Cargando…

Pathway-specific population attributable fractions

INTRODUCTION: A 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 ef...

Descripción completa

Detalles Bibliográficos
Autores principales: O’Connell, Maurice M, Ferguson, John P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9749703/
https://www.ncbi.nlm.nih.gov/pubmed/35536313
http://dx.doi.org/10.1093/ije/dyac079
_version_ 1784850098313756672
author O’Connell, Maurice M
Ferguson, John P
author_facet O’Connell, Maurice M
Ferguson, John P
author_sort O’Connell, Maurice M
collection PubMed
description INTRODUCTION: A 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. METHODS: We 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. RESULTS: Calculations 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. CONCLUSION: PS-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.
format Online
Article
Text
id pubmed-9749703
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-97497032022-12-15 Pathway-specific population attributable fractions O’Connell, Maurice M Ferguson, John P Int J Epidemiol Miscellaneous INTRODUCTION: A 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. METHODS: We 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. RESULTS: Calculations 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. CONCLUSION: PS-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. Oxford University Press 2022-05-10 /pmc/articles/PMC9749703/ /pubmed/35536313 http://dx.doi.org/10.1093/ije/dyac079 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the International Epidemiological Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Miscellaneous
O’Connell, Maurice M
Ferguson, John P
Pathway-specific population attributable fractions
title Pathway-specific population attributable fractions
title_full Pathway-specific population attributable fractions
title_fullStr Pathway-specific population attributable fractions
title_full_unstemmed Pathway-specific population attributable fractions
title_short Pathway-specific population attributable fractions
title_sort pathway-specific population attributable fractions
topic Miscellaneous
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9749703/
https://www.ncbi.nlm.nih.gov/pubmed/35536313
http://dx.doi.org/10.1093/ije/dyac079
work_keys_str_mv AT oconnellmauricem pathwayspecificpopulationattributablefractions
AT fergusonjohnp pathwayspecificpopulationattributablefractions