Health effects of selected environmental Exposomes Across the Life courSe in Indian populations using longitudinal cohort studies: GEOHealth HEALS Study protocol.

INTRODUCTION: Air pollution presents a major public health threat to India, affecting more than three quarters of the country's population. In the current project, GEOHealth Health Effects of Selected Environmental Exposomes Across the Life CourSe-India, we aim to study the effect of environmental exposomes-fine particulate matter (PM2.5), nitrogen dioxide (NO2), ozone (O3) and extremes of temperature-on multiple health outcomes using a modified life course approach. The associated training grant aims to build capacity in India to address the unique environmental health problems. METHODS AND ANALYSIS: The project aims to (A) Develop exposure assessments in seven cities, namely Delhi, Chennai, Sonipat, Vizag, Pune, Hyderabad and Bikaner, for: (1) A fine-scale spatiotemporal model for multiple pollutants (PM2.5, NO2, O3, temperature); (2) Combined ground monitoring and modelling for major chemical species of ambient PM2.5 at seven cities; and (3) Personal exposure assessment in a subsample from the six cities, except Pune, and (B) Conduct health association studies covering a range of chronic non-communicable diseases and their risk factors leveraging a unique approach using interdigitating cohorts. We have assembled existing pregnancy, child, adolescent, adult and older adult cohorts across India to explore health effects of exposomes using causal analyses. We propose to use Bayesian kernel machine regression to assess the effects of mixtures of all pollutants including species of PM2.5 on health while accounting for potential non-linearities and interactions between exposures. This builds on earlier work that constructed a fine spatiotemporal model for PM2.5 exposure to study health outcomes in two Indian cities. ETHICS AND DISSEMINATION: Ethical clearance for conduct of the study was obtained from the Institutional Ethics Committee (IEC) of the Centre for Chronic Disease Control, and all the participating institutes and organisations. National-level permission was provided by the Indian Council of Medical Research. The research findings will be disseminated through peer-reviewed publications, policy briefs, print and social media, and communicating with the participating communities and stakeholders. Training of Indian scientists will build the capacity to undertake research on selected adverse environmental exposures on population health in India.

Nationwide estimation of daily ambient PM2.5 from 2008 to 2020 at 1 km2 in India using an ensemble approach.

High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM2.5) pollution in India. We developed a model for daily average ambient PM2.5 between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories. Daily average predictions at each 1 km × 1 km grid from each learner were ensembled using a Gaussian process regression with anisotropic smoothing over spatial coordinates, and regression calibration was used to account for exposure error. Cross-validating by leaving monitors out, the ensemble model had an R2 of 0.86 at the daily level in the validation data and outperformed each component learner (by 5-18%). Annual average levels in different zones ranged between 39.7 µg/m3 (interquartile range: 29.8-46.8) in 2008 and 30.4 µg/m3 (interquartile range: 22.7-37.2) in 2020, with a cross-validated (CV)-R2 of 0.94 at the annual level. Overall mean absolute daily errors (MAE) across the 13 years were between 14.4 and 25.4 µg/m3. We obtained high spatial accuracy with spatial R2 greater than 90% and spatial MAE ranging between 7.3-16.5 µg/m3 with relatively better performance in urban areas at low and moderate elevation. We have developed an important validated resource for studying PM2.5 at a very fine spatiotemporal resolution, which allows us to study the health effects of PM2.5 across India and to identify areas with exceedingly high levels.

Fruit and vegetable purchasing patterns and preferences in South Delhi.

This study examines associations between consumer characteristics, beliefs, and preferences and fruit and vegetable (FV) purchasing and intake in South Delhi, India. Home interviews were conducted with 245 households, using a structured questionnaire to assess FV consumption and purchasing frequency, spending, place of purchase, mode of travel, knowledge and attitudes toward organics, and beliefs about barriers to FV consumption. In-depth interviews with 62 experts and key informants validated survey findings that street vendors and markets are currently the dominant source of FV in South Delhi and that affordability, not accessibility, is the main barrier to increasing FV intake.