Reducing socioeconomic disparities in health has been an important goal of public health in many countries. It is therefore of interest for both the general public and public health policymakers to be aware of these disparities and how they may have changed over time. For instance, the persistent black-white gap in infant mortality in the United States has led to call for focused efforts to reduce the disparities.1 It is unclear how disparities in birth outcomes by either individual- or neighborhood-level socioeconomic status have changed over time in Canada, which enjoys general favorable socioeconomic conditions and where a universal health insurance system has been in place for more than 3 decades.
Living in disadvantaged neighborhoods has been associated with a wide range of poor health outcomes in general,2–8 and higher risks of preterm birth, low birth weight, and infant mortality in particular9–18; moreover, the effects appear independent of individual-level socioeconomic characteristics.10,12,14 However, virtually all previous studies on disparities in birth outcomes by neighborhood socioeconomic measures have been cross-sectional and limited to a single birth outcome such as infant mortality or low birth weight.9–18 The overall patterns of birth outcomes by neighborhood socioeconomic status remain uncharted, as do changes in these patterns over time. In addition, studies on birth outcomes by neighborhood socioeconomic status have been limited to urban areas with little or no information available on these disparities in rural areas.
The goal of our study was to assess temporal trends in disparities in birth outcomes by neighborhood income in urban compared with rural areas. We carried out the study in British Columbia because this province has fairly complete recording of postal codes (98%) on birth registrations for defining small area-based neighborhoods.
We identified a cohort of all 713,950 births registered in British Columbia, Canada, from 1985 through 2000, using the linked stillbirth/live birth/infant death database of the British Columbia Vital Statistics Agency.19 We used vital records from 1985 onward because postal codes for the mother's place of residence, which were used to determine the small area-based neighborhood in which she lived, were unavailable on the machine-readable files of birth registrations before 1985.
Individual-level income data are not available on birth registrations in Canada. We created a small area-based neighborhood-income quintile variable to reflect the socioeconomic status of the neighborhoods in which the mothers lived. Neighborhood-income quintiles were derived from the household size-adjusted average family income of each enumeration area relative to other enumeration areas within the same census metropolitan area or census agglomeration using the Canadian census data from the closest census years (1986, 1991, or 1996). The enumeration area is the smallest census geographic unit, typically consisting of 125 to 440 dwellings.20,21 We estimated the household size-adjusted income per single person equivalent for each enumeration area,21 then ranked enumeration areas within the same census metropolitan area or census agglomeration into 5 quintiles from Q1 (the richest) to Q5 (the poorest) according to the calculated income per single person equivalent. Each quintile contains approximately one fifth of the total population within each census metropolitan area or census agglomeration but not necessarily one fifth of all births. The neighborhood-income quintile was assigned to each birth based on the mother's place of residence as recorded on the birth certificate with neighborhoods determined through postal code linkage.22 Income was the only available enumeration area-level information regarding neighborhood socioeconomic status.
Of all 713,950 births recorded in 1985–2000, 16,473 (2%) could not be assigned a neighborhood-income quintile value because it was missing, incomplete, or invalid; because census income data were absent for the enumeration area; or because the postal code referred to a school or university residence. The number of births remaining for comparison across neighborhood-income quintiles was 697,477.
Community Size and Definition of Rural versus Urban
We created a community size variable to account for potential differentials in access to and quality of health care at the community level. This was based on the 1996 Canadian Census population figures for each census metropolitan area or census agglomeration (25 valid codes for British Columbia in 1996). These codes were obtained through postal code linkage for each birth based on the mother's residential address.22 All rural areas and small towns with a community size less than 10,000 persons were considered “rural”; all larger communities were defined as “urban” in accordance with Statistics Canada's recommended definition.20
Of the 697,477 births, 593,394 (85%) were urban and 104,083 (15%) were rural. Within urban areas, community size was further categorized into 3 strata (10,000–99,999, 100,000–499,999, and >500,000) in urban areas to account for possible differences in access to and quality of health care.
