Open Collections

UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

Small for gestational age trends in Canada from 2000-2016 : an analysis of individual-level factors and… El Adam , Shiraz 2018

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata

Download

Media
24-ubc_2018_february_eladam_shiraz.pdf [ 1.6MB ]
Metadata
JSON: 24-1.0376031.json
JSON-LD: 24-1.0376031-ld.json
RDF/XML (Pretty): 24-1.0376031-rdf.xml
RDF/JSON: 24-1.0376031-rdf.json
Turtle: 24-1.0376031-turtle.txt
N-Triples: 24-1.0376031-rdf-ntriples.txt
Original Record: 24-1.0376031-source.json
Full Text
24-1.0376031-fulltext.txt
Citation
24-1.0376031.ris

Full Text

Small for gestational age trends in Canada from 2000-2016: an analysis of individual-level factors and the minimum wage  by  Shiraz El Adam B.Sc. Lebanese American University, 2013  A THESIS SUBMITTED IN PARTIAL FULFLLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE  in  THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES  (Population and Public Health)  THE UNIVERSITY OF BRITISH COLUMBIA  (Vancouver)  December 2018   © Shiraz El Adam, 2018  ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis/dissertation entitled:  Small for gestational age trends in Canada from 2000-2016: an analysis of individual-level factors and the minimum wage  submitted by Shiraz El Adam in partial fulfillment of the requirements for the degree of Master of Science in Population and Public Health  Examining Committee: Jennifer Hutcheon, PhD Co-supervisor Kim McGrail, PhD Co-supervisor  Chris McLeod, PhD Supervisory Committee Member Nick Bansback Additional Examiner   iii Abstract Background Earlier studies investigating birthweight trends in Canada indicated a downward trend in SGA births. Today, evidence suggests an unexplained upward trend, as well as regional differences, in SGA births from 2005-2014.  These variations, over time and across jurisdictions, might be explained through downstream individual-level risk factors and/or more upstream contextual factors such as the minimum wage. Recent studies in the US found that higher minimum wages were associated with fewer adverse birth outcomes. Given the differences between the two countries, it is unclear if similar effects might be observed in Canada. Objective Describe and analyze trends in SGA births across Canada from 2000 to 2016 using individual and contextual-level data and then explore the association between minimum wage and SGA outcomes. Methods Retrospective cross-sectional analyses of all singleton births in Canada from 2000-2016 modeled SGA births through logistic regression, adjusting for individual and contextual risk factors. These models were then further adjusted for real minimum wage lagged by nine months. Analyses in both studies were stratified by four provinces (Ontario, Quebec, Alberta, and BC). Two subgroup analyses on single and all mothers residing in low income neighborhoods were further conducted.  Results A secular upward trend in SGA births extended from 2000-2016 and was not completely explained by changes in maternal age, parental birthplace, marital status, community size and neighborhood income quintile. A dollar increase in real minimum wage was associated with 2% lower odds of an SGA birth (95% CI 0.97, 0.99), when adjusting for all other confounders.  Provincially-stratified analyses and subgroup analysis of mothers in low income neighbourhoods, however, had null findings. For single mothers residing in low income neighbourhoods, a dollar  iv increase in real minimum wage was associated with 3.0% [95% CI: 1.01, 1.05] higher odds of an SGA birth, adjusting for all other confounders.   Conclusion SGA trends in Canada result from complex interactions of many variables. Not all of these variables, including risk factors such as smoking, were available at an individual level for analysis.  Intermediate income and employment pathways between real minimum wage and SGA births, specifically for low income single mothers,  require further exploration.     v Lay Summary  Gradually between 2005 and 2014, more babies were being born small for their age in Canada. This thesis explored the reasons behind this trend using parental risk factors (maternal age, marital status, country of birth, number of children already born, community size, and neighborhood income), as well as broader labour market factors, such as the minimum wage, for all births in Canada from 2000-2016. Adjusting for these maternal risk factors explained some - but not all -  of the trend. Similar to recent findings in the US(4), a dollar increase in real minimum wage (RMW) in Canada was associated with – small, but significant- 2% lower odds of small babies.  However, for single mothers residing in low income neighborhoods, the relationship was the opposite (3% higher odds). These findings highlight the need for more data on income and employment, specifically for the latter group of women, to further validate these results.             vi Preface This thesis is an original intellectual product of the author, Shiraz El Adam (SE).  With the guidance of the thesis supervisory committee: Jennifer Hutcheon, PhD, Kim McGrail PhD, and Chris McLeod, PhD, SE developed the research objectives, study design, data access requests, and analytical approaches.  Along with Dr. Jennifer Hutcheon and Dr. Chris McLeod, SE completed the necessary data access requests, screening, and legal contracts to access Statistics Canada’s Vital Statistics Births’ database housed at UBC’s British Columbia Inter-university Research Data Centre (BCIRDC). SE completed data management and data analysis at BCIRDC. Results from the BCIRDC were only released after strict vetting procedures by the BCIRDC analysts.   Since the research conducted in this thesis relies exclusively on secondary use of anonymous information, and is legally accessible to the public and appropriately protected by law; this thesis is exempt from Research Ethics Board review (Article 2.2 and 2.4 for exemptions). Preliminary results from this thesis were disseminated by SE in a poster presentation “The Association between Minimum Wages and Small for Gestational Age Births in Canada” at the 15th Canadian Association for Health Services and Policy Research Conference. May 29-31, 2018. Montreal, Canada.  vii Table of Contents Abstract ..................................................................................................................................... iii Lay Summary ............................................................................................................................. v Preface ...................................................................................................................................... vi Table of Contents .................................................................................................................... vii List of Tables ............................................................................................................................ ix List of Figures ............................................................................................................................ x List of Abbreviations ................................................................................................................ xi Acknowledgements ................................................................................................................. xii Chapter 1: Introduction ...................................................................................................................... 1 1.1 Thesis Overview & Summary .................................................................................................................1 1.2 Research Questions & hypotheses ..........................................................................................................5 Chapter 2: Background ....................................................................................................................... 9 2.1 Small for Gestational Age Births .............................................................................................................9 2.2 Minimum Wage in Canada ................................................................................................................... 18 2.3 Conceptual Framework and Theory Behind Minimum Wages and SGA Births ........................................ 24 Chapter 3: Chapter 3: Methodology ................................................................................................. 34 3.1 Study Design ....................................................................................................................................... 34 3.2 Data Sources ....................................................................................................................................... 34 3.3 Study Population ................................................................................................................................. 35 3.4 Outcome Variable................................................................................................................................ 37 3.5 Main Independent Variables ................................................................................................................. 39  viii 3.6 Confounding Variables ........................................................................................................................ 41 3.7 Statistical Methodology ........................................................................................................................ 45 Chapter 4: Results from Study 1 ....................................................................................................... 47 4.1 National Trends in SGA Births in Canada (2000-2016) ........................................................................... 47 Chapter 5: Results from Study 2 ....................................................................................................... 75 5.1 Trends in Minimum Wages (2000-2016) ................................................................................................ 75 5.2 Model Results for All Singleton Live Births in Canada (Adjusting for Minimum wage) ............................. 78 5.3 Stratified Model Results for Ontario, Quebec, BC, and Alberta ............................................................... 81 5.4 Subgroup Analyses .............................................................................................................................. 86 Chapter 6: Discussion & Conclusion .................................................................................................. 90 6.1 Main Findings ..................................................................................................................................... 90 6.2 Discussion .......................................................................................................................................... 92 6.3 Recognized Limitations ...................................................................................................................... 100 6.4 Strengths to Acknowledge .................................................................................................................. 102 6.5 Conclusion and Future Implications .................................................................................................... 103 Bibliography .......................................................................................................................... 106 Appendices ............................................................................................................................ 113   ix List of Tables TABLE 1: SUMMARY OF MATERNAL, FETAL AND PLACENTAL FACTORS ASSOCIATED WITH SGA BIRTHS, ADAPTED FROM SUHAG ET AL(20,24). ................................................................................................................................................................... 10 TABLE 2: CHARACTERISTICS OF MINIMUM WAGE WORKERS, SELECT POPULATION GROUPS, FIRST QUARTER OF 2018, ADAPTED FROM STATISTICS CANADA(60). ............................................................................................................................. 20 TABLE 3: SGA BIRTHS AS A PROPORTION OF ALL SINGLETON BIRTHS BY PROVINCE AND BIRTH YEAR (2000-2016) ..... 56 TABLE 4: SGA BIRTHS AS A PROPORTION OF ALL SINGLETON BIRTHS BY TERRITORY AND BIRTH YEAR (2000-2016) ... 57 TABLE 5: MATERNAL AND CHILD CHARACTERISTICS FOR ALL BIRTHS AND SGA BIRTHS IN 2000 COMPARED TO 2016 .. 63 TABLE 6: MULTIPLE LOGISTIC REGRESSION MODEL RESULTS FOR ALL LIVE SINGLETON BIRTHS IN CANADA (2000-2016) ........................................................................................................................................................................................................ 69 TABLE 7: REGRESSION MODEL RESULTS FOR ALL SINGLETON BIRTHS IN CANADA (WITH REAL LAGGED MINIMUM WAGE) ............................................................................................................................................................................................ 79 TABLE 8: MULTIPLE LOGISTIC REGRESSION MODEL RESULTS IN ONTARIO ............................................................................. 82 TABLE 9: MULTIPLE LOGISTIC REGRESSION MODEL RESULTS IN BRITISH COLUMBIA ........................................................... 83 TABLE 10: MULTIPLE LOGISTIC REGRESSION MODEL RESULTS IN ALBERTA ........................................................................... 84 TABLE 11: MULTIPLE LOGISTIC REGRESSION MODEL RESULTS IN QUEBEC ............................................................................. 85 TABLE 12: MULTIPLE LOGISTIC REGRESSION MODEL RESULTS FOR ALL BIRTHS TO MOTHERS RESIDING IN THE LOWEST NEIGHBORHOOD INCOME QUINTILE..................................................................................................................... 86 TABLE 13: MULTIPLE LOGISTIC REGRESSION MODEL RESULTS FOR ALL BIRTHS TO SINGLE MOTHERS RESIDING IN THE LOWEST NEIGHBORHOOD INCOME QUINTILE..................................................................................................................... 87   x List of Figures FIGURE 1: CONCEPTUAL FRAMEWORK ADAPTED FROM THE WHO (SOLAR & IRWIN) ........................................................... 25 FIGURE 2: SGA BIRTHS AS A PROPORTION OF ALL SINGLETON LIVE BIRTHS IN CANADA (2000-2016) ............................. 48 FIGURE 3: SGA BIRTHS AS A PROPORTION OF ALL SINGLETON LIVE BIRTHS BY PROVINCE/TERRITORY IN 2016. ......... 49 FIGURE 4: DISTRIBUTION OF SGA BIRTHS BY MOTHER’S RESIDENTIAL NEIGHBORHOOD INCOME QUINTILE IN CANADA (2000-2015) .................................................................................................................................................................. 50 FIGURE 5: TREND IN MEAN BIRTH WEIGHT FOR MALE, FEMALE, AND ALL SINGLETON LIVE BIRTHS IN CANADA (2000-2016) .............................................................................................................................................................................................. 52 FIGURE 6: DISTRIBUTION OF BIRTHS BY GESTATIONAL AGE FOR ALL SINGLETON LIVE BIRTHS IN SELECT YEARS FROM 2000-2016...................................................................................................................................................................................... 53 FIGURE 7: DISTRIBUTION OF BIRTHS BY GESTATIONAL AGE FOR ALL SGA BIRTHS IN CANADA IN SELECT YEARS FROM 2000-2016...................................................................................................................................................................................... 54 FIGURE 8: TREND IN MEAN BIRTH WEIGHT Z-SCORES FOR MALE, FEMALE, AND ALL SINGLETON LIVE BIRTHS IN CANADA (2000-2016) .................................................................................................................................................................. 55 FIGURE 9: SGA BIRTHS AS A PROPORTION OF ALL SINGLETON LIVE BIRTHS 2000-2016 (ON, QC, AB, BC) .................... 59 FIGURE 10: SIDE BY SIDE COMPARISON GRAPHS OF SGA BIRTHS BY NEIGHBORHOOD INCOME QUINTILE IN ON, QC, AB AND BC (2000-2015). ........................................................................................................................................................... 60 FIGURE 11: UNADJUSTED TREND IN SGA BIRTHS IN CANADA FROM 2000-2016 ..................................................................... 67 FIGURE 12: COMPARISON OF ADJUSTED VS. UNADJUSTED SGA TRENDS FROM 2000-2016 (REFERENCE YEAR: 2000) .... 74 FIGURE 13: TRENDS IN NOMINAL, REAL AND LAGGED REAL MINIMUM WAGE (2016 CONSTANT CANADIAN DOLLARS) FROM 2000-2016 .......................................................................................................................................................................... 75 FIGURE 14: REAL MINIMUM WAGE IN ONTARIO, QUEBEC, ALBERTA, AND BRITISH COLUMBIA (2000-2016) ................... 78 FIGURE 15: SGA TRENDS CRUDE AND ADJUSTED MODELS (ALL SINGLETON LIVE BIRTHS IN CANADA, 2000-2016) .... 81 FIGURE 16: TRENDS IN THE CRUDE AND ADJUSTED (WITH AND WITHOUT REAL LAGGED MINIMUM WAGE) ODDS OF SGA BIRTHS TO SINGLE MOTHERS RESIDING IN THE LOWEST NEIGHBORHOOD INCOME QUINTILE FROM 2000-2016 ................................................................................................................................................................................................ 89   xi List of Abbreviations AB   Alberta  ART   Assisted Reproductive Technologies BC   British Columbia BMI   Body Mass Index C-section  Caesarean section CDH  Congenital Diaphragmatic Hernia CI   Confidence Interval  CPI   Consumer Price Index DOHaD  Developmental Origins of Health and Disease  GA    Gestational Age  GWG  Gestational Weight Gain  IUGR   Intrauterine Growth Restriction IVF   In-Vitro Fertilization LBW   Low birth Weight  LGA  Large for Gestational Age  LICO   Low Income Cut Off LIM   Low Income Measure  LIN   Low income neighborhood    MW   Minimum Wage  Obs   Observations  ON   Ontario  OR  Odds Ratio PCCF   Postal Code Conversion File  QC   Quebec RMW   Real Minimum Wage  SD   Standard Deviation  SGA   Small for Gestational Age  TB   Tuberculosis TORCH Toxoplasma, Others, Rubella, Cytomegalovirus, Herpes group of viruses  VSBD   Vital Statistics Birth Database  WHO   World Health Organization   xii Acknowledgements First, I offer my profound gratitude to my supervisor Dr. Jennifer Hutcheon, who welcomed me to the world of perinatal epidemiology, and redirected me to this master’s program at UBC. Over the past two years, Dr. Hutcheon’s guidance, financial support, and penetrating questions, allowed me to take this thesis on own while questioning more deeply. Dr. Hutcheon, you have been a source of inspiration, and I could not have asked for a better supervisor.    I owe particular gratitude to my co-supervisor, Dr. Kim McGrail, who has exceeded all my expectations in guidance and support. Dr. McGrail’s valuable and methodological input helped me understand the “big picture” without veering off course. I am very grateful for your “open door policy” and our endless informal exchanges, from which I learned and advanced. Thank you for welcoming me to CHSPR and financially sponsoring me over many occasions. I am very thankful for your extra support this last term and for being an amazing mentor throughout the entire journey.    To my supervising committee member, Dr. Chris Mcleod, I cannot emphasize the depth and scope of knowledge I’ve learned from you over the past year. I am particularly thankful for the time you took to go through my data at the RDC, your clear and concise feedback, and stimulating questions. It has been a true pleasure, and very nourishing experience, to work with you.   Special thanks to Cheryl and Wendy at the RDC for vetting numerous data requests from me. To Kim’s team at CHSPR, specifically Ruth and Dawn, thank you for your feedback and help over our weekly meetings.    xiii Last and definitely not least, I thank my mom for being my main source of support throughout my entire life. Thank you for instilling in me an eternal curiosity to learn, and constantly reminding me of what I’m capable of.        1 Chapter 1: Introduction 1.1 Thesis Overview & Summary   Small size at birth has received significant attention in epidemiologic research due to its strong association with infant mortality and the risks of developing life-long complications (3,6–8). In Canada, small for gestational age births (SGA; defined as births below the 10th percentile of a reference population by sex and gestational age (9)) place significant burdens on families and the health care system in general(7,10).   In addition to the burden of health risks for women and families associated with a small infant , the estimated average in-hospital cost of a small for gestational age birth in Canada in 2005-2006 was 63 percent higher than that of a non-SGA birth (7). For low birth weight babies (birth weight less than 2,500 grams), these differences are even greater. For a low birth weight infant the average in-hospital cost was $12,354 compared to $1,084 for an infant with birthweight above 2,500 grams.   In Canada, previous studies investigating trends in birth weight over time indicated an increase in mean birthweight, and a decrease in the proportion of small for gestational age births(2,11). The most recent of these studies, published in 2002, found that babies born at term or after are getting bigger due to increases in maternal anthropometry (various measurements of size), reduced cigarette smoking, and changes in sociodemographic factors(1).     Today, evidence suggests otherwise. A perinatal health report published in 2017 reports an increase in the proportion of small for gestational age births from 2005-2014(3). Since the only studies investigating birth weight and fetal growth trends in Canada referred to a downward trend in SGA  2 births from 1978 to 1996, these findings cannot be generalized to today’s context. The reasons behind this recent upward trend in SGA births remain unclear.  This thesis had two aims. The first was to identify, describe, and analyze trends in SGA births across Canada from 2000 to 2016 using individual-level data. The first study described trends in mean birth weight, parental, and sociodemographic characteristics over time. While most of the analyses were run using the entire population of live singleton births in Canada, separate analyses were conducted on  Canada’s four largest provinces (Ontario, Quebec, British Columbia, and Alberta).   The second aim of this thesis was to explore how labour market factors, specifically real minimum wages, might help explain the trends in SGA births in Canada. The second study explored the association between real minimum wages in Canada and the odds of an SGA birth, with the hypothesis that real minimum wage increases would be associated with  fewer SGA births. The main analyses  used the entire population of births, and separate subgroup and stratified analyses explored sub-populations. As in the first study, we ran stratified analyses for Canada’s largest provinces (Ontario, Quebec, British Columbia, and Alberta). Additionally, two subgroup analyses focused on groups most likely to benefit from changes in real minimum wage: mothers residing in the lowest neighborhood income quintile and single mothers residing in the lowest neighborhood income quintile.   The challenge in understanding the relation between province-level minimum wages and adverse birth outcomes can be due to the potential for a time lag of effect and the influence of multiple intervening pathways. Therefore, to conceptualize the different pathways between minimum wage and SGA births, this research question was explored based on recognized social determinants of  3 health frameworks as well as recent empirical evidence. One of the frameworks that this recognition stems from is the World Health Organization’s social determinants of infant health framework (12), where downstream maternal lifestyle factors are structurally driven by more upstream determinants such as individual and area level socioeconomic status (SES), economic and social policies (13), political factors (14), and culture.   To date, only a handful of studies have investigated the association between specific upstream labour market factors and the risks of a small infant. The most recent are studies in the United States showing that higher minimum wages are associated with fewer adverse birth outcomes including infant deaths (5,15). However, given the differences both in minimum wage increases and health care system structure between Canada and the United States, it is unclear if similar effects might be observed in Canada.   The findings of the first study indicated upward secular trends in SGA births over time and across provinces. When comparing these trends by province or neighborhood income quintiles there were variations both in proportions and trends over time. Contrary to the findings of earlier studies(1,2,11), there were modest decreases in mean birthweights and mean birthweight z-scores for male and female births from 2000-2016. When controlling for important maternal, paternal and sociodemographic factors, the trends in SGA births were reduced yet remained visible.   The second study found consistent results with the existing literature on the association between minimum wages and the odds of an SGA birth on a national scale. However, when stratified by provinces the results were non-significant. In addition, findings from the subgroup analyses were inconsistent with those of the overall population.   4  On a population scale the second study found that a dollar increase in real minimum wage, 9 months prior to a birth, was associated with a significant 2% decrease in the odds of an SGA birth, adjusting for parental place of birth, maternal age, marital status, number of liveborn children, community size, and neighborhood income quintile. When stratifying the latter analysis by the four  provinces (Ontario, Quebec, British Columbia, and Alberta), non-significant results were observed in all provinces.   The results of the subgroup analysis on mothers residing in low income neighborhoods were also non-significant. The subgroup analysis on single mothers living in low income neighborhoods showed a small, but positive (OR 1.03) and statistically significant association between real minimum wage and the odds of an SGA birth. With limited evidence in the literature on the potential pathways for this group of women, and the lack of data to explore them, it is challenging to provide plausible explanations for these non-anticipated findings. One suggested pathway may be through countervailing labour market factors, such as higher minimum wages leading to reduced employment(16) and hours worked. However, with the lack of data on the income and working conditions (hours worked, employment standards, benefits, schedule, type of work) of this group of mothers, it is not possible within the current study to make these conclusions.  Additionally, since the income quintile and marital status variables have limitations in terms of potential misclassifications, the findings of this subgroup should be interpreted with caution.    