Tracey Bushnik1, Seungmi Yang2, Jay S Kaufman2, Michael S Kramer3, Russell Wilkins4. 1. Health Analysis Division, Statistics Canada, Ottawa, Ontario. 2. Department of Epidemiology, Biostatistics and Occupational Health, McGill University. 3. Departments of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University, and the McGill University Health Centre Research Institute. 4. Department of Epidemiology and Community Medicine, University of Ottawa.
Abstract
BACKGROUND: Maternal socioeconomic disadvantage has been associated with increased risk of small-for-gestational-age birth and preterm birth. Few studies, however, have considered maternal education and income simultaneously to better understand the mechanisms underlying perinatal health disparities. This analysis examines both maternal education and income and their association with the risk of small-for-gestational-age birth and preterm birth. DATA AND METHODS: The study is based on 127,694 singleton live births from the 2006 Canadian Birth-Census Cohort, a national cohort of births registered from May 2004 to May 2006 that were linked to the 2006 long-form Census. Unadjusted rates of small-for-gestational-age birth (sex-specific birth weight below the 10th percentile for gestational age) and preterm birth (before 37 completed weeks of gestation) were estimated across selected maternal characteristics. Logistic regression was used to estimate crude and covariate-adjusted risk ratios of both outcomes according to maternal education and income adequacy quintiles. RESULTS: Small-for-gestational-age birth was associated with both maternal education and income adequacy, while preterm birth was associated with maternal education only. These findings persisted after taking factors including maternal age, ethnicity, and marital status into account. The results suggest that the mechanism by which maternal education is associated with these outcomes is likely not through income, nor does income replace education as a potentially meaningful measure of socioeconomic position. INTERPRETATION: The mechanisms underlying associations between socioeconomic position and perinatal health disparities are complex. The results of this study indicate that more than one socioeconomic factor may play a role.
BACKGROUND: Maternal socioeconomic disadvantage has been associated with increased risk of small-for-gestational-age birth and preterm birth. Few studies, however, have considered maternal education and income simultaneously to better understand the mechanisms underlying perinatal health disparities. This analysis examines both maternal education and income and their association with the risk of small-for-gestational-age birth and preterm birth. DATA AND METHODS: The study is based on 127,694 singleton live births from the 2006 Canadian Birth-Census Cohort, a national cohort of births registered from May 2004 to May 2006 that were linked to the 2006 long-form Census. Unadjusted rates of small-for-gestational-age birth (sex-specific birth weight below the 10th percentile for gestational age) and preterm birth (before 37 completed weeks of gestation) were estimated across selected maternal characteristics. Logistic regression was used to estimate crude and covariate-adjusted risk ratios of both outcomes according to maternal education and income adequacy quintiles. RESULTS: Small-for-gestational-age birth was associated with both maternal education and income adequacy, while preterm birth was associated with maternal education only. These findings persisted after taking factors including maternal age, ethnicity, and marital status into account. The results suggest that the mechanism by which maternal education is associated with these outcomes is likely not through income, nor does income replace education as a potentially meaningful measure of socioeconomic position. INTERPRETATION: The mechanisms underlying associations between socioeconomic position and perinatal health disparities are complex. The results of this study indicate that more than one socioeconomic factor may play a role.
Authors: Sara K Redd; Whitney S Rice; Monica S Aswani; Sarah Blake; Zoë Julian; Bisakha Sen; Martha Wingate; Kelli Stidham Hall Journal: BMC Health Serv Res Date: 2021-10-22 Impact factor: 2.908
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