ArticleInternational journal of epidemiology2022
Pathway-specific population attributable fractions.
Article in International journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 12 citations in OpenAlex.
- Article
- Use of causal inference methods in case-control studies: a methodology review.American journal of epidemiology · 2026Review
- Obesity-attributable risk of cardiovascular disease (CVD) in the United States: a Bayesian network analysis.American journal of preventive cardiology · 2025Article
- Associations of Violence Against Women With Comorbid Symptoms of Depression and Anxiety Among Left-Behind Women in Rural China: Cross-Sectional Study.JMIR public health and surveillance · 2025Article
- Cancers attributable to diet in Italy.International journal of cancer · 2025Article
- Path-specific causal decomposition analysis with multiple correlated mediator variables.Statistics in medicine · 2024Article
- Estimating and displaying population attributable fractions using the R package: graphPAF.European journal of epidemiology · 2024Article
- Long working hours and all-cause mortality in China: A 26-year follow-up study.Scandinavian journal of work, environment & health · 2023Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionA population attributable fraction represents the relative change in disease prevalence that one might expect if a particular exposure was absent from the population. Often, one might be interested in what percentage of this effect acts through particular pathways. For instance, the effect of a sedentary lifestyle on stroke risk may be mediated by blood pressure, body mass index and several other intermediate risk factors.
methodsWe define a new metric, the pathway-specific population attributable fraction (PS-PAF), for mediating pathways of interest. PS-PAFs can be informally defined as the relative change in disease prevalence from an intervention that shifts the distribution of the mediator to its expected distribution if the risk factor were eliminated, and sometimes more simply as the relative change in disease prevalence if the mediating pathway were disabled. A potential outcomes framework is used for formal definitions and associated estimands are derived via relevant identifiability conditions. Computationally efficient estimators for PS-PAFs are derived based on these identifiability conditions.
resultsCalculations are demonstrated using INTERSTROKE-an international case-control study designed to quantify disease burden attributable to a number of known causal risk factors. The applied results suggest that mediating pathways from physical activity through blood pressure, blood lipids and body size explain comparable proportions of stroke disease burden, but a large proportion of the disease burden due to physical inactivity may be explained by alternative pathways.
conclusionPS-PAFs measure disease burden attributable to differing mediating pathways and can generate insights into the dominant mechanisms by which a risk factor affects disease at a population level.
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