Distance to the Nearest Hospital With Obstetricians
Distance to the nearest hospital with obstetricians in British Columbia and the neighboring province of Alberta was calculated for each birth based on the residential postal code of the mother's address recorded on birth registrations and the postal code of the delivery hospital.23 Exploratory analyses suggested a higher risk of neonatal mortality for distance greater than 50 km. We therefore dichotomized the distance variable into 2 strata (<50 km vs. >50 km) to further account for potential differences in access to obstetric care.
Maternal and Pregnancy Characteristics
Several important maternal and pregnancy characteristics are recorded on the British Columbia Vital Statistics Agency's linked birth/infant death/stillbirth data files. The variables we examined were maternal age (<20, 20–34, ≥35 years), marital status (legally married or unmarried), abortion history (yes or no), infant sex, ethnicity of First Nations (the preferred term for North American Indians in Canada) or others among whom differences in risks of adverse birth outcomes were much smaller, parity (primiparous or multiparous), plurality (singleton or multiple), gestational age (in completed weeks), birth weight (in grams), maternal illness (presence or absence of diabetes, abnormal glucose tolerance, epilepsy, hypertension, preeclampsia, eclampsia, anemia, thyroid dysfunction, or renal or liver disorders), and mode of delivery (spontaneous or instrumental—the latter including cesarean section, forceps, or vacuum extraction). Exploratory analyses suggested underreporting of maternal illness during pregnancy (prevalence was lower than expected); however, exclusion of this variable had virtually no impact on the adjusted risk estimates of outcomes, and so the variable has been retained in all multivariate analyses.
Outcomes and Statistical Analyses
Main outcomes included rates of preterm birth (gestational age <37 completed weeks), small-for-gestational-age (SGA, <10th percentile, based on a recently published Canadian standard24), stillbirth (≥20 completed weeks), and neonatal (0–27 days) and postneonatal (28–264 days) mortality. Outcomes were compared across neighborhood-income quintiles and by 4-year intervals (1985–1988, 1989–1992, 1993–1996, and 1997–2000) to assess trends over time. Causes of neonatal and postneonatal death were investigated using the classification of the International Collaborative Effort on Perinatal and Infant Mortality.25
We compared rates of outcomes across neighborhood-income quintiles using chi-squared tests. Crude relative risks (RRs) of adverse birth outcomes were examined using the richest neighborhood-income quintile (Q1) as the reference. To provide a summary measure for trends across neighborhood-income quintiles, we estimated odds ratios (ORs) for characteristics or outcomes per change in neighborhood-income quintile by logistic regression using neighborhood-income quintile as a continuous variable. We estimated the adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for adverse outcomes in the poorest compared with the richest neighborhood-income quintiles using logistic regression analysis to control for infant sex, parity, plurality, ethnicity, maternal age, marital status, abortion history, mode of delivery, maternal illness, community size, and distance to the nearest hospital with obstetricians. We also examined the adjusted ORs by multilevel logistic regression analysis using the GLMM800 macro in SAS (SAS Institute, Cary, NC); virtually identical adjusted ORs were observed (owing to very low intraclass correlations), and therefore the results presented are based on ordinary (individual-level) logistic regression analysis.
The absolute income differences across neighborhood-income quintiles were larger in urban than in rural areas (Table 1). The relative income disparities across neighborhood-income quintiles declined in rural areas but rose in urban areas over the 3 census years (1986, 1991, and 1996). In rural areas, the ratios of the median income per single person equivalent for the poorest versus the richest neighborhood-income quintiles rose from 53% in 1986 to 63% in 1996; in urban areas, it declined from 51% to 46%.
Substantial differences in maternal and pregnancy characteristics were observed across neighborhood-income quintiles in both rural and urban areas (Table 2); mothers living in poorer neighborhoods were more likely to be of First Nations ethnicity, unmarried, under 20 years of age, and with a maternal illness, and were less likely to be 35 years of age or older and to have an instrumental delivery. In urban areas, a higher proportion of mothers in poorer neighborhoods lived in areas for which distance to the nearest hospital with obstetricians was more than 50 km. In rural areas, however, the pattern was not monotonic; the highest proportion was observed for mothers in the richest neighborhood-income quintile.
