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Birth Outcomes of Immigrants to Urban Ontario. A population-based study.
by
Marcelo Luis Urquia
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy
Dalla Lana School of Public Health Sciences
University of Toronto
© Copyright by Marcelo Luis Urquia (2009)
ii
Birth Outcomes of Immigrants to Urban Ontario.
A population-based study.
Marcelo Luis Urquia
Doctor of Philosophy (Epidemiology)
Dalla Lana School of Public Health Sciences University of Toronto
2009
Abstract
The total number of births among immigrants is on the rise and currently exceeds one fifth of
live births within industrialized countries. The relation between adverse birth outcomes and
migration remains unclear.
The objectives of this thesis are to undertake a literature review to clarify the relation between
migration and adverse birth outcomes, and to examine the interplay between duration of
residence, maternal country of origin, and the residential environment using data on immigrants
to Ontario Census Metropolitan Areas. The findings indicate that:
a) Analyzing disparities in birth outcomes by migrant status with migrants defined as a single
category is not informative. Rather, ethnicity and country of origin are important predictors of
birth outcomes among immigrants.
b) Duration of residence is linearly associated with low infant birth weight and preterm birth,
mainly driven by decreases in gestational age with prolonged stay in Canada.
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c) The detrimental effects of long duration of residence on preterm birth are modestly attenuated,
but not prevented, among immigrants living in urban neighbourhoods characterized by low
material deprivation.
d) Neighbourhood material deprivation has little, if any, influence on birth outcomes of recent
immigrants, and only becomes influential after 15 years of stay in Canada. Maternal world
region of origin constitutes a stronger predictor of adverse birth outcomes among recent
immigrants.
These findings stress the importance of the maternal country of birth and duration of residence as
key predictors of immigrants’ health. They also support further research aimed at clarifying the
nature of the association between time spent in Canada after migration and decreases in
gestational age at delivery, and the identification of immigrant groups at high risk of adverse
birth outcomes, based on these two key predictors.
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Acknowledgments
This thesis is the final product of a process that started some years ago, when I was doing my
Masters program. Most of the people directly or indirectly supporting my work remained the
same along the way. In first place, I thank my supervisor John Frank for his continuous financial,
academic, and social support. John encouraged me to go deeper in my scientific inquiry by
stressing my achievements rather than my limitations. He always had time to assist me when
needed, despite his extremely busy schedule. My other committee members, Rick Glazier and
Rahim Moineddin, were also readily available every time I needed them. My co-supervisor, Rick
Glazier, was the key person to identify and access data sources and research opportunities. He
provided me with student space and administrative support at the St. Michael Hospital and
supported my data analyses at ICES. Now I thank both John and Rick for having encouraged me
to pursue this thesis instead of other less fruitful topics I was attracted to. Rahim not only served
as my biostatistician but also as an insightful interlocutor to discuss the relation between
migration and health. I learnt more than biostatistics from him. I hope my committee had enjoyed
our meetings as much as I did. I also would like to acknowledge the ROAM Collaboration,
particularly Anita Gagnon. My involvement with this group of researchers certainly promoted
my interest in the area of research of this thesis. Alex Kopp and Kinwah Fung from ICES also
deserve my gratitude for being so helpful to clarify my concerns about the administrative data
sources. Discussions with other people, such as Flora Matheson and all the participants of the
Time Trends meetings, also fuelled my enthusiasm in trying a little bit harder. I also have to
acknowledge Marisa Creatore for sharing the long process of understanding the immigrant data. I
am also grateful to Doug Manuel and Patricia O’Campo, who have kindly accepted to review my
protocols since my Masters programs, providing useful tips to improve my theses, and my
Departmental reviewers Dionne Gesink Law and Joel Ray, and my external reviewer K.S.
Joseph, who also provided helpful comments and corrections. I would also like to thank staff at
the Institute of Population and Public Health (IPPH), Institute for Work and Health (IWH), St.
Michael Hospital, and ICES, which routine work indirectly supported the progress of this thesis:
Gail Bryant and Vera Ndaba at IPPH, Sandra Sinclair and Mary Cicinelli at the IWH, J.R.,
Jackson Wong, and Donna Hoppenheim at ICES, and Claudeth White at the St. Michael
Hospital. Finally I thank my wife Denise for her intangible, but not negligible, contribution to
this thesis through her positive influence on my self.
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Table of Contents TABLE OF CONTENTS............................................................................................................................................ V
LIST OF TABLES ..................................................................................................................................................... IX
LIST OF FIGURES ...................................................................................................................................................XI
LIST OF APPENDICES.......................................................................................................................................... XII
ABBREVIATIONS .................................................................................................................................................XIII
CHAPTER 1 INTRODUCTION ................................................................................................................................ 1
1.1. BACKGROUND ................................................................................................................................................... 1
1.2. STUDY OBJECTIVES......................................................................................................................................... 4
1.3. INVOLVEMENT/PARTICIPATION OF AUTHOR AND CO-AUTHORS IN THE RESEARCH............ 5
1.4. ORGANIZATION OF THE THESIS ................................................................................................................. 6
1.4.1. RATIONALE FOR THE OBJECTIVES ................................................................................................................. 6 1.4.2. OVERVIEW OF THE RESEARCH ....................................................................................................................... 9
1.5. REFERENCES.................................................................................................................................................... 12
CHAPTER 2 INTERNATIONAL MIGRATION AND ADVERSE BIRTH OUTCOMES: ROLE OF
ETHNICITY, REGION OF ORIGIN AND DESTINATION ............................................................................... 15
ABSTRACT ................................................................................................................................................................ 15
2.1. INTRODUCTION............................................................................................................................................... 16
2.2. METHODS .......................................................................................................................................................... 17
2.2.1. STUDY POPULATION...................................................................................................................................... 17 2.2.2. SEARCH AND STUDY SELECTION CRITERIA.................................................................................................. 17 2.2.3. DATA EXTRACTION ....................................................................................................................................... 19 2.2.4. STATISTICAL ANALYSES ............................................................................................................................... 19
2.3. RESULTS............................................................................................................................................................. 21
2.3.1. MIGRATION AND RACE/ETHNICITY .............................................................................................................. 22 2.3.2. MIGRATION AND WORLD REGIONS .............................................................................................................. 25
2.4. DISCUSSION ...................................................................................................................................................... 27
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2.4.1. MIGRATION AND ETHNIC DISPARITIES ........................................................................................................ 31 2.4.2. MIGRATION AND REGION OF ORIGIN AND DESTINATION ............................................................................ 32 2.4.3. FURTHER RESEARCH .................................................................................................................................... 33
2.5. REFERENCES.................................................................................................................................................... 35
CHAPTER 3 INCREASE IN PRETERM BIRTHS ASSOCIATED WITH DURATION OF RESIDENCE
AMONG IMMIGRANTS LIVING IN ONTARIO METROPOLITAN AREAS................................................ 46
ABSTRACT ................................................................................................................................................................ 46
3.1. INTRODUCTION............................................................................................................................................... 47
3.2. METHODS .......................................................................................................................................................... 49
3.2.1. DATA SOURCES.............................................................................................................................................. 49 3.2.2. OUTCOMES .................................................................................................................................................... 51 3.2.3. PREDICTORS.................................................................................................................................................. 51 3.2.4. STATISTICAL ANALYSES ............................................................................................................................... 53
3.3. RESULTS............................................................................................................................................................. 54
3.3.1. SENSITIVITY ANALYSES ................................................................................................................................ 61
3.4. DISCUSSION ...................................................................................................................................................... 63
3.5. REFERENCES.................................................................................................................................................... 70
CHAPTER 4 THE INTERPLAY BETWEEN IMMIGRANTS’ COUNTRY OF BIRTH AND
NEIGHBOURHOOD DEPRIVATION ON BIRTH OUTCOMES ...................................................................... 78
ABSTRACT ................................................................................................................................................................ 78
4.1. INTRODUCTION............................................................................................................................................... 79
4.2. METHODS .......................................................................................................................................................... 80
4.2.1. DATA.............................................................................................................................................................. 80 4.2.2. OUTCOMES .................................................................................................................................................... 81 4.2.3. PREDICTORS.................................................................................................................................................. 82 4.2.4. STATISTICAL ANALYSES ............................................................................................................................... 83 4.2.5. MODELING STRATEGY .................................................................................................................................. 84
4.3. RESULTS............................................................................................................................................................. 86
4.4. DISCUSSION ...................................................................................................................................................... 92
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4.5. REFERENCES.................................................................................................................................................... 98
CHAPTER 5 THE DIFFERENTIAL DETERIORATION OF PRETERM BIRTH AMONG URBAN
IMMIGRANTS BY NEIGHBOURHOOD DEPRIVATION .............................................................................. 107
ABSTRACT .............................................................................................................................................................. 107
5.1. INTRODUCTION............................................................................................................................................. 108
5.2. METHODS ........................................................................................................................................................ 109
5.3. RESULTS........................................................................................................................................................... 110
5.4. DISCUSSION .................................................................................................................................................... 112
5.5. REFERENCES.................................................................................................................................................. 113
CHAPTER 6 DISCUSSION.................................................................................................................................... 116
6.1. MAIN FINDINGS ............................................................................................................................................. 116
6.3. IMPLICATIONS FOR PRACTICE AND FUTURE RESEARCH............................................................. 121
6.4. UNANSWERED QUESTIONS AND FUTURE RESEARCH ..................................................................... 124
6.4.1. WHY IS DURATION OF RESIDENCE ASSOCIATED WITH PRETERM BIRTH?..................................................... 124 6.4.2. IS THE ASSOCIATION BETWEEN TIME SINCE MIGRATION AND PRETERM BIRTH MERELY A CANADIAN
PHENOMENON? ...................................................................................................................................................... 129 6.4.3. IS TIME SINCE MIGRATION ASSOCIATED WITH OTHER PREGNANCY-RELATED OUTCOMES? ........................ 130 6.4.4. WHY DO SOME MIGRANT GROUPS EXPERIENCE POOR OUTCOMES AND OTHERS DO NOT? ........................... 131
6.5. CONCLUDING REMARK.............................................................................................................................. 132
APPENDICES .......................................................................................................................................................... 140
APPENDIX 2.A. SEARCH STRATEGY............................................................................................................... 140
APPENDIX 3.A. DATA SOURCES ....................................................................................................................... 143
APPENDIX 3.B. MEASUREMENT OF STILLBIRTHS AND MULTIPLE BIRTHS USING THE
DISCHARGE ABSTRACT DATABASE .............................................................................................................. 151
APPENDIX 3.C. FLOWCHART DATA EXCLUSIONS .................................................................................... 162
APPENDIX 3.D. COVARIATE ADJUSTMENT BASED ON DIRECTED ACYCLIC GRAPHS (DAGS).. 164
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APPENDIX 3.E. USING A COHORT APPROACH TO RULE OUT CONFOUNDING BY COHORT
EFFECTS.................................................................................................................................................................. 169
APPENDIX 4.A. CROSS CLASSIFIED RANDOM EFFECTS MODEL (CCREM)....................................... 173
COPYRIGHT ACKNOWLEDGEMENTS ........................................................................................................... 174
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List of Tables
TABLE 1.1. STUDY OBJECTIVES AND RESEARCH QUESTIONS ...................................................................................... 4 TABLE 2.1. CHARACTERISTICS OF THE US-STUDIES INCLUDED IN THE META-ANALYSIS BY RACE/ETHNICITY ......... 21 TABLE 2.2. ODDS RATIOS (AND 95% CONFIDENCE INTERVALS) FOR ADVERSE BIRTH OUTCOMES BETWEEN ETHNIC
GROUPS AMONG MIGRANTS, AMONG US-BORN, AND BETWEEN MIGRANTS AND US-BORN, BY
RACE/ETHNICITY. ................................................................................................................................................ 24 TABLE 2.3: CHARACTERISTICS OF THE STUDIES INCLUDED IN THE META-ANALYSIS OF LBW BY WORLD REGIONS 25 TABLE 2.4: ODDS RATIOS (AND 95% CONFIDENCE INTERVALS) FOR LOW BIRTHWEIGHT BETWEEN INFANTS BORN
TO MIGRANT WOMEN FROM VARIOUS WORLD REGIONS IN EUROPE VERSUS EUROPEAN-BORN WOMEN, FROM
VARIOUS WORLD REGIONS IN THE UNITED STATES VERSUS US-BORN WOMEN, AND BETWEEN NATIVE-BORN
AND MIGRANT GROUPS IN EUROPE VERSUS THE US. ....................................................................................... 26 TABLE 3.1: CHARACTERISTICS OF THE STUDY POPULATION, BY MIGRANT STATUS, AND DURATION OF RESIDENCE,
URBAN ONTARIO, LIVE BIRTHS 2002-2007....................................................................................................... 55 TABLE 3.2. UNADJUSTED ODDS RATIOS (AND 95% CONFIDENCE INTERVALS) FOR ADVERSE BIRTH OUTCOMES
BETWEEN NON-IMMIGRANTS AND IMMIGRANTS, OVERALL AND BY DURATION OF RESIDENCE IN CANADA,
2002/2003 TO 2006/2007 ................................................................................................................................ 56 TABLE 3.3: ADJUSTED ODDS RATIOS (AND 95% CONFIDENCE INTERVALS) FOR ADVERSE BIRTH OUTCOMES BY
IMMIGRANTS’ DURATION OF RESIDENCE IN CANADA, URBAN ONTARIO LIVE BIRTHS 2002-2007.................... 58 TABLE 3.4. ODDS RATIOS ADJUSTED FOR ALL COVARIATES IN TABLE 3.3 AND ALSO ADJUSTED FOR PRETERM BIRTH
............................................................................................................................................................................ 58 TABLE 3.5: ADJUSTED* ODDS RATIOS PER 5-YEAR INCREASE IN DURATION OF RESIDENCE IN CANADA (BIRTH TO
IMMIGRANTS 2002-2007), BY WORLD REGION .................................................................................................. 61 TABLE 4.1. CHARACTERISTICS OF THE STUDY POPULATION BY GEOGRAPHY, MEAN INFANT’S BIRTHWEIGHT AND
LOW BIRTHWEIGHT AMONG RECENT IMMIGRANT MOTHERS TO URBAN ONTARIO. ............................................ 85 TABLE 4.2. FIXED EFFECTS (AND 95% CI) OF THE NEIGHBOURHOOD INDICES ON INFANT’S BIRTHWEIGHT (IN
GRAMS) AND RANDOM EFFECTS (AND STANDARD ERRORS) AMONG RECENT IMMIGRANTS TO URBAN ONTARIO.
............................................................................................................................................................................ 87 TABLE 4.3. FIXED EFFECTS (AND 95% CI) OF WORLD REGIONS ON INFANT’S BIRTHWEIGHT (IN GRAMS) AMONG
RECENT IMMIGRANTS TO URBAN ONTARIO. ....................................................................................................... 90 TABLE 4.4. ODDS RATIOS (AND 95% CI) OF WORLD REGIONS ON INFANT’S LOW BIRTHWEIGHT AMONG RECENT
IMMIGRANTS TO URBAN ONTARIO. ..................................................................................................................... 91 TABLE 5.1: ADJUSTED ODDS RATIOS (AND 95% CONFIDENCE INTERVALS) OF ONE STANDARD DEVIATION
INCREASE IN THE MATERIAL DEPRIVATION INDEX AND 10% INCREASE IN THE POPULATION LIVING BELOW THE
LOW-INCOME CUT-OFF ON PRETERM BIRTH, BY IMMIGRANT STATUS AND DURATION OF RESIDENCE, URBAN
ONTARIO, 2002-2007...................................................................................................................................... 110 TABLE 3.A.1. VARIABLE DEFINITIONS........................................................................................................................ 147
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TABLE 3.B.1. MEASUREMENT OF STILLBIRTHS (FETAL DEATHS PER 1,000 TOTAL BIRTHS) IN THE ONTARIO DAD-
CIHI AT ICES (FISCAL 1988/1989-2006/2007), BY METHOD, AND IN THE ONTARIO VITAL STATISTICS
(CALENDAR 1991-2004) .................................................................................................................................. 152 TABLE 3.B.2. MEASUREMENT OF MULTIPLE BIRTHS (MULTIPLE BIRTHS PER 100 TOTAL BIRTHS) IN THE ONTARIO
DAD-CIHI AT ICES (FISCAL 1988/1989-2006/2007), BY METHOD, AND IN THE ONTARIO VITAL STATISTICS
(CALENDAR 1991-2004) .................................................................................................................................. 155 TABLE 3.B.3. PERCENTILES OF BIRTHWEIGHT (IN GRAMS) BY METHOD .................................................................. 157 TABLE 3.B.4. LIST OF ICD CODES FOR STILLBIRTHS ACCORDING TO REVISION AND UNIT OF ANALYSIS ............... 158 TABLE 3.B.5. LIST OF ICD CODES FOR MULTIPLE BIRTHS ACCORDING TO REVISION AND UNIT OF ANALYSIS ....... 159 TABLE 3.E.1: IMMIGRANTS, BY WORLD REGION, VERSUS NON-IMMIGRANTS........................................................... 170 TABLE 3.E.2. ODDS RATIOS* (AND 85% CONFIDENCE INTERVALS) FOR IMMIGRANTS, BY WORLD REGION, VERSUS
NON-IMMIGRANTS ............................................................................................................................................. 171 TABLE 3.E.3. NUMBER AND PERCENTAGE OF LOW BIRTHWEIGHT (LBW), PRETERM BIRTH (PRT), AND SMALL FOR
GESTATIONAL AGE (SGA), AMONG RESIDENTS OF ONTARIO CENSUS METROPOLITAN AREAS, NON-
IMMIGRANTS AND IMMIGRANTS (ARRIVED 1985-1988) BY DURATION OF RESIDENCE IN CANADA, (BIRTHS
1988/89 TO 2006/2007) ................................................................................................................................. 171 TABLE 3.E.4. ODDS RATIOS* (AND 95% CI) COMPARING IMMIGRANTS BY DURATION OF RESIDENCE VERSUS NON-
IMMIGRANTS...................................................................................................................................................... 172 TABLE 3.E.5. ODDS RATIOS* (AND 95% CI) COMPARING IMMIGRANTS BY DURATION OF RESIDENCE .................. 172
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List of Figures
FIGURE 3.1. PREDICTED PROBABILITIES (AND 95% CI) OF PRETERM BIRTH (2002-2007) AMONG ONTARIO
IMMIGRANTS, BY DURATION OF RESIDENCE* ..................................................................................................... 59 FIGURE 3.2. GESTATIONAL AGE DISTRIBUTIONS (AND MEANS) BY DURATION OF RESIDENCE GROUPS.................... 60 FIGURE 3.3. PREDICTED PROBABILITIES* OF PRETERM BIRTH ACCORDING TO DURATION OF RESIDENCE, BY
COHORT OF ARRIVAL .......................................................................................................................................... 62 FIGURE 4.1. DISTRIBUTION OF BIRTHS BY NEIGHBOURHOOD MATERIAL DEPRIVATION TERTILES IN EACH WORLD
SUB-REGION........................................................................................................................................................ 89 FIGURE 4.2: CONFOUNDING BY SELF-SELECTION OF RECENT IMMIGRANTS TO NEIGHBOURHOODS ........................ 96 FIGURE 5.1. PREDICTED PROBABILITIES OF PRETERM BIRTH (2002-2007) BY DURATION OF RESIDENCE AND
NEIGHBOURHOOD DEPRIVATION TERTILES AMONG IMMIGRANTS TO URBAN ONTARIO................................... 111 FIGURE 3.B.1. MEASUREMENT OF STILLBIRTHS IN THE ONTARIO DAD-CIHI AT ICES (FISCAL 1988/1989-
2006/2007), BY METHOD, AND IN THE ONTARIO VITAL STATISTICS (CALENDAR 1991-2004) ..................... 153 FIGURE 3.B.2. MEASUREMENT OF MULTIPLE BIRTHS IN THE ONTARIO DAD-CIHI AT ICES (FISCAL 1988/1989-
2006/2007), BY METHOD, AND IN THE ONTARIO VITAL STATISTICS (CALENDAR 1991-2004) ..................... 156 FIGURE 3.D. DIRECTED ACYCLIC GRAPHS FOR SUFFICIENT CONFOUNDING, BEFORE (3.D.1) AND AFTER (3.D.2)
THE BACKDOOR TEST FOR SUFFICIENCY.......................................................................................................... 164
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List of Appendices
APPENDIX 2.A. SEARCH STRATEGY .......................................................................................................................... 140 APPENDIX 3.A. DATA SOURCES................................................................................................................................. 143 APPENDIX 3.B. MEASUREMENT OF STILLBIRTHS AND MULTIPLE BIRTHS USING THE DISCHARGE ABSTRACT
DATABASE ........................................................................................................................................................ 151 APPENDIX 3.C. FLOWCHART DATA EXCLUSIONS .................................................................................................... 162 APPENDIX 3.D. COVARIATE ADJUSTMENT BASED ON DIRECTED ACYCLIC GRAPHS (DAGS).............................. 164 APPENDIX 3.E. USING A COHORT APPROACH TO RULE OUT CONFOUNDING BY COHORT EFFECTS .................... 169 APPENDIX 4.A. CROSS CLASSIFIED RANDOM EFFECTS MODEL (CCREM)............................................................. 173
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Abbreviations
ARTs: Assisted reproductive technologies
BW: Birthweight
CCI: Canadian Classification of Health Interventions
CCP: Canadian Classification of Diagnostic, Therapeutic, and Surgical Procedures
CMA: Census Metropolitan Area
CIC: Citizenship and Immigration Canada
CIHI: Canadian Institute for Health Information
CCREM: Cross-classified Random Effects Model
CRH: Corticotrophin-releasing hormone
CT: Census tract
DA: Dissemination Area
DAD: Discharge Abstract Database
DAG: Directed acyclic graph
EA: Enumeration Area
ICD-9: International Classification of Diseases - 9th Revision
ICD-10-CA: International Classification of Diseases - 10th Revision, enhanced Canadian version
ICES: Institute for Clinical Evaluative Sciences
LBW: Low birthweight
LICO: Statistics Canada low-income cut-off
LIDS: Landed Immigrant Data System
MOHLTC: Ontario Ministry of Health and Long-Term Care
MOOSE: Meta-analysis of Observational Studies in Epidemiology
MLBW: Moderately low birthweight
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MPTB: Moderately preterm birth
OHIP: Ontario Health Insurance Plan
OR: Odds Ratio
PCCF+: Postal Code Conversion File Plus
PPROM: Preterm premature rupture of membranes
PTB: Preterm Birth
REB: Research Ethics Board
ROAM: Reproductive Outcome And Migration
RPDB: Registered Persons Data Base
SAS: Statistical Analysis System
SES: Socioeconomic status
SGA: Small for Gestational Age
SPTB: Small preterm birth
UNICEF: The United Nations Children's Fund
U.S.: United States
VLBW: Very low birthweight
VPTB: Very preterm birth
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Chapter 1 Introduction
1.1. Background
Immigration has been increasingly seen as a potential means to attenuate population decline,
sustain the size of the labour force, and slow down the pace of population aging.1 As many as
190 million people worldwide are estimated to be international migrants, about half of them
being women.2,3 The proportion of births to migrant women to many industrialized countries has
shown upward trends in the last two decades, reaching around one fifth of all live births in the
US, England and Wales, the Netherlands, Sweden, Switzerland, and Germany.1,4 Despite the
absence of statistics at the national level, Canada does not seem to be the exception. Immigration
currently accounts for two thirds of Canada’s population growth and is expected to be the only
contributing factor by around 2030.5 Although immigrants’ contribution to population growth is
mainly based on the flow of working aged migrants, it is closely followed by that of births to
migrant women, who generally have higher fertility rates than non-immigrants.1
The growing magnitude of the female migrant population and its contribution to Canada’s
newborns give good reason for the study of the health status of immigrants, including
reproductive health. Yet, there are additional important reasons. A second reason is that
immigrants may be different from the ‘native’ population, in terms of their determinants of
health. Indeed, immigrants concentrate a specific set of exposures that are not shared by their
‘native’ counterparts, such as previous environmental exposures in their countries of origin,
selection, language and socialization; these influences shape their health behaviours and status,
and exposures after arrival, such as adaptation and acculturation.6-8 Immigration is not just a
2
single attribute that can be contained into a variable defined at the individual level. Rather,
immigration entails a complex multilevel process that may influence health through diverse
pathways long after settlement and even across generations. This perspective sees immigrants as
a subpopulation with specific determinants of health not shared by the native-born. There is also
some evidence suggesting that common predictors of health outcomes, such as health care
utilization and different measures of socioeconomic status, do not have the same explanatory
power among immigrants than that observed in the general population, as exemplified by the
Mexican paradox, 9,10 by which foreign-born Mexicans show levels of low birthweight similar to
those of the White US-born despite lower prenatal care, education, and income. Immigrant
characteristics associated with enhanced health may not be shared by some immigrant sub-
groups, such as refugees 11 or undocumented immigrants.12
Among these specific determinants we can list the influence of country of origin influences,
adaptation and acculturation, language and culture barriers.
A third and related reason is that the trends of increasing proportions of births to women in a
subpopulation with specific determinants of health about which little is known may have
unexpected consequences for reproductive, child, and adult health. The diversity of the Canadian
immigrant population may contribute to variation in their health outcomes, and such diversity
expedites the detection of effects otherwise undetectable in more homogeneous populations. For
example, despite important advances in our understanding of the etiology of preterm birth during
the last two decades, about one quarter of the occurrence of preterm birth in developed countries
remains unexplained.13 Preterm birth is considered to be a syndrome initiated by multiple
mechanisms, and a precise mechanism cannot be established in most cases.14 Comparisons of
this outcome by migrant status might therefore contribute to our understanding of the
3
environmental influences leading to disparities in preterm birth and associated developmental
and health outcomes.
Despite a substantial body of literature focusing on the reproductive health of migrants to
western industrialised countries, there is no obvious pattern describing the relation between
migrant status and perinatal outcomes. The literature shows conflicting associations between
migration and perinatal health, suggesting different sources of heterogeneity. The heterogeneity
may result from methodological differences between studies, such as the definition of the
migrant groups and the choice of comparison groups as well as differences in the immigrant
populations under study. Unravelling these sources of heterogeneity represents a step towards the
clarification of the relation between migration and perinatal health.
This thesis attempts to contribute to the scientific literature by summarizing the literature on
migration and adverse birth outcomes and tackling some determinants of health specific to
immigrants, such as country of origin influences and duration of residence in the receiving
country, using secondary data on infants born to mothers residing in urban areas of Ontario.
Urban Ontario constitutes an appropriate setting to investigate migrant health. Ontario receives
about half of all immigrants to Canada, with more than 90 % of them concentrated in urban
areas,15 thus representing the largest migrant population of Canada.
4
1.2. Study objectives
Table 1.1. Study objectives and research questions
Objective Research questions Chapter
1. Meta-analysis: To assess disparities by migrants status and migrant subgroups
1.1. Do low birthweight (LBW), preterm birth (PTB), and small for gestational age (SGA) differ between migrants and non-migrants?
1.2. Do these outcomes differ between migrant subgroups, defined by ethnicity?
1.3. Do these outcomes differ between migrant subgroups, defined by country of origin and destination?
2
2. Determinants of birth outcomes for immigrants I: To examine the relation between duration of residence and birth outcomes
2.1. Is duration of residence independently associated with adverse birth outcomes among immigrants to urban Ontario?
2.2. Does such association differ by immigrant subgroups, defined by their regions of origin?
2.3. How do birth outcomes of immigrants, classified by duration of residence, compare with the level observed among non-immigrants?
3
3. Determinants of birth outcomes for immigrants II: To explore the interplay between material deprivation, country of birth, and duration of residence
3.1. What is the contribution of neighbourhood context and country of origin to birth outcomes of recent immigrants?
3.2. Regarding immigrants, is the relation between neighbourhood deprivation and preterm birth modified by duration of residence?
4
3.3. How does the neighbourhood deprivation gradient in preterm birth vary by immigrant status, and by duration of residence among immigrants?
5
5
1.3. Involvement/participation of author and co-authors in the research
Objective 1 arose from my involvement in the ROAM Collaboration (Reproductive Outcomes
and Migration). The ROAM is an international research collaboration between researchers of
Canada, Australia, and several European countries first established in September 2005. It is
being led by Anita Gagnon (McGill University) and was initially funded by the Canadian
Institutes of Health Research (CIHR) under their International Opportunities Program (#157033).
