 95% CI: 1.18- 3.81, vs poor T3) Kiboi et al 2017 (351) Kenya 254 pregnant women Hospital-based cross-sectional study DD ≥4 (out of 14 food groups) • Secondary level maternal education (vs no education, aOR 2.78, 95%CI: 1.06-5.32) • Salaried employment (vs unemployed aOR 2.2, 95% CI:1.18-4.14) • Monthly income (20001–30000 KSh vs <10000 aOR 2.08, 95% CI:1.32-3.03) * Land ownership was considered significant (p<0.05) but confidence interval crossed 0 thus excluded in our review • Single period (one month, data collection period unclear) • Recruitment at a single antenatal clinic at a large referral hospital • Potential overreliance on p-value Madzorera et al 2020 (40) Tanzania 7553 HIV-negative pregnant women Secondary analysis of a randomized controlled trial (Aug MDD-W (≥5 out of 10 healthy food Highest vs lowest dietary diversity • Older maternal age (p<0.001) • Secondary level maternal education or higher (p<0.001) • Did not analyze determinants of minimum DD 268 2001-Jul 2004) groups) -2.8% Highest DD (Q5) vs lowest DD (Q1) • Household wealth and greater food expenditure per day (p<0.001) • No children (p<0.05) • Did not adjust for potential confounders for determinants Nkoko et al 2023 (341) Lesotho 199 women 15–49 years Community-based cross-sectional study (Mar-Jun 2022) MDD-W (≥5 out of 10 healthy food groups) - 20.6% • Smaller household sizes (p<0.05) • Higher monthly income (p<0.05) • Older age (p<0.05) • Participated in agricultural development project (p<0.05) • Single period • Did not report crude along with adjusted outcomes; did not report point estimates Ochieng et al 2017 (300) Tanzania 204 households in two districts Community based cross-sectional study (Dec 2015-Jan 2016) MDD-W (≥5 out of 10 healthy food groups) – 46% • Male headed household (vs female headed, p<0.05) • Younger age of the household head (vs older age, p<0.05) • Production of vegetables (vs no production, p<0.05) • Access to agricultural land (vs no access, p<0.05) • Single period • Did not analyze determinants of minimum DD • Linear regression originally used for ordinal scale, though validated by ordinary least squares regression; point estimates not reported 269 Saaka et al 2021 (348) Ghana 423 pregnant women Health facility based cross-sectional study MDD-W (≥5 out of 10 healthy food groups) – 79.9% • Smaller household <4 members (aOR 3.07, 95%CI: 1.13-8.39) • High household wealth (aOR 1.92, 95%CI: 1.14-3.23) • Single period (data collection period unclear) • Recruiting women at antenatal care may miss women with late or lacking attendance Tilahun et al 2021 (345) Ethiopia 274 pregnant women Hospital-based cross-sectional study (Jan-Feb 2021) MDD-W (≥5 out of 10 healthy food groups) – 51% • Younger maternal age (< 25 years aOR 4.65, 95% CI: 1.404 - 15.396; 25–34 aOR 3.62, 95% CI: 1.315-10.269, vs > 34 years old) • Older husband age (26–34 aOR 2.24, 95% CI: 1.028 - 4.873; 35–44 aOR 3.55, 95% CI: 1.228-10.292) vs 19–25 years old) • Nutrition awareness (vs no awareness aOR 2.182, 95% CI: 1.243-3.829) • Single period • Recruitment at a single antenatal clinic at a large hospital aOR – adjusted odds ratio; CI – confidence interval; DD – dietary diversity; GHC - Ghanaian Cedi; KSh – Kenyan Shilling; MDD-W – minimum dietary diversity for women; OR – odds ratio; Q1/Q5 – quintile 1/ quintile 5; T1/T3 – tertile 1/tertile 3; WDDS – women dietary diversity score (previous version of MDD-W based on nine food groups) 270 F.2 Model selection for determinants of meeting MDD-W Model 1* (95% CI) Model 2† (95% CI) Model 3‡ (95% CI) Model 4§ (95% CI) Country Kenya ref ref ref ref Mozambique OR 0.79¶ (0.71-0.87) aOR 0.77¶ (0.68-0.86) aOR 0.87¶ (0.76-0.99) aOR 0.88 (0.77-1.00) The Gambia OR 2.27¶ (2.02-2.56) aOR 2.59¶ (2.27-2.96) aOR 2.94¶ (2.51-3.44) aOR 3.13¶ (2.64-3.71) Cohort Non-pregnant ref ref ref ref Pregnant OR 1.12¶ (1.00-1.25) aOR 1.38¶ (1.22-1.56) aOR 1.44¶ (1.27-1.63) aOR 1.42¶ (1.25-1.61) Residence Rural ref ref ref ref Periurban OR 0.81¶ (0.74-0.89) aOR 0.90¶ (0.82-0.99) aOR 0.85¶ (0.77-0.93) aOR 0.84¶ (0.77-0.93) Age 15-19 years OR 0.81¶ (0.70-0.93) aOR 0.76¶ (0.64-0.91) aOR 0.89 (0.74-1.07) aOR 0.90 (0.75-1.08) 20-24 years OR 0.94 (0.84-1.04) aOR 0.91 (0.81-1.03) aOR 0.98 (0.87-1.11) aOR 0.98 (0.86-1.11) 25-34 years ref ref ref ref ≥35 years OR 0.99 (0.86-1.14) aOR 1.04 (0.90-1.21) aOR 1.05 (0.90- 1.22) aOR 1.06 (0.91-1.24) Parity 0 previous births ref ref ref ref 1-4 previous births OR 1.05 (0.95-1.16) aOR 1.01 (0.89-1.14) aOR 1.18¶ (1.03-1.35) aOR 1.18¶ (1.03-1.36) 5 or more previous births OR 1.18¶ aOR 0.82 aOR 1.07 aOR 1.06 271 (1.01-1.39) (0.67-1.00) (0.87-1.33) (0.85-1.32) Marital status Single OR 0.92 (0.82-1.03) aOR 1.31¶ (1.14-1.50) aOR 1.22¶ (1.06-1.41) aOR 1.51¶ (1.25-1.81) Married/Co-habiting ref ref ref ref Polygamous marriage OR 1.60¶ (1.38-1.86) aOR 0.93 (0.78-1.11) aOR 0.98 (0.82-1.16) aOR 0.96 (0.81-1.14) Separated/Divorced/Widowed OR 0.84 (0.59-1.19) aOR 0.94 (0.65-1.35) aOR 0.94 (0.65-1.36) aOR 1.14 (0.76-1.69) Education None ref NA ref ref Primary school OR 0.52¶ (0.46-0.59) NA aOR 0.93 (0.80-1.09) aOR 0.93 (0.80-1.09) Secondary school OR 0.69¶ (0.61-0.79) NA aOR 1.30¶ (1.10-1.53) aOR 1.28¶ (1.09-1.51) Higher education OR 1.39¶ (1.14-1.71) NA aOR 2.06¶ (1.61-2.64) aOR 2.01¶ (1.57-2.58) Occupation Housewife ref NA ref ref Student OR 0.98 (0.82-1.17) NA aOR 1.09 (0.88-1.33) aOR 1.12 (0.91-1.38) Market trader OR 0.91 (0.77-1.09) NA aOR 1.06 (0.88-1.28) aOR 1.05 (0.87-1.27) Laborer OR 1.39 (0.97-1.99) NA aOR 1.66¶ (1.15-2.41) aOR 1.68¶ (1.15-2.45) Professional OR 1.60¶ (1.26-2.05) NA aOR 1.34¶ (1.02-1.76) aOR 1.35¶ (1.03-1.77) Women’s autonomy for decision-making on household spending No ref NA NA ref Yes OR 0.86¶ (0.75-0.98) NA NA aOR 1.07 (0.85-1.35) 272 Gender of primary household decision-maker Male-headed household ref NA NA ref Female-headed household OR 0.81¶ (0.73-0.91) NA NA aOR 0.89 (0.73-1.08) Living arrangements Lives alone OR 1.35¶ (1.10-1.67) NA NA aOR 0.91 (0.72-1.15) Husband or partner ref NA NA ref Lives with in-laws OR 1.21¶ (1.09-1.34) NA NA aOR 0.90 (0.78-1.03) Natal parents or relatives OR 0.93 (0.82-1.06) NA NA aOR 0.77¶ (0.63-0.95) Household size Small household ref NA NA ref Medium household OR 0.78¶ (0.70-0.88) NA NA aOR 0.85¶ (0.75-0.97) Large household OR 1.19 (1.07-1.34) NA NA aOR 0.91 (0.78-1.06) 95% CI – 95% confidence interval; OR – odds ratios; aOR – adjusted odds ratios; ref – reference category; NA – not applicable *Model 1 comprises of unadjusted odds ratios †Model 2 adjusted for basic demographics (country, cohort, location, age, parity, marital status) AIC: 10314 ‡Model 3 adjusted for basic demographics (country, cohort, location, age, parity, marital status) and social-economic status (education and occupation) AIC: 10190 §Model 4 adjusted for basic demographics (country, cohort, location, age, parity, marital status), social-economic status (education and occupation), women’s autonomy (decision-making), and household composition (gender of primary household