In urban areas, we found moderate disparities in rates of preterm, SGA, stillbirth, and neonatal and postneonatal mortality across neighborhood-income quintiles (Table 3). The disparities showed clear trends in risk across neighborhood-income quintiles in urban areas. The largest disparities in birth outcomes were observed between the poorest and the richest neighborhood-income quintiles; the disparities among the middle 3 quintiles were much smaller. In rural areas, the disparities in birth outcomes were smaller and showed no consistent risk gradients across neighborhood-income quintiles, except for preterm birth. The difference in preterm birth rates in rural areas was not monotonic across neighborhood-income quintiles, however, and was mainly observed for the poorest compared with the richest neighborhoods.
In urban areas, analyses of causes of death revealed a higher risk of neonatal death resulting from asphyxia (RR = 1.60; 95% CI = 1.05–2.46) and a higher risk of postneonatal death resulting from sudden infant death syndrome (SIDS) (2.38; 1.75–3.15), infection (2.11; 0.99–4.77), and external causes (2.09; 1.12–3.90) for the poorest compared with the richest neighborhoods. No differences were apparent for congenital anomalies or other causes of death during either the neonatal or postneonatal periods. The crude risk difference for the poorest versus the richest neighborhoods was largest for SIDS (0.9 per 1000 neonatal survivors; 95% CI = 0.7–1.2) among all causes of infant death. In rural areas, there were no apparent differences in cause-specific neonatal and postneonatal mortality for the poorest and the richest neighborhoods for any of these causes.
In urban areas, neonatal and postneonatal mortality rates declined substantially across all neighborhood-income quintiles from 1985–1988 to 1997–2000 (Table 4). However, moderate disparities in preterm birth, SGA, and postneonatal mortality rates persisted across neighborhood-income quintiles from 1985–1988 to 1997–2000. We observed a clear trend of higher risks of preterm birth, SGA, and postneonatal death in poorer neighborhood-income quintiles. Disparities in stillbirth rates were apparent across neighborhood-income quintiles only in 1993–1996. Disparities in neonatal mortality rates were apparent in the periods 1989–1992 and 1997–2000 only. In rural areas, disparities in all observed birth outcomes were small and showed no consistent trends across neighborhood-income quintiles for any period, except for preterm birth in 1997–2000 (results available on request).
There was no temporal decrease in crude RR for any adverse birth outcome in the poorest compared with the richest neighborhoods in urban areas (Table 4). The crude RRs for postneonatal death for the poorest versus the richest neighborhood-income quintiles actually rose from 1.61 (1.17–2.20) to 2.20 (1.24–3.92) from 1985–1988 to 1997–2000. The crude RRs showed little fluctuation over time for preterm, SGA, stillbirth, or neonatal death; for instance, the crude RR (95% CI) for the poorest versus the richest neighborhoods was 1.44 (1.37–1.52) for SGA in 1985–1988 versus 1.41 (1.33–1.49) in 1997–2000. In rural areas, we found no elevated risks of adverse outcomes in the poorest versus the richest neighborhood-income quintiles in any period, except for preterm birth for the periods 1989–1992 and 1997–2000 (results available on request).
In urban areas, the adjusted ORs of adverse birth outcomes for the poorest versus the richest neighborhoods followed a pattern similar to that of the crude RRs (Table 4). The adjusted risk estimates were lower than the crude RRs for postneonatal mortality but were similar to the crude RRs for other adverse birth outcomes. The adjusted ORs did not decline over time for any adverse birth outcome and actually rose slightly for stillbirth and postneonatal death. In rural areas, we observed no elevated risks of adverse birth outcomes for the poorest versus richest neighborhood-income quintiles after these adjustments, except for preterm birth for 1997–2000 (results available on request).