I joined ROAM in mid-2007, under the supervision of Rick Glazier, also a ROAM member. By
that time an overview paper was in preparation,16 the main research question was: “Do migrant
women in ‘western industrialized countries’ have poorer perinatal health outcomes than
receiving-country women (second generation immigrants or non-immigrants)?” A bibliographic
search had been done already for most outcomes (last updated in September 2006) to be used in
the overview paper. In their 2007 annual meeting, ROAM members agreed to split the diversity
of outcomes covered in the overview paper and form working groups to prepare manuscripts
focusing on specific outcomes. Rick Glazier and I agreed to lead a review on migration and low
birth weight and preterm birth. Our working group was composed of 8 other members [Béatrice
Blondel, (INSERM -France), Anita Gagnon (McGill University and MUHC– Canada), Mika
Gissler (STAKES -Finland), Maureen Heaman (University of Manitoba -Canada), Alison
Macfarlane (City University of London – UK), Edward Ng (Statistics Canada), Babill Stray-
Pedersen (University of Oslo – Norway), Jennifer Zeitlin (INSERM – France and EURO-
PERISTAT)]. To avoid overlap with the overview paper, the working groups would preferably
focus on mechanisms. Therefore, Rick and I concentrated on reviewing the literature on low
birth weight among migrant subgroups, and the potential explanations for disparities. ROAM
members provided important comments on the first manuscript plan and their input was critical
in narrowing down the research questions of the review. Once there was agreement on the
6
research questions I took the lead in updating the search (as of November 2007), designing the
study, systematizing the literature, analyzing the data, and writing the manuscripts.
Regarding objectives 2 and 3, I set the objectives, conceived the study design, analyzed and
interpreted the data, and wrote the manuscripts. Committee members supervised the study,
revised and provided critical comments on all manuscripts, including the literature review, from
the protocol to the preliminary results drafts to the final dissertation. They also helped access
data at the Institute of Clinical Evaluative Sciences (ICES) (RG), suggested novel perspectives to
interpret the data (JF), and advised on statistical methods (RM).
1.4. Organization of the thesis
1.4.1. Rationale for the objectives
Objective 1: Literature review:
It is important to review the literature because of the inconsistent associations found between
migration and birth outcomes, more specifically low birthweight, preterm birth, and fetal growth.
The purpose of the review is to clarify the existence and nature of these associations, since a
substantial part of the inconsistencies between studies may be due to differences in
methodological approaches (e.g.., definition of migrant groups, and choice of comparison
groups). A related goal is to learn about the specific determinants of immigrant health and the
mechanisms through which they influence birth outcomes. The knowledge gained from this
review may help avoid common mistakes in the field and fine-tune future research questions and
hypotheses.
7
Objective 2: Duration of residence and birth outcomes:
Heterogeneity between studies may result from unmeasured confounders. Probably one of the
most pervasive and elusive potential confounders or effect modifiers of the associations between
migration and birth outcomes is duration of residence. A few studies found that the association
between duration of residence and adverse birth outcomes is of such a nature that significant
changes in their association could be detected within short periods of time (less than five
years).7,17-19 However, it remains unknown whether such an association is still present when
longer observation periods are considered (up to 20 years). This is a limitation of the literature,
probably due to the lack of available data on these outcomes after prolonged duration of
residence, and because most studies focused on comparisons with the native-born as the referent
groups. Our data made it possible to assess the influence of duration of residence on birth
outcomes of immigrants over a 20-year period after arrival. This feature makes this study not
only original but also very informative for identifying groups at higher risk of adverse birth
outcomes according to their length of stay in Canada. Such information makes the present study
a substantial contribution to the international literature.
Objective 3: Interplay between material deprivation, country of birth, and duration of residence:
One of the most consistent associations in perinatal health is the existence of gradients in
socioeconomic status (SES) (i.e., the lower the SES, the poorer the outcomes in a graded
pattern).20 Immigrants are known to be a subpopulation generally characterized by having lower
SES indicators than in the general population. For example, female Mexicans in the US have
lower maternal education 9 and immigrants to Ontario cities have higher proportions of people
living in deprived neighbourhoods.21 Despite these disadvantages, Mexicans in the US and recent
immigrants to urban Ontario have levels of preterm birth comparable to the most advantaged
8
native-born groups.21,22 Moreover, the seemingly ubiquitous SES gradient in birth outcomes is
not consistently found among these populations.9,21,23,24 These apparent anomalies (or paradoxes)
may be clarified (at least partially) when other determinants of immigrant reproductive health are
considered, such as duration of residence and selection of immigrants into particular sorts of
neighbourhoods, in terms of SES. To assess the impact of SES on birth outcomes of migrants
there are issues of misclassification of immigrants’ SES, confounding by self-selection, and
duration of residence. Objective 3 aims at clarifying the interplay between these dimensions.
Such clarification is important from a public health perspective since it can identify particularly
vulnerable groups defined by the intersection of these dimensions. The contribution of the
present study to the international literature may be significant as well, since U.S. studies trying to
explain the Mexican paradox have not considered duration of residence in their analyses.10,25,26
Objectives 2 and 3 build upon my MSc thesis work that resulted in two papers: one reporting
lower twin rates among recent immigrants and residents of poorer neighbourhoods,27 and the
other reporting lower singleton preterm birth rates among recent immigrants but higher low-
birthweight rates.21 However, this research had two major limitations: first, recent immigration
was ascertained by means of a proxy (defined as a first-time registration to OHIP within a five-
year period preceding the delivery) and this proxy has not been validated; second, information on
the maternal country of origin was not available, which made it impossible to identify variations
by immigrant sub-groups. In this PhD thesis I tried to overcome these two limitations and
advance knowledge on the relation between immigration and birth outcomes using the Landed
Immigrant Data System (LIDS), which is the official immigration database and contains mostly
validated information on immigrant status, country of birth and origin (last permanent residence),
and date of arrival, among other characteristics as described in the Appendix on data sources
(Appendix 3.A). Access to the LIDS and linkage with the Discharge Abstract Database
9
(DAD),28,29 compiled by the Canadian Institute for Health Information (CIHI), allowed two types
of comparisons: 1) immigrants versus the rest of the population; and 2) comparisons between
immigrant subgroups, defined by world regions of origin and length of stay in Canada. Both
types of comparisons have been found relevant from an equity perspective. First, the general
population constitutes a referent group against which to compare immigrants as a whole and
assess the impact of immigration at the societal level. Secondly, to study differences between
immigrant sub-groups is of interest to identify high-risk sub-populations, understand the
underlying determinants of their health status, and inform potential strategies to improve their
outcomes.
1.4.2. Overview of the research
This section highlights the location of the study objectives in the thesis. Birth outcomes of
immigrants constitute the common theme of the following four papers. Although the focus was
on immigrants, comparisons with non-immigrants were made whenever feasible and relevant.
This thesis is limited to a few birth outcomes such as birthweight, preterm birth and small for
gestational age, which are intermediate outcomes in perinatology. Other potentially more
relevant outcomes such as stillbirth, neonatal mortality, and serious neonatal morbidity were not
chosen due to data limitations. Papers are ordered according to the increasing complexity of their
objectives.
The literature review (Chapter 2) was of great importance in classifying the literature, thus
providing a context for the interpretation of the Canadian data analyzed in Chapters 3 to 5. It also
helped identify what is known and not known on this topic, thus paving the way to the
10
recognition of two research gaps that could be explored with the Ontario data analyzed in
objectives 2 and 3.
The first research gap identified in the review was the relation between duration of residence and
adverse birth outcomes (Chapter 3). The literature review identified duration of residence as an
important determinant. Yet, the very few studies that have been able to collect data on duration
of residence were limited to recent immigrants.7,17,18 In contrast, chapter 3 is unique in assessing
the effects of the receiving environment across the 20 years after migration. The main finding
reported in this chapter is that duration of residence was linearly associated with higher odds of
low birthweight and preterm birth, most probably due to a steady decrease in the gestational age
distribution of immigrants with time spent in Canada.
The second gap is the relation between SES and birth outcomes among migrants. Migrants to
western industrialized countries represent a major exception to the well-known negative
association between SES and adverse birth outcomes. Chapter 4 provides an explanation of why
this association does not hold among recent immigrants to urban Ontario. These analyses were
carried out during 2007 and are restricted to infants born to recent immigrants mothers from
1993 to 2001. Additional data were accessed in 2008, thus allowing us to assess the effects of
duration of residence on birth outcomes of immigrants. Therefore, Chapter 5 goes beyond recent
immigrants and extends the observation period by including immigrants with 20 or more years of
stay in Canada. These data allowed the assessment of whether the influence of neighbourhood
deprivation on preterm birth was modified by immigrants’ duration of residence, and how these
gradients compared with that of the non-immigrant population.
11
The final discussion (Chapter 6) highlights the general strengths and limitations of the thesis,
summarizes the lessons learnt, and signals possible directions to further advance knowledge in
the area of migration and adverse birth outcomes.
12
1.5. References
(1) Sobotka T. Overview Chapter 7: The rising importance of migrants for childbearing in Europe.
Demographic Research. 2008;19(article 9):225-248.
(2) Carballo M, Nerukar A. Migration, refugees, and health risks. Emerging Infectious Diseases. 2001;7(3
Suppl):556-560.
(3) United Nations Population Fund (UNFPA). State of World Population 2006. A Passage to Hope: Women
and International Migration. 1-116. 2006. New York, UNFPA.
(4) Centers for Disease Control and Prevention (CDC), Centers for Disease Control and Prevention (CDC).
State-specific trends in U.S. live births to women born outside the 50 states and the District of Columbia--
United States, 1990 and 2000.[erratum appears in MMWR Morb Mortal Wkly Rep. 2002 Dec
13;51(49):1127.]. MMWR - Morbidity & Mortality Weekly Report. 2002;51(48):1091-1095.
(5) Bélanger, A, Martel, L, and Caron-Malenfant, E. Population Projections for Canada, Provinces and
Territories 2005-2031. Statistics Canada. Catalogue no. 91-520-XIE, 1-215. 2005. Ottawa, Statistics
Canada. Demography Division.
(6) English PB, Kharrazi M, Guendelman S. Pregnancy outcomes and risk factors in Mexican Americans: the
effect of language use and mother's birthplace. Ethnicity & Disease. 1997;7(3):229-240.
(7) Guendelman S, English PB. Effect of United States residence on birth outcomes among Mexican
immigrants: an exploratory study. Am J Epid. 1995;142(9 Suppl):S30-S38.
(8) Scribner R, Dwyer JH. Acculturation and low birthweight among Latinos in the Hispanic HANES. Am J
Public Health. 1989;79(9):1263-1267.
(9) Acevedo-Garcia D, Soobader MJ, Berkman LF. The differential effect of foreign-born status on low birth
weight by race/ethnicity and education. Pediatrics. 2005;115(1):e20-e30.
(10) Rosenberg TJ, Raggio TP, Chiasson MA. A further examination of the "epidemiologic paradox": birth
outcomes among Latinas. Journal of the National Medical Association. 2005;97(4):550-556.
13
(11) Desmeules M, Gold J, Kazanjian A et al. New approaches to immigrant health assessment. Can J Public
Health. 2004;95(3):I22-I26.
(12) Kelaher M, Jessop DJ. Differences in low-birthweight among documented and undocumented foreign-born
and US-born Latinas. SOC SCI MED. 2002;55(12):2171-2175.
(13) Kramer MS, Seguin L, Lydon J, Goulet L. Socio-economic disparities in pregnancy outcome: why do the
poor fare so poorly? Paediatr Perinat Epidemiol. 2000;14(3):194-210.
(14) Goldenberg RL, Culhane JF, Iams JD, Romero R. Epidemiology and causes of preterm birth. Lancet.
2008;371(9606):75-84.
(15) Statistics Canada. Immigration in Canada: A Portrait of the Foreign-born. Census year 2006. Catalogue no.
97-557-XIE. 2007. Ottawa, Statistics Canada, Minister of Industry.
(16) Gagnon, A. J., Zimbeck, M., Zeitlin, J., and and the ROAM Collaboration. Migration to western
industrialized countries and perinatal health: A systematic review. Social Science & Medicine (in press).
2009.
(17) Crump C, Lipsky S, Mueller BA. Adverse birth outcomes among Mexican-Americans: are US-born women
at greater risk than Mexico-born women? Ethnicity & Health. 1999;4(1-2):29-34.
(18) Rasmussen F, Oldenburg CE, Ericson A, Gunnarskog J. Preterm birth and low birthweight among children
of Swedish and immigrant women between 1978 and 1990.[erratum appears in Paediatr Perinat Epidemiol
1996 Apr;10(2):240-1]. Paediatr Peri Epid. 1995;9(4):441-454.
(19) Ray JG, Vermeulen MJ, Schull MJ, Singh G, Shah R, Redelmeier DA. Results of the Recent Immigrant
Pregnancy and Perinatal Long-term Evaluation Study (RIPPLES). CMAJ. 2007;176(10):1419-1426.
(20) Kramer MS, Seguin L, Lydon J, Goulet L. Socio-economic disparities in pregnancy outcome: why do the
poor fare so poorly? Paediatr Perinat Epidemiol. 2000;14(3):194-210.
(21) Urquia ML, Frank JW, Glazier RH, Moineddin R. Birth outcomes by neighbourhood income and recent
immigration in Toronto. Health Rep. 2007;18(4):1-10.
14
(22) Cervantes A, Keith L, Wyshak G. Adverse birth outcomes among native-born and immigrant women:
replicating national evidence regarding Mexicans at the local level. Matern Child Health J. 1999;3(2):99-
109.
(23) Fang J, Madhavan S, Alderman MH. Low birth weight: race and maternal nativity-impact of community
income. Pediatrics. 1999;103(1):E5.
(24) Pearl M, Braveman P, Abrams B. The relationship of neighbourhood socioeconomic characteristics to
birthweight among 5 ethnic groups in California. Am J Public Health. 2001;91(11):1808-1814.
(25) Buekens P, Notzon F, Kotelchuck M, Wilcox A. Why do Mexican Americans give birth to few low-birth-
weight infants? Am J Epid. 2000;152(4):347-351.
(26) Fuentes-Afflick E, Hessol NA, Perez-Stable EJ. Testing the epidemiologic paradox of low birth weight in
Latinos. Archives of Pediatrics & Adolescent Medicine. 1999;153(2):147-153.
(27) Urquia ML, Frank JW, Glazier RH, Moineddin R. Multiple maternities and neighbourhood income. Twin
Res Hum Genet. 2007;10(2):400-405.
(28) Canadian Institute for Health Information. Data Quality Documentation: Discharge Abstract Database
2001–2002. 2003. Ottawa, Canadian Institute for Health Information.
(29) Canadian Institute for Health Information. Data Quality Documentation: Discharge Abstract Database
2002–2003. 2005. Ottawa, Canadian Institute for Health Information.
15
Chapter 2 International Migration and Adverse Birth Outcomes: Role of
Ethnicity, Region of Origin and Destination
Abstract
Objective: To determine whether low birthweight (LBW), preterm birth (PTB), and small for
gestational age (SGA) differ between non-migrants and migrant subgroups, defined by
race/ethnicity and world region of origin and destination.
Methods: We conducted a systematic review and meta-analysis using three-level logistic
regression models to account for the heterogeneity between studies and between subgroups
within studies.
Results: Twenty six studies, involving more 30 million singleton births, met inclusion criteria.
Compared to US-born Black women, first-generation Black migrant women had lower odds of
delivering LBW (OR, 95% confidence intervals: 0.64, 0.50-0.83), PTB (0.70, 0.62-0.80) and
SGA babies (0.65, 0.49-0.85). Hispanic migrants also exhibited lower odds for these outcomes,
but Asian and White migrants did not. Sub-Saharan African and Latin American and Caribbean
women were at higher odds of delivering LBW babies in Europe but not in the US and South
Asians were at higher odds in both continents, compared with the native-born populations.
Conclusions: The association between migration and adverse birth outcomes varies by migrant
subgroup and it is sensitive to the definition of the migrant and reference groups.
16
2.1. Introduction
About 95 million women are international migrants worldwide and female immigrants have
recently outnumbered male immigrants in most industrialised countries.1 The proportion of live
births to immigrant women has risen during recent decades in several industrialized countries.2-5
Despite a substantial body of literature focusing on the reproductive health of migrants to
western industrialised countries, there is no obvious pattern describing the relation between
migrant status and perinatal outcomes. The literature shows positive, negative, and null
associations between migration and perinatal health, suggesting that different sources of
heterogeneity may play a role. It is uncertain to what extent the association between foreign-born
status and birth outcomes is a function of the characteristics of the migrant populations, of the
baseline risk of the native-born reference groups, or of some combination of both. For example,
foreign-born Blacks in the United States (US) had lower low birthweight compared with US-
born Blacks but not with US-born Whites.6 Such comparisons suggest that the influence of
migration may be modified by ethnicity.7 Ethnic disparities in birth outcomes are well
documented, particularly in the US, but the contribution of migration to these disparities is not
well understood. In studies comparing native-born versus migrant groups defined by their
regions of origin, there is uncertainty over whether the so-called healthy migrant effect 8 applies
to migrants from all or only some regions of the world, and what these regions are.
Most studies devoted to migration and perinatal health have focused on birth outcomes defined
by birthweight or gestational age or both. Our purpose was to conduct a systematic review to
clarify the relation between migration and those birth outcomes by determining the differences in
low birthweight (LBW), preterm birth (PTB), and small for gestational age (SGA) between
17
migrants and non-migrants by migrant subgroups, defined according to race/ethnicity, world
region of origin and actual destination.
2.2. Methods
This review was prepared following the MOOSE guidelines9 and draws on the material
identified by the ROAM collaboration (Reproductive Outcome And Migration) for a series of
systematic reviews on migration and reproductive health. The ROAM is an international research
collaboration devoted to study the relation between reproductive health and migration.
2.2.1. Study population
This study was restricted to published reports on any outcome requiring gestational age or
infant’s birthweight to define it. The exposure was maternal international migration to Western
industrialised countries, assessed by evidence of cross-border movement. Thus this definition
excludes internal migration, ‘protectorates’ such as Puerto Rico, and second generation
populations. Reference groups were the native-born women of the receiving countries. We
excluded case studies, clinical reports, reports without a comparison group, and reports in which
the results of the migrant group(s) were not presented separately from the comparison group.
2.2.2. Search and study selection criteria
Studies were identified through electronic literature databases from 1995 through October 2007
to represent the most recent immigration context. Ovid (version 10.5.1) was used in the
following order: Medline, Health Star, Embase, and PsychInfo. Searches were supplemented
with bibliographic citation hand-searches of included articles published from 2004 onward and
18
relevant articles referred to the authors by other ROAM members. No language exclusions were
routinely applied. Articles in French, Italian, and Spanish, were reviewed by the authors. Two
ROAM members independently assessed included studies for quality using the US Preventative
Services Task Force criteria for cohort and case-control studies 10 and no discrepancies were
found in the overall score between raters. Further details of the search strategy are summarized in
Appendix 2.A.
All articles for the meta-analyses were selected by applying the following criteria:
1. Definitions of the outcomes: LBW was restricted to a birthweight less than 2500 grams,
PTB to a gestational age of less than 37 completed weeks, but no restrictions were
applied to SGA, due to the small number of studies and variations in the definitions.
2. Restriction to singleton births.
3. Information on race/ethnicity and foreign-born status or country of birth or nationality
4. Descriptive tables including summary data on the outcomes with at least one native-born
and one foreign-born group.
Our searches identified eighty two studies. Of these, we excluded 10 studies from the meta-
analyses that did not include our outcomes of interest or used different definitions,11-20 31 studies
that did not discriminate between singleton and multiple births,2,3,5,21-48 four did not ascertain
migration appropriately,49-52 and seven did not have appropriate tables for the extraction of the
data.53-58 Finally, four studies 59-62 could not be used because the available number of studies
reporting PTB and SGA by world region of origin was too small for analysis. Twenty six studies
were meta-analyzed.
19
2.2.3. Data extraction
We extracted summary birth data consisting of at least two records per study: one for the migrant
and one for the native-born group, although many studies included several subgroups including
maternal ethnic groups, world regions or countries of origin or infant’s year of birth. Each record
contained a numerator and a denominator for the respective outcome, and indicators of migrant
status (foreign-born, native-born), race/ethnicity as categorised in US studies (Asians, Blacks,
Hispanics, and Whites),63 receiving country (US or European countries), migrants’ country of
birth or origin or nationality, and infant’s year of birth. If the birth data aggregated more than one
year, the midpoint was recorded, and for articles reporting numerator and denominator for
different periods, one record was assigned to each period. We grouped countries of birth into
world regions, following the classification of the United Nations in most cases.64 Asia was
subdivided into South Asia and rest of Asia, because we wanted to examine whether South
Asians differ in the risk of adverse birth outcomes compared to the rest of the continent, as has
been suggested in the literature.65 In the same vein, North Africans were separated from the rest
of Africa (i.e., Sub-Saharan Africa) because of their particularly good birth outcomes,66 and
grouped with Middle Eastern countries, because some studies 60,67 have grouped these regions
together. Sensitivity analyses performed without these two studies did not affect the results
regarding North Africans and therefore we did not exclude them.
2.2.4. Statistical analyses
In order to account for the potential heterogeneity between studies and subgroups within studies,
we employed random effects meta-regression analysis, which involves the application of
multilevel methods to meta-analysis.68-70 We used three-level models, with births at level 1,
20
subgroups at level 2 and studies at level 3. The inclusion of random effects at the subgroup-level
assumes that each subgroup represents a different population with its own distribution. Ignoring
the hierarchical structure of these data would produce over-precise confidence intervals.71,72
Analyses were conducted with Proc GLIMMIX in SAS 9.1 (SAS Institute, Cary, NC) to fit
multilevel logistic regression models for summary data.
Studies differed substantially in the way migrant groups were categorised. This heterogeneity in
the definition of migrant groups prevented us from combining all selected studies into one single
meta-analysis and therefore we conducted two meta-analyses, based on the two main approaches
that have been used to study the influences of international migration on birth outcomes.
The first meta-analysis was based on studies which analyzed births in the US defining migrant
subgroups both by their race/ethnicity 63 and migrant status, because most European studies did
not report birth data by ethnic groups. We used a product term between race/ethnicity and
migrant status in the models to obtain effect estimates of migrant status by race/ethnicity on all
three outcomes, adjusted for infant’s year of birth. We quantified the percent of variance
explained for logistic models by comparing a model including the product term between
race/ethnicity and migrant status relative to a model including migrant status as the only
predictor, with both models adjusted for infant’s year of birth.73
The second meta-analysis was based on studies which analyzed low birthweight in Europe or the
US, categorizing migrants and non-migrants by their countries of birth, irrespective of their
race/ethnicity. We could not analyze preterm birth and small for gestational age due to the small
number of studies and migrant groups. The low birthweight model included a product term
between world region of origin and a dummy indicator for receiving country (Europe versus US)
21
in order to test the hypothesis that the odds of LBW differ both according to the region of origin
and destination, adjusted for infant’s year of birth.
2.3. Results
Twenty six studies were included in the meta-analyses: 17 by race/ethnicity,6-8,74-87 17 by world
region,6,8,13,66,67,77,79,81,82,84,85,87-92 and 9 by both.6,8,77,79,81,82,84,85,87 Due to the small number of
studies it was not possible to choose a uniform definition of SGA, and therefore all were
considered, including SGA based on percentiles of the birth weight distribution of native-born
populations 8,76,81,85,91, full-term LBW infants,77,84 and other measures of SGA.83
Table 2.1. Characteristics of the US-studies included in the meta-analysis by race/ethnicity
Study (author, year)
Country, state/region
Type of databas
e b
Year of data
Outcome Migrants US-born # of subgroups
Total births a % migrant
Acevedo-Garcia et al. 2005
USA, national
PBR 1998 LBW Asians, Blacks, Whites
Asians, Blacks, Whites
6 2,102,393 9.3
Alexander et al. 1996
USA, regional NE
PBR 1983-1987 LBW Asians Asians 2 37,941 45.3
Cervantes et al. 1999
USA, Chicago City
PBR 1994 LBW, PTB Blacks, Hispanics,
Whites
Blacks, Hispanics,
Whites
8 52,033 27.0
Cocroft et al. 2002
USA, New York State
PBR 1993-1996 SGA Blacks, Hispanics,
Whites
Blacks, Hispanics,
Whites
8 2,356 21.2
Crump et al. 1999
USA, Washington State
PBR 1989-1994 LBW, PTB, SGA
Hispanics Hispanics 2 9,572 50.0
David et al. 1997
USA, Illinois State
PBR 1980-1995 LBW Blacks Blacks, Whites 3 90,503 3.5
English et al. 1997
USA, California
PBR + quest
1992 LBW, PTB Hispanics Hispanics 6 4,404 55.3
Fang et al. 1999
USA, New York City
PBR 1988-1994 LBW, PTB Blacks Blacks 5 269,863 35.9
Fuentes-Afflick et al. 1998
USA, California State
PBR 1992 LBW, PTB Asians, Blacks, Hispanics,
Whites
Asians, Blacks, Hispanics,
Whites
8 573,233 44.5
Gould et al. 2003
USA, California State
PBR 1995-1997 LBW, PTB, SGA
Asians, Hispanics
Blacks, Whites 4 1,057,977 42.2
Johnson et al. 2005
USA, Washington State
PBR 1993-2001 LBW, PTB Blacks Blacks, Whites 3 5,398 10.7
Kramer et al. USA, PBR 1998-2000 PTB, SGA Blacks Blacks 2 1,754,777 11.4
22
Study (author, year)
Country, state/region
Type of databas
e b
Year of data
Outcome Migrants US-born # of subgroups
Total births a % migrant
2006 national Landale et al. 1999
USA, national
PBR 1989-1991 LBW, SGA Asians, Blacks, Hispanics,
Whites
Asians, Blacks, Hispanics,
Whites
36 4,856,798 48.6
Madan et al. 2006
11 States PBR LBW, PTB, SGA
Asians, Hispanics,
Asians, Hispanics,
Whites
5 6,424,172 23.1
California, Hawaii, Illinois, New Jersey, New York, Texas, Washington
1995-1997
Minnesota 1997 Virginia 1998 Missouri,
West Virginia 1999-2000
Palotto et al. 2000
USA, Illinois State
PBR 1985-1990 LBW Blacks Blacks, Whites 3 103,746 2.2
Rosenberg et al. 2005
USA, New York City
PBR 1996-1997 LBW Hispanics Hispanics 14 156,084 63.1
Wingate et al. 2006
USA, national
PBR 1995-1999 LBW, PTB, SGA
Hispanics Hispanics 4 2,446,253 61.5
TOTAL 119 19,947,503 a When the sample size varies by outcome, the denominator for LBW was reported, followed by PTB and SGA if LBW was not reported. b HR: hospital record, PB: population-based, PBR: population-based registry, PBS: population-based survey
2.3.1. Migration and race/ethnicity
The first meta-analysis was based on 17 studies conducted in the US (Table 2.1). All studies used
self-reported race/ethnicity and foreign-born status. One UK study 13 also reported these data for
LBW but was excluded to restrict our analysis to the US context. Exclusion of this study did not
substantially change the effect estimates for LBW although it slightly increased the p-value for
the product term between race/ethnicity and migrant status shown below. We also excluded
Hispanics from one US study 7 to avoid data duplication with another study.8
We first fitted a three-level model with migrant status as the independent variable, adjusted for
infant’s year of birth, but ignoring race/ethnicity. The odds ratios (95% confidence interval) for
the comparisons between migrants and non-migrants were 0.81 (0.70-0.94) for LBW, 0.85 (0.74-
0.98) for PTB and 0.89 (0.72-1.10) for SGA, respectively. These are inappropriate models that
23
assume that the effect of migrant status can be averaged across racial/ethnic groups. Instead,
Table 2.2 shows the results of the three-level models including race/ethnicity and a product term
between race/ethnicity and migrant status for all three outcomes, adjusted for year of birth. The
p-values of the product term in the models were 0.0611 for LBW, 0.0018 for PTB, and 0.0013
for SGA. The percent of total variance explained by the introduction of race/ethnicity and the
product term “migrant status * race/ethnicity” relative to a model including only migrant status,
adjusted for year of birth, was 57%, 24% and 26% for LBW, PTB, and SGA, respectively,
suggesting that race/ethnicity and its interplay with migrant status explain substantial variability
in the outcomes not accounted for by migrant status alone.
The first, second and third columns of Table 2.2 present ethnic disparities within first generation
migrants, within US-born, and between foreign-born and US-born of the same race/ethnicity,
respectively, by outcome. The percent of singleton infants with LBW was 5%, 9% for PTB, and
3% for SGA among US-born White mothers. There was no evidence of differences in the
outcomes between foreign-born and US-born Whites (third column).
Among foreign-born migrants, Asians were somewhat more likely to have adverse birth
outcomes than Whites. Among the US-born, Asians were at higher odds of SGA compared with
Whites. Foreign-born Asians were not protected against these outcomes, compared to US-born
Asians.
24
Table 2.2. Odds ratios (and 95% confidence intervals) for adverse birth outcomes between ethnic groups
among migrants, among US-born, and between migrants and US-born, by race/ethnicity.