This thesis adds to the existing conceptual and empirical evidence on important public health and labour market indicators. In light of the re-emerging minimum wage policy debate in Canada, the findings of both studies have considerable epidemiologic, economic and perinatal health  5 implications. The collective findings from this thesis highlight the need for more current and up to date research on the determinants of trends in SGA births in Canada using linked and accurately measured individual and contextual risk factors. From a policy perspective, increasing minimum wages seemed to improve adverse birth outcome on a national scale; however, the findings of the subgroup analysis on single mothers residing in low income neighborhoods suggest that more targeted programs or policies for the most at-risk populations such as the basic income or the unconditional income supplement (17) may be more beneficial.   The findings of the second study introduce new directions for researchers to pursue around modifiable risk factors in infant health. Particularly, investigating the specific pathways involved between higher minimum wages and adverse birth outcomes, for low income single mothers, can better inform and validate these results. These findings also highlight the potential benefit of access to more detailed linked individual level data on maternal occupation, income, working conditions and maternal risk factors. In brief, this thesis offers evidence to inform policy makers and lays the foundation to further explore new avenues in researching the social determinants of infant health.             1.2 Research Questions & hypotheses   This thesis consists of two related quantitative studies. The objectives and research questions for each respective study are outlined below:  6      1.2.1 Study 1   Objective: Identify and describe levels, trends, and determinants of SGA births in Canada from 2000-2016.      Research Question 1: How has the prevalence of SGA births changed over time (from 2000 to 2016) among mothers residing in Canada?  Hypothesis: We hypothesize that the prevalence of SGA births has gradually increased over time from 2000 to 2016.    Rationale: Evidence from the recent perinatal health indicators report (3) showed an upward trend in the proportion of SGA births in Canada from 2005-2014. This trend may have been gradually increasing over time from 2000 - 2016.     Research question 2: Which parental and contextual characteristics can help explain the trend in SGA births over time?  Hypothesis: We hypothesize that adjusting for parental and contextual characteristics in SGA trends will explain most of the variation over time.   Rationale: Previous studies investigating changes in birthweight over time found that babies born at term or after are getting bigger due to increases in maternal anthropometry (various measurements of size), reduced cigarette smoking, and changes in sociodemographic factors(1). Although evidence  7 today suggests that a higher proportion of births are born smaller than the average(3,7), the same variables investigated in 2002 may still be able to explain the recent upward trend in SGA births over time. The hypothesis in this study is motivated by the availability of important sociodemographic factors (such as parental place of birth, maternal age, number of liveborn children, marital status, and neighborhood income quintile), yet restricted by data limitations on other factors such as maternal anthropometry and maternal smoking.   1.2.2 Study 2  Objective: Explore the association between real minimum wage rates and small for gestational age births between 2000 and 2016 in all Canadian provinces and territories.   Research Question 1: What is the association between real minimum wages and SGA births for all mothers residing in Canada between 2000 and 2016?   Hypothesis: We hypothesize that a unit increase in minimum wage rates will be associated with modest reductions in SGA births.  Rationale: Based on the findings from similar studies, this association may occur through the intermediate pathways of improved employment, income and financial security, reduced maternal smoking, maternal stress, and improved nutrition. However, due to the incremental nature of minimum wage increases in Canada over time, this association may be modest in nature.    8  Research Question 2: How does this association vary when restricted to mothers residing in the lowest neighborhood income quintile and/or single mothers residing in the lowest neighborhood income quintile?   Hypothesis: We hypothesize that a unit increase in real minimum wages will be associated with decreased odds of an SGA birth for mothers residing in the lowest neighborhood income quintile and/or single mothers residing in the lowest neighborhood income quintile.   Rationale: Residence in the lowest neighborhood income quintile can be a proxy for low income households. With limited data on the income/occupation of mothers, we hypothesize that mothers residing in the lowest neighborhood income quintile and/or single mothers residing in the lowest neighborhood income quintile are two subpopulations that are most likely to be affected by minimum wage changes . These two subgroups also have higher risks of SGA births(7,18). Therefore, based on the same rationale provided for research question one above, and the low income target population for minimum wage policies, this association may be slightly more pronounced for this subgroup.     9 Chapter 2: Background   2.1 Small for Gestational Age Births          2.1.1 Etiology and Risk Factors     Small for gestational age (SGA) is a term used to define infants weighing below the 10th percentile of a given reference population for the same sex and gestational age (19).  While small infants can be the result of three distinct etiologies, this birthweight measure is commonly used as a proxy for fetal growth restriction. In the absence of congenital anomalies, infants may be classified small due to physiological factors (constitutional smallness) or a pathological growth restriction (Intrauterine Growth Restriction)(20) (21). Infants who are “constitutionally small” have achieved their growth potential, and therefore considered healthy. On the other hand, infants who are small due to a pathological growth restriction have higher risks of adverse pregnancy outcomes such as infant mortality. While these two pathways are distinct in nature, distinguishing physiological from pathological growth restriction is specifically challenging in large population studies(22).   Generally, the mechanisms of fetal growth restriction are a reduction in utero-placental blood flow, reduction in maternal blood volume, decreased oxygen-carrying capacity, and/or suboptimal maternal nutrition (23). The result is an inadequate transfer of oxygen and/or nutrients to the fetus across the placenta leading to a smaller infant(20). Table 1 below is adapted from Suhag et al. (24) and outlines specific causes of SGA births are outlined organized under three main categories: maternal, fetal and placental disorders (20,24,25). The focus here is on maternal factors.      10 Table 1: Summary of Maternal, Fetal and Placental Factors associated with SGA births, adapted from Suhag et al(20,24). Maternal Factors Fetal Factors  Placental Factors  Other Maternal Factors  Demographic Genetic Placenta  Maternal Age Ethnicity  Low pre-pregnancy weight Poor maternal weight gain Parity  Trisomy 21, 18, 13 Turners syndrome Deletion of chromosome 4, 5 Genetic syndromes  Placental abruption Placenta accreta Placental infarction  Circumvallate placenta  Confined placental mosaicism  Placental hemangioma  Placental chorangioma  Diffuse chronic villitis Fetal villous obliteration  Umbilical cord Velamentous cord insertion  Single umbilical artery Artificial reproductive technologies Uterine factors  Medication  (anticonvulsants, beta blockers) Behavioral/Environment Congenital malformations Angiotensin gene mutation Smoking Congenital heart disease CDH Abdominal wall defect Anencephaly  Alcohol  Drug use  High altitude   Systemic disease Infections  Hypertension  Pre-Gestational Diabetes Renal disease Anemia Pulmonary disease Congenital heart disease Autoimmune disease Antiphospholipid syndrome GI disease Malnutrition TORCH  Malaria Chlamydia Mycoplasma Listeria TB  Multiple pregnancy                            Pre-pregnancy BMI and Gestational Weight Gain:   11 Several maternal factors have been investigated against the risk of an SGA birth. Maternal anthropometry before and during pregnancy have been found to be a strong predictor of birth weight (20,25). Low pre-pregnancy Body Mass Index (BMI) or inadequate weight gain during pregnancy is associated with higher risks of an SGA infant (26,27). In a case control study in Italy,  underweight women (measured as BMI < 19.8 kg/m2) were found to be at 90% higher odds of an SGA birth (95% CI 1.6-2.4), whereas overweight women had non-significant lower odds (OR 0.7, 95% CI 0.5-1.0) (26). Similar findings were observed in a Chinese prospective study, where mothers (BMI ≤ 18.5 kg/m2) were associated with  219 ± 40 g mean reductions in infant birthweight (27). Moreover, in an investigation of 1,104 pregnant women, each 1kg weight gain during pregnancy was associated with an increase of birth weight in about 260g (28).   Parity:   Infants born to primiparous mothers (bearing a child for the first time) have lower mean birth weights and higher risks of an SGA birth (20,29,30). Conventionally, SGA infants born to primiparous women were considered normal or physiologic, because slower rates of growth are expected in women giving birth for the first time. The implication of a physiological classification of parity is that such infants are normally small, therefore we would not expect to see increased risks of adverse pregnancy outcomes. However, recent evidence suggests that in contrast to the influence of short stature or low pregnancy BMI, the reduced growth in infants of primiparous women is associated with increased risks of perinatal death(30). These findings indicate a pathological consequence of parity rather than a physiologic one raising questions on the use of growth standards customized by ‘physiological factors’ including parity.   Maternal Age:   12 There is ample evidence suggesting that maternal age is a risk factor for an SGA birth. Young maternal age specifically, confers a considerable risk of SGA births. This association may be explained by a functional immaturity of the reproductive system as well as adverse social and genetic influences in younger mothers(25). Advanced maternal age on the other hand is an independent risk factor for SGA births(31).   Ethnic Origin:  Multiple studies have highlighted a strong association between ethnic origin and birthweight(29). When comparing birth weights across ethnic groups, a great amount of variation in birth weights is observed(32) . For instance, compared to North American or European babies, Asian babies generally have a lighter birth weight(29). This can be explained through pathological differences between ethnicities (such as higher rates of Gestational Diabetes Mellitus among South Asian and south east Asian mothers (33)), physiological factors related to ethnicity (such as anthropometry), and/or socioeconomic factors (such as culture, lifestyle, and socioeconomic status).   Behavioral and the Environmental Factors:  Maternal behavioral and environmental factors can strongly influence the risks of an SGA birth. For instance, maternal smoking is one of the strongest causes of restricted growth(29,34). There is a symmetric association between the number of cigarettes smoked during pregnancy and the risk of SGA births due to an impaired fetal oxygenation and reduction in the oxygen carrying capacity and uterine blood flow(35).  Combined with alcohol use, smoking was found to have a more pronounced effect on birth weight(36). Illicit drug use, specifically the use of heroin, has also been associated with an elevated risk of SGA Births (37). Living at high altitudes can also result in an  13 SGA birth by compromising blood flow (reduced blood volume from poor pregnancy-associated volume expansion) and/or decreasing oxygen carrying capacity (38). Other maternal risk factors:  Finally, other maternal risk factors such as infertility and assisted reproductive techniques (ART) have also been shown to be independent risk factors of SGA births. Singleton births resulting from in vitro fertilization (IVF) and superovulation are at higher risks of being SGA(39). Under these techniques, superovulation is believed to affect fetal growth and development by imprinting changes through DNA methylation(40).      2.1.2 Consequences of SGA Births   Small size at birth has been associated with an increased risk of developing life-long complications including malnutrition, impaired neurodevelopment, psychological or emotional distress, and non-communicable diseases(41)(8). As a result of these comorbidities, an SGA infant has higher risks of infant death(42,43).    While the mechanisms for the increased risks remain unclear, some of the most common hypotheses can be explained through an understanding of the developmental origins of health and disease (DOHaD) (44). This theory proposes that adverse prenatal environmental influences which impair fetal growth during sensitive periods (“plastic window”) can alter normal patterns of growth and induce permanent changes in growth and development(20,44). Two general developmental mechanisms have been proposed to support this hypothesis: developmental disruption and adaptation(44–46). On a molecular level, adverse environmental stimuli can lead to disruptive or adaptive developmental responses through: the remodeling of tissue development (common  14 examples include the kidney, pancreas, and neuronal density), the resetting of homeostatic endocrine axes, and the permanent alteration of gene expression.  To investigate these hypotheses, numerous experimental animal studies have shown a close relationship between fetal growth restriction and common disturbances in kidney function and metabolic homeostasis. The result is neonatal encephalopathy, multi-organ dysfunction, an increased susceptibility to metabolic and cardiovascular abnormalities in adult life(44).   2.1.3 Epidemiologic and Economic Burden of SGA Births within Canada   By definition, the proportion of SGA births should be up to 10% of all singleton live births. Yet, over the last decade this proportion has varied both in levels and trends across the region. In 2014, the proportion of SGA births was 9.1 per 100 singleton live births in all Canadian provinces, excluding Quebec(3). Between 2005 and 2008, this proportion fluctuated between 8.2 (95% CI: 8.1–8.3) and 8.4 (95% CI: 8.3–8.5) per 100 singleton live births. Starting from 2008, there was a steady upward trend from 8.2 (95% CI: 8.1–8.3) to 9.1 (95% CI: 9.0–9.2) per 100 singleton live births in 2014. These proportions also vary significantly across provinces. For instance, between 2010 and 2014, SGA proportions ranged from 5.3 per 100 singleton live births (95% CI: 4.3–6.4) in Yukon to 9.6 (95% CI: 9.5–9.7) in Alberta (3).    From an economic perspective, the average cost associated with SGA births in Canada is substantially higher than that of non-SGA births. In 2005-2006 the average in-hospital cost associated with an SGA birth was $2,297 compared to $1,407 for a non-SGA birth (7). For a low birth weight infant (birth weight less than 2,500 grams) the average in-hospital cost was $12,354 compared to $1,084. As for a singleton SGA birth born extremely preterm (28 weeks of gestation or  15 less) the average hospital cost was $109,286 compared to $85,103 for a singleton non-SGA infant born extremely preterm.   2.1.4 Results of Prenatal Clinical Interventions Aimed at Reducing SGA Births   When aiming to eliminate or attenuate the risks of an SGA birth, numerous clinical interventions were evaluated in the systematic reviews discussed below and have either had minimal impact on this outcome and its sequelae(19,20,47,48), or have only been effective for a specific at-risk population(48). A meta-analysis of 126 randomized controlled trials (RCTs) evaluating 36 prenatal interventions found that the success of these interventions was dependent on the timing and nature of interventions in preventing feto-placental injury(47). More specifically, smoking cessation, protein/energy supplementation, and the use of anti-malarial therapy were the most successful when administered prior to the determination of small fetal size.  Another Cochrane review also highlighted the success of nutritional advice and balanced energy/protein supplements in ameliorating the risks of SGA births (19).   A more recent systematic review of 834 clinical trials, including 45 different interventions, found the most effective interventions to prevent an SGA birth are those that aim to reduce the risks of its comorbidities (48). Of the 12 interventions focused on small fetal size, the most effective intervention to prevent an SGA birth was the administration of antiplatelet at less than 16 weeks in women at risk of pre-eclampsia (RR 0.47; CI 0.30–0.74) (48). The review of nine trials on micronutrient supplementation found some evidence of an effect on reducing the risks of an SGA infant (48,49). Finally, two interventions (β-blockers and high protein and isocaloric balanced protein supplementation) seemed to increase the risk of an SGA fetus(19,48,50).    16 While the classification of SGA birth as 10 percent of the population means that it is impossible to eliminate or abolish by definition, the risks or consequences of SGA births can be attenuated based on the etiology of this outcome. As discussed above, some SGA infants can be constitutionally small and therefore ‘small but healthy’. On the other hand, infants that are small due to a pathological growth restriction, experience higher risks of adverse birth outcomes. The findings of the systematic reviews above are important in understanding the role of clinical interventions in reducing these risks. These findings are enlightening in taking new directions in research and exploring the potential of upstream socioeconomic conditions to shape maternal behaviors of a larger population of women early on in pregnancy to ultimately alleviate the risks of small for gestational age births.   2.1.5 Studies investigating Trends in Birthweight or SGA births In Canada, the standard birth weight charts used to classify size at birth are based on a large and diverse population of births from 1994-1996(51).  Since then, there has been mixed evidence on the trends in SGA births over time.   Earlier studies investigating trends in birth weight over time indicated an increase in mean birthweight, and a decrease in the proportion of small for gestational age births(2,11). One study, published in 2002, investigated these changes and found that babies born at term or after are getting bigger due to increases in maternal anthropometry, reduced cigarette smoking, and changes in sociodemographic factors(1).     Today, evidence suggests otherwise. A report(3) released by the Public Health Agency of Canada in 2017 includes the longest study period and most recent data describing the proportion of SGA births in Canada from 2005 to 2014. The report clearly indicates an upward trend in SGA births and a downward trend in large for gestational age births. Between 2005 and 2008 the proportion of SGA  17 births fluctuated between 8.2 (95% CI: 8.1–8.3) and 8.4 (95% CI: 8.3–8.5) per 100 singleton live births, and steadily increased from 8.2 (95% CI: 8.1–8.3) in 2008 to 9.1 (95% CI: 9.0–9.2) per 100 singleton live birth in 2014. The report also describes cross-provincial variations in the rates of SGA births form 2010-2014.   Several studies have examined the association between individual and contextual factors and SGA births in Canada(7,52–54). The investigated factors range from maternal and child related factors (7,54), to health services use(52) and socioeconomic factors(7,17). Overall, studies found socioeconomic disparities in SGA births in Canada, with a negative gradient observed between the highest and lowest income quintiles(7,55). In other words, the higher the neighborhood socioeconomic status of the mother’s residence, the lower the risks of an SGA birth.   While these studies are vital in determining risk factors for SGA births in a Canadian context, most were limited in their study period and therefore could not identify whether these factors were associated with SGA trends. The only study investigating birth weight and fetal growth trends in Canada was based on a population of births from 1978 to 1996, and a downward trend in SGA births.  Since evidence today suggest an upward rather than a downward trend in SGA births, these findings cannot be generalized to today’s context, and the reasons behind the recent upward trend in SGA births remains unclear.  The perinatal indicators report released in 2017 is enlightening in terms of recognizing a trend in SGA births over time, and across provinces. However, the report excludes Quebec, and does not further explore the determinants or factors associated with this trend.   18  From this perspective, study 1 in this thesis will be the first and most recent in the Canadian literature to:  1. Describe proportions of SGA births across all provinces and territories (without exclusions)  2. Report on a 17-year study period (2000-2016) 3. Describe the change in mean birth weight and z-scores from 200-2016 by sex 4. Further describe these trends across income quintiles in Canada’s largest provinces (Ontario, Quebec, Alberta and British Columbia)  5. Identify which individual and contextual factors are associated with SGA trends  2.2 Minimum Wage in Canada  During the early 20th century, minimum wage policies were introduced in Canada to improve workers’ conditions and prevent the exploitation of women and children(56). Nowadays, increasing minimum wages is one of the most common tools used by policy-makers to reduce poverty and income inequality(57). Although nominal and real minimum wages widely ranged across the 13 jurisdictions in Canada from 2000 to 2016, these differences were relatively small. For instance, in 2015, the highest real minimum wage (in 2015 constant dollars) was $11.49 per hour in the Northwest Territories, while the lowest was only $1.21 less ($10.28 per hour in Saskatchewan) (57). In 2010, the highest real minimum wage ($10.06 in Ontario) was $2.06 more than the lowest ($8.00 in British Columbia) (57). Over time these differences have narrowed, specifically in recent years.   Between 2000 and 2016, five (Nova Scotia, Saskatchewan, Yukon, Alberta, and New Brunswick) of the 13 jurisdictions indexed their minimum wages by annually adjusting their value to the increase in the Consumer Price Index. Freezing minimum wages without indexation over long periods of time  19 can erode their value by the amount of inflation each year. This was the case in Ontario from 2000-2003 and from 2011-2015 where the minimum wage was frozen. In British Columbia, the minimum wage was frozen over a longer period of time from 2002 to 2010(57).     2.2.1  Description of Minimum Wage Employees in Canada  The proportion of Canadian employees on nominal minimum wage tends to be higher in certain provinces compared to others. For instance, in 2014, 1.7% of Alberta’s employees were on minimum wage compared to 10.9% in Ontario (56). The proportion also tends to be higher for women than men. For example, between 1997 and 2013, the proportion of Canadian males on minimum wage increased from 3.9% to 5.5%, whereas that for females increased from 6.2% to 8.0% (58).   Contradictory to the stereotype that minimum wage earners are teenagers, work part-time after school and live with their parents, a study in BC in 2015 found 82% of individuals earning minimum wage were 20 years or older, 39% were 35 or older, 60% were women, 58% work full time, and 68% did not live at home with parents (59).   A recent report by Statistics Canada in 2018 highlights the composition of minimum wage workers before and after the recent minimum wage changes (60). Between 2017 and 2018, the percentage of minimum wage workers increased from 6.2% (953,200 employees) to 10.1% (1,565,400 employees). However, between 2017 and 2018, minimum wage increases were substantial compared to previous years. In the first quarter of 2018, around 70% of minimum wage workers belonged to one of the three groups described in Table 2 below. These groups were also found to face diverse economic conditions. After controlling for differences in family size and regional differences in the cost of  20 living, single, lone parents or spouses/partners in single-earner couples lived in families where total weekly employment income was the lowest of all other groups.    Table 2: Characteristics of minimum wage workers, select population groups, first Quarter of 2018, adapted from Statistics Canada(60).  Group 1 Group 2 Group 3  Students and non-students aged 15 to 24 living with their parents Persons aged 15 to 64 who are unattached, lone parents or spouses/partners in single-earner couples Persons aged 15 to 64 who are spouses/partners in dual-earner couples This group as percentage of all minimum wage workers* 33.2 16.6 18.2 Working full time 17.5 65.7 68.8 Working in temporary jobs 32.9 13.9 14.2 Working in retail trade, food and accommodation services 72.4 49.9 42.9 Living in rented dwellings 27.7 62.1 38.2 With at most a high school diploma 62.2 44.4 35.6 With at least a bachelor's degree 3.0 18.7 26.0 Women 54.1 60.4 65.8 Immigrants 17.9 35.2 48.0 Average age 19.1 40.6 42.4 Aged 35 to 64 0.0 60.3 72.1 Note: All numbers are percentages Note: Minimum wage workers living in families with no self-employment income represent 78.1% (Group 1), 99.1% (Group 2) and 82.4% (Group 3) of all minimum wage workers in these groups. Source: Statistics Canada, Labour Force Survey, 2018.   2.2.2 Labour Market Intermediary Pathways   Raising minimum wages has long been a controversial topic fueled by mixed theoretical and empirical evidence on its economic effects(61). Those in favor suggest that such social protection  21 policies increase earnings of the low skilled workers, and reduce income inequalities. Opponents argue that raising minimum wages leads to higher labour costs, unemployment, and inflation.   Based on the framework above and evidence from the economic literature, this section will describe the positive and negative income and substitution effects of raising minimum wages. These effects are generally dependent on the economic cycle at which a minimum wage increase occur. For instance, employers’ response to higher minimum wages may be less sensitive in periods of expansion (economic growth), and more sensitive in periods of contraction (recession).   2.2.2.1 Positive Income and Substitution effects:  Assuming that the minimum wage is not far below the market rate so that no employees are bound by the increase, the results of an increase in minimum wage can have a direct income effect on those earning minimum wage as well as other low wage workers(62). This direct income effect can occur in an entirely inelastic labour demand curve where the increase in the minimum wage does not lead employers to lay off workers(62). In this case, workers who previously earned the old nominal minimum wage have their wage boosted to new higher minimum wage. Assuming that work hours are not reduced either, this increase in wage rate will be translated into higher weekly and monthly earnings, which on the long run increase average hourly wage rates and earnings(62).    