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To Adjust or Not to Adjust: The Role of Different Covariates in Cardiovascular Observational Studies Publisher Pubmed



Etminan M1 ; Brophy JM2 ; Collins G3, 4 ; Nazemipour M5, 6 ; Mansournia MA7
Authors
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Authors Affiliations
  1. 1. Departments of Ophthalmology and Visual Sciences, Medicine and Pharmacology, University of British Columbia, Vancouver, Canada
  2. 2. Department of Epidemiology and Medicine, McGill University, Montreal, Canada
  3. 3. Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom
  4. 4. NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, United Kingdom
  5. 5. Osteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
  6. 6. Psychosocial Health Research Institute, Iran University of Medical Sciences, Tehran, Iran
  7. 7. Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran

Source: American Heart Journal Published:2021


Abstract

Covariate adjustment is integral to the validity of observational studies assessing causal effects. It is common practice to adjust for as many variables as possible in observational studies in the hopes of reducing confounding by other variables. However, indiscriminate adjustment for variables using standard regression models may actually lead to biased estimates. In this paper, we differentiate between confounders, mediators, colliders, and effect modifiers. We will discuss that while confounders should be adjusted for in the analysis, one should be wary of adjusting for colliders. Mediators should not be adjusted for when examining the total effect of an exposure on an outcome. Automated statistical programs should not be used to decide which variables to include in causal models. Using a case scenario in cardiology, we will demonstrate how to identify confounders, colliders, mediators and effect modifiers and the implications of adjustment or non-adjustment for each of them. © 2021 Elsevier Inc.
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