In epidemiology, attributable risk is the difference in rate of a condition between an exposed population and an unexposed population. Attributable risk is mostly calculated in cohort studies, where individuals are assembled on exposure status and followed over a period of time. Investigators count the occurrence of the diseases. The cohort is then subdivided by the level of exposure and diseases frequency is compared subgroups. One is considered exposed and another unexposed. The formula commonly used in Epidemiology books for Attributable risk is Ie - Iu = AR, where Ie = Incidence in exposed and Iu = incidence in unexposed. We can calculate AR percent once we calculate AR. The formula for that is 100*(Ie - Iu)/Ie .
Note: Ie is calculated by simply dividing the number of exposed people who get the disease by the total number who are exposed (N-exposeddis / N-exposedtot = Ie). Similarly, the Iu is calculated by dividing the number of unexposed people who get the disease by the total number who are not exposed (N-unexposeddis / N-unexposedtot = Iu).
The concept was first proposed by Levin in 1953.
Read more about Attributable Risk: Diversity of Interpretation, Uses, Combined PAR, Worked Example
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... Example 1 risk reduction Example 2 risk increase Experimental group (E) Control group (C) Total (E) (C) Total Events (E) EE = 15 CE = 115 ... EE = 75 CE = 175 ... Non-events (N) EN = 135 CN = 285 ... EN = 75 CN ... Example 1 Example 2 CER − EER < 0 absolute risk reduction ARR (−)0.3, or (−)30% N/A > 0 absolute risk increase ARI N/A 0.1, or 10% (CER − EER) / CER < 0 ...
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