Some research also suggests that raising the minimum wage not only increases the earning of minimum wage workers, but those who earn above the minimum wage as well.  The term usually referred to in the economic literature is a “spillover effect”. In their book “What does the minimum wage do?”, Belman et al.(62) explain that spillovers may reach as high as the third decile of the wage distribution(63). Among several studies investigating the underlying factors for this spillover effect,  22 the general agreement is that employees base their expectations of wages and wage increases by comparison to other workers(62). This comparison can be the result of workers’ desire to maintain their social status, and/or to quantify what can be a reasonable wage increase. Higher expectations from workers earning above the minimum wage can place pressure on employers to avoid issues with fairness, labor efficiency and turnover(64).    The neoclassical theory also suggests that the wages of those earning above the new minimum wage may increase through a substitution effect. In other words, when the minimum wage increases, some employers may substitute more productive and higher wage workers for those whose productivity is below the new minimum wage. An increase in the demand for higher wage workers can ultimately increase their equilibrium wage depending on the size of the wage increase, the demand for higher wage labor, and the proximity of substitutes(62). This indirect income effect through substitution can spill over higher earnings to workers who were earning above the minimum wage.   2.2.2.2 Negative income and substitution effects Increasing minimum wages could alternatively have negative income effects through an increase in unemployment and a reduction in the number of hours worked. A review of evidence on the employment effects of minimum wage by Neumark et al. indicates a lack of consensus on the overall effects on low wage employment with an increase in minimum wage(61). The review further indicates a sizeable proportion of the reviewed studies showing negative employment effects of minimum wages (often not statistically significant) specifically for low skilled workers. Another study examining how minimum wage changes affect single mothers in the US found that less educated single mothers who were affected by the policy did not see an increase in their net income due to a negative effect on employment and hours (65). Specifically, for this low skilled population a 10 %  23 increase in the minimum wage was associated with an 8.8 % reduction in employment and an 11.8 % reduction in annual hours worked(65). Finally, a more indirect income effect can occur through wage compression. The theory suggests that when increases in the wages of workers at the lower end of the wage distribution outpace those of higher wage workers, a wage compression can occur. However, there is evidence suggesting that the implications of a wage compression is more likely to be for short term and specific occupations (white collars)(64).   Another negative substitution effect of raising the minimum wage can occur when employers retain their employees by reallocating their compensation packages, or substituting for cheaper inputs. In other words, since compensation consists of a combination of cash and non-cash attributes, and depends in part on worker productivity, an employer may increase the cash portion of the compensation due to higher minimum wages while reducing other non-cash benefits. A study using American Community Survey data from 2011-2016 found robust evidence that state level minimum wage changes decreased the likelihood of employer-sponsored health insurance, specifically among low-paying occupations(66). The study also finds a wage effect spillover into occupations moderately higher up the wage distribution. This spillover can be explained by firms that have collective benefit packages for both low- and high-skilled workers. This cohesion may cause spillover effects on the compensation packages of higher-skilled workers due to minimum wage increases. In Canada, recent evidence suggests that adverse employment effects are significantly greater for permanent minimum wage workers than for temporary minimum wage workers, however the employment effects are relatively small and declining over time(67).  The authors support this by explaining that employers are more likely to adjust/substitute for cheaper inputs when the cost implications are more long-term (permanent) than temporary or short-termed. Employers may be less tempted to reduce the  24 hiring, or lay off temporary workers with a fixed termination date, and may use this temporary period to evaluate prospects of these workers for future promotions to full time positions.  2.3 Conceptual Framework and Theory Behind Minimum Wages and SGA Births   2.3.1 Conceptual Framework    As indicated above, downstream lifestyle factors such as maternal nutrition, maternal smoking, illicit drug use, and pre-pregnancy BMI are known risk factors to a small for gestational age birth. These downstream lifestyle factors can be shaped by more upstream determinants known as the social determinants of infant mortality and birth outcomes (12,68) (Figure 1 below).  In this conceptual framework adapted from the World Health Organization’s Commission on Social Determinants of Health, material living, working conditions, and the social and environmental conditions in which people are born, live, work and age, are structurally driven by individual and area level socioeconomic status (SES), residential segregation, race/ethnicity, gender, economic and social policies (13), political factors (14), and culture.   Of the various macroeconomic regulations and social policies, raising minimum wage is one that may affect the material environment, specifically the living and working conditions (hours worked, benefits received) of individuals earning minimum wage through greater income and/or employment conditions. These pathways may further influence specific health behaviors (such as maternal smoking, balanced nutrition, and the availability of time to seek prenatal care) and other psychosocial factors (such as emotional and financial stress) which are associated with adverse birth outcomes.     25 Figure 1: Conceptual Framework Adapted from the WHO (Solar & Irwin)       2.3.2 Specific Implications based on economic/labor market pathways    For pregnant women, the decisions made by their employers upon an increase in minimum wage can have very different effects on their risks of an SGA birth. Using conceptual framework above and the different income and substitution effects of increasing minimum wages outlined earlier, we discuss below the possible implications on the mother’s risk of adverse birth outcomes.     26 1. Positive income effect without a reduction in the number of hours worked:   Implications:  Increased income may increase financial security, which may reduce maternal stress and/or maternal smoking - factors known to be associated with adverse birth outcome. A recent Canadian study found that an unconditional income supplement to low-income pregnant women in Manitoba was associated with 10% lower odds of an SGA birth(17).  The psychosocial interpretation also suggests that reducing income inequalities, could reduce maternal stress induced from one’s reflection of class segregation and inferiority in socioeconomic status. Greater income from an increase in the minimum wage can also improve nutrition. Evidence suggests that even small, short-term variations in income can impact a mothers’ nutritional intake especially in families experiencing food insecurity(69).   2. Substitution effect: Increased cash income, reduced fringe benefits or hours of work:   Implications:   In this scenario, there are multiple pathways dependent on the nature of work and the need for income. It may be that reduced work hours for pregnant women may reduce the risks of an SGA birth. Studies have shown that working shift work and/or working 40 hours or more a week significantly predicted a low birth weight(70). However, for pregnant women who rely on a minimum wage job as their primary source of income, the benefits of reduced work hours may be overcome by higher risks induced by financial insecurity.   3. Negative income effect: Layoffs or reduced hours of work:  Implications:  27  Aside from income, minimum wages can also be associated with adverse birth outcomes through modifiable occupational factors, working conditions, and/or unemployment. Studies have shown significant associations between physical work demand and the risks of a low birth weight(70). A study exploring unemployment and pregnancy outcomes in Finland (whereby maternity care is universally provided, free of charge) found that unemployed women had significantly higher odds of an SGA birth, OR 1.26 (95% CI: 1.12 – 1.42), than employed women (adjusting for maternal age, unmarried status and overweight, anemia, smoking, alcohol consumption and prior pregnancy terminations). These results were even higher when both parents were unemployed OR of 1.43 (95% CI: 1.18 – 1.73) (16). Another study looking at the effect of unexpected economic contractions (state unemployment rate was higher than its statistically expected value) on birthweight found similar results(71). In this study, exposure to unexpected economic contraction in the first trimester of pregnancy was associated with a 3.7 percentile point decrease in birth weight for gestational age (95% confidence interval [CI]= −6.8 to −0.6) and significantly higher odds of SGA births (odds ratio= 1.5 [95% CI= 1.1 to 2.1) and term SGA (1.6 [1.2 to 2.3]) (71).  2.3.3 Important Variables for SGA Trends and Minimum Wage When it comes to exploring the association between minimum wage and adverse birth outcomes (specifically SGA births) in Canada, there is evidence supporting the consideration of a number factors as potential confounders or effect modifiers. Included here are factors with evidence suggesting a relationship between both the SGA (the outcome of interest) and minimum wage (a main explanatory variable of interest).    Maternal and paternal places of birth   28 Maternal and paternal places of birth can be associated with SGA births through ethnicity, culture, and length of residence (72–74). Ethnicity has been shown to be an independent risk factor(75) and useful indicator of the fetus’ genetic potential for growth(76,77). Using place of birth as an indicator for ethnicity can account for the physiological factors related to ethnicity (anthropometry) as well as the social and cultural factors that contribute to these disparities.   Using parental place of birth can also be used as an indicator for immigration.  In addition to ethnicity, infants of immigrant women in Western countries have been observed to have lower birth weights than infants of native-born women. These differences could be physiologic or pathological. A Canadian study looking at singleton births between 2004 and 2006 found a positive association between parents’ length of residence in Canada and birthweight, when adjusted for all covariates (74). Parents with a length of residence in Canada less than or equal to five years, on average, had smaller babies compared with those of Canadian-born parents. One explanation for these variations by length of residence is acculturation. This phenomenon occurs when groups of individuals from different cultural backgrounds that are continuously in contact with each other start to adapt and become more similar to the new culture(78).   Immigration and acculturation can become more important in maternal behaviours that are well-known risk factors for SGA births. New insights on the social pathways between country of birth and poor maternal health behaviours from a recent study in the US  highlight the role of paternal place of birth and ethnicity in influencing maternal behaviours during pregnancies through acculturation (79). The study shows that native born mothers were less likely to smoke during pregnancy if their partners were foreign-born. In contrast, foreign-born mothers whose partners were native-born had higher odds of maternal smoking than if their partners were also foreign-born.  29 In addition to maternal smoking, immigrant mothers in Canada were also more likely to receive inadequate prenatal care than non- immigrants  (52). Some studies highlighted a positive association between prenatal care visits and improved birth outcomes (80).    In addition to its association with the outcome, parental place of birth is associated with minimum wage workers through immigration. A profile of minimum wage workers in 2017-2018 shows that more than 35% of minimum wage workers who are unattached, lone parents, or spouses are immigrants. As described above, women and recent immigrants are believed to benefit the most from minimum wage increases.   Maternal Age As described in the background of Chapter 2, maternal age is believed to be a common risk factor for SGA births (75). However, the relation between maternal age and SGA births is non-linear (81). Young maternal age (teenage)(75) and maternal age ≥35 years have been found in several studies to have an elevated risk of SGA (29).   In addition to its association with the risks of an SGA birth, maternal age is likely to be associated with minimum wage workers. By looking at the profile of minimum wage workers in Canada, there is an observable non-linear relation between age and minimum wage workers.  For instance, a significant proportion of minimum wage employees in 2017 were aged between 15 and 24 years old (33.2% in 2017), while the other two-thirds were over 35 years(60). In addition, research exploring the main determinants of minimum wages have highlighted the role of interest groups where women and youth, represented in interest groups, were significant predictors of minimum wage levels (82).    30 Marital Status  Single marital status is believed to be another characteristic associated with  an SGA birth (29,83,84). Marriage can infer a support system for pregnant women through improved income (financial security) and improved mental health. Unmarried women (especially in low income quintiles) are less likely to report an intended pregnancy than married women, and more likely to have adverse birth outcomes. Women with unintended pregnancies are more likely to have inadequate prenatal care which is another pathway to adverse birth outcomes (85).   In 2017, 16% of minimum wage workers were unattached, lone parents or partners in single earning couples, 18% were partners in dual earning couples. Single women have also been a specific population of interest to minimum wage researchers, particularly due to the lower income observed in this group compared to other groups in the population(62).   Community size  Variations in earnings is highly influenced by community size with a prevalent urban-rural earnings gap across Canada(86). Generally, the larger the community size the higher the earnings. Many factors influence this earnings gap including agglomeration economies due to numerous sources, access to shared infrastructure, and proximity to human capital(86). In terms of human capital, educational attainment appears key in explaining the disparities in earnings by community size. For instance, in 2001, the proportion of employees with a university degree was 25% in metropolitan areas with a population greater than 500,000 and 10%? in rural areas.  Disparities in adverse birth outcomes – specifically SGA births – by community size have also been cited in Canada(7). While one would expect that the limited access to health care services in rural  31 areas would result in higher rates of SGA in these areas, the opposite is observed.  In 2006-2007,  the SGA rate was significantly higher in urban compared to rural areas (8.7% versus 7.0%) (7). At the provincial level, SGA rates were significantly higher in urban areas in Alberta (9.2% versus 7.4%), Ontario (9.1% versus 6.6%) and Manitoba (8.1% versus 6.8%). These poor health outcomes may likely be due to factors associated with increased population density in urban areas. In addition, urban-rural differences in obesity rates in Canada may also contribute to the differences in SGA proportions by rural residence. For instance, higher rates of obesity(87) and lower rates of SGA births are both observed in rural residences in Canada. Obesity (measured by BMI≥ 30 kg/m2) has been found to be associated with lower risks of SGA(88).   Neighborhood Income Per Single Person Equivalent  Multiple studies in Canada have reported a gradient in adverse birth outcomes, specifically SGA births, by neighborhood income quintiles (7,55,89,90). This gradient shows that a lower level of neighborhood income is associated consistently with increased risks of small for gestational age babies and low birth weight. Neighborhood income level can be interpreted as an independent indicator for subpopulations at risk of adverse birth outcomes(55,89). Women with lower educational attainment and those living in poorer neighborhoods are more vulnerable to adverse birth outcomes (89). Neighborhood income quintile can also be a proxy for the mother’s income and educational attainment. As such, the association between minimum wage and adverse birth outcomes can either be through this variable, or may vary by the different levels of individual income.   32 2.3.4 Studies investigating the relationship between minimum wages and adverse birth outcomes While the economic effects of raising minimum wages is a widely-studied and controversial topic both in Canada and worldwide, only a handful of studies have measured the association of such policies with adverse birth outcomes. Currently, only two studies have examined the effect of minimum wage increases on infant health outcomes (5,15). Both studies were based in the United States (a heavily private healthcare setting). A simulation study examining the theoretical effect of minimum wage changes on preterm birth has also been conducted (91).  The first study examined the effect of minimum wages on infant mortality and low birth weight(15), while the second was a working paper (5). Both studies showed a decrease in the rates of adverse birth outcomes and infant deaths associated with every dollar increase in minimum wage rates. For instance, Komro et al.(15) found that a dollar increase in the minimum wage in the US above the federal level was associated with a 1% to 2% decrease in low birth weight births and a 4% decrease in post-neonatal mortality. Wehby et al(5) also found an association between higher minimum wages and birth weight, which they explain to be driven by increased gestational length (without measuring) and fetal growth rate (measured as birthweight divided by gestational age).   Although the study design of these studies was ecological, with a difference in differences methodology, both studies used aggregated individual level variables merged with contextual/macro-level variables. In Komro et al’s study, the models adjusted for state and year fixed effects, race, poverty, cigarette sales, and maternal age. These covariates were included as the percentage of African American and mean age of mothers from natality files, poverty rate from census data, and cigarette sales from Orzechowski and Walker(15). In Wehby et al’s research design, the models were  33 stratified based on the mother’s level of educational attainment (less than high school, and high school), race (white, non-white), age (18-29, and 30-39), and marital status (married, not married)(5).   While the findings in these studies are novel, there are some limitations in terms of internal and external validity. In terms of external validity, both studies identified above were conducted in the United States under a private health care system setting. As such, these findings can only be generalized to countries of similar systems and demographic characteristics. This is specifically important when one of the hypothesized pathways of the effect of higher minimum wages on birth outcomes is through prenatal care use as a result of higher income. Although the analysis by Wehby et al.(5) was stratified by characteristics that are important to minimum wage workers (such as mother’s level of education, race, age and marital status), neither study focused on mothers earning low income. Changes in minimum wages are likely to affect their target low income populations, and not necessarily all births in all jurisdictions. This threat to external validity was addressed in this thesis by conducting two subgroup analyses on mothers residing in neighborhoods of the lowest income quintile as well as single mothers residing in the lowest neighborhood income quintile.  Furthermore, although the analyses by Komro et al(4) adjusted for several maternal risk factors, the variables included in the models were based on aggregated proportions rather than individual level variables. Therefore, to avoid concerns with ecological fallacies, the inferences concluded from these analyses can only be made on a population scale and not on an individual level. In this thesis, all maternal risk factors will be adjusted for on an individual level.   34 Chapter 3: Chapter 3: Methodology   3.1 Study Design    Both studies 1 and 2 are retrospective, cross-sectional analyses of all singleton live births in Canada born between 2000 and 2016. In study 2, individual-level variables are merged with contextual province-level variables to expand the analyses of labour market factors.      3.2 Data Sources   Vital Statistics’ Births Database (VSBD): This database is based on a mandatory administrative census (operating under an agreement between the government of Canada and the governments of provinces and territories) that collects data from all provincial and territorial vital statistics registries on all live births in Canada. In addition to individual-level characteristics, this dataset contains contextual variables (such as neighborhood income quintile and community size) linked through the Postal Code Conversion File (PCCF) and Postal Code Conversion File Plus (PCCF+) to each birth’s postal code.   Government of Canada’s Minimum Wage Database: Data on nominal minimum wage rates across all provinces and territories between 2000-2016 were obtained from the publicly-available Government of Canada’s Minimum Wage Database.   Consumer Price Index (CPI) dataset: This is a publicly available mandatory administrative survey extracted and derived from other Statistics Canada’s monthly surveys. The Consumer Price Index (CPI) is obtained by comparing, over time, the cost of a fixed basket of goods and services purchased by Canadian consumers. The “all-items” CPI data was used to calculate minimum wages in 2016 constant dollars, i.e. a real minimum wage. This “all-item CPI” is made up of eight major  35 components of goods and services, which are:  "food", "shelter", "household operations, furnishings and equipment", "clothing and footwear", "transportation", "health and personal care", "recreation, education and reading", and "alcoholic beverages and tobacco products"(92). These eight components are further broken down into a hierarchical range of subgroups.       3.3 Study Population   The study population was drawn from all singleton live births registered in the Canadian Vital Statistics Births Database between 2000 and 2016. The reporting of births in this dataset is virtually complete since registration of births is a legal requirement in each Canadian province and territory. Rationale for selecting this population: - The inclusion of births from all provinces and territories reflects complete geographic diversity. - The existence of regional variations in perinatal outcomes makes it compelling to understand these differences.  - The economic literature encompasses diverse studies suggesting that increasing minimum wages might not only affect individuals who are on minimum wage the most, but rather employers, and other employees of various income levels through higher employment costs and less job hiring(93), thus a study including all births is relevant in exploring those questions  The study population excluded: stillbirths, multiple births, births with gestational age less than 22 weeks or greater than 43 weeks, births with birth weights (less than 300g or more than 5999 g),  36 births with unknown/missing birthweight, unknown/missing pregnancy duration, and unknown/missing sex. Rationale for exclusions:  - Multiple births have higher risks of SGA births than singleton births, which can be caused by distinct etiologies.  - Gestational age less than 22 weeks and greater than 43 weeks: the Canadian reference standard used to identify SGA births in this study is limited to gestational ages between 22 and 43 weeks. There is evidence showing that births with a gestational age less than 22 weeks are non-viable(94). On the other hand, pregnancies beyond 43 weeks are highly unlikely due to the advancement of obstetric practices in Canada, and clinical guidelines for inducing labor at 41+0 to 42+0 weeks to reduce the risks of perinatal mortality(95) or the option of elective C-sections. Births with birth weight less than 300g are also non-viable (96).  - Births in Canada where the mothers’ residence outside Canada: the study design is focused on trends in Canada.    Sub-Population 1: The study population for the first subgroup analysis was drawn from study population 1, restricted to births of mothers residing in the lowest neighborhood income quintile.    Rationale for selecting this population:  - Low neighborhood SES is a proxy measure determined by census data from statistics Canada that identifies the average income of the specified neighborhoods based on postal codes. This measure will be used as a proxy for low income families that are most likely to be affected by minimum wage changes.    37 Sub-Population 2: The study population for the second subgroup analysis was drawn from Sub-population 1, restricted to births of single mothers.  Rationale for selecting this population:  - Given the composition of minimum wage earners in Canada described in the background, single mothers have a significant share of minimum wage workers (over 50%).  As such, it is interesting to see the extent to which the association between minimum wage changes and SGA births varies in this specific sub population.          3.4 Outcome Variable    SGA birth is the dependent variable for all models.  A small-for-gestational-age birth was defined using the Canadian birthweight for gestational age reference charts developed by Kramer et al(51). Week- and sex-specific means and standard deviations of birthweight from this reference were used to generate a z-score for each birth in our cohort. SGA births were classified as below the tenth percentile of all births of the same sex and gestational age through a z-score of less than -1.28 (which corresponds to the 10th percentile assuming a standard normal distribution).  The z-score variable was created for births of the same sex and pregnancy duration as:  Z-Score = [birthweight (in observed birth) – mean birthweight (in reference chart)]     SD (in reference chart)  A binary variable for SGA was =1 if the birth’s z-score was below -1.28, and non-SGA (=0) if greater or equal.      