Medicine, Faculty of
Obstetrics and Gynaecology, Department of
DSpace
UBCV
Victory, Jenna
Master of Science - MSc
University of British Columbia
Infertility, the inability to conceive after twelve or more months of regular unprotected sexual intercourse, affects approximately 1 in 6 people globally. Fertility rates are declining worldwide, and use of assisted reproductive technologies like in-vitro fertilization (IVF) to conceive is increasing. Racial/ethnic disparities in SMM among women who conceived via IVF are understudied. In addition, the association between IVF conception and HELLP (haemolysis, elevated liver enzymes, low platelets) syndrome during pregnancy has not been quantified on the population level, distinctively in singleton and twin pregnancy. I conducted a population-based retrospective cohort study of all singleton births between 20-44 weeks in the United States between 2016-2021 using live birth and fetal death certificate data. The objective of this study was to quantify the association between IVF and SMM and to ascertain if the association was modified by race/ethnicity. Women who conceived by IVF had a two-fold higher rate of the SMM composite outcome. This higher risk was observed across all racial/ethnic groups. Racial/ethnic disparities were present in women who conceived spontaneously. Women who conceived by IVF generally had similar racial/ethnic disparities. However, these disparities in uterine rupture/intrapartum hysterectomy were larger for Hispanic women who conceived by IVF than spontaneously, and for NHB women who conceived by IVF than spontaneously. Asian women who used IVF also had greater odds of admission to the ICU than those who conceived spontaneously. I conducted a second population-based retrospective cohort study of all singleton and twin live births and stillbirths between 20-44 weeks in British Columbia, Canada, between 2008/09-2021/22. This study attempted to address whether spontaneous versus IVF conception was associated with HELLP syndrome among singleton/twin pregnancies. Women who conceived twins spontaneously had higher risk of HELLP syndrome than women who conceived twins using IVF. Twin pregnancies regardless of mode of conception had higher risks of HELLP syndrome compared with women with spontaneously conceived singleton pregnancy. In summary, IVF conception modifies the associations between risk factors such as race/ethnicity and plurality, and some components of severe maternal morbidity.
EXAMINING THE ASSOCIATION BETWEEN IN-VITRO FERTILIZATION AND SEVERE MATERNAL MORBIDITY IN THE UNITED STATES AND CANADA by Jenna Victory B.Sc., The University of Edinburgh, 2022 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in The Faculty of Graduate and Postdoctoral Studies (Women+ and Children’s Health Sciences) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) July 2024 © Jenna Victory, 2024 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Examining the association between in-vitro fertilization and severe maternal morbidity in the United States and Canada submitted by Jenna Victory in partial fulfilment of the requirements for the degree of Master of Science in Women+ and Children’s Health Sciences Examining Committee: Sarka Lisonkova, Associate Professor, Department of Obstetrics and Gynaecology, UBC Supervisor KS Joseph, Professor, Department of Obstetrics and Gynaecology, UBC Supervisory Committee Member Paul Yong, Associate Professor, Department of Obstetrics and Gynaecology, UBC Additional Examiner Additional Supervisory Committee Members: Hamideh Bayrampour, Assistant Professor, Department of Family Practice, UBC Supervisory Committee Member iii ABSTRACT Infertility, the inability to conceive after twelve or more months of regular unprotected sexual intercourse, affects approximately 1 in 6 people globally. Fertility rates are declining worldwide, and use of assisted reproductive technologies like in-vitro fertilization (IVF) to conceive is increasing. Racial/ethnic disparities in SMM among women who conceived via IVF are understudied. In addition, the association between IVF conception and HELLP (haemolysis, elevated liver enzymes, low platelets) syndrome during pregnancy has not been quantified on the population level, distinctively in singleton and twin pregnancy. I conducted a population-based retrospective cohort study of all singleton births between 20-44 weeks in the United States between 2016-2021 using live birth and fetal death certificate data. The objective of this study was to quantify the association between IVF and SMM and to ascertain if the association was modified by race/ethnicity. Women who conceived by IVF had a two-fold higher rate of the SMM composite outcome. This higher risk was observed across all racial/ethnic groups. Racial/ethnic disparities were present in women who conceived spontaneously. Women who conceived by IVF generally had similar racial/ethnic disparities. However, these disparities in uterine rupture/intrapartum hysterectomy were larger for Hispanic women who conceived by IVF than spontaneously, and for NHB women who conceived by IVF than spontaneously. Asian women who used IVF also had greater odds of admission to the ICU than those who conceived spontaneously. I conducted a second population-based retrospective cohort study of all singleton and twin live births and stillbirths between 20-44 weeks in British Columbia, Canada, between 2008/09-2021/22. This study attempted to address whether spontaneous versus IVF conception was associated with HELLP syndrome among singleton/twin pregnancies. Women who conceived twins spontaneously had higher risk of HELLP syndrome than women who conceived twins using IVF. Twin iv pregnancies regardless of mode of conception had higher risks of HELLP syndrome compared with women with spontaneously conceived singleton pregnancy. In summary, IVF conception modifies the associations between risk factors such as race/ethnicity and plurality, and some components of severe maternal morbidity. v LAY SUMMARY In-vitro fertilisation (IVF) is fertility process that is associated with pregnancy complications, including severe maternal morbidity (SMM). In my studies, SMM included eclampsia (seizures associated with high blood pressure), blood transfusion, admission to the intensive care unit, a tear in the uterus, removal of the uterus during childbirth due to complications, and/or HELLP syndrome. HELLP syndrome is characterized by breakdown of blood cells, liver dysfunction, and the inability to form blood clots. Race and/or ethnicity and twin pregnancy are both known to be associated with increased risk of developing or experiencing SMM conditions. I found that IVF use increases the risk of SMM outcomes, and that IVF is a stronger predictor of SMM than race/ethnicity. Conversely, I found that twin pregnancy is more strongly associated with HELLP syndrome risk than IVF. My results warrant more investigation to confirm my findings and reveal how IVF changes the biological processes of pregnancy. vi PREFACE All work presented henceforth is the original and independent work of the author, Jenna Victory. The work was conducted at the British Columbia Children’s and Women’s Hospital and Health Centre. The research project was developed by Dr. Sarka Lisonkova and Ms. Jenna Victory. Victory participated in the study design, performed data analysis, data interpretation, and drafted original manuscripts for each relevant chapter of this final thesis from this work. She has communicated findings at departmental, national, and international conferences, including the meeting of the Society for Perinatal and Paediatric Epidemiological Research in Portland, US, the Canadian National Perinatal Research Meeting in Montebello, Canada, and in Vancouver, Canada, and the European Perinatal Epidemiology Conference in Stockholm, Sweden. The data in Chapter 2, acquired from the National Center for Health Statistics, were de-identified and publicly available and the study based on these data did not require ethics approval. Ethics approval was granted from the University of British Columbia/Children's and Women's Hospital and Health Centre of British Columbia Research Ethics Board for the de-identified data utilized in Chapter 3, which were obtained from the British Columbia Perinatal Database Registry (H23-01730). A version of Chapter 2 was submitted for publication [Racial/Ethnic Disparity in Severe Maternal Morbidity Among Women Who Conceived by Assisted Reproduction. Victory J, John S, Wang LQ, Koegl J, Richter L, Bayrampour H, Joseph KS, Lisonkova S.]. Jenna Victory originally drafted the manuscript and the co-authors revised and assisted in the production of a final draft for publication. The results have been presented by Victory at the University of British Columbia Faculty of Medicine Academic Day 2023 in Vancouver, Canada, at the Canadian National Perinatal Research Meeting 2023 in Montebello, Canada, at the Society for Perinatal Epidemiology vii Research 2023 in Portland, US, and at the European Perinatal Epidemiology Conference 2023 in Stockholm, Sweden. A version of Chapter 3 was submitted for publication [The Association of In-Vitro Fertilization and Twin Pregnancy with HELLP Syndrome: A Population-Based Study. Victory J, Koegl S, Nicolls S, John S, Wang LQ, Bayrampour H, Joseph KS, Lisonkova S.]. Jenna Victory originally drafted the manuscript and co-authors revised and assisted in the production of a final draft for publication. The results will be presented at the Canadian National Perinatal Research Meeting 2024 in Vancouver, Canada. viii TABLE OF CONTENTS ABSTRACT ................................................................................................................................... iii LAY SUMMARY ........................................................................................................................... v PREFACE ...................................................................................................................................... vi TABLE OF CONTENTS ............................................................................................................. viii LIST OF TABLES ....................................................................................................................... xiv LIST OF FIGURES ..................................................................................................................... xvi LIST OF ABBREVIATIONS ..................................................................................................... xvii ACKNOWLEDGEMENTS ......................................................................................................... xix DEDICATION ............................................................................................................................. xxi CHAPTER 1: Introduction ............................................................................................................. 1 1.1 INFERTILITY ................................................................................................................. 1 1.1.1 Female Factor Infertility ........................................................................................... 1 1.1.1.1 Endometriosis ........................................................................................................ 2 1.1.1.2 Polycystic Ovary Syndrome .................................................................................. 3 1.1.1.3 Diminished Ovarian Reserve ................................................................................ 4 1.1.2 Male Factor Infertility ............................................................................................... 4 1.1.2.1 Hypogonadism ...................................................................................................... 5 1.1.2.2 Varicoceles ............................................................................................................ 5 ix 1.2 ASSISTED REPRODUCTIVE TECHNOLOGIES ........................................................ 6 1.2.1 In-Vitro Fertilization ................................................................................................. 6 1.2.1.1 Ovarian Stimulation and Oocyte Retrieval ........................................................... 6 1.2.1.2 Fertilization ........................................................................................................... 8 1.2.1.3 Embryo Transfer ................................................................................................... 8 1.2.2 Morbidities Associated with IVF .............................................................................. 9 1.2.2.1 Ovarian Hyperstimulation Syndrome .......................................................................... 9 1.2.2.2 Ectopic Pregnancy ................................................................................................. 9 1.2.2.3 Pregnancy Loss .......................................................................................................... 10 1.3 PREECLAMPSIA AND HELLP SYNDROME ........................................................... 11 1.3.1 HELLP Syndrome ................................................................................................... 12 1.3.1.1 Haemolysis .......................................................................................................... 13 1.3.1.2 Elevated Liver Enzymes ...................................................................................... 14 1.3.1.3 Low Platelet Count .............................................................................................. 14 1.4 MULTIFETAL PREGNANCY ..................................................................................... 15 1.4.1 Chorionicity ............................................................................................................ 16 1.4.2 Multifetal Pregnancy and IVF ................................................................................ 18 1.5 SEVERE MATERNAL MORBIDITY .......................................................................... 20 1.5.1 SMM and IVF ......................................................................................................... 21 1.5.2 Eclampsia ................................................................................................................ 22 x 1.5.3 Blood Transfusions ................................................................................................. 22 1.5.4 Uterine Rupture ....................................................................................................... 23 1.5.4.1 Intrapartum Hysterectomy ......................................................................................... 26 1.5.6 ICU Admission ....................................................................................................... 26 1.6 RACE AND ETHNICITY ............................................................................................. 27 1.6.1 Racial/Ethnic Disparities in Maternal Health Outcomes ........................................ 27 1.6.2 Racial/Ethnic Disparities in Maternal IVF Outcomes .................................................. 28 1.6.3 Racial/Ethnic Disparities in Risk Factors for Adverse Maternal Outcomes ........... 28 1.6.3.1 Pre-Pregnancy Body Mass Index ........................................................................ 28 1.6.3.2 Comorbidities in Pregnancy ................................................................................ 29 1.6.3.3 Socioeconomic Status ......................................................................................... 30 1.6.3.4 Rural Residence ................................................................................................... 31 1.6.3.5 Healthcare Insurance ........................................................................................... 32 1.7 THESIS OVERVIEW .................................................................................................... 33 1.7.1 Research Question .................................................................................................. 33 1.7.2 Rationale ................................................................................................................. 33 1.7.3 Specific Objectives and Hypotheses ....................................................................... 34 1.7.4 Aims ........................................................................................................................ 35 CHAPTER 2: Racial/Ethnic Disparity in Severe Maternal Morbidity Among Women Who Conceived by Assisted Reproduction ........................................................................................... 37 xi 2.1 OBJECTIVE ................................................................................................................... 37 2.2 METHODS .................................................................................................................... 37 2.2.1 Data Source and Study Population ......................................................................... 37 2.2.2 Severe Maternal Morbidity ..................................................................................... 38 2.2.3 Race/Ethnicity ......................................................................................................... 38 2.2.4 Statistical Analysis .................................................................................................. 39 2.2.5 Sensitivity Analysis ................................................................................................ 40 2.3 RESULTS ...................................................................................................................... 40 2.3.1 Study Population ..................................................................................................... 40 2.3.2 SMM by Race/Ethnicity and IVF ........................................................................... 43 2.3.3 Multivariable Analysis ............................................................................................ 45 2.3.4 Sensitivity Analyses ................................................................................................ 49 2.4 DISCUSSION ................................................................................................................ 49 2.4.1 Interpretation ........................................................................................................... 49 2.4.2 Strengths and Limitations ....................................................................................... 51 2.5 CONCLUSION .............................................................................................................. 52 CHAPTER 3: The Association of In-Vitro Fertilization and Twin Pregnancy with HELLP Syndrome: A Population-Based Study ......................................................................................... 54 3.1 OBJECTIVE ................................................................................................................... 54 3.2 METHODS .................................................................................................................... 54 xii 3.2.1 Study Population ..................................................................................................... 54 3.2.2 Twin pregnancy, IVF, HELLP Syndrome and Other Covariates ........................... 55 3.2.3 Statistical Analysis .................................................................................................. 55 3.2.4 Sensitivity Analysis ................................................................................................ 56 3.3 RESULTS ...................................................................................................................... 57 3.3.1 Study Population ..................................................................................................... 57 3.3.2 HELLP Syndrome by Plurality and IVF ................................................................. 59 3.3.3 Multivariable Analysis ............................................................................................ 59 3.3.4 Sensitivity Analysis ................................................................................................ 62 3.4 DISCUSSION ................................................................................................................ 62 3.4.1 Interpretation ........................................................................................................... 62 3.4.2 Strengths and Limitations ....................................................................................... 64 3.5 CONCLUSION .............................................................................................................. 65 CHAPTER 4: Discussion .............................................................................................................. 66 4.1 SUMMARY AND SIGNIFICANCE OF FINDINGS ................................................... 66 4.2 INTERPRETATION AND EXPLORATION OF CHAPTER 2: IVF, SMM, AND RACE/ETHNICITY .................................................................................................................. 67 4.2.1 IVF and Severe Maternal Morbidity ....................................................................... 67 4.2.2 Severe Maternal Morbidity and Race/Ethnicity ..................................................... 