decision-maker, living arrangements, household size) AIC: 10136 ¶ p <0.05 273 Chapter 6 appendix for the mixed methods study on characterizing dietary diversity patterns G.1 Qualitative content analysis coding framework from Nvivo Code Structure Hierarchical Name Code Codes Codes\\1. Grains and white roots Codes\\1. Grains and white roots\Grains Codes\\1. Grains and white roots\White roots Codes\\2. Beans Codes\\3. Nuts Codes\\4. Milk Codes\\5. Meat, poultry and fish Codes\\5. Meat, poultry and fish\Fish and seafood Codes\\5. Meat, poultry and fish\Meat and poultry Codes\\5. Meat, poultry and fish\Organ meats Codes\\6. Eggs Codes\\7. Dark green leafy vegetables Codes\\8. Other vitamin A-rich fruits and vegetables Codes\\8. Other vitamin A-rich fruits and vegetables\Dark yellow and orange fleshed fruits Codes\\8. Other vitamin A-rich fruits and vegetables\Orange fleshed vegetables Codes\\9. Other vegetables Codes\\10. Other fruit Codes\\11. Fried and salty foods Codes\\12. Sweets and bakery Codes\\13. Sweetened drinks Formatted Reports\\Coding Structure Formatted Report Page 1 of 1 274 G.2 Consumption patterns of meat, poultry and fish by sub-groups Kenya (n=2856) Mozambique (n=2066) The Gambia (n= 1244) Total (n=6166) Organ meats 267 (9.3%) 537 (26.0%) 153 (12.3%) 957 (15.5%) Meat and poultry 844 (29.6%) 711 (34.4%) 312 (25.1%) 1867 (30.3%) Fish and seafood 1057 (37.0%) 772 (37.4%) 876 (70.4%) 2705 (43.9%) G.3 Model-fit statistics for latent class analysis Pregnant women from the PRECISE cohort Kenya (n=2856) Mozambique (n=2066) The Gambia (n=1244) BIC BIC BIC Latent classes (dietary patterns) = 1 44895.48 31314.81 19397.04 Latent classes (dietary patterns) = 2 43693.07 26534.02 19081.51 Latent classes (dietary patterns) = 3 43410.19 25970.59 19125.36 Latent classes (dietary patterns) = 4 43445.88 25931 19169.55 Latent classes (dietary patterns) = 5 43510.36 25871.38 19235.21 Latent classes (dietary patterns) = 6 43578.62 25845.85 19304.34 Latent classes (dietary patterns) = 7 43651.39 25861.88 19377.42 BIC – Bayesian Information Criterion 275 G.4 Food group consumption patterns across latent classes in Kenya, Mozambique and The Gambia Kenya Mozambique The Gambia Class 1 (n=131) Class 2 (n=1637) Class 3 (n=1088) Class 1 (n=326) Class 2 (n=659) Class 3 (n=1081) Class 1 (n=158) Class 2 (n=630) Class 3 (n=456) Starchy staple foods 0.9667 0.9237 0.8357 0.9902 0.9782 0.9478 0.9773 0.9836 0.9297 Beans 0.9016 0.4054 0.2780 0.9532 0.2966 0.1426 0.5913 0.2504 0.1817 Nuts 0.6861 0.1371 0.0449 0.9281 0.4410 0.3525 0.7930 0.5758 0.5132 Milk 0.7822 0.5838 0.2104 0.8148 0.1951 0.0436 0.7743 0.5260 0.3211 Flesh foods 1.0000 0.6367 0.4567 0.9880 0.6462 0.3482 0.8972 0.9240 0.6388 Eggs 0.7392 0.1859 0.0589 0.9595 0.3555 0.0881 0.6557 0.2251 0.1549 Leafy greens 0.9441 0.6469 0.4948 0.9811 0.7775 0.6613 0.6520 0.3604 0.2653 Other vitamin A fruits and vegetables 0.9740 0.6253 0.2747 0.9864 0.7345 0.2939 0.7843 0.6474 0.4065 Other vegetables 0.8895 0.2902 0.2019 0.8440 0.4460 0.0373 0.8382 0.6952 0.3438 Other fruit 0.9137 0.5643 0.1560 0.7673 0.5439 0.0775 0.5969 0.3761 0.1576 Fried and salty foods 0.8704 0.4971 0.1905 0.9115 0.3354 0.0233 0.7103 0.3421 0.2069 Sweets 0.9032 0.4447 0.1414 0.8804 0.3055 0.0740 0.9058 0.5243 0.2517 Sweetened beverages 0.8130 0.5302 0.2120 0.8010 0.3404 0.0877 0.5551 0.3865 0.1403 276 G.5 Summary of main foods consumed in each food group Food group Kenya Mozambique The Gambia Grains and white roots and tubers Grains: Ugali (stiff maize meal porridge), rice, bread White roots: Cassava, Irish potatoes, matoke (green bananas) Grains: Xima (stiff maize meal porridge), rice, bread, pasta White roots: Cassava Grains: Coos (pearl millet), rice, maize, bread White roots: Cassava, potatoes Beans, peas and lentils Beans, green grams (lentils), cowpeas Tibawene/ nhemba bean (cowpeas), butter beans Beans, petit pois (green peas) Nuts and seeds Groundnuts Groundnuts and groundnut butter Groundnuts, groundnut butter, cashews Milk and milk products Milk for tea, maziwa mala (natural yogurt/ fermented milk) Milk for tea, powdered milk Cow’s milk, sour milk (yogurt), tin milk (powdered milk) Meat, poultry and fish Organ meats: goat, cow and sheep intestines Meat and poultry: chicken, beef, goat Fish and seafood: omena (small dried fish), kata shingo (fried sardines), kimala wari, dried shark Organ meats: beef pancreas, chicken gizzards Meat and poultry: chicken (whole or parts such as legs or wing), beef, pork, goat Fish and seafood: carapau (horse mackerel fish), xidliwane (tilapia), black fish (freshwater fish) Organ meats: liver Meat and poultry: chicken (whole or parts such as legs), beef, goat Fish and seafood: Fish, tilapia fish Eggs Chicken eggs Chicken eggs Chicken eggs 277 Dark green leafy vegetables Mchicha (amaranth leaves), mkunde (cowpea leaves), mchunga, tsalakushe, mnavu , mrenda and bwere (wild leafy greens), moringa, sukuma (kale) Matsavo (pumpkin) leaves, cacana (balsam apple) leaves, matapa (cassava leaves), sweet potato leaves, kale, Keren kereng (green leaves), moringa and nduro (wild leafy greens), sorrel leaves, baobab leaves, cassava leaves, sweet potato leaves Other vitamin A fruits & vegetables Dark yellow and orange fleshed fruit: Mango and pawpaw (papaya) Orange fleshed vegetables: carrots, sweet potatoes, pumpkins Dark yellow and orange fleshed fruit: Mango and papaya Orange fleshed vegetables: carrots, sweet potatoes, pumpkins Dark yellow and orange fleshed fruit: Mango and pawpaw (papaya) Orange fleshed vegetables: carrots, sweet potatoes, pumpkins Other vegetables Cabbage, tomatoes, onions, eggplants, okra, green peppers Cabbage, tomatoes, onions, okra, beets, lettuce (light green) Cabbage, tomatoes, bitter tomatoes, onions, garden eggs (eggplant), peppers, lettuce (light green) Other fruit Passionfruit, guavas, avocado, bananas, oranges, watermelon Banana, apple, oranges, tangerines, lemons, avocado Oranges, apples, bananas, watermelon, dudeh (bush mango), lemons, limes, tomborongs and kunkungs (wild fruits) Fried & salty foods Potato crisps, cassava crisps, fried potatoes, sambusa (samosa), mahamri (fried scones), chapatti (fried unleavened flatbread Junk food, take-away roast chicken or beef, fiosse (fried biscuits) Snacks 278 Sweets and bakery goods Toffi, lollipops, chewing gum, cakes, biscuits Sugarcane, cakes Sweets, mints, chewing gum Sweet beverages Soda (Coke, Fanta, Sprite, club soda), sweetened tea, juice Coke, Fanta, sweetened tea, G-Vita juices (powder juice), juice Attaya (sweetened green tea), wonjo (sweetened juice from sorrel), soft drinks 279 G.6 Illustrative quotes about food groups by country Food group Sub-groups Kenya Mozambique The Gambia Grains and white roots Grains “The food that is mostly eaten is ugali (stiff maize meal porridge) made of maize flour” Community leader (MRK-IDI-CL01) “Rice is eaten and also maybe chapatti, but mostly it is ugali.” Community leader (RBI-IDI-CL02) “Food that is mostly eaten…for breakfast is tea and … bread….” Mother (RBI-IDI-RM02) “Nowadays, they take it with tea, it does not matter if they have milk or not they would always take tea… They would take tea and tosi (toast), tea and bread…” “Here in this community, the typical dishes are rice and xima (stiff maize meal porridge), which are harvested in the field. Afterwards, the maize is ground in the mills to make xima” Spouse (IDI_001) “We eat more xima, so the expense of buying food is reduced” Mother-in-law (IDI_009) What is the most common thing to eat in this neighbourhood… is bread... Bread is a lot and you eat a lot of it.” Mother-in-law (IDI_004) “One takes tea [for breakfast], but… you see the development is that tea with xima or with bread” Community leader (IDI_008) “For us, we depend almost entirely on rice and coos (pearl millet)… We normally cook [coos] porridge in the morning as our breakfast. Rice as lunch and dinner… [It] is only maize that is seasonal that you cannot be able to have during certain times of the year…. our feeding depends mainly on coos, rice and bread.” Brother-in-law (IDI_005) “The type of food we eat here mostly is rice, [and] findi (fonio millet)… both during the day and during the night.” Husband (IDI_002) “Bread… is eaten here almost every day… People are always eating bread.” Mother (IDI_004) White roots and tubers or plantains “We get cassavas only when it rains” Mother (MRK-IDI-RM02) “For Irish potatoes, we have to buy them. We can cook rice and potato soup… These ones are mostly eaten during drought…” Community leader (MRK-IDI-CL02) “All the banana types…you have to buy them in shops… [M]aybe for the kids, they will have to buy “Cassava is consumed a lot…When you have cassava, [you can eat it] when you wake up everyday with tea… [but] cassava has a specific month… from August” Mother (IDI_003) “Cassava…takes us three to four months before we harvest it… It is only available during certain times of the year” Spouse (IDI_002) “Potatoes when you plant them… and… cassava … You can eat two times [a week, but] they are not available throughout the year” Mother (IDI_011) 280 matoke (green bananas) [and] beans to cook for the children Beans Beans “Beans, also green grams (lentils) but… mostly we cook beans….Mostly, it is two times [a week]” Mother (MRK-IDI-PG01) “Beans are what are regularly eaten especially in placement of omena (dried fish)… [but] it’s not [eaten] regularly… When someone has money to buy beans they would just buy and cook.” Community leader (MRK-IDI-CL01) “Now that it is raining, people have grown cowpeas, the cowpeas are especially grown unlike beans and green grams” Community leader (RBI-IDI-CL01) [For feast day,] “we can cook rice with beans or the chicken that I am raising” Pregnant woman (RBI-IDI-PG01) “We eat chapatti and beans but it’s not common. We can eat it once a month or even once a year due to the harsh living conditions” Husband (RBI-IDI-SP02) “It’s not common… unless such times when they are given [as] relief food… But finding them just buying peas to cook, no” “Butter beans is the most widely consumed… When we do the shopping first, we start with the beans, because it is one of the most consumed foods… but it also depends on money… sometimes there is no money to be able to buy” Mother-in-law (IDI_009) “Butter beans…They cook them twice a week.” Husband (IDI_013) “We cook beans…for lack of curry (stew)… you don't want to cook beans today then cook tomorrow, the day after tomorrow…We don't want eat beans all year round… [but] we people are always eating them. ” Mother-in-law (IDI_004) “The beans we eat are the ones that are sold.” Pregnant woman (IDI_005) “Now that it doesn't rain, what is cooked frequently is beans… Tibawene (nhemba beans) and the butter beans themselves. If it is bean time (harvest), you eat a lot of them. If it's not bean time now, you just have to buy butter beans and cook them… There may be those who eat 3 times (a week); there may be those who eat 2 times… At least for my part… I don't like beans… [but] I can't get something else I can cook at home so I cook...” Pregnant woman (IDI_006) “Beans, you can eat it about five times [a week], because we do grow beans and so we have it. When the rainy season comes, we grow beans and when it is ripe, we harvest and dry them in the sun. That is why we eat beans.” Mother (IDI_011) “We do eat beans as well, you know, because these are things that is produced by us. Although we don't grow it at a larger scale, but then we only produce it, for our domestic consumption… [S]ometimes, it takes a long time before you can be able to eat it… They are availability of beans is not constant but instead it's just seasonal.” Brother-in-law (IDI_005) “For beans, we eat from time to time but during the fast month (Ramadan), we give it to the women to cook and we break fast with it…every evening. During the dry season, we eat just a bit from time to time which you must buy from the Lumo (Weekly market).” Community leader (IDI_014) “One time [a week]... when they (pregnant women) have it, they would eat it, but you know to get the money is difficult.” Mother (IDI_010) “We do eat beans or petit pois (green peas)…from time to time. You cook when 281 Community leader (MRK-IDI-CL01) you have it… [P]etit pois…is not easy to get here.” Mother (IDI_007) Nuts Nuts “We only have groundnuts and that is only when a mother has got five shillings and so while she is walking around the shops and pass by them that’s when she will buy….It’s not a regular thing…It’s once a week or even less than once a week.” Community leader (MRK-IDI-CL01) “Mostly I have been seeing men eat more of them. You will find a man eating even in a matatu (shared van taxi) or while walking or while he is seated at some place making stories with fellow men while chewing khat (stimulant leaf) with groundnuts. But it is very rare to find a man bringing groundnuts to his wife or kids” Community leader (MRK-IDI-CL02) “For cashew nuts, I do not even remember when last I ate them. For the groundnuts, there times I eat them but I can finish a whole month without eating them… For groundnuts, if I see them and feel like having them then I can buy the sh. 10 packet and eat together with my children” Mother-in-law (MRK-IDI-ML02) “Truth is, they (groundnuts) are very rare. Maybe on a personal “There is not a house where you go more than two days without consuming groundnuts… Groundnut is not rare, there is just no monetary conditions in people” Community leader (IDI_011) “I also like groundnuts when I'm pregnant…Anytime having then money, even if it's 5mts, I was going to buy it.” Mother (IDI_003) “We use groundnuts a lot…Because groundnuts are not expensive compared to oil” Mother (IDI_002) “Groundnut butter is eaten and so are groundnuts… Most days we eat xitsakatu (green leafy vegetables with groundnuts).” Mother-in-law (IDI_004) “What we eat with some frequency is groundnuts… Sometimes we can buy two to three kilos… at least three months during the year… It is a food that we use to prepare meals and it is a healthy