What does the odds ratio represent in epidemiologic research?

What does the odds ratio represent in epidemiologic research?

• A. Ratio of the odds of exposure in diseased subjects to the odds of exposure in non-diseased subjects
• B. Ratio of the risk of disease in exposed to risk in unexposed
• C. A measure of absolute risk difference
• D. The prevalence of exposure in the population

Answer: (A)

The odds ratio measures how much the odds of exposure differ between those with disease and those without. In many epidemiologic studies, especially case-control designs, you can’t directly calculate risk, but you can compare how often people with disease were exposed to how often people without disease were exposed. So the odds ratio is the ratio of the odds of exposure among diseased individuals to the odds of exposure among non-diseased individuals. If you imagine the data in a 2x2 table, it’s calculated as the product of the two diagonals divided by the product of the other diagonal: (exposed and diseased × not exposed and non-diseased) divided by (not exposed and diseased × exposed and non-diseased). For example, if among diseased people 40 were exposed and 60 were not, and among non-diseased people 10 were exposed and 60 were not, the odds ratio would be (40×60)/(60×10) = 4, meaning the exposure is associated with disease and the odds of exposure are four times higher in cases than in controls. Relative risk would compare probabilities of disease between exposed and unexposed, not the odds. Absolute risk difference measures a change in risk, and prevalence refers to how common exposure is in the population.

The odds ratio measures how much the odds of exposure differ between those with disease and those without. In many epidemiologic studies, especially case-control designs, you can’t directly calculate risk, but you can compare how often people with disease were exposed to how often people without disease were exposed. So the odds ratio is the ratio of the odds of exposure among diseased individuals to the odds of exposure among non-diseased individuals.

If you imagine the data in a 2x2 table, it’s calculated as the product of the two diagonals divided by the product of the other diagonal: (exposed and diseased × not exposed and non-diseased) divided by (not exposed and diseased × exposed and non-diseased). For example, if among diseased people 40 were exposed and 60 were not, and among non-diseased people 10 were exposed and 60 were not, the odds ratio would be (40×60)/(60×10) = 4, meaning the exposure is associated with disease and the odds of exposure are four times higher in cases than in controls.

Relative risk would compare probabilities of disease between exposed and unexposed, not the odds. Absolute risk difference measures a change in risk, and prevalence refers to how common exposure is in the population.