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 oil social stratification, community empowerment, and environmental stressors. Methods: Census tract-level information on social risk was linked to birth 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 macrolevel 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.