Repositorio UFRO · Omeka S

Multinational prediction of household and personal exposure to fine particulate matter (PM2.5) in the PURE cohort study

Primer Autor	Shupler, Matthew
Co-autores	Hystad, Perry Birch, Aaron Li Chu, Yen Jeronimo, Matthew Miller-Lionberg, Daniel Gustafson, Paul Rangarajan, Sumathy Mustaha, Maha Heenan, Laura Seron, Pamela Lanas, Fernando Cazor, Fairuz Jose Oliveros, Maria Lopez-Jaramillo, Patricio Camacho, Paul A. Otero, Johnna Perez, Maritza Yeates, Karen West, Nicola Ncube, Tatenda Ncube, Brian Chifamba, Jephat Yusuf, Rita Khan, Afreen Liu, Zhiguang Wu, Shutong Wei, Li Tse, Lap Ah Mohan, Deepa Kumar, Parthiban Gupta, Rajeev Mohan, Indu Jayachitra, K. G. Mony, Prem K. Rammohan, Kamala Nair, Sanjeev Lakshmi, P. V. M. Sagar, Vivek Khawaja, Rehman Iqbal, Romaina Kazmi, Khawar Yusuf, Salim Brauer, Michael
Título	Multinational prediction of household and personal exposure to fine particulate matter (PM2.5) in the PURE cohort study
Editorial	PERGAMON-ELSEVIER SCIENCE LTD
Revista	ENVIRONMENT INTERNATIONAL
Lenguaje	en
Resumen	Introduction: Use of polluting cooking fuels generates household air pollution (HAP) containing health-damaging levels of fine particulate matter (PM2.5). Many global epidemiological studies rely on categorical HAP exposure indicators, which are poor surrogates of measured PM2.5 levels. To quantitatively characterize HAP levels on a large scale, a multinational measurement campaign was leveraged to develop household and personal PM2.5 exposure models. Methods: The Prospective Urban and Rural Epidemiology (PURE)-AIR study included 48-hour monitoring of PM2.5 kitchen concentrations (n = 2,365) and male and/or female PM2.5 exposure monitoring (n = 910) in a subset of households in Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania and Zimbabwe. PURE-AIR measurements were combined with survey data on cooking environment characteristics in hierarchical Bayesian log-linear regression models. Model performance was evaluated using leave-one-out cross validation. Predictive models were applied to survey data from the larger PURE cohort (22,480 households, 33,554 individuals) to quantitatively estimate PM2.5 exposures. Results: The final models explained half (R2 = 54%) of the variation in kitchen PM2.5 measurements (root mean square error (RMSE) (log scale):2.22) and personal measurements (R2 = 48%, RMSE (log scale):2.08). Primary cooking fuel type, heating fuel type, country and season were highly predictive of PM2.5 kitchen concentrations. Average national PM2.5 kitchen concentrations varied nearly 3-fold among households primarily cooking with gas (20 mu g/m3 (Chile), 55 mu g/m3 (China)) and 12-fold among households primarily cooking with wood (36 mu g/ m3 (Chile)), 427 mu g/m3 (Pakistan)). Average PM2.5 kitchen concentration, heating fuel type, season and secondhand smoke exposure were significant predictors of personal exposures. Modeled average PM2.5 female exposures were lower than male exposures in upper-middle/high-income countries (India, China, Colombia, Chile). Conclusion: Using survey data to estimate PM2.5 exposures on a multinational scale can cost-effectively scale up quantitative HAP measurements for disease burden assessments. The modeled PM2.5 exposures can be used in future epidemiological studies and inform policies targeting HAP reduction.
Tipo de Recurso	artículo original
doi	10.1016/j.envint.2021.107021
Formato Recurso	PDF
Palabras Claves	Household air pollution PM2 5 Kitchen concentrations Personal exposures Predictive modeling Bayesian hierarchical modeling INDOOR AIR-POLLUTION SOLID-FUEL USE BLOOD-PRESSURE COOKSTOVE INTERVENTION BIOMASS COMBUSTION SMOKE EXPOSURE RISK-FACTOR COOKING IMPACT WOMEN
Ubicación del archivo	http://dx.doi.org/10.1016/j.envint.2021.107021
Categoría OCDE	Ciencias Ambientales
Materias	Contaminación del aire en el hogar PM2 5 Concentraciones en la cocina Exposiciones personales Modelado predictivo Modelado jerárquico bayesiano CONTAMINACIÓN DEL AIRE INTERIOR USO DE COMBUSTIBLE SÓLIDO PRESIÓN ARTERIAL INTERVENCIÓN DE ESTUFA COMBUSTIÓN DE BIOMASA EXPOSICIÓN AL HUMO FACTOR DE RIESGO COCINAR IMPACTO MUJERES
Disciplinas de la OCDE	Ciencias del Medio Ambiente Epidemiología Salud Pública y Ambiental
Título de la cita (Recomendado-único)	Multinational prediction of household and personal exposure to fine particulate matter (PM2.5) in the PURE cohort study
Identificador del recurso (Mandatado-único)	artículo original
Versión del recurso (Recomendado-único)	version publicada
License	CC BY-NC-ND 4.0
Condición de la licencia (Recomendado-repetible)	CC BY-NC-ND 4.0
Derechos de acceso	acceso abierto
Access Rights	acceso abierto
Id de Web of Science	WOS:000733713000002