70 4.2.3 Race/Ethnicity and IVF ........................................................................................... 75 xiii 4.3 INTERPRETATION AND EXPLORATION OF CHAPTER 3: IVF, HELLP SYNDROME, AND TWIN GESTATION ............................................................................... 76 4.3.1 HELLP Syndrome and Twin Pregnancy ................................................................. 76 4.3.2 IVF and HELLP Syndrome .................................................................................... 76 4.4 STRENGTHS AND LIMITATIONS ............................................................................ 78 4.5 FUTURE DIRECTIONS ............................................................................................... 81 CHAPTER 5: Conclusion ............................................................................................................. 85 5.1 CONCLUSION .............................................................................................................. 85 REFERENCES ............................................................................................................................. 86 APPENDIX A: Supplemental Information for Chapter 2 .......................................................... 143 APPENDIX B: Supplemental Information for Chapter 3 ........................................................... 145 xiv LIST OF TABLES Table 2.1: Characteristics of women by race/ethnicity and mode of conception, singleton deliveries, United States, 2016-2021. ........................................................................................... 42 Table 2.2: Rates of severe maternal morbidity by race/ethnicity and mode of conception, singleton deliveries, United States, 2016-2021. ............................................................................ 44 Table 2.3: Adjusted odds ratios for severe maternal morbidity by race/ethnicity and mode of conception, singleton deliveries, United States, 2016-2021. ........................................................ 47 Table 2.4: Adjusted odds ratios showing modification of the association between race/ethnicity and severe maternal morbidity by mode of conception, singletons deliveries, United States, 2016-2021. .................................................................................................................................... 48 Table 3.1: Maternal and pregnancy characteristics of singleton and twin pregnancies conceived spontaneously and by IVF, British Columbia, Canada, 2008/09-2020/21. .................................. 58 Table 3.2: Rates of HELLP syndrome in singleton and twin pregnancies conceived spontaneously and by IVF, British Columbia, Canada, 2008/09-2020/21. .................................. 60 Table 3.3: Multivariable analysis of HELLP syndrome comparing singleton and twin pregnancies conceived spontaneously and by IVF, British Columbia, Canada, 2008/09-2020/21. ................. 61 Supplementary Table 2.1: Characteristics of women by IVF use, singleton deliveries, United States, 2016-2021. ....................................................................................................................... 143 Supplementary Table 2.2: Adjusted odds ratios showing modification of the association between race/ethnicity and severe maternal morbidity by mode of conception, singleton deliveries, United States, 2016-2021. ....................................................................................................................... 144 Supplementary Table 3.1: Maternal and pregnancy characteristics of women who conceived spontaneously and by IVF, British Columbia, Canada, 2008/09-2020/21. ................................ 145 xv Supplementary Table 3.2: Sensitivity analyses of HELLP syndrome comparing singleton and opposite-sex twin pregnancies conceived spontaneously and by IVF, British Columbia, Canada, 2008/09-2020/21. ........................................................................................................................ 146 xvi LIST OF FIGURES Figure 1.1 Chorionicity. ................................................................................................................ 17 Figure 1.2 Trends in the incidence of (a) singletons and (b) twins among all deliveries in the US by race 1971-2018. ........................................................................................................................ 19 Figure 1.3 Uterine Dehiscence versus Uterine Rupture. ............................................................... 25 xvii LIST OF ABBREVIATIONS AIAN American Indian/Alaskan Native AOR Adjusted odds ratio ART Assisted reproductive technologies BC British Columbia BCPDR British Columbian Perinatal Database Registry BMI Body-mass index CDC Centers for Disease Control and Prevention CI Confidence intervals CPSS Canadian Perinatal Surveillance System EP Ectopic pregnancy FSH Follicle stimulating hormone HELLP Haemolysis, elevated liver enzymes, low platelets HPG Hypothalamic-pituitary-gonadal ICD-10-CA International Classification of Diseases, version 10 codes (Canada) ICSI Intracytoplasmic sperm injection ICU Intensive care unit IUI Intrauterine insemination IVF In-vitro fertilization LH Luteinizing hormone NCHS National Center for Health Statistics NHB Non-Hispanic Black NHW Non-Hispanic White xviii OHSS Ovarian hyperstimulation syndrome PCOS Polycystic ovary syndrome PGT Pre-implantation genetic testing PI Pacific Islander RD Rate difference RR Rate ratio SES Socioeconomic status SMM Severe maternal morbidity US United States WHO World Health Organisation xix ACKNOWLEDGEMENTS I would principally like to thank my research supervisor Dr. Sarka Lisonkova who provided invaluable kindness, patience, and guidance to me throughout my graduate studies. Her dedication to my education and experience throughout this degree has allowed me to seize opportunities and accomplish goals beyond my imaginings. Thank you for your endless support and grace towards me, and for allowing me to participate in the Women+ and Children’s Health Sciences program. I hope I brought a fraction of the laughter and joy to you as you brought to me. I also wish to extend my gratitude to Dr. K.S. Joseph, Dr. Hamideh Bayrampour, and Dr. Paul Yong of my supervisory and examining committees; and to the chair, Dr. Patricia Janssen. I am extremely grateful for the time and effort you have invested in me as a graduate student. You have helped me navigate the fields of perinatal epidemiology and women’s health research, and I have learned skills I will continue to apply throughout my academic and professional careers as a result. To my co-authors Sid John, Sofia Nicolls, Johanna Koegl, Jeffrey Bone, and Li Qing Wang, thank you for your insight and advice, for your edits and suggestions. This work would not be possible without this team. I must acknowledge the Women+ and Children’s Health Sciences program administration for creating a nuanced and exciting new program that allowed me to explore my passion for women’s health. To my professors and peers, thank you for accompanying me along this journey, for broadening my perspective of healthcare research, for acting as genuine mentors and friends. Special thanks are owed to my incredible friends who have shown me genuine love and support throughout this process. I owe you so much of my joy and my happiness during my time in Vancouver. You have made this experience better than I ever could have hoped, and I love each xx of you more than I can describe. I am excited for all the future has in store for us. I cannot imagine living this life without you. Thank you. Words cannot express the gratitude and respect I feel towards my family. Matteen, you are an exemplary brother and have always spoken the loudest congratulations when I accomplish a goal. Nasim, you are one of my best friends, and I will always treasure these two years we spent in Vancouver together. To my mother Wendy, you are the light of my life and the list of reasons why I am proud to be your daughter grows every day. To my father Rahi, you are the reason I pursue my dreams, the driving force behind so much of my accomplishments, the one who has taught me the love of learning and healing. To my parents and my grandparents, I recognize all you have sacrificed to make our dreams come true, and I thank you from the bottom of my heart. I love you all. xxi DEDICATION Dedicated to all the mothers who made this work possible, and to all the mothers, women, and girls whom this research aims to help. 1 CHAPTER 1: Introduction 1.1 INFERTILITY Infertility is described as the inability to conceive after twelve or more months of regular unprotected sexual intercourse1. Recent estimates from the World Health Organisation (WHO) suggest infertility affects approximately 17% of the global population2. Impaired fecundity, the inability to carry a successful pregnancy and bear live children, is a frequent challenge to previously infertile couples who achieved pregnancy1. Global fertility rates are declining at a concerning pace, with some countries reaching historically low live birth rates3-5. Declining population growth is predicted to destabilize economies worldwide in coming decades5. Factors contributing to rising infertility rates include increased prevalence of sexually transmitted infections, exposures to pollutants, and substance use6-8. Ultimately, infertility poses a substantial threat to the sustenance of global population. 1.1.1 Female Factor Infertility When infertility presents in a couple, its origins are categorized as female factor, male factor, both, or unknown9. Unknown origins indicate that both individuals present with normal gonadal function, but infertility persists. Female factor infertility describes failure to achieve and maintain pregnancy, which can include dysfunction at the ovarian, tubal, or uterine levels10. Female factor infertility is attributed to many causes, though common morbidities include endometriosis, polycystic ovary syndrome, and diminished ovarian reserve10. 2 1.1.1.1 Endometriosis Endometriosis is a gynecologic pathology wherein endometrial-like tissue presents outside the uterine cavity in the intraabdominal space, latching onto the peritoneal lining or abdominal organs11. The exact mechanism by which this tissue migrates to the peritoneal space has not been determined. A commonly posited theory is the retrograde menstruation hypothesis, which proposes that menstrual tissue flows through the Fallopian tubes and into the abdomen rather than through the vagina12. Laparoscopic surgery to visualize endometriosis is considered the gold standard diagnosis as endometriotic adhesions can be missed when using ultrasound11. Surgery to remove adhesions is often coupled with hormonal contraceptives (thought to mitigate underlying endocrine dysfunction and prevent retrograde menstruation) as standard treatment11. Endometriosis sequelae complicate the fertility process and impair the ability to conceive and/or carry a pregnancy12. Superficial and deep dyspareunia, characteristic factors of endometriosis, make sexual intercourse difficult to initiate or sustain, reducing frequency of coitus and thus reducing opportunities to copulate12. There is growing evidence that endometriotic adhesions on the ovary (the most common site for adhesions) reduce ovarian reserve through structural tissue damage or toxic mechanisms via disrupting the endocrine environment12,13. Importantly, surgical trauma to ovarian tissue that may derive from removing the adhesions can potentially cause diminished ovarian reserve14-16. Gamete maturation, ovulation, fertilization and implantation are known to be impaired in women with endometriosis14,17-20. The dysregulation of these processes inhibits normal conception and contributes to the 50% of patients with endometriosis who experience infertility21. 3 1.1.1.2 Polycystic Ovary Syndrome Polycystic ovary syndrome (PCOS) describes a dysfunction of the hypothalamic-pituitary-gonadal (HPG) axis wherein excessive luteinizing hormone (LH) production stimulates irregular ovarian function22. Approximately 8-13% of women of reproductive age are affected globally23,24. The condition is multifactorial, with characteristic symptoms including hyperandrogenism (often presenting as hirsutism), polycystic ovaries, and ovulatory dysfunction25. Mental illness, insulin resistance, and obesity are common comorbidities in PCOS patients25-29. Current clinical mitigation strategies include hormonal contraceptives to exogenously regulate LH and subsequent androgen production, as well as “biguanides to improve insulin sensitivity […] clomiphene to induce ovulation and statins to lower blood cholesterol”30. The association between PCOS and infertility is well-documented25,31-34. PCOS favours LH production and consequently reduces follicle stimulating hormone (FSH) functionality, impairing normal oocyte maturation and ovulation25,31. Oligo-anovulation and amenorrhoea, both of which indicate abnormal reproductive function and reduced opportunity for fertilisation, are commonly observed in PCOS patients25,32. Recent studies also suggest that reduced DDAH1 function in PCOS patients facilitates oxidative stress which degrades oocyte quality33. Indeed, the prevalence of spontaneous abortion, often the result of genetically abnormal oocytes, in PCOS patients is greater than in their unaffected counterparts34. Additionally, insulin signalling is significantly altered in up to approximately 64% of women affected by PCOS35. Postulated pathophysiological mechanisms centre around reduced presence of the insulin receptor beta subunit and on altered post-receptor signalling mechanisms, though most studies concur that insulin resistance origins in PCOS patients are largely 4 heterogenous36-38. Nevertheless, obesity is a common sequela of PCOS-specific insulin resistance, presenting in 38-88% of patients39-41. Obesity independently impairs fertility – adipose tissue aromatises androgens into estrogens42 which directly dysregulates reproductive endocrine signalling. Obesity is also associated with increased difficulty in achieving pregnancy and maintaining pregnancy (i.e. miscarriage and stillbirth)43-45. 1.1.1.3 Diminished Ovarian Reserve Ovarian reserve, the quantity of oocytes capable of fertilisation and successful pregnancy an ovary can produce, diminishes over time46. The average age at menopause, when ovarian reserve is completely exhausted, is approximately 51 years47. However, decreasing ovarian reserve begins presenting around 35 years of age, after which likelihood of achieving and maintaining pregnancy is gradually reduced. One or more pregnancies prior to 35 years of age increases the likelihood of successful pregnancy thereafter48. Advanced age at first pregnancy has been an emerging trend across recent decades49. Indeed, birth rates in 15–29-year-old women in the United States (US) have notably declined since 201350. Thus, age-related diminished ovarian reserve is presenting an increasing challenge to contemporary global fertility. 1.1.2 Male Factor Infertility Male fertility is conventionally measured by assessing sperm quality, including sperm concentration, sperm motility, and sperm morphology51. Male factor infertility is primarily 5 characterised by testicular dysfunction resulting in an inability to fertilize an oocyte. Factors which commonly influence male fertility include hypogonadism and varicoceles52. 1.1.2.1 Hypogonadism Testosterone is produced in testicular Leydig cells and binds to androgen receptors on Sertoli cells to stimulate spermatogenesis51. Irregular testosterone synthesis/secretion alters spermatogenic processes, reducing sperm count and/or lowering sperm quality. Genetic causes of male hypogonadism include Klinefelter syndrome, renal failure, and aging53. Administration of exogenous testosterone can be used to increase serum testosterone levels and restore normal endocrine function. However, exaggerated or unnecessary use of anabolic steroids elevates testosterone levels such that FSH and LH secretion is suppressed54. Consequently, production of endogenous testosterone and subsequent spermatogenesis are impaired. Recovery of spermatogenic function averages approximately 3-6 months after use ends55, though some studies suggest that the likelihood of complete recovery is unpredictable and may not always occur55,56. 1.1.2.2 Varicoceles Testicular varicocele, the swelling of veins in the testicle, is a leading cause of male infertility57. It is estimated that approximately 21% of men referred for infertility are diagnosed with varicoceles58. Contemporary studies mostly concur that the pathogenesis that underlies the association between varicoceles and infertility is multifactorial. Blood flowing retrogradely in the testes causes swelling and induces oxidative stress in testicular tissues59. Varicoceles also inhibit Sertoli cell and Leydig cell function that impairs spermatogenic processes60. Hypoxia, scrotal 6 hyperthermia, and formation of sperm antibodies are also documented comorbidities of varicoceles57. Lifestyle changes and surgery are possible interventions to reduce swelling or remove varicoceles and restore fertility57. 1.2 ASSISTED REPRODUCTIVE TECHNOLOGIES Assisted reproductive technologies (ART) is a composite term comprising processes that improve the likelihood of or directly establish oocyte fertilisation61. There are variations about which processes are considered ART; for example, the Centers for Disease Control and Prevention (CDC) in the US considers ART to be “all fertility treatments in which either eggs or embryos are handled”61, which excludes the use of processes such as intrauterine insemination (IUI) and fertility drug use to boost natural conception (medically assisted reproduction), though it includes in-vitro fertilization (IVF). This definition is contested, as other groups including the American Society for Reproductive Medicine and many European countries consider IUI as an ART62,63. As rates of infertility increase in the global population, the use of ART is also rapidly increasing64,65. Approximately 2.3% of all infants born in the US each year are conceived by means of ART, a rate which has more than doubled in the past decade66. 1.2.1 In-Vitro Fertilization 1.2.1.1 Ovarian Stimulation and Oocyte Retrieval IVF is a multistep process that begins with exogenously regulating the menstrual cycle of the female patient via an oral contraceptive pill to ensure the cycle follows an optimal timecourse67. 7 The patient will subsequently cease contraceptive use and experience menses, after which the ovarian stimulation step begins62. In a normal menstrual cycle, one dominant follicle will progress to ovulation68; the purpose of ovarian stimulation is to increase the quantity of oocytes available to harvest. The stage at which the oocytes are harvested is colloquially considered “mature”, though this is only the first maturation process prior to full maturation at the time of fertilisation. Fertility-boosting drugs including follitropin-alfas (FSH only) and menotropins (FSH and LH) are administered subcutaneously to encourage multi-oocyte maturation69. Ganirelix acetate or similar compounds are also administered subcutaneously to prevent ovulation70. Frequent ultrasonographic monitoring to follow follicular development and size occur during this phase. Measurements for what constitute a mature follicle vary in contemporary literature, though there is a general consensus that follicles between 16-22 mm are most likely to contain mature oocytes71. Once a majority of follicles have reached the desired size, the patient will self-administer a final subcutaneous injection of an anti-ovulation medication67. Conventional procedure dictates the oocyte harvest procedure should occur 36 hours after the final trigger injection67. The patient is partially or fully sedated during the oocyte harvest process. The physician uses an external or internal ultrasound probe to visualise the abdominal cavity67. Oocytes are vacuumed through a hollow needle that punctures through the vagina and ovary into individual follicles67. Follicles are drained into dishes and assessed for any significant morphological defects. Morphologically normal oocytes will be frozen for later use or fertilized within 5-6 days67. 8 1.2.1.2 Fertilization Fertilization requires a semen sample provided by a male partner or donor. Traditional IVF involves placing a single oocyte and small volume of semen in a dish together72. This process mimics the natural fertilization process wherein multiple sperm cells compete to fertilize the oocyte. Intracytoplasmic sperm injection (ICSI), the process by which a single optimal sperm cell is isolated and then injected directly into an oocyte to fertilize, was introduced into clinical practice in 199272,73. Today, over 75% of IVF cycles in the US use ICSI74. 1.2.1.3 Embryo Transfer The optimal stage for embryonic transfer is five to six days postfertilization75. At this stage, the blastocyst is either transferred into the recipient uterus for implantation or frozen for later use. Pregnancy rates post-implantation vary according to clinical procedure and patient demographics. A study conducted by Wei et al. (2019) showed a 50% live birth rate following single frozen embryo transfers versus a 40% live birth rate following single fresh embryo transfers76. Other contemporary studies report 15-30% increase in clinical pregnancy rates when using frozen embryos77,78. However, a growing pool of literature report no significant difference in live birth rates when using frozen or fresh embryos79-81. More population-level studies are necessary to comprehensively analyse pregnancy and live birth rates in frozen versus fresh embryo transfers. 