food, but due to lack of money, it is difficult for us to catch, but we buy it when we have money.” Mother-in-law (IDI_009) “Groundnut is part of our daily meal because it is produced by us…. We always eat groundnut…. We keep eating groundnut soup throughout the year.” Mother-in-law (IDI_003) “[We eat groundnuts] almost once in a week, because you know that is a type of food that many people don’t seem to like now… It is always available. It has never been scarce… Sometimes, they (pregnant women) can prepare it as groundnut sauce (butter) and put it on coos flour, nown as Futo in the Mandinka language.” Mother-in-law (IDI_006) “Groundnuts, you may eat it up four times in a week… There are sometimes when they are not available because when the rainy season comes, things become difficult… Some do eat but others may not get what gives it to them (money). You may like to eat but you cannot get it” Mother (IDI_011) “Like groundnuts butter… even yesterday, my people cooked groundnuts soup, yes…It is good and is better than oil. According to what our grandparents said, groundnuts soup and green leaves are better than oil.” Community leader (IDI_014) “For cashews, it is seasonal. It is only during certain times of the year that you 282 level, if someone wants to eat them… they can be found on the roadside…for sh.5 or sh.10. They just like a snack” Community leader (RBI-IDI-CL02) can have it. Once that passes, you can no longer be able to see it around.” Brother-in-law (IDI_005) Milk or milk products Milk or milk products “On Christmas and New Year day, you might find people buying milk. That day people will buy for themselves milk and even take milk tea. But finding a family just taking milk? That is a very rare thing.” Community leader (MRK-IDI-CL01) Regarding milk consumption, “not often… (Laughs) Let me just say maybe two times [a week] because it is by luck… it is not that milk is not available. It is because of the ability” Pregnant woman (MRK-IDI-PG01) “As of now milk has become expensive. A packet of milk is sold at sh.80. If I get sh.100 and take sh.80 to buy milk, I will remain with only sh.20 and I have not yet bought sugar or bread. I would rather just buy the sugar and bread.” Mother (RBI-IDI-RM02) “Because of the weather (lack of rain), milk is in scarce quantities. There are very few houses where people drink milk.” Community leader (RBI-IDI-CL02) “We buy milk at the end of the month… We use it to make tea… Milk is consumed until it runs out.” Mother (IDI_002) “Even milk itself here, I don't know...It’s not much consumed much… [[J]ust to find can of milk here, it's a serious problem. When I mean the powdered milk, the one you take with tea… many families buy this included...in their monthly rations” Community leader (IDI_008) “[Yoghurt, cheeses] you have to have money to be able to buy… I can't lie, those products we never buy…I buy milk… when my husband has money, but nowadays it's rare because things are expensive” Mother-in-law (IDI_009) “I can say that… here in the community, we can enter every house [and] we will not find cheese.” Spouse (IDI_001) “People to struggle to get yoghurt… Women eat, [but] it depends on each woman. They are one of the things that the prices are a bit high, so that some may want but they don't have money.” Spouse (IDI_007) “Well, cow milk is becoming more and more difficult to obtain here… If you can afford it, you may be able to have it twice or three times in a week.” Sister-in-law (IDI_006) “We mostly have cow milk because that is what is common here…[We have it] at least four times in a month during the rainy season when there is enough grass available for grazing but during the dry season it reduces by half…”Spouse (IDI_002) “When you cook breakfast you put sour milk in it, and we eat it up to 4 times a week…During the rains is when the cows produce plenty of milk and we have a lot of sour milk up to the point that they go and sell some out. During the dry season, we depend more on the milk tins we buy from the shops.” Community leader (IDI_012) “The most common type available here is cow milk but others such as yoghurt, cheese and others are not available here… For cow milk, it is always available. People are always selling it around and if you have money, you can always buy it.” Mother-in-law (IDI_003) 283 “They will eat the food that will satisfy them rather than buying food that will not fill their stomach… They can not waste sh.60 to buy yoghurt” Mother (RBI-IDI-RM02) Meat, poultry and fish Animal organ meats “Goats’, cows’ and sheep’s intestines are what is commonly eaten…[once] in a month” Community leader (MRK-IDI-CL02) “Where will those be coming from? Because with those unless you get from the market and you must have money to buy those. Truly speaking such things are not common” Community leader (MRK-IDI-CL01) “For the liver, it is very difficult to buy” Mother (RBI-IDI-RM02) “In beef, we buy what is called mutxaze (pancreas)…The chicken, we buy…the gizzards” Community leader (IDI_010) “It's rare.” Mother (IDI_003) “You eat it once in a while, not often… [T]here is no weekly or monthly” Mother-in-law (IDI_009) “As for liver, we only eat it when we buy it (laughter)!” Mother (IDI_001) Meat or poultry “I eat chicken but it very rare, I can eat it after two to three months” Spouse (RBI-IDI-SP01) “Mostly for lunch, they (pregnant women) eat ugali and some vegetables, unless they have wanted to buy meat… Even if it's not that much, they would mix it with some green vegetables and eat” Spouse (MRK-IDI-SP02) “Meat is eaten…mostly… during an occasion. If there is a wedding or burial, then people can contribute “Chicken, when we get money we buy them, but it is rare…. Chicken is rare for us to eat here at home.” Mother-in-law (IDI_004) “In the community, people consume and like chicken, and there is no one who does not like it… It depends on the person due to lack of conditions” Community leader (IDI_011) “Meat, if we could buy it, we would eat it every day… (laughs) I would like to eat the chicken every day” Mother-in-law (IDI_009) “For chicken, especially the legs, we do eat often.” Mother (IDI_011) “We do it meat, such as chicken or cow… Sometimes twice, sometimes once, but also it maybe multiple times in a week.” Brother-in-law (IDI_005) “We always have chicken. My husband’s brother has a lot of chicks. Whenever we don't have fish, he would give us one of his chicks… Whenever we have scarcity of fish… we always rely on chicken.” Mother (IDI_004) 284 and buy a cow to slaughter and you will eat meat on that day. But for now, it is not easy for someone to decide to go buy meat especially now that meat is expensive.” Mother (RBI-IDI-RM02) “People perceive meat to be expensive and so eating or buying meat from a butchery or anywhere in the market is not easy…Even once in a week is not possible. There is no meat… Mostly it’s during Christmas celebrations, New Year, that’s when you will see people eating chicken but it’s not a common thing to see a person