Kalpana Balakrishnan, Sankar Sambandam, Padmavathi Ramaswamy, Sumi Mehta, Kirk R Smith
{"title":"Exposure assessment for respirable particulates associated with household fuel use in rural districts of Andhra Pradesh, India.","authors":"Kalpana Balakrishnan, Sankar Sambandam, Padmavathi Ramaswamy, Sumi Mehta, Kirk R Smith","doi":"10.1038/sj.jea.7500354","DOIUrl":null,"url":null,"abstract":"<p><p>Indoor air pollution associated with combustion of solid fuels seems to be a major contributor to the national burden of disease in India, but relatively few quantitative exposure assessment studies are available. This study quantified the daily average concentrations of respirable particulates (50% cut-off at 4 microm) in 412 rural homes selected through stratified random sampling from three districts of Andhra Pradesh, India and recorded time activity data from 1400 individuals to reconstruct 24-h average exposures. The mean 24-h average concentrations ranged from 73 to 732 microg/m(3) in gas- versus solid fuel-using households, respectively. Concentrations were significantly correlated with fuel type, kitchen type, and fuel quantity. The mean 24-h average exposures ranged from 80 to 573 microg/m(3). Among solid fuel users, the mean 24-h average exposures were the highest for women cooks and were significantly different from men and children. Among women, exposures were the highest in the age group of 15-40 years (most likely to be involved in cooking or helping in cooking), while among men, exposures were highest in the age group of 65-80 years (most likely to be indoors). The data are being used to develop a model to predict quantitative categories of population exposure based on survey information on housing and fuel characteristics. This would facilitate the development of a regional exposure database and enable better estimation of health risks.</p>","PeriodicalId":15789,"journal":{"name":"Journal of Exposure Analysis and Environmental Epidemiology","volume":"14 Suppl 1 ","pages":"S14-25"},"PeriodicalIF":0.0000,"publicationDate":"2004-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1038/sj.jea.7500354","citationCount":"199","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Exposure Analysis and Environmental Epidemiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/sj.jea.7500354","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 199
Abstract
Indoor air pollution associated with combustion of solid fuels seems to be a major contributor to the national burden of disease in India, but relatively few quantitative exposure assessment studies are available. This study quantified the daily average concentrations of respirable particulates (50% cut-off at 4 microm) in 412 rural homes selected through stratified random sampling from three districts of Andhra Pradesh, India and recorded time activity data from 1400 individuals to reconstruct 24-h average exposures. The mean 24-h average concentrations ranged from 73 to 732 microg/m(3) in gas- versus solid fuel-using households, respectively. Concentrations were significantly correlated with fuel type, kitchen type, and fuel quantity. The mean 24-h average exposures ranged from 80 to 573 microg/m(3). Among solid fuel users, the mean 24-h average exposures were the highest for women cooks and were significantly different from men and children. Among women, exposures were the highest in the age group of 15-40 years (most likely to be involved in cooking or helping in cooking), while among men, exposures were highest in the age group of 65-80 years (most likely to be indoors). The data are being used to develop a model to predict quantitative categories of population exposure based on survey information on housing and fuel characteristics. This would facilitate the development of a regional exposure database and enable better estimation of health risks.