9 1.2.2 Morbidities Associated with IVF 1.2.2.1 Ovarian Hyperstimulation Syndrome Ovarian hyperstimulation syndrome (OHSS) is an iatrogenic outcome of excessive fertility stimulation drugs administered in the oocyte harvesting process. Ovarian stimulation increases capillary permeability such that there is a net flow of fluid into the extracellular space 82. OHSS is clinically categorised as mild, moderate, and severe. Contemporary literature suggests mild OHSS occurs in up to 30% of all IVF cycles, while moderate and severe cases present in 2-3% of patients83. Complications include abdominal bloating, abdominal pain, oliguria, nausea and vomiting. Moderate and severe cases present with elevated haematocrit, hyponatremia, hypoproteinaemia, elevated white cell count, clinical ascites, and in critical cases, thromboembolism82. Physicians can carefully cultivate a drug regimen and administer aspirin and/or metformin to prevent OHSS82. Mild OHSS can resolve itself, though moderate and severe cases require interventions such as paracentesis, moderated intake of fluids, or heparin82. 1.2.2.2 Ectopic Pregnancy Ectopic pregnancy (EP) occurs when a fertilized egg implants outside the uterus, most commonly in the fallopian tubes. The abnormal implantation induces a highly inflammatory response that can cause severe damage. EP is an important cause of maternal mortality worldwide84. Other complications include haemorrhagic shock, salpingectomy, and increased risk of recurrent EP84. Ultrasound monitoring and serum human chorionic gonadotropin measurements are used as diagnostic tools84. Once diagnosed, the patient must undergo a medical or surgical termination procedure to avoid severe complications associated with EP84. 10 Furthermore, underlying tubal disease and dysfunction are strongly associated with increased risk of EP. Pelvic inflammatory disease, endometriosis, and previous tubal EP can create a nidus of excessive inflammation manifesting as both biochemical and structural risk factors for tubal tissue destruction and EP85-87. Tubal dysfunction collectively comprises approximately 30-40% of female factor infertility for which individuals seek IVF treatment88. Recent studies suggest the risk of EP is up to four times greater when conceiving by IVF than when conceiving naturally89,90. Uterine contractility and altered endometrial receptivity exogenously induced by IVF drugs are also believed to contribute to retrograde migration of the embryo into the Fallopian tubes84. 1.2.2.3 Pregnancy Loss Pregnancy loss is a composite term which includes miscarriage (defined as loss of fetal life and expulsion of dead fetus before 20 weeks of gestation), and stillbirth (typically defined as delivery of dead fetus at or after 20 weeks of gestation)91. Miscarriage occurs in approximately 10-16% of naturally conceived pregnancies with increased rates observed in pregnancies conceived using IVF92-95. Recent evidence suggests that frozen embryo IVF cycles may have increased risk of early spontaneous abortion (prior to 12 weeks) relative to fresh embryo cycles, though the reverse effect is seen in late miscarriages (after 12 weeks)96. Nonviable genetic anomalies are the predominant pathology underlying approximately 50% of all pregnancy loss97. Importantly, genetic anomalies are common in embryos conceived by IVF98. Advanced maternal age is a leading risk factor for both miscarriage and stillbirth, and an increasingly common reason for women to seek fertility assistance95,99. Stillbirth risk is also elevated in pregnancies conceived by IVF (odds ratio 1.82, 11 95% CI 1.37-2.42) according to a systematic review of 19 studies by Gundersen Sarmon et al (2021)100. 1.3 PREECLAMPSIA AND HELLP SYNDROME The female body undergoes significant haematopoietic and cardiovascular changes during pregnancy. Blood volume increases by 45%, with plasma volume increasing by up to 60% by the final weeks of gestation; blood pressure initially decreases but then increases in late pregnancy to pre-pregnancy levels; cardiac volume increases by 40% throughout pregnancy; systemic vascular resistance decreases by up to 30%101. Hypertension can arise as a result of the stress the body endures trying to adapt to these changes. Preeclampsia is a hypertensive disorder of pregnancy that occurs in 2%-8% of pregnancies and its complications are a leading cause of perinatal morbidity and mortality worldwide102. Diagnostic criteria include high blood pressure (140 mmHg systolic or 90 mmHg diastolic) with at least one additional systemic symptom (e.g., proteinuria, pulmonary edema, cerebral symptoms, etc.)103. Preeclampsia typically occurs after 20 weeks gestation and commonly presents closer to full term (37 weeks)104. Its pathophysiology derives from “impaired trophoblast invasion and spiral artery remodelling” at the maternofetal interface that causes placental dysfunction102. Dysfunctions in the renal, hepatic, neurological, and haematological systems are associated complications102. Proteinuria, a renal complication in preeclampsia, is associated with greater risk of caesarean delivery and adverse pregnancy events (e.g., stillbirth, preterm delivery, and fetal distress)105. Interventions include antihypertensive medication and early delivery to prevent exacerbation to eclampsia106. Eclampsia is a severe hypertensive state that causes seizures which can result in stroke or death107. 12 1.3.1 HELLP Syndrome HELLP syndrome is a complication of pregnancy characterized by haemolysis, elevated liver enzymes, and low platelet count. While it is generally considered to be a severe and progressive subtype of preeclampsia, it can manifest independently108. Indeed, recent evidence suggests preeclampsia and HELLP syndrome have different aetiologies and should be considered as separate conditions108,109. The pathophysiologies of HELLP syndrome and preeclampsia both include abnormal placentation that results in damage to endothelial tissue. Immune processes are irregularly activated in HELLP syndrome, which incite excessive inflammation and damage to endothelial tissue108. Hypertension and proteinuria are common but not ubiquitous in HELLP syndrome cases109. Nevertheless, the two pathologies often occur concomitantly and can both exacerbate to eclampsia106,109. HELLP syndrome occurs in 0.2-0.8% of all pregnancies109. Typically, it manifests in the final trimester of pregnancy, and delivery of fetus and placenta is the standard treatment109. However, symptoms (which include abdominal pain, blurred vision, fatigue, nausea, and vomiting) can persist or even initially manifest in the postpartum period110,111. Postpartum development of HELLP syndrome accounts for approximately 30% of all cases, and usually onsets within the first 48 hours after delivery112. Diagnostic criteria (according to the Tennessee classification) include “microangiopathic haemolytic anemia with abnormal blood smear, low serum haptoglobin and elevated lactate dehydrogenase levels, (2) elevation of aspartate aminotransferase above 70 IU/L and lactate dehydrogenase above 600 IU/L (both enzyme levels more than twice the upper limit of normal values) or bilirubin more than 1.2 mg/dL, and (3) a platelet count below 100 × 109 per 13 litre”110,113. Risk factors include genetic factors, age greater than 35 years, primiparity, pre-existing hypertension, obesity, and diabetes111,114-116. While the ultimate treatment for HELLP syndrome is immediate delivery, other mitigation strategies include antihypertensive medication and blood transfusions111. 1.3.1.1 Haemolysis Haemolysis is the process by which erythrocytes are destroyed prematurely relative to their natural lifespan. HELLP syndrome is specifically characterised by microangiopathic haemolytic anemia117. Insufficient spiral artery remodelling during placentation activates autoinflammatory processes such as cytokine release and the complement cascade, which damage endovascular tissue118-120. Erythrocytes passing through damaged blood vessels fragment and degrade, reducing serum haemoglobin and inducing an exacerbated anemic state (some measure of anemia is normal during pregnancy due to the increase in blood volume)110. Maternal anemia is linked to intrauterine growth restriction (IUGR), which alters fetal development, including metabolism, endocrine signalling, atrophy and hypertrophy of normally balanced cell types, and altered gene expression121,122. These complications culminate and increase risk of fetal hypoglycaemia, premature delivery, neurological complications, poor growth in childhood, and even increases risks of cardiovascular and metabolic complications in adulthood122. Haemolysis is alleviated by increasing erythrocyte volume via blood transfusions, immunotherapy and/or corticosteroids which directly target and reduce erythrophagocytosis123,124. 14 1.3.1.2 Elevated Liver Enzymes A dysfunctional placenta critically underlies HELLP syndrome’s systemic pathology125. Insufficient spiral artery remodelling undermines optimal maternofetal nutrient exchange, induces secretion of antiangiogenic factors, and causes structural damage to placental tissues and blood cells125-127. Placentas in HELLP syndrome patients release cellular debris into maternal circulation that induces an inflammatory response and leads to the formation of fibrin deposits and accumulated leukocytes in hepatic sinusoids110,128. Sinusoids are blood vessels which carry arterial and venous blood throughout hepatic tissue for nutrient and waste exchange. When sinusoids are damaged, blood cannot filter properly through the liver, resulting in periportal necrosis117,129. Elevated alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, gamma glutamyl transferase, bilirubin, and lactate dehydrogenase levels are characteristic of hypertension-related liver damage and HELLP syndrome130,131. Abdominal ascites, renal dysfunction, enlarged veins in the digestive system, enlarged liver and spleen, and internal bleeding are potential comorbidities132. While rare, liver transplant as a treatment for hepatic damage from HELLP syndrome has been reported. In 2005, a review reported that 2 of the 8 women that underwent liver transplant for HELLP syndrome between 1987 and 2003 died within one month of transplantation, and 2 others required subsequent transplants133. 1.3.1.3 Low Platelet Count Failure of spiral arteries to properly remodel stimulates apoptosis of endothelial tissues, causing an ischaemic-reperfusion injury to the placenta108,134. The injury activates immune responses which further damage endothelia in blood vessels, resulting in the exposure of underlying 15 extracellular collagen to the bloodstream134,135. Platelets bind to damaged vascular tissue which activates the coagulation cascade, causing further platelet aggregation and agglutination135. Thus, platelets are removed from circulation to form microthrombi, which reduces serum platelet levels. Platelet levels below 150,000 per mm3 are considered a diagnostic criterion in HELLP syndrome117. Activated platelets also release thromboxane A, serotonin, and pro-inflammatory cytokines which ultimately induce vasospasm and damage endothelial tissues further136. Damage to hepatic tissues reduces thrombopoietin production and thereby reduces overall platelet synthesis137. While mild thrombocytopenia is normal in healthy pregnancies, the low platelet count becomes pathological in HELLP syndrome137. A reduction in bioavailable platelets represents a significant threat to maternal health. If haemorrhage occurs and the body cannot form a sufficient clot to stop bleeding, mothers face severe morbidities and mortality. Cerebral haemorrhage, while rare, is a documented complication associated with severe HELLP syndrome138. 1.4 MULTIFETAL PREGNANCY Multifetal pregnancy occurs when more than one fetus develops in utero. Approximately 97.2% of births are singletons (one fetus), with twin and triplet births comprising approximately 2.7% and 0.1% of births, respectively139. Higher order plural pregnancies are extremely uncommon. Multifetal pregnancy is associated with greater risk of adverse pregnancy outcomes140-145. Delivery before 37 weeks of gestation (which defines preterm birth) occurs in 50% of twin pregnancies and 100% of triplet pregnancies140. Preterm birth is associated with neonatal, infant, and child morbidity and mortality141. Low birth weight (less than 2500g at delivery) and intrauterine growth restriction are also more likely to occur in multifetal pregnancies142-145. In some cases of high-risk 16 pregnancy, selective reduction of one or multiple fetuses is offered to reduce adverse outcome risk to both mother and fetuses146. 1.4.1 Chorionicity Twin pregnancies can differ by zygosity, amnionicity, and chorionicity. Zygosity describes the embryonic origins of each fetus: one embryo splitting into two (monozygotic), or two independent embryos (dizygotic)147. Embryonic trophoblast cells differentiate into the chorion and the amnion, two layers of the sac in which fetuses develop. Diamniotic twins develop in different amniotic sacs; monoamniotic twins develop in the same amniotic sac147. Dichorionic twins each develop separate chorions with separate placentas; monochorionic twins develop one largened but shared placenta147. Dizygotic twins predominantly develop as dichorionic diamniotic, while monozygotic twins can develop as any combination thereof147. Importantly, monochorionic twins face greater risk of preterm delivery and twin-to-twin transfusion syndrome, a condition wherein one twin receives more placental blood flow148,149. The other twin face elevated risk of malnutrition, intrauterine growth restriction, and mortality149. 17 Figure 1.1 Chorionicity. Dizygotic twins form as a result of two independent ova fertilizing and implanting simultaneously. Most dizygotic twins form distinct chorions and amnions. Monozygotic twins develop when a single fertilized zygote splits into two distinct cell bodies prior to or following implantation. Dichorionic diamniotic monozygotic twins form when the zygote splits at the morula stage; monochorionic diamniotic twins form when the cells split at the hatching phase; monochorionic monoamniotic twins form when the cells split post-implantation. Source: George Nikolopous Gynaecology & Reproduction Clinic150. 18 1.4.2 Multifetal Pregnancy and IVF IVF is known to increase the likelihood of twin gestation by up to 20-fold (32.1% twin rate in IVF pregnancies versus 1.5% twin rate in spontaneously conceived pregnancies), according to a 2021 Chinese study151. Some clinics transfer multiple embryos into the uterus to increase likelihood of at least one pregnancy. Consequently, the majority of twin pregnancies conceived by IVF are dizygotic, though the incidence of monochorionic twins is also elevated in IVF pregnancies150-153. Although the 2-embryo transfer is less common now, twin rates have risen during past decades, a phenomenon widely attributed to increased use of ART139. Indeed, a 2020 study found that rates of overall singleton births have decreased from 1971 – 2017, with a concurrent increase in twin births across the same period139 (Figure 2). The selective fetal reduction procedure was created to mitigate the increasing number of preterm deliveries and adverse outcomes in multifetal pregnancies following IVF conception153. Twin pregnancy, as a result of IVF or spontaneous conception, is associated with increased risk of preterm delivery and perinatal mortality, as well as gestational diabetes, pulmonary edema, placenta previa, preeclampsia, and eclampsia154-158. 19 Figure 1.2 Trends in the incidence of (a) singletons and (b) twins among all deliveries in the US by race 1971-2018. Figure 2A shows a decreasing trend in singleton births across the period; Figure 2B shows an increase in the incidence of twin births across the period. Rates of twins have increased across all racial/ethnic groups across the given period though rates are disproportionately high among NHW women. AAPC, average annual percentage change; *95% confidence interval. Adapted from source: Temporal Trends in the Rates of Singletons, Twins and Higher-order Multiple Births Over Five Decades Across Racial Groups in the US139. 20 1.5 SEVERE MATERNAL MORBIDITY Severe maternal morbidity (SMM) is a composite term for pregnancy outcomes that carry a high risk of maternal death. Blood transfusions, admission to the intensive care unit (ICU), cardiovascular complications, and hysterectomy are among the commonly recognized outcomes or indicators of SMM159. SMM occurs in approximately 2.5% of pregnancies, though it is likely to be underreported160. Studies analysing temporal trends in SMM in Canada have reported a rate increase from 14.0 cases to 16.4 cases per 1,000 deliveries between 2005 to 2013 and a decline to 14.2 cases per 1,000 deliveries by 2015161. Risk factors for SMM include, for instance, history of caesarean delivery, maternal age at or above 35 years old, comorbidities, twin pregnancy, caesarean delivery and pre-term delivery 162-165. Findings regarding parity as a contributory factor to SMM risk are mixed: Norhayati et al. (2016) reported no association where Lindquist et al. (2015) and Gray et al. (2012) found primiparity to be a definitive risk factor162,163,166: Norhayati et al. conducted a comparative cross-sectional study in two tertiary referral hospitals in Malaysia with a population of 21,756 women, of whom 395 had SMM, though only 353 were considered eligible (353/21,756, 1.65%)162. Lindquist et al. conducted a case-control analysis using the Victorian Perinatal Data Collection from Victoria, Australia163. Their study population comprised of 211,060 women, including 1,119 cases of severe maternal morbidity (0.53%)163. Gray et al. utilized a population-based case-control study design linking birth certificate and hospital discharge data from Washington State in the US166. Their study population included 50,597 women, of whom 9,485 had SMM and 41,112 were randomly selected controls166. While all studies used logistic regression for multivariable analyses, the differences in setting, population type, and nuances in the covariates used in each study could contribute to the studies’ differing results on parity as a factor for SMM. 167. Zeitlin et al. (2019) reported that first-year mortality among infants born to 21 mothers who experienced SMM is higher than for those whose mothers had low-risk pregnancies (relative risk 1.39, 95% CI 1.14 – 1.70)168. Importantly, SMM is a condition which disproportionately affects women with limited access to resources169. Preventing SMM requires a multifactorial approach, including prevention of chronic medical conditions, mitigating the effects of socioeconomic determinants of SMM and upholding a dedication to delivering effective, considerate, and supportive care to mothers during pregnancy and postpartum. 1.5.1 SMM and IVF The incidence of SMM is higher among mothers who used ART and specifically in women who conceived by IVF;170-173 and some evidence shows that IVF using donor genetic material places mothers at greater risk for severe morbidities than IVF using autologous embryos170. Risk of SMM is also higher in multifetal pregnancies that often occur as a result of IVF170,171,173. Women who undergo IVF are more likely to experience three or more severe morbidities relative to those who conceived naturally173. Sepsis (relative risk (RR) 1.54, 95% CI 1.13-2.10), haemorrhage (adjusted odds ratio 2.7, 95% CI 1.9 – 3.7), cardiac complications (RR 1.32, 95% CI 0.87 – 1.98), intensive care unit (ICU) admission (RR1.51, 95% CI 1.17 – 1.94), and blood transfusion (RR 1.70, 95% CI 1.39 – 2.08) were commonly evaluated as outcomes or indicators of SMM in the literature170,173. My thesis focused on SMM components including the need for blood transfusion, ICU admission, eclampsia, uterine rupture, and intrapartum hysterectomy. 22 1.5.2 Eclampsia Eclampsia is a severe complication of preeclampsia characterised by new onset of multifocal local or tonic-clonic seizure activity or unexplained coma during pregnancy or postpartum174. It occurs in approximately 0.8%-1.6% of pregnancies complicated by preeclampsia175. Global incidence has decreased across recent years, though incidence varies; rates of eclampsia range from 1.6 to 10 per 10,000 deliveries in high-income countries and 50 to 151 per 10,000 deliveries in low- and middle-income countries176. Eclampsia is responsible for 7% of maternal deaths worldwide177,178, representing a notable threat to maternal and neonatal health. Long term sequelae include increased risk of preeclampsia in subsequent pregnancies, cardiovascular complications, and maternal memory and cognitive dysfunction179-183. Treating preeclampsia with antihypertensives, reducing exposure to risk factors, and inducing delivery can prevent progression to eclampsia174. 