slaughtering a chicken for family to just eat… Meat, if it were affordable, they (people) would… eat every day” Community leader (MRK-IDI-CL01) “Beef…goat and chicken meat…we can have it almost every day…we can have beef today and goat or chicken meat tomorrow” Mother (RBI-IDI-RM01) ““The foods that people would eat every day if they could would be rice and meat, but what gives the most energy is not meat but beans.” Community leader (IDI_011) “At the end of the month, I usually buy chicken meat, chicken pieces among other things” Mother (IDI_003) “Nowadays it is easy because chicken is sold in pieces, (laughs), the legs are components of the chicken... The wings are also components of the chicken, so you will have eaten meat” Mother-in-law (IDI_009) “Beef is not very common” Mother-in-law (IDI_014) “In the community, I see that… pork and cow are things that are consumed a lot when the end of the year comes or on holidays when the 25th comes” Spouse (IDI_001) “Chicken is eaten here….A week may pass without eating meat, but for chicken, especially the legs we do eat often.” Mother (IDI_011) “The day fish is not brought for sale, we go and buy chicken from the shop…That is almost all the time (year-round)…. The children now when we cook groundnut paste sauce, but if there is no fish, they will buy chicken” Community leader (IDI_015) “You know at our junction here, they… slaughter a bull to sell the meat and whenever you have money you can go and buy from there, but because of poverty, you cannot do all the things....” Community leader (IDI_014) “Foods like meat and fish are things that people like so much and would like to eat it every day” Spouse from The Gambia (IDI_002) Fish or other seafood “Let’s say currently we are lucky because of the rains we have some vegetables but for the other days it’s ugali and omena (small dried fish). We have them all, like kata shingo (fried sardines), kimala wari, omena, we even have shark… Those are just like staple food.” “What we often eat as meat is horse mackerel and tilapia fish… It is sold at a reasonable price; a plate costs 50 meticais…They are consumed throughout the year… Fish is our everyday meat” Community leader (IDI_010) “We are close to a branch of the River Gambia, and we catch small tilapia fish from there…Fish is eaten every day. If it is not caught from the river, people bring it for sale and we buy. I can say it is eaten 4 times in a week” Community leader (IDI_012) 285 Community leader (MRK-IDI-CL01) “For the dried fish, since it is stew that is cheap we can eat even thrice a week… During the dry season, the fish and dried fish are eaten a lot because the greens are not easily available unless you buy from the market… [P]regnant women eat the dried fish if they do not have money to buy vegetables” Mother-in-law (MRK-IDI-ML02) “If there are no green (leafy vegetables), the dried fish can replace them… A pregnant woman will have to eat dried fish is there is no other food… They do not have any means (money).” Community leader (RBI-IDI-CL01) “The fish available are the dried fish. Due to poverty and not having money people eat the small fish… There are salt water fish, there are many different fish… They are eaten regularly but in small quantities, because they are more expensive than meat… [I]t depends if someone can afford it because now fish goes for sh.300 a kilo.” Spouse (RBI-IDI-SP01) “The fresh fish are rarely eaten.” Community leader (MRK-IDI-CL02) “ Haaa here in the community freshwater fish is consumed…Because... in the lack of curry (stew), people run to that kind of fish” Spouse (IDI_001) “What is often freshwater fish… Hahh, those fish so small… On the days when there is money, we get about 50 meticais we buy… Even the next day having the 50, we buy again…That's how it works because (laughs), we run more to buy those foods because we don't have money.” Mother-in-law (IDI_009) “What is frequent is horse mackerel, and what is not frequent and what people don't like is black fish (freshwater fish), but most fish are consumed.” Community leader (IDI_011) “They (pregnant women) like to eat that white fish…often 2-3 times a week… It is possible to eat all year round.” Spouse (IDI_013) “When it is winter, it is more expensive... but when it rains, it [the river] is very full… We eat xidliwane (tilapia) and there is no [part of the] year that we don't eat, even though it is expensive… but we buy them to eat” Pregnant woman (IDI_006) “We eat abundant fish, particularly when there's enough rainfall…We eat fish throughout the week. It is always available…Fish is always available.” Mother-in-law (IDI_006) “When the work on the farms is less, they (men) would go for fishing everyday and if they get [fish], they bring home. Sometimes you eat it every day but sometimes, you do not eat it every day because you do not get. It is their work and whenever they have the chance, they go for fishing…. It can be throughout the year [but] especially during the rainy season when water is still there, and you can eat it (fish) every day” Mother (IDI_007) “For us here we never see fish without buying, yes, I ate it the day before yesterday and yesterday. For today, I have not yet bought because I have not been out yet. We eat fish any time, yes… [D]uring the rainy season fish is plenty… when there is a lot of water in the river.” Community leader (IDI_014) Regarding shrimps and oysters, “Apart from fish, no… For fish, I can estimate that we eat every day, yes” Mother-in-law (IDI_009) “We do not hate them but with shrimps even if they are caught in Illiassa, they are never sold here, they are taken to Farafenni to be sold there. For yohos (oysters), you only see it when you go to 286 “When it rains, there are green leafy vegetables and when there is no rain, then we eat sardines… When there is drought, we would eat sardines unless you get money to buy beans but when you do not have enough money to buy beans then you would buy sardines and fry.” Mother-in-law (RBI-IDI-ML01) the Kombo’s because we do not have the here. But for fish from the river, even tilapia we go to the Mandinka community to buy them. Yes, that is where we go to get fish that we eat” Community leader (IDI_015) Eggs Eggs “It depends with the family that can afford it, but for me, I can go six months without eating an egg” Community leader (RBI-IDI-CL01) “It depends if you can afford as the eggs are sold at the shops but if you do not have the money, will you eat eggs? …[I]n my house we can eat then once in a month” Mother-in-law (MRK-IDI_ML02) “[We] do not keep chicken for eggs…they want the chicken to hatch the eggs and get chicks hence…the eggs are not eaten often” Mother (RBI-IDI_RM02) “It can not be eaten regularly. It is eaten once or twice in a month. When she has no other means and there is a chicken laying eggs then she would go and get some to make egg soup for the children to eat with some ugali.” Community leader (MRK-IDI-CL02) “During my pregnancy, my husband use to buy a full crate of eggs