Outcome Ethnicity Migrants US-born Migrants versus US-bornb Low birthweight N=6,487,938 N=11,702,432 OR (95% CI) a OR (95% CI) a OR (95% CI) a Whites 1.00 1.00 0.83 (0.60-1.16) Asians 1.31 (0.95-1.80) 1.14 (0.88-1.48) 0.95 (0.75-1.21) Blacks 2.41 (1.73-3.35) 3.10 (2.38-4.04) 0.64 (0.50-0.83) Hispanics 1.16 (0.86-1.57) 1.25 (1.00-1.58) 0.77 (0.64-0.93) Preterm birth N=4,009,158 N=8,587,564 OR (95% CI) a OR (95% CI) a OR (95% CI) a Whites 1.00 1.00 0.82 (0.66-1.01) Asians 1.44 (1.15-1.81) 1.08 (0.88-1.35) 1.09 (0.88-1.35) Blacks 1.62 (1.30-2.03) 1.89 (1.64-2.19) 0.70 (0.62-0.80) Hispanics 1.35 (1.10-1.66) 1.24 (1.09-1.44) 0.89 (0.79-1.00) Small for Gestational age
N=5,268,854 N=9,299,526
OR (95% CI) a OR (95% CI) a OR (95% CI) a Whites 1.00 1.00 1.13 (0.78-1.63) Asians 1.67 (1.18-2.36) 1.63 (1.28-2.08) 1.15 (0.94-1.41) Blacks 1.48 (0.99-2.21) 2.58 (2.00-3.34) 0.65 (0.49-0.85) Hispanics 0.97 (0.69-1.37) 1.34 (1.07-1.69) 0.81 (0.68-0.97)
a Includes random effects at the subgroup and study levels. Adjusted for infant’s year of birth b US-born is the reference group
Among the foreign-born, Black migrants were the group at the highest odds for LBW and PTB,
and Blacks were the group at the highest odds for all three outcomes among US-born women.
There was evidence of a protective effect of being foreign-born among Blacks for all three
outcomes.
Foreign-born Hispanics were at slightly higher odds for PTB compared with foreign-born White
migrants. The Hispanic-White gap was wider among the native-born than among the foreign-
born in LBW and SGA but not in PTB. Hispanic migrants were at lower odds of all three
outcomes compared with their US-born counterparts.
25
2.3.2. Migration and world regions
Table 2.3: Characteristics of the studies included in the meta-analysis of LBW by World regions
Study Country, state/region
Type of database b
Year of data
Migrants’ world regions # of subgroups
Total births % migrants
Buekens/ 1998
Belgium, national
PBR 1981-1988 North Africa 2 839 972 4.2
Collinwood-Bakeo/ 2004
UK, national PBR 1983-2001 Caribbean, East Africa, West Africa, South Asia, East Europe, Western Europe
55 11 401 247 8.0
Crump/ 1999 USA, Washington State
PBR 1989-1994 Latin America (Mexico) 2 9 572 50.0
David/ 1997 USA, Illinois State
PBR 1980-1995 Sub-Saharan Africa 3 90 503 3.5
Fang/ 1999 USA, New York City
PBR 1988-1994 Caribbean, South America, Africa (excl North)
5 269 863 35.9
Fuentes-Afflick/ 1997
USA, California State
PBR 1992 Cambodia, China, Philippines, India, Korea, Laos, Thailand, Vietnam
9 268 949 17.5
Gissler/ 2003 Sweden, national
PBR 1987-1988 Finland 6 140 390 23.8
Gould/ 2003 USA, California
PBR 1995-1997 India, Mexico 4 1 057 977 42.2
Guendelman/ 1999
Belgium, national
PBR 1992 North Africa 2 107 968 4.3
France, national
PBS 1995 North Africa 2 11 802 5.4
USA, national
PBR 1995 Latin America (Mexico) 2 3 417 003 8.4
Harding/ 2004
UK, national PBR 1983-2000 South Asia, Caribbean, Africa (excl North)
11 57 474 6.3
Johnson/ 2005
USA, Washington State
PBR 1993-2001 Somalia 3 5 398 10.7
Landale/ 1999
USA, national
PBR 1989-1991 Latin America, China, Philippines, Japan
16 4 856 798 48.6
Madan/ 2006 USA, national
PBR 1995-2000 India, Latin America (Mexico)
5 6 424 172 23.1
Rasmussen/ 1995
Sweden, national
PBR 1978-1990 West Europe/North America, East Europe, North Africa/Middle East, Sub-Saharan Africa, Latin America,
8 1 265 531 11.8
Rosenberg/ 2005
USA, New York City
PBR 1996-1997 Latin America 12 156 084 63.1
Vangen/ 2002
Norway, national
PBR 1980-1995 Pakistan, Vietnam, North Africa
4 820 256 1.4
Wingate/ 2006
USA, national
PBR 1995-1999 Latin America (Mexico) 4 2 446 253 61.5
TOTAL 155 33 647 212 b HR: hospital record, PB: population-based, PBR: population-based registry, PBS: population-based survey
26
Table 2.4: Odds ratios (and 95% confidence intervals) for low birthweight between infants born to migrant
women from various World Regions in Europe versus European-born women, from various World
Regions in the United States versus US-born women, and between native-born and migrant groups in
Europe versus the US.
Infants born in Europe
Infants born in the US
Infants born in Europe versus in the
USb OR (95% CI) a OR (95% CI) a OR (95% CI) a
Native-born women 1.00 1.00 0.66 (0.50-0.86)
Migrants from:
Western Europe and North America 0.84 (0.72-0.99) - -
East Europe 0.91 (0.73-1.14) - -
North Africa/ME 0.75 (0.58-0.98) - -
Sub-Saharan Africa 1.57 (1.31-1.89) 0.74 (0.54-1.01) 1.40 (0.93-2.11)
South Asia 1.66 (1.41-1.94) 1.25 (1.01-1.55) 0.87 (0.62-1.22)
Rest of Asia - 0.78 (0.62-0.99) -
Latin America / Caribbean 1.32 (1.06-1.64) 0.72 (0.62-0.82) 1.21 (0.88-1.68) a Includes random effects at the subgroup and study levels. Adjusted for infant’s year of birth. b Infants born in the US are the reference group
The second meta-analysis was based on studies that ascertained migration by the maternal
country of birth or nationality and included several European countries (Table 2.3). In one study
that stratified the outcomes by national origin we included national-origin groups with at least
90% of foreign-born women and therefore excluded Japanese and Filipino women (25).
Table 2.4 presents the results of the three-level model including a product term between world
region of origin and destination (Europe versus US) (p-value <0.0001). A few comparisons were
not possible because some subgroups migrating to Europe or to the US were not represented in
the selected studies.
Women from Sub-Saharan Africa and Latin America and the Caribbean were at higher odds for
LBW if migrating to European countries but at lower odds if migrating to the US, compared to
27
the respective native-born women. South Asians were at higher odds in both contexts but the
association was stronger in Europe. The direction and strength of these associations are affected
by the different baseline risk of the European and US reference groups, with European-born
women less likely to deliver LBW infants compared to US-born women (OR = 0.66 [95% CI =
0.50-086]). Despite this, Sub Saharan African women migrating to Europe seemed to be more
likely to deliver LBW babies compared to those from the same region who migrated to the US,
although there was no strong evidence to support the hypothesis that LBW within migrant groups
differed according to their destination (third column).
2.4. Discussion
One of the main findings of this systematic review is that the association between foreign-born
status and birth outcomes is not uniform but depends on the migrant subgroup, either defined by
a combination of maternal race/ethnicity and migrant status or by the world region of origin and
actual destination. We found that infants born to first-generation Black and Hispanic migrant
women were at lower risk of adverse birth outcomes than their US-born counterparts, but did not
find evidence of such protective effect among Asians and Whites. Migrants from these
ethnicities were at higher risk than White migrants overall. Regarding subgroups defined by
region of origin, Sub-Saharan African and Latin American and Caribbean migrants were at
higher odds of LBW in Europe but not in the US and South Asians were at higher odds in both
continents.
Unlike most meta-analyses of observational studies, we chose to use unadjusted summary data.
This approach had the advantage of freeing comparison groups from the reported measures of
28
effect in multivariate analyses thus making it possible to examine comparisons not explored in
previous studies. This allowed assessment of ethnic disparities by migrant status and
comparisons within migrant groups according to their place of origin and destination. Another
advantage is that our analyses used the same set of covariates and definitions for each study
(with the exception of SGA) thus making interpretation of results less problematic than in meta-
analyses based on effect estimates adjusted for varying number of covariates with heterogeneous
definitions. However, the limit of our approach was the inability to extract birth data stratified by
potential confounders. Immigration policies in the receiving countries and social class dynamics
in the source countries may favour the selection of women or couples for migration, based on
certain characteristics for which distributions may differ both from those of the source and the
receiving population (e.g., maternal age, maternal and paternal social class, marital status, overall
health) and that are also associated with birth outcomes. For example, differences in maternal
age may explain part of the foreign-born advantage among Blacks and Hispanics in the US, since
these groups have lower proportions of teenage pregnancy than their US-born
counterparts.7,75,79,80,84 Those two groups had also lower proportions of single mothers.7,75,80
Despite these favourable characteristics foreign-born Mexicans but not foreign-born Blacks in
the US had lower education, less prenatal care, and lower income compared to US-born
mothers.7,77,85 This phenomenon makes up part of the so-called “Latino paradox”,52,54,84,87 that
also can be extended to the birthweight advantage of North Africans in France and Belgium.12,93
The appropriateness of adjusting for factors likely affected by exposure, such as prenatal care
use, language knowledge, and health behaviours, mainly tobacco smoking, alcohol consumption
and drug use, is dubious, although this has been done in several studies.7,8,76,78-80
Another potential source of bias is measurement error, mainly resulting from self-reported
race/ethnicity and country of birth and nationality in birth certificates. A validation study found
29
that at least 94% of the mothers from the major racial/ethnic groups whose race/ethnicity was
reported in 1994-1995 California birth certificates were also classified in the same way in a face-
to-face structured postpartum interview.94 Similar results were obtained in a previous national
study,95 suggesting that the impact of this bias is small. The meaning and limitations of the
racial/ethnic classification for epidemiologic research had been extensively discussed.96,97 The
reviewed literature on birth outcomes tended to consider the racial/ethnic categories as markers
for a social process external to individual physiology rather than indicators of biological types.
Although reduced by means of model specification, heterogeneity across studies and subgroups
remained in our full models. Unexplained variability may result from unmeasured characteristics
and from the residual variability between countries within migrant subgroups. Some effect
estimates may also be affected by the uneven representation of some countries within world
regions between receiving countries, such as those of the Latin America and the Caribbean
subgroup, mainly driven by Mexicans in the US but not in Europe. In the same vein, residual
confounding may also be due to different distributions of generations within ethnic groups, with
US-born Hispanics and Asians more likely to be second generation than US-born Blacks or
Whites, who are mostly fourth or higher generation.98 Even first generation migrants may differ
in their risk of adverse birth outcomes according to their length of residence in the receiving
country, information that was rarely collected.51,67,77
Studies were heterogeneous in the way migrants were grouped into world regions, possibly
reflecting the diversity of immigration patterns between receiving countries, lack of consensus
about appropriate classifications, constraints in the availability of data, or population size
considerations. We did not assess publication bias because selected studies were mostly
exploratory, had high variation in their objectives and hypotheses and in the choice of the
30
comparison groups. However, publication bias may be present if some authors were unwilling or
unable to publish studies showing no associations between migration and pregnancy outcomes,
although the direction of such expected associations is not obvious, given the diversity of
migrant and native-born groups.
Our findings should be regarded as global tendencies that may not apply to particular migrant
subgroups settling in particular countries, regions or even cities. Although it is recognised that
LBW may result from either early delivery or fetal growth restriction,99 explaining results of
LBW based on the results of PTB and SGA for particular groups should be limited to hypothesis
generation, since the studies included in the analyses are not the same for LBW, PTB and SGA.
Differences in birth outcomes by migrant status may be influenced by the processes of selective
migration and acculturation. Selective migration has been one of the major mechanisms used to
explain the birth weight advantage of migrant compared with receiving-country women,
particularly Mexicans in the US,6,7,18,29,66,74,79 although there was no direct evidence to support
this hypothesis. While some studies referred to the ‘healthy migrant effect’ by highlighting the
favourable distribution of some risk factors for birth outcomes among migrant versus non-
migrant women,6,26,33 the relevant comparison group for assessing selective migration is the one
that stayed in the home countries100 and the few studies referring to this comparison discussed
only secondary data.18,66,93
31
2.4.1. Migration and ethnic disparities
The protective effect in the immigrant generation has a clear gradient: It is stronger for Black
migrants, still present among Hispanics, but virtually absent among Asians and Whites. This
gradient mirrors the ethnic group hierarchy in the US, which places people of African descent at
the bottom, Hispanics in the middle, and gives (East) Asians a favourable treatment close to that
of Whites. 101,102 These findings are at odds with the classical assimilation theory that predicts a
convergence of the outcomes of migrant groups towards the level observed in the mainstream
White society. 103 Instead, the observed pattern is more consistent with the segmented
assimilation theory that suggests that migrants are selectively incorporated into the system of
stratification of the American society based on their ethnic affiliation. 102
The better birth outcomes of foreign-born Blacks versus their US-born counterparts cannot be
explained by the ‘genetic hypothesis’, which would predict that US-born Blacks be an
intermediate risk group between foreign-born Blacks and US-born Whites because of
intermarriage and genetic mixing over previous generations. 6,83 Among the environmental
explanations, assimilation theories cannot fully account for US-Black disadvantage, since these
theories focus on how migrants and their offspring are incorporated into the host society 102,103
and about 97% of US-born Blacks were fourth or higher generation in 1990. 98 A few studies
have proposed a socio-historic hypothesis, pointing to continuous exposure to socioeconomic
and structural discrimination, 44,86,104 from past historical periods to the urban underclass. Such
explanation is consistent with a substantial sociological literature indicating that racial
segregation concentrates deprivation in Black neighbourhoods by concentrating people who fit
negative racial stereotypes and by restricting the poverty created by economic downturns into a
small number of visible minority neighbourhoods, mainly through discrimination in the housing
32
market. 105,106 Residential racial segregation has been positively associated with infant mortality
among Blacks but negatively among Whites,107 and the Black-White gap in PTB was found to be
higher in hypersegregated areas.108
Because international migration barely contributes to the number of Blacks in the US, the
relative advantage of foreign-born Blacks have little impact on the birth outcomes of Blacks as a
whole. In contrast, migrant women contributed to nearly 60% of births among Hispanics, thus
shaping the birth outcomes of this ethnic group.
2.4.2. Migration and region of origin and destination
Regarding subgroups defined by region of origin and destination, Sub-Saharan African and Latin
American and Caribbean migrants were at higher odds of LBW in Europe but not in the US and
South-Asians were at higher odds in both continents, although their disadvantage was somewhat
attenuated in the US. Part of these differences can be explained by the ethnic composition of the
native-born populations in these analyses, defined by their place of birth but not by their ethnic
groups, and by the patterns of emigration. Thus, US-born compare unfavourably with European-
born partly due to the heavier weight of their ethnic minorities. In the same vein, the Latin
American advantage in the US may be driven by the disproportionate representation of Mexicans
in the US, but not in Europe. Low birthweight rates of Mexicans were among the lowest among
Latin American immigrants. 87 It is believed that Mexicans in the US are protected because of
their residential proximity with co-ethnics, social support systems, and cultural orientation,
75,77,84,109 all of which is facilitated by the spatial contiguity with the home country. The
safeguarding of such protective traits may be more difficult to achieve in transatlantic Europe.
33
The reasons for the higher odds of LBW of Sub-Saharan Africans in Europe compared with
those settling in the US are not clear. Differential migration could not be assessed because, with
one exception, 82 studies did not provide information at the country-level. It is unlikely that the
distribution of reported risk factors accounts for the difference, since the rates of anaemia,
tobacco smoking, marital status, maternal education, and low income were comparable in both
continents. 6,12,60,79,82 Unmeasured factors or a differential effect of the receiving environments
may likely play a role. However, the same receiving environment may affect some migrant
groups favourably and others unfavourably, as suggested in a Swedish study.67
2.4.3. Further research
It remains to be determined whether and to what extent the risk of adverse birth outcomes differs
for particular migrant groups according to their actual destination and whether such effect, if
existent, is due to selective migration or to differential exposures in the receiving environment.
Although we did not find strong evidence that the risk of LBW among particular migrant
subgroups differed according to their geographic destination, the strength of the associations
between particular migrant groups and the native-born population differed by continent (Table
2.4). While our analyses suggest that these differences are mainly driven by differences in the
baseline risk of the European and American populations, the existence of differences in the risk
of adverse birth outcomes within migrant groups according to place of migration remains a
plausible hypothesis. A recently published systematic review 110 reported that the incidence of
adverse birth outcomes among immigrants to European countries were higher in receiving
countries with weak integration policies, such as the U.K. Although this review seems to support
the existence of receiving country-level determinants, confounding is likely to partially account
for its findings, since authors did not control for country of birth. This limitations is of concern
34
when we realized that about 60% of births to immigrants included in the review were born in the
U.K., a country which immigration is dominated by South Asians and Sub-Saharan Africans,89
two groups at high risk of adverse birth outcomes.
Although the comparison between migrants and majority populations may be of interest in itself
for highlighting disparities by migrant status as a single category, the marginal effect estimate of
being foreign-born is actually an average of several groups with high variation in their risk of
birth outcomes. Future research should thus strive to distinguish subgroups defined by their
regions and, when feasible, by their countries of origin since there may be heterogeneity between
countries within the same world region.87,90 Distinguishing subgroups within the receiving-
country population is also recommended, especially in countries highly stratified by
race/ethnicity such as the US.96 Our analyses imply that the definition of the migrant groups and
the choice of the reference groups have a decisive impact on the direction and strength of the
effect estimates for the migrant groups.
Further research on migration and adverse birth outcomes may advance knowledge by examining
why some migrant groups experience poor outcomes and why others do not and what are the
dynamics leading to worse outcomes among the offspring of some migrant groups. Future
studies will benefit from obtaining longitudinal measurements on migrants, including pre-
migration characteristics and circumstances of immigration, and social environment, medical
care and health behaviour after arrival.
35
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46
Chapter 3 Increase in Preterm Births Associated with Duration of Residence
among Immigrants living in Ontario Metropolitan Areas
Abstract
The proportion of live births to migrant women in industrialized countries has been growing
during the last decades. Yet, the determinants of adverse birth outcomes among immigrants are
not well understood. The ‘convergence hypothesis’ suggests that health outcomes of immigrants
will approach the level observed in the native population with increasing time in the new
environment. We linked birth data (2002-2007) with an immigration database of all legal
immigrants to Ontario, Canada, who obtained their permanent residence between 1985 and 2000
to examine the association between duration of residence and birth outcomes among immigrants
(N=83,233) and compare it with the birth outcomes of non-immigrants (N=314,237). We used
hierarchical models to account for the clustering of births into maternal countries of birth. After
adjustment for pregnancy and immigration characteristics, duration of residence was associated
with increases in low birth weight [5-year adjusted odds ratio (95% CI)]: 1.08 (1.03-1.13),
preterm birth: 1.14 (1.10-1.19), and small preterm: 1.15 (1.09-1.21) but not with small for
gestational age: 0.99 (0.96-1.02). Our findings suggest that the deterioration of the birth
outcomes was driven by a shortening of gestational age with time spent in Canada.
47
3.1. Introduction
Women constitute half – almost 95 million - of all international migrants.1 The percentage of
births among migrant women in most industrialized countries has shown upward trends in the
last two decades.2-4 Currently, immigrant women contribute to more than one fifth of all live
births in the United States3 and several European countries.5
Much of the research on the effects of acculturation on birth outcomes has been carried out in the
US, particularly among women of Mexican descent, who experienced deterioration in their birth
outcomes with increased acculturation.6,7 Acculturation has been measured by acculturation
scales7, and proxies such as language use8, nativity8-11 (i.e., foreign-born versus native-born or
country of birth), and duration of residence.12-14 Language use was identified as the main
component of acculturation6 and it was suggested that it may modify the effect of nativity.8
Differences in birth outcomes between foreign-born and native-born (second generation) women
of the same ethnicity may reflect selection bias (the healthy migrant effect) or the effect of the
receiving country environment, either via acculturation or environmental exposures.
While nativity is useful to measure changes in the outcomes from one generation to the next, it
cannot assess changes in the outcomes within first generation migrants after arrival.
Comparisons by nativity status may be confounded by selection of healthy migrants, cohort
effects, or by duration of residence of foreign-born women if there is an association between
duration of residence and birth outcomes.
Data needed to assess duration of residence are scarce, thus limiting the number of studies on
this issue. Duration of residence was associated with a deterioration of birth outcomes among
foreign-born Mexicans in Washington12 and California.13 However, it is not clear whether
48
women from other regions of the world are equally affected by the length of residence in the
receiving countries. Finns lowered their risk of low birthweight and preterm birth after 3 years of
stay in Sweden but Sub-Saharan Africans experienced the opposite, suggesting that this relation
may vary by the maternal world region of origin.14 In addition, it has been suggested that the
relation between acculturation and low birthweight may not be linear.8,15 The few studies
assessing the association between duration of residence in the host country and low birthweight
and preterm birth have measured duration of residence as a dichotomous variable, with recent
immigrants defined by less than two,12 three,14 and five13 years versus the remaining immigrants
(long-term residents). The length of the observation period may impact on the study conclusions.
It is unknown whether duration of residence considered in all its length has a threshold effect, a
dose-response effect, or a non-linear effect on birth outcomes of immigrants, and whether such
relations vary according to the maternal world region of origin.
One potential pattern is provided by the ‘convergence hypothesis’, inspired on the studies on
coronary heart disease and stroke gradients of Japanese men living in Japan, Hawaii, and
California.16 The convergence hypothesis suggests that health outcomes of immigrants will tend
to converge over time towards the level observed in the host population, presumably via changes
in health-related behaviours. While this hypothesis seems to hold for overweight/obesity,17,18 and
behavioural risk factors18-20 the evidence is not consistent for mortality21, and it is not known
whether it applies to birth outcomes.
Our objectives were to examine the relation between immigrants’ duration of residence in Urban
Ontario and adverse birth outcomes (low birthweight and preterm birth and its components, and
small for gestational age) across 20 years since arrival, overall and by maternal world regions of
origin, and to make comparisons with the non-immigrant population. Urban Ontario is an
49
appropriate setting to study immigrants’ health as Ontario is Canada’s most populated province
and receives annually about half of all immigrants to Canada, with more than 90 % of them
concentrated in urban areas.22
3.2. Methods
3.2.1. Data sources
The Discharge Abstract Database (DAD) of the Canadian Institute for Health Information (CIHI)
compiles information on admissions/services/discharges of all acute Ontario hospitals, where
most deliveries take place, excepting home births.
Birth and maternal records were internally merged according to an algorithm described
elsewhere,23 updated to reflect the changes from ICD-9 to ICD-10-CA, resulting in 96% of
mothers with a valid match to an infant in the fiscal years 2002/2003-2006/2007. Although the
DAD includes a deterministic linkage between the records of the mother and the child since
fiscal 2002/2003 the resulting match was in between 80% and 90%, and therefore ICES
programmers preferred the probabilistic linkage as the most sensitive. Further details on the data
sources are in Appendix 3.A.
We extracted 474,614 singleton live births (see Appendix 3.B. for details about the exclusion of
stillbirths and multiple births) born to mothers living in any of the 11 Ontario Census
Metropolitan Areas (Great Sudbury, Hamilton, Kingston, Kitchener, London, Oshawa, St.
Catherines-Niagara, Ottawa-Gatineau, Thunder Bay, Toronto, and Windsor)24 at the time of
delivery, between April 1, 2002 and March 31, 2007.
50
Data on immigration were contained in the Landed Immigrant Data System (LIDS), which is the
official immigration registry compiled by Citizenship and Immigration Canada (CIC) and
contains information on sociodemographic and immigration characteristics. These records were
linked with the registry of the Ontario Health Insurance Plan (OHIP), which provides universal
access to nearly all physician and hospital services (except for asylum seekers and during the
first 3 months’ residence). This linkage matched 84% of individuals whose intended destination
was Ontario and that obtained their legal permanent residence from January 1, 1985 to December
31, 2000. Many unmatched individuals may have moved out of the province shortly upon arrival.
In order to avoid misclassification of immigrant status regarding immigrants obtaining their
permanent residence after December 2000, we excluded 74,961 infants whose mothers were first
registered into the Ontario Health Insurance Plan after March 31, 2001 (to account for the 3-
month waiting period), who may be newcomers either from abroad or from other provinces. We
further excluded births weighing less than 500 grams and more than 6000 grams because of the
high likelihood of data errors (N=360), with missing information on the outcomes or gestational
age (N=125), with gestational age less than 22 and more than 43 completed weeks (N=72), with
missing information on infant sex, parity, or maternal age (N=54), on maternal
sociodemographic and immigration characteristics (N=576), and immigrants classified as ‘other’
(N=487). These data were finally merged with small-area data (census tracts) from the 2001
Canadian census. After excluding 509 records to which census information could not be
assigned, our study population for analyses comprised 397,470 singleton live births (21% of
them born to immigrant mothers). A flowchart of the data exclusions is shown in Appendix 3.C.
51
3.2.2. Outcomes
We used several adverse birth outcomes, all defined as categorical. Low birthweight (LBW) was
defined as a birth with less than 2,500 grams, very low birthweight (VLBW) with less than 1,500
grams, and moderately low birthweight (MLBW) within the range 1,500-2,499 grams. Preterm
birth (PTB) was defined as a delivery before 37 completed weeks of gestation, very preterm birth
(VPTB) before 32 weeks, and moderately preterm birth (MPTB) as 32 weeks or more but before
37 weeks. We included small preterm birth (SPTB) defined as infants having both LBW and
PTB, because these babies are at higher risk of subsequent adverse outcomes, such as infant
mortality.25 We defined small for gestational age (SGA) as a birth weight lower than the 10th
lowest percentile of the most recent Canadian sex- and gestational age-specific birthweight
distribution,26 because this measure represents a proxy for fetal growth that is relatively
independent of gestational age.
3.2.3. Predictors
We assessed the amount of exposure to a Canadian setting by duration of residence in Canada,
defined as the time (in days) since arrival to delivery. We also modeled duration in completed
years and in approximately 5-year duration groups (15 months to 4 years, 5 to 9 years, 10 to 14
years, and 15 years and more).
As potential confounders, we considered from hospital records infant gender (male as referent),
maternal age at delivery (15-19, 20-24, 25-29, 30-34 [referent], 35-39, and ≥ 40 years), parity
(primiparae versus multiparae). We conceptualized maternal morbidity during pregnancy as a
potential mediator of the effect of duration of residence on preterm birth by including genito-
52
urinary infection (ICD-10: O230-O235, O239), pregnancy-induced hypertension (O13, O140,
O141, O149), incompetent cervix (O343), and placental abruption (O450, O458, O459).
Immigrant characteristics that may confound the association between duration of residence and
adverse birth outcomes included maternal country of birth, maternal age at arrival (<12, 12-18,
19-25, 26-30, and > 30 years), high school graduation (yes as referent), and marital status
(married or common law [referent] versus single, widowed, or separated), immigrant class
(economic class, family class [referent], and refugee status), and knowledge of any official
Canadian language (English or French [referent] versus none). These characteristics were
measured at landing and based on legal documentation provided by the immigrants during the
application process, with the only exception of language knowledge, which was self-reported.
Countries of birth were grouped into world regions following the UNICEF classification.27 We
also assigned each mother a material deprivation score based on their place of residence at
delivery. The material deprivation score was constructed by summarizing information on six
census variables28 (percentage of population aged ≥ 20 years without high school graduation,
percentage of lone parent families, percentage of families receiving government transfer
payments, percentage of population aged ≥ 15 years unemployed, percentage living below the
low income cut off, and percentage of homes needing major repair) at the census-tract level by
means of factor analysis. The resulting continuous score was standardized thus having a mean of
0 and a standard deviation of 1. We collapsed it into tertiles of approximately equal number of
census tracts for easier interpretation. Census tracts (our neighbourhoods) were relatively stable
urban neighbourhoods with a typical population of 2500 to 8000 and were relatively
homogeneous in population characteristics and living conditions.
53
3.2.4. Statistical analyses
We inspected the shape of the relation between duration of residence (measured as days from
arrival to delivery) and all birth outcomes using bivariate plots and logistic models with linear,
quadratic, and cubic terms, as well as with dummy variables (approximately 5-year duration
groups). A linear specification of duration resulted in a better fit assessed by the likelihood ratio
test.
Selection of variables for covariate adjustment for the association between duration of residence
and preterm birth among immigrants was based on directed acyclic graphs (DAGs).29 We
checked the hypothesized relation between the variables in our conceptual model by empirically
assessing the association between the variables before conducting the backdoor test for
sufficiency.29,30 All potential confounders were included in the adjusted models, with the
exception of neighbourhood material deprivation because it was a mediator and infant sex
because it was not directly or indirectly associated with the exposure. We did not consider health
behaviours and maternal morbidity during pregnancy because they are considered to mediate the
effects of duration on birth outcomes. Causal diagrams are shown in Appendix 3.D.
