Cargando…

Recommendation on unbiased estimation of population attributable fraction calculated in “prevalence and risk factors of active pulmonary tuberculosis among elderly people in China: a population based cross-sectional study”

Population attributable fraction (PAF) refers to the proportion of all cases with a particular outcome in a population that could be prevented by eliminating a specific exposure. The authors of a recent paper evaluated the prevalence and estimated the PAFs for risk factors of TB among elderly people...

Descripción completa

Detalles Bibliográficos
Autores principales: Khosravi, Ahmad, Mansournia, Mohammad Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6699105/
https://www.ncbi.nlm.nih.gov/pubmed/31422773
http://dx.doi.org/10.1186/s40249-019-0587-8
_version_ 1783444659744276480
author Khosravi, Ahmad
Mansournia, Mohammad Ali
author_facet Khosravi, Ahmad
Mansournia, Mohammad Ali
author_sort Khosravi, Ahmad
collection PubMed
description Population attributable fraction (PAF) refers to the proportion of all cases with a particular outcome in a population that could be prevented by eliminating a specific exposure. The authors of a recent paper evaluated the prevalence and estimated the PAFs for risk factors of TB among elderly people in China [Inf Dis Poverty. 2019;8:7]. Confounding is inevitable in observational studies and Levin’s formula is of limited use in practice for unbiasedly estimating PAF. In a complex survey design, an unbiased estimation of the PAF can be calculated using a sample-weighted version of the Miettinen formula or a sample weighed parametric g-formula. With respect to causal interpretation of PAF in public health setting, computation of PAF is logical and practical when the exposure is amenable to intervention. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40249-019-0587-8) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-6699105
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-66991052019-08-26 Recommendation on unbiased estimation of population attributable fraction calculated in “prevalence and risk factors of active pulmonary tuberculosis among elderly people in China: a population based cross-sectional study” Khosravi, Ahmad Mansournia, Mohammad Ali Infect Dis Poverty Letter to the Editor Population attributable fraction (PAF) refers to the proportion of all cases with a particular outcome in a population that could be prevented by eliminating a specific exposure. The authors of a recent paper evaluated the prevalence and estimated the PAFs for risk factors of TB among elderly people in China [Inf Dis Poverty. 2019;8:7]. Confounding is inevitable in observational studies and Levin’s formula is of limited use in practice for unbiasedly estimating PAF. In a complex survey design, an unbiased estimation of the PAF can be calculated using a sample-weighted version of the Miettinen formula or a sample weighed parametric g-formula. With respect to causal interpretation of PAF in public health setting, computation of PAF is logical and practical when the exposure is amenable to intervention. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40249-019-0587-8) contains supplementary material, which is available to authorized users. BioMed Central 2019-08-19 /pmc/articles/PMC6699105/ /pubmed/31422773 http://dx.doi.org/10.1186/s40249-019-0587-8 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Letter to the Editor
Khosravi, Ahmad
Mansournia, Mohammad Ali
Recommendation on unbiased estimation of population attributable fraction calculated in “prevalence and risk factors of active pulmonary tuberculosis among elderly people in China: a population based cross-sectional study”
title Recommendation on unbiased estimation of population attributable fraction calculated in “prevalence and risk factors of active pulmonary tuberculosis among elderly people in China: a population based cross-sectional study”
title_full Recommendation on unbiased estimation of population attributable fraction calculated in “prevalence and risk factors of active pulmonary tuberculosis among elderly people in China: a population based cross-sectional study”
title_fullStr Recommendation on unbiased estimation of population attributable fraction calculated in “prevalence and risk factors of active pulmonary tuberculosis among elderly people in China: a population based cross-sectional study”
title_full_unstemmed Recommendation on unbiased estimation of population attributable fraction calculated in “prevalence and risk factors of active pulmonary tuberculosis among elderly people in China: a population based cross-sectional study”
title_short Recommendation on unbiased estimation of population attributable fraction calculated in “prevalence and risk factors of active pulmonary tuberculosis among elderly people in China: a population based cross-sectional study”
title_sort recommendation on unbiased estimation of population attributable fraction calculated in “prevalence and risk factors of active pulmonary tuberculosis among elderly people in china: a population based cross-sectional study”
topic Letter to the Editor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6699105/
https://www.ncbi.nlm.nih.gov/pubmed/31422773
http://dx.doi.org/10.1186/s40249-019-0587-8
work_keys_str_mv AT khosraviahmad recommendationonunbiasedestimationofpopulationattributablefractioncalculatedinprevalenceandriskfactorsofactivepulmonarytuberculosisamongelderlypeopleinchinaapopulationbasedcrosssectionalstudy
AT mansourniamohammadali recommendationonunbiasedestimationofpopulationattributablefractioncalculatedinprevalenceandriskfactorsofactivepulmonarytuberculosisamongelderlypeopleinchinaapopulationbasedcrosssectionalstudy