Apportioning causes, targeting populations and predicting risks: population attributable fractions

Our plain-English summary of Apportioning causes, targeting populations and predicting risks: population attributable fractions, by N. Chatterjee, P. Hartge (European Journal of Epidemiology, 2003).

The study

• Authors: N. Chatterjee, P. Hartge
• Journal: European Journal of Epidemiology
• Published: 2003;18(10):933-5
• Type of article: Comment
• Cited by: 2 articles, as counted by NIH iCite
• Read it: PubMed · Publisher

In plain English

This article was a commentary, not an original study. The authors discussed a paper by Gustavsson and co-authors, published in the same journal issue, on population attributable fractions (PAF): the share of all cases of a disease in a population that should be ascribed to particular causes. The authors argued that when two exposures occur together, a PAF should be calculated for each exposure, adjusted for the other, as well as for both together. Gustavsson's paper included a real-world example of lung cancer attributable to asbestos and combustion products in Stockholm, Sweden. Using that example, the authors estimated individual PAFs of 4.4% for asbestos and 2.4% for combustion products. Gustavsson and co-authors had estimated about 6.9% for the two together. The authors noted that this total roughly equaled the sum of the individual figures. They linked this to the two exposures having approximately additive effects on risk. In a hypothetical example, by contrast, the individual fractions (0.24 and 0.44) added up to more than the combined 0.56. The authors also discussed other uses of PAF. They concluded that PAF measures involving multiple exposures deserve attention.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: commentary on another article (Gustavsson and co-authors) about methods for calculating population attributable fractions
• Who was studied: No population was studied directly. The commentary reworked figures from Gustavsson and co-authors' example of lung cancer incidence in Stockholm, Sweden, and from their hypothetical example with two exposures, A and B.
• Exposure: asbestos and combustion products, taken from Gustavsson and co-authors' lung cancer example; no fiber types, jobs or doses are given
• Main results:
  • Using the data in Gustavsson and co-authors' Table 2, the commentary authors estimated the individual PAF for lung cancer in Stockholm at 4.4% for asbestos and 2.4% for combustion products.
  • Gustavsson and co-authors, not the commentary authors, estimated the overall PAF for asbestos and combustion products together at about 6.9%.
  • In the lung cancer example, the combined PAF roughly equaled the sum of the individual PAFs. The authors related this to the condition for additive effects being approximately satisfied for asbestos and combustion products.
  • In Gustavsson and co-authors' hypothetical example, the individual PAFs for exposures A and B were 0.24 and 0.44. Their sum exceeded the overall PAF of 0.56 for both together.
• The authors' conclusion: The authors stated that they shared the view of Gustavsson and co-authors that PAF measures involving multiple exposures deserve attention, because these measures will play roles in epidemiology and public health.

Topics

Medical terms in this study, explained in our Lexicon: Population Attributable Fraction (PAF).

Related studies

• Calculation of fractions of lung cancer incidence attributable to occupational exposure to asbestos and combustion products in Stockholm, Sweden — P. Gustavsson, A. Ahlbom, et al. (2003)
• Evaluation of Confounding and Selection Bias in Epidemiological Studies of Populations Exposed to Low-Dose, High-Energy Photon Radiation — M.K. Schubauer-Berigan, A. Berrington de Gonzalez, et al. (2020)
• Attributable Fraction of Cancer Related to Occupational Exposure in Italy — G. Collatuzzo, F. Turati, et al. (2023)
• Estimating the contribution of individual risk factors to disease in a person with more than one risk factor — P. McElduff, J. Attia, et al. (2002)
• Attributable risk in men in two French case-control studies on mesothelioma and asbestos — A. Lacourt, P. Rolland, et al. (2010)
• Biomarkers for Predicting Malignant Pleural Mesothelioma in a Mexican Population — G. Aguilar-Madrid, B. Pesch, et al. (2018)

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