Neighborhood risk factors for low birthweight in Baltimore: A multilevel analysis

Objectives. Past research on low birthweight has focused on individual-level risk factors. We sought to assess the contribution of macrolevel social factors by using census tract-level data on social stratification, community empowerment, and environmental stressors. Methods. Census tract-level information on social risk was linked to blah certificate records from Baltimore, Md, for the period 1985 through 1989, Individual-level factors included maternal education, maternal age, medical assistance health insurance (Medicaid), and trimester of prenatal care initiation. Methods of multilevel modeling using two-stage regression analyses were employed. Results. Macrolevel factors had both direct associations and interactions with low birthweight. All individual risk factors showed interaction with macroleveI variables; that is, individual-level risk factors for low birthweight behaved differently depending upon the characteristics of the neighborhood of residence, For example, women living in high-risk neighborhoods benefited less from prenatal care than did women living in lower-risk neighborhoods. Conclusions. Multilevel modeling is an important tool that allows simultaneous study of macro- and individual-level risk factors. Multilevel analyses should play a larger role in the formulation of public health policies.