Examinando por Materia "Household air pollution"

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  • Publicación
    Acceso abierto
    Environmental risk factors associated with respiratory diseases in children with socioeconomic disadvantage
    (2021-04-01) Cortes-Ramirez, Javier; Wilches-Vega, Juan D.; Paris-Pineda, Olga Maria; Rod, J.E.; Ayurzana, Lkhagvadulam; Sly, Peter D.; Fisioterapia Integral
    Children are more vulnerable to environmental exposures determinant of respiratory diseases due to their dynamic developmental physiology. Whereas social determinants of health are also associated with a higher risk of these diseases in children exposed to environmental risk factors, most studies incorporate them as covariates in the statistical analysis rather than focusing on specific vulnerable populations. In this study a systematic review searched and selected studies of respiratory diseases in children with socioeconomic disadvantage to identify the environmental risk factors associated with these diseases. The review followed the PRISMA protocol to identify eleven eligible studies of children with socioeconomic conditions that included low income and low socioeconomic status, overcrowding, adults with low education level and Indigenous status. Infectious respiratory diseases, asthma, rhinitis and mortality due to respiratory diseases were associated with risk factors such as biomass fuel use, tobacco smoking, particulate matter, coal dust and other pollutants including ozone, nitrogen dioxide and sulphur dioxide. The most common associations were between respiratory infections and household air pollution and asthma with indoor and outdoor air pollution. The findings support previous reports on these associations and suggest that specific vulnerabilities such as indigenous children and living with adults with low socioeconomic status and education level increase the risk of respiratory diseases. These populations can be given special attention to prioritize public health interventions to lower the burden of disease of respiratory diseases in children.
  • Publicación
    Acceso abierto
    Environmental risk factors associated with respiratory diseases in children with socioeconomic disadvantage
    (2021-04-01) Cortes-Ramirez, Javier; Wilches-Vega, Juan D.; Paris-Pineda, Olga Maria; Rod, J.E.; Ayurzana, Lkhagvadulam; Sly, Peter D.; Salud Comuniudes
    Children are more vulnerable to environmental exposures determinant of respiratory diseases due to their dynamic developmental physiology. Whereas social determinants of health are also associated with a higher risk of these diseases in children exposed to environmental risk factors, most studies incorporate them as covariates in the statistical analysis rather than focusing on specific vulnerable populations. In this study a systematic review searched and selected studies of respiratory diseases in children with socioeconomic disadvantage to identify the environmental risk factors associated with these diseases. The review followed the PRISMA protocol to identify eleven eligible studies of children with socioeconomic conditions that included low income and low socioeconomic status, overcrowding, adults with low education level and Indigenous status. Infectious respiratory diseases, asthma, rhinitis and mortality due to respiratory diseases were associated with risk factors such as biomass fuel use, tobacco smoking, particulate matter, coal dust and other pollutants including ozone, nitrogen dioxide and sulphur dioxide. The most common associations were between respiratory infections and household air pollution and asthma with indoor and outdoor air pollution. The findings support previous reports on these associations and suggest that specific vulnerabilities such as indigenous children and living with adults with low socioeconomic status and education level increase the risk of respiratory diseases. These populations can be given special attention to prioritize public health interventions to lower the burden of disease of respiratory diseases in children.
  • Publicación
    Acceso abierto
    Multinational prediction of household and personal exposure to fine particulate matter (PM2.5) in the PURE cohort study
    (Elsevier, 2022-01-15) Shupler, Matthew; 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; Oliveros, Maria Jose; Lopez-Jaramillo, Patricio; Camacho López, Paul Anthony; Otero, Johanna; 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; Kuma, Parthiban; Gupta, Rajeev; Mohan, Indu; Jayachitra, K.G.; Mony, Prem; Rammohan, Kamala; Nair, Sanjeev; Lakshmi, P.V.M.; Sagar, Vivek; Khawaja, Rehman; Iqbal, Romaina; Kazmi, Khawar; Yusuf, Salim; Brauer, Michael; PURE-AIR study investigators; Masira
    Abstract 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 μg/m3 (Chile); 55 μg/m3 (China)) and 12-fold among households primarily cooking with wood (36 μg/m3 (Chile)); 427 μg/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.