1.5.3 Blood Transfusions According to the Canadian Perinatal Surveillance System (CPSS), blood transfusion is the most common SMM condition161. Blood or blood component transfusions are mostly used to treat haemorrhages that occur peri- or postpartum184. Postpartum haemorrhage is defined as blood loss of ≥ 1000mL during vaginal or caesarean delivery or within 24 hours of birth184. According to some studies, over 50% of patients who experience postpartum haemorrhage receive blood transfusions185. Additionally, postpartum haemorrhage and blood transfusion are more common in IVF-conceived pregnancies171. Embryo implantation in the lower segment of the uterus, which is more common in IVF pregnancies, has been suggested as a reason behind the observed elevated risk of haemorrhage186. Maternal anaemia is a common cause for blood transfusion, affecting 23 approximately 36% of pregnant women globally187,188. Importantly, the severity of maternal condition can vary among women who receive a blood transfusion189, and more detailed information on reasons for transfusion and clinical context are needed to identify which cases constitute a true SMM. 1.5.4 Uterine Rupture Uterine dehiscence is defined as a partial separation of uterine tissue layers (endometrium, myometrium, and perimetrium) and is most commonly caused by a structural damage originating in prior caesarean delivery190. Uterine dehiscence occurs in approximately 4.6%-9.0% of mothers who have previously undergone a caesarean delivery191,192. In severe cases, dehiscence can lead to uterine rupture193. Rupture of the uterus is characterised by separation of all three uterine tissue layers from one another194. Uterine ruptures occur most commonly in patients who have experienced at least one prior delivery by caesarean section, especially those who attempt to deliver vaginally after having a previous cesarean195. Incidence of uterine rupture is approximately 0.3% of women who have had one prior caesarean section (with a scarred uterus) and 3.0% of patients who have had more than one prior caesarean delivery195. Ruptures are exceedingly rare in unscarred uteri196. Incidence of uterine rupture and rates of associated mortality are significantly greater in low-income countries (e.g., Pakistan, Uganda) relative to high-income countries (e.g., Japan)197; the United States is considered a high-income country according to the World Bank198. Additional risk factors for uterine rupture include physical trauma/injury to the uterus, genetic disorders such as Ehlers-Danlos syndrome, excessive stimulation of labour by oxytocin, advanced 24 maternal age, fetal macrosomia, and multifetal gestation194,195,199-202. It is estimated that 97% of uterine ruptures are preventable by reducing exposure to major risk factors203. 25 Figure 1.3 Uterine Dehiscence versus Uterine Rupture. Uterine dehiscence describes a partial separation or shift from the normal locations of the uterine tissue layers. Uterine rupture describes a full separation of the three tissue layers of the uterus. Source: Operative Obstetrics & Gynecology204. 26 1.5.4.1 Intrapartum Hysterectomy While the majority of uterine ruptures can be surgically repaired,200 severe ruptures may sometimes require a hysterectomy to prevent further haemorrhage or tissue necrosis. A 2019 study reported that 37.8% women with a rupture of scarred uterus underwent hysterectomy, compared with 12.1% of women with a rupture of an unscarred uterus200. Mothers who underwent hysterectomy were more likely to have infection, thromboembolism, genitourinary injury, and neuropathies205. The risk of developing de novo anxiety and depression is also elevated in women who undergo hysterectomy206. 1.5.6 ICU Admission ICU admission, while not a morbidity itself, represents an indicator of severe morbidity. Maternal admission to the ICU is associated with conditions such as hypertensive disorders of pregnancy, haemorrhage, stroke, embolism, shock, diverse cardiac complications, and placental complications207-210. Risk factors include advanced maternal age, pre-existing medical conditions, and comorbidities in pregnancy210,211. Maternal ICU admission rates vary widely, ranging from 26 to 454 per 10,000 deliveries212,213. The observed variation is likely due to region-specific availability of ICU facilities; areas with a greater availability and accessibility will have higher admission rates214. Multiple studies have reported that rates of maternal ICU admission are increasing210,215. One study showed that over 35% of patients with SMM were admitted to ICU213. ICU admission can occur at any point in pregnancy, though a 2017 study reported higher ICU admission rates for pregnancy-associated complications in the antepartum (any point in pregnancy prior to delivery) and postpartum periods (within 6 weeks after delivery) relative to a time period 27 around delivery216. A study by Farr et al. (2017) show mortality among mothers admitted to ICU ranging from 4.4% to 5.8% in Germany210. Some patients may face increased levels of pain, anxiety, and depression following ICU admission217. Effective antenatal care, regular monitoring, and preventive measures against high risk-morbidities are needed for reducing maternal ICU admission. 1.6 RACE AND ETHNICITY Race and ethnicity are often conflated terms. Race is a socially constructed categorisation of individuals based on shared phenotypic presentations of diverse genetics218. Race is also rooted in geographic and national contexts. Ethnicity defines shared culture, values, language, food, beliefs, and more218. In essence, race is associated with physical traits while ethnicity represents one’s ancestry, history, and culture. Both are closely tied to self-perception and identity. The first chapter in this body of work focuses on non-Hispanic White (NHW), non-Hispanic Black (NHB), Asian, American Indian and Alaskan Native (AIAN), Pacific Islander (PI), Hispanic, and mixed-race women. 1.6.1 Racial/Ethnic Disparities in Maternal Health Outcomes Racial/ethnic disparities in pregnancy outcomes have been well documented in the US219-224. Contemporary literature suggests that NHW women have on average lower rates of maternal morbidity and better pregnancy outcomes if morbidity occurs compared with other race/ethnicity groups222,225,226. For example, NHB women are 2- to 3-fold more likely to die or suffer severe 28 morbidity related to pregnancy-related conditions than NHW women, and AIAN women are more likely to deliver via caesarean section than NHW women219-221. Although these disparities reflect differences in socioeconomic status and healthcare access for various racial and ethnic groups in the US, individual risk factors and SES do not completely explain these disparities222-224. 1.6.2 Racial/Ethnic Disparities in Maternal IVF Outcomes Racial/ethnic disparities in SMM in women who conceived by IVF have not been adequately studied. Lisonkova et al. in 2022 reported that racial/ethnic disparities in adverse fetal and infant outcomes are larger in women who conceived by ART than in those who conceived spontaneously227. For instance, the disparity in neonatal mortality between NHB and NHW women was 2-fold larger in those who conceived by ART compared with the disparity among NHB and NHW women who conceived spontaneously227. More studies are needed to elucidate the effects of race and ethnicity on perinatal outcomes of women who conceived by ART. 1.6.3 Racial/Ethnic Disparities in Risk Factors for Adverse Maternal Outcomes 1.6.3.1 Pre-Pregnancy Body Mass Index The body-mass index (BMI) is a ratio of an individual’s height and weight calculated as kilogram of mass per square metre of height. BMI values are categorised as underweight (<18.5 kg/m2), healthy weight (18.5 – 24.9 kg/m2), overweight (25.0 – 29.9 kg/m2) or obese (≥30.0 kg/m2)228. Proportions of mothers who are overweight and obese have increased in recent decades229. BMI is largely associated with lifestyle and environmental factors. Unhealthy food options and lack of 29 exercise critically underlie the development of obesity, but it is important to acknowledge the role of access to and affordability of healthy lifestyle choices. Low-income neighbourhoods have 2.5-fold greater opportunities for unhealthy food options relative to high-income neighbourhoods230. Safe, usable outdoor spaces or facilities for physical activity are also less common in low-income neighbourhoods231. Thus, individuals living in deprived areas have, on average, less opportunity for a healthy lifestyle; proportions of women with high BMI and associated sequelae are consequently greater in these groups. Most Non-White racial/ethnic groups have on average a higher prevalence of risk factors that contribute to obesity232,233. These groups have higher risk of unemployment and food insecurity, as well as reduced access to spaces for exercise234. Approximately 38% of NHB and approximately 33% of Hispanic people in the US are obese compared with approximately 29% in NHW adults234. AIAN people are 50% more likely to have obesity than NHW people in the US235. BMI outside of the healthy weight range is a risk factor for many adverse maternal outcomes. Elevated BMI is associated with gestational diabetes, gestational hypertension, caesarean delivery, postpartum haemorrhage, preeclampsia, and preterm birth,236,237 while low BMI is associated with increased risk of small for gestational age, low birth weight, preterm delivery, stillbirth, admission to ICU, and anemia238-240. Managing weight gain and following healthy lifestyle choices are integral parts of a healthy pregnancy. 1.6.3.2 Comorbidities in Pregnancy Gestational diabetes and hypertensive disorders are among the most common morbidities observed in pregnancy. Gestational diabetes occurs in approximately 8% of pregnancies, and 30 disproportionately affects women in non-White racial/ethnic groups241. Hispanic and Asian women are at highest risk for developing gestational diabetes242,243. NHB, Hispanic, and Asian women are also more likely to develop type II diabetes following gestational diabetes during pregnancy relative to NHW women244,245. Obesity, which is a strong risk factor for gestational diabetes, is more prevalent in NHB, AIAN, and Hispanic groups232,233. While Asian people tend to have a lower BMI than NHWs, obesity-related health complications tend to occur at lower BMI among Asian people246,247. Hypertensive and cardiovascular events in pregnancy like eclampsia (0.27 per 1,000 delivery hospitalizations), heart failure (0.46 per 1,000 delivery hospitalizations), thromboembolisms (0.08 per 1,000 delivery hospitalizations) and haemorrhage resulting in blood transfusion (6.90 per 1,000 delivery hospitalizations) are leading causes of severe maternal morbidity162. These conditions can cause intrapartum and postpartum complications for both mother and fetus. Gestational hypertension and preeclampsia are more common in NHB and Hispanic women relative to NHW women248. Risks of haemorrhage and preeclampsia are also higher in AIAN relative to NHW women249,250. Haemorrhage and hypertension are more likely to result in pregnancy-related death in non-White race/ethnicity groups159, indicating racial/ethnic disparities in both maternal morbidities and case-fatality rates. 1.6.3.3 Socioeconomic Status Socioeconomic status (SES) describes the social positioning of an individual or a group as a multidimensional representation of various social and economic factors251. Educational level, occupation, median household income, access to resources, and social capital contribute to SES252. 31 In the US, NHB, Hispanic, and AIAN individuals are more likely to belong to lower SES than NHW and Asian individuals253. Indeed, Asians have the highest median household income of any race/ethnicity in the US253. In a relative comparison, NHB and Hispanic individuals earn 59 cents and 70 cents, respectively, for every dollar an NHW person earns 253. Postsecondary education is also lower in non-White racial/ethnic groups253. Importantly, a strong association exists between SES and maternal health outcomes. Lower SES is associated with reduced access to quality maternal care and greater risk of preterm delivery, gestational diabetes, spontaneous abortion, caesarean delivery, preeclampsia, and eclampsia254,255. Higher SES is linked to reduced rates of SMM risk factors such as smoking, substance use, and chronic hypertension and diabetes256. Studies report that AIAN, NHB and Hispanic women have reduced antenatal care relative to NHW women,255 and NHB and AIAN women have an elevated risk of preterm delivery257. In addition, NHB women are more likely to die from preeclampsia, haemorrhage, placenta previa and/or placental abruption than NHW women226. Caesarean delivery is also more common in non-White women255,258. 1.6.3.4 Rural Residence Women living in rural areas have higher rates of poor health than women in urban or metropolitan areas259. This phenomenon is known as the “rural mortality penalty”259. Lower rates of healthy food intake and exercise in rural areas are associated with in higher incidence of obesity and diabetes260,261. Substance use and smoking are more common in rural areas;262 as well as SMM, preterm delivery, and postpartum depression 263-265. While exposure to these risk factors is prevalent across all racial/ethnic groups in rural areas, non-White people are disproportionately 32 affected by the consequent adverse health outcomes. For example, NHB and AIAN populations in rural settings are more likely to have diabetes and hypertension than NHWs262. NHB, Asian, AIAN, PI and Hispanic groups are less likely to have an individual healthcare provider than NHWs; NHB, Asian, and Hispanic groups are also less likely to have seen a physician in the past year266. Lack of access to resources is associated with increased maternal morbidity and mortality265. Many solutions have been proposed to improve delivery of health care services in rural populations265. However, more funding and opportunity for implementation of effective strategies are necessary to achieve improvements in maternal health outcomes. 1.6.3.5 Healthcare Insurance Health care options in the US include, besides a private insurance, two main publicly funded health care insurance providers: Medicare, for individuals 65 years of age or older or those with disabilities, and Medicaid for low-resource individuals267. Private health care insurance is available through employers or private firms267. The US Department of Health and Human Services notes that having health care insurance improves access to resources and improves health outcomes268. NHW and Asian people are more likely to have private health care insurance and they are most likely to be insured among all race/ethnicity groups269. Conversely, Hispanic, NHB, AIAN and PI individuals are more likely to be uninsured or use Medicaid, showing the disparity in access to healthcare and its affordability269. Indeed, the majority of NHB, AIAN, and Hispanic mothers in the US use Medicaid to cover the cost of delivery270,271. NHW women are also more likely to have continuous health care insurance coverage across the whole pregnancy and postpartum periods than NHB, Hispanic, and AIAN women275. Continuous coverage is associated with better maternal 33 health271. Women who use public healthcare insurance have been shown to have higher rates of hospital readmission within 30 days after delivery than those with private funding272. Brown et al. (2021) reported that the rate of SMM in Medicaid users was greater among NHB, Hispanic, and Asian mothers relative to NHW mothers270. Studies suggest that Medicare users face elevated risk of adverse maternal health outcomes relative to Medicaid users269,271. The observed disparity is likely attributable to higher rates of pre-existing conditions among Medicare users, which qualifies them for Medicare insurance coverage and, at the same time, predisposes them to adverse pregnancy outcomes267. 1.7 THESIS OVERVIEW 1.7.1 Research Question This thesis aims to answer the following broader question: How does in-vitro fertilisation combined with other risk factors, including race/ethnicity or plurality, affect severe maternal morbidity? 1.7.2 Rationale IVF use is increasing globally, with a correlated decline in fertility. While recommendations have been instituted to reduce pregnancy complications or adverse health outcomes associated with IVF, such as the preference for a single embryo transfer, IVF continues to be associated with a 2-fold increase in the risk of SMM. Despite extensive research on IVF effects, racial/ethnic disparity in SMM among women who conceived using IVF has not been adequately studied. To my 34 knowledge, a population-level study assessing the association between IVF and SMM and potential effect modification by race/ethnicity has been lacking. In addition, the association between IVF conception and preeclampsia and eclampsia has been investigated. However, a population-based study quantifying the association between IVF and HELLP syndrome has not been conducted to date. Understanding IVF and its interactions with other risk factors for adverse maternal health outcomes is important for clinical practice and for improving perinatal health of mothers who conceived via IVF. Thus, I aimed to address these gaps in the contemporary medical literature through my thesis with the following objectives. 1.7.3 Specific Objectives and Hypotheses To answer the research questions, I conducted two retrospective cohort studies using data from live birth and fetal death certificates in the US and BC Perinatal Database Registry in British Columbia (BC), Canada. The specific objectives were: 1. To examine the association between IVF and SMM and how race/ethnicity potentially modifies this association. 2. To examine the relationship between IVF, HELLP syndrome, and how twin pregnancy modifies this association. I hypothesised that IVF use increases the incidence of adverse maternal health outcomes. Specifically, I purported that women who use IVF are at greater risk for SMM compared with 35 women who conceived spontaneously. I also hypothesized that racial/ethnic disparities would be larger in women who conceived using IVF. I further hypothesized that women who use IVF are at greater risk for HELLP syndrome compared with women who conceived spontaneously. Additionally, I expected that women carrying twin pregnancies are at greater risk for HELLP syndrome relative to singleton pregnancies, among women with and without IVF-conceived pregnancy. 1.7.4 Aims The following specific aims will address my hypotheses. 1.7.4 Study 1: Racial/Ethnic Disparity in Severe Maternal Morbidity Among Women Who Conceived by Assisted Reproduction Aim 1.1: To determine whether the use of IVF for conception is associated with SMM. Aim 1.2: To determine how race/ethnicity potentially modifies the association between IVF and SMM and quantify disparities in SMM between racial/ethnic groups. 1.7.5 Study 2: The Association of In-Vitro Fertilization, Twin Pregnancy and HELLP Syndrome: A Population-Based Study Aim 2.1: To examine the association between IVF use and HELLP syndrome incidence. 36 Aim 2.2: To examine how twin gestation modifies the association between IVF and HELLP syndrome. 37 CHAPTER 2: Racial/Ethnic Disparity in Severe Maternal Morbidity Among Women Who Conceived by Assisted Reproduction 2.1 OBJECTIVE To examine the association between IVF conception and SMM and how race/ethnicity potentially modifies this association. 2.2 METHODS 2.2.1 Data Source and Study Population The study population included all women who delivered a singleton live birth or stillbirth in the US from 2016 to 2021. I used National Center for Health Statistics (NCHS) data that included information from live birth and fetal death certificates273. These files comprise self-reported and chart-abstracted data on demographic and clinical characteristics, pregnancy complications, and birth outcomes for all live births and stillbirths in the US. I excluded births occurring before 20 weeks and after 44 weeks gestation and those with missing data on gestational age, plurality, race and ethnicity, or mode of conception. Live birth and fetal death certificates included self-reported information about assisted reproduction, either IVF or other treatments. For the group of women identified as having delivered following use of ART, I included women who indicated using “assisted reproductive technology (e.g., IVF, gamete intrafallopian transfer)”. 273 Women who conceived using other modes of assisted conception (e.g., fertility drug treatment or artificial insemination) were excluded, while all other women constituted the comparison group of women 38 who conceived spontaneously. The datasets were publicly accessible and deidentified; thus, the study did not require ethics approval. All analyses were conducted using SAS version 9.4 (SAS Institute, Inc). 2.2.2 Severe Maternal Morbidity Five SMM conditions were the primary outcomes of interest: eclampsia, blood transfusion, uterine rupture, intrapartum hysterectomy and ICU admission. Uterine rupture and intrapartum hysterectomy are very rare and can be concurrent events, and therefore these two morbidities were combined into one category. ICU admission is not a morbidity itself but an indicator for severe morbidity. Besides the 4 severe morbidity conditions listed above, I also examined the composite SMM which included any of these conditions (eclampsia, blood transfusion, uterine rupture/intrapartum hysterectomy and/or ICU admission). 