We conducted multilevel logistic regression analyses using GLIMMIX in SAS 9.1 (SAS
Institute, Cary, NC) to account for the clustering of births within maternal countries of birth
among immigrants, a clustering that was found to be more relevant for immigrants than
clustering into neighbourhoods (see Chapter 4). The use of hierarchical models avoids incurring
in the ecologic fallacy 31 that consists in drawing inferences at the individual level (level 1) using
data measured at higher levels (level 2) (e.g., countries, neighbourhoods) and allows the
estimation of cross-level effects (e.g., country of origin effects on birth outcomes). Hierarchical
54
models are useful even when the independent variable of interest is measured at the individual-
level (e.g., duration of residence) because the effect estimate of the level 1 variable on the
outcome is adjusted for the statistical dependency of the individual observations within level 2
units (e.g., maternal countries of origin).32 Failure to take into account the dependence of
individual observations within higher-level units may lead to underestimate standard errors and
misleading conclusions. In fact, ordinary least squares (OLS) regression is one special case of the
multilevel model in which the level-2 variance equals zero, meaning that all the variability is
inter-individual and there is no inter-group variability.
3.3. Results
Immigrants exhibited higher proportions of adverse outcomes with increasing duration of
residence, with the exception of SGA (Table 3.1). Immigrants also differed in marital status,
education, and knowledge of official languages, according to duration of residence, but part of
these differences were due to the fact that these variables were measured at arrival and therefore
affected by the maternal age at arrival. Yet, the trends across duration groups remained
significant after restricting the population to women aged 20 years or more at arrival (not
shown). Higher proportions of refugees and immigrants from Latin America and industrialized
countries with more years of residence reflect changing immigration patterns over time, more
recently dominated by immigrants from East and South Asia.
55
Table 3.1: Characteristics of the study population, by migrant status, and duration of residence, Urban
Ontario, live births 2002-2007
Immigrants by duration of residence
Non-immigrants
All Immigrants
p-value* < 5 y 5-9 y 10-14 y 15 y + p-trend**
Singleton live births 314,237 83,233
14,555 32,539 23,827 12,312
Outcomes Low birthweight % 4.29 5.34 <.0001 4.61 4.98 5.93 6.03 <.0001 Very low birthweight % 0.63 0.88 <.0001 0.61 0.80 0.99 1.19 <.0001 Moderately low birthweight % 3.66 4.46 <.0001 4.00 4.18 4.94 4.83 <.0001 Preterm birth % 6.25 5.99 0.0059 4.72 5.57 6.61 7.43 <.0001 Very preterm birth % 0.77 0.99 <.0001 0.66 0.91 1.12 1.34 <.0001 Moderately preterm birth % 5.48 5.00 <.0001 4.06 4.66 5.48 6.09 <.0001 Small preterm birth % 2.88 3.24 <.0001 2.39 2.96 3.73 4.03 <.0001 Small for gestational age % 7.68 11.06 <.0001 11.37 11.00 11.01 10.95 0.3145 Infant and maternal characteristics
Infant sex (male) 51.18 51.66 0.0149 51.67 51.78 51.34 51.93 0.9409 Maternal age at delivery < 20 years 3.67 1.83 <.0001 1.06 1.63 2.49 2.00 <.0001 20-24 years 11.42 10.85 <.0001 12.87 9.67 10.77 11.76 0.2868 25-29 years 26.22 27.93 <.0001 33.47 28.73 23.92 27.01 <.0001 30-34 years 36.54 34.01 <.0001 35.67 36.71 31.70 29.37 <.0001 35-39 years 18.53 20.49 <.0001 14.68 19.66 24.49 21.79 <.0001 ≥ 40 years 3.62 4.89 <.0001 2.25 3.60 6.63 8.07 <.0001 Primipara 46.54 36.55 <.0001 40.97 33.74 35.79 40.21 0.5541 Neighbourhood material deprivation
Low 44.41 29.66 <.0001 23.84 30.01 29.62 35.97 <.0001 Med 29.18 28.44 <.0001 30.14 28.72 27.57 27.39 <.0001 High 26.41 41.90 <.0001 46.02 41.27 42.81 36.94 <.0001 Maternal morbidity Genito-urinary infection 1.95 1.55 <.0001 2.08 1.48 1.50 1.20 <.0001 Pregnancy-induced hypertension 0.97 0.77 <.0001 0.51 0.69 0.91 1.04 <.0001
Incompetent cervix 0.31 0.49 <.0001 0.27 0.45 0.59 0.67 <.0001 Abruptio placenta 1.02 0.92 0.0122 0.90 0.90 0.97 0.93 0.5727 Maternal age at arrival < 12 y N/A 9.47 0.03 1.66 11.77 36.79 <.0001 12-18 y 22.28 4.79 16.22 32.76 38.70 <.0001 19-25 y 40.59 39.53 46.57 42.44 22.51 <.0001 26-30 y 20.92 36.47 27.83 11.78 1.96 <.0001 30 y + 6.74 19.18 7.72 1.25 0.04 <.0001 Unmarried / not cohabiting at arrival N/A 56.06 18.35 45.59 76.17 89.38 <.0001
No High School graduation at arrival N/A 63.36 38.19 54.66 77.53 88.69 <.0001
Knowledge of English/French at arrival N/A 56.60 51.90 55.63 58.53 61.03 <.0001
Immigrant Class N/A Economic 28.73 38.72 27.01 23.01 32.50 <.0001 Family 57.42 57.32 63.99 56.94 41.11 <.0001 Refugee 13.85 3.96 9.00 20.06 26.39 <.0001 World Region of birth N/A Central / East Europe 7.42 9.28 9.64 5.65 2.75 <.0001
56
Immigrants by duration of residence
Non-immigrants
All Immigrants
p-value* < 5 y 5-9 y 10-14 y 15 y + p-trend**
Latin America & Caribbean 18.24 7.18 12.82 23.51 35.45 <.0001 Middle East / North Africa 7.42 9.21 8.23 6.33 5.26 <.0001 East Asia / Pacific 18.32 22.51 19.31 17.06 13.18 <.0001 South Asia 27.05 40.16 32.36 19.91 11.35 <.0001 Sub Saharan Africa 7.70 4.19 7.60 10.56 6.59 <.0001 Industrialized Countries 13.85 7.47 10.64 16.98 25.41 <.0001
* Chi square between immigrants versus non-immigrants ** Two-sided p-value of Cochran-Armitage test for trends for binomial proportions across duration groups (when the variable had more than 2 categories, each category was compared to the rest)
Table 3.2. Unadjusted odds ratios (and 95% confidence intervals) for adverse birth outcomes between
non-immigrants and immigrants, overall and by duration of residence in Canada, 2002/2003 to 2006/2007
All immigrants versus Non-immigrants
Immigrants by duration of residence versus non-immigrants
Outcome < 5 years 5 – 9 years 10 -14 years ≥ 15 years OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Low birthweight 1.26 (1.22-1.30) 1.08 (1.00-1.16) 1.17 (1.11-1.23) 1.41 (1.33-1.49) 1.43 (1.33-1.55)
Very low birthweight 1.39 (1.28-1.52) 0.97 (0.78-1.20) 1.26 (1.11-1.44) 1.57 (1.37-1.80) 1.90 (1.61-2.25)
Moderately low birthweight 1.23 (1.19-1.28) 1.10 (1.01-1.19) 1.15 (1.09-1.22) 1.37 (1.29-1.46) 1.34 (1.23-1.46)
Preterm birth 0.96 (0.93-0.99) 0.74 (0.69-0.80) 0.88 (0.84-0.93) 1.06 (1.01-1.12) 1.21 (1.12-1.29)
Very preterm birth 1.28 (1.19-1.39) 0.85 (0.69-1.05) 1.17 (1.04-1.33) 1.46 (1.29-1.66) 1.74 (1.49-2.04)
Moderately preterm birth 0.91 (0.88-0.94) 0.73 (0.67-0.79) 0.84 (0.80-0.89) 1.00 (0.95-1.06) 1.12 (1.04-1.21)
Small preterm birth 1.13 (1.08-1.18) 0.82 (0.74-0.92) 1.03 (0.96-1.10) 1.31 (1.22-1.40) 1.42 (1.29-1.55)
Small for gestational age 1.50 (1.46-1.53) 1.54 (1.46-1.63) 1.49 (1.43-1.54) 1.49 (1.43-1.55) 1.48 (1.39-1.57)
Table 3.2 compares the unadjusted odds of adverse birth outcomes of immigrant women (as a
single category and by duration of residence) relative to non-immigrants. Adjustment for infant
sex, maternal age, and parity did not alter the estimates substantially.
57
Comparisons of all immigrants as a single category with non-immigrants represent average
estimates that mask the importance of duration of residence as a determinant of adverse birth
outcomes (except SGA) among immigrants. Immigrant women with short duration of residence
had lower odds of adverse birth outcomes than the average while those with long duration had
higher odds than the average (Table 3.2). In addition, recent immigrant women (< 5 years)
exhibited similar or lower odds of adverse birth outcomes than their Canadian counterparts, but
these advantages were lost after 5 to 14 years, depending on the outcome, and exhibited
consistently higher odds than the reference group after 15 years of residence.
Table 3.3 shows the results of the multilevel models fitted to better evaluate whether the
association between immigrants’ duration of residence and adverse birth outcomes was not due
to confounding by maternal and immigration characteristics. With the exception of small for
gestational age, duration of residence was independently associated with all remaining outcomes.
The absence of an association between duration and SGA when the remaining outcomes were all
associated with duration is suggestive of the presence of some mechanism related to a shortening
of gestational age. To explore this possibility we fitted models for LBW and its components,
further adjusted for preterm birth or gestational age. Results shown in Table 3.4 indicate that the
trends in these outcomes with increasing duration were mainly explained by shorter gestations.
58
Table 3.3: Adjusted odds ratios (and 95% confidence intervals) for adverse birth outcomes by immigrants’
duration of residence in Canada, urban Ontario live births 2002-2007
5-year AOR* Immigrants by duration of residence
outcome <5 years 5 – 9 years 10 -14 years ≥ 15 years p-trend
Low birthweight 1.08 (1.03-1.13) 1.00 1.06 (0.96-1.17) 1.20 (1.07-1.34) 1.17 (1.02-1.33) 0.0044
Very low
birthweight 1.17 (1.06-1.30) 1.00 1.22 (0.95-1.57) 1.34 (1.01-1.78) 1.54 (1.11-2.12) 0.0099
Moderately low
birthweight 1.06 (1.01-1.11) 1.00 1.03 (0.93-1.15) 1.17 (1.04-1.32) 1.10 (0.95-1.27) 0.0527
Preterm birth 1.14 (1.10-1.19) 1.00 1.14 (1.04-1.26) 1.27 (1.14-1.42) 1.39 (1.23-1.58) <.0001
Very preterm birth 1.18 (1.07-1.30) 1.00 1.28 (1.01-1.63) 1.40 (1.07-1.84) 1.60 (1.18-2.17) 0.0037
Moderately
preterm birth 1.13 (1.09-1.19) 1.00 1.12 (1.01-1.24) 1.25 (1.11-1.40) 1.35 (1.18-1.55) <.0001
Small preterm birth 1.15 (1.09-1.21) 1.00 1.18 (1.04-1.34) 1.36 (1.17-1.57) 1.40 (1.18-1.67) <.0001
Small for
gestational age 0.99 (0.96-1.02) 1.00 0.98 (0.92-1.05) 0.97 (0.90-1.05) 0.95 (0.86-1.04) 0.2984
* AOR= adjusted odds ratios, adjusted for maternal age at delivery, parity, immigrant class, country and region of birth, language
knowledge, high school graduation, and unmarried status.
Table 3.4. Odds ratios adjusted for all covariates in Table 3.3 and also adjusted for preterm birth
Immigrants by duration of residence Outcome 5-year AOR*
<5 years 5 – 9 years 10 -14 years ≥ 15 years p-trend
Low birthweight 1.00 (0.95-1.05) 1.00 0.97 (0.87-1.09) 1.06 (0.92-1.21) 0.96 (0.82-1.12) 0.9963
Very low
birthweight 1.05 (0.94-1.17) 1.00 1.08 (0.82-1.41) 1.05 (0.77-1.42) 1.14 (0.81-1.61) 0.5567
Moderately low
birthweight 0.99 (0.94-1.04) 1.00 0.96 (0.85-1.08) 1.05 (0.92-1.20) 0.92 (0.79-1.08) 0.7234
* AOR= adjusted odds ratios, adjusted for maternal age at delivery, parity, immigrant class, country and region of birth, language
knowledge, high school graduation, unmarried status, and preterm birth.
Figure 3.1 depicts predicted probabilities based on a preterm birth 2-level model, with births
nested within maternal countries of birth, including duration of residence as a continuous
variable and adjusted for the variables selected based on the DAG. The flat line represents the
59
crude average preterm birth percent for non-immigrants during the study period, that is, the level
achieved by the host population, against which to compare the level of preterm birth achieved by
the immigrants according to their years of residence in Canada.
Figure 3.1. Predicted probabilities (and 95% CI) of Preterm Birth (2002-2007) among Ontario immigrants,
by duration of residence*
* adjusted for maternal age at delivery, parity, immigrant class, country and region of birth, language knowledge, high school
graduation, unmarried status.
60
Figure 3.2. Gestational age distributions (and means) by duration of residence groups
The frequency distribution of gestational age shifts uniformly to the left (and also their means –
vertical lines) with increasing duration of residence.
These estimates of Table 3.5 were obtained by stratified analyses by world region. Multilevel
modeling was used for all immigrants but not in stratified analysis by world regions due to the
small number of countries within them. For those outcomes previously associated with duration
of residence there were no great differences between world regions. With the exception of SGA,
the direction of the association with duration did not substantially vary across world regions,
being positive or null but not negative.
61
Table 3.5: Adjusted* odds ratios per 5-year increase in duration of residence in Canada (birth to
immigrants 2002-2007), by world region LBW VLBW MLBW PTB VPTB MPTB Small PTB SGA
All immigrants 1.08
(1.03-1.13)
1.17
(1.06-1.30)
1.06
(1.01-1.11)
1.14
(1.10-1.19)
1.18
(1.07-1.30)
1.13
(1.09-1.19)
1.15
(1.09-1.21)
0.99
(0.96-1.02)
By world region
Central/East
Europe
1.26 (1.02-1.57)
1.11
(0.64-1.93)
1.29 (1.02-1.64)
1.19
(0.99-1.42)
1.02
(0.64-1.61)
1.22 (1.00-1.48)
1.32 (1.02-1.71)
1.06
(0.90-1.25)
Latin America &
Caribbean
1.00
(0.92-1.08) 1.11
(0.94-1.31)
0.97
(0.89-1.06)
1.07 (1.00-1.16)
1.10
(0.94-1.29)
1.06
(0.98-1.16)
1.12 (1.01-1.23)
0.94
(0.88-1.00)
Middle East /
North Africa
0.98
(0.81-1.18)
0.79
(0.49-1.28)
1.02
(0.83-1.25)
1.07
(0.90-1.26)
1.26
(0.83-1.89)
1.04
(0.87-1.24)
1.07
(0.85-1.36)
0.83 (0.72-0.94)
East Asia /
Pacific
1.25 (1.12-1.40)
1.10
(0.81-1.50)
1.27 (1.13-1.43)
1.25 (1.13-1.38)
1.05
(0.80-1.40)
1.27 (1.14-1.42)
1.20 (1.04-1.38)
1.08
(1.00-1.18)
South Asia 1.06
(0.97-1.16)
1.45 (1.17-1.79)
1.00
(0.91-1.10)
1.13 (1.03-1.23)
1.32 (1.07-1.63)
1.09
(0.99-1.20)
1.19 (1.06-1.34)
0.96
(0.90-1.02)
Sub Saharan
Africa
1.44 (1.22-1.69)
1.32
(0.94-1.85)
1.45 (1.21-1.75)
1.31 (1.11-1.53)
1.52 (1.08-2.14)
1.24 (1.04-1.48)
1.31 (1.07-1.61)
1.18 (1.04-1.33)
Industrialized
Countries
1.10
(0.97-1.25)
1.28
(0.93-1.77)
1.07
(0.93-1.23)
1.20
(1.07-1.34)
1.24
(0.93-1.64)
1.19
(1.05-1.34)
1.12
(0.95-1.31)
1.08
(0.98-1.17)
* adjusted for maternal age at delivery, parity, immigrant class, language knowledge, high school graduation, and unmarried status.
3.3.1. Sensitivity analyses
In order to evaluate the possibility that the observed associations between duration of residence
and adverse birth outcomes were confounded by cohort effects, we selected a group of
immigrants (N=69,522) that obtained their permanent residence from January 1985 to December
31, 1998, and observed their LBW and PTB over time and the results were consistent with our
main analyses (see Appendix 3.E). In this ‘cohort approach’ we could not adjust for parity
because this variable was not available prior to fiscal 2002/2003 but we adjusted for year of birth
to control for the secular trends in preterm birth over time.33,34
62
Figure 3.3. Predicted probabilities* of preterm birth according to duration of residence, by cohort of arrival
* Based on a stratified multilevel model (country of birth as random intercept) by 4-year cohort of arrival (1985 to 1988, 1989 to
1992, 1993 to 1996, and 1997 to 2000), adjusted for maternal age at delivery, immigrant class, language knowledge, high school
graduation, unmarried status, and year of birth.
We also performed stratified analyses by cohort of arrival to Ontario and plotted the predicted
probabilities of preterm birth according to the duration of residence (Figure 3.3). Although
cohorts differed somewhat in their risk of preterm birth (more recent cohorts have higher risk;
this being consistent with the secular trends in preterm birth over time), the pattern of increasing
preterm birth with longer duration was pervasive across all four cohorts.
Although we based our covariate adjustment on causal diagrams, we also fitted our models with
the excluded variables material deprivation and infant sex but the results of Table 3.3 remained
unaffected. We expected that the inclusion of material deprivation would have attenuated the
association between duration and birth outcomes but it had the opposite effect, basically because
63
recent immigrants (who had the best outcomes) were more concentrated in deprived
neighbourhoods than long-term immigrants (who had the worse outcomes). As maternal
education, marital status, and knowledge of official languages were measured at arrival, and
therefore affected by the age at arrival, we repeated our analyses restricted to women aged 20
years and more at arrival but the association between duration of residence and adverse birth
outcomes did not change substantially. Finally, although the possibility of confounding by
secular increases in preterm delivery was controlled for by design (i.e., we restricted the study
population to liveborns delivered in the most recent 5-year period available), preterm deliveries
increased nearly 10% from fiscal year 2002/2003 to 2006/2007, thus raising the possibility of
residual confounding by trends over time within the study period. We therefore included year of
birth in the adjusted model to control for such potential residual confounding but its addition did
not have any visible impact on the effect estimates of duration of residence. Stratified analyses
restricted to one fiscal year at a time showed an independent association between duration of
residence and preterm birth, thus confirming that the association was not confounded by year of
delivery.
3.4. Discussion
The longer the time immigrant women resided in urban Ontario the higher their probability of
having adverse birth outcomes, except for small for gestational age. This exception, in
conjunction with a gestational age distribution shifted to the left among women with 15 or more
years spent in Canada and with the disappearance of the association between duration of
residence and LBW and its components after adjusting for preterm birth, strongly suggests that
the observed association between length of stay in Canada and adverse birth outcomes was
64
mainly driven by decreases in gestational age, which is consistent with a previous study on
Mexicans in the US.13 This finding cannot be explained by the secular trends in preterm birth
35,36 because we controlled such potential confounding effect by design (i.e., restriction of infants
born in the most recent 5-year period available, within which secular trends in the outcomes were
largely minimized). Confounding by cohort effects was a more serious threat that was partially
accounted for in our main analyses by adjusting for immigrant class and maternal country and
region of birth. We ruled out confounding by cohort effects as an alternate explanation to our
findings by repeating our analyses on a group of immigrant women arrived in the late ‘80s and
observed from 1988 to 2007 and the results were consistent with our main analyses (see
Appendix 3.E). Although cohort effects may have confounded somewhat our estimates,
principally those of particular world regions, the magnitude of such potential bias is small, since
the estimates obtained with the immigrants arrived from 1985 to 1989 were very similar to those
of the main analysis.
Our findings do not seem to support the convergence hypothesis. Low birthweight was
somewhat higher among recent immigrants compared with non-immigrants and continued to
increase with duration, contrary to the hypothesis. Recent immigrants were protected from
preterm birth and small preterm but lost their advantage after approximately 10 years. Instead of
remaining at that level, immigrants experienced a continuous deterioration that placed them at a
disadvantage after 15 years of stay, compared with non-immigrants. Rather than a ‘convergence’
the pattern of risk of preterm birth exhibited an ‘overshoot’, in which the risk of preterm birth
passed over the risk at which a plateau would be expected. Finally, because small for gestational
age was higher among immigrants than among non-immigrants a convergence would have
predicted a decrease but duration of residence had no visible impact on this outcome.
65
Our study had some limitations. Out of hospital births are not captured by the DAD. Gestational
age (in weeks) was measured in the DAD at the time of maternal admission but not at delivery
for the study period. Therefore, preterm birth rates may be higher using the DAD than other data
sources (e.g., Vital Statistics). It is unlikely that the bias resulting from using gestational age at
admission rather than at delivery would account for the observed association between duration of
residence and preterm birth, since maternal length of stay at the hospital from the admission date
to the delivery date showed little variation with duration of residence, and such variation was
explained by maternal sociodemographic characteristics (not shown).
Because immigrants’ data started in 1985 we could not identify those immigrants that obtained
their permanent residence prior to that year. This misclassification, however, would bias our
results towards the null because false non-immigrants were immigrants with at least 17 years of
residence, presumably at higher risk of adverse birth outcomes.
Although immigration data was of good quality, mostly ascertained by notarized documentation
provided by the applicants during the immigration process, some variables were measured at
arrival and not at delivery, which may be more relevant for time-dependent variables. Marital
status and maternal education may have changed for some women, especially for young women
at arrival who may have become married and more educated with longer duration of residence.
As educational attainment is not reversible the bias resulting from adjustment for an
underestimate of the true educational attainment of long term immigrants would have moved our
results towards the null, because higher education protects against adverse birth outcomes.
We could not control for maternal health behaviours during pregnancy, particularly tobacco
smoking. Although adjustment for these factors is not appropriate because they are
66
conceptualized as mediators between socioeconomic exposures and adverse birth outcomes,37
their consideration may have clarified potential mechanisms involved with duration of residence.
To measure small for gestational age we used a sex-specific Canadian standard (excluding
Ontario). 26 The use of a single standard of birthweight by gestational age that does not take into
account ethnic group differences may not be valid for infants born to mothers from particular
regions of the world, such as Asians. 38,39 The failure of using ethnic-specific standards of
birthweight by gestational age may have resulted in misclassification (i.e., greater probability of
classifying infants born to Asian mothers as SGA when they would not be SGA according to an
Asian-specific standard).39 Therefore, SGA findings must be interpreted with caution,
particularly when comparing immigrants versus non-immigrants. However, the effects estimates
of duration of residence on SGA within each migrant group defined by their maternal world
region of origin are supposed to be less biased because the reference group is internal to the
ethnic group (i.e., recent immigrants). It remains to be determined whether the use of ethnic-
specific standards may reveal an association between duration of residence and SGA among
various immigrant groups.
Despite these limitations, the association between duration of residence and gestational age-
related outcomes was quite robust, remaining unaltered under a range of sensitivity analyses,
such as covariate adjustment, restriction to women aged 20 years and older, and a different study
population composed of births delivered between 1988 to 2007.
Although our data were not detailed enough to elucidate mechanisms we can explore some clues.
First, the distribution of gestational age among immigrants with 15 or more years of stay is
shifted towards the left compared with the distribution of women delivering within the first five
years of stay. Although the curves do not reflect a true longitudinal process (i.e., the two groups
67
were composed of different women), it is noteworthy that the differences between the
distributions are spread all over the gestational age range. This feature strongly suggests the
presence of influences operating across the entire range of the gestational age distribution rather
than on a ‘high-risk’ subgroup affecting a critical period of gestation. 40,41
One candidate explanation is acculturation, which has already been linked with adverse birth
outcomes.6-8,42 Although a complex construct, acculturation basically entails a process by which
immigrants incorporate the behaviours and values of the host population.43 This suggests that the
effect of duration of residence may be mediated by changes in health behaviours and related risk
factors. Indeed, duration of residence has been used as a proxy for acculturation and been
associated with increases in obesity/overweight, smoking, alcohol consumption, and physical
inactivity, 17-20,44,45 factors that may negatively affect gestational age. Although we could not
assess mediation by these factors, secondary data suggest that acculturation is a plausible
hypothesis. Immigrants to Canada as a whole were less likely to have high-fat and carbohydrate
diet than non-immigrants46 as well as lower cigarette smoking and alcohol consumption
rates.47,48 Perhaps more intriguing is that immigrants with more than 10 years of residence in
Ontario had a right-shifted body weight distribution compared with those with less than 10 years
of stay, and twice their obesity rate. (Canadian Community Health Survey cycle 3.1, 2005)
While high pre-pregnancy weight has not been consistently associated with preterm birth in the
literature,49-51 it is interesting to note that higher body mass index has been found to be protective
for small for gestational age.49,52-54 It is reasonable to speculate that in our immigrant population
increases in body mass index may have compensated the detrimental effect of changes in risk
factors thus rendering a null association between duration of residence and small for gestational
age.
68
Another unexplored aspect of acculturation to Western societies may involve increased
medicalization with time spent in Canada. Such medicalization may be translated in a shortening
of the time from conception to first prenatal visit, increased compliance and enhanced prenatal
surveillance, preference for elective cesarean delivery, and use of assisted reproductive
technologies. When compared with menstrual dates, early ultrasound based dating results in a
left shift in the gestational age distribution. If immigrants with longer duration of residence were
more medicalized and enter antenatal care earlier, their gestational age estimate might has been
more likely to be based on early ultrasound than among less medicalized immigrant women who
had their first prenatal visit at a more advanced stage of their pregnancies. Even assuming
complete polarization of early ultrasound use in our study population, this could not completely
explain our results, since the bias resulting from using ultrasound dating only versus the last
menstrual period only was estimated to be no more than a 10-20% increase in the risk of preterm
birth,55 and we observed a 14%, 30%, and 49% increased odds associated with 5, 10, and 15
years of residence, respectively. Another potential pathway related to increased medicalization
may be increased preference for elective cesarean section, which may shorten gestation length
for some women. It is also possible that use of assisted reproductive technologies (ARTs) have
become more frequent among the more acculturated migrant couples. Use of ARTs has been
linked with increased risk of preterm birth, even among singleton infants.56
Another potential pathway may be maternal morbidity during pregnancy, especially pregnancy-
induced hypertension and incompetent cervix, conditions that increased with duration of
residence. However, these trends were counterbalanced by declining rates of genito-urinary
infections, which inclusion in the models strengthened the association between duration of
residence and preterm birth.
69
A last potential pathway leading to adverse birth outcomes, albeit unexplored among immigrant
women, may be related to their labour market experiences. Working conditions, such as long
working hours, prolonged standing, and physically demanding work has been associated with
PTB.57,58 Psychosocial exposures such as job strain, low job control and satisfaction may be
concomitant causes of preterm birth among immigrant women,59-62 who are more likely to be
employed in manual, clerical, and shift jobs. Despite 1990’s immigration policies favouring
immigrants with higher education, which resulted in an almost doubling of the rate of recent
immigrants with bachelor’s degrees to more than 40% in 2001, one third of recent immigrant and
one fourth of other immigrant working women worked in jobs requiring less than their education
level.63 Moreover, immigrants are more likely than non-immigrants to live in deprived
neighbourhoods, which may contribute to ‘weather’ migrant women, jointly with experiences of
subordination and discrimination.64
The clarification of the mechanisms behind the association between duration of residence and
preterm birth merits further investigation, especially when the contribution of immigrants to live
births in developed countries is growing. Our findings suggest that influences at the population
level are likely to play a key role and support the use of length of residence as an important
indicator for surveillance of immigrant health.
70
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(8) English PB, Kharrazi M, Guendelman S. Pregnancy outcomes and risk factors in Mexican Americans: the
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78
Chapter 4 The Interplay between Immigrants’ Country of Birth and
Neighbourhood Deprivation on Birth Outcomes
Abstract
Objectives: We compared the influence of the residential environment and of maternal country
of birth on the birthweight and low birthweight of infants born to recent immigrants to urban
Ontario.
Methods: We linked delivery records (1993-2000) to an immigration database (1993-1995) and
small-area census data (1996). The data were analyzed using cross-classified random effects
models (CCREM) and standard multilevel methods. Higher-level predictors included four
independent measures of neighbourhood context constructed using factor analysis, and maternal
world regions of origin.
Results: Births (N=22,189) were distributed across 1,396 census tracts and 155 countries of
origin. The associations between neighbourhood indices and birthweight disappeared after
controlling for the maternal country of birth in a cross-classified multilevel model. Significant
associations between world regions and birthweight and low birthweight persisted after
controlling for the neighbourhood context and individual characteristics.
