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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. <\/jats:p>","DOI":"10.2105\/ajph.87.7.1113","type":"journal-article","created":{"date-parts":[[2008,11,29]],"date-time":"2008-11-29T13:30:23Z","timestamp":1227965423000},"page":"1113-1118","source":"Crossref","is-referenced-by-count":347,"title":["Neighborhood risk factors for low birthweight in Baltimore: a multilevel analysis."],"prefix":"10.2105","volume":"87","author":[{"given":"P","family":"O'Campo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"X","family":"Xue","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M C","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M","family":"Caughy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"844","reference":[{"key":"p_1","unstructured":"McCormick M. 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