differences, or those variables can be controlled for in the analysis. The odds of exposure to the agent among cases are then compared with the odds of exposure among controls. The comparison generates an odds ratio, which is a statistic that depicts the odds that those exposed to the agent in question will have a health effect relative to the odds that those not exposed will have the health effect. An odds ratio greater than 1 indicates that there is a potential association between exposure to the agent and the health effect; the greater the odds ratio, the stronger the association.
Case-control studies are useful for testing hypotheses about the relationships between exposure to specific agents and a health effect. They are especially useful and efficient for studying the etiology of rare effects. Case-control studies have the advantages of ease, speed, and relatively low cost. They are also valuable for their ability to probe multiple exposures or risk factors. However, case-control studies are vulnerable to several types of bias, such as recall bias, which can dilute or enhance associations between exposure and a health effect. Other problems include identifying representative groups of cases, choosing suitable controls, and collecting comparable information about exposures of cases and controls. Those problems might lead to unidentified confounding variables that differentially influence the selection of cases or control subjects or the detection of exposure. For the reasons discussed above, case-control studies are often the first approach to testing a hypothesis about whether factors contribute to a specific health effect, especially a rare one.
A “nested” case-control study draws cases and controls from a previously defined cohort. Thus, it is said to be nested in a cohort study. Baseline data are collected at the time that the cohort is identified, and this ensures a more uniform set of data on cases and controls. Members of the cohort who are identified as having a health effect serve as cases, and a sample of those who are effect-free serve as controls. Baseline data are used to compare exposure in cases and controls, as in a regular case-control study. Nested case-control studies are efficient with respect to the time and cost needed to reconstruct exposure histories of cases and of only a sample of controls rather than the entire cohort. In addition, because the cases and controls come from the same previously established cohort, concerns about unmeasured confounders and selection bias are decreased.
The main differentiating feature of a cross-sectional study is that exposure information and health-effect information are collected at the same time. The selection of people for the study—unlike selection for cohort and case-control studies—is independent both of the exposure to the agent in question and of health-effect characteristics. Cross-sectional studies seek to uncover potential associations between exposure to a specific agent and development of a health effect. In a cross-sectional study, effect size is measured as relative risk, preva-