38 Rationale for using the z-scores:  The reference chart publishes birthweight cutoffs by percentiles, as well as means and standard deviations for each gestational age. While either method can be used to classify SGA births, we chose to use a z-score=-1.28 (equivalent to the lowest 10th percentile) to compare each birth in the dataset to the reference population. The use of z-scores for population-based assessment has been recognized by the WHO (97) as the best system for analyzing and presenting anthropometric data due to few advantages, including:  - Allows the measurement of a binary SGA variable as well as a continuous birthweight z-score variable.  - Compared to percentiles which are bound by 0 and 100 and follow a uniform distribution, z-score follow a normal distribution making it more suitable for the assumptions of least squares regression.   It is worth noting here that since the use of z-score method assumes a normal distribution, the numbers obtained from this method may not perfectly match those using a percentile birthweight cutoff.   Birth weight is a continuous variable indicating the weight of the fetus or newborn obtained immediately after birth, expressed in grams. This variable was used to calculate SGA births (along with sex and gestational age). Births with unknown birth weights (coded as 9999 or blank) were excluded from the dataset.   Gestational Age is a continuous variable indicating the gestation period of the pregnancy, in completed number of weeks, between the first day of the mother’s last menstrual period and the day of  39 delivery. Since Canadian birth registration documents do not specify how the gestational age was calculated, it is unknown if the reported gestational age was based on ultrasound, maternal recall of the first day of the last normal menstrual period, a neonatal physical examination or other method. However, based on a report by the Public Health Agency of Canada, 99.8% of women who participated in the Maternity Experiences Survey (2006) reported having an early ultrasound, with an average of three ultrasounds per woman(98). On average, the first ultrasound was reported at approximately 14 weeks. Additionally, 66.8% of mothers had their first ultrasound prior to 18 weeks(98). This shows that the estimates on the birth certificates were most likely confirmed by an early ultrasound, and therefore accurately measured.   Sex is an indicator variable identifying the sex of the child. Due to the restrictions of birthweight reference charts to males or females, any births with unknown sex were also excluded.  Values  Meaning  1  Male  2  Female         3.5 Main Independent Variables    Study 1:   Birth year was used as the main independent time trend variable for all analyses.  This variable code represents the year when the birth occurred.  The completion rate for this field in the VSBD was 100%.    Study 2:   Lagged Real Minimum wage is the main independent variable for all analyses in the second study. This variable was created using the nominal minimum wage and Consumer Price Index data and  40 lagged 9 months. Since both variables were obtained from publicly available datasets, both the nominal minimum wage and Consumer Price index data were merged with each individual birth based on three variables:  - Mother’s province of residence - Birth month  - Birth year   The real minimum wage was measured as the nominal minimum wage adjusted for inflation and expressed in 2016 constant dollars:    Real minimum wage = Nominal minimum wage * (CPI in December 2016)/ (CPI merged with each individual birth)   Adjusting for inflation:  Rationale:  - Comparing the value of nominal minimum wage over 17 years without adjusting for inflation can introduce strongly biased estimates. In other words, the purchasing power of $10 in 2000 is not the same as that in 2016. This is due to the change in the cost of living over time. From a confounding perspective, minimum wage increases are determined through several factors, the strongest of which is the consumer price index. Inflation or higher CPI also implies higher food prices which affects the affordability of a nutritious diet for pregnant women. This in turn can influence gestational weight gain -  a risk factor for SGA birth.   Lagging Real minimum wage 9 months:   41 Rationale: - To better capture the relationship between minimum wages and birth outcomes, this variables was lagged 9 months to reflect the real minimum wage around the time of conception, rather than at the time of birth. The choice of 9 months allows for an increase in minimum wage to have an effect on fetal growth (both in lean and fat mass). Findings from the Generation R Study show that maternal risk factors are associated with human embryonic trajectories (estimated with crown-rump length (CRL) measurements), as early as the first trimester, suggesting that the onset of small size is earlier than previously thought (99).       3.6 Confounding Variables    Mother’s/father’s geographic birth place are two separate categorical variables indicating the mother’s and father’s birthplace by geographic region. Using the Statistical Classification of Countries and Areas of Interest for Social Statistics - SCCAI 2017 adopted by Statistics Canada, the mother’s/father’s country of birth variable available in the VSBD was regrouped into a larger geographic region as outlined below(100). Mother’s/father’s place of birth variable is reported as indicated on the registration form and according to the boundaries in effect at the time of birth and not according to the most recent boundaries. In such cases, these countries were matched with their most recent equivalent boundaries in the SCCAI 2017(100). Mother’s Geographic Birth Place Value  Meaning  1000 Canada  1110 North America excluding Canada  1120 Central America  1130 Caribbean and Bermuda  1140 South America  2000 Africa  3000 Asia   42 4000 Europe  5000 Oceania  6000 Antarctica and Adjacent Islands  999 Unknown   Maternal age is a categorical variable based on the mother’s age. In the VSBD, mother’s age is coded in years, as reported on the registration document. It is expressed as the number of completed years (i.e., age as of last birthday preceding delivery). Due to the non-linear relationship between maternal age, SGA birth, and minimum wage workers, this variable was regrouped from a continuous to a categorical variable as following:  Value Meaning 1 less than 20 years old  2 Between 20 and 24 years old  3 Between 25 and 29 years old  4 Between 30 and 34 years old 5 Between 35 and 39 years old   6 40 years or older  9 Unknown    Number of live born children is a categorical variable based on the number of children ever live born. In the VSBD, “Born total ever live born” is a variable indicating the number of children ever live born to this mother, previous to and including this birth event. This excludes fetal deaths or stillbirths. A woman with zero parity has had no live births; a woman of parity 1 has had one live birth, of parity 2, two live births, and so on.   Value  Meaning 1 First live born child 2 Second live born child 3 Third Live born Child 4 Fourth live born child  43 5 Fifth or more live born child 99 Unknown or missing  Marital relation is a categorical variable indicating a regrouped marital status variable. The reporting of the marital status of the mother in the VSBD is inconsistent across provinces with respect to common law status. For instance: In British Columbia, common law partners are submitted to Statistics Canada as “other”. In Alberta, only the legal status of “married” or “not married” is collected. The “not married” option gets converted to “unknown” at Statistics Canada. For Ontario, Yukon Territory and Northwest territories, and any other jurisdiction that collects common-law status, this category is mapped to “unknown” in the VSBD. In Québec, it is reported as the “legal” marital status. Therefore, due to these inconsistencies, this variable was regrouped into “single” , “married” and “other” as below. Under this grouping, the “single” marital status contains only “single” reported marital status across all jurisdictions, the “married” marital status contains only the “legally married” reported marital status across all jurisdictions, while the “other” category contains a mix of partnered and non-partnered mothers (widowed, divorced, separated, common-law, not-married, and unknown) and therefore has limited interpretability.  Value  Meaning  Restrictions  1  Single  A single person is one who has never married, or a person whose marriage has been annulled and who has not remarried.  2  Married  A married person is one who is legally married and not separated.  3  Other  Includes a person whose marital status is common law, widowed, divorced, separated, or unknown  Community size is a categorical variable indicating the size of the community based on the Census Metropolitan Area and Census Agglomeration in terms of the closest census population year. Since data on occupation, earnings or education were unavailable, adjusting for community size would  44 take into consideration the economic and socio-demographic disparities by community size that affect the proportion of minimum wage earners. Value Meaning  1 1,250,000+  2 500,000-1,249,999  3 100,000- 499,999  4 10,000- 99,999 (any CA < 100,000)  5 – Rural  < 10,000 (non-CMACA)   9 Missing   Neighborhood Income Per Single Person Equivalent is a household size-adjusted measure of household income based on census summary data at the Dissemination Area (DA) level and using person-equivalents implied by the low-income cut-offs (LICO). For instance, the 2006 single person equivalents were 1.00 for 1 person, 1.24 for 2 persons, 1.53 for 3 persons, 1.94 for 4 or 5 persons, and 2.44 for 6 or more persons sharing the same household (regardless of age). Within each census metropolitan area (CMA) or census agglomeration (CA) or provincial residual area not in any census metropolitan area or census agglomeration, the dissemination area average IPPE was used to rank all dissemination areas, and then the population was divided into approximate fifths, thus creating community-specific income quintiles based on IPPE (101).  Neighborhood Income Quintile Value  Description  1  Lowest quintile  2  Medium-low quintile  3  Middle quintile  4  Medium-high quintile  5  Highest quintile        9   Missing   45         3.7 Statistical Methodology          3.7.1 Study 1  Using the statistical software Stata version 13.1 (StataCorp, 2013),  data analysis was conducted through 2 steps:  The first step includes descriptive statistics to summarize overall and province specific SGA trends.  This includes time trend graphs to visualize any underlying trend or seasonal patterns in SGA births over time and across provinces. A time trend plot of sex-specific mean birthweight and mean gestational age between 2000 and 2016 was also included to detect any shift in the birthweight distribution over time. Finally, we present univariate summaries (frequency distributions) for maternal and child characteristics between 2000 and 2016. The descriptive statistics cover the following:  - SGA over time and by province  - SGA by income quintile for ON, QC, BC, AB  - Birthweight (sex specific means over time) - Gestational age (mean and frequency distribution over time) - Maternal and child characteristics over time   The second step of this analysis includes logistic regression models to explain the trend in SGA births over time. Since the outcome variable - SGA birth – is a binary variable,  a multiple logistic regression model was used to generate crude odds ratios (ORs) and adjusted ORs with 95% confidence interval (CIs) for selected individual and sociodemographic factors believed to be associated with the outcome SGA births. The inclusion of covariates in the model was based on:  - Previously-reported association with SGA birth in the existing literature  46 - Meaningful changes in the frequency distribution of a potential confounder over time  - Data availability For all analyses, a value of p<0.05 was considered statistically significant.           3.7.2 Study 2           The statistical analysis in study two follows up on the results from study 1.  The first step in this analysis adds the lagged real minimum wage variable to the adjusted model from study 1. The model in this step is not restricted to a specific province or population and rather estimates the effect of adjusting for the lagged real minimum wage on the SGA trend in all Canada.  The rationale for running this full model is to describe associations on a population scale both in terms of size effect and statistical significance.    The second step includes stratified models for Canada’s four largest provinces: Ontario, Quebec, Alberta, and British Columbia. Identical models are run on the four provinces separately to explore any effect modification by province.   The third step includes two subgroup analyses restricted to the populations that are most likely to be affected by minimum wage – mothers residing in low income neighborhoods, as well as single mothers residing in low income neighborhoods.     47 Chapter 4: Results from Study 1  Between 2000 and 2016, 5,941,820 births met our inclusion criteria, of which 449,015 were small for gestational age (7.6%). The following section describes national trends in SGA births over time and by income quintiles.  4.1        National Trends in SGA Births in Canada (2000-2016) 4.1.1 Overall Trend in All SGA Births in Canada (2000-2016) Figure 2 shows an increase in the number of SGA births per 100 singleton live births between 2000 and 2016. Compared to a national SGA proportion of 7.2% in 2000, 8.0% of all singleton live births in 2016 were born SGA.  There is also an unexplained pattern in the rates of SGA births, with lower rates observed every four years in 2000, 2004, 2008 and 2012.              48 Figure 2: SGA Births as a Proportion of All Singleton Live Births in Canada (2000-2016)   4.1.2 SGA Births Across All Provinces and Territories in 2016    Taking a closer look at the most recent SGA rates in Canada, Figure 3 presents the geographic variation in SGA rates in 2016. Across Canada, the highest rate of SGA births is observed in Alberta (8.9%). Yukon comes in next with an SGA rate of 8.2%, however it is worth noting the small population in the territories which may contribute to unstable estimates. While Alberta has the highest rate of SGA births, British Columbia - a neighboring province -  has a markedly lower rate (7.0%). Similarly, in eastern Canada, two of Canada’s largest provinces – 7.2%7.4% 7.4% 7.3% 7.1%7.4% 7.5% 7.4%7.1%7.5% 7.7%7.8% 7.7% 7.9%7.9% 7.9% 8.0%0.00%1.00%2.00%3.00%4.00%5.00%6.00%7.00%8.00%9.00%10.00%2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016SGA Births per 100 Singleton Live Births Calendar Year  49 Ontario and Quebec - have meaningfully different SGA rates. Ontario’s SGA rate in 2016 (8.4%) is noticeably lower than that of its neighboring province - Quebec (7.6%). Figure 3: SGA Births as a Proportion of All Singleton Live Births by Province/Territory in 2016.   4.1.3 SGA Trends by Mother’s Residential Neighborhood Income Quintile  There is a clear gradient from highest to lowest income quintile for trends in SGA births for all live singleton births in Canada from 2000-2015. As expected, and supported by the literature, this graph shows that at all points in time, the lower the neighborhood income quintile, the higher the proportion of SGA births. Furthermore, we notice a stable proportion of SGA births in the lowest  50 income quintile around 9% for the entire period. The lowest point in SGA proportions for this income quintile was in 2008 (8.4%) and the highest in 2015 (9.1%). While the trend in the second lowest income quintiles decreases, and flattens after 2011, it seems to continue trending upwards for the highest income quintiles. For the highest income quintile (income quintile 5), the proportion of SGA births increased from 6.0% in 2008 to 7.0% in 2015. Figure 4: Distribution of SGA Births by Mother’s Residential Neighborhood Income Quintile in Canada (2000-2015)  Note:  Due to quality concerns with the neighborhood income quintile variable in 2016, we limited the results from 2000-2015 inclusive.   8.5%Income Quintile 1, 9.1%7.8%Income Quintile 2, 8.3%6.9%Income Quintile 3, 7.7%6.3%Income Quintile 4, 7.3%5.9%Income Quintile 5, 7.0%0.00%2.00%4.00%6.00%8.00%10.00%2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015SGA Births Per 100 Singleton Live Births Calendar Year Income Quintile 1 Income Quintile 2 Income Quintile 3 Income Quintile 4 Income Quintile 5 51   4.2  Birth Weight and Gestational Age Distribution (2000-2016)    Figure 5 below highlights the mean birth weight for all singleton live births in Canada from 2000 to 2016. The graph shows a relatively stable mean birth weight over time with a slight decline between 2000 and 2016. This trend starts at a mean birth weight of 3442 grams [95% CI: 3440,3444] in 2000, decreasing over time to 3367 grams [95% CI: 3365, 3369] in 2016. Therefore, the mean birthweight for all births in Canada in 2016 was 75 grams less than that in 2000.   Throughout the study period, the mean birthweight for female births was around 100 grams less than that for male births. In terms of trends, the same  slightly declining trend was observed in birthweight for males and females. For male births the mean birth weight appeared to have slightly decreased from 3499 grams [95% CI 3496, 3502] in 2000 to 3421grams [95% CI: 3419, 3424] in 2016. Compared to 2016, the mean birth weight for male births was 78 g less than that in 2000.  For female births, the mean birth weight decreased from 3383 g [95% CI:3380, 3386] in 2016 to 3310 [95% CI: 3307, 3312] in 2000. Therefore, compared to 2000, the mean birth weight for all female births in Canada in 2016 was 73 g less than that in 2000.        52 Figure 5: Trend in Mean Birth Weight for Male, Female, and All Singleton Live Births in Canada (2000-2016)   Due to changes in obstetrical interventions in Canada in recent years, specifically an increase in  early-term and late- preterm deliveries, it is unclear whether the declining trend in mean birthweight ( Figure 5) might be due to a decrease in the mean gestational age. Therefore, the figures below focus on the change in the distribution of all live births as well as all SGA births by gestational age over multiple points in time. Furthermore, to account for differences in the timing of birth, Figure 5 below describes the change in the mean birthweight z-score from 2000-2016.   24002600280030003200340036002000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Birth Weight (grams)Birth YearMean Birthweight for Male births Mean Birthweight for Female BirthsMean Birthweight for All  Births in Canada 53 Figure 6: Distribution of Births by Gestational Age for All Singleton Live Births in Select Years from 2000-2016  Figure 6 above shows notable changes in the proportion of live births for gestational ages 36 -41. Between 2000 and 2016 we notice a shift of 1 week in the distribution of births by gestational age. For instance, in 2000, 31.6% of all singleton live births were born at 40 weeks of gestation. This proportion appears to gradually and consistently decrease to 24.8% in 2016, while the proportion of births with a gestational age of 39 weeks increased from 25.0% to 30.6%. There is also an increase in the share of term births born between 37 and 39 weeks, and a decrease in the share of births born beyond 39 weeks. For preterm births (below 37 weeks of gestation) the proportions in each gestational age remained relatively stable over time.    Further analysis of the mean gestational age by sex also indicates a negligible decrease in the mean gestational age of female births from 39.1 weeks [95% CI: 39.1, 39.1] in 2000 to 38.9 weeks [95%CI: 0.00%5.00%10.00%15.00%20.00%25.00%30.00%35.00%<or =30 31 32 33 34 35 36 37 38 39 40 41 ≥42Proportion of  Gestational Age for All Births by Year2000 2004 2008 2012 2016 54 38.9, 38.9] in 2016. Similarly, for male singleton births, the mean gestational age was 39.0 weeks [95% CI: 39.0, 39.0] in 2000 and 38.8 weeks [95% CI: 38.8, 38.8] in 2016.  Figure 7: Distribution of Births by Gestational Age for All SGA Births in Canada in Select Years from 2000-2016  When focusing specifically on SGA births by gestational age from 2000 to 2016, we notice similar observations and shifts. However, compared to all births (Figure 7 above), the changes in the proportion of SGA births in gestational ages 37, 38, and 40 are more pronounced. Between 2000 and 2016 the proportion of SGA births born at 40 weeks of gestation decreased from 33.5% to 24.6%. Similarly, the increases in the share of SGA births born at 37 and 38 weeks of gestation are more pronounced.   0.00%5.00%10.00%15.00%20.00%25.00%30.00%35.00%<or =30 31 32 33 34 35 36 37 38 39 40 41 ≥42Proportion of  Gestational Age for SGA Births by Year2000 2004 2008 2012 2016 55 Since z-scores were generated for births of the same sex and gestational age, the mean birthweight z-scores described in the figure below accounts for differences in the timing of birth.  Between 2000 and 2016, the mean birthweight z-score for male, female, and all births combined appeared to follow the same modestly declining trend. Overall, mean birthweight z-scores for female births were consistently higher than those of male births over the entire study period. Over time the mean z-score for all births decreased from 0.12 (95% CI: 0.11, 0.12) in 2000 to 0.01 (95% CI: 0.01, 0.01) in 2016. While the change over time is relatively small, the decrease in mean birthweight z-scores suggests a potential decrease in fetal size regardless of changes in gestational age over time. Figure 8: Trend in Mean Birth Weight Z-scores for Male, Female, and All Singleton Live Births in Canada (2000-2016)   -0.010.000.010.020.030.040.050.060.070.080.090.100.110.120.130.141999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Mean Z-Score Birth Year Mean Z-score for All Births Mean Z-score for Male BirthsMean Z-score for Female Births 56 4.3  Distribution of SGA Births by Province/Territory (2000-2016)  Using the mother’s province of residence and birth year, Table 3 below lists the percentage distribution of SGA births across provinces/territories for each birth year. The denominator for each cell is the number of all singleton livebirths in the province and year.    Table 3: SGA births as a Proportion of All Singleton Births by Province and Birth Year (2000-2016)  NFL PEI NS NBR QC ON MB SK AB BC CAN 2000 6.2% 5.7% 7.3% 6.6% 7.1% 7.6% 6.4% 6.6% 7.7% 6.5% 7.2% 2001 6.4% 6.4% 7.5% 6.7% 7.3% 7.8% 6.6% 6.4% 7.8% 7.0% 7.4% 2002 6.5% 6.6% 7.3% 6.9% 7.4% 7.8% 6.7% 6.6% 7.4% 7.0% 7.4% 2003 6.1% 5.1% 6.9% 6.5% 7.2% 7.8% 6.5% 6.7% 7.4% 6.8% 7.3% 2004 6.6% 7.0% 7.0% 6.2% 6.8% 7.6% 6.6% 6.2% 7.5% 6.7% 7.1% 2005 5.6% 6.9% 6.8% 7.4% 7.2% 7.9% 7.0% 6.5% 7.6% 6.8% 7.4% 2006 5.4% 5.5% 7.8% 7.1% 7.4% 7.9% 7.4% 6.6% 7.9% 6.8% 7.5% 2007 5.5% 6.4% 7.3% 6.5% 7.4% 7.8% 7.2% 6.4% 7.8% 6.7% 7.4% 2008 6.2% 4.5% 7.3% 6.1% 6.9% 7.6% 6.5% 6.5% 7.5% 6.4% 7.1% 2009 7.0% 5.8% 7.9% 7.6% 7.5% 7.8% 7.3% 6.8% 7.9% 6.8% 7.5% 2010 7.2% 4.8% 8.0% 6.5% 7.5% 8.2% 7.2% 7.0% 7.9% 6.7% 7.7% 2011 5.9% 5.7% 7.7% 7.3% 8.0% 8.1% 7.6% 6.6% 8.3% 7.1% 7.8% 2012 5.9% 5.5% 7.7% 6.9% 7.5% 8.0% 7.5% 7.0% 8.4% 6.9% 7.7% 2013 6.3% 7.0% 8.0% 7.1% 7.7% 8.1% 7.8% 7.3% 8.8% 6.8% 7.9% 2014 5.9% 5.8% 8.1% 7.1% 7.8% 8.2% 7.5% 7.8% 8.8% 6.8% 7.9% 2015 6.6% 5.4% 7.9% 7.3% 7.8% 8.2% 7.5% 7.8% 8.8% 6.8% 7.9% 2016 6.1% 6.3% 8.0% 6.3% 7.6% 8.4% 7.6% 8.0% 8.9% 7.0% 8.0% When looking at the proportion of SGA births to the total number of singleton live births, we notice variations both across provinces and over time. Table 3 above highlights the annual proportion of SGA births/all singleton livebirths in each province. Across all provinces, Prince Edward Island and Newfoundland and Labrador had the lowest proportion of SGA births over time. In 2008, the proportion of SGA births in PEI was the lowest at 4.5%. While markedly lower than the national SGA proportion, both Prince Edward Island and New Foundland and Labrador have the smallest numbers of live births compared to all other provinces.   57 Table 4: SGA births as a Proportion of All Singleton Births by Territory and Birth Year (2000-2016)   Yukon  Northwest Territories Nunavut Canada 2000 7.0% 4.6% 5.8% 7.2% 2001 6.0% 5.0% 8.2% 7.4% 2002 6.1% 6.5% 4.3% 7.4% 2003 6.2% 6.0% 4.9% 7.3% 2004 5.7% 4.1% 5.5% 7.1% 2005 6.5% 5.8% 5.2% 7.4% 2006 5.6% 5.3% 6.9% 7.5% 2007 2.9% 4.2% 3.9% 7.4% 2008 5.4% 5.9% 6.3% 7.1% 2009 6.9% 5.8% 6.4% 7.5% 2010 5.4% 5.9% 6.2% 7.7% 2011 4.8% 5.2% 4.9% 7.8% 2012 6.0% 5.2% 3.1% 7.7% 2013 5.2% 6.1% 5.0% 7.9% 2014 3.8% 5.4% 5.1% 7.9% 2015 4.8% 3.8% 4.7% 7.9% 2016 8.2% 4.8% 5.7% 8.0%  Among the territories, the proportion of SGA births appears to be lower than the rest of Canada, ranging from 2.9% in the Yukon in 2007 – the lowest - up to 8.2% in Nunavut in 2001 and the Yukon in 2016– the highest. Due to the extremely small number of live births in the territories, fluctuations are easily observed making it harder to detect a stable trend.         58 4.4  Temporal trends in SGA Births in Ontario, Quebec, British Columbia, and Alberta 4.1.4 Overall Temporal Trends in SGA Births    Throughout larger provinces, the highest proportions of SGA births were in Ontario and Alberta. Prior to 2010, Ontario had the highest proportion of SGA births over time. After 2010, there appeared to be a steeper increase in SGA births in Alberta, leading to the highest rates of SGA births nationally with 8.9% in 2016. British Columbia (BC), on the other hand, appeared to have consistently maintained the lowest rates of SGA births among those provinces over the study period. Generally, the proportion of SGA births in BC appeared to be relatively stable with a slight upward trend from 2008-2011. Quebec appeared to follow the same trends as BC, with overall higher levels of SGA.      4.1.5 Trends by Neighborhood Income Quintile      To observe more specific trends within provinces, the figures below focus on SGA births as a proportion of all singleton live births within each of the five neighborhood income quintiles in Canada’s largest provinces from 2000-2015.  Due to quality concerns with the neighborhood income quintile variable in 2016, results are limited to 2000-2015 inclusive.   59 Figure 9: SGA births as a Proportion of All Singleton Live Births 2000-2016 (ON, QC, AB, BC)           Quebec, 7.6%Ontario, 8.4%Alberta, 8.9%British Columbia, 7.0%0.00%1.00%2.00%3.00%4.00%5.00%6.00%7.00%8.00%9.00%10.00%2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Number of SGA Births per 100 Singleton Live Births Calendar Year 60 Figure 10: Side by Side comparison graphs of SGA births by Neighborhood Income Quintile in ON, QC, AB and BC (2000-2015).       Overall, when comparing the four largest provinces, there is a noticeable variation in levels, trends, and gradients. It appeared that the steepest upward trends are particularly noticeable in Alberta, and for a short period of time in Quebec. In terms of gradients, the most noticeable gradient in SGA births over the five neighborhood income quintiles was observed in Ontario, while those in other provinces tended to be narrower and often overlapping. Overall, the lowest two income quintiles appeared to have consistently higher SGA births than the highest two income quintiles.       