2.2.3 Race/Ethnicity The categories of self-reported maternal race and ethnicity were based on the NCHS categories274 and included: (1) non-Hispanic White (NHW), (2) non-Hispanic Black (NHB); (3) American Indian and Alaska Native (AIAN); (4) Asian (Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, and other Asian); (5) Pacific Islander (Native Hawaiian, Guamanian or Chamorro, Samoan, and Other Pacific Islander); (6) Hispanic (all women of Hispanic origin: Mexican, Mexican American, Chicana, Puerto Rican, Cuban, and other Hispanic origin, regardless of race) and (7) mixed-race. The mixed-race category comprised women who self-reported more than one 39 of any race/ethnicity. Details of which races/ethnicities comprised each mother’s identity was not included in this analysis. 2.2.4 Statistical Analysis The primary independent variable was IVF, and race/ethnicity was examined as a factor that potentially modified the effect of IVF on severe maternal morbidity. I quantified rates of SMM outcomes and compared SMM rates between women with IVF versus spontaneous conception within categories of race/ethnicity. Rate ratio (RR) and rate difference (RD) with 95% confidence intervals (CI) were used to express the magnitude of the differences in SMM rates. I used logistic regression models to quantify the association between IVF and SMM (within categories of race/ethnicity) using adjusted odds ratios (aOR). The statistical significance of differences in SMM frequency between IVF and spontaneous conception groups by race/ethnicity was assessed using interaction terms (between IVF and race/ethnicity). aORs were adjusted for maternal characteristics, including previous caesarean delivery, chronic hypertension, chronic diabetes, previous fetal death or termination of pregnancy, previous infant death, pre-pregnancy body mass index (BMI), maternal age (<25 and ≥35 years versus 25–34 years), parity (nulliparous, parity 1–3, parity >=4), education (high school or higher versus less than high school), the type of health care insurance (Medicaid, self-paid, or other versus private), prenatal care (no prenatal care versus some prenatal care), smoking during pregnancy, and fetal sex (male versus female). BMI (kg/m2) was categorized as follows: underweight (<18.5), normal BMI (18.5–24.9), overweight (25.0–29.9), and obesity class 1 (30.0–34.9), class 2 (35.0–39.9), and class 3 (≥40). Records with missing values for any covariate (<3% in total) were excluded from multivariable analyses. 40 2.2.5 Sensitivity Analysis I was not able to adjust the regression models for the type of health care insurance in the primary analysis, because this information was not available on fetal death certificates. Sensitivity analyses restricted to live births were carried out using logistic regression models with 95% CI and these analyses were adjusted for the type of health care insurance (in addition to covariates adjusted for in primary analysis). 2.3 RESULTS 2.3.1 Study Population Overall, 21,990,215 women had a singleton live birth or stillbirth in the US between 2016 to 2021. I excluded records with missing data for gestational age, pregnancies delivered at <20 weeks and >44 weeks gestation, and women who reported using non-IVF medically assisted fertility procedures. My study population comprised 21,585,015 women, of whom 11,154,848 (52%) were NHW; 3,145,738 (15%) were NHB; 167,468 (0.8%) were AIAN; 1,367,352 (6%) were Asian; 55,930 (0.2%) were PI; 5,210,196 (24%) were Hispanic; and 5,210,196 (2%) were mixed-race. IVF was used by 183,662 (0.85%) of the total study population. The proportions of women who used IVF by race/ethnicity was as follows: 127,982 (1.2%) of NHW women, 9,535 (0.3%) of NHB women, 228 (0.1%) of AIAN women, 26,383 (1.9%) of Asian women, 104 (0.2%) of PI women, 16,224 (0.3%) of Hispanic women, and 3,206 (0.7%) of mixed-race women (Table 2.1). 41 Among women who conceived by IVF, more than 50% were above 35 years old in each race/ethnicity category; conversely, the majority (58%) of women who conceived spontaneously were between 25 to 34 years old. Women who used IVF were also more likely to be nulliparous, have secondary or higher education (>93% in each race/ethnic group), chronic diabetes and chronic hypertension, and more likely to deliver by caesarean section in the current pregnancy than women who conceived spontaneously. Rates of smoking and pre-pregnancy underweight were higher among women who conceived spontaneously (Table 2.1, Appendix A Supplementary Table 2.1). Racial/ethnic disparities in risk factors for adverse pregnancy outcomes were generally similar between IVF and spontaneous conception groups, with the exception of PI women who had the highest proportion of obese women in the spontaneous conception group, but one of the lowest proportions in the IVF groups (Table 2.1). 42 Table 2.1: Characteristics of women by race/ethnicity and mode of conception, singleton deliveries, United States, 2016-2021. Some percentages do not add up because of missing values; missing values <3% are not shown. IVF, in-vitro fertilization; NHW, non-Hispanic White; NHB, non-Hispanic Black; AIAN, American Indian and Alaska Native; PI, Pacific Islander; BMI, Body Mass Index. Clinical characteristics Spontaneous conception IVF NHW NHB AIAN Asian PI Hispanic Mixed-Race NHW NHB AIAN Asian PI Hispanic Mixed-Race N= 11026866 N= 3136203 N= 167240 N= 1340969 N= 55826 N= 5193972 N= 480277 N= 127982 N= 9536 N= 228 N= 26383 N= 104 N= 16224 N= 3206 % % % % % % % % % % % % % % Maternal age (years) < 25 20.5 32.4 37.0 6.9 30.8 31.4 34.8 0.7 1.3 2.6 0.3 1.0 1.5 1.4 25-34 61.6 52.5 51.1 64.7 54.1 52.3 51.5 42.4 33.5 37.7 33.2 40.4 36.8 37.4 ≥ 35 17.9 15.2 11.9 28.5 15.1 16.4 13.7 56.9 65.2 59.7 66.5 58.7 61.7 61.2 Nullipara 39.7 36.0 30.9 45.2 29.8 34.9 41.9 58.3 63.9 51.3 64.8 59.6 59.7 60.4 BMI (kg/m2) < 18.5 3.1 2.9 2.1 6.6 1.5 2.3 3.3 2.0 0.9 0.9 4.4 1.0 1.5 2.0 18.5 - 24.9 44.7 30.9 29.4 58.5 22.3 34.4 39.0 49.9 25.9 35.1 59.5 43.3 38.6 47.2 25.0 - 29.9 24.9 25.9 26.6 22.8 24.7 29.8 25.3 24.9 33.2 26.8 24.0 30.8 30.4 26.3 ≥ 30.0 25.5 37.1 39.3 9.7 45.5 30.9 30.3 21.8 37.8 36.8 10.4 23.1 27.9 23.3 Maternal education ≤ Primary 7.1 12.9 20.7 6.4 21.9 25.8 11.8 0.4 1.4 1.3 1.2 1.0 5.1 0.9 ≥ Secondary 92.3 86.1 78.5 92.1 76.1 72.8 87.6 98.9 97.3 97.8 97.4 95.2 93.2 98.3 Prior caesarean delivery No 85.7 82.6 84.4 84.8 82.4 83.2 86.2 84.8 84.5 79.4 86.8 87.5 86.6 84.6 1-2 Deliveries 13.3 15.5 13.1 14.8 14.9 15.1 12.4 14.7 14.8 19.3 13.0 11.5 14.4 12.9 3+ Deliveries 1.01 1.92 2.54 0.41 2.63 1.66 1.34 0.49 0.67 1.32 0.19 0.96 1.02 0.56 Chronic hypertension 2.0 4.2 2.9 1.1 1.9 1.4 2.4 3.3 8.8 6.1 2.6 6.7 3.3 4.4 Pre-existing diabetes 0.8 1.3 2.5 1.0 2.0 1.1 1.0 0.9 2.1 2.6 1.7 3.9 1.6 1.2 Smoking in pregnancy 9.2 5.0 14.8 0.5 3.8 1.6 10.5 0.4 0.5 0.9 0.1 1.0 0.3 0.5 Caesarean delivery in current pregnancy 29.0 34.3 27.6 31.1 30.1 30.2 28.3 46.5 60.9 54.0 50.6 44.2 52.3 47.5 Gestational age (weeks) 20-33 1.9 4.6 2.9 1.9 3.2 2.4 2.5 3.2 8.9 4.8 4.3 4.8 5.4 4.3 34-36 5.6 8.1 7.8 5.5 7.7 6.4 6.5 8.0 11.2 10.5 7.8 14.4 9.5 7.6 ≥ 37 92.5 87.4 89.3 92.6 89.1 91.3 91.1 88.8 80.0 84.7 87.9 80.8 85.0 88.1 Male fetal sex 51.3 50.8 51.0 51.6 51.5 51.0 51.1 50.9 50.8 51.8 52.7 47.1 50.5 51.7 43 2.3.2 SMM by Race/Ethnicity and IVF The rate of composite SMM was 18.5 per 1000 deliveries in the IVF group relative to 7.9 per 1000 deliveries in the group who conceived spontaneously (rate ratio 2.34; 95% CI 2.26 – 2.43; rate difference 10.6 per 1000 deliveries, 95% CI 9.96 – 11.2 per 1000) (Table 2.2). The most frequent SMM component was blood transfusion, comprising up to 30% of all SMM cases (Table 2.2). Rates of SMM stratified by race/ethnicity and mode of conception are shown in Table 2.2. In the IVF group, the highest rates were in NHB women (26.2 per 1000 singleton deliveries); while in the spontaneous conception group, the highest rates were in PI women (23.5 per 1000 singleton deliveries) (Table 2.2). 44 Table 2.2: Rates of severe maternal morbidity by race/ethnicity and mode of conception, singleton deliveries, United States, 2016-2021. Conception Mode Race/Ethnicity Total N Composite SMM ICU Admission Transfusion** Eclampsia Uterine Rupture/Hysterectomy N Per 1000* N Per 1000* N Per 1000* N Per 1000* N Per 1000* Spontaneous Non-Hispanic White 11026866 78958 7.2 15321 1.4 38240 3.5 26264 2.4 7690 0.7 Non-Hispanic Black 3136203 33522 10.7 8115 2.6 14478 4.6 11225 3.6 2992 1.0 AIAN 167240 2863 17.1 413 2.5 1784 10.7 742 4.4 200 1.2 Asian 1340969 9464 7.1 2450 1.8 4287 3.2 3043 2.3 1082 0.8 Pacific Islander 55826 1313 23.5 176 3.2 365 6.5 794 14.2 70 1.3 Hispanic 5193972 37594 7.2 8187 1.6 19146 3.7 10997 2.1 3603 0.7 Mixed-Race 480277 5035 10.5 799 1.7 1787 3.7 2512 5.2 328 0.7 All race/ethnicity 21401353 168749 7.9 35461 1.7 80087 3.7 55577 2.6 15965 0.7 IVF Non-Hispanic White 127982 2292 17.9 434 3.4 1524 11.9 436 3.4 262 2.0 Non-Hispanic Black 9535 250 26.2 68 7.1 156 16.4 47 4.9 39 4.1 AIAN 228 5 21.9 0 0.0 3 13.2 1 4.4 1 4.4 Asian 26383 477 18.1 151 5.7 298 11.3 76 2.9 67 2.5 Pacific Islander 104 2 19.2 1 9.6 2 19.2 0 0.0 0 0.0 Hispanic 16224 284 17.5 68 4.2 179 11.0 55 3.4 49 3.0 Mixed-Race 3206 82 25.6 18 5.6 49 15.3 21 6.6 5 1.6 All race/ethnicity 183662 3392 18.5 740 4.0 2211 12.0 636 3.5 423 2.3 SMM, severe maternal morbidity; ICU, intensive care unit; IVF, in-vitro fertilization; AIAN, American Indian and Alaska Native. *Per 1000 deliveries **Transfusion includes blood or red blood cells transfusion. 45 2.3.3 Multivariable Analysis PI and AIAN women who conceived by IVF constituted only a relatively small group with very few cases of SMM, and therefore these two race categories were not included in multivariable analyses. Adjusted analyses using NHW women who conceived spontaneously as refence category showed that women of mixed-race who conceived by IVF had the highest adjusted odds of SMM (aOR= 3.21, 95% CI 2.56 - 4.01) (Table 2.3), followed by NHB women who conceived by IVF (aOR= 2.93 95% CI 2.57 - 3.33) (Table 2.3). NHB women with IVF conception had the highest relative odds of blood transfusion (aOR=4.45, 95% CI 3.78 - 5.22) and uterine rupture/hysterectomy (aOR= 5.74, 95% CI 4.17 - 7.91) relative to NHW women who conceived spontaneously (Table 2.3). Table 2.4 shows aORs between race/ethnicity and composite SMM/individual outcomes separately for spontaneous and IVF groups, with NHWs in each mode of conception group as the reference category. aORs for each racial/ethnic category were similar across spontaneous and IVF and there were no significant interactions between race/ethnicity and IVF. Multivariable analyses of each SMM component showed that Asian women had significantly greater aOR for ICU admission in the IVF conception group (aOR= 1.34, 95% CI 1.29 – 1.41 compared with the spontaneous conception group (aOR= 1.67, 95% CI 1.38 – 2.02; P value for interaction= 0.001). Additionally, NHB had an aOR=1.34 (95% CI 1.28 – 1.40) in the spontaneous conception group versus aOR= 2.02 (95% CI 1.44– 2.85) in the IVF group (P value for interaction=0.001) (Table 2.4). Similarly, Hispanic women had aOR= 0.96 (95% CI 0.92 – 1.00) in the spontaneous conception group versus aOR= 1.49 (95% CI 1.09 – 2.03) in the IVF group (P value for interaction<0.001; Table 2.4). 46 47 Table 2.3: Adjusted odds ratios for severe maternal morbidity by race/ethnicity and mode of conception, singleton deliveries, United States, 2016-2021. NHW spontaneous and NHW IVF were used as reference categories. †aORs were adjusted for maternal demographic and pregnancy characteristics, including pre-pregnancy BMI, smoking during pregnancy, nulliparity, parity, prior caesarean delivery (0 versus ≥1), chronic diabetes, chronic hypertension, age (<25, >34 years versus 25–34 years), education (high school or higher versus less than high school), prenatal care (no prenatal care versus some prenatal care), previous fetal death or termination of pregnancy, previous infant death, and fetal sex (male versus female). American Indian and Alaska Native and Pacific Islander were excluded from the multivariable analysis due to small numbers. SMM, severe maternal morbidity; ICU, intensive care unit; IVF, in-vitro fertilization; aOR, adjusted odds ratio; CI, confidence interval; NHW, non-Hispanic White; NHB, non-Hispanic Black. Conception Mode Race/Ethnicity SMM ICU Admission Blood Transfusion Eclampsia Uterine Rupture/Hysterectomy aOR† 95% CI aOR 95% CI aOR 95% CI aOR 95% CI aOR 95% CI Spontaneous Non-Hispanic White Ref Ref Ref Ref Ref Ref Ref Ref Ref Ref Non-Hispanic Black 1.39 1.37 - 1.41 1.78 1.73 - 1.83 1.30 1.27 - 1.32 1.32 1.29 - 1.35 1.34 1.28 - 1.40 Asian 1.04 1.02 - 1.07 1.34 1.28 - 1.40 0.95 0.92 - 0.98 1.09 1.04 - 1.13 1.18 1.10 - 1.26 Hispanic 0.98 0.97 - 0.99 1.18 1.15 - 1.22 1.04 1.02 - 1.06 0.83 0.81 - 0.85 0.96 0.92 - 1.00 Mixed-Race 1.42 1.38 - 1.46 1.23 1.14 - 1.32 1.03 0.98 - 1.08 2.07 1.98 - 2.15 1.04 0.93 - 1.16 IVF Non-Hispanic White 2.31 2.22 - 2.42 2.02 1.83 - 2.23 3.41 3.23 - 3.59 1.22 1.10 - 1.34 2.84 2.50 - 3.22 Non-Hispanic Black 2.93 2.57 - 3.33 3.57 2.77 - 4.59 4.45 3.78 - 5.22 1.36 1.01 - 1.81 5.74 4.17 - 7.91 Asian 2.35 2.14 - 2.57 3.38 2.87 - 3.99 3.17 2.82 - 3.56 1.07 0.85 - 1.34 3.75 2.94 - 5.43 Hispanic 2.12 1.88 - 2.39 2.47 1.94 - 3.16 3.06 2.63 - 3.55 1.05 0.79 - 1.38 4.23 3.18 - 5.63 Mixed-Race 3.21 2.56 - 4.01 3.46 2.18 - 5.55 4.22 3.16 - 5.63 2.18 1.41 - 3.39 2.26 0.94 - 5.43 48 Table 2.4: Adjusted odds ratios showing modification of the association between race/ethnicity and severe maternal morbidity by mode of conception, singletons deliveries, United States, 2016-2021. NHW spontaneous and NHW IVF were used as reference categories. †aORs were adjusted for maternal demographic and pregnancy characteristics, including pre-pregnancy BMI, smoking during pregnancy, nulliparity, parity, prior caesarean delivery (0 versus ≥1), chronic diabetes, chronic hypertension, age (<25, >34 years versus 25–34 years), education (high school or higher versus less than high school), prenatal care (no prenatal care versus some prenatal care), previous fetal death or termination of pregnancy, previous infant death, and fetal sex (male versus female). American Indian and Alaska Native and Pacific Islander were excluded from the multivariable analysis due to small numbers. SMM, severe maternal morbidity; ICU, intensive care unit; IVF, in-vitro fertilization; aOR, adjusted odds ratio; CI, confidence interval; NHW, non-Hispanic White; NHB, non-Hispanic Black. Bolded text indicates statistically significant differences in aOR in spontaneous versus IVF conception group, i.e., a statistically significant interaction. Conception Mode Race/Ethnicity SMM ICU Admission Blood Transfusion Eclampsia Uterine Rupture/Hysterectomy aOR† 95% CI aOR 95% CI aOR 95% CI aOR 95% CI aOR 95% CI Spontaneous Non-Hispanic White Ref Ref Ref Ref Ref Ref Ref Ref Ref Ref Non-Hispanic Black 1.39 1.37 - 1.41 1.78 1.73 - 1.83 1.30 1.27 - 1.32 1.32 1.29 -1.35 1.34 1.28 - 1.40 Asian 1.04 1.02 - 1.07 1.34 1.29 - 1.41 0.95 0.92 - 0.98 1.09 1.04 - 1.13 1.18 1.10 - 1.26 Hispanic 0.98 0.97 - 1.00 1.18 1.15 - 1.22 1.04 1.02 - 1.06 0.83 0.81 - 0.85 0.96 0.92 - 1.00 Mixed-Race 1.42 1.38 - 1.46 1.23 1.14 - 1.32 1.03 0.99 - 1.09 2.07 1.98 - 2.15 1.04 0.93 - 1.16 IVF Non-Hispanic White Ref Ref Ref Ref Ref Ref Ref Ref Ref Ref Non-Hispanic Black 1.26 1.10 - 1.45 1.77 1.35 - 2.31 1.31 1.10 - 1.55 1.12 0.82 - 1.51 2.02 1.44 - 2.85 Asian 1.01 0.92 - 1.12 1.67 1.38 - 2.02 0.93 0.82 - 1.06 0.88 0.68 - 1.13 1.32 1.01 - 1.73 Hispanic 0.92 0.81 - 1.04 1.22 0.94 - 1.59 1.24 0.92 - 1.66 0.86 0.64 - 1.15 1.49 1.09 - 2.03 Mixed-Race 1.39 1.10 - 1.74 1.71 1.07 - 2.75 0.90 0.77 - 1.05 1.80 1.15 - 2.82 0.80 0.33 - 1.93 49 2.3.4 Sensitivity Analyses Due to limited data on some SMM components in fetal birth records, I performed sensitivity analyses including only live births, with additional adjustment for the type of health care insurance (information only available for live births). There was no change or a small change in the aORs and 95% CIs for ICU admission among Asian women both in the IVF group (aOR= 1.67, 95% CI 1.38 – 2.03) and spontaneous conception group (aOR= 1.37, 95% CI 1.31 – 1.43) although the interaction term was not statistically significant. Other results were also similar to the results of analyses including all births (Appendix A, Supplementary Table 2.2). 2.4 DISCUSSION 2.4.1 Interpretation My study showed a more than 2-fold increased risk of SMM in women with singleton pregnancies who conceived by IVF relative to those who conceived spontaneously. IVF conception overall was associated with more than a 2-fold increased risk of eclampsia and admission to the ICU, and more than a 3-fold increased risk of blood transfusion and uterine rupture/intrapartum hysterectomy. NHW and Asian women had a higher proportion of births with IVF conception compared with other race/ethnic groups. Although the overall racial/ethnic disparities in composite SMM were consistent between the spontaneous conception and IVF groups, the disparities were greater with respect to ICU admission in Asian women who conceived by IVF and with respect to uterine rupture/intrapartum hysterectomy in Hispanic and NHB women who conceived by IVF. I delineated a stronger association between SMM and IVF than between SMM and race/ethnicity, suggesting IVF use is a stronger predictive factor for SMM outcomes than race/ethnicity. 50 My study findings align with the contemporary literature demonstrating increased risk of maternal morbidity in pregnancies conceived by IVF173,275,276. A Swedish study found an elevated risk of preeclampsia, placental abruption, premature rupture of membranes and bleeding during vaginal delivery in singleton pregnancies conceived by IVF,276 while a Canadian study showed approximately 30% higher risk of SMM and/or maternal death in women who conceived by IVF.173 The latter study included multiple pregnancies, and also reported a higher risk of SMM in women who conceived by IVF than other types of fertility treatments. A 3-fold elevated rate of SMM was also reported in another Canadian study that included multiple pregnancies and used a broader definition of SMM as well as ART (including ovulation induction treatments).275 Recent studies have shown an increased risk of maternal and perinatal mortality, and SMM amongst racialized groups relative to NHW women222,277-280. I found increased rates SMM or some of its components among NHB, Asian, AIAN, PI, Hispanic, and mixed-race women relative to NHW women in both spontaneous and IVF groups. This finding was consistent for outcomes such as ICU and eclampsia. However, Hispanic women had similar or lower rates of SMM relative to NHW women. This finding may be attributed to a phenomenon recognised as the “Hispanic paradox”, wherein Hispanic persons face lower risk of adverse health outcomes relative to other racial/ethnic groups.281 Higher risk of adverse perinatal outcomes has been observed in racialized groups who use IVF. In 2020, Seifer et al. reported disparities in perinatal outcomes among NHB versus NHW women who use IVF.282 Other studies have reported lower pregnancy and live birth rates and greater odds of spontaneous abortion among NHB, Asian and AIAN women who conceived by IVF.280,283 Additionally, larger racial disparities in perinatal death, preterm birth and other adverse infant health outcome have been reported in women who conceived by IVF.284 These findings align 51 with the increased risk of ICU admission and uterine rupture/intrapartum hysterectomy in some minority race/ethnicity groups relative to NHW women in my study. Socioeconomic inequalities and institutionalised racial discrimination have been highlighted as leading factors contributing to inadequate access to fertility treatments and perinatal care among vulnerable minority women.280,285 Previous studies highlight an association between higher socioeconomic status and IVF use.286-288 Non-Hispanic White peoples in the US have a high median household income, second only to Asians,289 and I found that mothers from these groups had mostly lower rates of SMM compared with other racial/ethnic groups. For some racial/ethnic minority groups, barriers to accessing high quality health care during pregnancy and childbirth could contribute to racial/ethnic disparities in SMM. 2.4.2 Strengths and Limitations The strengths of my study include the population-based design that enhances generalisability and reduces selection bias compared with hospital-based studies. The large study size increased the statistical power necessary to assess rare outcomes. The data that I utilized have been consistently collected by trained personnel using standard certificates for live birth and fetal death over many years and provided detailed information about many potential confounders. Birth records from non-hospital sites (i.e. home births, birthing centres) are also included in the dataset, which improves the comprehensiveness of the data and better informs the study of the current landscape of maternal delivery characteristics and health outcomes. My study has several limitations. First, the self-reported information on IVF conception is subject to misclassification. Such misclassification should be relatively similar across 52 race/ethnicity groups; however, a study by Thoma et al. (2014) reported that IVF was underreported in birth certificate data290. Further exploration would be required to see how my study results would be affected by potential underreporting of IVF information in our data versus hospital-based data. Second, data about postpartum haemorrhage, uterine rupture/hysterectomy, and health care insurance were not included in fetal death certificates. Thus, the results with respect to SMM may be slightly underestimated in my study, as SMM is associated with stillbirth (although the rate of stillbirths is far less than live births). However, my sensitivity analysis did not yield significantly different results to general analyses. Third, I did not have data on other severe maternal morbidity conditions (e.g. pulmonary embolism, shock, severe cardiovascular events), and information regarding the severity of SMM components (e.g. the number of units of blood transfused). Even though severe morbidity components are potentially life-altering events and thus more likely to be noted and documented, studies show that SMM is seriously underreported on birth certificates291. However, under-reporting of SMM would have biased the aORs in my study towards the null and would not have altered my study findings, unless the under-reporting was differential by race/ethnicity. Further studies are required to assess if under-reporting of SMM and other information on birth certificates is differential by race/ethnicity. Lastly, I was not able to assess the relative risks of SMM components in PI and AIAN women who conceived by IVF due to a very small number of SMM women from these racial/ethnic groups. 