Multilevel analysis in public health research

Over the past few years there has been growing interest in considering Fact ors defined at multiple levels in public health research. Multilevel analys is has emerged as one analytical strategy that may partly address this need , by allowing the simultaneous examination of group-level and individual-le vel factors. This paper reviews the rationale for using multilevel analysis in public health research, summarizes the statistical methodology, and hig hlights some of the research questions that have been addressed using these methods. The advantages and disadvantages of multilevel analysis compared with standard methods are reviewed. The use of multilevel analysis raises t heoretical and methodological issues related to the theoretical model being tested, the conceptual distinction between group- and individual-level var iables, the ability to differentiate "independent" effects, the reciprocal relationships between factors at different levels, and the increased comple xity that these models imply. The potentialities and limitations of multile vel analysis, within the broader context of understanding the role of facto rs defined at multiple levels in shaping health outcomes, are discussed.