IQ1, 9.72%IQ2, 8.57%IQ3, 7.96%IQ4, 7.51%IQ5, 6.91%0.00%2.00%4.00%6.00%8.00%10.00%2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015Proportion of  SGA Births by Neighborhood Income Quintile in OntarioIQ1 , 8.66%IQ2 , 8.05%IQ 3 , 7.66%IQ 4 , 7.25%IQ 5 , 7.24%0.00%2.00%4.00%6.00%8.00%10.00%2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015SGA Births by Neighborhood Income Quintile in Quebec IQ 1 , 9.82%IQ2, 9.46%IQ3, 8.51%IQ4, 8.49%IQ5, 7.42%0.00%2.00%4.00%6.00%8.00%10.00%2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015Proportion of  SGA Births by Neighborhood Income Quintile in AlbertaIQ 1 , 7.04%IQ2, 7.65%IQ3, 6.78%IQ4, 6.60%IQ5, 5.50%0.00%2.00%4.00%6.00%8.00%10.00%2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015Proportion of  SGA Births by Neighborhood Income Quintile in British Columbia 61  Ontario:  In Ontario, there is a clear gradient in the proportion of SGA births across the five income quintiles. Consistent over time, the lower the income of the mother’s residential neighborhood, the higher the proportion of SGA births in that neighborhood. In terms of trends, the proportion of SGA births in neighborhoods of the lowest income quintiles in Ontario were stable around 9-10% between 2000 and 2015. Neighborhood income quintiles 3 4 and 5, increased approximately 1% between 2000 and 2015.   Quebec:  In Quebec, the level difference in SGA births between the lowest income quintile and the second lowest income quintile seems much larger than that between any other successive income quintiles. SGA births in income quintiles 3, 4 and 5 seem to be much similar in levels and trends than the lowest income quintile. In addition, the trend in SGA births in the lowest income quintile was mainly stable - lowest 8.3% in 2008 and highest 9.1% in 2011 - around 8% from 2000-2015. Trends in other income quintiles seemed more upward with the most noticeable upward trend between 2008 and 2011 for the second lowest income quintile (from 6.9% to 7.9%) and the highest income quintile (from 6.1% to 7.1%).   Alberta:  Alberta appeared to be one of the provinces with the highest levels of SGA births across the neighborhood income quintiles, and the steepest upward trends post 2008. Alberta, seemed to be similar to Ontario in terms of higher levels of SGA births, and to Quebec in terms of a steep upward trend post 2008. On the other hand, the gradient in Alberta seemed to be less pronounced  62 than other provinces, specifically Ontario. Overall, this gradient ranges from 6.4% in 2000 in the lowest income quintile to 9.8% in the highest neighborhood income quintile in 2015. In terms of trends, both the lowest and highest income quintiles experience steep upward trends from 2008 to 2013. In the lowest neighborhood income quintile, the proportion of SGA births ranged from 7.6% in 2008 to 9.8% in 2013. In the highest income quintile, that proportion ranged from 6.5% in 2008 to 7.9% in 2013.   British Columbia:  British Columbia seems to have the lowest, steadiest SGA proportions across the five neighborhood income quintiles. The range of the gradient in BC is appears to be the lowest among the four provinces, ranging from 5.2% in 2000 to 7.7% in 2015. Contrary to the gradients in other provinces, in BC the second lowest income quintile had higher proportions of SGA births than the lowest income quintile from 2000-2002 and from 2013-2015. More broadly, the gradient seemed harder to identify specifically between 2000-2005 and 2012-2015, where different levels overlapped or had opposing trends. In addition, the level difference between income quintiles 2 and 3 seems larger than any other consecutive levels from 2000-2011. Overall, the trends in BC seemed relatively stable in each neighborhood income quintiles, with some variations between 2012 and 2015.   4.5 Maternal, Paternal and Infant Characteristics over time (2000 vs. 2016)  Table 5 below presents a comparison of frequency distributions for select parental and infant characteristics for all singleton live births as well as SGA births in Canada in 2000 compared to 2016.     63 Table 5: Maternal and Child Characteristics for All Births and SGA births in 2000 compared to 2016 Birth Year All Births in  All Births in SGA Births in SGA Births in Number of Singleton Live Births 2000 (N=318510) 2016 (N=370545) 2000 (N=22985) 2016 (N=29580) Maternal characteristics        Maternal Age       <20  17190 (5.4%) 8380 (2.3%) 1585 (6.9%) 820 (2.8%) 20-24  58265 (18.3%) 44145 (11.9%) 4915 (21.4%) 3880 (13.1%) 25-29  98500 (30.9%) 106465 (28.7%) 6835 (29.7%) 8605 (29.1%) 30-34  93265 (29.3%) 131985 (35.6%) 6015 (26.2%) 9965 (33.7%) 35-39 43640 (13.7%) 66020 (17.8%) 3010 (13.1%) 5200 (17.6%) >or= 40 7610 (2.4%) 13550 (3.7%) 625 (2.7%) 1110 (3.8%) Missing  45 (0.0%) 0 (0.0%) 5 (0.0%) 0 (0.0%) Number of liveborn Children       1 142825 (44.8%) 159785 (43.1%) 12980 (56.5%) 17060 (57.7%) 2 111365 (35.0%) 131310 (35.4%) 6335 (27.6%) 8015 (27.1%) 3 42550 (13.4%) 50755 (13.7%) 2410 (10.5%) 2835 (9.6%) 4 13575 (4.3%) 17035 (4.6%) 790 (3.4%) 950 (3.2%) 5 or more  8150 (2.6%) 11400 (3.1%) 470 (2.0%) 695 (2.4%) Unknown/missing 45 (0.0%) 255 (0.1%) 5 (0.0%) 30 (0.1%) Mother’s Birth Place      Canada 240035 (75.4%) 253435 (68.4%) 15645 (68.1%) 17685 (59.8%) North America, excluding Canada  3820 (1.2%) 3565 (1.0%) 220 (1.0%) 240 (0.8%) Central America  2790 (0.9%) 3940 (1.1%) 185 (0.8%) 260 (0.9%) Caribbean and Bermuda 5330 (1.7%) 4385 (1.2%) 560 (2.4%) 465 (1.6%) South America  3325 (1.0%) 4435 (1.2%) 325 (1.4%) 405 (1.4%) Africa  6080 (1.9%) 17025 (4.6%) 540 (2.4%) 1525 (5.2%) Asia  37055 (11.6%) 62700 (16.9%) 4105 (17.9%) 7450 (25.2%) Europe 14480 (4.6%) 14345 (3.9%) 905 (3.9%) 955 (3.2%) Oceania  920 (0.3%) 705 (0.2%) 105 (0.5%) 50 (0.2%) Missing/unknown 4670 (1.5%) 6010 (1.6%) 400 (1.7%) 545 (1.8%) Father’s Birth Place      Canada 223315 (70.1%) 238240 (64.3%) 13980 (60.8%) 16295 (55.1%) North America, excluding Canada  3660 (1.2%) 3770 (1.0%) 200 (0.9%) 280 (1.0%) Central America  2715 (0.9%) 4080 (1.1%) 180 (0.8%) 275 (0.9%) Caribbean and Bermuda 5940 (1.9%) 5915 (1.6%) 635 (2.8%) 570 (1.9%) South America  3145 (1.0%) 4170 (1.1%) 310 (1.4%) 370 (1.3%) Africa  6685 (2.1%) 17920 (4.8%) 550 (2.4%) 1550 (5.2%) Asia  35205 (11.1%) 58050 (15.7%) 3940 (17.1%) 7005 (23.7%) Europe 16100 (5.1%) 15500 (4.2%) 975 (4.2%) 1035 (3.5%) Oceania  965 (0.3%) 1015 (0.3%) 115 (0.5%) 70 (0.2%) Missing/unknown 20770 (6.5%) 21885 (5.9%) 2095 (9.1%) 2130 (7.2%) Marital relation      Single  85845 (27.0%) 111435 (30.1%) 7175 (31.2%) 9305 (31.5%) Married 196025 (61.5%) 224895 (60.7%) 12925 (56.2%) 17625 (59.6%) Other (Widowed, Divorced, Common-Law, Unknown) 36640 (11.5%) 34215 (9.2%) 2885 (12.6%) 2655 (9.0%) Newborn Characteristics     Sex     Male 163565 (51.4%) 190010 (51.3%) 12175 (53.0%) 15600 (52.7%) Female 154950 (48.7%) 180535 (48.7%) 10810 (47.0%) 13980 (47.3%)  64 Maternal Age:  Under maternal age, there are two things to note. The first is the noticeable shift in the highest proportion of mothers from age group 25-29 (30.9% in 2000) to age group 30-34 (35.6% in 2016). The second noteworthy observation is the drop in the proportion and absolute number of teen mothers. In 2000, the number of births to mothers aged less than 20 years old was 17190 (5.4%). This number and proportion dropped by almost half in 2016 (8380, 2.3%). Similarly, for age group 20-24, there is a noticeable drop in the number of births to mothers of this age group from 58265 (18.3%) in 2000 to 44145 (11.9%) in 2016. Hence, we can note reductions of teen mothers and a shift in the age group distribution of mothers between 2000 and 2016, which is in line with the increase in advanced maternal age reported in the literature.   As for SGA births, the changes in the distribution of births between 2000 and 2016 are similar to that observed for all births with some differences. For instance, we notice higher proportions of SGA births for mother’s age group <20 and 20-24 for both years than those for all births. This aligns with the evidence on younger (specifically teenage) maternal age as a risk factor for SGA births. Furthermore, the proportion of SGA births born to mothers aged 35-39 years old markedly increased from 13.1% in 2000 to 17.6% in 2016. For SGA births born to mothers with advanced maternal age (>=40 years old) both the proportion and number of SGA births increased from 625 SGA births (2.7%) in 2000 to 1110 (3.8%) in 2016.   Number of live-born children:  Under number of live-born children, the first thing to notice is a substantial difference in the distribution of all births vs. SGA births. Specifically, the proportion of all births born to mothers having their first live-born child ranged from 44.8% in 2000 to 43.1% in 2016, while that of SGA  65 births ranged from 56.7% in 2000 and 57.7% in 2016. These numbers are not surprising considering that this variable is a proxy measure of parity and nulliparous mothers are at higher risks of an SGA birth.  Mother’s birth place:  The distribution of births by a mother’s place of birth – a proxy for immigration – has had key changes between 2000 and 2016. As expected, the share of births to Canadian born mothers has declined from 75.36% in 2000 to 68.40% in 2016. This observation can be explained by Canada’s inclusive policies on immigration over the years. To be more specific, the highest uptake was to African- and Asian-born mothers. Births to African-born mothers have more than doubled between 2000 (6685) and 2016 (17920). Similarly, births to Asian-born mothers have markedly increased from 35205 in 2000 to 58050.  As for SGA births, while the change over time is in line with that for all births, there appears to be noticeably higher proportions of SGA births for Asian-born mothers. For instance, in 2000, 11.63% of all births were born to Asian-born mothers compared to 17.9% of SGA births. In 2016, 25.0% of SGA births were born to Asian-born mothers, although only 15.7% of all births in that year had Asian-born mothers.  Father’s birth place and mother’s marital status:  The changes under father’s birthplace are strongly in line with those of mother’s birthplace - both in change over time and distribution - which may also support possible couples’ immigration. As for the mother’s marital status, between 2000 and 2016, both the number and share of births to single mothers have increased from 85845 (27%) in 2000 to 111435 (30%) in 2016. These numbers may be  66 of potential concern considering the burden on the mother, and the higher risks of adverse birth outcomes associated with being single.   For SGA births, we notice three observations. The first is that the share of SGA births born to single mothers is higher than that of all births for both years. Under single mothers, there is minimal change in the proportion of SGA births over time. On the other hand, the opposite is occurring for legally married women: while the share of all births remained the same between 2000 and 2016, that of SGA births seems to have markedly changed. Between 2000 and 2016, the proportion of SGA births born to legally married mothers increased from 56.2% to 59.6%.  Sex of newborn:  There is an almost negligible change over time for sex of the newborn. Between 2000 and 2016, the share of males of both all births and SGA births was slightly higher than that of females. Compared to all births, it appears that a slightly higher proportion of SGA births are born male than female.            67 4.6  Regression Model Results (Crude and Adjusted)       4.1.6 Crude Analysis  Under this crude analysis, the unadjusted odds of an SGA birth is reported from 2000 to 2016 (reference year: 2000).    Figure 11: Unadjusted Trend in SGA Births in Canada from 2000-2016   Since the results of the descriptive analysis of SGA trends over time showed a non-linear trend, calendar year was used as an indicator variable rather than a continuous variable. In addition, using an indicator variable for birth year allows us to better visualize and understand the trend by observing annual differences. Figure 11 is a plot of the odds ratios (OR) of SGA births over time, 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Unadjusted Odds Ratio 1.00 1.03 1.03 1.01 0.99 1.02 1.04 1.03 0.99 1.05 1.06 1.09 1.07 1.10 1.10 1.11 1.12[95% Conf. 1.01 1.01 0.99 0.97 1.01 1.03 1.01 0.97 1.03 1.05 1.07 1.05 1.08 1.08 1.09 1.10Interval] 1.05 1.05 1.03 1.01 1.04 1.06 1.05 1.01 1.06 1.08 1.11 1.09 1.12 1.12 1.13 1.140.800.850.900.951.001.051.101.151.20Unadjusted Odds Ratio of an SGA Birth Unadjusted Odds Ratio [95% Conf. Interval]Ref 68 with 2000 as the reference year. Generally, there was an upward trend in the odds of an SGA birth compared to 2000. Specifically:   1. The odds of an SGA birth in 2016 compared to 2000 was 1.12, 95% CI [1.10, 1.14]. That is, the odds of an SGA births in 2016 was 12% higher than that in 2000.  2. The lowest ORs were observed in 2004 and 2008, with 0.99 [95% CI: 0.97, 1.01] and 0.99 [95% CI: 0.97, 1.01] respectively. In addition, the odds of an SGA birth in 2003, 2004, and 2008 were not significantly different from the odds in 2000. 3. There is a drop in the ORs every 4 years. Compared to the years before or after, we notice that 2000, 2004, 2008 and 2012 have lower odds.  4. Compared to 2000, the period between 2000-2008, has lower odds ratios than the period from 2009-2016. Compared to 2000, the odds of an SGA birth born between 2009-2016 are 5-12% higher than if born 2000.           4.1.7 Adjusted Trends          The tables that follow outline the results of multiple logistic regression models with “SGA Birth” as the binary dependent variable and “Year” as the main independent indicator variable. Key assumptions of logistic regression (binary dependent variable, independent observations, little or no collinearity among independent variables) were verified for all models. The models also adjusted for other important and independent predictors of SGA births based on the existing literature for known SGA risk factors. The final model adjusted for mother’s birthplace, father’s birthplace, marital status, maternal age, number of live-born children, community size, and income quintile.     69 Table 6: Multiple Logistic Regression Model Results for all live singleton births in Canada (2000-2016) Logistic regression                                   Number of Obs   =    5941815                                                        LR chi2(57)     =   71248.24                                                         Prob > chi2     =     0.0000  Log likelihood = -1555653.1                           Pseudo R2       =     0.0224       SGA Birth  OR SE z P>z [95% Conf. Interval] Year (Ref: 2000)             2001 1.03 0.01 3.44 0.00 1.01 1.05 2002 1.03 0.01 2.83 0.01 1.01 1.05 2003 1.00 0.01 0.44 0.66 0.98 1.02 2004 0.98 0.01 -2.39 0.02 0.96 1.00 2005 1.01 0.01 1.09 0.28 0.99 1.03 2006 1.03 0.01 3.10 0.00 1.01 1.05 2007 1.02 0.01 1.79 0.07 1.00 1.04 2008 0.97 0.01 -2.77 0.01 0.96 0.99 2009 1.03 0.01 3.09 0.00 1.01 1.05 2010 1.02 0.01 2.18 0.03 1.00 1.04 2011 1.07 0.01 7.69 0.00 1.05 1.09 2012 1.04 0.01 4.49 0.00 1.02 1.06 2013 1.07 0.01 7.25 0.00 1.05 1.09 2014 1.07 0.01 7.72 0.00 1.05 1.09 2015 1.08 0.01 8.01 0.00 1.06 1.10 2016 1.08 0.01 7.88 0.00 1.06 1.10 Mother’s Birth Place (Ref: Canada)           Missing/unknown 1.16 0.01 11.31 0.00 1.13 1.19 North America, excluding Canada  1.03 0.02 1.65 0.10 0.99 1.06 Central America  1.09 0.02 4.81 0.00 1.05 1.14 Caribbean and Bermuda 1.40 0.02 23.86 0.00 1.36 1.44 South America  1.29 0.02 15.95 0.00 1.25 1.33 Africa  1.26 0.02 17.58 0.00 1.23 1.29 Asia  1.38 0.01 42.90 0.00 1.36 1.40 Europe 1.03 0.01 3.43 0.00 1.01 1.05 Oceania  1.47 0.05 12.57 0.00 1.38 1.56 Father’s Birth Place (Ref: Canada)        Missing/unknown 1.29 0.01 41.36 0.00 1.27 1.30 North America, excluding Canada  1.03 0.02 1.75 0.08 1.00 1.06 Central America  1.12 0.02 6.17 0.00 1.08 1.17 Caribbean and Bermuda 1.33 0.02 21.48 0.00 1.30 1.37 South America  1.31 0.02 16.50 0.00 1.27 1.35 Africa  1.15 0.01 10.79 0.00 1.12 1.18 Asia  1.52 0.01 54.69 0.00 1.50 1.55 Europe 1.00 0.01 0.30 0.77 0.98 1.02 Oceania  1.34 0.04 9.98 0.00 1.26 1.41 Marital Status (Ref: Married)             Single  1.26 0.01 57.13 0.00 1.25 1.27 Other  1.23 0.01 39.37 0.00 1.21 1.24 Maternal Age (ref: 25-29)           <20  0.96 0.01 -5.56 0.00 0.94 0.97  70   Mother and Father’s Country of Birth:   Controlling for year of birth, father’s country of birth, marital status, number of liveborn children, income quintile, and community size, births to mothers born anywhere except in North America have significantly higher odds of an SGA birth than births to Canadian-born mothers. The highest odds were for births to mothers born in Oceania (OR 1.47 95%CI 1.38, 1.56), in the Caribbean or Bermuda (OR 1.40 95%CI 1.36, 1.44), or in Asia (OR 1.38 95%CI 1.36, 1.40).   For father’s country of birth, births to European or North American fathers did not have statistically significant higher odds ratios compared to Canadian born father, when controlling for year of birth, 20-24  1.06 0.01 11.55 0.00 1.05 1.07 30-34  1.01 0.00 1.28 0.20 1.00 1.01 35-39 1.07 0.01 12.71 0.00 1.06 1.08 >or= 40 1.17 0.01 17.17 0.00 1.15 1.19 Missing  1.22 0.21 1.15 0.25 0.87 1.71 Number of live-born Children (Ref: 1)             2 0.57 0.00 -150.96 0.00 0.57 0.58 3 0.54 0.00 -111.75 0.00 0.54 0.55 4 0.56 0.00 -65.89 0.00 0.55 0.57 5 or more  0.58 0.01 -50.13 0.00 0.57 0.59 Unknown/missing 0.98 0.06 -0.34 0.74 0.86 1.11 Community Size (ref: 1,250,000+)        500,000-1,249,999  1.02 0.00 4.58 0.00 1.01 1.03 100,000- 499,999  0.96 0.00 -7.69 0.00 0.95 0.97 10,000- 99,999  0.98 0.01 -3.74 0.00 0.97 0.99 < 10,000 (rural)   0.97 0.01 -6.00 0.00 0.96 0.98 Missing  1.03 0.02 1.38 0.17 0.99 1.08 Income Quintile (Ref: 5)             1 (Lowest) 1.19 0.01 31.74 0.00 1.17 1.20 2 1.12 0.01 21.22 0.00 1.11 1.14 3 1.07 0.01 13.02 0.00 1.06 1.09 4 1.03 0.01 6.05 0.00 1.02 1.05 Missing/Unknown  1.07 0.01 4.53 0.00 1.04 1.10               _cons 0.07 0.00 -292.21 0.00 0.07 0.07  71 mother’s country of birth, marital status, number of liveborn children, income quintile, and community size.   Similar to mother’s country of birth, births to fathers born in the Caribbean or Bermuda, South America, Asia, Africa, Central America and Oceania had significantly higher odds of an SGA birth than births to Canadian born fathers. Compared to the odds of an SGA birth to a Canadian born father, births to Asian born fathers had 52% higher odds (95% CI 1.50, 1.55), and 31-34% higher odds for fathers born in South America (OR 1.31, 95% CI 1.27,1.35), Caribbean or Bermuda (OR 1.33, 95% CI 1.30, 1.37), or Oceania (OR 1.34, 95% CI 1.26,1.41). On the other hand, the magnitude of the estimate seems to be different from that of mother’s country of birth.   When comparing the odds of an SGA birth by mother or father’s country of birth we notice different size effects by parents of the same country of birth. For instance, births to Asian born mothers have 1.38 times the odds of an SGA birth (95%CI 1.36, 1.40) compared to Canadian born mothers. On the other hand, births to Asian born fathers have 1.52 times (95%CI 1.50, 1.55) the odds of an SGA birth compared to Canadian born fathers. Additionally, an African born mother has 26% higher odds (95% CI 1.23, 1.29) of an SGA birth compared to a Canadian born mother, while an African born father has 15% higher odds of an SGA birth (95 % CI 1.12, 1.18) compared to a Canadian born father.  Marital Status:  For marital status, single mothers had 26% higher odds of an SGA birth [95% CI: 1.25, 1.27] compared to a married mother, controlling for year of birth, mother and father’s country of birth, maternal age, number of liveborn children, community size and income quintile. Similarly, mothers  72 whose marital status is widowed, divorced, common law or unknown also had 22% higher odds of an SGA birth [95% CI:1.21, 1.24] compared to legally married mothers (controlling for the same variables). These results indicate a protective effect of legally married mothers against higher odds of an SGA birth.  Maternal Age: The relationship between maternal age and the risks of an SGA birth was non-linear. Births to mothers whose age was less than 20 had only 4% lower odds of an SGA birth [95% CI 0.94, 0.97] than births to mothers in the age of 25-29 years when controlling for year of birth, mother and father’s country of birth, marital status, number of liveborn children, community size and income quintile. Alternatively, births to mothers whose age was between 20-24 years had 6% higher odds of an SGA birth (p-value =0.00) compared to mothers in the age group 25-30, and adjusting for all other confounders. We also find comparable odds of SGA births for mother’s age category 30-34 compared to mothers in the age group of 25-29. On the other hand, the highest odds of an SGA birth were for mothers in the age group of 40 years or more [OR=1.17, 95% CI:1.15, 1.19].  Number of Live-born children:  As the number of live-born children increased, the odds of an SGA birth decreased. While having the first live-born child had higher odds of an SGA birth than any other group, the lowest odds were for 3rd order births who had 46% lower odds of an SGA birth [95% CI: 0.54, 0.55] than 1st order births.     73 Community size:  Compared to births in a community size greater than 1,250,000, births in a community size ranging from 500,000 to 1,249,999 had 1.02  higher odds of an SGA birth [95% CI: 1.01, 1.03]. On the other hand, all other communities with less than 100,000 had slightly lower odds (2-4%)of an SGA birth than those born in the largest community size (>1,250,000), adjusting for all other variables.   Income Quintile:  Income quintile had a clear gradient in the odds of an SGA birth when controlling for all other variables.  Compared to the highest neighborhood income quintile, births in the lowest income quintile had 19% higher odds of an SGA birth [95% CI: 1.17, 1.20]. As the income quintile increased, the odds of an SGA birth gradually decreased.   The figure below visualizes the crude and adjusted SGA trends. We notice that adjusting for parental birth place, marital status, maternal age, number of live-born children, and community size attenuated the trend over time but did not completely explain or eliminate it. The effect size of the controlled variables seemed to also vary by calendar year. Specifically, the reduction in the ORs appears to be more noticeable after 2009. For instance, compared to 2000, the odds of an SGA birth in 2010 was 2% higher (95% CI 1.00, 1.04), while the crude odds for the same year was 6% higher (95% CI 1.05, 1.08). Between 2000 and 2009, the crude and adjusted SGA trends appear to be similar.     74 Figure 12: Comparison of Adjusted vs. Unadjusted SGA Trends from 2000-2016 (reference year: 2000)   0.800.850.900.951.001.051.101.151.201999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Odds Ratio of an SGA BirthCalendar YearUnadjusted SGA Trend Adjusted SGA Trend 75 Chapter 5: Results from Study 2          5.1 Trends in Minimum Wages (2000-2016)       Figure 13 shows the annual mean nominal minimum wage, real minimum wage (in 2016 constant dollars) and real minimum wage lagged 9 months for all of Canada. Without adjusting for inflation, we see that the nominal minimum wage steadily increased from 6.24 CAD in 1999 to 9.99 CAD in 2012. Between 2012 and 2016 the trend seems to be flatter than the one before, ranging from 9.99 CAD in 2012 to 11.08 CAD in 2016.    Figure 13: Trends in Nominal, Real and Lagged Real Minimum Wage (2016 Constant Canadian Dollars) from 2000-2016    0.002.004.006.008.0010.0012.002000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Canadian  Dollars Calendar YearNominal Minimum Wage Real Minimum Wage Lagged 9 Months Real Minimum Wage (2016 Constant Dollars) 76 Looking at the change in the annual mean real minimum wage (adjusted for inflation in 2016 Canadian dollars), we notice three different trends:  - Between 1999 and 2008, the real minimum wage was relatively stable ranging from 8.60 in 1999 to 9.06 CAD in 2008 - Between 2008 and 2012, the increase in real minimum wage was the greatest , increasing from 9.06 in 2008 to 10.55 in 2013.  - Between 2013 and 2016, the increase in real minimum wage was small gradually rising tog 11.08 in 2016.   Overall, the real minimum wage ranged from 8.51CAD in 2000 to 11.08 CAD in 2016. The trend in the lagged real minimum wage is expectedly very similar to that of the real minimum wage, yet slightly lower between 2008 and 2010 and in 2016.   5.1.1 Provincial Trends in Nominal and Real Minimum Wage Looking at the real minimum wage (lagged 9 months) across Canada’s four largest provinces, we notice  different trends.  - As with the trend in the mean minimum wage in Canada, Ontario follows a similar trend over 3 divided periods of stability, slight upward trend that starts to decrease and level off from 2011 to 2016.  - Alberta had a stable to a slightly declining trend between 2000 and 2005, followed by a steeper upward trend between 2005 and 2010 (from 7.50 to 9.74), after which the trend levels off reaching 10.75 in 2016.  - Quebec seemed to have the most stability in its minimum wage for the entire period between 2000-2016. However, we do notice a jump in its minimum wage from 9.34 in 2010  77 to 10.20 CAD in 2011. Overall, Quebec’s real minimum wage increased from 9.18 CAD in 2000 to 10.54 CAD in 2016.  - British Columbia’s trend in real minimum wage appears to differ from those in other provinces. Between 2000 and 2003, real minimum wage in BC appeared to increase slightly. From 2003 to 2011, the real minimum wage consistently declined from 9.74 in 2003 to 8.57 in 2011. Between 2011 and 2013, BC’s real minimum wage increased to 10.60 CAD, and thereafter remained relatively stable.  In terms of absolute dollars, Alberta had the lowest real minimum wage compared to Ontario, BC and Quebec for the entire period (2000-2016). BC started off with the highest level of minimum wage until 2006. From 2006 to 2016, Ontario had the highest level of real minimum wage. Between 2013 and 2016 all four provinces had very similar  real minimum wages.                      78 Figure 14: Real Minimum Wage in Ontario, Quebec, Alberta, and British Columbia (2000-2016)    5.2 Model Results for All Singleton Live Births in Canada (Adjusting for Minimum wage)  After adding a province level real and lagged minimum wage variable to our model, we find that a dollar increase in real lagged minimum wage in Canada was associated with a small, but statistically significant 2% lower odds of an SGA birth [95% CI 0.97, 0.98], adjusting for birth year, mother and father’s country of birth, marital status, number of liveborn children, maternal age, community size and income quintile. In order to allow for the potential of income quintile to act as a confounder rather than an intermediary variable along the pathway to SGA, the same analysis on all births from 2000-2016 including the variable income quintile was repeated. The estimates and results were the same as those in the model above (Appendix A).  Adding the real minimum wage variable to the model changed the odds ratios of the time trend variable, but did not affect any other maternal and contextual risk factors.  