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      Bringing context back into epidemiology: variables and fallacies in multilevel analysis.

      American Journal of Public Health
      Epidemiologic Measurements, Humans, Models, Theoretical

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          Abstract

          A large portion of current epidemiologic research is based on methodologic individualism: the notion that the distribution of health and disease in populations can be explained exclusively in terms of the characteristics of individuals. The present paper discusses the need to include group- or macro-level variables in epidemiologic studies, thus incorporating multiple levels of determination in the study of health outcomes. These types of analyses, which have been called contextual or multi-level analyses, challenge epidemiologists to develop theoretical models of disease causation that extend across levels and explain how group-level and individual-level variables interact in shaping health and disease. They also raise a series of methodological issues, including the need to select the appropriate contextual unit and contextual variables, to correctly specify the individual-level model, and, in some cases, to account for residual correlation between individuals within contexts. Despite its complexities, multilevel analysis holds potential for reemphasizing the role of macro-level variables in shaping health and disease in populations.

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          Most cited references45

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          Choosing a future for epidemiology: II. From black box to Chinese boxes and eco-epidemiology.

          Part I of this paper traced the evolution of modern epidemiology in terms of three eras, each with its dominant paradigm, culminating in the present era of chronic disease epidemiology with its paradigm, the black box. This paper sees the close of the present era and foresees a new era of eco-epidemiology in which the deployment of a different paradigm will be crucial. Here a paradigm is advocated for the emergent era. Encompassing many levels of organization--molecular and societal as well as individual--this paradigm, termed Chinese boxes, aims to integrate more than a single level in design, analysis, and interpretation. Such a paradigm could sustain and refine a public health-oriented epidemiology. But preventing a decline of creative epidemiology in this new era will require more than a cogent scientific paradigm. Attention will have to be paid to the social processes that foster a cohesive and humane discipline.
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            The fallacy of the ecological fallacy: the potential misuse of a concept and the consequences.

            Ecological studies have been evaluated in epidemiological contexts in terms of the "ecological fallacy." Although the empirical evidence for a lack of comparability between correlations derived from ecological- and individual-level analyses is compelling, the conceptual meaning of the ecological fallacy remains problematic. This paper argues that issues in cross-level inference can be usefully conceptualized as validity problems, problems not peculiar to ecological-level analyses. Such an approach increases the recognition of both potential inference problems in individual-level studies and the unique contributions of ecological variables. This, in turn, expands the terrain for the location of causes for disease and interventions to improve the public's health.
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              Ecologic studies in epidemiology: concepts, principles, and methods.

              An ecologic study focuses on the comparison of groups, rather than individuals; thus, individual-level data are missing on the joint distribution of variables within groups. Variables in an ecologic analysis may be aggregate measures, environmental measures, or global measures. The purpose of an ecologic analysis may be to make biologic inferences about effects on individual risks or to make ecologic inferences about effects on group rates. Ecologic study designs may be classified on two dimensions: (a) whether the primary group is measured (exploratory vs analytic study); and (b) whether subjects are grouped by place (multiple-group study), by time (time-trend study), or by place and time (mixed study). Despite several practical advantages of ecologic studies, there are many methodologic problems that severely limit causal inference, including ecologic and cross-level bias, problems of confounder control, within-group misclassification, lack of adequate data, temporal ambiguity, collinearity, and migration across groups.
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                Author and article information

                Journal
                9491010
                1508189

                Chemistry
                Epidemiologic Measurements,Humans,Models, Theoretical
                Chemistry
                Epidemiologic Measurements, Humans, Models, Theoretical

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