for me, and I use to eat at least one every day… Everyday I take one… Pregnant women should eat it always if they have… but some do have, some don’t have… [S]ome have so many other responsibilities so they may not be able to provide eggs for their families all the time.” Mother (IDI_001) “Whenever you have money, you can be able to buy boiled egg and eat it with bread…It depends on you. Entirely. If you have money, you can buy it and use it as breakfast.” Mother-in-law (IDI_006) “Sometimes we do have our local chickens which lay eggs but usually we do not dare to touch the eggs… so we allow it to hatch them itself.” Community leader (IDI_014) “Ah eggs don't have frequency, eggs if someone eats is because that person is not well or if the person has money. They buy them to prepare and drink with tea… Eggs are not something that the person can eat all the time. ” Mother-in-law (IDI_004) “I can end the month, end the year without eating an egg… [D]uring the year, one day make a surprise if I have hit some money, but I can finish the month without really eating any eggs” Pregnant woman (IDI_006) “The eggs that hens lay are not always eaten, but only from time to time” Mother-in-law (IDI_009) 287 Dark green leafy vegetables Dark green leafy vegetables “When there was rain, we could eat mchicha (amaranth leaves) or… we can come to the market and buy mchicha. With mchicha and cowpeas leaves, sometimes we eat them thrice a week…” Sister-in-law (RBI-IDI-SL01) “For the vegetables, there is mchunga (wild leafy green), mchicha (amaranth leaves)….and the cowpea leaves…when it rains…. During the drought season, someone might buy twenty shillings worth of cabbage or kale” Mother-in-law (MRK-IDI-ML01) “Those vegetables are eaten when it has rained and they have been planted…We can say that with mchicha; unless it has rained, that's when it grows. For cowpeas leaves, unless you have grown it. Mchunga, with that one, it is ill mannered and just grows anywhere.” Community leader (MRK-IDI-CL02) “I get the matapa (cassava leaves) in the farm, pick and put it in the pestle and add the garlic, then crush, wash the pot and put it to boil, and it cooks. After that, I crush the groundnuts and grate the coconut when I have it. I add it and let it boil” Mother (IDI_012) “Most days, we eat xitsakatu (pumpkin leaves or other leafy greens cooked with a little peanut)…”Mother-in-law (IDI_004) “The sweet potato leaf, the pumpkin leaf…that food we collect from the fields” Mother (IDI_002) “Kale is also eaten; it’s just expensive… The person can no longer plant because it is already very hot (summer season), and when…we buy at 30mt, we only eat that day.” Pregnant woman (IDI_006) “We eat greens both wild and the ones we cultivate in our gardens. The wild leaves are mostly available during the rainy season but other greens we cultivate are also available during certain time of the dry season too…We normally eat greens once in a week” Spouse (IDI_002) “Moringa (wild leafy green)… is always sometimes every day…during this time of the year (start of rainy season)” Mother-in-law (IDI_006) “When gardens are started (dry season), you can have cassava leaves.” Mother (IDI_011) “Like baobab [leaves]… we do eat it.” Brother-in-law (IDI_008) Other vitamin-A rich foods Orange fleshed vegetables and roots “The sweet potatoes… I can cook them even three times a week mostly during Ramadhan… For the carrots and pumpkins, I do eat but it has been long since I ate pumpkins. I haven’t eaten them this whole year” Mother-in-law (MRK-IDI-ML02) “Twice a week, we can vary it, in the sense that today we cook sweet potato and tomorrow cassava and for example on Saturday, we cook sweet potato” Mother (IDI_012) “We also eat cassava and sweet potato, but these foods are no longer abundant…We plant the sweet potato and it grows when it rains… Sweet “We do eat pumpkins… [but] eating these is just a time because they are not all the time available. They are available by the end of the rainy season.” Community leader (IDI_012) “For sweet potatoes…their availability depends on the rainy season. Towards the end of the rainy season is when sweet 288 “Mostly people would plant these during rainy seasons. So around July you would find plenty of pumpkins in the shambas (fields)… It’s not many people who would plant them but for those who would have planted by around July and August or still September they are plenty” Community leader (MRK-IDI-CL01) [Carrots, sweet potatoes and pumpkins] are eaten but it is long since when it last rained [so] they are now scarce” Mother-in-law (MRK-IDI-ML01) potatoes have specific months because [otherwise], they are scarce” Mother-in-law (IDI_009) “Carrot is consumed…because you add it to the beans…[We eat it] once a week” Mother-in-law (IDI_014) “Carrots [are] for those who are used to it, those who have conditions (money)… so, not many consume…you can find a carrot at 25 meticais or 30 meticais per carrot, imagine, I only have 50 to spend” Spouse (IDI_007) potatoes… are ready…” Community leader (IDI_014) “Carrots are less here but sometimes if you go to Farafenni you can buy and bring… It doesn’t go beyond [eating] once a week” Spouse (IDI_002) Dark yellow or orange fruits “For mangos …there is a season where they are in plenty… We usually have mango trees at home so we do not buy” Mother (RBI-IDI-PG01) “The pawpaw (papaya) trees… they have died due to the dry season (drought)” Community leader (RBI-IDI-CL01) “When it is mango season, a lot of mango is consumed… it could be two or three times a week” Community leader (IDI_008) “Sometimes they eat papayas….They may be able to eat once a week….[but] that also depends because papaya is now rare (out of season)” Spouse (IDI_013) “Mangoes are there, pawpaw (papaya) also we eat them here… For mangoes, when they are ready, we eat them every day… It is available towards the end of the dry season.” Community leader (IDI_012) Other vegetables Other vegetables “Cabbage is eaten… I can eat them twice or thrice in a week” Mother-in-law (MRK-IDI-ML02) “If the family is able, then they can buy tomato, onions and oil to cook.” Mother (RBI-IDI-RM02) “Being the season when there is plenty of the cabbage, we can eat every day” Mother-in-law (IDI_009) “We rarely have cabbage in the summer, and even to buy, it is expensive.” Mother (IDI_002) “There is no restriction as to how much we should eat because is produced by ourselves. We cook it with oil sometimes and at times we cook it with different condiments like bitter tomatoes, cabbages and the like” Mother-in-law (IDI_003) “For cabbage, we always add it in our food almost every day, except sometimes 289 “okra and eggplant…[may be eaten] once a week” Spouse (MRK-IDI-SP01) “During… the rainy season, someone can make a kitchen garden and plant the okras or eggplants and cook the at home when they are ready” Community leader (RBI-IDI-CL01) “In the community or the country, there are no days that onions and garlic are not used.” Mother (IDI_006) “There are different