Javier Llorca1, Miguel Delgado-Rodríguez. 1. Division of Preventive Medicine and Public Health, University of Cantabria School of Medicine, Av. Cardenal Herrera Oria s/n, Santander 39011, Spain. llorcaj@unican.es
Abstract
OBJECTIVE: Attributable fraction in the exposed and (population) attributable fraction have been extensively used to determine the proportion of cases of a particular disease that can be attributable to any risk factor. Epidemiologists know that these measurements can add up to more than 100%; nevertheless, in a clinical context or in mass media, this characteristic is sometimes misinterpreted. This article provides a way to estimate the contribution of a risk factor in populations. STUDY DESIGN AND SETTING: McElduff et al. have suggested a method for estimating the contribution of a risk factor in a person with more than one risk factor. We extend their suggestion to populations where risk factors are mixed in different proportions. We illustrate the usage of this method by enlarging the example provided by them and compare it with the average attributable fraction suggested by Eide and Gefeller. RESULTS: Population attributable fraction can be modified to obtain additivity; therefore, the contribution of a risk factor in populations can be estimated, which would be of interest, for example, in clinical or in court settings. CONCLUSION: The suggested method and the average attributable fraction provide different results, and would be applicable under different assumptions.
OBJECTIVE: Attributable fraction in the exposed and (population) attributable fraction have been extensively used to determine the proportion of cases of a particular disease that can be attributable to any risk factor. Epidemiologists know that these measurements can add up to more than 100%; nevertheless, in a clinical context or in mass media, this characteristic is sometimes misinterpreted. This article provides a way to estimate the contribution of a risk factor in populations. STUDY DESIGN AND SETTING: McElduff et al. have suggested a method for estimating the contribution of a risk factor in a person with more than one risk factor. We extend their suggestion to populations where risk factors are mixed in different proportions. We illustrate the usage of this method by enlarging the example provided by them and compare it with the average attributable fraction suggested by Eide and Gefeller. RESULTS: Population attributable fraction can be modified to obtain additivity; therefore, the contribution of a risk factor in populations can be estimated, which would be of interest, for example, in clinical or in court settings. CONCLUSION: The suggested method and the average attributable fraction provide different results, and would be applicable under different assumptions.
Authors: Haiqun Lin; Heather G Allore; Gail McAvay; Mary E Tinetti; Thomas M Gill; Cary P Gross; Terrence E Murphy Journal: Am J Public Health Date: 2012-04-19 Impact factor: 9.308
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