Invited commentary: Advancing theory and methods for multilevel models of residential neighborhoods and health.

In less than 10 years, the field of epidemiology has been transformed. During this time, multilevel modeling has gone from a little-known and perhaps even unwelcome method of analysis to a household name. Multilevel models appeared much earlier in the fields of demography, sociology of education, and criminology (refer, for example, to Raudenbush et al. (1), Mason et al. (2), and Nuttal et al. (3)), but public health and epidemiology have lagged behind in conceptualizing and measuring how contexts affect individual-level health risks and outcomes. The growth in the publication of multilevel studies has paralleled and contributed greatly to the reemergence of social epidemiologic research (4–11). Multilevel models assessing the effects of neighborhood residential environments on health outcomes have been the most common type of contextual study to date. Research has examined associations between neighborhood characteristics, frequently socioeconomic position, and a variety of health outcomes, including perinatal health (12– 15), mortality (16, 17), health behaviors (18, 19), women’s health (20, 21), heart disease (22–24), disability (25), and child health (26) among others. Furthermore, many reviews have been published concerning the statistical methods and rationale for, as well as the quality of, the existing multilevel studies on health (27–34). Yet, it is perhaps still premature to celebrate the exponential growth of multilevel epidemiologic studies on neighborhood residential effects on health. On the one hand, the growth in publication of these studies reflects increased interest in and support for social epidemiologic approaches. This increased support is encouraging in light of recent controversies about the legitimacy of social epidemiology as a subfield of epidemiology (35–40). On the other hand, these studies have emerged in public health and epidemiology without the appropriate theoretical and methodological foundations to guide their implementation. Hence, despite dozens of multilevel studies of neighborhoods and health, we still lack a clear picture of the intervention and policy implications of this body of work. In this issue of the Journal, Buka et al. (41) examine whether levels of neighborhood social support affect the birth weights of African-American and White mothers residing in Chicago, Illinois. Their paper contributes to the small, but growing literature on multilevel analyses of neighborhood residential effects on perinatal outcomes (12–15, 42). It offers several methodological advancements over previous multilevel studies on neighborhood residence and health. Moreover, it highlights additional theoretical and methodological challenges that multilevel analysis, given its recent appearance in public health, must overcome if significant gains are to be made in understanding disease etiology and designing appropriate interventions and policies to prevent adverse health. These theoretical and methodological issues are the topic of this commentary.