We observed modest and persistent disparities in birth outcomes by neighborhood income over time in urban but not rural areas of British Columbia despite a universal health insurance system and general favorable socioeconomic conditions. The largest disparities were observed between the poorest versus the richest neighborhoods. Disparities were particularly apparent in preterm birth, SGA, and postneonatal mortality and did not diminish over time.
It is noteworthy that similarly large disparities in maternal characteristics across neighborhood-income quintiles were observed in both rural and urban areas, yet the differences for virtually all birth outcomes in rural areas were insignificant and showed no trends across neighborhood-income quintiles. The observed trend in disparities (Table 3) may well reflect the smaller and narrowing differences in income across neighborhood-income quintiles in rural areas (Table 1). The increasing relative income disparities across neighborhood-income quintiles in urban areas coincided with increasing crude RRs for postneonatal mortality for the poorest compared with the richest neighborhoods. These observations suggest a strong association of neighborhood income with the risks of adverse birth outcomes in urban areas, presumably because disparities across social gradients are larger in urban areas.
The adverse effects of poorer neighborhoods were strongly associated with SGA (a proxy for restricted fetal growth) and preterm delivery, even after accounting for potentially confounding maternal and pregnancy characteristics. Preterm birth and SGA have been associated with many adverse long-term health consequences,26,27 suggesting that the impact of living in poor neighborhoods may extend well beyond infancy. Mothers living in poor neighborhoods may be more stressed during pregnancy and less effective in their use of healthcare resources.28–30
The reductions in neonatal and postneonatal mortality across all neighborhood-income quintiles from 1985–1988 to 1997–2000 are likely attributable to improvements in general socioeconomic conditions and health care (eg, maternal antenatal steroids, surfactant therapy). Most of the disparities in postnatal mortality was the result of preventable causes of death (SIDS, infection, and external causes), suggesting that improvements in infant care are needed in poor neighborhoods.
The Canadian progressive income tax system reduces income inequalities in Canada to a greater extent than in the United States.31,32 However, even within Canada, income disparities have not diminished and in fact may have widened in recent years.32–34 We would expect similar trends in disparities in birth outcomes by neighborhood income in urban areas elsewhere in Canada, although comparable data from other provinces are unavailable. We further speculate that even larger disparities would be observed across neighborhood-income quintiles in settings such as the United States, where income inequalities and neighborhood segregation are more pronounced and there is no universal health insurance system.
Neighborhood income measures are derived from individual-level measures (usually based on census data). This presents a challenge for interpretation, even with use of multilevel statistical models,35 because community- and individual-level measures are strongly correlated. It is thus difficult to tell whether the effects of a neighborhood socioeconomic measure are “contextual” or merely reflect the aggregate impact of individual-level socioeconomic status, or represent a combination of contextual and individual effects.29,35 Although some studies have suggested that the effects of neighborhood socioeconomic measures on birth outcomes are independent of individual-level socioeconomic status,10,12,14 we are unable to make these distinctions. Poor neighborhoods are strongly associated with many other adverse neighborhood socioeconomic characteristics such as higher prevalence of unemployment and low educational attainment.17 Furthermore, rich neighborhoods in most cities have better living environments, including less crime, noise, and exposure to industrial wastes. Neighborhood-income quintile may be therefore a surrogate measure of broad neighborhood socioeconomic status, partly reflecting the aggregated effects of broad neighborhood socioeconomic characteristics. The risk ratios of adverse health outcomes for the poorest versus the richest neighborhood-income quintiles may serve as a good indicator of socioeconomic disparities in health at the community level. Interpretation and intervention need to consider the broad socioeconomic and political contexts; more resources for improved living environments in poor areas may be a key.