2.5 CONCLUSION My population-based study showed that SMM rates were elevated among women who conceived by IVF, and the association between IVF and SMM was stronger than the association between 53 race/ethnicity and SMM. In some racial/ethnic groups, larger disparities in uterine rupture/hysterectomy and ICU admission were found in women who conceived by IVF as compared with the same disparities among women who conceived spontaneously. My data also suggests racial/ethnic disparities in access to IVF. Women of all race/ethnicities who are considering IVF should be informed and counselled regarding the risks for SMM before the ART process is initiated. Further research is needed to assess the role of prenatal and intrapartum care and the root causes of disparities in SMM by race/ethnicity. 54 CHAPTER 3: The Association of In-Vitro Fertilization and Twin Pregnancy with HELLP Syndrome: A Population-Based Study 3.1 OBJECTIVE To compare HELLP syndrome in twin versus singleton pregnancies contrasting spontaneous and in-vitro conception. 3.2 METHODS 3.2.1 Study Population I included singleton and twin live births and stillbirths in British Columbia (BC), Canada, between fiscal years 2008/09 and 2020/21. The data was obtained from the BC Perinatal Database Registry (BCPDR)292, which includes detailed information on maternal demographic characteristics, obstetric history, clinical and behavioral characteristics, pregnancy complications, type of delivery, stillbirth and infant health outcomes. The BCPDR includes >99% of births in BC. Up to 20 diagnoses associated with the delivery hospitalization are captured for each mother (and infant) using the International Classification of Diseases, version 10 codes (ICD-10-CA). I excluded births occurring before 20 weeks or after 44 weeks’ gestation, conceptions caused by non-IVF fertility treatments (e.g. intrauterine inseminations, medically assisted reproductions), and those with missing data on gestational age, plurality, or mode of conception. 55 3.2.2 Twin pregnancy, IVF, HELLP Syndrome and Other Covariates Chart-abstracted and self-reported information about twin and singleton births IVF use was obtained from the BC Perinatal Database Registry (BCPDR). The BCPDR also included information about HELLP syndrome, abstracted directly from the medical charts associated with the delivery and indicated by an ICD-10 code O14.2. Potential confounders included maternal age (<25, >34 years versus 25–34 years), pre-pregnancy body mass index (BMI), gravida (1-3, 4-6, and 7+ pregnancies), nulliparity, chronic diabetes, chronic hypertension, previous caesarean delivery, previous stillbirths, self-reported prior mental illness, substance use, alcohol use, smoking (no smoking, smoking pre-pregnancy, smoking during pregnancy), gestational age at delivery, and fetal sex (sensitivity analysis). Although gravidity and parity were expected to be correlated, there was a large variation in the number of miscarriages in each stratum of parity. Thus, both parity and gravidity contributed independently to the regression model. BMI (kg/m2) was categorized as follows: normal (18.5–24.9), underweight (<18.5), overweight (25.0–29.9), and obesity class 1 (30.0–34.9), class 2 (35.0–39.9), and class 3 (>=40). 3.2.3 Statistical Analysis The exposures of interest included IVF conception and twin pregnancy, and my primary outcome of interest was HELLP syndrome. I calculated the rates of HELLP syndrome with 95% confidence intervals (CI). Rate ratios (RR), rate differences (RD) and 95% CIs were used to assess relative and absolute differences in the rates of HELLPs syndrome between singleton and multiple pregnancies stratified by mode of conception. I used logistic regression models to assess the association between IVF (twin versus singleton) and HELLP syndrome, using adjusted odds ratios 56 (aOR) with 95% CIs. aORs were adjusted for the maternal characteristics mentioned above. Records with missing values for any covariate (<3% in total) were excluded from multivariable analyses, except for BMI, for which missing values (26%) were included as a separate category in the logistic regression. Modification of the associations between plurality and HELLP syndrome by mode of conception was assessed in the regression model in two ways: 1) a subcategory analysis comparing 4 categories (twins with IVF, singletons with IVF, twins with spontaneous conception versus singletons with spontaneous conception as a refence category); and 2) analysis comparing twin versus singleton pregnancy stratified by mode of conception (i.e., twin versus singleton pregnancy within both the IVF conception and spontaneous conception groups). The statistical significance of the interaction between plurality and mode of conception was assessed based on the P-value for the interaction term in the logistic regression models. All analyses were carried out using SAS version 9.4 (SAS Institute, Inc., Cary, NC). Ethics approval was obtained from the University of British Columbia/Children's and Women's Hospital and Health Centre of British Columbia Research Ethics Board (H23-01730). 3.2.4 Sensitivity Analysis Information on twin chorionicity was unavailable in the BCPDR. In sensitivity analyses, I restricted twin pregnancies to those with opposite sex fetuses, as these are always dichorionic, to create a more homogenous group of twin pregnancies across mode of conception strata and assess the effect of chorionicity. 57 3.3 RESULTS 3.3.1 Study Population Overall, 563,705 women had a singleton or twin live birth or stillbirth in British Columbia between 2008/09 to 2020/21. I excluded records with missing data for gestational age, pregnancies delivered at <20 weeks’ and >44 weeks’ gestation, or mode of conception (n=39,838, 7.1%). My study population comprised 523,867 women, of whom 8,337 (1.6%) delivered twins and 515,530 (98.4%) delivered singletons. Overall, 16,707 (3.2%) of women conceived by IVF, while 507,160 (96.8%) conceived spontaneously. The proportion of twin deliveries was 14.7% (2,455/16,707) among women who conceived by IVF, and 1.2% (5,882/507,160) among women with spontaneous conception. Women who conceived by IVF were more likely to be 35 years or older (63.0%) and nulliparous (66.1%). Conversely, the majority of women who conceived spontaneously were between 25-34 years old (61.7%) and more likely to have previously delivered (65.9%). Proportions of women who self-reported prior mental illness, substance use, and smoking prior to or during pregnancy were elevated among mothers who conceived spontaneously relative to those who conceived by IVF (Table 3.1, Appendix B Supplementary Table 3.1). Among women who conceived by IVF, those with a singleton pregnancy were more likely to be younger, multiparous, overweight or obese, more likely to smoke pre-pregnancy or during pregnancy, and more likely to have had a previous stillbirth than their counterparts with twins (Table 3.1). In the spontaneous conception group, women with a singleton pregnancy had a higher proportion of young mothers (<25 years of age), nulliparity and low BMI. Twins were more likely to be delivered at an earlier gestational age, and IVF conceived twins had a higher proportion of opposite-sex twins (Table 3.1). 58 Table 3.1: Maternal and pregnancy characteristics of singleton and twin pregnancies conceived spontaneously and by IVF, British Columbia, Canada, 2008/09-2020/21. Some percentages do not add up because of missing values; missing values <3% are not shown. IVF, in-vitro fertilization; BMI, Body Mass Index. * During pregnancy Maternal and pregnancy characteristics Spontaneous conception IVF conception Singleton Twin Singleton Twin N (501278) % N (5882) % N (14252) % N (2455) % Maternal age <25 years 56251 11.2 522 8.9 220 1.5 6 0.2 25 - 34 years 309270 61.7 3587 61.0 5152 36.0 828 33.7 ≥35 years 135757 27.1 1773 30.1 8908 62.5 1621 66.0 Pre-pregnancy BMI (kg/m2) < 18.5 21527 4.3 187 3.2 476 3.3 67 2.7 18.5 - 24.9 224907 44.9 2338 39.8 6372 44.7 1015 41.3 25.0 - 29.9 83056 16.6 991 16.9 2421 17.0 382 15.6 ≥ 30.0 53964 10.8 715 12.2 1572 11.0 220 9.0 Missing 117824 23.5 1651 28.1 3411 23.9 771 31.4 Gravida 1 - 3 pregnancies 418007 83.4 4676 79.5 12245 85.9 2109 85.9 4-6 pregnancies 72626 14.5 1045 17.8 1760 12.4 301 12.3 7+ pregnancies 9503 1.9 159 2.7 230 1.6 43 1.8 Nullipara 231221 46.1 2607 44.3 9320 65.4 1723 70.2 Chronic diabetes 3190 0.6 36 0.6 129 0.9 26 1.1 Chronic hypertension 3421 0.7 65 1.1 224 1.6 53 2.2 Previous caesarean delivery 79549 15.9 948 16.1 1921 13.5 276 11.2 Previous stillbirths 5022 1.0 86 1.5 168 1.2 23 0.9 Prior mental illness (self-reported) 101957 20.3 1193 20.3 2464 17.3 295 12.0 Substance use* 21674 4.3 251 4.3 189 1.3 18 0.7 Alcohol use* 5613 1.1 51 0.9 64 0.5 <5 0.2 Smoking No 423253 84.4 4876 82.9 13185 92.5 2306 93.9 Pre-pregnancy 34113 6.8 450 7.7 1559 1.1 19 0.8 During pregnancy 43912 8.8 556 9.5 908 6.4 130 5.3 Delivery characteristics Gestational age 20-34 weeks 9216 1.8 1103 18.8 465 3.3 487 19.8 34-36 weeks 32663 6.5 2812 47.8 1249 8.8 1166 47.5 ≥37 weeks 459399 91.7 1967 33.4 12538 88.0 802 32.7 Opposite-sex twins / / 1770 30.1 / / 1116 45.6 59 3.3.2 HELLP Syndrome by Plurality and IVF Overall, rates of HELLP syndrome were higher in IVF versus spontaneous pregnancies (9.3 versus 3.0 per 1000 pregnancies, respectively) (Table 3.2). Rates of HELLP syndrome were higher in twin pregnancies (2.4 per 1000 pregnancies) than in singleton pregnancies (0.3 per 1000 pregnancies). Furthermore, the rate of HELLP syndrome was 2.8 per 1000 among singleton pregnancies and 23.3 per 1000 for twin pregnancies conceived spontaneously, while the same rates were 6.4 versus 26.1 per 1000 for singleton and twin pregnancies conceived by IVF (Table 3.2). The RR expressing the singleton versus. twin relationship with HELLP syndrome differed between spontaneous and IVF pregnancies (RR 8.3 versus 4.1, respectively). However, the RD expressing this relationship were similar (RD 20.5 versus 19.7 per 1000 pregnancies, respectively) (Table 3.3). 3.3.3 Multivariable Analysis Analysis using singletons conceived spontaneously as the reference category showed higher adjusted odds of HELLP syndrome among women with twins conceived spontaneously (aOR= 8.34; 95% CI: 6.98-9.97), singletons conceived by IVF (aOR= 1.64; 95% CI 1.32 – 2.04), and twins conceived by IVF (aOR= 6.27; 95% CI 4.82 – 8.15; Table 3). The stratified analysis (using singleton pregnancy as the reference in each mode of conception category) showed elevated adjusted odds of HELLP syndrome in twins versus singleton pregnancies conceived spontaneously (aOR= 8.34; 95% CI: 6.98-9.97), while this association was weaker in women who conceived by IVF (aOR= 3.83; 95% CI 2.76–5.30; interaction P value <0.001) (Table 3.3). 60 Table 3.2: Rates of HELLP syndrome in singleton and twin pregnancies conceived spontaneously and by IVF, British Columbia, Canada, 2008/09-2020/21. *Per 1000 deliveries IVF, in-vitro fertilization. Conception Mode Number of pregnancies HELLP Syndrome Plurality Number of pregnancies HELLP Syndrome N Rate Per 1000* (95% CI) N Rate Per 1000* (95% CI) Spontaneous 507160 1546 3.0 (2.9-3.2) Singleton 501278 1409 2.8 (2.7-3.0) Twin 5882 137 23.3 (19.4-27.1) IVF 16707 155 9.3 (7.8-10.7) Singleton 14252 91 6.4 (5.1-7.7) Twin 2455 64 26.1 (19.8-32.4) 61 Table 3.3: Multivariable analysis of HELLP syndrome comparing singleton and twin pregnancies conceived spontaneously and by IVF, British Columbia, Canada, 2008/09-2020/21. Singleton spontaneous conception was used as the reference category for the first adjusted odds calculation (aOR1). Singleton spontaneous and singleton IVF conceptions were used as reference categories for comparisons within mode of conception (aOR2). †aORs were adjusted for maternal age (<25, ≥35 years versus 25–34 years), pre-pregnancy BMI categories, gravida (1-3 pregnancies, 4-6 pregnancies, 7+ pregnancies), nulliparity, chronic diabetes, chronic hypertension, previous caesarean delivery, previous stillbirths, self-reported prior mental illness, substance use, alcohol use, and smoking (no smoking, smoking pre-pregnancy, smoking during pregnancy). IVF, in-vitro fertilization; aOR, adjusted odds ratio; CI, confidence interval. Conception Mode Rate Ratio Plurality Rate ratios and rate differences Adjusted Odds Ratios† Rate ratio (95% CI) Rate difference (per 1000) aOR1 (95% CI) aOR2 (95% CI) Spontaneous Ref Singleton Ref. Ref. Ref. Ref. Twin 8.28 (6.97-9.85) 20.5 (16.6-24.3) 8.34 (6.98 – 9.97) 8.34 (6.98 – 9.97) IVF 3.04 (2.58-3.59) Singleton Ref Ref 1.64 (1.32 – 2.04) Ref Twin 4.08 (2.97-5.60) 19.7 (13.2-26.1) 6.27 (4.82 – 8.15) 3.83 (2.76 – 5.30) 62 3.3.4 Sensitivity Analysis Among twins conceived spontaneously, 30.1% were of opposite sex (1770/5882), while among those conceived by IVF, 45.6% were opposite-sex twins (1116/2455; Table 3.1). The results of sensitivity analyses restricted to singleton and opposite sex twin pregnancies were similar to the primary analyses (Appendix B, Supplementary Table 3.2). The RR for HELLP syndrome comparing IVF versus spontaneous pregnancies was slightly lower compared with the primary analysis (RR 2.75, 95% CI 2.29-3.21 versus 3.04 95% CI 2.58-3.59, respectively), though the difference was not statistically significant. 3.4 DISCUSSION 3.4.1 Interpretation My study showed that rates of HELLP syndrome were greater among women with IVF versus spontaneous conception and among women with twin relative to singleton pregnancies. Risk ratios for HELLP syndrome associated with twin pregnancy were larger in women with spontaneous conception than in those with IVF; while the absolute risk differences associated with twinning were similar in both modes of conception. I found an increased risk of HELLP syndrome among twin pregnancies in both IVF and spontaneous conception groups relative to singleton pregnancies. These results are congruent with previous studies showing that the risk of hypertensive disorders increases progressively with the number of fetuses293,294. For instance, a two-fold increase in the incidence of hypertensive disorders of pregnancy was reported in twin pregnancies versus singletons295. Similarly, the rate 63 of preeclampsia was reported to be 2.3% in singleton pregnancies versus rates of 8.1% and 6.0% in dichorionic and monochorionic twin pregnancies, respectively296. My study aligns with contemporary literature that indicates conception via IVF is associated with an elevated risk of adverse pregnancy outcomes, including hypertensive disorders of pregnancy293-298. For instance, Sabr et al. showed that assisted reproductive technology is associated with a 3.8-fold increase in the rates of HELLP syndrome277. However, that study did not differentiate between HELLP syndrome in twin versus singleton pregnancies. My study showed elevated rates of HELLP syndrome in IVF pregnancies relative to spontaneous pregnancies (regardless of plurality), and elevated odds of HELLP syndrome in singleton IVF pregnancies relative to singleton spontaneous pregnancies. However, rates of HELLP syndrome were similar between twin pregnancies conceived spontaneously and by IVF. Some studies have found higher rates of preeclampsia in IVF twin pregnancies compared with twin pregnancies conceived spontaneously292,299-302. From the clinical perspective, HELLP syndrome is a life-threatening condition with an elevated risk of maternal mortality303. My findings show that the rate of HELLP syndrome is about 6- to 8-fold higher in twin pregnancies compared with singleton pregnancies conceived spontaneously. Selective reduction of multifetal pregnancies from triplet to twin or from twin to singleton has been shown to significantly reduce the risk of preeclampsia,304,305 suggesting that selected reduction could also prevent HELLP syndrome (although few such cases have been reported to date).305 As delays in diagnosis have been linked to increased mortality in women with HELLP syndrome306, my findings, which quantify the rates of HELLP in twin pregnancies, underscore the importance of timely recognition of this serious pregnancy complication in twins. 64 3.4.2 Strengths and Limitations The strengths of my study include a population-based design which reduces selection bias relative to hospital-based studies and increases generalizability of my findings to similar populations. The BCPDR database contains a wealth of validated information307 about demographic and clinical characteristics of individual pregnancies enabling a robust adjustment for potential confounders. My study has a few limitations. First, IVF conception was self-reported and thus subject to underreporting. I expect that the degree of underreporting would be similar between singleton and twin pregnancy, as there is no evidence in the current literature to suggest otherwise. Thus, any potential bias would be towards a null association between mode of conception and HELLP syndrome. Second, HELLP syndrome may have been miscoded as severe preeclampsia or eclampsia. However, I expect the frequency of these errors to be small and similar between singleton and twin pregnancies and between the modes of conception. Such potential non-differential misclassification would again bias the results towards null. I did not have information on laboratory values or clinical signs that led to the diagnosis, thus was not able to comment on severity of HELLP syndrome. Third, I did not have information about the chorionicity of twins. Dichorionic twin pregnancies typically have a lower rate of pregnancy complications than monochorionic twins308, which are more common in IVF-conceived versus spontaneously conceived twins309. Differences in chronicity between IVF and spontaneously conceived twins may explain, in part, my findings that the twin-associated risk of HELLP is higher in spontaneous versus IVF pregnancies (adjusted odds ratio 8.3 versus 3.8, respectively). However, my sensitivity analyses showed similar results to general analyses when the twin pregnancy group was restricted to a subgroup of opposite-sex (i.e. dichorionic) twins. Finally, information on some risk factors known to be associated with pregnancy complications and potentially with HELLP syndrome, 65 including socioeconomic factors, race/ethnicity and geographical barriers to health care access, was not available in my data, which could have led to residual confounding. 3.5 CONCLUSION This study quantifies the associations between ART, twin pregnancy and HELLP syndrome, showing that the relative risk of HELLP syndrome associated with twin pregnancy differed between IVF and spontaneously conceived pregnancies. Even though the rates of HELLP syndrome in women with twins were similar between IVF and spontaneously conceived pregnancy, these rates were more than 3-fold higher compared with women with IVF-conceived singleton pregnancy. Women who choose multiple embryo transfer during IVF treatment should be counselled regarding the elevated risks of pregnancy complications. 66 CHAPTER 4: Discussion 4.1 SUMMARY AND SIGNIFICANCE OF FINDINGS I carried out two studies examining the association between IVF and adverse maternal pregnancy outcomes including eclampsia, ICU admission, blood transfusion, and uterine rupture/intrapartum hysterectomy (Chapter 2), and HELLP syndrome (Chapter 3). The objective of this thesis was to understand how IVF affects maternal outcomes and how these effects differ by race/ethnicity or twin pregnancy. Both aims of my thesis were accomplished by conducting two population-based epidemiological studies. For the purposes of this discussion, the term “disparities” is used to describe the difference in the adjusted odds of SMM between racial/ethnic groups (NHB, Asian, Hispanic, mixed-race) and NHW women within one mode-of-conception category. For example, the disparity between the risk of composite SMM for NHB mothers who conceived spontaneously relative to NHW mothers who conceived spontaneously was expressed by aOR= 1.39 (95% CI 1.37 – 1.41) (Table 2.4). “Differences in disparities” describes the difference between the aORs of one race/ethnicity in each mode of conception group. For example, the risk of composite SMM in NHB mothers who conceived by IVF was expressed by aOR= 1.26 (95% CI 1.10 – 1.45) versus the risk in NHB mothers who conceived spontaneously (aOR= 1.39; 95% CI 1.37 – 1.41). The difference in the disparities refers to the difference between these aOR values. Differences in disparities were considered statistically significant if the interaction term in the regression model was statistically significant (p-value <0.05)). Furthermore, HELLP syndrome is critically understudied in the contemporary medical literature. While HELLP and preeclampsia are distinct conditions, they share a very similar 67 underlying pathophysiological mechanism. Preeclampsia is a much larger focus in research today. Thus, for the purposes of this discussion, my findings on HELLP syndrome are frequently compared and contrasted to published findings on preeclampsia. 