Effects of disease-dependent changes of exposure in cross-sectional studies

The possibility of disease-related changes in exposure is a major limitation of many epidemiologic studies. This limitation particularly applies to cross-sectional studies, in which exposure and presence of disease are measured at the same point of time. In some cross-sectional studies, attempts are made to collect information not only on current exposure, but also on exposure at some period in the past. Various methods have been proposed to assess the relation of past and current exposure with disease in such situations. Systematic methodologic work is lacking, however, on the performance of these methods in the presence of disease-related changes of exposure. In this paper, we provide a model to assess the effects of such changes, and we illustrate the effects with a variety of numerical examples. We show that all of the proposed methods can yield seriously biased measures of current exposure effects in the presence of disease-related changes in exposure, and we illustrate the direction and order of magnitude of the biases. Our results imply that there is usually no alternative to longitudinal approaches to measure exposure in relation to disease onset if disease-related changes of exposure are of concern.