0246810122000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Real Minimum Wage (2016 Constant Dollars, Lagged  9 Months)Calendar YearAlberta British Columbia Ontario Quebec 79  Table 7: Regression Model Results for All Singleton Births in Canada (with real lagged minimum wage) Logistic regression     Number of observations= 5,939,250         LR chi2(53) = 69951.4         Prob > chi2 = 0 Log likelihood = -1555721.8     Pseudo R2 = 0.022   SGA Birth  OR SE z P>z [95% Conf. Interval] Lagged Real MW 0.98 0.00 -6.96 0.00 0.97 0.98 Year (Ref: 2000)           2001 1.03 0.01 2.95 0.00 1.01 1.05 2002 1.02 0.01 2.21 0.03 1.00 1.04 2003 0.99 0.01 -0.56 0.58 0.98 1.01 2004 0.96 0.01 -3.64 0.00 0.95 0.98 2005 1.00 0.01 -0.19 0.85 0.98 1.02 2006 1.02 0.01 1.99 0.05 1.00 1.04 2007 1.01 0.01 0.98 0.33 0.99 1.03 2008 0.97 0.01 -3.35 0.00 0.95 0.99 2009 1.03 0.01 3.47 0.00 1.01 1.05 2010 1.03 0.01 3.17 0.00 1.01 1.05 2011 1.10 0.01 9.25 0.00 1.08 1.12 2012 1.06 0.01 6.26 0.00 1.04 1.09 2013 1.10 0.01 8.97 0.00 1.07 1.12 2014 1.10 0.01 9.37 0.00 1.08 1.12 2015 1.11 0.01 9.68 0.00 1.08 1.13 2016 1.11 0.01 9.94 0.00 1.09 1.13 Mother’s Birth Place (Ref: Canada)         Missing/unknown 1.17 0.02 12.32 0.00 1.14 1.20 North America, excluding Canada  1.03 0.02 1.64 0.10 0.99 1.06 Central America  1.11 0.02 5.65 0.00 1.07 1.15 Caribbean and Bermuda 1.44 0.02 25.61 0.00 1.40 1.48 South America  1.31 0.02 16.98 0.00 1.27 1.35 Africa  1.29 0.02 19.83 0.00 1.26 1.33 Asia  1.41 0.01 45.78 0.00 1.39 1.43 Europe 1.04 0.01 4.13 0.00 1.02 1.06 Oceania  1.48 0.05 12.90 0.00 1.40 1.58 Mother’s Birth Place (Ref: Canada)      Missing/unknown 1.31 0.01 44.26 0.00 1.29 1.33 North America, excluding Canada  1.03 0.02 1.86 0.06 1.00 1.07 Central America  1.14 0.02 7.06 0.00 1.10 1.19 Caribbean and Bermuda 1.36 0.02 23.24 0.00 1.33 1.40 South America  1.33 0.02 17.50 0.00 1.29 1.37 Africa  1.17 0.02 12.39 0.00 1.14 1.20 Asia  1.55 0.01 57.20 0.00 1.53 1.57 Europe 1.01 0.01 0.91 0.36 0.99 1.03 Oceania  1.34 0.04 10.17 0.00 1.27 1.42 Marital Status (Ref: Legally Married)            80 Single  1.28 0.01 60.51 0.00 1.27 1.29 Other (Widowed, Divorced, Common-Law, Unknown) 1.25 0.01 42.52 0.00 1.23 1.26 Maternal Age (ref: 25-29)         <20  0.97 0.01 -3.17 0.00 0.96 0.99 20-24  1.07 0.01 14.16 0.00 1.06 1.08 30-34  1.00 0.00 -1.07 0.28 0.99 1.00 35-39 1.05 0.01 9.99 0.00 1.04 1.06 >or= 40 1.15 0.01 15.40 0.00 1.13 1.17 Missing  1.18 0.21 0.95 0.34 0.84 1.66 Number of Liveborn Children (Ref: 1)           2 0.57 0.00 -150.45 0.00 0.57 0.58 3 0.55 0.00 -110.46 0.00 0.54 0.55 4 0.57 0.01 -64.13 0.00 0.56 0.58 5 or more  0.59 0.01 -47.58 0.00 0.58 0.61 Unknown/missing 0.99 0.06 -0.08 0.94 0.88 1.13 Community Size (ref: 1,250,000+)     500,000-1,249,999  1.02 0.00 3.45 0.00 1.01 1.03 100,000- 499,999  0.97 0.00 -7.08 0.00 0.96 0.97 10,000- 99,999  0.98 0.01 -4.18 0.00 0.96 0.99 < 10,000 (rural)   0.96 0.01 -7.24 0.00 0.95 0.97 Missing  1.01 0.02 0.46 0.65 0.97 1.05        When comparing the trends after adjusting for minimum wage, adjusting for minimum wage tends to further increase or decrease the size of the variation in the odds depending on the time-period observed. For instance, compared to the trend adjusting for SGA risk factors, adding minimum wage further reduced the odds of an SGA birth between 2002 and 2008. On the other hand, between 2010 and 2016, adjusting for minimum wage further increased the odds of an SGA birth (compared to the adjusted model). Between 2011 and 2016, the SGA trend adjusting for real minimum wage appears to be the same as the unadjusted SGA trend.      81 Figure 15: SGA Trends Crude and Adjusted Models (All Singleton Live Births in Canada, 2000-2016)     5.3 Stratified Model Results for Ontario, Quebec, BC, and Alberta     For each of the four provinces, the tables below present the results of a multiple logistic regression model adjusting for real and lagged minimum wage, birth year, mother’s birthplace, father’s birthplace, relationship status, maternal age, number of live-born children, community size. The odds ratios for the two variables (real and lagged minimum wage and birth year) in each province: are presented to interpret two relations:  - The association between minimum wage and SGA birth in each province.  0.800.850.900.951.001.051.101.151.201999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Odds RatioORs, UnadjustedORs, Adjusting for SGA Risk FactorsORs, Adjusting for SGA Risk Factors and Real Lagged Minimum Wage 82 - The effect of adding minimum wage to the model on the overall adjusted trend in each province.   The following section includes an examination and comparison of the trends for the crude and adjusted ORs of SGA birth in each province.   When stratifying by the four provinces, the association between real minimum wage (lagged 9 months) varied by province, but for all provinces this association was non-significant (p-value> 0.05). The same models were repeated adjusting for “neighborhood income quintile” as well, to allow for this variable to act as a potential confounder. The results (Appendix B,C, D and E) were consistent/essentially the same as those listed below.   5.3.1 Results in Ontario   In Ontario, the results show a non-significant association between a dollar increase in real minimum wage and the odds of an SGA birth (OR 0.984, [95% CI 0.96, 1.01]), adjusting for birth year, mother’s birthplace, father’s birthplace, relationship status, maternal age, number of live-born children, and community size. The change in the trend of SGA births (mainly upward) after adding real minimum wage to the adjusted model is non-significant for all years except from 2011-2016.  Table 8: Multiple Logistic Regression Model Results in Ontario Logistic regression     Number of observations= 2,242,095         LR chi2(53) = 33079.42         Prob > chi2 = 0 Log likelihood = -604681.12     Pseudo R2 = 0.0266  SGA Birth  Odds Ratio Std. Err. z P>z [95% Conf. Interval] Real Minimum Wage (Lagged 9 months) 0.98 0.01 -1.18 0.24 0.96 1.01  83 Birth Year (Ref: 2000)       2001 1.02 0.02 1.33 0.18 0.99 1.05 2002 1.01 0.02 0.80 0.42 0.98 1.05 2003 0.99 0.02 -0.26 0.79 0.96 1.03 2004 0.97 0.02 -1.81 0.07 0.93 1.00 2005 1.00 0.02 0.07 0.95 0.97 1.04 2006 1.01 0.02 0.64 0.52 0.98 1.04 2007 1.01 0.02 0.44 0.66 0.98 1.04 2008 0.99 0.02 -0.95 0.34 0.96 1.02 2009 1.01 0.02 0.79 0.43 0.98 1.05 2010 1.04 0.03 1.68 0.09 0.99 1.09 2011 1.09 0.03 2.82 0.01 1.03 1.15 2012 1.06 0.03 2.26 0.02 1.01 1.11 2013 1.08 0.03 3.00 0.00 1.03 1.13 2014 1.08 0.02 3.55 0.00 1.04 1.13 2015 1.10 0.03 3.70 0.00 1.05 1.15 2016 1.13 0.03 4.84 0.00 1.07 1.18        5.3.2 Results in British Columbia  Similar to the results in Ontario, the association between real minimum wage (lagged 9 months) in BC was not significantly associated with the odds of an SGA birth (p-value = 0.82), adjusting for birth year, mother’s birthplace, father’s birthplace, relationship status, maternal age, number of live-born children, and community size. The change in the trend of SGA births after adding real minimum wage to the adjusted model was mainly non-significantly different from 2000, with the exception of 2001, 2002, and 2011.  Table 9: Multiple Logistic Regression Model Results in British Columbia Logistic regression     Number of observations   = 703,290          LR chi2(51)= 9896.79          Prob > chi2= 0 Log likelihood = -169611.61      Pseudo R2= 0.0283  SGA Birth  Odds Ratio Std. Err. z P>z [95% Conf. Interval] Real Minimum Wage (Lagged 9 months) 0.99 0.03 -0.23 0.82 0.94 1.05 Birth Year (Ref: 2000)       2001 1.09 0.03 3.16 0.00 1.04 1.16 2002 1.09 0.03 2.81 0.01 1.03 1.16  84 2003 1.06 0.03 1.75 0.08 0.99 1.13 2004 1.03 0.03 0.98 0.33 0.97 1.09 2005 1.03 0.03 1.00 0.32 0.97 1.09 2006 1.05 0.03 1.59 0.11 0.99 1.11 2007 1.03 0.03 1.03 0.30 0.97 1.09 2008 0.98 0.03 -0.63 0.53 0.92 1.04 2009 1.04 0.03 1.14 0.26 0.97 1.11 2010 1.02 0.03 0.67 0.50 0.96 1.09 2011 1.08 0.04 2.37 0.02 1.01 1.16 2012 1.05 0.03 1.83 0.07 1.00 1.12 2013 1.05 0.05 1.09 0.28 0.96 1.16 2014 1.05 0.05 0.89 0.37 0.95 1.15 2015 1.05 0.05 1.10 0.27 0.96 1.15 2016 1.07 0.05 1.51 0.13 0.98 1.17        5.3.3 Results in Alberta  In Alberta, the results also show a non-significant relationship between SGA and minimum wage. A dollar increase in real minimum wage in Alberta (lagged 9 months) was associated with the same (OR 1.01) odds of SGA birth [95% CI: 0.98, 1.04], adjusting for birth year, mother’s birthplace, father’s birthplace, relationship status, maternal age, number of live-born children, community size, and income quintile. The change in the trend of SGA births after adding real minimum wage to the adjusted model was also non-significant for all years, except in 2008.   Table 10: Multiple Logistic Regression Model Results in Alberta Logistic regression     Number of observations= 781,665          LR chi2(51)= 10661.47          Prob > chi2= 0 Log likelihood = -214178.62      Pseudo R2= 0.024  SGA Birth  Odds Ratio Std. Err. z P>z [95% Conf. Interval] Real Minimum Wage (Lagged 9 months) 1.01 0.02 0.70 0.48 0.98 1.04 Birth Year (Ref: 2000)       2001 1.01 0.03 0.48 0.63 0.96 1.07 2002 0.95 0.03 -1.65 0.10 0.90 1.01 2003 0.95 0.03 -1.54 0.12 0.90 1.01 2004 0.95 0.03 -1.59 0.11 0.89 1.01 2005 0.98 0.03 -0.76 0.45 0.92 1.04 2006 0.99 0.03 -0.39 0.69 0.94 1.04 2007 0.97 0.03 -1.24 0.22 0.92 1.02 2008 0.92 0.02 -3.08 0.00 0.87 0.97 2009 0.95 0.03 -1.59 0.11 0.90 1.01  85 2010 0.95 0.03 -1.62 0.11 0.89 1.01 2011 1.00 0.03 -0.09 0.93 0.94 1.06 2012 0.98 0.03 -0.49 0.62 0.92 1.05 2013 1.03 0.04 0.75 0.45 0.96 1.10 2014 1.01 0.04 0.21 0.83 0.94 1.09 2015 1.01 0.04 0.36 0.72 0.94 1.09 2016 1.00 0.04 0.09 0.93 0.92 1.09             5.3.4 Results in Quebec         Quebec has similar results to Alberta, where the minimum wage had a non-significant association with SGA births. In Quebec, a dollar increase in real minimum wage was associated with 1.05 odds of an SGA birth [95% CI: 0.985, 1.119], adjusting for birth year, mother’s birthplace, father’s birthplace, relationship status, maternal age, number of live-born children, and community size. The change in the trend of SGA births after adding real minimum wage to the adjusted model was non-significantly different from 2000 for all years except in 2002, 2006, 2007, 2009, 2010, and 2011.    Table 11: Multiple Logistic Regression Model Results in Quebec Logistic regression     Number of observations= 1,350,040          LR chi2(52)= 11525.34          Prob > chi2= 0 Log likelihood = -351669.54      Pseudo R2= 0.0161  SGA Birth  Odds Ratio Std. Err. z P>z [95% Conf. Interval] Real Minimum Wage (Lagged 9 months) 1.05 0.03 1.47 0.14 0.98 1.12 Birth Year (Ref: 2000)       2001 1.04 0.02 1.99 0.05 1.00 1.09 2002 1.06 0.02 2.65 0.01 1.02 1.11 2003 1.02 0.02 0.80 0.43 0.97 1.07 2004 0.97 0.02 -1.42 0.16 0.93 1.01 2005 1.02 0.02 0.88 0.38 0.98 1.07 2006 1.06 0.02 2.57 0.01 1.01 1.11 2007 1.06 0.02 2.75 0.01 1.02 1.11 2008 0.97 0.02 -1.26 0.21 0.94 1.01 2009 1.05 0.02 2.45 0.01 1.01 1.10 2010 1.06 0.02 2.94 0.00 1.02 1.10 2011 1.09 0.04 2.28 0.02 1.01 1.18 2012 1.02 0.04 0.50 0.61 0.95 1.09 2013 1.04 0.04 1.09 0.28 0.97 1.13  86 2014 1.05 0.05 1.02 0.31 0.96 1.14 2015 1.04 0.05 0.80 0.42 0.95 1.13 2016 1.01 0.05 0.24 0.81 0.92 1.11         5.4 Subgroup Analyses           5.4.1 Lowest Neighborhood Income Quintile   This subpopulation included 1,333,820 singleton births, of which 118,005 (8.8%) were small for gestational age. The results of the first subgroup analysis show that for infants born to mothers residing in the lowest neighborhood income quintile, a dollar increase in real minimum wage 9 months prior to the birth was not significantly associated with the odds of an SGA birth [OR 1.01, 95% CI: 1.00, 1.02], adjusting for birth year, mother and father’s country of birth, marital status, number of liveborn children, maternal age, and community size. The SGA trend for births to mothers residing in the lowest income quintile , after adjusting for minimum wage, seemed to be stable for the entire study period. In addition the odds of an SGA birth at any year did not significantly differ from the odds in 2000, except for 2002, 2009, and 2013-2016.   Table 12: Multiple logistic Regression Model Results for All Births to Mothers Residing in the Lowest Neighborhood Income Quintile  Logistic regression       Number of obs =1,333,200          LR chi2(52) =13740.18          Prob > chi2 =0 Log likelihood = -391792.49      Pseudo R2 =0.0172  SGA Birth  Odds Ratio Std. Err. z P>z [95% Conf. Interval] Real Minimum Wage (Lagged 9 months) 1.01 0.01 1.30 0.19 1.00 1.02 Year (Ref: 2000)       2001 1.03 0.02 1.86 0.06 1.00 1.07 2002 1.04 0.02 2.34 0.02 1.01 1.08 2003 1.02 0.02 1.28 0.20 0.99 1.06 2004 1.00 0.02 -0.16 0.88 0.96 1.03 2005 1.03 0.02 1.64 0.10 0.99 1.07 2006 1.04 0.02 2.20 0.03 1.00 1.08  87 2007 1.03 0.02 1.50 0.13 0.99 1.06 2008 0.98 0.02 -0.89 0.37 0.95 1.02 2009 1.04 0.02 2.44 0.02 1.01 1.08 2010 1.02 0.02 1.17 0.24 0.99 1.06 2011 1.03 0.02 1.69 0.09 0.99 1.07 2012 1.02 0.02 1.02 0.31 0.98 1.06 2013 1.05 0.02 2.48 0.01 1.01 1.09 2014 1.04 0.02 2.09 0.04 1.00 1.08 2015 1.06 0.02 2.81 0.01 1.02 1.10 2016 1.04 0.02 2.02 0.04 1.00 1.08     5.4.2 Single Mothers in the Lowest Neighborhood Income Quintile  This subpopulation included 458,750 singleton births, of which 41,4015 (9.0%) were small for gestational age. The results of this subgroup analysis show that for infants born to mothers with “single” marital status residing in the lowest neighborhood income quintile in Canada, a dollar increase in real Canadian minimum wage 9 months prior to the birth was associated with 3.0% [95% CI: 1.01, 1.05] higher odds of an SGA birth, adjusting for birth year, mother and father’s country of birth, number of liveborn children, maternal age, and community size.   Table 13: Multiple logistic Regression Model Results for All Births to Single Mothers Residing in the Lowest  Neighborhood Income Quintile Logistic regression      Number of Obs= 458,310          LR chi2(50)= 2507.76          Prob > chi2= 0 Log likelihood = -137700.61      Pseudo R2= 0.009   SGA Birth  Odds Ratio Std. Err. z P>z [95% Conf. Interval] Real Minimum Wage (Lagged 9 Months) 1.03 0.01 2.54 0.01 1.01 1.05 Year (Ref: 2000)       2001 1.02 0.03 0.68 0.50 0.96 1.08 2002 1.02 0.03 0.79 0.43 0.97 1.09 2003 1.00 0.03 -0.12 0.90 0.94 1.06 2004 0.97 0.03 -0.92 0.36 0.91 1.03 2005 1.00 0.03 0.09 0.93 0.94 1.07 2006 1.01 0.03 0.30 0.77 0.95 1.07 2007 0.99 0.03 -0.38 0.71 0.93 1.05  88 2008 0.95 0.03 -1.76 0.08 0.89 1.01 2009 1.02 0.03 0.67 0.50 0.96 1.08 2010 0.93 0.03 -2.21 0.03 0.88 0.99 2011 0.95 0.03 -1.47 0.14 0.89 1.02 2012 0.93 0.03 -2.12 0.03 0.87 0.99 2013 0.98 0.03 -0.61 0.55 0.92 1.05 2014 0.96 0.03 -1.26 0.21 0.89 1.02 2015 0.95 0.03 -1.39 0.17 0.89 1.02 2016 0.94 0.03 -1.71 0.09 0.88 1.01   Comparing the trends to births of single mothers, we notice minor and almost negligible differences between the crude ORs and ORs adjusted for all SGA risk factors including real minimum wage prior to 2010. From 2010-2016, adding real minimum wage to the adjusted SGA models seemed to have lower ORs compared to 2000.      89 Figure 16: Trends in the Crude and Adjusted (with and without Real Lagged Minimum Wage) Odds of SGA Births to Single Mothers Residing in the Lowest Neighborhood Income Quintile from 2000-2016  0.800.850.900.951.001.051.101.151.201999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016Odds RatioCalendar Year Crude OR Adjusted OR Adjusted OR including RMW 90 Chapter 6: Discussion & Conclusion         6.1 Main Findings   The results of the two studies conducted in this thesis outline the following key findings:    6.1.1 Study 1  - There was an upward secular trend in SGA births from 2000 to 2016, that could not be explained by adjusting for important maternal, paternal, contextual and infant related risk factors.   - Between 2000-2015, there was a clear gradient from highest to lowest neighborhood income quintile for trends in SGA births. The lower the neighborhood income quintile, the higher the proportion of SGA births. In the lowest income quintile the proportion of SGA births was stable around 9% for the entire period, while that of the highest income quintiles seemed to be trending upwards from 2008-2015.  - SGA proportions varied by level and trend across Canada’s largest provinces: Ontario, Quebec, British Columbia, and Alberta. The highest proportions of SGA births were in Ontario and Alberta, while the lowest were in British Columbia followed by Quebec.   - These trends also varied by neighborhood income quintile across those provinces. There was a general income quintile gradient in all provinces. The most noticeable gradient over the five neighborhood income quintiles was observed in Ontario, while those in other provinces appeared narrower and often overlapping. The steepest upward trends appeared to be particularly noticeable in Alberta, and for a short period of time in Quebec. Overall, the lowest two income quintiles appear to have consistently higher SGA births than the highest two income quintiles.    - The trend in mean birthweight from 2000-2016 was relatively stable with modest reduction over time. Similarly the mean birth weight z-scores of all births, seemed to modestly decline from 0.12 in 2000 to 0.01 in 2016.  This indicates that the mean birth weight for all births in  91 2000 was 0.12 standard deviations away from the mean birthweight in the reference population, and declined over time to reach the same mean birthweight as the reference standard in 2015-2016.  - Between 2000 and 2016, the proportion of SGA births born at 40 weeks of gestation decreased from 33.5% to 24.6%, while those born at 37 and 38 weeks of gestation increased from 6.0% to 9.0% and from 15.0% to 18.4% respectively.    6.1.2 Study 2  - On a population scale (all singleton live births in Canada from 2000-2016), a dollar increase in real minimum wage 9 months prior to a birth was associated with 2% lower odds of an SGA birth (95% CI 0.974, 0.986), when adjusting for parental place of birth, maternal age, number of liveborn children, marital status, and community size. Assuming a causal relationship and maximum effects, these numbers suggest that a $1 increase in real minimum wage is associated with 15 fewer SGA births per 10,000 singleton live births.  - When stratifying the latter analysis by province, non-significant results were observed in all provinces.   - Our subgroup analysis of births to mothers residing in the lowest neighborhood income quintile showed a non-significant association between a dollar increase in real minimum wage and SGA (OR 1.01,  p-value=0.194) when adjusting for parental place of birth, maternal age, number of liveborn children, marital status, and community size.   - Analysis on all births to single mothers residing in the lowest neighborhood income quintile showed a positive and statistically significant association between real minimum wage (lagged 9 months) and the odds of an SGA birth. Specifically, a dollar increase in real minimum wage 9 months prior to a birth was associated with 3.0% [95% CI: 1.01, 1.05] higher odds of an SGA birth, adjusting for birth year, mother and father’s country of birth, number of liveborn children, maternal age, and community size. Assuming a causal relationship and  92 maximum effects, these numbers suggest that a $1 increase in real minimum wage is associated with 27 more SGA births per 10,000 singleton live births.         6.2 Discussion     6.2.1 Study 1  In terms of the upward trend in SGA births, the results in this thesis are consistent with the recent perinatal indicators report by the public health agency of Canada(3). However, while the trends are the same, the levels are different by approximately 1 percent. This is likely due to the different methods used to measure the outcome SGA birth. As outlined in the methods section, the z-score method was used to quantify SGA births below a z-score of -1.28 (equivalent to the lowest 10th percentile). The perinatal report however used specific cutoff birth weight values for the 10th percentile. The inconsistency in the results may be due to birthweight distributions that are not perfectly normal. To ensure that this method did not result in any systematic differences in the characteristics that may introduce confounding, we looked at the distribution of SGA births as a proportion of all live births and as a proportion of all SGA births over the variables: birth year, maternal residence province, income quintile, maternal age, maternal birth place, and gestational age. The distributions were very similar / the same when comparing distributions of SGA births. When comparing the proportions of all live births, z-score method resulted in a level difference equivalent to 1% less than birthweight cutoff measurement without any systematic differences.  The findings on SGA trends and mean birthweights over time are inconsistent with findings from earlier studies which showed an increase in mean birthweight, and a decrease in the proportion of small for gestational age births over time(2,11). Our findings from the first study show, instead, modest decreases in the mean birth weight and birthweight z-scores, and an increase in the proportion of SGA births over time. The inconsistency in the results may simply reflect the fact that  93 the most recent (previous) research investigating SGA trends and mean birthweights in Canada was based on a population of births from 1978 to 1996. Moreover, the increase in the proportion of SGA births born at 37 and 38 weeks of gestation due to changes in obstetric interventions (induction of labor(95), planned C-sections) may have contributed to the slight decrease in mean birthweights; however, when isolating the differences in gestational age at time of delivery using the mean birthweight z-scores, the results showed the same modestly declining trend between 2000-2016. Our findings, suggest important demographic changes in the population of births from 2000-2016, and a potential slight decrease in fetal growth over time which may be partly responsible for these results.   When stratified by province, the results from this study (1) showed regional variations in the levels and trends of SGA births across the four provinces (ON, QC, AB, and BC). These results are consistent with previous reports(3). Moreover, these differences may be associated with regional variations in important SGA risk factors such as cigarette and alcohol consumption during pregnancy, and the use of assisted reproductive technologies.  In the perinatal health indicator report of 2013, maternal smoking substantially varied by province(102). Among Canada’s largest provinces in 2001-2004, British Columbia had the lowest maternal smoking rate 11.2 (8.4–13.9) followed by Ontario 11.7 [95% CI: 9.8–13.7], while Alberta 18.9 [95% CI:15.1–22.7] and Quebec 18.0 [95% CI: 14.8–21.3] had substantially higher rates(102). Between 2005-2008, both BC 9.4 [95% CI: 6.8–12.1] and Ontario 9.9 [95% CI: 8.0–11.7] remained with the lowest rates, while Quebec 14.3 [95% CI: 11.1–17.5] and Alberta 13.0 [95% CI: 10.0–16.1] the highest(102). Our findings show that the lowest proportion of SGA births was in BC and the highest in AB, which may be correlated with differences in maternal smoking – a known SGA risk  94 factor- in these two provinces. As for alcohol consumption during pregnancy – another known risk factor – the highest rates among the provinces between 2005-2008 were in Quebec (25.6 %,  [95% CI: 23.9–27.3]) and Ontario (12.0%, [95% CI 11.0-13.0]) (102). These risk factors seem to explain some but not all of the regional differences. For instance, the lowest rates alcohol consumption in BC may be correlated with the low SGA proportions in this province. Alternatively, the highest proportion of smoking and alcohol consumption during pregnancy observed in Quebec (the province with the second lowest level of SGA trends), suggest that other maternal or lifestyle factors and social policies may better explain these trends.   In addition to the regional variations in maternal risk factors, differences in the trends of SGA births across neighborhood income quintiles between Alberta and British Columbia may further highlight an economic context behind these disparities. Compared to a relatively stable trend across all neighborhood income quintiles in BC, trends in SGA births in all neighborhood income quintiles in Alberta were increasing at a faster rate following 2008 - a period of global financial crisis. This upward trend was specifically steeper in the highest income quintiles in Alberta.  Alberta’s highest income neighborhoods are concentrated in Fort McMurray, an urban region in Northern Alberta that is the centre of the local economy due to its large hydrocarbon reserves.   Following the global financial crisis in 2008, Canada entered an economic recession that affected Alberta’s resource-based economy the most(103). Labour market analyses between 2008 and 2009, showed that across all provinces, Alberta’s unemployment rates changed by 82.3%, while that of BC changed by 46.8%(103). While unemployment rates were higher for males (43.5%) than females (22.5%) (103), these effects can influence the financial and psychological wellbeing of the entire household as well as an individual.  A study looking at the impact of economic recessions on  95 maternal and infant mortality found substantial and statistically significant increases in maternal mortality in Canada with decreases in GDP between 1950-1966(104). In addition to the recession in 2008, the collapse of oil prices in 2014 further exacerbated the economy in Alberta(105). A recent study that looked at the impact of this oil recession on community mental health service utilization in Fort McMurray, found that patients who were males, married, Caucasian, own a home, have higher levels of education and unemployment had disproportionately elevated service use utilization post-recession (106). As outlined in the background and the WHO’s social determinants of infant mortality’s conceptual framework(68), there are many pathways that connect these larger macroeconomic factors -such as an economic recession – to adverse birth outcomes. The ones of importance in a period of economic recession, are unemployment, income, stress, and psychosocial wellbeing.    Finally, with the advancement of maternal age and delayed childbearing, the use of assisted reproductive technologies (ART) have gained popularity in the last decade or two. As explained in the background, births occurring through ART have higher risks of adverse birth outcomes, including SGA births(39). Using the Canadian ART Register’s annual reports, we extracted from each report the number of singleton births from all ART procedures by year in Canada excluding stillbirths (107–118). Between 2001 and 2012, the number of live singleton births born through ART increased substantially from 1124 births (0.4% of all singleton births, and 2.1% of all births in the highest income quintile) to 5031 births (1.4% of all singleton births and 8.3% of all births in the highest income quintile).  The reports also include the percentage of ART births that had a low birth weight. From 2000-2012, the proportion of LBW births ranged from 7% to 10% of all ART births. In 2012, 7.8% of ART births had a low birth weight. If we assume that these LBW births were also SGA, ART would account for a maximum of 1.4 percent of all SGA births in 2012. ART became  96 publicly funded in QC in 2010, and so may contribute to the  steep upward trends in SGA births in Quebec from 2010 onwards.            6.2.2 Study 2    As outlined in the literature review, only two studies to date have explored the association between minimum wage and adverse birth outcomes(5,15). On a population scale, the results of the full model are consistent with Komro et al’s findings(4) both in direction and magnitude of effect. Komro et al(4) found that a dollar increase in real minimum wage (lagged 12 months) was associated with l.3% less low birthweight births (95% CI -2.7, 0.0), adjusting for state and year fixed effects, race, poverty, cigarette sales, and maternal age. Similarly, the analysis on all births in Canada from 2000-2016 showed that a dollar increase in the Canadian real minimum wage (lagged 9 months) was associated with 2% lower odds (95% CI [0.97, 0.98]) of small for gestational birth, while adjusting for all other confounders. While similar, these findings differ in the statistical modeling (fixed effects vs. logistic regression), outcome measurement( LBW vs. SGA), and controlled variables (individual level vs. population estimates).  