Conclusions: Residential environment has little, if any, influence on birthweight among recent
immigrants to Ontario. Regarding low birthweight, the origin of recent immigrants is more
important than where they currently live. Caution should be exercised when interpreting findings
of neighbourhood influences on perinatal outcomes among recent immigrants.
79
4.1. Introduction
Socioeconomic disparities in birth outcomes are well documented,1-3 even in countries with
universal access to health care 4-6 such as Canada. There is also an increasing body of literature
suggesting that context affects birth outcomes, particularly neighbourhood influences in
predominantly urban areas, including several multilevel studies.7-18
Little is known, however, about neighbourhood influences among immigrants.12,19-21 There are
theoretical and practical reasons to explore this issue. It has been suggested that exposure to
neighbourhoods may take some time to exert its effects on human health.22 Even if
neighbourhood influences are detected among the offspring of recent-immigrant women exposed
to neighbourhoods during their entire pregnancy, a life-course perspective suggests that early life
experiences and pre-migration exposures may still affect birth outcomes of migrants in the new
country.19,22,23 The maternal country of birth thus constitutes another relevant “context” to be
considered when analyzing differences in birthweight among recent immigrants, since
substantial differences in birthweight have been reported by geographical region and nativity
status.24-26 It is important to clarify the role of the pre- and post-migration exposures, since the
proportion of live births to immigrant women has been showing an upward trend during recent
decades in several industrialized countries.24,27
The purpose of our study is to compare the influence of the residential environment at the time of
delivery, with that of the maternal country of birth, on the birthweight and low birthweight of
infants born to recent immigrant women who settled in Ontario census metropolitan areas from
1993 to 1995. We hypothesized that the maternal country of birth will have a greater impact on
their infant’s birthweight than the residential environment in which immigrants currently reside
in urban Ontario.
80
4.2. Methods
4.2.1. Data
Anonymized birth and maternal obstetric records from all Ontario hospitals were extracted from
hospital discharge abstracts compiled by the Canadian Institute for Health Information (1993-
2000). These data were internally merged to combine maternal and newborn records using an
algorithm described elsewhere,28 resulting in a 95 percent valid match of the newborn records to
a mother. Encrypted health care numbers of the Ontario Health Insurance Plan, which provides
universal access to nearly all physician and hospital services (except for asylum-seekers and
before three months’ residence), were used to link birth data with the Landed Immigrant Data
System (LIDS) (1993-1995), compiled by Citizenship and Immigration Canada. The LIDS
contains sociodemographic information and characteristics related to the immigration process.
These data were finally merged with small area data from the 1996 Canadian census.
We selected a group of women immigrating to Ontario’s census metropolitan areas from January
1, 1993 to March 31, 1995 who had at least one live singleton weighing more than 500 grams
and less than 6,000 grams (N= 38,121). We restricted the study population to infants born to
recent immigrant mothers, defined as residents with less than five years of stay.29,30 We slightly
modified this definition by shifting the five year observation period to begin after the 40th week
of the mothers’ arrival, to ensure that all mothers had been exposed to Canadian neighbourhoods
during their entire pregnancy (N=29,625). We only retained the first Canadian singleton born
alive of each woman within the five-year period (N= 22,516). The study population used for
analyses consisted of 22,189 live singleton infants born to women who immigrated to the
Ontario census metropolitan areas from January 1993 to March 1995, after excluding births to
mothers aged less than 15 years and more than 55 years (N=5), with atypical immigrant class
81
(N=62), coming from countries that could not be classified according to their socioeconomic
conditions (N=180) and records with missing information on place of residence (N=80).
Mothers born in one of 155 countries were distributed across 1,396 census tracts from ten 1996
Ontario Census Metropolitan Areas.31 Census tracts (our neighbourhoods) are relatively stable
urban neighbourhoods with a typical population of 2,500 to 8,000 and are relatively
homogeneous with respect to population characteristics and living conditions.31 Use of these data
was approved within the ethical review process of the Sunnybrook Health Sciences Centre,
Toronto, Ontario.
4.2.2. Outcomes
Birthweight was modeled as a continuous response variable (measured in grams). Use of
birthweight as a continuous outcome has several advantages. Birthweight is measured with high
precision, and provides directly interpretable effect estimates (differences expressed in grams)
and greater statistical power relative to categorical outcomes. We also modeled low birthweight,
as a binary outcome (proportion of births weighting less than 2,500 grams). It has been argued
that birthweight is a more meaningful perinatal outcome (i.e., proxy for fetal growth) if restricted
to term births, since the mean is not affected by the residual distribution (i.e., left-tale of the
birthweight distribution, mainly composed of preterm infants). 32 We did include all births
because the focus of this paper is not on fetal growth and the use of the same outcome definition
ensures comparability of our findings with those already published in the literature of
neighbourhood and contextual effects on perinatal health. 3,7,8,13,14,17,21 Birthweight (and low
birthweight) are sensitive to environmental influences and these influences are the focus of this
paper. Sensitivity analyses using birthweight at term and preterm birth did not alter the main
findings (not shown).
82
4.2.3. Predictors
Table 4.1 presents the predictors at each level of the hierarchical structure of the data. To obtain
groups of countries as homogeneous as possible in terms of their socioeconomic conditions, we
considered world region and the income-level of the country of birth. Both variables are based on
the World Bank classification of world economies 2000,33 in which countries are classified
according to their gross national income (GNI) per capita, using the World Bank Atlas method.
We modified the World Bank sub-region classification by separating the United States from the
remaining countries of the Americas. The group with the highest mean birthweight (East
Europe/Central Asia) was used as the referent.
We used more than one indicator of neighbourhood context based on the literature linking
neighbourhood stressors and poor health.14,34-37 In order to capture the complexity of the
neighbourhood environment, four independent measures were obtained by factor-analyzing
census variables; this had the added benefit of avoiding problems of multicollinearity, since the
principal components are not correlated. The neighbourhood indices are material deprivation
(Cronbach’s alpha 0.88), residential instability (Cronbach’s alpha 0.93), dependency
(Cronbach’s alpha 0.72) and ethnic diversity (Cronbach’s alpha 0.93). All four indices are
standardized continuous scores for modeling purposes. They are collapsed into tertiles for
descriptive purposes in Table 4.1. Details of how these measures were constructed and their
statistical properties are given elsewhere.38
At the individual level we considered established predictors of birthweight available in our data,
and some circumstances of the immigration process that may operate as potential confounders.
We considered: infant sex (male as referent), maternal age (15-19, 20-24, 25-29, 30-34 as
referent, and 35-55 years), maternal education groups (0-9, 10-12 years, some post-secondary
83
non-university diploma, and university diploma as referent), and marital status (married as
referent, single/widowed/separated). Gestational age in weeks was not available in the discharge
records for the study period. We approximated gestational age using gestational age groups (less
than 28, 28-36, 37-41 as referent and 42 and more weeks), based on the International
Classification of Diseases codes (ninth revision).39 Circumstances of immigration that have been
linked to birth outcomes and may vary by maternal country of birth include immigrant class
(economic class, family class, with refugees as referent) 40,41 and self-reported knowledge of any
official Canadian language (English or French) (”yes” as referent). 42,43 Length of residence in
Canada after the beginning of the observation period (0 to 4 completed years) was used to assess
the amount of exposure to a Canadian setting. 29,44,45
4.2.4. Statistical analyses
Commonly used multilevel models cannot be used when the data do not present a purely nested
structure. Immigrant mothers living in a particular neighbourhood may have come from several
different countries, and mothers coming from a particular country may settle in different
neighbourhoods. Thus, this data structure presents a cross-classification of countries and
neighbourhoods. Raudenbush and Bryk developed an extension of the multilevel model to
analyze such data, known as the crossed-classified random effects model (CCREM). 46,47 (see
Appendix 4.A for technical details) According to guidelines based on simulation studies, the
number of units at each level of our data structure is sufficient to obtain unbiased and precise
regression coefficients, variance components and standard errors. 48,49
84
4.2.5. Modeling strategy
Prior to developing the cross-classified model we conducted preliminary analyses focusing on
one level at a time 50 to assess whether there was significant variation at each level separately.
We first used the usual two-level random intercept model with births as level-1 units and with
neighbourhood as level-2 units. In a second model countries were the level-2 units. The presence
of statistically significant variance for each of these models warrants the use of the cross-
classified model to assess whether the variations in the outcome at each level are independent (in
which case further modeling is based on the CCREM) or are associated (if one factor is
confounded by the other, rendering a variance non-significant, further modeling may be reduced
to the usual two-level model). Then we proceeded to sequentially fit models adjusted for
individual-level characteristics and group-level characteristics. We also tested for cross-level
interactions to see whether the effect of neighbourhood-level variables differed by maternal
country of birth but none were statistically significant.
The MIXED procedure in SAS 9.1 for UNIX was used to fit models using the continuous
measure of birthweight and PROC GLIMMIX was used to model low birthweight (SAS Institute
Inc., Cary, NC). Variance components estimates are reported with their standard errors and p-
values. The proportion of variance explained at each level was calculated with the intra-class
correlation coefficient (ICC). 46-49 Wald tests were used to test for significant variances in low
birthweight. 48 Fixed effects in birthweight are reported as differences in mean birthweight
expressed in grams; fixed effects in low birthweight are reported as adjusted odds ratios (OR)
with 95 percent confidence intervals (95% CI).
85
Table 4.1. Characteristics of the study population by geography, mean infant’s birthweight and low
birthweight among recent immigrant mothers to urban Ontario.
Countries
Census
tracts Births BW
Low BW
N (%) N (%) N (%) Mean 95% CI % 95% CI
Total 155 (100) 1396 (100) 22189 (100) 3288 (3281, 3295) 5.7 (5.4, 6.0)
Country-level characteristics World regions East Europe / Central Asia 25 (16.1) 730 (52.3) 2188 (9.9) 3497 (3475, 3520) 2.9 (2.2, 3.6) Rest of Europe 22 (14.2) 589 (42.2) 1022 (4.6) 3421 (3390, 3453) 3.8 (2.7, 5.0) United States 1 ( 0.6) 319 (22.9) 411 (1.8) 3463 (3413, 3513) 2.4 (0.9, 3.9) Latin America & Caribbean 32 (20.6) 829 (59.4) 3467 (15.6) 3265 (3245, 3285) 7.4 (6.5, 8.3) East Asia / Pacific 18 (11.6) 995 (71.3) 5880 (26.5) 3237 (3225, 3250) 5.4 (4.8, 5.9) South Asia 6 ( 3.9) 793 (56.8) 5960 (26.9) 3207 (3194, 3220) 7.0 (6.3, 7.6) Middle East 12 ( 7.7) 516 (37.0) 1285 (5.8) 3359 (3332, 3385) 3.7 (2.7, 4.8) North Africa 7 ( 4.5) 160 (11.5) 202 (0.9) 3435 (3364, 3505) 3.5 (0.9, 6.0) East/South Africa 19 (12.3) 466 (33.4) 1328 (6.0) 3367 (3336, 3397) 4.8 (3.8, 6.0) West Africa 13 ( 8.4) 202 (14.5) 446 (2.0) 3220 (3158, 3282) 9.2 (6.5, 11.9) <0.001a <0.001b Country income level Low Income 47 (30.3) 978 (70.1) 6691 (30.2) 3234 (3221, 3246) 6.4 (5.8, 7.0) Lower Middle Income 43 (27.7) 1146 (82.1) 10308 (46.5) 3293 (3283, 3304) 5.9 (5.4, 6.4) Upper Middle Income 31 (20.0) 874 (62.6) 2614 (11.8) 3348 (3327, 3369) 4.6 (3.8, 5.4) High Income non-OECD 10 ( 6.5) 361 (25.9) 1153 (5.2) 3256 (3229, 3283) 4.5 (3.3, 5.7) High Income (OECD) 24 (15.5) 778 (55.7) 1423 (6.4) 3418 (3392, 3445) 3.4 (2.4, 4.3) <0.001c <0.001d Neighbourhood-level characteristics
Material deprivation tertiles 1 Lowest 140 (90.3) 740 (53.0) 7336 (33.1) 3296 (3284, 3308) 5.1 (4.6, 5.6) 2 142 (91.6) 401 (28.7) 7413 (33.4) 3298 (3286, 3311) 5.6 (5.1, 6.1) 3 Highest 126 (81.3) 255 (18.3) 7440 (33.5) 3270 (3257, 3282) 6.4 (5.8, 6.9) 0.003c <0.001d Residential instability tertiles 1 Lowest 136 (87.7) 610 (43.7) 7387 (33.3) 3268 (3257, 3280) 5.6 (5.1, 6.1) 2 139 (89.7) 430 (30.8) 7358 (33.2) 3294 (3281, 3306) 6.0 (5.5, 6.6) 3 Highest 142 (91.6) 356 (25.5) 7444 (33.5) 3302 (3289, 3314) 5.4 (4.9, 5.9) <0.001c 0.586d Dependency tertiles 1 Lowest 144 (92.9) 464 (33.3) 7382 (33.3) 3305 (3293, 3318) 5.5 (5.0, 6.1) 2 137 (88.4) 401 (28.7) 7373 (33.2) 3271 (3259, 3284) 5.9 (5.3, 6.4) 3 Highest 135 (87.1) 531 (38.0) 7434 (33.5) 3287 (3275, 3299) 5.6 (5.1, 6.1) 0.038c 0.914d Ethnic diversity tertiles 1 Lowest 143 (92.3) 864 (61.9) 7367 (33.2) 3316 (3304, 3328) 5.1 (4.6, 5.6) 2 137 (88.4) 336 (24.1) 7405 (33.4) 3280 (3267, 3292) 6.0 (5.4, 6.5) 3 Highest 131 (84.5) 196 (14.0) 7417 (33.4) 3268 (3256, 3280) 5.9 (5.4, 6.5) <0.001c 0.027d Individual-level characteristics
Infant sex Male 11357 (51.1) 3337 (3327, 3347) 5.4 (4.9, 5.8) Female
10832 (49.9) 3236 (3227, 3246) 6.0 (5.5, 6.4)
Gestational age (completed weeks)
< 28 98 (0.4) 842 (779, 906) 99.0 (99.0, 100.0) 28-36 1016 (4.6) 2353 (2319, 2386) 62.5 (59.5, 65.5) 37-41 20949 (94.4) 3344 (3337, 3350) 2.5 (2.3, 2.7) ≥ 42 126 ( 0.6) 3494 (3407, 3581) 0.8 (0.0, 4.3) <0.001c <0.001d Maternal age group (years) 15-19 461 (2.1) 3188 (3139, 3237) 7.4 (5.0, 9.8) 20-24 3770 (17.0) 3221 (3205, 3237) 6.4 (5.6, 7.2) 25-29 7266 (32.7) 3289 (3277, 3301) 5.1 (4.6, 5.6) 30-34 6903 (31.1) 3323 (3310, 3336) 5.3 (4.8, 5.8) 35-54 3789 (17.1) 3301 (3283, 3320) 6.4 (5.7, 7.2) <0.001a 0.002b Maternal education 0 to 9 years of schooling 4100 (18.5) 3259 (3243, 3275) 6.3 (5.6, 7.1) 10 to 12 years of schooling 8339 (37.6) 3264 (3253, 3276) 6.2 (5.7, 6.7) Post-secondary non-university diploma
6152 (27.7) 3319 (3306, 3332) 5.0 (4.5, 5.6)
University diploma
3598 (16.2) 3323 (3305, 3340) 4.8 (4.1, 5.5)
86
Countries
Census
tracts Births BW
Low BW
N (%) N (%) N (%) Mean 95% CI % 95% CI
Marital status Married/common law 13764 (62.0) 3312 (3303, 3321) 5.3 (4.9, 5.7) Single/divorced/separated 8425 (38.0) 3248 (3237, 3260) 6.3 (5.8, 6.8) <0.001a 0.001b Immigrant class Economic class 4965 (22.4) 3325 (3310, 3341) 5.6 (5.0, 6.2) Family class 14137 (63.7) 3257 (3248, 3265) 5.9 (5.5, 6.3) Refugees 3087 (13.9) 3371 (3352, 3391) 4.9 (4.1, 5.6) <0.001a 0.09b Knowledge of English or French
Yes 13186 (59.4) 3302 (3293, 3312) 5.8 (5.4, 6.2) No 9003 (40.4) 3267 (3257, 3278) 5.5 (5.0, 5.9) <0.001a 0.29b Length of residence (completed years)
0 7734 (34.9) 3278 (3266, 3290) 5.4 (4.9, 5.9) 1 5028 (22.7) 3282 (3267, 3297) 6.0 (5.3, 6.6) 2 3949 (17.8) 3306 (3289, 3322) 5.1 (4.5, 5.8) 3 3016 (13.6) 3285 (3266, 3306) 6.2 (5.4, 7.1) 4 2462 (11.1) 3304 (3282, 3326) 6.1 (5.2, 7.0) 0.019c 0.148d
a p-value of analysis of variance used for comparison of means b p-value of Chi-Square test for comparison of proportions c p-value of linear-trend across means d p-value of the Cochran-Armitage test for trend for proportions
4.3. Results
The largest share of births was among women from Asian countries, followed by immigrants
from Latin American and Caribbean countries (Table 4.1). There were significant differences in
birthweight according to world regions and to the income level of the mother’s country of birth.
Differences in birthweight by neighbourhood tertiles were not very pronounced. Material
deprivation was the only neighbourhood characteristic showing a gradient in low birthweight in
the expected direction, such that higher material deprivation was associated with lower
birthweight.
At the individual-level, heavier birthweight was found for males and in infants with higher
gestational age (Table 4.1). Maternal characteristics associated with higher birthweight include:
increasing age up to 30-34 years although this differs for low birthweight, having a university
87
diploma, being married, being a refugee, having knowledge of English or French (although this
is reversed for low birthweight), and having spent more time in Canada although this differs for
low birthweight.
Table 4.2. Fixed effects (and 95% CI) of the neighbourhood indices on infant’s birthweight (in grams) and
random effects (and standard errors) among recent immigrants to urban Ontario.
Two level models with random neighbourhood variance Cross-classified models with random neighbourhood and
country of birth variances
Model 1: with
Neighbourhood predictors
Model 2: adjusted for
individual characteristics c
Model 3: with
Neighbourhood predictors
Model 4: adjusted for
individual characteristics c
Fixed effects beta (95% CI) beta (95% CI) beta (95% CI) beta (95% CI)
Intercept 3321 (3311, 3332) 3531 (3505, 3557) 3364 (3337, 3390) 3523 (3489, 3558)
Material deprivation -10 (-21, 1) 1 (-8, 10) -8 (-18, 2) -2 (-11, 7)
Residential instability 20 (10, 29) 12 (3, 20) 0 (-9, 9) -1 (-9, 7)
Dependency -14 (-24, -3) -9 (-18, 0) -8 (-18, 2) -7 (-15, 2)
Ethnic diversity -25 (-34, -17) -23 (-30, -16) -4 (-12, 4) -4 (-10, 3)
Random effects Variance
Standard
Error Variance
Standard
Error Variance
Standard
Error Variance
Standard
Error
: Variance at the
neighbourhood level 2022 b 571 1320 a 431 215 399 255 304
: Variance at the
country level 13737 b 2596 10400 b 1995
: Residual variance 283014 b 2724 208223 b 2007 272954 b 2626 201375 b 1939
a p< 0.01; b p<0.001 c Adjusted for infant sex, maternal age groups, gestational age groups, maternal education groups, immigrant class, marital status,
knowledge of English or French, length of residence in Canada.
Table 4.2 shows the results of the multilevel models assessing neighbourhood effects on
birthweight, before (Models 1 and 2) and after including the country-of-origin context (Models 3
and 4). Model 1 and 2 represent the usual two-level model with births nested within
neighbourhoods. Model 1 included the four neighbourhood factors, which were significant, with
88
the exception of the material deprivation score. All four neighbourhood factors explained 42
percent of the variability found across neighbourhoods. When individual characteristics were
included in Model 2 significant variability between neighbourhoods remained.
Models 3 and 4 show the results of the cross-classified models. They differ from Models 1 and 2
by including an additional random variance component at the country-level. The addition of the
country-level context in Model 3 rendered both the neighbourhood-level variance and all the
neighbourhood indices non-significant. The country-level variance, however, remained highly
significant even after adjusting for individual characteristics in Model 4. In this model, the
partition of the variance indicates that 4.9 percent of the total variance in birthweight occurred at
the country level and only 0.12 percent at the neighbourhood level. Collapsing the
neighbourhood indices into tertiles did not improve the fit of the model (data not shown) and
therefore we kept the continuous specification of the neighbourhood indices. Models adjusted for
individual characteristics show higher infant mean birthweight because most reference categories
are those associated with higher birthweight, such as being male infants born within 37-41
completed weeks of gestation, and born to married mothers with high maternal age and
education.
In order to understand why the variability in birthweight at the neighbourhood-level disappeared
after controlling for country of birth, we tested the hypothesis that the pattern of settlement of
recent immigrants was not random, by cross tabulating material deprivation tertiles of births with
world regions (Figure 4.1). The Chi-Square test was highly significant (χ2(df=18)=1,052,
p<0.0001), indicating that newly arrived immigrant women from particular regions of the world
did not settle randomly across urban neighbourhoods. Women coming from poorer regions of the
world settled in neighbourhoods characterized by higher material deprivation (e.g., African and
89
Latin American countries, and to a lesser extent South Asia) whereas women coming from richer
regions tended to concentrate in less deprived neighbourhoods (e.g., United States, non-Eastern
Europe, and East Asia and Pacific to a lesser extent). The neighbourhood-level variance and
predictors were no longer significant in the cross-classified models; the model then reduced to a
usual two-level model, with births nested within countries of origin.
Figure 4.1. Distribution of births by neighbourhood material deprivation tertiles in each world sub-region
Table 4.3 shows the results of the two-level model including world regions as the only country-
level predictor (Model 5), since income levels of the country of birth were no longer significant
after including world regions. The ICC indicates that 46.7 percent of the variance at the country
level was explained by grouping the countries into world regions. Significant differences in
90
birthweight between world regions persisted after controlling for individual characteristics in
Model 6, as did the unexplained variability at the country-level. Most world regions had lower
mean birthweight than East Europe/Central Asia, except the United States and North Africa,
probably due to low statistical power as a result of very few countries in these world regions.
Table 4.3. Fixed effects (and 95% CI) of world regions on infant’s birthweight (in grams) among recent
immigrants to urban Ontario.
Model 5: Unadjusted for
individual characteristics
Model 6: Adjusted for
individual characteristics a
World regions beta (95% CI) beta (95% CI)
East Europe / Central Asia referent referent
Rest of Europe -73 (-153, 7) -76 (-143, -9)
U.S.A. -42 (-229, 145) -47 (-200, 105)
Latin America & Caribbean -150 (-220, -80) -133 (-192, -75)
East Asia / Pacific -246 (-323, -169) -238 (-302, -174 )
South Asia -281(-377, -184 ) -241 (-320, -162)
Middle East -168 (-257, -79) -157 (-230, -83)
North Africa -83 (-207, 41) -89 (-192, 15)
East/South Africa -236 (-322, -151) -206 (-278, -135)
West Africa -226 (-350, -102 ) -195 (-298, -91)
a Adjusted for infant sex, maternal age groups, maternal education groups, gestational age groups, immigrant class,
marital status, knowledge of English or French, length of residence in Canada.
The results for low birthweight differed in the significance of the variance at the neighbourhood
level (Table 4.3). Unlike birthweight, there was no significant variability in low birthweight in
the two-level model with births nested within neighbourhoods ( = 0.01, standard error=0.03,
p > 0.05 one-sided) or in the cross-classified model considering both the neighbourhood and
country-level contexts. None of the neighbourhood indices were significantly associated with
91
low birthweight in either of these two models. We therefore dropped the neighbourhood context
and continued the modeling of low birthweight considering the country context only. Variability
in low birthweight at the country-level, in contrast, was significant in the two-level model with
births nested within countries and also in the cross-classified model ( = 0.20, standard
error=0.06, p < 0.001 one-sided). It remained significant after controlling for individual-level
covariates ( = 0.15, standard error=0.05, p < 0.01 one-sided), although the variance was
somewhat reduced.
Table 4.4. Odds ratios (and 95% CI) of world regions on infant’s Low Birthweight among recent
immigrants to urban Ontario.
World regions Odds ratio (95% CI) a
East Europe / Central Asia 1.00
Rest of Europe 1.59 (0.88, 2.86)
U.S.A. 0.87 (0.31, 2.43)
Latin America & Caribbean 2.15 (1.34, 3.45)
East Asia / Pacific 1.96 (1.21, 3.18)
South Asia 2.80 (1.67, 4.68)
Middle East 1.81 (1.02, 3.22)
North Africa 1.38 (0.49, 3.84)
East/South Africa 2.08 (1.17, 3.67)
West Africa 2.22 (1.01, 4.85) a Adjusted for infant sex, maternal age groups, maternal education groups, gestational age groups, immigrant class, marital status,
knowledge of English or French, length of residence in Canada.
The full model (Table 4.4) including all individual characteristics and world regions rendered the
country-level variance non significant ( = 0.07, standard error = 0.05, p > 0.05 one-sided),
implying that after grouping countries into regions there was no further variability to be
explained at the country-level. Fixed effect estimates resemble the pattern found for birthweight.
92
The risk of low birthweight varied considerably according to the region of origin of the
immigrant mothers.
4.4. Discussion
In a study population of recent immigrant women to urban Ontario, we found that the
neighbourhood context had little, if any, impact on birthweight and low birthweight.
Neighbourhood influences on birthweight disappeared after controlling for the mother’s country
of birth, suggesting that self-selection of recent immigrants from various world regions into
particular neighbourhoods explains the observed associations between neighbourhood
characteristics and birthweight. By contrast, we found important contextual effects at the
maternal country of birth level for both birthweight and low birthweight, after adjusting for
individual characteristics. Compared to migrants from East Europe/ Central Asia, migrants from
other world regions had worse outcomes, with the exception of North Africa, the United States
and Western Europe. Low rates of preterm birth (< 37 weeks of gestation) and low birthweight
have already been documented among North African migrants to Belgium 51-54 and France.55 US-
migrants to Ontario presented lower rates of singleton low birthweight than the US-born non-
Hispanic Whites in the US in a comparable period, 56 suggesting that US-migrants to Ontario
constitute a healthier group than their non-migrant counterparts.
Among the strengths of this study we highlight that this is a population-based study with almost
complete coverage of the target population. Selection bias is not an issue since almost all Ontario
permanent residents are insured by the provincial health plan. Unlike in many studies,
immigration status, country of birth, and other maternal characteristics were not self-reported but
93
ascertained through the governmental computerized immigration database, which is quite
accurate and complete because of its associated legal requirement for notarized copies of the
personal documentation of the principal applicant and family members. The use of an
appropriate statistical method that allows simultaneous consideration of the role of two relevant
contexts strengthens our conclusions.
This study has some limitations. Imperfect measurement of some individual control variables
may have introduced some residual confounding. Maternal education and marital status were
measured at arrival but could have changed for some women during the study period; however
the relatively short period of time from arrival to delivery makes it improbable that substantial
shifts in educational attainment were experienced by many women before delivering their first
Canadian-born child. Information on parity was not available in hospital records for the study
period. We reduced confounding for parity, however, by selecting only the first Canadian-infant
born of each mother, although many women may already have had prior babies. We do not have
reason to believe that parity would differ systematically according to the country of birth, with
the possible exception of immigrants from China where having more than one child is penalized.
Finally, we did not control for behavioural risk factors and maternal morbidity during pregnancy
because they are conceptualized as mediators in the relationship between socioeconomic factors
and birth outcomes.1,57,58
Neighbourhood context was assessed at the time of delivery but some of the mothers may have
been exposed to more than one neighbourhood within the study period, the probability being
higher for those mothers who took longer to have their first Canadian-born infant. A lack of
information about the residential trajectory of the mothers prevented us from assessing the extent
of this bias. Residential mobility is a complex phenomenon that may be influenced by individual
94
and neighbourhood characteristics and class relations, and vary by ethnic group, nativity status
and length of residence. 59-61 It is unlikely, however, that residential mobility would have
introduced serious bias since our study population was restricted to recent immigrants, with short
length of stay. Moreover, a recent study did not find substantial differences between longitudinal
and cross-sectional estimates of neighbourhood effects on children well-being, 60 suggesting that
most families moved between neighbourhoods of the same socioeconomic type, which is
consistent with the research of South and colleagues 61 on inter-neighbourhood socioeconomic
mobility.
We used four independent indices of neighbourhood context, based on census data that
essentially reflect aggregated characteristics of the population, but did not use measures based on
other data sources that may have provided information about other aspects of the residential
milieu. In Canada, census tract boundaries have been found to correspond well to those of
‘natural’ neighbourhoods. 62 Several Canadian studies have found significant area-level effects
using this geographic unit of analysis with a broad array of outcomes, 38,63-66 including birth
outcomes. 28,67
We did not expect higher birthweight among refugees, compared with non-refugee immigrants,
since they usually emigrate from high-stressed environments, which could lead to adverse birth
outcomes. The birthweight advantage of refugees was reduced in the adjusted models but it
remained significant, implying a role of unmeasured factors. Studies comparing obstetric
outcomes of refugees and asylum-seekers from Somalia and Kosovo-Albania with those of UK-
born and US-born White women did not find significant differences, 41,68,69 probably due to small
sample sizes.
