{
  "abstract": "Objective Present methods to detect and evaluate confounding bias in epidemiologic studies.Methods Confounding is bias that arises when the exposure and outcome share a common cause. Confounding can lead to spurious associations away from or toward the null. Potential confounders can be identified a priori by looking at the literature, to see what others have identified as confounders. Confounders must not be confused with intermediate variables which are on the pathway between exposure and disease.Results Once identified, potential confounders can be controlled in the study design by matching (in either case–control or cohort studies), by stratifying on them in the analysis, or by their inclusion in a model where the outcome is regressed on exposure and potential confounders. Reviewers will need to assess how well potential confounders have been controlled. If there is likely uncontrolled confounding, a reviewer should assess the direction and magnitude of possible confounding bias. This can be done by 1) using negative control outcomes or negative control exposures, 2) triangulation, ie., considering different types of evidence from studies with different designs, or 3) quantitative bias adjustment, using a priori knowledge of the effect of a confounder on outcomes, as well as the likely prevalence of the exposure among exposed and non-exposed, to judge the likely effect of the confounder.Conclusion In some studies, investigators will have measured potential confounders and controlled for them in the design or analysis. Reviewers will want to consider whether residual confounding is likely to be present. If there are potentially important uncontrolled confounders, reviewers will want to assess the likely impact of such confounding.",
  "authors": [
    {
      "affiliations": [
        "Dept. Env. Health, Rollins School of Public Health, Emory U., Atlanta, GA, USA"
      ],
      "name": "Kyle Steenland"
    }
  ],
  "title": "8000011 Confounding appraisal in case–control and cohort studies",
  "uid": "0af7baff-6ec7-5b22-99dd-a79e3b8ecad3"
}