BMJ  2005;330:960-962 (23 April), doi:10.1136/bmj.330.7497.960

Education and debate

Reader's guide to critical appraisal of cohort studies: 2. Assessing potential for confounding

¹ Institute for Clinical Evaluative Sciences, Toronto, ON Canada, ² Department of Health Care Policy, Harvard Medical School, Boston, USA, ³ Department of Psychiatry, University of Toronto, ON, Canada, ⁴ Kunin-Lunenfeld Applied Research Unit, Baycrest Centre for Geriatric Care, Toronto, ON, Canada, ⁵ Department of Health Policy, Management and Evaluation, Faculty of Medicine, University of Toronto, Toronto, ON Canada

Although confounding is an important problem of cohort studies, its effects can be minimised to enable valid comparison

The first 150 words of the full text of this article appear below.

Introduction

In cohort studies, who does or does not receive an intervention is determined by practice patterns, personal choice, or policy decisions. This raises the possibility that the intervention and comparison groups may differ in characteristics that affect the study outcome, a problem called selection bias. If these characteristics have independent effects on the observed outcome in each group, they will create differences in outcomes between the groups apart from those related to the interventions being assessed. This effect is known as confounding.¹ In the first paper in the series we dealt with the design and use of cohort studies and how to identify selection bias.² This paper focuses on the definition and assessment of confounders.

What is a confounder?

For a characteristic to be a confounder in a particular study, it must meet two criteria.¹ The first is that it must be related to the outcome in terms of prognosis or susceptibility. For example, . . . [Full text of this article]

Has there been a systematic effort to identify and measure potential confounders?

Is there information on distribution of potential confounders between groups?

What methods are used to assess differences in distribution of potential confounders?

CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?

Relevant Articles

Readers guide to critical appraisal of cohort studies: 3. Analytical strategies to reduce confounding

Sharon-Lise T Normand, Kathy Sykora, Ping Li, Muhammad Mamdani, Paula A Rochon, and Geoffrey M Anderson
BMJ 2005 330: 1021-1023. [Extract] [Full Text] [PDF]

Reader's guide to critical appraisal of cohort studies: 1. Role and design

Paula A Rochon, Jerry H Gurwitz, Kathy Sykora, Muhammad Mamdani, David L Streiner, Susan Garfinkel, Sharon-Lise T Normand, and Geoffrey M Anderson
BMJ 2005 330: 895-897. [Extract] [Full Text] [PDF]

Association between falls in elderly women and chronic diseases and drug use: cross sectional study

Debbie A Lawlor, Rita Patel, and Shah Ebrahim
BMJ 2003 327: 712-717. [Abstract] [Full Text] [PDF]

Statistics notes: Treatment allocation in controlled trials: why randomise?

Douglas G Altman and J Martin Bland
BMJ 1999 318: 1209. [Extract] [Full Text] [PDF]

This article has been cited by other articles:

• Normand, S.-L. T. (2008). Some Old and Some New Statistical Tools for Outcomes Research. Circulation 118: 872-884 [Full text]  
• Frobisher, C., Tilling, K., Emmett, P. M, Maynard, M., Ness, A. R, Davey Smith, G., Frankel, S. J, Gunnell, D. J (2007). Reproducibility measures and their effect on diet-cancer associations in the Boyd Orr cohort. J. Epidemiol. Community Health 61: 434-440 [Abstract] [Full text]  
• Giorda, C. B., Avogaro, A., Maggini, M., Lombardo, F., Mannucci, E., Turco, S., Alegiani, S. S., Raschetti, R., Velussi, M., Ferrannini, E., The DAI Study Group, (2007). Incidence and Risk Factors for Stroke in Type 2 Diabetic Patients: The DAI Study. Stroke 38: 1154-1160 [Abstract] [Full text]  
• Coverdale, J., Roberts, L., Louie, A., Beresin, E. (2006). Writing the Methods. Acad. Psychiatry 30: 361-364 [Full text]  
• Dominguez, J., Kanna, B. (2006). Three-year duration of benefit from abciximab in patient receiving stents for acute myocardial infarction in the randomized double-blind ADMIRAL study. Eur Heart J 27: 1508-1509 [Full text]  
• Normand, S.-L. T, Sykora, K., Li, P., Mamdani, M., Rochon, P. A, Anderson, G. M (2005). Readers guide to critical appraisal of cohort studies: 3. Analytical strategies to reduce confounding. BMJ 330: 1021-1023 [Full text]  

Rapid Responses:

Read all Rapid Responses

Adding an operational definition to confounding

James M O'Brien
bmj.com, 26 Apr 2005 [Full text]

assessing differences in distribution

Richard Goldstein
bmj.com, 4 May 2005 [Full text]