95
We also found that the trend for birth weight increased with length of residence, even after
adjustment. Although the reasons for this finding in Ontario are not clear, previous research
suggests that birth outcomes may either improve or deteriorate with length of residence among
first generation immigrants, depending on the migrant group and/or the receiving environment.
For instance, the risk of preterm birth and low-birthweight increased with length of residence
among Mexican migrants to the U.S. 29,44 and Asians and Pacific Islanders in Sweden but
decreased among Finns, 45 while other migrant groups were unaffected.
Our finding regarding the absence of significant neighbourhood effects on birthweight among
immigrants is not surprising given the inconsistent associations with measures of socioeconomic
position found among diversely ethnic immigrant groups to the United States. 19,21,56,70,71 The
finding of important country-level effects is consistent with a literature reporting wide variability
in pregnancy outcomes by world region, country and ethnic groups.26,71 Although our findings
are consistent with a recent study in which the association between residential segregation and
low birthweight disappeared after controlling for nativity among immigrant Black women to
New York City,12 generalization to North American cities with little ethnic and nativity diversity
may be limited.
Figure 4.2 displays a simplified causal diagram conceptualizing the interplay of country of birth
and neighbourhood deprivation on birthweight. (Appendix 3.D for a more complex causal
diagram) Self-selection of immigrants to neighbourhoods according to their countries of origin
creates a modest spurious association between neighbourhood deprivation and birthweight,
which is removed by controlling by country of birth. The corollary is that if we are interested in
the independent association between neighbourhood deprivation and birthweight then we should
control for country of birth. But if our analytic goal is to assess the total association between
96
immigration/country of birth and birthweight then we should not control for neighbourhood
context. It is important to remember that the diagram conceptualizes what happens among recent
immigrants, but it may not be valid for immigrants with longer stay in Canada.
Figure 4.2: Confounding by self-selection of recent immigrants to neighbourhoods
Our findings are also consistent with three-level studies that showed significant reductions in the
amount of variability attributable to the neighbourhood context, after taking account of an
additional context such as the family or household. 72-74 Such evidence suggests that two-level
studies of neighbourhood effects may overestimate the contribution of the residential
environment if they disregard other contexts potentially relevant to the population and outcome
under study.
Interventions and policy recommendations at the neighbourhood level should be cautious if
based on studies that did not control for other meaningful contexts for the study population. We
did not find evidence that neighbourhoods matter for immigrants’ offsprings’ birthweight but this
cannot be generalized to other outcomes without further empirical research. These findings could
help to direct prenatal and even pre-conception programming towards recent immigrant women
97
from higher-risk countries of origin. While neighbourhood may not be a major exposure for low
birthweight in urban Ontario, it can provide a vehicle to reach out to women that are at particular
risk upon entry into Canada through facilitating local access to culturally sensitive prenatal care
and translation services.
Credits
This chapter represents a prepublication version of the following article:
Urquia ML, Frank JW, Glazier RH, Moineddin R, Matheson FI, Gagnon AJ. Neighborhood
context and infant birthweight among recent immigrant mothers: a multilevel analysis. Am J
Public Health. 2009 Feb;99(2):285-93.
98
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(72) Boyle MH, Lipman EL. Do places matter? Socioeconomic disadvantage and behavioral problems of
children in Canada. J Consult Clin Psychol. 2002;70(2):378-389.
(73) Chandola T, Clarke P, Wiggins RD, Bartley M. Who you live with and where you live: setting the context
for health using multiple membership multilevel models. J Epidemiol Community Health. 2005;59(2):170-
175.
(74) Sacker A, Wiggins RD, Bartley M. Time and place: putting individual health into context. A multilevel
analysis of the British household panel survey, 1991-2001. Health Place. 2006;12(3):279-290.
107
Chapter 5 The Differential Deterioration of Preterm Birth among urban
Immigrants by Neighbourhood Deprivation
Abstract
Socioeconomic gradients in birth outcomes seem to be ubiquitous but immigrants represent one
major exception to this pattern. Chapter 4 showed that neighbourhood context had no significant
influence on birthweight of recent immigrants, after adjusting for maternal country of birth.
However, those results are only valid among recent immigrants. The purpose of this chapter is to
examine the simultaneous contribution of the maternal country of birth and the neighbourhood
context on the preterm delivery of immigrants whose time from arrival in Canada to delivery
varied from 1 to 20 years. Using hierarchical models we examined whether neighbourhood
deprivation gradients in preterm birth were modified by duration of residence in Ontario urban
areas. There were no visible deprivation gradients among immigrants before 15 years of
residence. After 14 years, gradients for immigrants approached the gradients observed among
non-immigrants. Evaluation of neighbourhood influences among immigrants should pay close
attention to duration of residence.
108
5.1. Introduction
Socioeconomic gradients in birth outcomes are well documented. 1-4 Associations between low
SES and adverse birth outcomes can be observed through a wide range of measures, such as
individual income, education, occupation, or neighbourhood material deprivation and racial
segregation. However, immigrants represent one major exception to this pattern.5-12 Researchers
have elaborated some potential explanations to make sense of the inconsistent and even reversed
gradients found in various immigrant populations, such as Asian, Black, and Hispanic groups.
These include selective migration, low variability in socioeconomic status among immigrants,
and group-level attributes such as a protective cultural orientation.5,11,13
It is also possible that the lack of consistency of the socioeconomic gradients in birth outcomes
of migrants is affected by confounding by duration of residence in the receiving country. Recent
immigrants are more likely to be misclassified with respect to socioeconomic measures because
they experience a mismatch between their educational credentials and their initial insertion in the
labour market, and tend to settle in low-rental dwellings concentrated in poor
neighbourhoods,12,14 thus flattening the gradients. In contrast, measures of socioeconomic
position can be expected to be more consistent among long-term immigrants that have gone
through the adaptation process to the new physical and social environment and have reached a
relatively stable position in the new society. In addition, time would be needed for social
exposures, including neighbourhood deprivation, to exert its effects on health.15
We hypothesized that material deprivation gradients would tend to be more consistent with
increasing length of residence and examined whether the relation between neighbourhood
109
deprivation and preterm birth among immigrants to urban Ontario was modified by duration of
residence. We also compared immigrant gradients with those observed in the general population.
5.2. Methods
We extracted from the Discharge Abstract Database 397,470 singleton live births born to
mothers living in any of the 11 Ontario Census Metropolitan Areas16 at the time of delivery,
between April 1, 2002 and March 31, 2007, and with complete information on covariates. The
Landed Immigrant Data System (LIDS), which is the official immigration registry compiled by
Citizenship and Immigration Canada (CIC), was used to obtain sociodemographic and
immigration information of all legal immigrants that attained their permanent residence within
1995-2000, although some of them had temporary residence before, which is accounted for in
our measure of duration of residence defined as days from arrival to delivery. These data were
merged with small-area data (census tracts as neighbourhoods) from the 2001 Canadian census,
from which we constructed a material deprivation score17 with mean zero and standard deviation
one.
We first performed stratified analyses by duration groups, using a two-level model for non-
immigrants with births nested within neighbourhoods and cross-classified random effects models
(CCREM) for immigrants in order to account for the clustering within maternal countries of birth
and neighbourhoods. Details of this approach were given in Chapter 4.18 We calculated adjusted
odds ratios for the effect of one standard deviation of neighbourhood deprivation change on
preterm birth. We also used a 10% change in the population living below the Statistics Canada
low-income cut-off,19 for easier interpretation. Finally, we plotted predicted probabilities of
110
preterm birth based on a CCREM with all immigrants including an interaction term between
neighbourhood deprivation tertiles and duration of residence (p=0.0389).
5.3. Results
Table 5.1: Adjusted odds ratios (and 95% confidence intervals) of one Standard Deviation increase in the
material deprivation index and 10% increase in the population living below the low-income cut-off on
preterm birth, by immigrant status and duration of residence, urban Ontario, 2002-2007.
Births Coun
tries
Cens
us-
tracts
Country-level
Variance (SE)
Census-tract level
Variance (SE)
AOR per one SD
material
deprivation
(95% CI)
AOR per 10%
increase in
population below
LICO
(95% CI)
Non-
immigrants a 314,237 1 1801 0.019*** (0.004) 1.12 (1.10-1.14) 1.09 (1.07-1.11)
Immigrants by
duration b
<5 years
14,555 148 1472 0.125*
(0.067) 0.029 (0.061)
0.96 (0.89-1.03) 0.94 (0.88-1.00)
5-9 years 32,539 162 1649 0.101**
(0.040) 0.015 (0.019)
1.03 (0.99-1.08) 1.02 (0.98-1.07)
10-14 years
23,827 161 1622 0.045* (0.023) 0.009 (0.022) 1.01 (0.96-1.06) 1.01 (0.96-1.05)
≥ 15 years 12,312 133 1523 0.008 (0.022) 0.125** (0.054)
1.09 (1.02-1.17) 1.06 (1.00-1.13)
a based on a two-level model adjusted for infant sex, maternal age and parity. b based on a cross-classified model adjusted for infant sex, maternal age, parity, immigrant class, language knowledge, high school
graduation, maternal world region of birth, and unmarried status.
* p<0.05 ; ** p<0.01 ; *** p<0.001 (p-values for variances are one-sided)
Immigrants approached the association between the neighbourhood measures and preterm birth
observed in the general population after 15 years of stay (Table 5.1). The clustering of births to
immigrants, assessed by the neighbourhood variance, only reached statistical significance among
those with 15 or more years of residence, even after adjustment. It is noteworthy that among
111
these long-term immigrants, the variance for country of birth was no longer statistically
significant; implying that for this group, the neighbourhood context was more relevant. In other
words, country of birth is a good predictor of preterm birth among immigrants up to 14 years of
stay in Ontario but not afterwards. Conversely, measures of neighbourhood context only can
predict preterm birth among immigrants with 15 or more years of residence.
Figure 5.1. Predicted probabilities of preterm birth (2002-2007) by duration of residence and
neighbourhood deprivation tertiles among immigrants to urban Ontario
The risk of preterm birth increased with duration of residence in a cumulative dose-response
pattern across all neighbourhood deprivation tertiles. However, the deterioration of preterm birth
was attenuated (less steep slope) among those immigrants living in the least deprived
neighbourhoods at the time of delivery. The flat lines represent the levels (tertiles) of preterm
birth observed in the non-immigrant population living in low- and highly-deprived
neighbourhoods. Recent immigrants had lower preterm birth than non-immigrants living in low-
112
deprivation neighbourhoods, irrespective of the type of neighbourhood they lived in but they lost
their advantage over time, the sequence being consistent with the deprivation gradient.
5.4. Discussion
Consistent with the results obtained in Chapter 4, neighbourhood measures are not good
predictors of birth outcomes among recent immigrants. However, these new findings suggest that
they become more predictive with increasing duration of residence.
As our neighbourhood measures were based on the mothers’ residence at the time of delivery
and many may have moved since arrival, our findings cannot be interpreted as resulting from
cumulative exposure to neighbourhood deprivation levels. Rather, the type of neighbourhoods in
which mothers lived in at delivery is conceptualized here as a marker of the socioeconomic
position achieved by that time.
Unlike Chapter 4 that is restricted to recent immigrants, this Chapter also compares the gradients
found among immigrants with those found in the majority population. Although the levels of
preterm birth among immigrants did not ‘converge’ with time spent in urban Ontario towards the
average observed in the non-immigrant population, as discussed in Chapter 3, the socioeconomic
gradient in preterm birth (i.e., the distance between tertiles 1 an 3) among immigrants
approximated the gradient observed in the majority population after 14 years of stay
approximately, this being consistent with a pattern of convergence.
Duration of residence can be considered a key dimension in studies of immigrants’ health.
113
5.5. References
(1) Grady SC. Racial disparities in low birthweight and the contribution of residential segregation: a multilevel
analysis. Soc Sci Med. 2006;63(12):3013-3029.
(2) Kramer MS, Seguin L, Lydon J, Goulet L. Socio-economic disparities in pregnancy outcome: why do the
poor fare so poorly? Paediatr Perinat Epidemiol. 2000;14(3):194-210.
(3) Krieger N, Chen JT, Waterman PD, Soobader MJ, Subramanian SV, Carson R. Choosing area based
socioeconomic measures to monitor social inequalities in low birth weight and childhood lead poisoning:
The Public Health Disparities Geocoding Project (US). J Epidemiol Community Health. 2003;57(3):186-
199.
(4) O'Campo P, Xue X, Wang MC, Caughy M. Neighbourhood risk factors for low birthweight in Baltimore: a
multilevel analysis. Am J Public Health. 1997;87(7):1113-1118.
(5) Acevedo-Garcia D, Soobader MJ, Berkman LF. The differential effect of foreign-born status on low birth
weight by race/ethnicity and education. Pediatrics. 2005;115(1):e20-e30.
(6) David RJ, Collins JW, Jr. Differing birth weight among infants of U.S.-born blacks, African-born blacks,
and U.S.-born whites.[see comment]. New England Journal of Medicine. 1997;337(17):1209-1214.
(7) Fang J, Madhavan S, Alderman MH. Low birth weight: race and maternal nativity-impact of community
income. Pediatrics. 1999;103(1):E5.
(8) Gould JB, Madan A, Qin C, Chavez G. Perinatal outcomes in two dissimilar immigrant populations in the
United States: a dual epidemiologic paradox. Pediatrics. 2003;111(6 Pt 1):e676-e682.
114
(9) Landale NS, Oropesa, Gorman BK. Immigration and infant health:birth outcomes of immigrant and native-
born women. Children of Immigrants: Health, Adjustment and Public Assistance. Washington, DC:
National Academy Press, 1999: 244-85.
(10) Madan A, Palaniappan L, Urizar G, Wang Y, Fortmann SP, Gould JB. Sociocultural factors that affect
pregnancy outcomes in two dissimilar immigrant groups in the United States. J Pediatr. 2006;148(3):341-
346.
(11) Pearl M, Braveman P, Abrams B. The relationship of neighbourhood socioeconomic characteristics to
birthweight among 5 ethnic groups in California. Am J Public Health. 2001;91(11):1808-1814.
(12) Urquia ML, Frank JW, Glazier RH, Moineddin R. Birth outcomes by neighbourhood income and recent
immigration in Toronto. Health Rep. 2007;18(4):1-10.
(13) Cervantes A, Keith L, Wyshak G. Adverse birth outcomes among native-born and immigrant women:
replicating national evidence regarding Mexicans at the local level. Matern Child Health J. 1999;3(2):99-
109.
(14) Galarneau D, Morissette R. Immigrants: Settling for Less? Perspectives on Labor and Income. 2004;5(6):5-
16.
(15) O'Campo P. Invited commentary: Advancing theory and methods for multilevel models of residential
neighbourhoods and health. Am J Epidemiol. 2003;157(1):9-13.
(16) Statistics Canada. Standard Geographical Classification (SGC). Volume I. The Classification. [Statistics
Canada]. 2007. Accessed December 12, 2008.
115
(17) Matheson FI, Moineddin R, Dunn JR, Creatore MI, Gozdyra P, Glazier RH. Urban neighbourhoods,
chronic stress, gender and depression. Soc Sci Med. 2006;63(10):2604-2616.
(18) Urquia ML, Frank JW, Glazier RH, Moineddin R, Matheson FI, Gagnon AJ. Neighbourhood Context and
Infant Birthweight Among Recent Immigrant Mothers: A Multilevel Analysis. Am J Pub Health.
2009;99(2):1-9.
(19) Statistics Canada. Low Income Cut-offs. [Statistics Canada]. 1999. Accessed December 11, 2008.
116
Chapter 6 Discussion
6.1. Main Findings
The pieces of work comprising this thesis indicate that:
a) Ethnicity, country of origin, and time since migration are important predictors of birth
outcomes among immigrants.
b) Duration of residence is linearly associated with increases in low birth weight and preterm
birth, mainly driven by decreases in gestational age with prolonged stay in Canada.
c) The detrimental effects of long duration of residence on preterm birth are modestly attenuated,
but not prevented, among immigrants living in urban neighbourhoods characterized by low
material deprivation.
d) Neighbourhood material deprivation has little, if any, influence on birth outcomes of recent
immigrants but the influence of neighbourhood deprivation becomes visible with longer stay in
Canada. Maternal world region of origin constitutes a stronger predictor among recent
immigrants.
117
6.2. Strengths and Limitations
Although the strengths and limitations have been discussed in each paper, it is convenient to
briefly highlight here the main ones, considering all the foregoing chapters in the context of the
broader literature.
One of the common strengths is that all analyses are based on relatively large sample sizes, in
most cases population-based.
Although it is virtually impossible to control for all relevant covariates, due to data limitations
and ignorance about what the relevant confounders are, the 95% confidence intervals of the
effect estimates obtained from these analyses partially account for unknown sources of
heterogeneity, since hierarchical models were used to account for the clustering of births within
studies and subgroups within studies in the meta-analyses (Chapter 2) and within
neighbourhoods and maternal countries of birth in the analyses using Ontario data (Chapters 3-
5).
Regarding the potential confounders with available data, selection of covariates was based on
causal diagram theory,1,2 which improves the likelihood of obtaining unbiased effect estimates
by avoiding improper control. However, the helpfulness of the causal diagrams depends on our
knowledge of what the potential confounders are, which is not exhaustive in this area of
research.
The Ontario birth and immigration data spanned several years to allow estimation of the effects
of duration of residence over 20 years since arrival, which has not been done before for birth
outcomes. Moreover, with the exception of knowledge of official languages, which was self-
reported, the remaining immigration data were collected through the documentation provided by
118
the immigrants during the Canadian-entry application process and last updated at the port of
entry on the landing date.
One common limitation in our analyses, as well as in the literature, is the use of data for legal
international migrants only. Temporary, internal, and illegal migration are not captured by the
Ontario immigration data, and is rarely and inconsistently recorded in birth certificates
worldwide, which represent the main data source of the studies included in the meta-analyses.
Finally, there is a generalized lack of information on emigrants of the receiving countries, who
represent another unmeasured influence shaping the health outcomes of the ‘native’ populations
(i.e., comparison groups).3
A second common limitation found in the literature is the heterogeneity in the definition of what
an immigrant is and its measurement. Different migrant labels have been used in the reviewed
literature, such as “foreign-born”, not always specifying the country of birth/origin, and
nationality.4 Although the Ontario immigrant data constitute an excellent source to identify
immigrants, the dataset used started with migrants landed in 1985. Therefore, immigrants landed
before 1985 were misclassified as non-immigrants thus slightly biasing the results towards the
null; “slightly” because immigrant women who arrived before 1985 were somewhat less likely to
deliver babies at least 17 years after arrival (2002-2007) and the proportion of babies born to
immigrant women decreases dramatically with such long duration of residence; “towards the
null” because duration of residence is associated with increased risk of low birthweight and
preterm birth and high-risk immigrant women with long duration of residence were counted as
part of the non-immigrant population, thus narrowing the differences between long-term
immigrants and non-immigrants.
119
A third common limitation is that although the outcomes analyzed in this thesis have been
widely used for surveillance, they are imperfect outcomes for etiologic research.5,6 Birthweight
differences by migrant subgroups generally focus on one parameter of the birthweight
distribution (i.e., mean birthweight), which may not be the most relevant for perinatal health.6
Despite the strong associations found between low birthweight and infant mortality, low
birthweight alone is ill-suited for etiologic studies, since it cannot discriminate between those
infants who are small because of being born preterm and those with growth restriction. In terms
of perinatal knowledge, the models of low birthweight do not provide significant additional
information beyond the information provided by the models of preterm birth and small for
gestational age (Chapter 3). However, the models of low birthweight were kept to allow
comparisons with the broader literature, which has mainly focused on that outcome. In addition,
and despite its acceptance, the 2,500 grams cut-off has been criticized for being arbitrary.6 This
same criticism can be applied to the 37 weeks cut-off defining preterm birth.7 Moreover, it has
been suggested that gestational age is in fact follow up time and should be better considered as
such in causal models rather than as an endpoint on its own.5 Finally, the measurement of intra-
uterine fetal growth still remains a challenge.8 Small for gestational age represents a proxy based
on cross sectional estimates (sex-specific birthweight percentiles by week of gestation) at birth
but does not accurately reflect the longitudinal process of fetal development over the gestation
period,6,8 which may vary across subpopulations (e.g., ethnic groups). The use of a Canadian-
based standard for small for gestational age may not be appropriate to assess disparities by
migration status, since differences between ethnic groups have been suggested to be more
physiological than pathological.9 Caution is therefore advised when interpreting the reported
differences in birthweight-related outcomes between migrant subgroups. Low birthweight,
preterm birth and small for gestational age are intermediate outcomes in perinatology that have
120
been associated with perinatal mortality, serious neonatal morbidity, and childhood disabilities.
Although perhaps more relevant, these endpoints were not chosen as the main outcomes of this
thesis because of data quality concerns and measurement issues. In addition, these are rare
outcomes that may have reduced the power to detect statistically significant differences for
various comparison groups, given our sample sizes.
Another limitation is that our main analyses assessing the influence of duration of residence on
birth outcomes (Chapters 3 and 5) were based on cross-sectional estimates. Although we
conducted sensitivity analyses on a cohort of immigrants who arrived during 1995-1998 and by
subsequent 4-year cohorts, yielding results consistent with the main analyses, we choose not to
report the cohort estimates as the main analyses because this approach suffered from other
weaknesses. These comprise: our inability to measure some relevant outcomes (very preterm
birth and small for gestational age); the use of different methods for ascertaining preterm birth
(ICD-9 codes from fiscal 1988/1989 to 2001/2002 and gestational age in weeks from 2002/2003
to 2006/2007); potential confounding by secular increases in preterm birth due to obstetric
practice and other unmeasured maternal characteristics;10,11 and the lack of information on parity
prior to fiscal 2002/2003.
Another limitation is that we could not provide satisfactory explanations of why preterm birth
increases with duration of residence among immigrants. The testing of some hypothetical
explanations as found in the literature, such as changes in health behaviours and job-related
exposures, requires data that were not available in the datasets used for this thesis. In particular,
the lack of information on maternal smoking and pre-pregnancy weight prevented the testing of
mediation by these factors when assessing the association between duration of residence and
preterm birth.
121
Generalization of findings is also difficult. Given the diversity of migrant groups, defined by
their country, region, and city of origin, ethnicity, religion, social class background, and of the
receiving environments, defined by their country, region, city, labour market and social
dynamics, it is virtually impossible to generalize the findings of this thesis and predict the
outcomes of immigrants in particular situations. Moreover, our findings may not be generalizable
to countries where access to health care is not universal (e.g., United Sates), thus introducing
another potential source of disparities. However, this thesis provides some insights that may help
health practitioners and policymakers avoid misleading approaches when focusing on immigrant
groups, and may help researchers design sounder studies to advance knowledge in this field.
6.3. Implications for practice and future research
The first insight from this work is that attention must be paid to the definition of migrant groups
and choice of comparison groups, when drawing conclusions about disparities by migrant status.
As shown in the literature review, a specific migrant group (e.g., Sub-Saharan Africans in the
US) can be easily labelled as ‘protected’ or ‘at high-risk’ merely by changing the referent group
from ‘US-born Blacks’ to ‘US-born Whites’. Thus, arbitrary manipulation of comparison groups
may result in contrasting conclusions. Moreover, as shown in Chapters 3 and 5, disparities by
migrant status are modified by duration of residence. Recent immigrants compare favourably to
non-immigrants but the opposite is true for long-term immigrants. Such differences may be
bigger when socioeconomic gradients are also considered. This leads us to a related issue.
The second insight from this work is that health studies of immigrants defined as a single
category are not informative. All chapters have shown substantial heterogeneity among
immigrants according to their world region of origin and duration of residence in the receiving
122
country, with specific migrant subgroups experiencing risks below and above the average, and
below and above the native-born. Grouping together all immigrants not only masks these
important heterogeneities, but also generates misleading statistics to inform policy and
interventions directed to particular migrant groups. Differences in birth outcomes between
immigrants from various regions of the world may be greater than differences found with
established predictors, such as maternal education, marital status, parity, or some pregnancy
complications. Duration of residence is especially important because immigrants can be seen as a
cohort exposed to a new environment starting on arrival. Although duration of residence can be
conceptualized as a marker for other exposures (e.g., acculturation), it remains of interest in itself
because it measures time of exposure to the new environment (i.e., follow-up time). Therefore,
both country of birth/origin and duration of residence have been found to be key predictors of
birth outcomes among immigrants. These two predictors should be considered in future studies
and also for surveillance, whenever feasible. Prenatal and women’s health programs would also
benefit from separate clinical management of those migrant subgroups at higher risk of adverse
birth outcomes: long-term immigrants (particularly those living in poor neighbourhoods), and
immigrants from South Asia, Sub-Saharan Africa, and Latin America and Caribbean.
The association between duration of residence and preterm birth might have important
implications for public health. Preterm birth has been considered to be a determinant of other
adverse health outcomes in the perinatal period (e.g., acute neonatal illness, perinatal
mortality)12, and long-term consequences.13 Preterm survivors are at higher risk of
neurodevelopmental disabilities that in turn make them more prone to develop language
disorders, learning disabilities, attention deficit-hyperactivity disorder, and behavioural
problems. Preterm infants have lower intelligence quotients and academic achievement scores,
experience greater difficulties at school, and require significantly more educational assistance
123
than children who were born at term. They also have an increased risk of re-hospitalization
during the first few years of life, increased use of outpatient care, and chronic health disorders in
adulthood.13,14 Thus, the long-term consequences of preterm birth have been estimated to
produce a substantial financial burden on the health care system15-17 and are likely to spill over
into other sectors of society. The existence of these sequelae provides a strong rationale for the
prevention of preterm birth. However, the increasing trends in preterm birth in recent years in the
general population of North America, mostly driven by obstetric interventions at 34-36 weeks of
gestation (medically indicated preterm delivery), were not accompanied by increases in infant
mortality (indeed infant mortality decreased) or in certain neurodevelopmental disabilities, such
as cerebral palsy.5,10,18 Whether these secular trends observed in the general population apply to
immigrants to Ontario is something to be confirmed by empirical research. The investigation of
these issues is likely to advance knowledge on the links between migration and perinatal health
and beyond. The prevention of the deterioration of gestational age among immigrants over time
spent in Canada may represent a worthy public health priority, if further research can better
clarify the causal pathways involved, and identify candidate interventions to be successfully
applied to different migrant groups. To date, most interventions to reduce preterm birth have
yielded disappointing results.18,19 Success was achieved in reducing the negative consequences of
preterm birth (tertiary prevention) due to intensive and improved obstetric and neonatal care
rather than preterm birth itself.18 While some risk factors affecting migrant women are not
modifiable (e.g., genetics, maternal height, early-life exposures), migrant women could benefit
from primary and secondary prevention of preterm birth (targeting health behaviours,
overweight/obesity, diet, removing barriers to women’s health and prenatal services, community
outreach for identification of women at risk, control of risk factors during pregnancy), but these
strategies are not receiving as much attention as tertiary interventions.18
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6.4. Unanswered questions and future research
Our understanding of the relation between reproductive health and international migration
remains poor. Here, I pose a few questions for which answers may help advance knowledge in
this area and briefly discuss some related study design issues.