The results of the second study by Wehby et al(5) were stratified by mothers’ educational attainment (less than high school, or high school) and marital status (married vs. not married), and therefore cannot be compared to our full model results.   Wehby et al. (5)found that a 10% increase in the relative minimum wage (nominal minimum wage/median hourly wage in each state) was associated with 0.2 percentage points decrease (reported as a 2% relative decrease) in low birth weight for mothers with less than high school degree education. Among this group, a 10% increase in the relative nominal minimum wage was associated with a 1.4 percentage point (13.5%) decrease in the probability of having less than five prenatal visits over the course of the pregnancy, a 0.2 month (5.3%) decrease in delaying prenatal  97 care, and a 0.9 percentage point (4%) decrease in the probability of prenatal smoking. While significant, these findings were, like the present study, small in effect size.   For mothers who were “not married” , the results in Wehby et al.’s study (5) were reported as a significant decrease in 0.3 percentage points in low birth weights. It is unclear how this percentage point estimate translates to probability change for this group, making it challenging to compare the effect size to the findings here. In terms of the direction of association, the positive association observed in our subgroup analysis on single mothers in low income neighborhoods contradict with Wehby et al’s stratified results of “not married” women (negative association). These differences may be due to measurement and misclassification bias of  the “marital status” variable. For instance, the “not married” category used in the latter study(5) may not only contain “single” women, but all other statuses including “common-law”. While this measurement error may have existed in our subgroup analysis as well, the extent of misclassification is less than that in the other study, given that most -if not all – common law union status were regrouped under “other” marital status. Furthermore, prenatal care and maternal smoking did not significantly change with a 10% increase in relative nominal minimum wage for the “not married” group in Wehby et al’s study. This finding further supports the hypothesis of this study that for this subgroup of single low-income women, intermediate pathways other than those identified for the general population may be taking place.   Findings from two studies in the United States and Canada provide insight on potential pathways for low income women and single low income women. The results of a study in the US showed that single mothers with lower education affected by minimum wage increases did not see a rise in their net income, mainly due to negative effects on employment and reduced working hours. Specifically, the study finds that a 10 % increase in the minimum wage was associated with 8.8 % reduction in  98 employment and 11.8 % reduction in annual hours worked (65). Since the results in Wehby et al’s study (5) were conditional on an improved income effect only, the findings here suggest that in the absence of improved income, negative employment and  reduced hours effect of minimum wage may present different pathways and associations with SGA births.    For low income mothers, a recent study in Canada examined the association between an unconditional income supplement to low-income pregnant women and SGA births(17). This income supplement (Healthy Baby Prenatal Benefit) was introduced in 2001 in Manitoba to improve prenatal health and birth outcomes by providing prenatal income support (up to Can$81.41 monthly) to low-income women during the second and third trimesters(17). The study finds a reduction of 30% in the adjusted risks of low birth weights (aRR, 0.71 [95% CI, 0.63–0.81]), and a 10% reduction in the adjusted risks of small for gestational age births (aRR, 0.90 [95% CI, 0.81–0.99]). These results suggest that “unconditional” increases in income (without working, or restrictions on spending) may have a larger effect on reducing the risks of SGA births.    Results from the stratified analyses in this study show minimum wage adjusted trends in different directions for ON and AB vs. BC and QC, but none of the results were statistically significant.  As outlined in the background section, improved income, labour market conditions (unemployment, hours of work, economic shocks, and shift work), and lifestyle factors (maternal smoking, stress, assisted reproductive technologies) are all common risk factors and pathways between minimum wage and adverse birth outcomes. When we observe these factors by province, we notice important variations, which may have influenced the regional differences in SGA proportions (as described above), as well as the pathways between minimum wage and this outcome.    99 To further contextualize the effect size of province-stratified findings of Study 2, it is informative to consider the proportion of employees paid minimum wage in these provinces. A report by Statistics Canada finds that the proportion of employees on minimum wage in 2014 was the lowest in Alberta at 1.7%, and the highest in Ontario at 10.9%, and about 6% in Quebec and British Columbia (58). Since we were not able to identify mothers on minimum wage in this study, these figures suggest we might expect a greater likelihood of effect in Ontario than in Alberta. The direction of effect was in fact consistent with this, but without statistical significance.    Looking at female unemployment, Quebec had the highest rates of female unemployment (aged 15-64 years) for the first half of the study period (2000-2008) and the second highest in the latter period (2008-2016). While Alberta had the lowest rates of female unemployment from 2000-2008, this rate experienced the highest fluctuations in the second part of the study period, varying from 3.8% in 2008 to 7.4% in 2016. Without making inferences, studies have found significant associations between unemployment, economic shocks, and adverse birth outcomes (16) (71). Therefore, with the lack of occupational data in this study, it is challenging to distinguish whether unemployment is acting as and intermediate pathway or a potential confounder.   Finally, when interpreting the results of this study, it is also important to take into consideration the nature of minimum wage changes in Canada over the study period.  Compared to minimum wage changes in the US, which are large hikes introduced over long interrupted periods of time, minimum wages in Canada have been incrementally increasing annually or semi-annually from 2000 to 2016. For instance, the results of study 2 in British Columbia are somehow different from the results in Quebec. While Quebec continuously increased its minimum wage annually and semi-annually over the study period, BC had a long period of frozen minimum wage, which resulted in a declining trend  100 in its real minimum wage. With continuous incremental changes over time or different implementation dates across provinces, it becomes harder to detect an effect size.  Overall, the results of the full model in this thesis are similar to findings from previous studies(4), with limitations. First the comparisons are made based on a very limited literature (only two studies). Second, there are important methodological differences in terms of statistical modeling, measurement, and confounding variables. The null findings observed in the province stratified models and on mothers residing in low income neighborhoods can be more accurately explained by identifying minimum wage employees, and observing changes in income and employment pathways.  Finally, the results of the subgroup analyses appear be dependent on the minimum wage effects (positive vs. negative income and substitution effects), and the accessibility of prenatal care, which may have been different between Canada and the United States.    6.3 Recognized Limitations   The two research studies presented in this thesis provide new information regarding small for gestational age births and the labour market in Canada; however, it is important to interpret these findings in the light of their limitations. While some study specific limitations and strengths have been discussed in previous chapters, broader limitations are expanded on below:   The first limitation is related to the limited availability of data on important variables, which limits the potential for causal inferences. Due to data limitations, we could not control for important SGA risk factors such as pre-pregnancy BMI, pregnancy weight gain, maternal smoking, use of assisted reproductive technologies, prenatal care visits, working conditions, nor stratify based on known individual income levels or occupations. In a study design that involves a long study period, a  101 correlation between two trends (such as SGA and real minimum wage) may be spurious as a result of unmeasured confounders. For instance, although we used the lowest neighborhood income quintile as a proxy for mothers with low income, we recognize that this not may be an inaccurate measure of the population that is affected by minimum wage changes. Hence, the results of both studies can only establish associations, and cannot determine causality.    A second important limitation is the use of the Canadian reference chart for birthweights that is based on a population from 1994-1996. The results of the SGA trends in the first study suggest that there may be changes in other risk factors over time, or a potential shift in the birthweight distribution. SGA births are defined as all births below the 10th percentile of a population. Therefore, assuming no changes in the reference population, we would expect to see a constant and flat trend of SGA births over our study period. The results of both this thesis and other reports (3) have indicated otherwise. There is clearly a secular SGA trend that could not be completely explained even when adjusting for maternal demographic factors such as place of birth, age, number of liveborn children, and residential factors. When looking at the mean birth weight  and birthweight z-scores over time , we observed a modest decrease from 2000-2016. These results show that in earlier years the lower SGA proportions may have been due to a mean birthweight higher than that of the reference population.   A third limitation pertains to the secondary use of administrative data for health care research.  An unexplained four-year systematic and recurrent dip in the overall SGA trend was noticeable in most provinces and income quintiles in study 1. There may be either contextual factors affecting this systematic observation that we were not able to explain using our data, and/or changes in data collection. Since the data are collected for administrative (birth registration) rather than research  102 purposes, the selection and quality of data collection is not under the researcher’s control and hence can be difficult to validate (119). In addition, the quality of measurement can also be hard to assess. For instance, due to the large nature of the dataset used, and the different reporting by jurisdictions, inconsistencies can be observed in measuring some variables such as marital status (married vs. common law), and gestational age (ultrasound vs. last menstrual period) which may contribute to misclassification. On the other hand, the cohort size and population-based nature of the data coupled with the complete reporting, offers significant advantages over previous studies.         6.4 Strengths to Acknowledge    Despite the study limitations, both studies presented in this thesis had several notable strengths that should be acknowledged.   The first strength relates to the use of the entire Canadian singleton birth population without exclusions. While the Canadian perinatal reports use a large sample of births covering most provinces, Quebec is often excluded from the analysis. In this thesis, both studies include all births in all provinces and territories without exclusions, thereby representing complete geographic diversity.   In addition to using complete national datasets, both studies are the first of their kind to report on a study period spanning 17 years of data– from 2000-2016. For the results in study one, most studies exploring SGA births rely on a two year study period(7) or at the most 10 years (3). The studies presented in this thesis provide extensive and valuable information over the longest time-period in the existing literature. Additionally, this thesis is also the first to present a comprehensive and descriptive analysis of SGA trends over time using individual-level and contextual factors in Canada.    103  Study two also expands on the external validity of the available evidence. Since the identified studies (5,15) have all been conducted in the United States under a private health care system and in a different labour market environment, the generalizability of the results is limited to similar systems only. This is specifically important when one of the hypothesized pathways of the effect of higher minimum wages on birth outcomes is through improved prenatal care use as a result of higher income. Thus, the Canadian universal health care setting of our study have expanded on the external validity of the available literature both in terms of similar universal health care systems and demographic characteristics.  Finally, none of the studies in the available literature have focused on the population that is most likely to be affected by minimum wages. Changes in minimum wages are likely to affect their target low income populations. This thesis included stratified analyses by Canada’s largest provinces given the regional variations in the outcome, SGA births. In addition, two subgroup analyses were conducted on mothers residing in the lowest neighborhood income quintile as well as single mothers residing in the lowest neighborhood income quintile. While the overall findings are in line with those in the United States, the results of the stratified and subgroup analyses were new and inconsistent. These findings further support the need for targeted sub-population analyses.         6.5 Conclusion and Future Implications         From an epidemiologic perspective, this thesis finds a secular upward trend in SGA births from 2000-2016 that could not be completely explained even after adjusting for important risk factors such as parental place of birth (a proxy for ethnicity and immigration), maternal age, number of liveborn children (proxy for parity), marital status, community size and neighborhood income  104 quintile. The results highlight the need to explore other factors that may be associated with these trends such as pre-pregnancy BMI, maternal smoking, income, and the use of assisted reproductive technologies.   From an economic perspective, the findings of the second study exploring minimum wages are novel to the Canadian literature. On a population scale, the results show an overall significant reduction in small for gestational births associated with every dollar increase in real minimum wage 9 months prior to the birth. Similar findings in the US hypothesized a few pathways for their results including an increase in prenatal care use as a result of increased income(5). Canada on the other hand has a universal health care system with further targeted maternal and child health services for low income mothers. Therefore, the results of this study indicate that pathways other than increased prenatal care use may be more significant in the overall conceptual framework.   The collective findings from this thesis highlight the need for more current and up to date research on the determinants of trends in SGA births in Canada. These trends can be better explained with access to linked and accurately measured maternal risk factors. The findings of the second study introduce new directions for researchers to pursue around modifiable risk factors in infant health. Particularly, investigating the specific pathways involved between higher minimum wages and adverse birth outcomes, for low income single mothers, can better inform and validate these results. To better capture the effect of minimum wage policies, these findings also highlight the need to access linked individual level data on maternal occupation, income, working conditions and maternal risk factors. One of the challenges of the analysis in this study was due to the complexity of population trends in the main variables (minimum wage and SGA births), and the lack of individual level data. Therefore, having income and occupational data to identify pregnant mothers who are on  105 or close to minimum wage can reduce the bias from unmeasured confounding associated with analyzing population trends, allow the observation of income and substitutions effects for the policy’s targeted population, and make the use of other more methodologically rigorous study designs possible.   From a policy perspective, increasing minimum wages was associated with a reduction in the odds of an adverse birth outcome on a population scale; however, the significant findings of the subgroup analysis on single mothers residing in low income neighborhoods suggest the need for more targeted programs or policies for the most at-risk populations such as the basic income or the unconditional income supplement (17).   In brief, the implications of these findings for policy makers, minimum wage advocates, public health practitioners, and researchers are noteworthy. Small for gestational age births place a significant economic burden on families, and the health care system in general(7). While numerous researchers have long studied the employment effects of minimum wage or the maternal risk factors of SGA births, these findings lay the foundation to further explore new avenues in researching the social determinants of infant health.        106 Bibliography   1.  Kramer MS, Morin I, Yang H, Platt RW, Usher R, McNamara H, et al. Why are babies getting bigger? Temporal trends in fetal growth and its determinants. J Pediatr. 2002;141(4):538–42.  2.  Wen SW, Kramer MS, Platt R, Demissie K, Joseph KS, Liu S, et al. Secular trends of fetal growth in Canada, 1981 to 1997. Paediatr Perinat Epidemiol. 2003;  3.  Public Health Agency of Canada. Government of Canada. PERINATAL HEALTH INDICATORS FOR CANADA 2017 A REPORT FROM THE CANADIAN PERINATAL SURVEILLANCE SYSTEM. 2017.  4.  Komro KA, Livingston MD, Markowitz S, Wagenaar AC. The effect of an increased minimum wage on infant mortality and birth weight. Am J Public Health. 2016;106(8):1514–6.  5.  Wehby G, Dave D, Kaestner R. Effects of the Minimum Wage on Infant Health. NBER Work Pap Ser. 2016;48.  6.  Katz J, Lee ACC, Kozuki N, Lawn JE, Cousens S, Blencowe H, et al. Mortality risk in preterm and small-for-gestational-age infants in low-income and middle-income countries: A pooled country analysis. Lancet. 2013;382(9890):417–25.  7.  Canadian Institute for Health Information (CIHI). Too Early, Too Small: A Profile of Small Babies Across Canada [Internet]. 2009. 1-112 p. Available from: https://secure.cihi.ca/free_products/too_early_too_small_en.pdf 8.  Hernández MI, Mericq V. Metabolic syndrome in children born small-for-gestational age. Arq Bras Endocrinol Metabol [Internet]. 2011;55(8):583–9. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22218440 9.  Kramer MS, Platt RW, Wen SW, Joseph KS, Allen A, Abrahamowicz M. Birth Weight for Gestational Age. 2001;108(2):110–3.  10.  Johnston KM, Gooch K, Korol E, Vo P, Eyawo O, Bradt P, et al. The economic burden of prematurity in Canada. BMC Pediatr [Internet]. 2014;14(1):93. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24708755%5Cnhttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4108009%5Cnhttp://bmcpediatr.biomedcentral.com/articles/10.1186/1471-2431-14-93 11.  Arbuckle TE, Sherman GJ. An analysis of birth weight by gestational age in Canada. CMAJ. 1989;  12.  Kim D, Saada A. The social determinants of infant mortality and birth outcomes in western developed nations: A cross-country systematic review. Int J Environ Res Public Health. 2013;10(6):2296–335.  13.  Muntaner C, Chung H, Benach J, Ng E. Hierarchical cluster analysis of labour market regulations and population health: a taxonomy of low- and middle-income countries. BMC Public Health [Internet]. 2012;12(1):286. Available from: http://www.biomedcentral.com/1471-2458/12/286 14.  Bezo B, Maggi S, Roberts WL. The rights and freedoms gradient of health: Evidence from a cross-national study. Front Psychol. 2012;3(NOV):1–16.  15.  Komro KA, Livingston MD, Markowitz S, Wagenaar AC. The effect of an increased minimum wage on infant mortality and birth weight. Am J Public Health. 2016;106http://(8http://www.statcan.gc.ca/tables-tableaux/sum-som/l01/cst01/health21a-htm):1514–6.   107 16.  Raatikainen K, Heiskanen N, Heinonen S. Does unemployment in family affect pregnancy outcome in conditions of high quality maternity care ? 2006;7:1–7.  17.  Brownell MD, Chartier MJ, Nickel NC, Chateau D, Martens PJ, Sarkar J, et al. Unconditional Prenatal Income Supplement and Birth Outcomes. Obstetrical and Gynecological Survey. 2016.  18.  Bushnik T, Yang S, Kaufman JS, Kramer MS, Wilkins R. Socioeconomic disparities in small-forgestational- age birth and preterm birth. Heal Reports. 2017;28(11):3–10.  19.  Kramer MS, Kakuma R. Energy and protein intake in pregnancy. Cochrane database Syst Rev. 2003;  20.  Kiess W. Small for Gestational Age Causes and Consequences. KARGER. 2009;13.  21.  Manning FA. Fetal medicine: principles and practice. Norwalk, Connecticut: Appleton & Lange; 1995;  22.  Ananth C V., Vintzileos AM. Distinguishing pathological from constitutional small for gestational age births in population-based studies. Early Hum Dev [Internet]. 2009;85(10):653–8. Available from: http://dx.doi.org/10.1016/j.earlhumdev.2009.09.004 23.  Hendrix N, Berghella V. Non-Placental Causes of Intrauterine Growth Restriction. Semin Perinatol. 2008;32(3):161–5.  24.  Suhag A, Berghella V. Intrauterine Growth Restriction (IUGR): Etiology and Diagnosis. Curr Obstet Gynecol Rep [Internet]. 2013;2(2):102–11. Available from: http://link.springer.com/10.1007/s13669-013-0041-z 25.  Wollman H. Children Born Small for Gestational Age: Definitions and Etiology. KARGER. 13.  26.  Ricci E, Parazzini F, Chiaffarino F, Cipriani S, Polverino G. Pre-pregnancy body mass index, maternal weight gain during pregnancy and risk of small-for-gestational age birth: Results from a casecontrol study in Italy. J Matern Neonatal Med. 2010;23(6):501–5.  27.  Ronnenberg AG, Wang X, Xing H, Chen C, Chen D, Guang W, et al. Low Preconception Body Mass Index Is Associated with Birth Outcome in a Prospective Cohort of Chinese Women. J Nutr [Internet]. 2003;133(11):3449–55. Available from: https://academic.oup.com/jn/article/133/11/3449/4817965 28.  Nahar S, Mascie-Taylor CGN, Begum HA. Maternal anthropometry as a predictor of birth weight. Public Health Nutr. 2007;  29.  Kramer MS. Determinants of low birth weight: methodological assessment and meta-analysis. Bull World Health Organ. 1987;  30.  Zhang X, Cnattingius S, Platt RW, Joseph KS, Kramer MS. Are Babies Born to Short, Primiparous, or Thin Mothers “Normally” or “Abnormally” Small? J Pediatr. 2007;  31.  Odibo AO, Nelson D, Stamilio DM, Sehdev HM, Macones GA. Advanced maternal age is an independent risk factor for intrauterine growth restriction. Am J Perinatol. 2006;  32.  Schumacher LB, Pawson IG, Green JR, Partridge JC, Kretchmer N. Ethnic variation in the size of infant at birth. Am J Hum Biol. 1990;  33.  Yuen L, Wong VW. Gestational diabetes mellitus : Challenges for different ethnic groups. 2015;6(8):1024–32.  34.  Steyn K, De Wet T, Saloojee Y, Nel H, Yach D. The influence of maternal cigarette smoking, snuff use and passive smoking on pregnancy outcomes: The Birth to Ten Study. Paediatr Perinat Epidemiol. 2006;20(2):90–9.  35.  Bouhours-Nouet N, May-Panloup P, Coutant R, de Casson FB, Descamps P, Douay O, et al. Maternal smoking is associated with mitochondrial DNA depletion and respiratory chain complex III deficiency in placenta. Am J Physiol - Endocrinol Metab. 2004;288(1):171–7.   108 36.  Okah FA, Cai J HG. Term-gestation low birth weight and health- compromising behaviors during pregnancy. Obstet Gynecol. 2005;  37.  Naeye RL, Blanc W, Leblanc W, Khatamee MA. Fetal complications of maternal heroin addiction: Abnormal growth, infections, and episodes of stress. J Pediatr. 1973;  38.  Krampl E. Pregnancy at high altitude. Ultrasound Obstet Gynecol. 2002;19(6):535–9.  39.  D’Angelo D V., Whitehead N, Helms K, Barfield W, Ahluwalia IB. Birth outcomes of intended pregnancies among women who used assisted reproductive technology, ovulation stimulation, or no treatment. Fertil Steril. 2011;  40.  Sato A, Otsu E, Negishi H, Utsunomiya T, Arima T. Aberrant DNA methylation of imprinted loci in superovulated oocytes. Hum Reprod. 2007;22(1):26–35.  41.  Blencowe H, Cousens S, Chou D, Oestergaard M, Say L, Moller A-B, et al. Born too soon: the global epidemiology of 15 million preterm births. Reprod Health [Internet]. 2013;10 Suppl 1(Suppl 1):S2. Available from: /pmc/articles/PMC3828585/?report=abstract 42.  Malloy MH. Size for gestational age at birth: Impact on risk for sudden infant death and other causes of death, USA 2002. Arch Dis Child Fetal Neonatal Ed. 2007;  43.  Altman M, Bonamy AKE, Wikström AK, Cnattingius S. Cause-specific infant mortality in a population-based Swedish study of term and post-term births: The contribution of gestational age and birth weight. BMJ Open. 2012;  44.  Krechowec S. · Thompson N. · Breier B. Fetal Growth Restriction and the Developmental Origins of Adult Disease Hypothesis: Experimental Studies and Biological Consequences. KARGER. 2008;  45.  Joss-Moore LA, Lane RH. The developmental origins of adult disease. Current Opinion in Pediatrics. 2009.  46.  Bateson P, Barker D, Clutton-Brock T, Deb D, D’Udine B, Foley RA, et al. Developmental plasticity and human health. Nature. 2004;  47.  Gülmezoglu M, de Onis M, Villar J. Effectiveness of interventions to prevent or treat impaired fetal growth. Obstet Gynecol Surv. 1997;  48.  Morris RK, Oliver EA, Malin G, Khan KS, Meads C. Effectiveness of interventions for the prevention of small-for-gestational age fetuses and perinatal mortality: A review of systematic reviews. Acta Obstet Gynecol Scand. 2013;92(2):143–51.  49.  Smith V. Multiple-micronutrient supplementation for women during pregnancy. Pract Midwife. 2014;  50.  Magee L, Duley L. Oral beta-blockers for mild to moderate hypertension during pregnancy. In: Cochrane Database of Systematic Reviews. 2003.  51.  Health Canada. Birth weight for gestational age. 2001;108(613):5995.  52.  Debessai Y, Costanian C, Roy M, El-Sayed M, Tamim H. Inadequate prenatal care use among Canadian mothers: Findings from the Maternity Experiences Survey. J Perinatol. 2016;  53.  Shah RR, Ray JG, Taback N, Meffe F, Glazier RH. Adverse Pregnancy Outcomes Among Foreign-Born Canadians. J Obstet Gynaecol Canada [Internet]. 2011;33(3):207–15. Available from: http://dx.doi.org/10.1016/S1701-2163(16)34821-6 54.  Behlim T. Differences in birth weight by maternal and paternal nativity in Canada. 