dishes when feast days come…When you consume a lot of potatoes, beets” Community leader (IDI_008) when it is scarce, we would normally go to Farafenni (town) to get it from the market.” Mother (IDI_004) “Tomato, cabbages, garden eggs (eggplant) and so on… we do eat them because these are foods that are produced by our women in their gardens…But even whereas they are not available… they go to the market” Brother-in-law (IDI_005) “Things like…garden eggs (eggplant), cabbage, bitter tomato, greens and as well as…onions and sorrel… We produce them during the dry season” Mother (IDI_001) Other fruit Other fruit “Normally here, we take oranges and bananas. They are the common fruits…and they are cheap” Mother (MRK-IDI-RM01) “Oranges and bananas are sold so you buy if you have the money. You can get a fruit today and maybe after three or four days is when you get money to buy another fruit. You can eat fruits twice a month or eat them twice or thrice depending on if you can afford it” Mother-in-law (MRK-IDI-ML02) “We need money to buy bananas and watermelons…They are eaten…when one has an urge or when they have money they can buy to satisfy their urge” “The banana, the apple and orange…and the tangerines… although is expensive, she manages to buy” Mother (IDI_002) “Oranges have their season… They (pregnant women) can covet, but if you don't have the money, you just covet and don't go beyond that” Spouse (IDI_013) “We also eat the banana, but we can stay two, three and even four months, we can even stay a year when we don't have production at home…” Community leader (IDI_010) “Many people like avocado because it gives them an appetite… [L]emon is added to its preparation and this helps them to have an appetite too, [but] it is “Oranges…are less here but sometimes if you go to Farafenni (town) you can buy and bring…It doesn’t go beyond [eating] once a week” Spouse (IDI_002) “Oranges are available only during certain times of the year.” Mother-in-law (IDI_003) “Watermelon is not available throughout the year, but only during certain time of the year. It is seasonal. But once it is available, we eat it almost every day.” Mother (IDI_004) “Well, people buy them from banana sellers and eat them when they have money… Mandarins, and some other fruits like “Tomborongs” and “Kunkungs” that are obtained from trees in the bush. These are fruits they often 290 Community leader (MRK-IDI-CL02) “Mostly we have guavas and avocado. What is also common here are passionfruit but not the avocados…It’s just like when you are farming and you have them in your shamba (fields) that’s when people eat be eating regularly.” Community leader (MRK-IDI-CL01) rare to get” Community leader (IDI_011) obtained seasonally.” Community leader (IDI_013) “Dudeh (bush mango)…you can eat it about three to four times a week as you go to the bush and harvest it yourself… Just before the rains start is when bush mango is ready” Mother (IDI_011) Fried or salty foods Fried or savoury snacks “The snacks that are mostly eaten are crisps…, fried potatoes, samosa and such, which are used to trick children. Maybe if a pregnant woman or mother goes to the hospital and they have stayed for long, she can buy the snacks for her child” Community leader (RBI-IDI-CL02) “The home budget, if we plan to buy flour and kales then you cannot go against that and buy cassava crisps…It is if you have change after buying something, maybe like 20 shillings, you can buy the snacks and eat them” Mother (RBI-IDI-RM01) “They are eaten regularly especially the potato crisps. My children really like them. They would eat them everyday….Because it’s just five shillings so I would buy for them… [Pregnant women] really “We eat junk food…at the end of the month…It would be those foods that the person craves” Mother (IDI_002) “[a] person buys if he has desire and buys that thing, [such as]…fiosse (fried biscuits)” Mother-in-law (IDI_004) “For snacks, they are always available at the shop. People buy them from the shop and eat it... If anybody have money to buy, you can get them from the shops.” Mother-in-law (IDI_003) 291 likes them… She can even eat ten packets” Spouse (RBI-IDI-SP02) “Weekly, we have cassava crisps… [T]hey are deep fried and very dry so they not nutritious. So if you have them it’s just to pass time… it’s a mouth exercise (laughs)” Mother (MRK-IDI-RM02) “For those that can afford it, they buy mahamri (fried bread scones) and others chapatti (fried unleavened flatbread)” Mother (RBI-IDI-RM02) Street foods, fast food, take-away foods [Regarding fried potatoes] “Those ones are eaten daily….When you have twenty shillings, you can easily buy with that. For one to cook those in the house you must incur some cost with buying the cooking oil, potatoes, flour and so instead of cooking at all that it's better to just buy. And so you can pass by the road and buy to satisfy your urge” Community leader (MRK-IDI-CL02) “In the morning and the afternoon...I used to just love eating fried potatoes (during last pregnancy)” Mother (MRK-IDI-RM02) “She eats fried potatoes, sambusa (samosa)… anytime she feels like “Buying dosage (roast quarter chicken) on the way… You can get it done at home, but because she wants it in a big hurry and her heart lusted for it she goes running to buy it so she can eat” Spouse (IDI_013) “You may have a craving for roast beef...If she is walking by, she may feel like buying it” Mother (IDI_002) “They (pregnant women) eat often… There are times when they pass those places and smell those foods, and when she has money, she will buy” Mother-in-law (IDI_014) “These fried things are much more on the weekends… [O]n normal days, they (pregnant women) eat beans and vegetables, but when the weekend “Food that they sell on the streets, we do not buy because is not available here” Mother (IDI_007) “If you can afford it, when you go to Farafenni (town), you buy it and eat…” Sister-in-law (IDI_006) 292 eating them, she goes to eat when there is money” Spouse (MRK-IDI-SP01) comes here, life is different….you have to get this meat…They like to eat roast beef. There are many women who like.” Spouse from Mozambique (IDI_007) Sweet foods Sweets “Sweets are for children…Kids love the one shilling sweets” Mother-in-law (MRK-IDI-ML01) “The sweets available are the lollipops, ball gum, in short, all the sweets… Anytime you feel like eating sweets, you can go buy at the shop and eat them… If someone is having different thoughts, they can decide to have sweets to clear their mind” Mother (RBI-IDI-RM01) “As we are close to the company, there is sugarcane… Sweet things are eaten every day” Mother (IDI_006) “We consume a lot, we suck a lot of [sugar]cane here.” Community leader (IDI_008) [Regarding sweet things, such as lollipops, and other sugary things] “They are consumed, but require great care… Because it can cause diabetes, you have to eat very cautiously. Even when you drink tea, you can't fill too much sugar, you have to put measuring… And so can soft drinks, they can cause