Cause-specific premature death from ambient PM2.5 exposure in India: Estimate adjusted for baseline mortality |
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| Institution: | 1. State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China;2. State Key Laboratory of Atmospheric Boundary Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;3. The Beijing Innovation Center for Engineering Science and Advanced Technology, Peking University, Beijing, China;1. Department of Environmental Medicine, New York University School of Medicine, Tuxedo, NY, 10987, United States of America;2. Department of Environmental Health Engineering, Faculty of Public Health, Sri Ramachandra University, Porur, Chennai, 600116, India;3. Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India;4. Department of Internal Medicine, Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106, United States of America;5. RTI International, Research Triangle Park, NC, United States of America;6. CSIR Institute of Genomics and Integrative Biology, Delhi University, New Delhi, India;7. Division of Extramural Research and Training, National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, United States of America;8. All India Institute of Medical Sciences, New Delhi, India;9. Chest Research Foundation, Pune, India;10. Office of Research and Development, U.S. E.P.A., Research Triangle Park, NC 27711, United States of America |
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| Abstract: | In India, more than a billion population is at risk of exposure to ambient fine particulate matter (PM2.5) concentration exceeding World Health Organization air quality guideline, posing a serious threat to health. Cause-specific premature death from ambient PM2.5 exposure is poorly known for India. Here we develop a non-linear power law (NLP) function to estimate the relative risk associated with ambient PM2.5 exposure using satellite-based PM2.5 concentration (2001 − 2010) that is bias-corrected against coincident direct measurements. We show that estimate of annual premature death in India is lower by 14.7% (19.2%) using NLP (integrated exposure risk function, IER) for assumption of uniform baseline mortality across India (as considered in the global burden of disease study) relative to the estimate obtained by adjusting for state-specific baseline mortality using GDP as a proxy. 486,100 (811,000) annual premature death in India is estimated using NLP (IER) risk functions after baseline mortality adjustment. 54.5% of premature death estimated using NLP risk function is attributed to chronic obstructive pulmonary disease (COPD), 24.0% to ischemic heart disease (IHD), 18.5% to stroke and the remaining 3.0% to lung cancer (LC). 44,900 (5900–173,300) less premature death is expected annually, if India achieves its present annual air quality target of 40 μg m− 3. Our results identify the worst affected districts in terms of ambient PM2.5 exposure and resulting annual premature death and call for initiation of long-term measures through a systematic framework of pollution and health data archive. |
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