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Heat exposure is an escalating public health concern, where limited policy attention and infrastructure constraints hinder effective risk assessment and response. This study introduce a multi-perspective and multi-scale analytical framework to quantify socioeconomic disparities in heat exposure using spatiotemporally resolved data, providing key insights for targeted public health interventions and policy development. Taking India as the study area, we integrated temperature, human mobility, and socioeconomic data at geohash-5 level and 3-hour intervals throughout 2019. Our results reveal distinct spatialtemporal patterns of extreme heat, suggesting that socioeconomic conditions are weakly associated with differences in heat exposure, particularly across populated metropolitan regions. A significant but modest association between the Relative Wealth Index (RWI) and Wet Bulb Globe Temperature (WBGT) is observed at the metropolitan scale (r ≈ 0.32***), reflecting broad population scale gradients across large urban regions, rather than neighborhood level intra-urban variability. Mobility analysis further shows that lower-income groups not only experience greater heat stress during daily activities but also face constrained capacity to adapt their travel behavior under extreme heat. These findings underscore the need to incorporate mobility-informed exposure assessments. The proposed framework offers practical guidance for data-driven, equity-oriented planning and is particularly suited for developing country contexts where high-quality big data remains limited. • Integrates multi-source data to assess heat exposure disparities. • Reveals multi-perspective heat exposure across India. • Lower-income groups face more exposure and limited behavioral flexibility. • Heat stress is concentrated, prolonged in populated areas. • A scalable framework for diagnosing heat exposure in data-scarce areas.
Ma et al. (Thu,) studied this question.