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Research

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Research Aims

  • Developing a model to estimate ambient exposure to air pollution (AP) levels in Chennai and Delhi

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  • Estimating association between exposure to AP, temperature, CM risk factors & diseases, and built environment

 

  • Examining DNA methylation patterns associated with AP

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  • Examining the association between AP & vitamin D levels

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Mandal S et al. Ensemble averaging based assessment of spatiotemporal variations in ambient PM2. 5 concentrations over Delhi, India, during 2010-2016. Atmospheric Environment. 2020 Mar 1;224:117309.

Pilot Study

  • Expanding the exposure model Pan-India to utilize health data collected across additional cohorts

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  • Evaluating personal PM2.5 exposure measurements in the CARRS cohort, Delhi – A sub study

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Characterizing personal PM2.5 exposures and their variability among adults in a highly polluted Indian city​

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To characterize real-time personal exposure of PM2.5 among 100 adults belonging to various age and socio-economic groups residing in Delhi during the summer and winter seasons.

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Features

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  • Covered participants from 17 neighborhoods in Delhi.

  • Measured exposures of people employed in more than 40 different professions

  • Included participants from slums, non-slums, and slum resettlement colonies

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Personal Monitoring Bag with details of the instruments

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 PM2.5 exposure profile of a participant

Preliminary Findings

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  • Personal PM2.5 exposures in the range of 85± 117 µg/m3

  • Wintertime personal exposures (152±120 µg/m3) ~300% higher than Summer (49±35 µg/m3) 

  • Slum residents have higher exposures than non-slum and slum resettlement colony residents

  • Informal sector employees and housewives have  higher exposures than formal sector employees

  • Cooking, Heating, Passive Smoking, and  Worship – Activities with higher exposures

Outputs

  1. Association of Long-Term Exposure to Fine Particulate Matter and Cardio-Metabolic Diseases in Low- and Middle-Income Countries: A Systematic Review

     

        Key findings:

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  • 17 articles were included for final review, and these studies were from Brazil, Bulgaria, China, India, and Mexico.

  • Outcome assessed were hypertension, type 2 diabetes mellitus and insulin resistance, and cardiovascular disease (CVD)-related emergency room visits/admissions, death, and mortality.

  • Largely a positive association between exposure to PM2.5 and CMDs was found, and CVD mortality with effect estimates ranging from 0.24% to 6.11% increased per 10 μg/m3 in PM2.5.

  • CVD-related hospitalizations and emergency room visits increased by 0.3% to 19.6%. Risk factors like hypertension had an odds ratio of 1.14, and type 2 diabetes mellitus had an odds ratio ranging from 1.14–1.32.

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  2.  Ensemble averaging based assessment of spatiotemporal variations in ambient PM 2.5

      concentrations over Delhi, India, during 2010-2016

     

      Key findings:

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  • Overall cross-validated prediction accuracy of the model was 80% over the study period with high spatial model accuracy and predicted annual average concentrations ranging from 87 to 138 μg/m3.

  • Annual average root mean squared errors for the ensemble averaged predictions were in the range 39.7-62.7 μg/m3 with prediction bias ranging between 4.6-11.2 μg/m3.

  • Our findings indicate important seasonal and geographical differences in particulate matter concentrations within Delhi over a significant period of time, with meteorological and land use features that discriminate most and least polluted regions.

  • This exposure assessment can be used to estimate dose response relationships more accurately over a wide range of particulate matter concentrations.

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  3.  Exposure to Particulate Matter Is Associated With Elevated Blood Pressure and Incident

      Hypertension in Urban India  

    

      Key findings:

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  • Median annual and monthly exposure at baseline was 92.1 μg/m3 (interquartile range, 87.6–95.7) and 82.4 μg/m3 (interquartile range, 68.4–107.0), respectively.

  • We observed higher average systolic BP (1.77 mm Hg [95% CI, 0.97–2.56] and 3.33 mm Hg [95% CI, 1.12–5.52]) per interquartile range differences in monthly and annual exposures, respectively, after adjusting for covariates.

  • Additionally, interquartile range differences in long-term exposures of 1, 1.5, and 2 years increased the risk of incident hypertension by 1.53× (95% CI, 1.19–1.96), 1.59× (95% CI, 1.31–1.92), and 1.16× (95% CI, 0.95–1.43), respectively.

  • Observed effects were larger in individuals with higher waist-hip ratios.

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  4. Daily nonaccidental mortality associated with short-term PM 2.5 exposures in Delhi, India

     

    Key findings:

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  • Median exposures to PM2.5 were 91.1 µg/m3 (interquartile range = 68.9, 126.2)

  • Total nonaccidental deaths recorded in Delhi during the study period were 700,512. Each 25 µg/m3 increment in exposure was associated with a 0.8% (95% confidence intervals [CI] = 0.3, 1.3%) increase in daily nonaccidental mortality in the study population and a 1.5% (95% CI = 0.8, 2.2%) increase in mortality among those with 60 years of age or over.

  • The exposure-response relationship was nonlinear in nature, with relative risk rising rapidly before tapering off above 125 µg/m3.

  • Meeting WHO guidelines for acceptable levels of exposure over the study period would have likely averted 17,526 (95% CI = 6,837, 25,589) premature deaths, with older and male populations disproportionately affected.

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