Methods for summarizing the risk associations of quantitative variables in epidemiologic studies in a consistent form.

A major problem in reviewing the published results of different epidemiologic studies of the relation between a quantitative variable and the risk of disease is that the results are presented in many different ways. The purpose of this paper is to exemplify methods by which results expressed either as risks (or rates) according to quantlle groups of the quantitative variable or as results derived from a logistic regression analysis can be reexpressed in a uniform manner, as a mean difference in the quantitative variable between the cases of disease and the other subjects in the study. An important assumption of the methods is that the quantitative variable has an approximately normal distribution, and a way of investigating the appropriateness of this assumption is given. The methods can be applied to both prospective and case-control studies and are exemplified by a number of studies of serum albumin concentrations and mortality. In some applications, these methods can be used as a precursor to formal meta-analysis, for example, when differential control of potential confounding factors is not a problem. At the least, the methods can be useful either in quantitatively reviewing published studies before undertaking new research or in putting the results of a new study into the context of previously published ones.