Young maternal age and low birth weight risk: An exploration of racial/ethnic disparities in the birth outcomes of mothers in the United States

This research is based on work supported by a grant from the Department of Health and Human Services, Office of Public Health Service (#1 APRPA006015-01-00). A previous version of this work was presented at the 2009 Southern Demographic Association meetings. The authors thank Professor Richard Jessor for his contributions and work on this project.

Abstract

This study considers how low birth weight (LBW) prevalence varies by race/ethnicity and maternal age and explores mechanisms that explain disparities. Results show that maternal age patterns in LBW risk for African Americans differ from Whites and foreign- and U.S.-born Hispanics. Background socioeconomic disadvantage, together with current socioeconomic status and smoking during pregnancy, explain almost all of the LBW disparity between white teenage mothers and their older counterparts. These findings suggest that social disadvantage is a primary driver in unfavorable birth outcomes among white teenage mothers compared to older white mothers. Alternatively, background disadvantage and other social characteristics explain very little of the LBW disparities among African Americans and U.S.- and foreign-born Hispanics. Overall, these results indicate LBW disparities by maternal age are a complex product of socioeconomic disadvantage and current social and behavioral factors, such that LBW risk does not operate uniformly by race/ethnicity or maternal age.

Keywords:

• Low birth weight
• Maternal age
• Race/ethnicity
• Weathering hypothesis

Notes

This research is based on work supported by a grant from the Department of Health and Human Services, Office of Public Health Service (#1 APRPA006015-01-00). A previous version of this work was presented at the 2009 Southern Demographic Association meetings. The authors thank Professor Richard Jessor for his contributions and work on this project.

1 All N's are rounded to nearest 50 to accommodate data security restrictions.

2 Odds obtained by exponentiating logistic regression coefficients, e.g., in Model 2: = e^(0.48) = 1.62.

3 = e^{(0.48−0.12)} = 1.43.