2016;  55.  Statistics Canada - Government of Canada. Socioeconomic disparities in birth outcomes. Heal Reports, Dly. 2017;8300.  56.  Statistics Canada - Government of Canada. Minimum wage in Canada since 1975 [Internet]. The daily. [cited 2017 Feb 9]. Available from: http://www.statcan.gc.ca/pub/11-630-x/11-630-x2015006-eng.htm 57.  Battle K. Minimum Wage Rates in Canada : 1965-2015. 2015;(September).   109 58.  Statistics Canada - Government of Canada. The ups and downs of minimum wage [Internet]. [cited 2017 Feb 9]. Available from: http://www.statcan.gc.ca/pub/75-006-x/2014001/article/14035-eng.htm 59.  AAA. Behind the numbers. Assoc Commun 2015 [Internet]. 2015;(6):11. Available from: http://ezproxy.library.dal.ca/login?url=http://search.proquest.com/docview/205826439?accountid=10406%5Cnhttp://sfxhosted.exlibrisgroup.com/dal?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&genre=unknown&sid=ProQ:ProQ%3Acbcacomplete&atitle=B 60.  Morissette R, Dionne-simard D. Recent changes in the composition of minimum wage workers. Stat Canada. 2018;(75).  61.  Neumark D, Wascher W. MINIMUM WAGES AND EMPLOYMENT: A REVIEW OF EVIDENCE FROM THE NEW MINIMUM WAGE RESEARCH. NBER Work Pap [Internet]. 2006; Available from: file:///Users/ket/Documents/Library.papers3/Articles/Unknown/Unknown/Untitled-1835.pdf%5Cnpapers3://publication/uuid/72A005E1-FBE1-4385-83E5-0C858006850C 62.  Belman D, Wolfson P. What Does the Minimum Wage Do? Wages and Earnings. W.E. Upjohn Institute. 2014.  63.  Butcher BT, Commission LP. The hourly earnings distribution before and after the National Minimum Wage. 2005;(October):427–35.  64.  Grossman JB. The Impact of the Minimum Wage on Other Wages. J Hum Resour. 1983;18(3):359–78.  65.  Sabia J. Minimum Wages and the Economic Well-Being of Single Mothers. J Policy Anal Manag. 2008;27(4).  66.  Clemens J, Kahn LB. The Minimum Wage, Fringe Benefits, and Worker Welfare. 2018;  67.  Campolieti M, Gunderson M, Lee B. Minimum wage effects on permanent versus temporary minimum wage employment. Contemp Econ Policy. 2014;32(3):578–91.  68.  Solar O, Irwin A. A Conceptual Framework for Action on the Social Determinats of Health. World Heal Organ [Internet]. 2010; Available from: http://www.keepontrack.eu/contents/publicationsbiannualnationalpolicyupdatesversions/kot-policy-paper-on-retrospective-changes-to-res-support--october-2013-update.pdf 69.  Tarasuk V, McIntyre L, Li J. Low-income women’s dietary intakes are sensitive to the depletion of household resources in one month. J Nutr [Internet]. 2007;137(8):1980–7. Available from: http://jn.nutrition.org/content/137/8/1980.long 70.  Niedhammer I, O’Mahony D, Daly S, Morrison JJ, Kelleher CC. Occupational predictors of pregnancy outcomes in Irish working women in the Lifeways cohort. BJOG An Int J Obstet Gynaecol. 2009;  71.  Margerison-Zilko CE, Catalano R, Hubbard A, Ahern J. Maternal exposure to unexpected economic contraction and birth weight for gestational age Claire. 2011;6(9):790–5.  72.  McCowan L, Horgan RP. Risk factors for small for gestational age infants. Best Pract Res Clin Obstet Gynaecol. 2009;  73.  Thompson JMD, Clark PM, Robinson E, Becroft DMO, Pattison NS, Glavish N, et al. Risk factors for small-for-gestational-age babies: The Auckland birthweight collaborative study. J Paediatr Child Health. 2001;  74.  Urquia ML, Frank JW, Moineddin R. Immigrants ’ duration of residence and adverse birth outcomes : a population-based study. 2010;591–601.  75.  Lang JM, Lieberman E, Cohen A. A comparison of risk factors for preterm labor and term small-for-gestational-age birth. Epidemiology [Internet]. 1996;7(4):369–76. Available from:  110 http://www.ncbi.nlm.nih.gov/pubmed/8793362 76.  Gardosi J. Intrauterine growth restriction: new standards for assessing adverse outcome. Best Pract Res Clin Obstet Gynaecol. 2009;  77.  Hutcheon JA, Zhang X, Cnattingius S, Kramer MS, Platt RW. Customised birthweight percentiles: Does adjusting for maternal characteristics matter? BJOG An Int J Obstet Gynaecol. 2008;  78.  Berry JW. Psychology of acculturation. In: Cross-cultural Perspectives Nebraska Symposium on Motivation. 1990.  79.  Cheng ER, Taveras EM, Hawkins SS. Paternal Acculturation and Maternal Health Behaviors: Influence of Father’s Ethnicity and Place of Birth. J Women’s Heal. 2017;  80.  Koroukian S, Rimm  a. The “Adequacy of Prenatal Care Utilization” (APNCU) index to study low birth weightIs the index biased? J Clin Epidemiol. 2002;  81.  Weng Y-H, Yang C-Y, Chiu Y-W. Risk Assessment of Adverse Birth Outcomes in Relation to Maternal Age. PLoS One. 2014;  82.  Journal T. The determinants of provincial minimum wages in Canada. 2002;  83.  Auger N, Daniel M, Platt RW, Luo ZC, Wu Y, Choinière R. The joint influence of marital status, interpregnancy interval, and neighborhood on small for gestational age birth: A retrospective cohort study. BMC Pregnancy Childbirth. 2008;  84.  House L. EFFECTS OF MARITAL STATUS AND RACIAL DISPARITIES IN LOW BIRTHWEIGHT INFANTS OF MEDICAID WOMEN. Michigan State University; 2014.  85.  Hohmann-Marriott B. The couple context of pregnancy and its effects on prenatal care and birth outcomes. Matern Child Health J. 2009;13(6):745–54.  86.  Beckstead D, Brown M, Guo Y, Newbold B. Cities and Growth: Earnings Levels Across Urban and Rural Areas: The Role of Human Capital. The Canadian Economy in Transition Series. 2010.  87.  Public Health Agency of Canada. Obesity in Canada: A joint report from the public health agency of Canada and the Canadian Institute for health information [Internet]. Public Health Agency of Canada. 2011. p. 62. Available from: http://www.phac-aspc.gc.ca/hp-ps/hl-mvs/oic-oac/assets/pdf/oic-oac-eng.pdf 88.  Goetzinger K, Cahill A, MacOnes G, Odibo A. The relationship between maternal body mass index and tobacco use on small-for-gestational-age infants. Am J Perinatol. 2012;  89.  Luo Z, Wilkins R, Kramer MS, Health I, Group S. Effect of neighborhood income and maternal education on birth outcomes: a population-based study. 2006;174(10):1415–21.  90.  Liu N, Wen SW, Katherine W, Bottomley J, Yang Q, Walker MC. Neighbourhood Family Income and Adverse Birth Outcomes Among Singleton Deliveries. J Obstet Gynaecol Canada. 2010;  91.  Tsao T, Konty K, Van Wye G, Barbot O, Hadler J, Linos N, et al. Estimating Potential Reductions in Premature Mortality in New York City from Raising the Minimum Wage to $15. Am J Public Health. 2016;106(6):1036–41.  92.  Statistics Canada - Government of Canada. Table 18-10-0004-13 Consumer Price Index by product group, monthly, not seasonally adjusted, Canada, provinces, Whitehorse, Yellowknife and Iqaluit.  93.  Neumark D. The Effects of Minimum Wages on Employment. 2015;1–5. Available from: http://www.frbsf.org/economic-research/files/el2015-37.pdf 94.  Macfarlane PI, Wood S, Bennett J. Non-viable delivery at 20-23 weeks gestation: observations and signs of life after birth. Arch Dis Child Fetal Neonatal Ed [Internet]. 2003;88(3):F199-202. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1721558&tool=pmcentrez&ren 111 dertype=abstract 95.  Sogc. Guidelines for the Management of Pregnancy at 41+0 to 42+0 Weeks. J Obs Gynaecol Can. 2008;30(9):800–10.  96.  Inoue H, Ochiai M, Yasuoka K, Tanaka K, Kurata H, Fujiyoshi J, et al. Early Mortality and Morbidity in Infants with Birth Weight of 500 Grams or Less in Japan. J Pediatr. 2017;190:112–117.e3.  97.  WHO. WHO | The Z-score or standard deviation classification system. WHO. 2010.  98.  Agency PH, Agence C. What Mothers Say : The Canadian Maternity. Methods.  99.  van Uitert EM, van der Elst-Otte N, Wilbers JJ, Exalto N, Willemsen SP, Eilers PH, et al. Periconception maternal characteristics and embryonic growth trajectories: the Rotterdam Predict study. Hum Reprod. 2013;28(12):3188–96.  100.  Statistics Canada - Government of Canada. Standard Classification of Countries and Areas of Interest ( SCCAI ). 2018.  101.  Statistics Canada. Postal Code Conversion File Plus (PCCF +) Version 6A, Reference Guide. 2014;(82):57.  102.  Public Health Agency of Canada. Perinatal health indicators for Canada 2013: a report of the Canadian Perinatal Surveillance System [Internet]. 2013. 1-82 p. Available from: http://www.phac-aspc.gc.ca/rhs-ssg/phi-isp-2013-eng.php 103.  July C. Canadian Labour Market Developments : Recession Impacts , Recent Trends and Future Outlook. 2009;  104.  T. E, S. C, L. D, A. F, W.J. G. The impact of economic recession on maternal and infant mortality: lessons from history. BMC Public Health [Internet]. 2010;10:727. Available from: http://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=reference&D=emed11&NEWS=N&AN=21106089 105.  Deer R, Jasper B, Mountain R, Deer R, Deer R. Alberta Labour Force Statistics December , 2014 Employment by Industry , Alberta Employment Rate , Canada & Provinces Unemployment Rate , Canada & Provinces. 2014;(December):1–2. Available from: http://work.alberta.ca/documents/labour-force-stats-Dec14-public-package.pdf 106.  Ritchie A, Hrabok M, Igwe O, Omeje J, Ogunsina O, Ambrosano L, et al. Impact of oil recession on community mental health service utilization in an oil sands mining region in Canada. Int J Soc Psychiatry. 2018;64(6):563–9.  107.  Gunby J, Bissonnette F, Librach C, Cowan L. Assisted reproductive technologies (ART) in Canada: 2001 results from the Canadian ART Register. Fertil Steril. 2001;93(7):2189–201.  108.  Gunby J, Bissonnette F, Librach C, Cowan L. Assisted reproductive technologies (ART) in Canada: 2002 results from the Canadian ART Register. Fertil Steril. 2002;93(7):2189–201.  109.  Gunby J, Bissonnette F, Librach C, Cowan L. Assisted reproductive technologies in Canada: 2011 results from the Canadian Assisted Reproductive Technologies Register. Fertil Steril [Internet]. 2011;91(5):1721–30. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0015028208004937 110.  Gunby J, Bissonnette F, Librach C, Cowan L. Assisted reproductive technologies in Canada: 2012 results from the Canadian Assisted Reproductive Technologies Register. Fertil Steril [Internet]. 2012;91(5):1721–30. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0015028208004937 111.  Gunby J, Bissonnette F, Librach C, Cowan L. Assisted reproductive technologies (ART) in Canada: 2003 results from the Canadian ART Register. Fertil Steril. 2003;93(7):2189–201.  112.  Gunby J, Bissonnette F, Librach C, Cowan L. Assisted reproductive technologies (ART) in Canada: 2004 results from the Canadian ART Register. Fertil Steril. 2004;93(7):2189–201.   112 113.  Gunby J, Bissonnette F, Librach C, Cowan L. Assisted reproductive technologies in Canada: 2005 results from the Canadian Assisted Reproductive Technologies Register. Fertil Steril [Internet]. 2005;91(5):1721–30. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0015028208004937 114.  Gunby J, Bissonnette F, Librach C, Cowan L. Assisted reproductive technologies (ART) in Canada: 2006 results from the Canadian ART Register. Fertil Steril. 2006;93(7):2189–201.  115.  Gunby J, Bissonnette F, Librach C, Cowan L. Assisted reproductive technologies (ART) in Canada: 2007 results from the Canadian ART Register. Fertil Steril. 2007;93(7):2189–201.  116.  Gunby J, Bissonnette F, Librach C, Cowan L. Assisted reproductive technologies in Canada: 2008 results from the Canadian Assisted Reproductive Technologies Register. Fertil Steril [Internet]. 2009;91(5):1721–30. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0015028208004937 117.  Gunby J, Bissonnette F, Librach C, Cowan L. Assisted reproductive technologies in Canada: 2009 results from the Canadian Assisted Reproductive Technologies Register. Fertil Steril [Internet]. 2009;91(5):1721–30. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0015028208004937 118.  Gunby J, Bissonnette F, Librach C, Cowan L. Assisted reproductive technologies in Canada: 2010 results from the Canadian Assisted Reproductive Technologies Register. Fertil Steril [Internet]. 2010;91(5):1721–30. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0015028208004937 119.  Groen JA. Sources of error in survey and administrative data: The importance of reporting procedures. J Off Stat. 2012;28(2):173–98.    113 Appendices   Appendix A   Logistic regression     Number of obs = 5939250         LR chi2(58) = 71277.39         Prob > chi2 = 0 Log likelihood = -1555058.8     Pseudo R2 = 0.0224  SGA Birth  OR SE z P>z [95% Conf. Interval] Lagged Real MW 0.98 0.00 -6.63 0.00 0.97 0.99 Year (Ref: 2000)      2001 1.03 0.01 3.01 0.00 1.01 1.05 2002 1.02 0.01 2.34 0.02 1.00 1.04 2003 1.00 0.01 -0.36 0.72 0.98 1.02 2004 0.97 0.01 -3.33 0.00 0.95 0.99 2005 1.00 0.01 0.17 0.86 0.98 1.02 2006 1.02 0.01 2.41 0.02 1.00 1.04 2007 1.01 0.01 1.42 0.16 0.99 1.03 2008 0.97 0.01 -2.87 0.00 0.96 0.99 2009 1.04 0.01 3.91 0.00 1.02 1.06 2010 1.04 0.01 3.74 0.00 1.02 1.06 2011 1.10 0.01 9.61 0.00 1.08 1.12 2012 1.07 0.01 6.64 0.00 1.05 1.09 2013 1.10 0.01 9.36 0.00 1.08 1.12 2014 1.11 0.01 9.81 0.00 1.08 1.13 2015 1.11 0.01 10.12 0.00 1.09 1.13 2016 1.11 0.01 10.02 0.00 1.09 1.14 Mother’s Birth Place (Ref: Canada)     Missing/unknown 1.15 0.01 11.08 0.00 1.13 1.18 North America, excluding Canada  1.03 0.02 1.66 0.10 0.99 1.06 Central America  1.10 0.02 4.84 0.00 1.06 1.14 Caribbean and Bermuda 1.40 0.02 23.92 0.00 1.36 1.44 South America  1.29 0.02 16.01 0.00 1.25 1.33 Africa  1.26 0.02 17.58 0.00 1.23 1.29 Asia  1.38 0.01 43.03 0.00 1.36 1.40 Europe 1.03 0.01 3.54 0.00 1.01 1.05 Oceania  1.47 0.05 12.53 0.00 1.38 1.56 Mother’s Birth Place (Ref: Canada)      Missing/unknown 1.29 0.01 41.87 0.00 1.28 1.31 North America, excluding Canada  1.03 0.02 1.73 0.08 1.00 1.06 Central America  1.12 0.02 6.18 0.00 1.08 1.17 Caribbean and Bermuda 1.33 0.02 21.56 0.00 1.30 1.37 South America  1.31 0.02 16.56 0.00 1.27 1.35 Africa  1.15 0.01 10.73 0.00 1.12 1.18 Asia  1.52 0.01 54.68 0.00 1.50 1.55 Europe 1.00 0.01 0.34 0.74 0.99 1.02 Oceania  1.33 0.04 9.94 0.00 1.26 1.41  114 Marital Status (Ref: Legally Married)      Single  1.26 0.01 56.73 0.00 1.25 1.27 Other (Widowed, Divorced, Common-Law, Unknown) 1.23 0.01 39.54 0.00 1.22 1.24 Maternal Age (ref: 25-29)     <20  0.96 0.01 -5.53 0.00 0.94 0.97 20-24  1.06 0.01 11.51 0.00 1.05 1.07 30-34  1.01 0.00 1.30 0.19 1.00 1.01 35-39 1.07 0.01 12.71 0.00 1.06 1.08 >or= 40 1.17 0.01 17.14 0.00 1.15 1.19 Missing  1.19 0.21 0.97 0.33 0.84 1.67 Number of Liveborn Children (Ref: 1)      2 0.57 0.00 -150.91 0.00 0.57 0.58 3 0.54 0.00 -111.69 0.00 0.54 0.55 4 0.56 0.00 -65.84 0.00 0.55 0.57 5 or more  0.58 0.01 -50.04 0.00 0.57 0.59 Unknown/missing 0.99 0.06 -0.23 0.82 0.87 1.12 Community Size (ref: 1,250,000+)     500,000-1,249,999  1.01 0.00 3.09 0.00 1.01 1.02 100,000- 499,999  0.96 0.00 -7.93 0.00 0.95 0.97 10,000- 99,999  0.97 0.01 -4.52 0.00 0.96 0.99 < 10,000 (rural)   0.96 0.01 -6.81 0.00 0.95 0.97 Missing  1.03 0.02 1.26 0.21 0.98 1.08 Neighborhood Income Quintile (ref: 5 -highest)       1 = lowest  1.19 0.01 31.71 0.00 1.17 1.20 2 1.12 0.01 21.20 0.00 1.11 1.14 3 1.07 0.01 13.02 0.00 1.06 1.09 4 1.03 0.01 6.04 0.00 1.02 1.05 Missing/Unknown 1.07 0.01 4.60 0.00 1.04 1.10                         115 Appendix B   Logistic Regression Model Results in British Columbia  Logistic regression      Number of obs = 703290         LR chi2(56) = 9980.37         Prob > chi2 = 0 Log likelihood = -169569.82     Pseudo R2 = 0.0286  SGA Birth  OR SE z P>z [95% Conf. Interval] Lagged Real MW 0.99 0.03 -0.22 0.82 0.94 1.05 Year (Ref: 2000)      2001 1.09 0.03 3.16 0.00 1.03 1.16 2002 1.09 0.03 2.82 0.01 1.03 1.16 2003 1.06 0.03 1.77 0.08 0.99 1.13 2004 1.03 0.03 1.02 0.31 0.97 1.09 2005 1.03 0.03 1.06 0.29 0.97 1.09 2006 1.05 0.03 1.66 0.10 0.99 1.11 2007 1.03 0.03 1.10 0.27 0.98 1.09 2008 0.98 0.03 -0.58 0.56 0.93 1.04 2009 1.04 0.03 1.19 0.23 0.98 1.11 2010 1.02 0.03 0.73 0.47 0.96 1.09 2011 1.09 0.04 2.42 0.02 1.02 1.16 2012 1.06 0.03 1.88 0.06 1.00 1.12 2013 1.05 0.05 1.11 0.27 0.96 1.16 2014 1.05 0.05 0.93 0.35 0.95 1.15 2015 1.05 0.05 1.14 0.25 0.96 1.16 2016 1.08 0.05 1.75 0.08 0.99 1.19 Mother’s Birth Place (Ref: Canada)     Missing/unknown 1.22 0.07 3.54 0.00 1.09 1.36 North America, excluding Canada  0.98 0.04 -0.56 0.58 0.90 1.06 Central America  1.19 0.06 3.22 0.00 1.07 1.33 Caribbean and Bermuda 1.52 0.14 4.42 0.00 1.26 1.83 South America  1.17 0.07 2.45 0.01 1.03 1.32 Africa  1.49 0.07 8.47 0.00 1.36 1.63 Asia  1.42 0.03 18.77 0.00 1.37 1.47 Europe 1.08 0.03 2.86 0.00 1.02 1.13 Oceania  1.64 0.08 10.64 0.00 1.49 1.79 Mother’s Birth Place (Ref: Canada)      Missing/unknown 1.42 0.03 16.23 0.00 1.36 1.48 North America, excluding Canada  1.03 0.04 0.80 0.42 0.95 1.12 Central America  1.31 0.07 5.01 0.00 1.18 1.46 Caribbean and Bermuda 1.20 0.10 2.28 0.02 1.03 1.41 South America  1.09 0.08 1.18 0.24 0.95 1.25 Africa  1.10 0.05 1.99 0.05 1.00 1.20 Asia  1.53 0.03 22.41 0.00 1.47 1.59 Europe 0.98 0.02 -0.66 0.51 0.94 1.03 Oceania  1.61 0.07 10.91 0.00 1.48 1.76  116 Marital Status (Ref: Legally Married)      Single  1.18 0.02 11.41 0.00 1.15 1.21 Other (Widowed, Divorced, Common-Law, Unknown) 1.23 0.02 12.31 0.00 1.19 1.27 Maternal Age (ref: 25-29)     <20  0.86 0.02 -5.07 0.00 0.82 0.91 20-24  1.03 0.02 2.08 0.04 1.00 1.07 30-34  1.03 0.01 2.67 0.01 1.01 1.06 35-39 1.10 0.02 6.37 0.00 1.07 1.13 >or= 40 1.20 0.03 7.06 0.00 1.14 1.26 Missing  1.00 (empty)     Number of Liveborn Children (Ref: 1)      2 0.51 0.01 -59.26 0.00 0.50 0.52 3 0.48 0.01 -40.95 0.00 0.47 0.50 4 0.49 0.02 -23.05 0.00 0.46 0.52 5 or more  0.49 0.02 -16.78 0.00 0.45 0.53 Unknown/missing 0.48 0.35 -1.02 0.31 0.11 1.98 Community Size (ref: 1,250,000+)     500,000-1,249,999  1.00 (empty)     100,000- 499,999  0.94 0.01 -3.93 0.00 0.92 0.97 10,000- 99,999  1.01 0.01 0.82 0.41 0.98 1.04 < 10,000 (rural)   1.09 0.02 5.04 0.00 1.05 1.13 Missing  1.69 0.46 1.93 0.05 0.99 2.88 Neighborhood Income Quintile (ref: 5 -highest)       1 = lowest  1.12 0.02 7.03 0.00 1.09 1.16 2 1.13 0.02 7.54 0.00 1.10 1.17 3 1.08 0.02 4.69 0.00 1.05 1.12 4 1.05 0.02 2.65 0.01 1.01 1.08 Missing/Unknown 0.98 0.04 -0.41 0.68 0.91 1.06                            117 Appendix C   Logistic Regression Model Results in Alberta  Logistic regression      Number of obs = 781665         LR chi2(56) = 10722.28         Prob > chi2 = 0 Log likelihood = -214148.21     Pseudo R2 = 0.0244  SGA Birth  OR SE z P>z [95% Conf. Interval] Lagged Real MW 1.01 0.02 0.72 0.47 0.98 1.04 Year (Ref: 2000)      2001 1.01 0.03 0.51 0.61 0.96 1.07 2002 0.96 0.03 -1.60 0.11 0.90 1.01 2003 0.96 0.03 -1.44 0.15 0.90 1.02 2004 0.95 0.03 -1.48 0.14 0.90 1.02 2005 0.98 0.03 -0.63 0.53 0.92 1.04 2006 0.99 0.03 -0.24 0.81 0.94 1.05 2007 0.97 0.03 -1.05 0.29 0.92 1.02 2008 0.93 0.02 -2.88 0.00 0.88 0.98 2009 0.96 0.03 -1.41 0.16 0.91 1.02 2010 0.95 0.03 -1.46 0.15 0.89 1.02 2011 1.00 0.03 0.08 0.94 0.94 1.07 2012 0.99 0.03 -0.33 0.75 0.93 1.06 2013 1.03 0.04 0.91 0.36 0.96 1.11 2014 1.01 0.04 0.36 0.72 0.94 1.09 2015 1.02 0.04 0.52 0.60 0.95 1.10 2016 1.02 0.05 0.35 0.73 0.93 1.11 Mother’s Birth Place (Ref: Canada)     Missing/unknown 1.41 0.12 3.86 0.00 1.18 1.67 North America, excluding Canada  1.05 0.04 1.10 0.27 0.97 1.13 Central America  1.03 0.05 0.70 0.48 0.94 1.13 Caribbean and Bermuda 1.29 0.09 3.75 0.00 1.13 1.47 South America  1.09 0.05 1.79 0.07 0.99 1.20 Africa  1.31 0.05 7.85 0.00 1.22 1.40 Asia  1.35 0.03 15.16 0.00 1.29 1.40 Europe 1.00 0.03 -0.17 0.86 0.95 1.05 Oceania  1.61 0.10 7.59 0.00 1.42 1.82 Mother’s Birth Place (Ref: Canada)      Missing/unknown 1.33 0.03 14.93 0.00 1.28 1.38 North America, excluding Canada  1.03 0.05 0.74 0.46 0.95 1.13 Central America  1.20 0.06 3.86 0.00 1.09 1.31 Caribbean and Bermuda 1.41 0.08 6.21 0.00 1.27 1.58 South America  1.12 0.06 2.18 0.03 1.01 1.24 Africa  1.32 0.04 8.21 0.00 1.23 1.41 Asia  1.65 0.03 25.16 0.00 1.59 1.72 Europe 1.01 0.03 0.41 0.68 0.96 1.06 Oceania  1.39 0.08 5.36 0.00 1.23 1.56  118 Marital Status (Ref: Legally Married)      Single  1.27 0.02 14.72 0.00 1.23 1.31 Other (Widowed, Divorced, Common-Law, Unknown) 1.28 0.02 20.14 0.00 1.25 1.31 Maternal Age (ref: 25-29)     <20  0.84 0.02 -7.93 0.00 0.81 0.88 20-24  0.98 0.01 -1.88 0.06 0.95 1.00 30-34  1.03 0.01 3.01 0.00 1.01 1.06 35-39 1.10 0.02 7.07 0.00 1.07 1.13 >or= 40 1.20 0.03 7.03 0.00 1.14 1.27 Missing  1.00 (empty)     Number of Liveborn Children (Ref: 1)      2 0.58 0.01 -55.00 0.00 0.57 0.59 3 0.53 0.01 -44.37 0.00 0.51 0.54 4 0.50 0.01 -30.06 0.00 0.48 0.53 5 or more  0.52 0.01 -24.25 0.00 0.50 0.55 Unknown/missing 0.55 0.57 -0.57 0.57 0.07 4.22 Community Size (ref: 1,250,000+)     500,000-1,249,999  1.00 0.08 0.05 0.96 0.87 1.16 100,000- 499,999  1.00 0.09 0.04 0.97 0.85 1.18 10,000- 99,999  1.00 0.08 0.05 0.96 0.87 1.16 < 10,000 (rural)   0.98 0.07 -0.31 0.75 0.84 1.13 Missing  1.00 (omitted)     Neighborhood Income Quintile (ref: 5 -highest)       1 = lowest  1.10 0.02 6.86 0.00 1.07 1.14 2 1.09 0.02 5.62 0.00 1.06 1.12 3 1.05 0.02 3.26 0.00 1.02 1.08 4 1.04 0.02 2.53 0.01 1.01 1.07 Missing/Unknown 1.02 0.03 0.59 0.55 0.96 1.08                           119 Appendix D   Logistic Regression Model Results in Ontario  Logistic regression    Number of obs = 2242095        LR chi2(58) = 33789.08        Prob > chi2 = 0 Log likelihood = -604326.29    Pseudo R2 = 0.0272  SGA Birth  OR SE z P>z [95% Conf. Interval] Lagged Real MW 0.98 0.01 -1.15 0.25 0.96 1.01 Year (Ref: 2000)      2001 1.02 0.02 1.39 0.17 0.99 1.05 2002 1.02 0.02 0.89 0.37 0.98 1.05 2003 1.00 0.02 -0.14 0.89 0.96 1.04 2004 0.97 0.02 -1.61 0.11 0.93 1.01 2005 1.01 0.02 0.32 0.75 0.97 1.04 2006 1.02 0.02 0.95 0.35 0.98 1.05 2007 1.01 0.02 0.79 0.43 0.98 1.04 2008 0.99 0.02 -0.57 0.57 0.96 1.02 2009 1.02 0.02 1.14 0.25 0.99 1.05 2010 1.05 0.03 2.04 0.04 1.00 1.10 2011 1.09 0.03 3.02 0.00 1.03 1.16 2012 1.07 0.03 2.52 0.01 1.01 1.12 2013 1.08 0.03 3.29 0.00 1.03 1.14 2014 1.09 0.03 3.90 0.00 1.05 1.14 2015 1.11 0.03 4.03 0.00 1.05 1.16 2016 1.13 0.03 4.79 0.00 1.07 1.18 Mother’s Birth Place (Ref: Canada)     Missing/unknown 1.27 0.04 8.44 0.00 1.20 1.35 North America, excluding Canada  1.03 0.03 1.21 0.23 0.98 1.09 Central America  1.08 0.03 2.81 0.01 1.02 1.14 Caribbean and Bermuda 1.38 0.02 18.42 0.00 1.33 1.43 South America  1.35 0.03 15.07 0.00 1.30 1.41 Africa  1.30 0.02 13.96 0.00 1.25 1.35 Asia  1.37 0.01 29.77 0.00 1.34 1.40 Europe 1.01 0.01 0.89 0.38 0.99 1.04 Oceania  1.23 0.08 3.05 0.00 1.08 1.40 Mother’s Birth Place (Ref: Canada)      Missing/unknown 1.22 0.01 18.30 0.00 1.19 1.25 North America, excluding Canada  1.00 0.03 0.09 0.93 0.95 1.06 Central America  1.08 0.03 2.54 0.01 1.02 1.14 Caribbean and Bermuda 1.30 0.02 15.84 0.00 1.26 1.35 South America  1.40 0.03 16.23 0.00 1.34 1.46 Africa  1.20 0.02 9.53 0.00 1.16 1.25 Asia  1.47 0.02 35.46 0.00 1.44 1.51 Europe 1.00 0.01 0.12 0.91 0.98 1.03 Oceania  1.05 0.07 0.80 0.42 0.93 1.19  120 Marital Status (Ref: Legally Married)      Single  1.32 0.01 33.42 0.00 1.30 1.34 Other (Widowed, Divorced, Common-Law, Unknown) 1.19 0.01 23.31 0.00 1.17 1.21 Maternal Age (ref: 25-29)     <20  1.08 0.02 5.71 0.00 1.05 1.11 20-24  1.11 0.01 12.47 0.00 1.09 1.13 30-34  0.98 0.01 -3.58 0.00 0.96 0.99 35-39 1.01 0.01 1.13 0.26 0.99 1.03 >or= 40 1.11 0.02 7.22 0.00 1.08 1.14 Missing  1.16 0.28 0.64 0.52 0.73 1.85 Number of Liveborn Children (Ref: 1)      2 0.60 0.00 -88.50 0.00 0.59 0.60 3 0.56 0.00 -66.60 0.00 0.55 0.57 4 0.57 0.01 -38.86 0.00 0.56 0.59 5 or more  0.56 0.01 -30.66 0.00 0.54 0.58 Unknown/missing 1.10 0.08 1.41 0.16 0.96 1.26 Community Size (ref: 1,250,000+)     500,000-1,249,999  0.79 0.01 -26.74 0.00 0.78 0.81 100,000- 499,999  0.89 0.01 -16.69 0.00 0.88 0.90 10,000- 99,999  0.91 0.01 -8.24 0.00 0.89 0.93 < 10,000 (rural)   0.82 0.01 -19.04 0.00 0.80 0.84 Missing  0.93 0.03 -2.34 0.02 0.87 0.99 Neighborhood Income Quintile (ref: 5 -highest)       1 = lowest  1.21 0.01 21.98 0.00 1.19 1.24 2 1.13 0.01 14.00 0.00 1.11 1.15 3 1.07 0.01 7.47 0.00 1.05 1.09 4 1.02 0.01 2.53 0.01 1.01 1.04 Missing/Unknown 1.10 0.02 4.48 0.00 1.06 1.15                            121 Appendix E   Logistic Regression Model Results in Quebec  Logistic regression     Number of obs = 1350040         LR chi2(57) = 12049.47         Prob > chi2 = 0 Log likelihood = -351407.47     Pseudo R2 = 0.0169   SGA Birth  OR SE z P>z [95% Conf. Interval] Lagged Real MW 1.05 0.03 1.51 0.13 0.99 1.12 Year (Ref: 2000)      2001 1.04 0.02 2.02 0.04 1.00 1.09 2002 1.06 0.02 2.73 0.01 1.02 1.11 2003 1.02 0.02 0.90 0.37 0.97 1.07 2004 0.97 0.02 -1.28 0.20 0.93 1.02 2005 1.02 0.02 1.05 0.30 0.98 1.07 2006 1.07 0.02 2.79 0.01 1.02 1.12 2007 1.07 0.02 2.98 0.00 1.02 1.12 2008 0.98 0.02 -0.95 0.34 0.94 1.02 2009 1.06 0.02 2.74 0.01 1.02 1.10 2010 1.07 0.02 3.26 0.00 1.03 1.11 2011 1.10 0.04 2.43 0.02 1.02 1.19 2012 1.02 0.04 0.65 0.51 0.95 1.10 2013 1.05 0.04 1.23 0.22 0.97 1.13 2014 1.05 0.05 1.14 0.25 0.96 1.15 2015 1.04 0.05 0.90 0.37 0.95 1.14 2016 1.02 0.05 0.41 0.68 0.93 1.12 Mother’s Birth Place (Ref: Canada)     Missing/unknown 1.09 0.02 4.88 0.00 1.05 1.13 North America, excluding Canada  1.06 0.05 1.28 0.20 0.97 1.17 Central America  1.07 0.05 1.46 0.14 0.98 1.17 Caribbean and Bermuda 1.28 0.04 8.51 0.00 1.21 1.36 South America  1.02 0.04 0.53 0.60 0.94 1.11 Africa  1.01 0.03 0.36 0.72 0.96 1.06 Asia  1.21 0.03 7.89 0.00 1.16 1.27 Europe 1.02 0.02 1.02 0.31 0.98 1.07 Oceania  1.03 0.23 0.15 0.88 0.67 1.61 Mother’s Birth Place (Ref: Canada)      Missing/unknown 1.24 0.02 16.18 0.00 1.21 1.28 North America, excluding Canada  1.17 0.04 4.11 0.00 1.09 1.26 Central America  1.04 0.05 0.97 0.33 0.96 1.14 Caribbean and Bermuda 1.20 0.03 6.41 0.00 1.13 1.26 South America  0.96 0.04 -0.98 0.33 0.88 1.04 Africa  1.04 0.03 1.36 0.17 0.98 1.09 Asia  1.33 0.03 11.80 0.00 1.27 1.40 Europe 0.97 0.02 -1.36 0.17 0.93 1.01 Oceania  0.92 0.17 -0.44 0.66 0.64 1.32  122 Marital Status (Ref: Legally Married)      Single  1.16 0.01 18.19 0.00 1.14 1.18 Other (Widowed, Divorced, Common-Law, Unknown) 1.14 0.02 7.47 0.00 1.10 1.18 Maternal Age (ref: 25-29)     <20  1.03 0.02 1.68 0.09 0.99 1.07 20-24  1.07 0.01 7.13 0.00 1.05 1.09 30-34  1.05 0.01 5.42 0.00 1.03 1.06 35-39 1.17 0.01 13.91 0.00 1.14 1.19 >or= 40 1.32 0.03 13.31 0.00 1.26 1.37 Missing  1.00 (empty)     Number of Liveborn Children (Ref: 1)      2 0.55 0.00 -76.82 0.00 0.54 0.56 3 0.51 0.01 -56.87 0.00 0.49 0.52 4 0.52 0.01 -32.09 0.00 0.50 0.54 5 or more  0.57 0.02 -21.37 0.00 0.54 0.60 Unknown/missing 0.91 0.43 -0.20 0.84 0.36 2.29 Community Size (ref: 1,250,000+)     500,000-1,249,999  0.91 0.01 -8.85 0.00 0.89 0.93 100,000- 499,999  0.98 0.01 -1.43 0.15 0.95 1.01 10,000- 99,999  1.01 0.01 1.03 0.31 0.99 1.04 < 10,000 (rural)   1.03 0.01 2.96 0.00 1.01 1.05 Missing  0.76 0.35 -0.60 0.55 0.31 1.88 Neighborhood Income Quintile (ref: 5 -highest)       1 = lowest  1.25 0.01 20.19 0.00 1.22 1.28 2 1.13 0.01 10.86 0.00 1.11 1.16 3 1.09 0.01 7.81 0.00 1.07 1.12 4 1.03 0.01 2.88 0.00 1.01 1.06 Missing/Unknown 0.99 0.04 -0.24 0.81 0.92 1.07         

Cite

Citation Scheme:

        

Citations by CSL (citeproc-js)

Usage Statistics

Share

Embed

Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                        
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            src="{[{embed.src}]}"
                            data-item="{[{embed.item}]}"
                            data-collection="{[{embed.collection}]}"
                            data-metadata="{[{embed.showMetadata}]}"
                            data-width="{[{embed.width}]}"
                            async >
                            </script>
                            </div>
                        
                    
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:
https://iiif.library.ubc.ca/presentation/dsp.24.1-0376031/manifest

Comment

Related Items