4.2 INTERPRETATION AND EXPLORATION OF CHAPTER 2: IVF, SMM, AND RACE/ETHNICITY 4.2.1 IVF and Severe Maternal Morbidity In Chapter 2, I demonstrated that use of IVF was associated with an increased risk of SMM, which in my study was as a composite outcome that comprised eclampsia, blood transfusion, uterine rupture/hysterectomy, and ICU admission, in singleton pregnancies. Risk of SMM as a composite outcome increased more than 2-fold in women who conceived via IVF. Eclampsia and ICU admission risk increased 2-fold in women who conceived using IVF, while blood transfusion and intrapartum hysterectomy risk were each associated with a 3-fold or larger increase when conceiving by IVF. Table 2.3 shows aORs of SMM in women who conceived spontaneously or using IVF across all racial/ethnic categories. Similar to my findings, Le Ray et al. reported a significantly greater risk of all-cause SMM and SMM due to hypertensive disorders in women who used IVF171. Le Ray et al conducted a case-control study including six regions in France and comprising 182,309 women from the EPIMOMS multiregional prospective population-based study throughout pregnancy and up to 42 days postpartum171. The exposure of interest was mode of conception and SMM was defined according to the EPIMOMS definition that was derived from a national Delphi formal consensus process171. In their study, multivariable logistic regression analyses were used to compare interaction terms. Martin et al. also found elevated rates of blood transfusion and hysterectomy in 68 singleton pregnancies conceived by IVF310. Martin et. al used data from the Truven Health MarketScan Commercial Claims and Encounters Databases in the United States to conduct a retrospective cohort study of women throughout pregnancy and 42 days postpartum310. The exposure of interest was also mode of conception and diagnoses of SMM outcomes identified from the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) diagnosis and procedure codes and Current Procedural Terminology (CPT) codes310. In their study, multivariable logistic regression was used to model the interaction between exposure, outcome, and covariates. In my study, blood transfusions accounted for a large proportion of SMM cases in my study and significantly contributed to the observed differences in risk of SMM between modes of conception. The phenomenon of blood transfusion constituting a large proportion of all SMM cases has been reported previously, as recent studies have delineated the difficulty in validating blood transfusion as indicative of severe morbidity159,189,311-313. While transfusion information is available, it often lacks the details on quantity of units transfused and the reason for transfusion159,312. Thus, transfusions administered to avoid significant morbidity or mortality may be conflated with those administered in normal deliveries to prevent any morbidities. Main et al. identified that only 26% of deliveries with transfusions of blood or blood components could be considered as SMM – the remaining 74% were relatively low-risk deliveries313. Indeed, a CPSS report demonstrated that the rate of overall transfusions was significantly greater than the rate of transfusions associated with any comorbidity and the rate of transfusions associated with postpartum haemorrhage specifically (786.6 versus 565.3 versus 483.9 per 100,000 births, respectively)311. Thus, the interpretation of my results with respect to SMM and blood transfusion 69 requires caution as I did not have information about the reasons for transfusion or the quantity of blood transfused. Additionally, I observed an increased risk of eclampsia and uterine rupture/intrapartum hysterectomy in women who conceived via IVF (Table 2.2, Table 2.3, Table 2.4). Studies directly assessing the association between IVF and eclampsia are scarce. Available evidence suggests that risk of preeclampsia and associated sequelae are greater in IVF-conceived pregnancies300,314. My research focused on the incidence of HELLP syndrome (which is associated with preeclampsia) in IVF-conceived pregnancies (Chapter 3), which has not been reported previously. Uterine rupture is a very rare SMM outcome that presents more frequently in women who conceived via IVF315. A major risk factor for uterine rupture is a prior caesarean delivery, and the risks increases further with more than one prior caesarean316. Information on trial of labour after caesarean (the process of attempting vaginal delivery after a previous caesarean delivery) was not available in the data and we were not able to control for it. The rate of uterine rupture/peripartum hysterectomy in my study was 0.7 per 1000 births for spontaneous conceptions and 2.3 per 1000 births for IVF conceptions in all US singleton births from 2016 to 2021. Interestingly, my results consistently showed more than a 3-fold higher risk of uterine rupture/intrapartum hysterectomy in IVF-conceived pregnancies even when adjusted for prior caesarean delivery (Appendix A, Supplementary Table 2.2). More research is needed to fully elucidate the association between IVF and uterine rupture/intrapartum hysterectomy as the reasons for rupture and/or intrapartum hysterectomy may differ in women by mode of conception. 70 4.2.2 Severe Maternal Morbidity and Race/Ethnicity In Chapter 2, I showed that NHB and mixed-race women had a greater risk of SMM (defined as composite SMM, or the individual components of eclampsia, blood transfusion, uterine rupture/hysterectomy or ICU admission) than NHW women, whether conceiving naturally or via IVF (Table 2.4). IVF was associated with increased risk of SMM in all racial/ethnic groups. Hispanic women had slightly lower adjusted odds of SMM relative to NHW women, and Asian women had slightly higher or similar risk relative to NHW women in both mode of conception categories. Differences in the disparities of each outcome between racial/ethnic groups and NHW women were mostly not statistically significant. However, I did find a significantly increased risk of uterine rupture/intrapartum hysterectomy when conceiving by IVF in Hispanic and NHB versus NHW women. Additionally, I reported significantly increased risk in ICU admission among Asian versus NHW women in the when conceiving by IVF. Lisonkova et al. (2022) assessed fetal/infant outcomes and found larger racial/ethnic disparities in women who conceived by ART than by spontaneous conception, stating: “neonatal mortality was twofold higher among infants of non-Hispanic Black versus non-Hispanic White women in the spontaneous-conception group (aRR= 1.9, 95% CI: 1.8–1.9), whereas in the ART-conception group, neonatal mortality was more than fourfold higher in infants of non-Hispanic Black women (aRR= 4.1, 95% CI: 2.9–5.9)”227. Building upon this report, my findings about racial/ethnic differences in SMM by mode of conception add to the literature on this important issue. The association between Hispanic ethnicity and SMM is contested in the contemporary literature. A population-based study in New York City showed that risk of SMM was greater (odds ratio 1.42, 95% CI 1.22 – 1.66) among Latina women than in NHW women317. A similar study also reported a 1.8-fold greater risk for SMM in Hispanic versus NHW mothers318. In contrast, my study showed that the risk of composite SMM was lower in Hispanic than in NHW mothers (Table 71 2.4). A population-based retrospective cohort study by Liese et al. (2019) using national data found that Hispanic women had a 19% lower risk of SMM than White women319. Furthermore, it is possible that Hispanic women are less likely to have accessible, affordable care and more likely to have lower SES than NHW in New York City specifically, which could have contributed to the disparity between New York-specific data and my findings that included all US births at a population-level317,318. The Hispanic paradox, an epidemiological phenomenon wherein Hispanic women have lower rates of adverse pregnancy outcomes despite greater exposure to risk factors, could also be a contributing explanatory factor for my findings320. Researchers posit that intergenerational teaching of healthy pregnancy habits and strong sociocultural community support networks contribute to better health outcomes for Hispanic mothers which underlie the Hispanic paradox321,322. Notably, my study did find that among those who conceived by IVF, Hispanic versus NHW women had a higher relative risk of uterine rupture/intrapartum hysterectomy compared with the relative risk in Hispanic versus NHW women who conceived spontaneously (Table 2.4). To my knowledge, this is a novel finding, and my results should be replicated in future studies to confirm this finding. NHB race and its association with adverse health outcomes is well-documented232,234,255,257,323,324. NHB race in the US is associated with lower SES, greater exposure to risk factors for adverse health outcomes, and/or less access to quality medical care compared with Asian, AIAN, PI, Hispanic and NHW groups in the US232,234,257. Prior literature shows that NHB mothers are more likely to experience preterm delivery and hypertension in pregnancy, have more barriers to obstetric care, and are more likely to experience long-term morbidities or die from pregnancy-related complications than White women255,257,323. My study found that NHB mothers had the highest risk for ICU admission, blood transfusion, and uterine rupture/intrapartum 72 hysterectomy in both mode of conception categories (Table 2.4). My findings align with previous literature showing elevated risk of blood transfusions, eclampsia, and ICU admission in NHB relative to NHW women314,325-327. My descriptive analysis of maternal demographic characteristics showed that NHB mothers had higher proportion of low maternal education than NHW women (whether they conceive naturally or by IVF), which indicates disparities in SES. One retrospective multi-centre cohort study in the US found that NHB women were less likely to experience uterine rupture324. My study showed similar results, however, only among women who conceived spontaneously; in women who conceived via IVF, NHB women were more likely to experience uterine rupture than NHW women (Table 2.4). Previous studies support my findings which showed that the proportion of women with previous caesarean delivery, a major risk factor for uterine rupture, is larger in NHB mothers328-331. However, these results are new and exploratory, and need to be replicated in other populations to rule out a chance finding. Asian race had varying association with SMM components. In the IVF conception group, Asian women had lower odds for blood transfusion and eclampsia, similar odds for overall SMM, and greater odds for ICU admission and uterine rupture/intrapartum hysterectomy relative to NHW women (Table 2.4). In contrast, in the spontaneous conception group, a significantly smaller Asian-NHW disparity was observed in the odds of ICU admission (Table 2.4). All other disparities were relatively similar in the IVF and spontaneous conception groups. In contrast to my findings, other studies have reported that adjusted risk of SMM among Asian women was greater than in NHW women222,278. However, these studies included PI in the race/ethnicity category ‘Asian’, whereas I considered both as distinct groups, which could have contributed to these differences in findings. One previous retrospective cohort study found that Asian women face elevated risk of SMM-associated ICU admission relative to NHW332. Igbinosa et al. (2023) found that Asian women have 73 higher risk of blood transfusion than White women333. Their study used California state-level data, while my study used US national population-level data. This difference in study populations could account for a discordance between results333. The medical literature also reports diverse results for rates of preeclampsia in Asian women: Minhas et al. (2021) found that risk of preeclampsia/eclampsia was greater in Asian women than in other racial/ethnic groups334; while Nakagawa et al. (2016) reported that Chinese women had lower risk of preeclampsia relative to NHW women335. I observed that Asian women had a higher rate of chronic diabetes relative to NHW women (Table 2.1), which has been linked to the development of preeclampsia336. However, after adjustment, Asian women did not have higher rates of eclampsia relative to NHW women. More research investigating adverse maternal outcomes specifically in Asian-American women are necessary to further elucidate pregnancy-associated risks in this group. Mixed-race ethnicity is a self-reported race/ethnicity category that includes two or more of NHW, NHB, Hispanic, Asian, AIAN, PI or other races/ethnicities. In Chapter 2, I reported that mixed-race women had the highest adjusted risk of the composite SMM among all racial/ethnic categories (Table 2.4). Mixed-race ethnicity mothers had elevated odds of ICU admission, blood transfusion, eclampsia, and uterine rupture/intrapartum hysterectomy relative to NHW women in both conception groups. Mixed-race ethnicity is currently understudied. A recent study (2020) showed that mixed-race mothers had elevated risk of SMM relative to NHW women337, which aligns with my findings. Similarly, a previous study found that women who identified with more than one race/ethnicity had higher risk of blood transfusion than White women332. There were no significantly different disparities in SMM components in mixed-race versus NHW women between spontaneous and IVF conception groups in my study. However, those with mixed-race 74 had much higher adjusted odds of eclampsia compared with NHW women in both conception groups (Table 2.4), which warrants further investigation. AIAN and PI women were the smallest racial/ethnic groups in my study population (Appendix A, Supplementary Table 2.1). I was unable to conduct multivariable analyses of SMM and its components including AIAN and PI women due to low rates of IVF use in these two groups and therefore low absolute numbers of women. However, the available data among those with spontaneous conception were large enough to show that the rates of SMM and its components were the highest in AIAN and PI women than the other races/ethnicities. I found a notable 5-fold higher rate of eclampsia in PI women compared to the average rate in women (of all races/ethnicities) with spontaneous conception (Table 2.2). The current literature shows an elevated risk of SMM in both AIAN and PI women compared with NHW women, though these studies do not differentiate by mode of conception278,332,338. SMM risk among AIAN women is particularly elevated in rural communities338. Rural communities in the US often have a higher prevalence of risk factors and reduced access to quality health services261,262,266. The breakdown of traditional birthing practices and support networks, racism and discrimination from healthcare workers, the lack of cultural context in care provided, and physical barriers (i.e., distance to perinatal resources, availability of transport, etc.) have been cited as significant barriers to care for expectant Indigenous mothers339-343. According to the WHO, PI nations constitute 9 out of 10 countries with the highest obesity rates344. PI women have high rates of pre-pregnancy and gestational diabetes345,346; and these morbidities are significant risk factors for development of SMM347. More in-depth analyses of mode of conception and severe maternal outcomes are necessary to understand these associations within AIAN an PI groups. 75 4.2.3 Race/Ethnicity and IVF In Chapter 2, I showed that IVF conception had a stronger impact on risk of developing SMM than race/ethnicity. The association between IVF and SMM is well-described in the literature170-173. There was also an association between race/ethnicity and IVF, which was not a focus of this study. My data showed that Asian and NHW women comprised the largest proportion of IVF users (Appendix A, Supplementary Table 2.1). NHW and Asian women are more likely to have higher SES358, and therefore more likely to afford the costs of IVF. An IVF cycle costs between $12,000 and $25,000, with a national average cost of $18,865 to give birth348,349. Indeed, rates of IVF use are reported to be lower in AIAN, NHB, and Hispanic groups350,351. Rates of IVF use in PI women, considered as a distinct group from Asian race/ethnicity, have not been reported in the literature. In my study, only 0.12% of AIAN and 0.06% of PI mothers conceived using IVF (Appendix A, Supplementary Table 2.1), and I was unable to include them in multivariable analyses of SMM. Lack of affordability and accessibility (including finding a physician, taking leave from work, communication/language limitations) have been factors reportedly responsible for lower IVF use rates among NHB and Hispanic women in the US352. NHB women are reported to have lower live birth rates when using IVF relative to NHW women353. Low live birth rates among Asian mothers following ART have also been reported353,354. Despite often belonging to a higher SES, which is associated with better birth outcomes, Asian women seeking infertility treatment tend to be older, which can reduce success of the IVF therapy254,255,355. However, the mechanism underlying lower live birth rates in Asian women relative to their NHW counterparts remains largely unexplained356. 76 4.3 INTERPRETATION AND EXPLORATION OF CHAPTER 3: IVF, HELLP SYNDROME, AND TWIN GESTATION 4.3.1 HELLP Syndrome and Twin Pregnancy In Chapter 3, I described the association between IFV conception, twin pregnancy, and an increased risk of HELLP syndrome. The risk of HELLP syndrome was greater among twin pregnancies than in singletons regardless of mode of conception (Table 3.3). This finding is consistent with current literature which states that preeclampsia is more frequent and more likely to progress to severe complications in multifetal pregnancies298,301,357. Studies report that preeclampsia occurs and progresses to more severe complications earlier in twin pregnancies298,358. One hypothesis regarding why hypertensive disorders are more common in multifetal pregnancies is that placental mass is increased in twin pregnancies and shallow placentation, the pathophysiology which underlies HELLP syndrome and preeclampsia, is more common359. This phenomenon potentially leads to more severe endothelial damage which stimulates the development of preeclampsia and its severe forms359. 4.3.2 IVF and HELLP Syndrome In Chapter 3, I also demonstrated an association between IVF and HELLP syndrome, in singleton and twin pregnancies. Overall, women who conceived by IVF had a 3-fold increase in the rate of HELLP syndrome relative to women who conceived spontaneously (Table 3.2). This association has been described in the literature309,310,359,360. A retrospective cohort study found that women who experienced preeclampsia were 2-fold more likely to have conceived via ART (5-fold more likely to have used IVF), compared with women who conceived spontaneously300. A case-control study by Calhoun et al. (2011) analysed the association between IVF and preeclampsia. They found that 77 in an American population of 1,031 of whom 440 had preeclampsia, women who conceived by IVF were more likely to experience HELLP syndrome and severe hypertensive complications than those who conceived spontaneously359. Indeed, several studies have indicated that IVF is associated with increased risk of preeclampsia and its progression to more severe complications including eclampsia and stroke300,301. Preeclampsia in twin pregnancies conceived by IVF is also known to be highly associated with preterm delivery, caesarean delivery, and low birth weight361. One of the novel findings in my thesis is the differential association between HELLP syndrome in singleton versus twin pregnancy in women with IVF conception and those with spontaneous conception. While the rates of HELLP syndrome were much higher in women with singletons conceived by IVF compared with spontaneous conception, the adjusted odds risk of HELLP syndrome was higher in twins conceived spontaneously than those conceived by IVF (Table 3.3). Previous studies have indicated higher risk of preeclampsia or HELLP syndrome in twin pregnancies conceived by IVF than twin pregnancies conceived spontaneously306,311, which contrasts with my findings. Francisco et al. proposed that preeclampsia incidence is underestimated in twin pregnancies due to the elevated rate of preterm delivery among this population,358 as incidence of preeclampsia increases with gestational age362. I also observed a higher rate of preterm delivery between 20-34 weeks among IVF-conceived twins compared with spontaneously conceived twins, as described in the literature363,364. If these pregnancies had been allowed to progress, HELLP syndrome would have occurred at later gestation and the incidence of HELLP syndrome in twin pregnancies conceived by IVF would be therefore have been higher. I also hypothesize that mothers who conceived by IVF may have had a healthier lifestyle and a lower prevalence of behavioural risk factors365-367 for preeclampsia. I found that the frequency of substance use, alcohol use, and previous caesarean delivery were lower in women who conceived 78 via IVF in general, and also in IVF-conceived twin pregnancies (Table 3.1). IVF patients can opt for pre-implantation genetic testing (PGT) to reduce likelihood of transferring genetically abnormal embryos. Studies have shown that PGT also reduces risk of other adverse pregnancy outcomes, which could potentially explain the reduced risk of preeclampsia and HELLP syndrome in twins conceived by IVF368-372. However, this theory does not account for greater HELLP syndrome risk in singleton IVF pregnancies relative to singleton spontaneous pregnancies. My finding that twin pregnancies conceived by IVF are at a lower risk of HELLP syndrome than spontaneously conceived twins is novel and evokes more questions about the pathophysiology of HELLP syndrome in IVF conceptions and in twin pregnancy. More research is necessary to delineate the mechanisms behind this association. 