Both absolute and relative income measures in relation to health outcomes have been examined, and health status appears more sensitive to relative measures, at least in developed countries.4,28,29 Neighborhood-income quintile is a relative measure of socioeconomic status of a small neighborhood within a large area. Its method of calculation is novel, and its validity and use should be further investigated. It is based on the smallest census geographic unit and uses information for all households in the closest census years, and may have more precision and relevance in defining neighborhoods than measures used in previous studies (commonly, percent of low-income families in larger areas such as census tracts). The definition or size of “neighborhood” has been the subject to debate.35 We argue that much larger units such as county or metropolitan area may not adequately reflect important differences in neighborhood socioeconomic characteristics. However, some socioeconomic indices (such as measures of income inequality, ie, how income is distributed) are more relevant at higher geographic levels.4,18,35
Like in most Canadian population-based studies of birth outcomes using linked birth/death registration data, we did not have information on individual-level income, education, occupation, smoking, alcohol and drug use, or use of prenatal care. Disparities in unmeasured characteristics or risk behaviors could partly account for the disparities in birth outcomes across neighborhoods that were not explained by observed maternal and pregnancy characteristics. Such unmeasured health behaviors and individual-level income could mediate or confound the associations we observed between area-level poverty and pregnancy outcomes. This limitation should not, however, compromise the importance of the findings of persistent or even widening urban neighborhood disparities in birth outcomes. Social and psychologic stress, smoking, and inadequate infant care may all play a role and deserve further study. The much smaller disparities in rural compared with urban settings suggest that the most likely solutions may be policies and initiative directed to reducing income disparity itself through direct or indirect means such as increasing low-income family subsidies and maternal education and improving the living environment of poor neighborhoods.
We are grateful to the British Columbia Vital Statistics Agency and Statistics Canada for providing access to the data. We gratefully acknowledge the constructive comments provided by members of the Fetal and Infant Health Study Group of the Canadian Perinatal Surveillance System on a preliminary draft of the manuscript.
1.Singh GK, Yu SM. Infant mortality in the United States: trends, differentials, and projections, 1950 through 2010. Am J Public Health
2.Diez Roux AV, Mekin SS, Arnett D, et al. Neighborhood of residence and incidence of coronary heart diseases. N Engl J Med
3.Balfour JL, Kaplan GA. Neighborhood environment and loss of physical function in older adults: evidence from the Alameda County Study. Am J Epidemiol
4.Lynch J, Smith GD, Hillemeier M, et al. Income inequality, the psychosocial environment, and health: comparisons of wealthy nations. Lancet
5.Gwatkin DR. Health inequalities and the health of the poor: what do we know? What can we do? Bull World Health Organ
6.Adler NE, Ostrove JM. Socioeconomic status and health: what we know and what we don't. Ann N Y Acad Sci
7.Lynch JW, Kaplan GA, Pamuk ER, et al. Income inequality and mortality in metropolitan areas of the United States. Am J Public Health
8.Adler N, Boyce WT, Chesney MA, et al. Socioeconomic differences in health: no easy solution. JAMA
9.Wilkins R, Sherman GJ, Best PA. Birth outcomes and infant mortality by income in urban Canada 1986. Health Reports
10.Pickett KE, Ahern JE, Selvin S, et al. Neighborhood socioeconomic status, maternal race and preterm delivery: a case-control study. Ann Epidemiol
11.Orr ST, Blackmore-Prince C, James SA, et al. Race, clinical factors and pre-term birth in a low-income urban setting. Ethn Dis
12.O'Campo P, Xue X, Wang MC, et al. Neighborhood risk factors for low birthweight in Baltimore: a multilevel analysis. Am J Public Health
13.Crosse EA, Alder RJ, Ostbye T, et al. Small area variation in low birthweight: looking beyond socio-economic predictors. Can J Public Health
14.Pearl M, Braveman P, Abrams B. The relationship of neighborhood socioeconomic characteristics to birthweight among 5 ethnic groups in California. Am J Public Health
15.Szwarcwald CL, Andrade CL, Bastos FI. Income inequality, residential poverty clustering and infant mortality: a study in Rio de Janeiro, Brazil. Soc Sci Med
16.Pena R, Wall S, Persson LA. The effect of poverty, social inequity, and maternal education on infant mortality in Nicaragua, 1988–1993. Am J Public Health
17.Wilkins R, Berthelot JM, Ng E. Trends in mortality by neighbourhood income in urban Canada from 1971 to 1996. Health Rep.