6.4.1. Why is duration of residence associated with preterm birth?
The first question is what the mechanisms are through which time of exposure to urban Ontario
leads to higher risk of preterm birth. Connecting the dots between time spent in Canada after
migration and preterm birth represents a challenge, since several mediators may be operating
simultaneously forming one or more complex bio-psycho-social causal chains. Based on the
literature, it can be hypothesized that the following types of mediators are likely to be involved:
social environment, health behaviours, maternal illnesses before gestation, maternal
complications during pregnancy, and obstetric practices. First, the social environment is not
really a mediator but rather the broad context of acculturation, the cumulative influence of which
was proxied for by duration of residence after migration. The conceptualization and
decomposition of the social environment into measurable characteristics may help identify
specific stressors operating after migration. Such stressors may be influences operating in the
residential environment, labour market and workplace effects, as well as gender, ethno-cultural,
and psychological problems resulting from parental insertion in the Canadian society.20-24
Second, the social environment may exert its effects on health by modifying individual health
behaviours.25-28 Changes in maternal health behaviours and risk factors for preterm birth are
likely to be at least partially responsible for the increase in preterm birth risk experienced by
migrants with time spent in Canada. Indeed, deterioration of health behaviours and risk factors
125
after migration is supported by non-negligible evidence in the U.S.26,29-31, the U.K.,27 and also in
Canada.20,25,32,33
Another unexplored aspect of acculturation to Western societies may involve increased
medicalization with time spent in the new society. Such medicalization may be translated in a
shortening of the time from conception to first prenatal visit, increased compliance and enhanced
prenatal surveillance, and preference for elective cesarean delivery. When compared with
menstrual dates, early ultrasound based dating results in a left shift in the gestational age
distribution. If immigrants with longer duration of residence were more medicalized and enter
antenatal care earlier, their gestational age estimate might has been more likely to be based on
early ultrasound than among less medicalized immigrant women who had their first prenatal visit
at a more advanced stage of their pregnancies. Even assuming complete polarization of early
ultrasound use in our study population, this could not completely explain our results, since the
bias resulting from using ultrasound dating only versus the last menstrual period only was
estimated to be no more than a 10-20% increase in the risk of preterm birth,34 and we observed a
14%, 30%, and 49% increased odds associated with 5, 10, and 15 years of residence,
respectively. Another potential pathway related to increased medicalization may be increased
preference for elective cesarean section, which may shorten gestation length for some women. It
is also possible that use of assisted reproductive technologies (ARTs) have become more
frequent among the more acculturated migrant couples. Such a hypothetical pathway is plausible
for the following reasons: recent immigrants are on average less likely to have multiple
gestations and make use of ARTs than the general population; ARTs use is associated with
higher incomes35 and immigrants in Canada improve their income with time spent in Canada,
and use of ARTs has been associated with increased preterm birth even among singleton
pregnancies.36 Third, pre-existing maternal conditions and complications arising during
126
pregnancy are strong predictors of preterm birth and other adverse birth outcomes.37,38 Some of
these maternal conditions (e.g., hypertension, diabetes) are the result of underlying risk factors
such as lack of physical activity, unhealthy diet, overweight/obesity, and tobacco smoking,
which in turn may have been acquired by a number of women at some point after migration. The
plausibility of this pathway for our study population is supported by one Ontario-based study
reporting that the lower risk of maternal placental syndrome (assessed by a diagnosis of pre-
eclampsia or eclampsia, placental abruption or placental infarction) among newly arrived
immigrants came close to the level observed in the majority population (Canadian-born and
immigrants with more than 5 years of residence) in five years, presumably due to adoption of a
Western-diet and lifestyle.33 However, we have observed opposite trends in other maternal
conditions leading to preterm birth, such as genito-urinary infections, which may cancel out the
explanatory power of maternal conditions positively associated with time since migration.
Specific studies should be designed to weight the contribution of diverse maternal conditions on
the observed association between time since migration and preterm birth. Fourth, the existence of
maternal medical conditions affecting either the mother or the fetus constitutes one major reason
for medical interventions leading to preterm deliveries, which account for about one third of all
preterm births,37 either by induction of labour or by pre-labour caesarean section. Although
studies assessing the association between maternal obesity/overweight and preterm birth have
produced mixed results,14,39-43 there is increasing evidence supporting the existence of a link
between maternal overweight/obesity and pregnancy complications, such as gestational diabetes
and pre-eclampsia.44,45 High maternal pre-pregnancy weight and weight gain during pregnancy
have also been found to be associated with caesarean sections.11,46 These associations between
overweight/obesity and immediate predictors of preterm birth make the hypothesized pathway
“migrant cumulative exposure to Canada increase in body weight indicated preterm birth”
127
a plausible one. Specific studies would be needed to test whether and to what extent maternal
weight gain with time spent in Canada was responsible for increases in preterm birth among
immigrants, and if such hypothetical association varied by preterm birth types. The challenge,
however, is to obtain data on maternal pre-pregnancy weight, since maternal anthropometric
measures are not available in routinely collected administrative data. Survey data (various
Canadian Community Health Survey waves) linkable to administrative hospital data contain self-
reported weight and height, but these measures were obtained at the interview, and therefore not
around conception among the subset reporting having a baby in the 5 years preceding the
interview. However, these survey data can be used as secondary evidence to assess prevalence in
anthropometric, lifestyle, and psychosocial risk factors by time since migration.
Preterm births not caused by medical intervention are categorized as spontaneous, which in turn
subdivide into spontaneous preterm labour with intact membranes, and preterm premature
rupture of membranes (PPROM), irrespective of the mode of delivery (i.e., vaginal or caesarean).
Risk factors (both distal and proximal) for preterm birth were reported to differ between these
subtypes.37,47 One such factor is ethnic group, which is closely related to world region of origin
among migrants. For instance, spontaneous preterm birth is most commonly caused by preterm
labour among White women, but by PPROM among Black women in the U.S.19,37 This example
suggests that pathways linking immigrants’ duration of residence and preterm birth may also be
ethnic-specific. One potential strategy would be to restrict future studies to specific migrant
groups to avoid residual confounding. The task of connecting the dots between time spent after
migration and preterm birth may become even more complex and challenging if there is effect
modification by factors other than ethnic group.
128
Finally, it is also likely that duration of residence in Canada is an effect modifier of some risk
factors on its own. We have already found that the effects of duration of residence interacted
with neighbourhood deprivation (Chapter 5). It can be expected that some of the risk factors
hypothesized to be in the causal pathway “time since migration preterm birth” may be
present or absent at certain times or their effect may vary over time spent in Canada. For
example, cultural and language barriers may be more critical among recent immigrants but no
longer be a source of stress some years after arrival. In the same vein, exposure to jobs below
maternal educational and skill level is most likely to occur among recent immigrants and be less
prevalent among those who acquired some Canadian experience and upgraded their educational
credentials to Canadian standards after some years after arrival. However, after labour market
insertion has been successfully completed, migrants may face new challenges related to upward
social mobility, which may represent a new source of stress.
Although mediation by changes in maternal health behaviours and related risk factors is one
candidate explanation, other pathways are also possible. For example, chronic stressors, such as
low social position and discrimination, are more pervasive among minority women48 and may
represent alternative mechanisms leading to preterm birth among immigrants. Such hypothetical
pathways may involve health behaviours or not. Adoption of unhealthy health behaviours, such
as smoking and alcohol consumption, may be considered as a culturally acceptable way to cope
with chronic stress or adverse life events, imitated by immigrants. Even if migrants do not adopt
local unhealthy behaviours like these, exposure to stressful situations might precipitate preterm
labour via elevation of serum corticotrophin-releasing hormone (CRH), which creates a state of
hypervigilance or “arousal pathology”.48,49 Plasma CRH has emerged as a potential biological
marker for the prediction of preterm labour, although results obtained so far are not promising
enough to warrant its use as a routine clinical test.50 Different pathways may also intersect. It
129
has been suggested that genetic polymorphisms may interact with stress and obesity/overweight
to produce genitor-urinary infections, such as chorioamnionitis, that may trigger preterm
labour.51
The previous considerations, although speculative, draw attention to the potential complexity of
the observed association between time since migration and preterm birth. Whatever the pathways
are, future studies on this issue would greatly benefit from simultaneously obtaining data on
factors located at different steps in the hypothesized causal web (demographic, behavioural,
psychosocial, biological, and obstetrical). The acquisition and analysis of longitudinal data at the
individual level (e.g., before migration, at arrival, before and during pregnancy, and at delivery)
may allow the detection of changes in already established risk factors and their impact on
preterm birth. If obtaining detailed longitudinal data is not feasible, a first exploratory step would
be to compare recent and long-term immigrants, and try to explain their differences in preterm
birth by examining their differences in risk factors measured during pregnancy.
6.4.2. Is the association between time since migration and preterm birth merely a Canadian
phenomenon?
A second question is whether this direct association between length of stay after immigration and
risk of preterm birth is expected to be found in other settings. There is some evidence suggesting
that a positive association is likely to exist among migrants to Quebec25 and the U.S.,31,52
although it is not known whether such associations are characterized by a linear dose-response
pattern, such as ours. New comparisons, which will have to wait for similar studies to be
conducted elsewhere, may reveal similarities and differences between studies, which may help
identify underlying factors and potential pathways.
130
6.4.3. Is time since migration associated with other pregnancy-related outcomes?
The third question is whether the findings regarding duration of residence could be expected for
pregnancy-related outcomes other than preterm birth. For example, chapter 3 showed that
duration of residence affected gestational age but not fetal growth, as measured by SGA, which
is intriguing, since both outcomes are known to share common risk factors38,53 and
socioeconomic risk factors usually are associated with both outcomes in the same direction.54-56
One candidate risk factor to explain the association of duration of residence with preterm birth
(but not with “small for gestational age”) is maternal pre-pregnancy weight. Potential increases
in maternal pre-pregnancy body mass index with time spent in Canada (if confirmed) might be at
least partially responsible for counterbalancing the effect of other deleterious influences on small
for gestational age (e.g., smoking). In addition, the contribution of maternal pre-pregnancy
weight to gestational age is not clear in the literature 14,39,42 but could have influenced preterm
birth in our population. Although the testing of such hypotheses would need appropriate data that
are not easily available, the point here is to illustrate that further investigation of the potential
causal pathways behind these differential associations may advance our understanding of how
environmental exposures shape birth outcomes. A second candidate factor may be psychosocial
exposures, since some studies finding a positive association between different measures of stress
and preterm birth did not detect an association with intrauterine growth restriction.57-59
Another open question is whether time since migration is expected to predict infant mortality and
long-term consequences of preterm birth. It is reasonable to hypothesize that maternal duration
of residence since immigration would also be associated with those long-term childhood
outcomes that are known to follow after the occurrence of preterm birth, such as cerebral palsy,
although preterm birth may not be their cause but an endpoint resulting from common underlying
131
causes (e.g., pregnancy complications).5 That hypothesis could be tested using linkable
administrative health care databases, such as those used in this thesis, by following infants born
to immigrant women for some years after birth.
These kinds of questions would lead us to distinguishing which outcomes are affected similarly
by time since migration, and which outcomes are not, and why. Such inquiry could represent a
first step towards the elucidation of the influences operating on migrant women after arrival.
6.4.4. Why do some migrant groups experience poor outcomes and others do not?
The fourth question is why some migrant groups experience poor outcomes and others do not.
Unlike duration of residence that affected birth outcomes of immigrants from different world
regions almost uniformly in the same direction, differences between birth outcomes of
immigrants at a given duration of residence (e.g., recent immigrants by world region of origin in
chapter 4) are of great magnitude. The clarification of these differences would lead to the
investigation of the role of influences operating at multiple levels. At the country level, some
characteristics may explain differences between countries, such as the level of socioeconomic
and human development. Regional differences and social class dynamics within countries may
also be important in explaining why some people emigrate and why others do not and why, and
how such selection affects birth outcomes in the two groups. Finally, source and receiving
countries may differ in their patterns of emigration-immigration, thus shaping particular
immigrant experiences in many settings. The local environment of the receiving country may be
crucial in understanding immigrant health, particularly with increasing duration of stay.
Although the emphasis of this thesis was on urban neighbourhoods, other contexts such as the
physical environment, the workplace, and the family may be also relevant. Also, regional labour
and housing markets may attract or reject certain immigrants, especially at the city level. At the
132
individual level, maternal (and paternal) characteristics collected prior to migration may help
elucidate whether and to what extent so-called “healthy immigrant selection” is shaping the
outcomes of emigrants in their new home. Repeated measures of the same characteristics after
migration are desirable, although difficult to obtain, in order to track changes in risk factors and
their impact on the outcomes. In other words, longitudinal data should be ideally obtained on
time-dependent variables, at different points in time, in order to properly assess the impact of
migration and subsequent adaptation on immigrants’ health.
6.5. Concluding remark
Although this thesis can be labelled as a thesis on immigrants’ health, the relation between
migration and reproductive health goes beyond the health of minority groups. Indeed, the
offspring of Canada’s many immigrants are ‘Canadian-born’; and therefore, disparities in
reproductive outcomes among immigrants contribute directly to disparities in related childhood
and subsequent adult outcomes among the ‘non-immigrant’ population. They are therefore surely
worthy of increased Canadian research attention.
133
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140
Appendices
Appendix 2.A. Search strategy
Original search strategy carried out by ROAM1
Criteria for considering studies for review
Study outcomes: Reports were excluded if the outcome under study was not directly related to
perinatal health indicators commonly cited by national or international bodies (e.g., EURO-
PERISTAT),2 or to outcome differences specific to pregnant migrants such as infectious disease
and smoking/ drug/ alcohol use.
Type of exposure: Migration was the exposure of interest. Therefore, any report of women who
had migrated was initially included. Reports were subsequently excluded if international cross-
border movement was unlikely (thus ‘protectorates’ such as Puerto Rico did not meet our
definition of migrant, nor did second-generation populations.)
Type of study designs: We excluded case studies, clinical reports, reports without a comparison
group, and reports in which the results of the migrant group(s) were not presented separately
from the comparison group.
Study population: Migrant women in ‘western industrialized’ countries were included. Those in
refugee camps were excluded.
An author search of ROAM collaborators was also conducted. Searches were supplemented with
bibliographic citation hand-searches of included literature published from 2004 onward. Other
relevant literature referred to the authors was also reviewed. Government documents or ‘grey
literature’ were not reviewed and no attempts were made to contact authors of published works
due to the volume of literature under consideration.
141
No language exclusions were routinely applied. French, Spanish, Swedish, and Italian- language
articles were reviewed by members of ROAM or their associates. Review of other non-English
language articles was restricted to their English abstracts. On two occasions, an English abstract
was not available and the article was not reviewed.
Search strategy: Electronic literature databases from 1995 through September 2006 were
searched using Ovid (version 10.5.1) in the following order: Medline, Health Star, Embase, and
PsychInfo. The search strategy was developed in conjunction with a McGill University Health
Sciences librarian and was as follows:
1 exp emigration/ and immigration.mp. 2 *Ethnic Groups/ 3 *Minority Groups/ 4 (migration history or premigration).tw. 5 exp refugees/ or refugee$.tw. 6 migrant.tw. 7 perinatal$.tw. 8 exp pregnancy/ or pregnancy outcomes.mp. or pregnancy complications.mp. or pregnancy.tw. 9 equity.tw. 10 exp delivery of healthcare/ 11 exp maternal health service$/ 12 exp social support/ or social isolation.tw. 13 exp prejudice/ or (racism or prejudice).tw. 14 1 or 2 or 3 or 4 or 5 or 6 15 14 and 8 16 9 or10 or 11 or 12 or 13 17 14 and 16 18 7 and 17 19 15 or 17 20 limit 19 to yr="1995 - 2006"
Updated search: The above search identified 78 studies relevant for the review of low
birthweight and preterm birth by migrant subgroups.
142
The same search was repeated in early December 2007 to include articles published up until
November 2007. One article written in Serbian was translated into English. Back references
were also checked and potential articles pointed out by ROAM members were also considered.
Thus, six new papers were considered but only four met inclusion criteria, totalling 82.
References
(1) Gagnon, A. J., Zimbeck, M., Zeitlin, J., and the ROAM Collaboration. Migration to western industrialized
countries and perinatal health: A systematic review. Social Science & Medicine (In press), 2009.
(2) Zeitlin J, Wildman K, Breart G et al. PERISTAT: indicators for monitoring and evaluating perinatal health in
Europe. European Journal of Public Health. 2003;13(3 Suppl):29-37.
143
Appendix 3.A. Data sources
Discharge Abstracts Database (DAD-CIHI): The DAD contains information on the individual
health number, address information, birth date, admission and discharge dates, 16 diagnostic
codes, 10 procedure codes from fiscal years 1988/1989 to 2001/2002 (ICD-9) and 25 diagnostic
and 20 procedure codes from fiscal year 2002/2003 onwards (ICD-10-CA), among many other
variables describing the nature of the hospital services. CIHI data are available at ICES thanks to
an agreement held between the Institute for Clinical Evaluative Sciences (ICES) and the Ontario
Ministry of Health and Long-Term Care (MOHLTC). The DAD has three main limitations. First,
out-of-hospital births are not captured, which would represent about 1.1% of all births.1 Second,
information on gestational age and recent parity were not captured until fiscal year 2002/2003,
when a data-system redevelopment took place. Since fiscal 2002/2003, gestational age is
recorded in completed weeks and is derived from medical charts, thus representing the best
clinical estimate of gestation, which includes both ultrasound- and LMP-based estimates.1 Third,
the mother and child records were unrelated until fiscal year 2002/2003, when a link was created
through the inclusion of both the mother and child health number in each record. This study
therefore had to rely on a probabilistic linkage, which is known to capture close to 95% of births
up until fiscal 2001/2002. Despite the deterministic link between the mother and child records
was available since 2002/2003, the matching rate (under 80% in 2002/2003 and under 90% in
2003/2004) was not as good as the one obtained with the probabilistic approach. Therefore, the
probabilistic was used throughout the study period.
The approach of extracting data on both live births and mothers from the DAD was evaluated by
members of the Canadian perinatal surveillance system group,2 proving to have excellent
coverage and accurate rates for Ontario. More sensitive methods have been developed in order to
144
capture some births missed by the Wen’s approach.3,4 An ICES re-abstraction study based on the
DAD (2002/03 and 2003/04 fiscal years) found excellent percent agreement on variables key for
this study (99% in sociodemographic variables, 100% in liveborn infants according to place of
birth and 92.3% in comorbid diagnoses such as preterm delivery).5 The meaning of each variable
was interpreted following the CIHI Abstracting Manual (1995)6 and DAD Data Quality
Documentation.7,8 Diagnostic and procedure codes correspond to the International Classification
of Diseases - 9th Revision (ICD-9)9 and to the Canadian Classification of Diagnostic,
Therapeutic, and Surgical Procedures (CCP) up until fiscal 2002/2003, when the enhanced
Canadian version of the 10th revision (ICD-10-CA) and the Canadian Classification of Health
Interventions (CCI) were adopted in Ontario.8,10
Landed Immigrant Data System (LIDS): The LIDS dataset spans from calendar year 1985 to
2000. The Ontario LIDS is composed of the landing records of all legal immigrants whose
intended destination was Ontario. A probabilistic linkage with the provincial administrative
health care database (RPDB) was carried out at ICES using a special algorithm based on
surname, given names, sex, and date of birth, and complemented by manual review of non-
matched records.11 The information contained in each record is based on the documentation
provided by the migrants during their application process: age, gender, marital status, country of
birth, citizenship, and last permanent residence, mother tongue, intended destination; immigrant
category, special program codes, principal applicant code, employment status; intended
occupation, years of schooling, level of education, knowledge (self–assessed) of an official
language. All of the information taken from the Landing Record was recorded as of the date of
issue of the landing visa and is retained intact regardless of the year of observation.
145
The Registered Persons Data Base (RPDB): Upon approval for Ontario health coverage (Ontario
Health Insurance Plan - OHIP), client registration and identification information is entered onto
the Registered Persons Data Base (RPDB), maintained by the Ministry of Health since 1990. The
RPDB contains information on individuals such as their surname, given name, health number,
gender, date of birth, place of residence, and the dates of the start and end of eligibility for the
provincial health coverage for all people residing in Ontario. This database was used to extract
information on new registrants to OHIP, as a proxy for recent immigration (i.e., within the last
five years).
Details of the linkage between the LIDS and the RPDB
Because the probabilistic linkage of the LIDS with the provincial administrative health care
database (RPDB) was done provincially (84.4% match), the linkage does not capture those
international migrants residing in Ontario who came into Canada via any port of entry outside
Ontario and moved in afterwards. Conversely, migrants who arrived to Ontario and moved out of
the province shortly after arrival may not be captured by the linked dataset. A initial validation
study 12 concluded that there was little bias for linkage based on the percent linked for different
predictor variables included in the LIDS. There were differences in the following categories: 1)
Landing year: The percent linked diminished to a low of 72% prior to 1990, presumably due to
the creation of new electronic health cards in 1991; 2) Visa category: Business class had a
relatively low linkage (72.3%), most likely because immigrants in this category were more likely
to continue to live in their home country, such as those from Hong Kong who transferred power
to China after becoming landed immigrants; 3) Education: Slightly lower linkage for Masters
and PhD degrees; 4) Country: There were no great variations across countries represented by
146
more than 100 migrants. Hong Kong had one of the lowest linkage rates (66.5%), probably due
to their Visa Category.
The lower linkage rates for migrants in the business class category, holding post-secondary
education, and from Hong Kong suggest that non-linked migrants were more resourceful
individuals that may have abandoned Ontario shortly after arrival pursuing better prospects
somewhere else. If this is true, the low linkage rate among these groups would not result in
misclassification because they are not supposed to be counted as non-immigrant residents of
Ontario. However, potential bias may arise if many immigrants came to Ontario after landing in
other provinces, since this type of immigrants could not be captured by the linkage. Such bias
would affect comparisons between immigrants and non-immigrants towards the null effect, since
immigrants whose intended destination was not Ontario would be ‘false non-immigrants’.
However, there is no bias when comparisons are made between immigrant groups, because the
reference group is an internal group of immigrants.
Canadian Censuses 1996 and 2001: Contextual data at the census tract (CT) level were merged
with the above datasets through the Postal Code Conversion File Plus (PCCF+) from Statistics
Canada. The PCCF+ is a SAS program that assigns each 6-digit postal code to enumeration
areas/dissemination areas, census tracts and other levels of census geography, and is routinely
updated to reflect changes in census geography.
147
Table 3.A.1. Variable definitions
Variable Definition Scale Data source Availability
Outcomes
Birthweight (BW) In grams (>=500 and <=6000) Continuous DAD-CIHI 1988/89 – 2006/07
Low birthweight
(LBW)
Infant weighting <2500 grams Binary DAD-CIHI 1988/89 – 2006/07
Very low
birthweight
(VLBW)
Infant weighting < 1,500 grams Binary DAD-CIHI 1988/89 – 2006/07
Moderately low
birthweight
(MLBW)
Infant weighting 1,500-2,499 grams Binary DAD-CIHI 1988/89 – 2006/07
Preterm birth
(PTB)
Infant born before the 37th completed week
of gestation (at maternal hospital
admission)
Binary DAD-CIHI 1988/89 – 2001/02
based on ICD-9
codes
2002/03 – 2006/07
based on weeks of
gestation
Very preterm birth
(VPTB)
Infant born before 32 weeks Binary DAD-CIHI 2001/02 – 2006/07
Moderately
preterm birth
(MPTB)
Infant born between 32 weeks or more but
before 37 weeks
Binary DAD-CIHI 2001/02 – 2006/07
Small preterm
birth (SPTB)
Infants having both LBW and PTB Binary DAD-CIHI 1988/89 – 2006/07
Small for
gestational age
(SGA)13
Gender and gestational-age specific
birthweight below the 10th percentile of the
most recent published sex-specific
Canadian reference values based on
infants born in 1994–96
Binary DAD-CIHI 2001/02 – 2006/07
Independent
variables
Immigrant status Presence of a landing record Binary LIDS 1985 - 2000
Immigrant status
by length of stay
Presence of a landing record 0-4 years to
delivery (recent immigrant), 5-9 years, 10-
14 years, more than 14 years (long-term
resident)
Categorical LIDS and
DAD-CIHI
1985 – 2006/07
Length of stay Time from arrival to delivery (in days).
Based on a combination of arrival and
landing date.
Continuous LIDS and
DAD-CIHI
1985 - 2006/07
World regions Groupings by country of birth based on Categorical LIDS 1985 - 2000
148
Variable Definition Scale Data source Availability
international classifications (World Bank,
UNICEF, United Nations)
Area-based
material
deprivation
Neighbourhood indexes obtained by
principal component analysis (Material
deprivation, residential instability,
dependency, ethnic diversity)
Continuous CENSUS 1996, 2001
Covariates
Infant sex Female, male Categorical DAD-CIHI 1988/89 – 2006/07
Maternal age Maternal age at delivery (15-20, 20-24, 25-
29[ref], 30-34, 35-39, 40-55)
Categorical DAD-CIHI 1988/89 – 2006/07
Parity Number of previous live births Discrete DAD-CIHI 2002/03 – 2006/07
Previous preterm
delivery
Yes, no [ref] Binary DAD-CIHI 2002/03 – 2006/07
Marital status at
arrival
Married/common law [ref],
Single/divorced/separated
Categorical LIDS 1985 - 2000
Immigrant class Economic class [ref], Family class,
Refugees
Categorical LIDS 1985 - 2000
Knowledge of
English/French Yes [ref], no Binary LIDS 1985 - 2000
Maternal
education at
arrival
0 to 9, 10 to 12 years of schooling, any
post-secondary diploma [ref]
Categorical LIDS 1985 - 2000
High School
graduation
Yes [ref], no Binary LIDS 1985 - 2000
Pre-existing
maternal illnesses
and pregnancy
complications
Yes, no [ref] Binary DAD-CIHI 1988/89 – 2006/07
Recent
registration to
OHIP
Start of eligibility for OHIP coverage within
a five-year period prior to delivery after April
1, 1991
Binary RPDB 1995/96 – 2006/07
References
(1) Canadian Institute for Health Information. Too Early, Too Small: A Profile of Small Babies Across
Canada. 2009. Ottawa, Ont, CIHI.
149
(2) Wen SW, Liu S, Marcoux S, Fowler D. Uses and limitations of routine hospital admission/separation
records for perinatal surveillance. Chronic Dis Can. 1997;18(3):113-119.
(3) Health Canada. Canadian Perinatal Health Report, 2003. Cat. No. H49-142/2003E. 2003. Ottawa, Minister
of Public Works and Government Services Canada.
(4) Urquia ML, Frank JW, Glazier RH, Moineddin R. Birth outcomes by neighbourhood income and recent
immigration in Toronto. Health Rep. 2007;18(4):1-10.
(5) Juurlink D, Preyra, C, Croxford, R, Chong, A, Austin, P, Tu, J, and Laupacis, A. Canadian Institute for
Health Information Discharge Abstract Database: a validation study. 2006. Toronto, Institute for Clinical
Evaluative Sciences (ICES).
(6) Canadian Institute for Health Information (CIHI). Abstracting Manual. 1995. Canadian Institute for
Health Information (CIHI).
(7) Canadian Institute for Health Information. Data Quality Documentation: Discharge Abstract Database
2001–2002. 2003. Ottawa, Canadian Institute for Health Information.
(8) Canadian Institute for Health Information. Data Quality Documentation: Discharge Abstract Database
2002–2003. 2005. Ottawa, Canadian Institute for Health Information.
(9) World Health Organization. International Classification of Diseases, Injuries and Causes of Death. 9th
revision. Geneva: The Organization; 1979.
(10) Canadian Institute for Health Information. Final Report. The Canadian Enhancement of ICD-10
(International Statistical Classification of Diseases and Related Health Problems, Tenth Revision). 2001.
Ottawa, Ont., CIHI.
150
(11) Desmeules, M., McDermott, S., Cao, Z., Manuel, D., Kazanjian, A., Vissandee, B., Ruddick, E., Kleiwer,
E., Mao, Y., and Gold, J. Immigrant Health and Health Care Utilization in Canada: Phase II of the National
Immigrant Health Initiative. 2004.
(12) Cernat, G, Wall, C, Iron, K, and Manuel, D. Initial Validation of Landed Immigrant Data System (LIDS)
with the Registered Person's Database (RPDB) at ICES. 2002.
(13) Kramer MS, Platt RW, Wen SW et al. A new and improved population-based Canadian reference for birth
weight for gestational age. Pediatrics. 2001;108(2):E35.
151
Appendix 3.B. Measurement of Stillbirths and Multiple Births Using the Discharge
Abstract Database
Approaches to extracting stillbirths and multiple births from the DAD vary according to the unit
of analysis, and the use of diagnostic codes. For example, one ICES report 1 used ICD-9/10
codes in the mothers’ records presumably because the unit of analysis of the report was the
mother and not the child. In the same vein, two recent CIHI reports used information contained
in the child records because the report focused on the infant.2,3
Stillbirths
One CIHI report used ICD codes to identify multiple births but not to identify stillbirths.3
Instead, the report used a variable “hospital entry code = S (stillborn)”. However, this
information has not been consistently sent to ICES by CIHI (Alex Kopp, personal
communication). Therefore, we relied solely on the diagnostic codes. Table 1 and Figure 1 show
the stillbirth ‘rates’ from 1998 to 2006 using different approaches: a) information in the maternal
records only; b) information in the infant records only; c) information in either the maternal or
infant records; and d) the Vital Statistics estimates, added as an external comparison.4,5 The same
definition of fetal death rate (crude) (i.e., number of stillbirths per 1,000 total births (live births
and stillbirths)) was used for all estimates.