4.4 STRENGTHS AND LIMITATIONS My thesis has several strengths. First, I aimed to assess the association between IVF and adverse maternal pregnancy outcomes with datasets well-suited to the study designs. By using data from Canada and the US I was able to complement strengths and limitations of each dataset. Both of my studies are population-based at the provincial or national levels. Using population-based data reduces selection bias, increases statistical power, and provides information on provincial or country-level prevalence or incidence rates. A large population size (e.g., all births in the US) was especially important because some SMM outcomes and HELLP syndrome are very rare and require a large sample size to conduct statistical analyses. Population-level data also increases the generalisability of findings to similar populations (e.g. the US and Canada) and provide descriptive information on the prevalence of important maternal and pregnancy characteristics. I had detailed information on a relatively large number of potential confounders, including maternal education, 79 body-mass-index, pre-pregnancy chronic conditions, obstetric history, smoking, alcohol, and substance use during pregnancy, among others. US data included detailed information on race/ethnicity, which is an important predictor of SMM. Using self-reported and chart-abstracted live birth and fetal death certificate data (rather than hospitalisation records) allowed me to include deliveries occurring at home or birthing centres, which adds to the completeness of the study population and further mitigates selection bias. My thesis has some limitations. Maternal and pregnancy demographic characteristics were partially self-reported in both studies, and thus subject to recall bias. HELLP syndrome was abstracted from physician’s notes in medical charts (as a diagnosis during delivery hospitalization). However, details regarding severity of HELLP syndrome were not available in my data sources. Underreporting of specific risk factors is also a potential consideration as patients may be less likely to admit smoking and substance or alcohol use to preserve a positive image in the eyes of healthcare providers; therefore, behaviours and factors that are perceived negatively are potentially underreported. IVF use was also self-reported, introducing an element of potential underreporting. This underreporting is likely to have been similar across mode of conception and racial/ethnic groups, although Thoma et al. suggest some differential underreporting of IVF treatments in birth certificate data373. If the misclassification is non-differential, the bias is typically towards null. However, differential misclassification can result in bias in either direction. Some degree of misclassification of HELLP syndrome as severe preeclampsia or other severe morbidity is also possible. I expect, however, that the extent of this misclassification would be similar between twin and singleton pregnancies. In addition, the BCPDR data lacked information about dichorionic versus monochorionic twins, which could differentially influence the risks of adverse pregnancy outcomes. I circumvented this problem in a sensitivity analysis by 80 restricting twins in the study population to opposite-sex twins only, thus including dichorionic twins only. The sensitivity analysis yielded results similar to the primary analyses (of all twins), ruling out the hypothesis that differences in chorionicity are responsible for the unexpected findings with respect to IVF versus spontaneously conceived twins. Maternal SES and race/ethnicity information was not available in the BC data, and I was thus unable to adjust for these factors, possibly resulting in residual confounding. Data sources for both of my studies were very different, and direct comparisons between datasets and combining was not possible. For instance, NCHS data included records for each birth, but did not contain information to link twin births and identify twin pregnancies, while BCPDR data did not contain information regarding race/ethnicity. The race/ethnicity categories analysed in Chapter 2 were determined based on an NCHS algorithm for US Vital Statistics data. Race/ethnicity information was self-reported, and categories were determined by the NCHS algorithm analysing information on overall geographical prevalence of various race/ethnicity groups. This list was not exhaustively inclusive of all races/ethnicities occurring in the US. For instance, Middle Eastern ethnicity was not represented as a distinct category, and I was thus unable to conduct analyses on this subgroup. Additionally, data on other SMM components (e.g., shock, embolism) and information on severity of SMM components were lacking. Underreporting and/or misclassification of SMM components (e.g., reporting only ICU admission without reporting the causative eclampsia) is also expected. I assumed such underreporting would be similar across the race/ethnicity categories; however, a recent study by Gemmill et al. (2024) showed that blood transfusion, eclampsia, hysterectomy, and uterine rupture were underreported in birth certificate data when compared with hospitalisation records374. The underreporting was differential by race/ethnicity, specifically between NHB and White mothers374. Non-differential underreporting 81 would have possibly biased my findings towards a null association; however, differential underreporting may bias the results in either direction, if this underreporting is also differential by mode of conception. 4.5 FUTURE DIRECTIONS Future research should study SMM using more detailed data sources. For instance, datasets that link pregnancy, delivery, post-delivery hospitalisation, physician visit, and birth records would facilitate a more direct tracking of maternal and fetal outcomes in the antenatal, delivery, and postpartum periods. Comprehensive datasets are also important in racial/ethnic comparisons wherein outcomes and exposures may both be differentially underreported in some data sources. Data combined and linked from multiple sources could provide more accurate findings regarding the influence of social determinants of health. The NCHS list of race/ethnicity categories is not comprehensive and conflates some racial/ethnic groups. Many studies of racial/ethnic disparities in birth outcomes group PI and Asian women together278,375. In my study, Asian women and PI women constituted 6% and 0.2% of the total population, respectively. Thus, differences in the incidence of adverse birth outcomes between PI and Asian women may not be recognised in studies which conflate these groups. My thesis shows that PI and Asian mothers have different rates of IVF use and different rates of SMM composite outcome and individual outcomes, indicating a need to consider these groups separately. Additionally, other small specific racial/ethnic subgroups within larger race/ethnicity categories were not represented in the data. Research suggests various Asian subgroups differ in risk factors and health outcomes376,377. For instance, Nakagawa et al. (2016) reported that Filipino women have 82 a higher risk of preeclampsia than Native Hawaiians, and a higher prevalence of chronic diabetes than Chinese women376. Native Hawaiian mothers had also more than a 3-fold higher rate of obesity compared to Filipino women and a 7-fold higher rate relative to Chinese and Japanese women376. Incidence of maternal ‘near miss’, which is defined as “a woman who nearly died but survived a complication that occurred during pregnancy, childbirth or within 42 days of termination of pregnancy”378, was found to be higher in Korea than in China, yet higher in China compared with Pakistan377. Furthermore, women of Middle Eastern ethnicity would be considered as ‘Asian race’ in studies using NCHS classification and not distinctly represented in research, including my study. Recent estimates suggest that people of Middle East origin comprise approximately 1% of the US population379. AIAN women, who are included in the US data as a separate category, represent an estimated 1.1% of the US population380. Rates of female infertility are estimated to be high in the Middle East and North Africa relative to the rest of the world381,382. Genetic factors, increased exposure to air pollutants and endocrine disrupting chemicals, and obesity are credited as factors that contribute to elevated prevalence of PCOS and infertility observed in this population381. Thus, there is a compelling reason to include more specific racial/ethnic categories in future studies of US births. Women from smaller race/ethnicity groups may have elevated risks of adverse outcomes which remain undetected when these small groups are included in larger race/ethnicity categories. These considerations can be implemented in future maternal health research to provide more inclusive and representative perspective. The definition of SMM as a composite outcome, as well its individual components, varies across medical literature382. According to the American CDC, SMM is defined as “the occurrence of at least one of a possible total of 21 indicators, consisting of 16 diagnostic codes and six procedural codes during the postnatal hospital stay”382-385. According to a frequently adopted 83 European definition, SMM is diagnosed as one or more of five conditions, including: ICU admission, uterine rupture, blood transfusion, eclampsia, and other adverse maternal outcomes the physician deems to be SMM386. While these definitions overlap, their idiosyncrasies can create difficulty in establishing a global approach to SMM. Creating a universal definition of SMM that would be used by all clinicians and researchers would improve maternal monitoring and knowledge sharing between countries and ultimately ameliorate maternal health outcomes worldwide. The purpose of this thesis and the body of research to which it belongs is to ameliorate maternal health outcomes and prevent severe morbidity in pregnancy. The changes necessary to accomplish these goals must occur at the individual, community, and institutional levels. Individual behavioural changes can be facilitated by educating women regarding the risks associated with assisted conception, twin pregnancy and other factors related to lifestyle so that women can make informed decisions regarding their health. Encouraging healthy diets and exercise for current and prospective mothers can reduce exposure to risk factors (e.g., obesity) for adverse health outcomes. At the community level, encouraging community building and support networks during pregnancy and in the postpartum period can reduce maternal stress and improve health outcomes387,388. Empowering patients to discuss their concerns with healthcare providers, and educating physicians to deliver care in a culturally sensitive and supportive manner can improve trust in the healthcare system and reduce maternal stress. At the systemic level, equitable access to healthcare for all mothers must be prioritised. Frequency of antenatal checkups is directly associated with healthy maternal and fetal outcomes254. Low SES and rural residence are associated with barriers to adequate perinatal care, and both of these factors are disproportionately prevalent in NHB, AIAN, and Hispanic women relative to NHW women253,255,262,263,266,389. Studies 84 suggest that improving accessibility (including affordability) of transportation to healthcare facilities can improve birth outcomes390. Instituting culturally sensitive and competent clinical care policies and reforming medical education to reduce implicit biases would contribute to long-term improvements in maternal care. 85 CHAPTER 5: Conclusion 5.1 CONCLUSION Together, these studies present novel findings in the field of perinatal epidemiology, fertility treatment and obstetrics. After exploring these associations, I infer that social determinants of health and pregnancy characteristics both significantly interact with IVF to influence maternal health outcomes. I found that IVF is more strongly associated with SMM than race/ethnicity, and that twin pregnancy is a stronger risk factor for HELLP syndrome than IVF. I recognise and acknowledge the pervasive nature of racial disparities in birth outcomes in the US and hope that my thesis will contribute to efforts to improve maternal health outcomes in ethnic minorities. Ultimately, my thesis provides a significant step towards a more complete understanding of the effects of IVF conception on maternal health outcomes. Improvements to data collection and establishing a consensus-based common definition of SMM are warranted to enhance maternal health research in the future. 86 REFERENCES 1. Centers for Disease Control and Prevention. Infertility. CDC. Published April 26, 2023. Accessed February 13, 2024. https://www.cdc.gov/reproductivehealth/infertility/index.htm 2. World Health Organisation. Infertility Prevalence Estimates, 1990–2021. Vol 1. 1st ed. World Health Organisation; 2023. Accessed February 13, 2024. https://www.who.int/publications/i/item/978920068315 3. Wang H, Abbas KM, Abbasifard M, et al. 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Characteristics Mode of Conception IVF Spontaneous N % N % Maternal Age (years) Less than 25 1413 0.77 5242998 24.50 25-34 73527 40.03 12384769 57.87 ≥ 35 108722 59.2 3773586 17.63 Nullipara 109656 59.77 8200640 38.38 Maternal Education ≤ Primary education 1838 1.0 2716721 12.62 ≥ Secondary education 179757 98.05 18490323 86.49 BMI (kg/m2) < 18.5 4100 2.23 658066 3.07 18.5 - 24.9 89900 48.95 8717384 40.73 25.0 - 29.9 47252 25.73 5594887 26.14 ≥ 30.0 39612 21.57 5948758 27.80 Prior Caesarean delivery No 156246 85.07 181371727 84.56 1-2 deliveries 26467 14.41 3023491 14.13 ≥3 deliveries 931 0.51 275322 1.29 Chronic Hypertension Yes 6445 3.51 459638 2.15 No 177217 96.49 2094175 97.85 Pre-existing Diabetes Yes 2136 1.16 209823 0.98 No 181526 98.84 21191530 99.02 Smoking Yes 664 0.36 1332453 6.23 No 181088 98.6 19894959 92.96 Gestational Age (weeks) 20-33 7133 3.88 518047 2.42 34-36 15192 8.27 1328376 6.21 ≥37 161337 87.84 19550000 91.37 Fetal Sex Female 89813 48.9 104549642 48.83 Male 93849 51.1 10951711 51.17 Race Non-Hispanic White 127982 69.68 11026866 51.52 Non-Hispanic Black 9535 5.19 3136203 14.65 AIAN 228 0.12 167240 0.78 Asian 26383 14.36 1340969 6.27 PI 104 0.06 55826 0.26 Hispanic 16224 8.83 5193972 24.27 Mixed-Race 3206 1.75 480277 2.24 IVF, in-vitro fertilization; AIAN, American Indian and Alaska Native; PI, Pacific Islander; BMI, Body Mass Index. 144 Supplementary Table 2.2: Adjusted odds ratios showing modification of the association between race/ethnicity and severe maternal morbidity by mode of conception, singleton deliveries, United States, 2016-2021. Conception Mode Race/Ethnicity SMM ICU Admission Blood Transfusion Eclampsia Uterine Rupture/Hysterectomy aOR† 95% CI aOR 95% CI aOR 95% CI aOR 95% CI aOR 95% CI Spontaneous Non-Hispanic White Ref Ref Ref Ref Ref Ref Ref Ref Ref Ref Non-Hispanic Black 1.38 1.36 - 1.40 1.75 1.70 - 1.81 1.30 1.27 - 1.32 1.31 1.28 - 1.34 1.32 1.26 - 1.38 Asian 1.05 1.03 - 1.07 1.37 1.31 - 1.43 0.95 0.92 - 0.98 1.09 1.05 - 1.13 1.19 1.12 - 1.28 Hispanic 0.98 0.97 - 1.00 1.20 1.17 - 1.24 1.04 1.02 - 1.06 0.83 0.81 - 0.85 0.97 0.93 - 1.02 Mixed-Race 1.43 1.39 - 1.47 1.24 1.15 - 1.33 1.03 0.99 - 1.09 2.07 1.99 - 2.16 1.05 0.94 - 1.18 IVF Non-Hispanic White Ref Ref Ref Ref Ref Ref Ref Ref Ref Ref Non-Hispanic Black 1.26 1.10 - 1.44 1.74 1.33 - 2.29 1.31 1.10 - 1.55 1.12 0.83 - 1.52 2.02 1.43 - 2.85 Asian 1.01 0.92 - 1.12 1.67 1.38 - 2.03 0.93 0.82 - 1.06 0.87 0.68 - 1.12 1.34 1.02 - 1.76 Hispanic 0.91 0.80 - 1.04 1.22 0.94 - 1.60 0.90 0.77 - 1.05 0.85 1.15 - 2.83 1.49 1.09 - 2.03 Mixed-Race 1.37 1.09 - 1.73 1.64 1.01 - 2.67 1.24 0.92 - 1.66 1.80 0.63 – 1.14 0.81 0.33 - 1.96 NHW spontaneous and NHW IVF were used as reference categories. †aORs were adjusted for maternal demographic and pregnancy characteristics, including pre-pregnancy BMI, smoking during pregnancy, nulliparity, parity (parity 1–3, parity ≥4), prior caesarean delivery (0 versus ≥1), age (<25, >34 years versus 25–34 years), education (high school or higher versus less than high school), prenatal care (no prenatal care versus some prenatal care), previous fetal death or termination of pregnancy, previous infant death, and fetal sex (male versus female). American Indian and Alaska Native and Pacific Islander were excluded from the multivariable analysis due to small numbers. SMM, severe maternal morbidity; ICU, intensive care unit; IVF, in-vitro fertilization; aOR, adjusted odds ratio; CI, confidence interval; NHW, non-Hispanic White; NHB, non-Hispanic Black. Bolded text = indicates statistically significant differences in aOR in spontaneous versus IVF conception group, i.e., a statistically significant interaction. 145 APPENDIX B: Supplemental Information for Chapter 3 Supplementary Table 3.1: Maternal and pregnancy characteristics of women who conceived spontaneously and by IVF, British Columbia, Canada, 2008/09-2020/21. IVF, in-vitro fertilization; BMI, body mass index. Maternal and pregnancy characteristics Spontaneous conception IVF conception N = 507160 % N = 16707 % Maternal age <25 years 56773 11.2 226 1.4 25 - 34 years 312857 61.7 5952 35.6 ≥35 years 137530 27.1 10529 63.0 Pre-pregnancy BMI (kg/m2) < 18.5 21714 4.3 543 3.3 18.5 - 24.9 227245 44.8 7387 44.2 25.0 - 29.9 84047 16.6 2803 16.8 ≥ 30.0 54679 10.8 1792 10.7 Missing 119475 23.6 4182 25.0 Gravida 1 - 3 pregnancies 422683 83.3 14354 85.9 4-6 pregnancies 73671 14.5 2061 12.3 7+ pregnancies 9662 1.9 2061 1.6 Nullipara 233828 46.1 11043 66.1 Chronic diabetes 3226 0.6 155 0.9 Chronic hypertension 3486 0.7 277 1.7 Previous stillbirths 5108 1.0 191 1.1 Previous caesarean delivery 80497 15.9 2197 13.2 Prior mental illness (self-reported) 103150 20.3 2759 16.5 Substance use 21925 4.3 207 1.2 Alcohol use 5664 1.1 68 0.4 Smoking No 428129 84.4 15491 92.7 Pre-pregnancy 34563 6.8 178 1.1 During pregnancy 44468 8.8 1038 6.2 Gestational age 20-34 weeks 10319 2.0 952 5.7 34-36 weeks 35475 7.0 2415 14.5 ≥37 weeks 461366 91.0 13340 79.9 Plurality Singleton 501278 98.8 14252 85.3 Twin 5882 1.2 2455 14.7 Hypertensive disorders of pregnancy HELLP syndrome 1546 0.3 155 0.93 Severe preeclampsia 980 0.19 115 0.69 Eclampsia 35 0.01 <5 0.06-0.24 146 Supplementary Table 3.2: Sensitivity analyses of HELLP syndrome comparing singleton and opposite-sex twin pregnancies conceived spontaneously and by IVF, British Columbia, Canada, 2008/09-2020/21. Singleton spontaneous conception was used as the reference category for the first adjusted odds calculation (aOR1). Singleton spontaneous and singleton IVF conceptions were used as reference categories for comparisons within mode of conception (aOR2). †aORs were adjusted for maternal age (<25, ≥35 years versus 25–34 years), pre-pregnancy BMI categories, gravida (1-3 pregnancies, 4-6 pregnancies, 7+ pregnancies), nulliparity, chronic diabetes, chronic hypertension, previous caesarean delivery, previous stillbirths, self-reported prior mental illness, substance use, alcohol use, and smoking (no smoking, smoking pre-pregnancy, smoking during pregnancy). IVF, in-vitro fertilization; aOR, adjusted odds ratio; CI, confidence interval. Conception Mode N HELLP syndrome (N) Rate per 1000 (95% CI) Rate Ratio (95% CI) Plurality N HELLP syndrome (N) Rate per 1000 (95% CI) Adjusted Odds Ratio aOR1 (95% CI) aOR2 (95% CI) Spontaneous 503048 1450 2.9 (2.7-3.0) Ref Singleton 501278 1409 2.8 (2.7-3.0) Ref. Ref. Twin* 1770 41 23.2 (16.1-30.2) 8.33 (6.07 - 11.43) 8.33 (6.07 - 11.43) IVF 15368 122 7.9 (7.5-9.3) 2.75 (2.29-3.31) Singleton 14252 91 6.4 (5.1-7.7) 1.61 (1.29 - 2.00) Ref Twin* 1116 31 27.8 (18.1-37.4) 6.20 (4.27 - 9.01) 3.86 (2.53 - 5.87)
Thesis/Dissertation
eng
Women+ and Children’s Health Sciences
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Lisonkova, Sarka
Examining the association between in-vitro fertilization and severe maternal morbidity in the United States and Canada
Text