Cause-specific premature death from ambient PM2.5 exposure in India: Estimate adjusted for baseline mortality

- Annual premature death from ambient PM2.5 exposure in India is estimated.
- Estimate utilizes bias-corrected satellite-based PM2.5 data.
- Estimate is adjusted for spatially varying baseline mortality using GDP as proxy.
- Annual death is estimated to be 486,100 (811,000) using NLP (IER) risk functions.
- Statistics are provided at district level to facilitate policymakers.

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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