diseases… While there are people who like it, not having money, they have no way to do anything. I consume once in a while and not always.” Mother-in-law (IDI_009) “We eat sweets always because it’s always available… If you don’t eat it in the morning, you can eat them in the evenings…They (pregnant women) do [eat sweets]… because it gives them appetite” Mother (IDI_001) “[Sweets] is almost every day and almost every time, particularly children. They like it so much and eat is so frequently…They keep buying it from the shop and chewing it all the time” Mother (IDI_004) “People eat it (sweets) every day… It is all about affordability because once you have money you can buy it from the shop… I used to see them (pregnant women) eating it.” Mother-in-law (IDI_006) Pastries and cakes “Cakes would probably be eaten during end of month or when invited for a birthday celebration or wedding” Community leader (MRK-IDI-CL02) “There are many foods with sugar like sweets, cakes…mostly it is during occasions like weddings, birthdays and other such “When the year ends, they cook different foods…. that's when they make cakes” Spouse (IDI_013) N/A 293 celebrations that the sweets are eaten” Spouse (RBI-IDI-SP01) “Biscuits are eaten… Adults would eat but they are perceived to be children’s food” Community leader (MRK-IDI-CL01) Sweetened beverages Fizzy drinks “People would drink in such times like Christmas or in New Year. That day you would find crates of sodas and people would drink but when that day is over, that’s the end.” Community leader (MRK-IDI-CL01) “At my house the time when club soda would be drank a lot was during Ramadhan after breaking the fast. Thats was when they could drink two times a week each but since Ramadan is over, I do not see the sodas being brought” Mother-in-law (MRK-IDI-ML02) “I drink soda and mostly I have Coca cola or Fanta… We can drink it anytime but mostly we have it during occasions.” Pregnant woman (RBI-IDI-PG01) “They do not have specific time, like when you are pregnant and want to drink something cold you will just go buy that club soda and drink. It’s not like daily, perhaps weekly” Sister-in-law (RBI-IDI-SL01) “Soft drinks are consumed…I consume when I feel like it but I can go for a month without feeling like consuming…” Mother (IDI_002) “The soft drinks that have sugar in them …when you have money you buy them… but it's not frequent, it's not every day.” Mother-in-law (IDI_004) “They (pregnant women) adhere more to Coke; there are few who love Fanta… If they have money, they can consume three times per week…The Fanta, it's almost orange isn't it so … it's part vitamin.” Spouse (IDI_007) “Soft drinks also are every day... If you have money, you can go and buy soft drink from the shop and drink it every day” Mother-in-law (IDI_006) “For attaya (sweetened green tea), they drink it here every time but for the soft drinks, is not all the time.” Community leader (IDI_012) 294 Other sugar added beverages “sugary drinks like tea…it’s just that” Pregnant woman (MRK-IDI-PG01) “Long time ago tea was not common …but nowadays it is something common” Community leader (RBI-IDI-CL01) “I use sugar in my tea or make juice and add sugar to it to make it sweet.” Mother (MRK-IDI-RM01) [Regarding consumption of sweet drinks], “Very often. For Afya drink (commercial sweetened fruit juice), it strengthens because it is a fruit drink… They (pregnant women) drink Afya because it increases blood circulation as it is made of fruits.” Mother (RBI-IDI-RM03) “If a pregnant woman craves for something they will buy that and eat. There was a pregnant woman who would buy the iced juice everyday… She would eat the iced juice everyday after her meals. So whatever the pregnancy craves for that is what the woman will eat” Mother (RBI-IDI-RM02) “You can take it today and take it tomorrow as I am addicted to tea…. Tea, when we put it on the table for everyone to drink, there's one who puts 2 spoons [of sugar], there's one who puts 4 spoons and…even putting 5 little spoons in the cup to take tea…. there are those who like sweet things” Mother-in-law (IDI_004) “They are consumed, it is summer and we have been taking G-Vita juices (powder juice)…I in particular don't like tea, I take G-Vita (powdered juice)…Not a day goes by that I don't take G-Vita” Community leader (IDI_010) “We are… used to making juice and drink after lunch…. Some children would come to sell some already prepared juice or wonjo (sweetened juice made from sorrel) and we buy from them to drink” Mother (IDI_007) “Particularly (sweetened) green tea, which is taken multiple times in a day… People don’t drink juice always but for green tea, we drink it morning, afternoon, and evening” Mother (IDI_001) “We never do without attaya (sweetened green tea) and even our bodies are addicted to attaya (laughs)” Mother (IDI_007) “For attaya (sweetened green tea), some do it in the afternoon and evening. Some do it in the morning, afternoon, and evening…some pregnant women drink it a lot.” Community leader (IDI_012) “If it comes to juice, sometimes we can drink it three times in a day… Attaya (sweetened green tea)…that one is always… For juice, I know it gives the body water” Mother-in-law (IDI_009) 295 Chapter 7 appendix for the association between maternal dietary diversity and pregnancy hypertension study H.1 Model selection Models were initially unadjusted (model 1), then adjusted for country (model 2), then adjusted for country, rural/periurban residence, age, parity, marital status (model 3), then adjusted for country, rural/periurban residence, age, parity, marital status, education and occupation (model 4), then finally adjusted for country, rural/periurban residence, age, parity, marital status, BMI, HIV, and pre-gestational diabetes (model 5). Education and occupation were not included in the final model due to higher AIC (model 3: 5546.1 vs model 4: 5556.6). AIC Standard MDD-W (gestational hypertension) Modified MDD-W (gestational hypertension) Modified MDD-W (any HDP) Model 1 5652.2 5651.9 5955.2 Model 2 5563.8 5558.9 5868.2 Model 3 5546.1 5540.5 5835.1 Model 4 5556.6 5550.3 5843.1 Model 5 5414.8 5410.1 5650 A review and meta-analysis of studies from sub-Saharan Africa found a non-significant association between pre-eclampsia and maternal education (467). Systematic review and meta-analyses found rotating shifts (468), prolonged bending and heavy lifting of 11 kg or more (469) were associated with increased odds of gestational hypertension/pre-eclampsia. Highly specific occupational hazards highlight the complex association between occupation and risk of developing pregnancy hypertension, and may not have been relevant to our study population in sub-Saharan Africa.
Thesis/Dissertation
eng
Women+ and Children’s Health Sciences
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Elango, Rajavel
Moore, Sophie E.
Maternal diets and dietary diversity in relation to pregnancy hypertension in sub-Saharan Africa
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