The study of group-level factors in epidemiology: rethinking variables, study designs, and analytical approaches.

A key notion that has received much attention in epidemiology over the past few years has been that not all disease determinants can be conceptualized as individual-level attributes, hence the need to consider features of the groups to which individuals belong when studying the causes of ill health. This has led epidemiologists and public health researchers to rethink the ideas on ecologic studies and ecologic variables traditionally espoused in epidemiology (1–6). This reconceptualization of ecologic or group-level variables has been manifested, for example, in recent interest and debate on the possible health effects of group-level constructs, such as income inequality (7, 8), social capital (9, 10), and neighborhood characteristics (11–14). In this context, the advent of the statistical technique of multilevel models has been viewed as especially promising because of its ability to incorporate both group-level and individuallevel predictors in the study of health (4, 15–17). The idea that factors beyond individuals, referred to as group-level, ecologic, macro-level, or population-level factors (1, 3, 5, 18, 19), are important to health is not new. Two well-known examples include the concept of herd immunity in infectious diseases and Rose’s distinction between the causes of cases and the causes of incidence rates in chronic diseases. Herd immunity implies that a person’s likelihood of contracting an infectious disease depends in part on the level of immunity in the population to which he or she belongs (20). In his seminal paper, “Sick Individuals and Sick Populations,” Geoffrey Rose (18) discusses a related concept: the idea that studies that focus on what distinguishes sick individuals from healthy individuals within a population or group may miss important disease determinants. This is because population-level factors are invariant within a population and, hence, cannot be investigated in studies restricted to comparisons of individuals within a population (21). To detect these factors, researchers need studies that compare different populations (or groups) and investigate population-level (or group-level) factors. Discussions of group-level and individual-level factors in epidemiology are sometimes interpreted as implying that population-level factors are important in understanding between-population differences and that individual-level factors are important in understanding between-individual differences. A key point, however, is that factors at multiple levels may be important to understanding the causes of variability within a level. For example, both individual-level and group-level factors are important in understanding the causes of between-population differences in disease rates. Likewise, both population-level and individual-level factors are important in understanding the causes of disease in individuals. For example, herd immunity, a group-level property, is important in understanding not only the reasons for group differences in the incidence of disease but also an individual’s probability of contracting the disease. Group-level or population-level factors, such as the mass production of foods, may be important in understanding not only betweencountry differences in rates of hypertension but also the causes of hypertension in an individual. Of course, only individual-level factors will explain interindividual differences in outcomes within groups (18, 21). Although discussion of the importance of group-level or population-level factors has long been present in epidemiology, the interest in empirically testing for group effects in epidemiologic studies is relatively new. This interest has recently motivated many methodological discussions on the uses and misuses of ecologic variables and the strengths and limitations of multilevel models (1, 2, 4, 15, 22–24). This review will summarize selected issues related to the use of ecologic variables, ecologic studies, and multilevel studies in epidemiology. It will conclude with a discussion of the new challenges raised by the emerging multilevel paradigm. The focus will be on basic conceptual and methodological issues, rather than on specific empirical applications.