2002;13(suppl):1–27. Ottawa: Statistics Canada, Catalogue 82-003-SIE.
18.Hales S, Howden-Chapman P, Salmond C, et al. National infant mortality rates in relation to gross national product and distribution of income. Lancet
19.British Columbia Vital Statistics Agency, First Nations and Inuit Health Branch of Health Canada. Analysis of Health Statistics for Status Indians in British Columbia, 1991–1998
. Vancouver: British Columbia Vital Statistics Agency; 2000.
20.Plessis V, Beshiri R, Bollman RD, et al. Definitions of rural. Rural
and Small Town Canada Analysis Bulletin
2001, vol 3, no 3. (Catalogue no. 21-006-XIE). Ottawa: Statistics Canada; 2001. Available at: http://www.statcan.ca
. Accessed February 20, 2003.
21.Statistics Canada. 1996 Census Dictionary
, final edition (Catalogue no. 92-301E). Ottawa: Statistics Canada; 1999.
22.Wilkins R. PCCF+ Version 3G User's Guide (Geocodes/PCCF). Automated Geographic Coding Based on the Statistics Canada Postal Code Conversion Files, Including Postal Codes to May 2002.
(Catalog no. 82F0086-XDB). Ottawa: Health Analysis and Modeling Group, Statistics Canada; July 2002.
23.Ng E, Wilkins R, Perras A. How far is it to the nearest hospital? Calculating distances using the Statistics Canada Postal Code Conversion File. Health Rep
24.Kramer MS, Platt RW, Wen SW, et al. A new and improved population-based Canadian Reference for birth weight for gestational age. Pediatrics
25.Cole S, Hartford RB, Bergsjo P, et al. International collaborative effort (ICE) on birthweight, plurality, perinatal, and infant mortality. Acta Obstet Gynecol Scand
26.Roth S, Chang TC, Robson S, et al. The neurodevelopmental outcome of term infants with different intrauterine growth characteristics. Early Hum Dev
27.Barker DJ. The fetal and infant origins of disease. Eur J Clin Invest
28.Adler NE, Newman K. Socioeconomic disparities in health: pathways and policies. Health Aff (Millwood)
29.Marmot M. The influence of income on health: views of an epidemiologist. Health Aff (Millwood)
30.Dunlop S, Coyte P, McIsaac W. Socio-economic status and the utilisation of physicians’ services: results from the Canadian National Population Health Survey. Soc Sci Med
31.Ross NA, Wolfson MC, Dunn JR, et al. Relation between income inequality and mortality in Canada and in the United States: cross sectional assessment using census data and vital statistics. BMJ
32.Wolfson MC, Murphy BB. New Views on Inequality Trends in Canada and the United States.
Analytical Studies Branch Research Paper Series No. 124 (Catalogue 11F0019MPE98124). Ottawa: Statistics Canada; 1998. Available at: http://www.statcan.ca
. Accessed February 20, 2003.
33.Myles J, Picot G, Pyper W. Neighbourhood Inequality in Canadian Cities.
Analytical Studies Branch Research Paper Series No. 160 (Catalogue no. 11F0019MPE00160). Ottawa: Statistics Canada; 2000. Available at: http://www.statcan.ca
34.Morissette R, Zhang X, Drolet M. The Evolution of Wealth Inequality in Canada, 1984–1999.
Analytical Studies Branch Research Paper Series No. 187 (Catalogue 11F0019MPE02187). Ottawa: Statistics Canada; 2002. Available at: http://www.statcan.ca
. Accessed February 20, 2003.
35.O'Campo P. Advancing theory and methods for multilevel models of residential neighborhoods and health. Am J Epidemiol