152
Table 3.B.1. Measurement of stillbirths (fetal deaths per 1,000 total births) in the Ontario DAD-CIHI at
ICES (fiscal 1988/1989-2006/2007), by method, and in the Ontario Vital Statistics (calendar 1991-2004)
(a) (b) (c) (d)
Year Mothers’
ICD
Infants'
ICD
Either
ICD
Vital
Stats
1988 5.7 2.0 6.4
1989 6.4 1.6 7.0
1990 5.0 1.6 5.7
1991 5.2 2.6 6.9 5.3
1992 5.1 1.9 6.1 7.1
1993 4.7 2.8 6.1 6.5
1994 4.3 1.6 4.8 6.4
1995 4.3 1.7 5.2 6.6
1996 4.9 3.2 6.6 6.4
1997 4.8 2.9 5.7 6.6
1998 5.4 2.1 6.2 6.4
1999 5.7 2.7 6.8 6.3
2000 5.2 2.6 6.5 6.4
2001 5.6 3.6 7.7 6.3
2002 10.0 0 10.0 6.3
2003 6.8 0 6.8 7.3
2004 7.0 0 7.0 6.3
2005 5.2 0 5.2
2006 4.5 0 4.5
153
Figure 3.B.1. Measurement of stillbirths in the Ontario DAD-CIHI at ICES (fiscal 1988/1989-2006/2007),
by method, and in the Ontario Vital Statistics (calendar 1991-2004)
The use of infant records only clearly underestimates stillbirth counts and gives no information
after the implementation of the ICD-10, supposedly because of a change in the coding (see Table
3.B.4 below). The use of maternal records provides a better estimate that is still below the Vital
statistics’ estimates, with the exception of the first years following the implementation of the
ICD-10 where the sudden jump in the rates is suggestive of an artefact. Such interruption of the
trends from the ICD-9 to the ICD-10 is common to many other outcomes (Alex Kopp, personal
communication). The combination of both the maternal and infant records increases the rate for
most years, indicating that the codes in the infant records capture some stillborns not included in
the maternal records. This combination approaches Vital Stats data reasonably well for some
years but it is generally below. However, in theory it is expected that the measurement of
stillbirths would result in higher rates than those based on the Vital Stats. First, the exclusion of
154
home births from the CIHI should have a modest impact on these rates as stillbirths and multiple
births typically occur in hospital (about half of all stillbirths result from multiple pregnancies)
and the healthy singletons born outside hospital are not included in the denominator. Second, the
CIHI data are likely to capture extremely small babies which may not get registered in the Vital
Statistics data. For instance, the coders at the hospital code the CIHI records but the physicians
are those who likely determine whether a stillbirth certificate is to be filled out or not (K.S.
Joseph, personal communication).
Therefore, based on these considerations, the best possible estimate of stillbirths from the DAD
to be used in this thesis is to combine maternal and infant records.
Multiple births
Table 3.B.2 and Figure 3.B.2 show the multiple birth percent from 1998 to 2006 using
different approaches: a) information in the maternal records only; b) information in the infant
records only; c) information in either the maternal or infant records; d) counting the number of
child records per delivery episode; e) a combination of (c) and (d); and f) the Vital Statistics
estimate, added as an external comparison. The same definition was used for all estimates (i.e.,
number of multiple births per 100 births, including stillbirths and live births).5
155
Table 3.B.2. Measurement of multiple births (multiple births per 100 total births) in the Ontario DAD-CIHI
at ICES (fiscal 1988/1989-2006/2007), by method, and in the Ontario Vital Statistics (calendar 1991-
2004)
(a) (b) (c) (d) (e) (f)
Maternal
ICD
Infants'
ICD
Either
ICD
Count
method
Either count
or either ICD
Vital
Stats
1988 1.47 1.08 1.53 3.13 3.96
1989 1.53 1.11 1.58 2.54 3.33
1990 1.63 1.27 1.70 2.16 2.82
1991 2.20 1.71 2.27 2.74 2.96 2.0
1992 2.41 1.86 2.46 2.73 2.84 2.1
1993 2.42 2.15 2.49 2.69 2.75 2.1
1994 2.51 2.27 2.58 2.76 2.82 2.4
1995 2.40 2.17 2.46 2.69 2.75 2.4
1996 2.64 2.43 2.69 2.86 2.95 2.6
1997 2.77 2.53 2.80 2.90 2.98 2.7
1998 2.91 2.71 2.96 3.08 3.16 2.8
1999 2.92 2.68 2.95 3.06 3.16 2.9
2000 2.90 2.71 3.05 3.14 3.22 2.9
2001 3.07 2.81 3.13 3.25 3.35 3.0
2002 3.17 2.94 3.24 3.38 3.45 3.2
2003 3.24 3.02 3.27 3.43 3.48 3.2
2004 3.30 3.10 3.36 3.44 3.53 3.2
2005 3.27 3.07 3.31 3.40 3.50
2006 3.36 3.13 3.41 3.46 3.49
156
Figure 3.B.2. Measurement of multiple births in the Ontario DAD-CIHI at ICES (fiscal 1988/1989-
2006/2007), by method, and in the Ontario Vital Statistics (calendar 1991-2004)
Again, in theory it is expected that the estimates from the DAD will be higher than those based
on the Vital Stats because: i) multiple births are much more likely to occur in hospitals and home
births are represented by mostly uncomplicated single deliveries that are not included in the
denominator, ii) The main form for the registration of a live birth is completed by the parents,
who are responsible for filing it with the local registrar and failure to do this by the parents is one
cause of underegistration of births in the Ontario Vital Stats system and it might be higher when
multiple births are involved, iii) Over-coverage in the Vital Stats is minimal. Births to non-
resident women in Canada are registered but are excluded from most tabulations. Duplicate birth
registrations are identified as part of the regular processing operations on each provincial and
territorial subset, as well as additional inter-provincial checks, and comparisons between the
birth and stillbirth databases for multiple births. Possible duplicate registrations are checked
157
against microfilmed registrations or optical images, or by consulting with the provinces and
territories. In contrast, the probabilistic linkage of maternal and infant records may produce some
duplicates in a few cases where the criteria (i.e., postal code, maternal admission date, hospital)
are met by more than one delivery. Although the program developed at ICES includes a cleaning
algorithm, some duplicates remained. This is particularly evident when we consider the count
method (i.e., counting the number of infant records per maternal delivery episode), which is
consistently higher than the combination of maternal and infant ICD codes. A quick look at
Table 3.B.3 suggests that the count method is not a good approach to measure multiple births
since it overcounts some singletons matched to more than one mother, thus producing duplicate
records, as a result of the probabilistic linkage.
Table 3.B.3. Percentiles of birthweight (in grams) by method
5th
percentile
25th
percentile
50th
percentile
75th
percentile
95th
percentile
Multiple births by
ICD 1105 2070 2495 2850 3350
Singleton births by
ICD 2540 3105 3435 3770 4286
Multiple births by
the count method
but not by ICD
2360 3045 3400 3760 4290
If the count method identified only true multiples we would expect that the birthweight
distribution of those identified as multiple by the count method but not by the ICD codes’
method would be approximately similar to that of the rest of the multiples identified by the ICD
codes’ method. However, as seen in Table 3.B.3 this is not the case. These additional infants are
most likely false multiple births because their birthweight distribution is quite similar to that of
158
the singleton births. In conclusion, these exploratory analyses suggest that the best estimate of
multiple births obtained from the DAD, as available for this thesis, is the one based on a
combination of infant and maternal ICD codes.
Table 3.B.4. List of ICD codes for stillbirths according to Revision and unit of analysis
Stillbirths ICD-9 Description ICD-10 Description
Infants’
records
V320 Twin, mate stillborn, born in
hospital
P95 Fetal death of unspecified cause
V321 Twin, mate stillborn, born before
admission
V322 Twin, mate stillborn, born outside
hospital
V350 Other multiple, mates all stillborn,
born in hospital
V351 Other multiple, mates all stillborn,
born before admission
V352 Other multiple, mates all stillborn,
born outside hospital
Mothers’
records
6564 Intrauterine death O364 Maternal care for intrauterine
death
V271 Single stillborn Z371 Single stillbirth
V274 Twins, both stillborn Z374 Twins, both stillborn
V277 Other multiple birth, all stillborn Z377 Other multiple births, all stillborn
159
Table 3.B.5. List of ICD codes for multiple births according to Revision and unit of analysis
Multiple
births
ICD-9 Description ICD-10-
CA
Description
Infants’
records
7594 Conjoined twins Q894 Conjoined twins
V310 Twin, mate liveborn, born in
hospital
V311 Twin, mate liveborn, born before
admission
V312 Twin, mate liveborn, born outside
hospital
V330 Twin, unspecified, born in hospital Z383 Twin, born in hospital
V331 Twin, unspecified, born before
admission
Z384 Twin, born outside hospital
V332 Twin, unspecified, born outside
hospital
Z385 Twin, unspecified as to place of
birth
V340 Other multiple, mates all liveborn,
born in hospital
V341 Other multiple, mates all liveborn,
born before admission
V342 Other multiple, mates all liveborn,
born outside hospital
V360 Other multiple, mates live- and
stillborn, born in hospital
V361 Other multiple, mates live- and
stillborn, born before admission
V362 Other multiple, mates live- and
stillborn, born outside hospital
V370 Other multiple, unspecified, born
in hospital
Z386 Other multiple, born in hospital
V371 Other multiple, unspecified, born
before admission
Z387 Other multiple, born outside
hospital
V372 Other multiple, unspecified, born
outside hospital
Z388 Other multiple, unspecified as to
place of birth
Mothers’
records
6510 Twin pregnancy O300 Twin pregnancy
6511 Triplet pregnancy O301 Triplet pregnancy
6512 Quadruplet pregnancy O302 Quadruplet pregnancy
6513 Twin pregnancy with fetal loss
and retention of one fetus
160
Multiple
births
ICD-9 Description ICD-10-
CA
Description
6514 Triplet pregnancy with fetal loss
and retention of one or more
fetus(es)
6515 Quadruplet pregnancy with fetal
loss and retention of one or more
fetus(es)
6516 Other multiple pregnancy with
fetal loss and retention of one or
more fetus(es)
6517 Multiple gestation following
(elective) fetal reduction
6518 Other specified multiple gestation O308 Other multiple gestation
6519 Unspecified multiple gestation O309 Multiple gestation, unspecified
6526 Multiple gestation with
malpresentation of one fetus or
more
O325 Maternal care for multiple
gestation with malpresentation of
one fetus or more
6605 Locked twins O661 Obstructed labour due to locked
twins
7615 Multiple pregnancy O848 Other multiple delivery
O849 Multiple delivery, unspecified
V272 Twins, both liveborn Z372 Twins, both liveborn
V275 Other multiple birth, all liveborn Z375 Other multiple births, all liveborn
O840 Multiple delivery, all spontaneous
O841 Multiple delivery, all by forceps
and vacuum extractor
O842 Multiple delivery, all by
caesarean section
References
(1) Maaten S, Guttman A, Kopp A, Janda M, Jaakkimainen L. Care of women during pregnancy and
childbirth. Primary Care in Ontario. Toronto, Ontario: Institute for Clinical Evaluative Sciences, 2006: 15-
34.
(2) Canadian Institute for Health Information. Too Early, Too Small: A Profile of Small Babies Across Canada.
2009. Ottawa, Ont, CIHI.
161
(3) Canadian Institute for Health Information. Analysis in Brief: Factors Associated With Low Birth Weight,
2002-2003 to 2006-2007. [Canadian Institute for Health Information]. 2009. Available at:
http://secure.cihi.ca/cihiweb/dispPage.jsp?cw_page=RC_2309_E&cw_topic=2309.
(4) Health Canada. Canadian Perinatal Health Report, 2003. Cat. No. H49-142/2003E. 2003. Ottawa, Minister of
Public Works and Government Services Canada.
(5) Public Health Agency of Canada. Canadian Perinatal Health Report, 2008 Edition. Public Health Agency of
Canada . 2008. Ottawa, Public Health Agency of Canada.
162
Appendix 3.C. Flowchart Data Exclusions
Flow chart: Selection criteria for the study population
N Selection criteria
2,361,427 Birth records matched to a mother fiscal 1988-2006
↓ Keep only those babies born after ‘31MAR2002’ (New CIHI data)
630,925
↓ Keep those infant born within 2001 CMAs (1,913 records had
missing CMAs and were deleted)
491,324
↓ Exclude multiple births and stillbirths (N=16,710)
474,614
↓ Exclude infants born to mothers that had never been registered to
OHIP up until ‘31MAR2001’(last date in the LIDS=‘31DEC2000’ +
3-month waiting period). These may be migrants arriving after
‘31DEC2000’ (last date in the LIDS) or interprovincial migrants. As
these do not appear in the available LIDS data, we do not want them
to be misclassified as ‘non-immigrants’ (N=74,961)
399,653
↓ Exclude live births weighting less than 500 (due to increased
registration of near viable births) and more than 6000 g (and likely
data errors) (N=360)
399,293
↓ Exclude records with missing data on the outcomes or in gestational
age (N=125)
399,168
↓ Exclude records with gestational age lower than 22 weeks and higher
than 43 weeks (N=72)
399,096
↓ Exclude records with missing data on infant sex, maternal age or
163
N Selection criteria
parity (N=54)
399,042
↓ Exclude records with missing data on immigration characteristics
(N=576)
398,466
↓ Exclude immigrants classified as “OTHER” (i.e., other than ‘family’,
‘economic, or ‘refugee’) (N=487)
397,979
↓ Exclude records to which census information could not be assigned
(N=509)
397,470 Population size for analyses (immigrants = 83,233 and Canadian-
born/long-term residents = 314,237)
164
Appendix 3.D. Covariate Adjustment Based on Directed Acyclic Graphs (DAGs)
Here we present the rationale behind the covariate selection for the models shown in Table 3.3,
Chapter 3. The conventional criteria for confounding control works well when the effect of
exposure on disease is influenced by a third variable. However, these criteria may be inadequate
when multiple confounders are considered simultaneously. The theory of directed acyclic graphs
(DAGs),1,2 involves rules to guide the identification of variables (or combination of variables)
that must be controlled for in order to obtain unbiased effect estimates of the exposure. First, we
provide a background on the relations between the variables in our model. Second, we apply the
DAGs graphical criteria to obtain a sufficient set of variables for confounding adjustment. 1,2
Figure 3.D. Directed acyclic graphs for sufficient confounding, before (3.D.1) and after (3.D.2) the
backdoor test for sufficiency
165
Age at arrival determines both age at delivery (women aged 30 and more at arrival can only
deliver after that age) and duration of residence, defined as time from arrival to delivery (the
older the women at arrival the shorter the fertile window to be a mother). Maternal age at
delivery equals maternal age at arrival plus time from arrival to delivery. Therefore, age at
delivery is influenced directly by age at arrival, and partially via length of residence. Parity is
influenced by the previous three variables (the older the mother the more likely she is to have
had a previous birth). Age at arrival is not directly associated with preterm birth but age at
delivery, duration of residence, and parity are. Age at arrival also influences knowledge of
official languages (English/French), maternal education and marital status, because these three
variables were measured at arrival (older women were more likely to be married, to have learnt
some official language, and to bring higher educational credentials than those who arrived
younger). These three variables are also associated both with the exposure (see Table 3.1 in
Chapter 3) and the outcome (knowledge of official languages is positively associated with
preterm birth, maternal education is negatively associated with preterm birth, as well as being
married or cohabiting with their partners). Immigrant class is associated with the outcome
(refugees are at slightly higher risk of preterm birth than the rest) and also with the exposure
(refugees are more common as duration of residence increases, indicating a decline in the
refugee influx over time). Immigrant class is subsequently influenced by country of birth
(refugees originate in specific countries and the composition of family members may also vary
across countries). In the same vein, country of birth is also associated with duration of residence,
as a result of uneven waves of migration in the last two decades. Country of birth is associated
with preterm birth and also with neighbourhood material deprivation (immigrants from poor
countries tend to settle and live in poor neighbourhoods and vice versa). Thus, neighbourhood
material deprivation mediates the effects of country of origin on preterm birth. Finally, infant sex
166
is associated with preterm birth (males are at a higher risk) but is not associated with any other
variable in the graph.
Given the DAG in Figure 3.D.1 and a set S of variables in the graph that are not effects of the
exposure (duration of residence) or the outcome (preterm birth), S is sufficient for adjustment if,
upon adjustment for S, there is no unblocked backdoor path from the exposure to the outcome.
An unblocked path is a sequence of arrows connecting any two variables, irrespective of the
direction of the arrows. A path is blocked when the sequence of arrows connecting two variables
contains a variable used for adjustment (that is, included in S). In a DAG, there are only two
possible kinds of unblocked paths between variables: directed paths (direct causal connection)
and backdoor paths through a shared ancestor (that is, through a common cause of both
variables). The sequence must not contain a collider, which is represented by a variable with two
or more single arrows pointing at it (that is, a collider is a common effect of two or more
variables – a collider is a child that shares ancestors). Including a collider in S creates an
association between their common causes, even if they were not associated originally, and
therefore given a pair of variables sharing a child, if the child is included in S then one of these
two parents must be also included in S. These conditions can be checked by means of an
algorithm called the “backdoor test for sufficiency”. The test involves the following steps:
1. Delete all arrows originating from the exposure (the dashed arrows in Figure 3.D.1)
2. Draw undirected arcs to connect every pair of variables that share a child that is either in
S or has a descendant in S (parity is the only child shared by age at arrival and age at
delivery and they are already connected)
3. In the new graph resulting from applying steps 1 and 2, see whether there is any
unblocked path from exposure to disease that does not pass through S. If there is not, then
S is sufficient.
167
Regarding the association between duration of residence and preterm birth, the set S (composed
of the variables enclosed in a box in Figure 3.D.2) is sufficient for confounding adjustment, as
follows.
Control for language knowledge blocks the backdoor path preterm birth – language knowledge –
age at arrival – duration of residence. Similarly, control for maternal education and marital status
blocks similar backdoor paths connecting the outcome with the exposure. Control for immigrant
class and country of birth blocks any backdoor path connecting the outcome and the exposure via
these two variables. This also blocks the path connecting the outcome and the exposure via
neighbourhood deprivation, and therefore no adjustment for this variable is necessary. This
reflects the conventional criterion that adjustment for a mediator is not appropriate. Parity is the
only collider in S. Adjustment for parity and maternal age at delivery blocks the last backdoor
paths connecting the outcome and the exposure via maternal age at arrival, which is not
necessary for confounding control. Although it is not recommended to adjust for colliders
because this creates an association between their common causes, adjusting for maternal age at
delivery without adjusting for parity would remove the influence of maternal age of delivery on
parity, and thus parity would no longer be a collider, making it necessary to control for parity to
block the backdoor path PTB – parity – age at arrival – duration of residence. Hence, adjustment
for both maternal age at delivery and parity is necessary. Adjustment for infant sex is not
necessary because there was no association between this and any other variable in the graph and
therefore no backdoor path through this variable. This also meets the conventional criteria for
confounding in that a potential confounder is associated with both the exposure and outcome.
168
Finally, neighbourhood deprivation is associated with length of residence (Table 1 of Chapter 3).
It could also be hypothesized to be associated with age, language, education, and marital status.
However, as these covariates are included in the adjusted model any backdoor path connecting
neighbourhood deprivation with duration of residence through these variables has been blocked.
References
(1) Greenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research. Epidemiology. 1999;10(1):37-
48.
(2) Jewel NP. Statistics in Epidemiology. Boca Raton: Chapman & Hall/CRC; 2004.
169
Appendix 3.E. Using a Cohort Approach to rule out Confounding by Cohort Effects
One alternative way of ruling out confounding by cohort effects is using a “cohort approach”.
This involves the selection of a group of immigrant women who arrived early in the study period
(landed in calendar years 1985-1988 = arrived before JAN 1 1989) so they can be followed over
time and thus ascertain their birth outcomes, compared with their non-immigrants counterparts.
As birth data span up to fiscal 2006/07, the sample size is large enough to assess duration of
residence in Canada in 5-year groups with a group composed of women 15 years and more,
which has not been done before for birth outcomes. One limitation of this approach, however,
given our data, is that birth outcomes are ascertained over 19 years (from fiscal 1988/89 to
2006/07) with the inherent problems of changing coding schemes ( ICD-9 to ICD-10-CA) and
the related issue of secular trends in the selected outcomes, which are well documented in
Ontario and elsewhere for preterm birth. Other limitations are that it is not possible to assess very
preterm birth (VPTB), moderately preterm birth (MPTB), and small for gestational age (SGA),
or to control for parity before the redesign of the DAD in fiscal 2002/03.
N Selection criteria
2,361,427 Birth records matched to a mother fiscal 1988-2006
↓ Keep those infant born within 2001 CMAs
1,802,398
↓ Exclude multiple births and stillbirths
1,752,103
↓ Keep only those mothers arriving in 1985-1988 (calendar)
1,509,962
↓ Exclude live births weighting less than 500 (due to increased
registration of near viable births) and more than 6000 g (and likely
170
N Selection criteria
data errors)
1,508,266
↓ Exclude infants born to mothers that had never been registered to
OHIP up until ‘31MAR2001’ (last date in the LIDS + 3-month
waiting period). These may be migrants arriving after ‘31DEC2000’
(last date in the LIDS) or interprovincial migrants. As these do not
appear in the available LIDS data, we do not want them to be
misclassified as ‘non-immigrants’
1,399,893
↓ Exclude records with missing data on infant sex or maternal age (not
parity)
1,399,870
↓ Exclude records with missing data on immigration characteristics
1,399,178
↓ Exclude immigrants classified as “OTHER” (i.e., other than ‘family’,
‘economic, or ‘refugee’)
1,399,043 Population size for analyses (immigrants = 69,522 and Canadian-
born/long-term residents = 1,329,521)
Table 3.E.1: Immigrants, by world region, versus non-immigrants
N LBW VLBW MLBW PTB Small PTB
Non-immigrants 1,329,521 4.23 0.62 3.60 5.03 2.72
Immigrants 69,522 5.53 0.96 4.58 5.37 3.49
Central & East Europe 1,419 4.37 1.06 3.31 4.23 3.03
Latin America & Caribbean 24,084 6.76 1.36 5.41 6.62 4.55
Middle East & North Africa 2,917 4.05 0.86 3.19 4.01 2.37
East Asia/Pacific 10,073 5.52 0.54 4.98 5.45 3.21
South Asia 9,699 6.30 0.92 5.38 5.02 3.56
Sub Saharan Africa 4,259 6.97 1.64 5.33 6.43 4.51
Industrialized Countries 17,071 3.37 0.50 2.86 3.83 2.09
Please compare Table 3.E.1 with Table 3.1 of the results section (Chapter 3).
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Table 3.E.2. Odds Ratios* (and 85% confidence intervals) for Immigrants, by world region, versus non-
immigrants LBW VLBW MLBW PTB Small PTB
All Immigrants 1.33 (1.28-1.37) 1.54 (1.42-1.67) 1.28 (1.24-1.33) 1.13 (1.10-1.17) 1.30 (1.25-1.36)
By World region
Central & East Europe 1.05 (0.81-1.35) 1.72 (1.03-2.86) 0.93 (0.69-1.24) 0.89 (0.69-1.15) 1.14 (0.84-1.54)
Latin America & Caribbean 1.61 (1.53-1.69) 2.16 (1.93-2.42) 1.50 (1.41-1.58) 1.37 (1.30-1.45) 1.69 (1.59-1.79)
Middle East & North Africa 0.96 (0.80-1.16) 1.38 (0.93-2.05) 0.89 (0.72-1.10) 0.83 (0.69-1.00) 0.88 (0.69-1.12)
East Asia & Pacific 1.31 (1.20-1.43) 0.83 (0.64-1.09) 1.39 (1.27-1.53) 1.12 (1.03-1.23) 1.17 (1.05-1.31)
South Asia 1.56 (1.44-1.69) 1.53 (1.24-1.89) 1.55 (1.42-1.70) 1.09 (1.00-1.20) 1.37 (1.23-1.53)
Sub Saharan Africa 1.72 (1.53-1.94) 2.67 (2.11-3.39) 1.53 (1.34-1.75) 1.37 (1.21-1.55) 1.72 (1.48-1.99)
Industrialized Countries 0.80 (0.74-0.87) 0.82 (0.66-1.02) 0.80 (0.73-0.88) 0.81 (0.75-0.87) 0.78 (0.71-0.87)
* adjusted for maternal age, infant sex and fiscal year
Table 3.E.3. Number and percentage of low birthweight (LBW), preterm birth (PRT), and small for
gestational age (SGA), among residents of Ontario Census Metropolitan Areas, non-immigrants and
immigrants (arrived 1985-1988) by duration of residence in Canada, (births 1988/89 to 2006/2007) Immigrants by duration of residence
outcome Non-imm All imm < 5 y 5 – 9 y 10 -14 y 15 + y p-trend*
N 1,329,521 69,522 19,703 24,195 15,227 10,397
LBW % 4.23 5.53 4.99 5.07 6.25 6.61 <.0001
VLBW 0.62 0.96 0.75 0.90 1.12 1.24 <.0001
MLBW 3.60 4.58 4.24 4.17 5.12 5.37 <.0001
PTB % 5.03 5.37 4.21 4.69 6.34 7.74 <.0001
Small PTB 2.72 3.49 2.91 3.12 4.14 4.46 <.0001
* Cochran-Armitage Trend test (2-sided)
Please compare Table 3.E.3 with Table 3.1 of Chapter 3.
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Table 3.E.4. Odds Ratios* (and 95% CI) comparing immigrants by duration of residence versus non-
immigrants
Immigrants by duration of residence versus non-immigrants*
Outcome <5 y 5 – 9 y 10 -14 y 15 + y
LBW % 1.20 (1.12-1.28) 1.23 (1.16-1.30) 1.49 (1.39-1.59) 1.55 (1.43-1.68)
VLBW % 1.27 (1.07-1.49) 1.48 (1.30-1.70) 1.73 (1.49-2.02) 1.84 (1.54-2.19)
MLBW % 1.18 (1.10-1.27) 1.18 (1.10-1.26) 1.43 (1.33-1.54) 1.48 (1.36-1.62)
PTB % 1.04 (0.97-1.11) 1.04 (0.98-1.10) 1.22 (1.14-1.30) 1.28 (1.19-1.38)
Small PTB% 1.13 (1.04-1.23) 1.19 (1.11-1.28) 1.50 (1.38-1.62) 1.55 (1.41-1.70)
*adjusted for infant sex, maternal age, and fiscal year.
Table 3.E.5. Odds Ratios* (and 95% CI) comparing immigrants by duration of residence
Immigrants by duration of residence*
Outcome <5 y 5 – 9 y 10 -14 y 15 + y p-trend
LBW % 1.00 1.04 (0.94-1.15) 1.29 (1.11-1.50) 1.39 (1.12-1.73) 0.0011
VLBW % 1.00 1.11 (0.87-1.42) 1.26 (0.88-1.80) 1.30 (0.78-2.15) 0.2587
MLBW % 1.00 1.03 (0.92-1.15) 1.29 (1.10-1.52) 1.41 (1.11-1.78) 0.0022
PTB % 1.00 1.03 (0.92-1.15) 1.24 (1.06-1.45) 1.38 (1.11-1.72) 0.0028
Small PTB% 1.00 1.07 (0.94-1.22) 1.37 (1.14-1.66) 1.47 (1.13-1.92) 0.0016
*adjusted for infant sex, maternal age, immigrant class, region of birth, language knowledge, high school graduation, unmarried
status, and fiscal year.
Please compare Table 3.E.4 with Table 3.2 of Chapter 3.
Please compare Table 3.E.5 with Table 3.3 of Chapter 3.
Because of the cohort approach, we also adjusted for year of birth to take account of the secular
increases in preterm birth over the last two decades.
Despite some differences in the methodology (different population, different comparison group,
changes in coding, and no adjustment for parity) these results are quite close to the main results
and support the same conclusions, particularly regarding the effects of duration of residence,
which are the focus here.
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Appendix 4.A. Cross classified random effects model (CCREM)
The unconditional CCREM can be written as follows:
Yijk = θ000 + b0j0 + c00k + eijk
b0j0 ~ N(0, τb002), c00k ~ N(0, τc00
2), eijk ~ N(0, σ2) (equation 1)
Where Yijk is the birth weight of infant i whose mother lives in neighborhood j and comes from
country k
θ000 is the overall mean birth weight for all infants
b0j0 is the random main effect of neighborhood j, that is, the contribution of neighborhood j
averaged over all countries
c00k is the random main effect of country k
eijk is the deviation of infant ijk’s birth weight from the cell mean; that is, the difference between
the birth weight of infant i and the mean birth weight of the infants born to mothers living in
neighborhood j and immigrating from country k.
Note that if one of the random effects b0j0 or c00k is equal to zero then they drop out of the
equation and the cross-classified model reduces to a standard two-level model. The combined
model with predictors (fixed-effects) can be written as follows:
Yijk = θ000 + Xβi + Xβj + Xβk + b0j0 + c00k + eijk ,
eijk ~ N(0, σ2) (equation 2)
where Xβi is a vector of predictors at the individual-level,
Xβj is a vector of predictors at the neighborhood-level,
and Xβk is a vector of predictors at the country-level.
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Copyright Acknowledgements
Chapter 4 “The Interplay between Immigrants’ Country of Birth and Neighbourhood Deprivation
on Birth Outcomes” is prepublication version of the article “Neighborhood Context and Infant
Birthweight Among Recent Immigrant Mothers: A Multilevel Analysis”, published in the
American Journal of Public Health, February 2009, Vol 99, No. 2, 285-293.
Permission granted by The American Public Health Association (APHA) to use the material in
this thesis is enclosed below.