A spatiotemporal Bayesian hierarchical model of heat-related mortality in Catalonia, Spain (2012--2022): The role of environmental and socioeconomic modifiers
David Solano, Marta Solans, Xavier Perafita, Anna Ruiz-Comellas, Marc Saez, Maria A. Barcel\'o

TL;DR
This study used a Bayesian hierarchical model to analyze how environmental and socioeconomic factors modify heat-related mortality in Catalonia, revealing that ozone pollution and social vulnerabilities significantly influence mortality risks during heat events.
Contribution
It introduces a novel spatiotemporal Bayesian hierarchical approach to quantify the combined effects of heat, air pollution, and socioeconomic factors on mortality.
Findings
Ozone levels significantly increase heat-related mortality risk.
Socioeconomic vulnerabilities amplify mortality during heatwaves.
Extreme heat alone was not independently associated with mortality.
Abstract
Background: Extreme heat is a major public health risk, yet its relationship with mortality may be confounded or modified by air pollution and social determinants. Objectives: We aimed to quantify the effects of extreme maximum temperatures and heatwaves on daily mortality in Catalonia (2012--2022), and to assess the modifying and confounding roles of air pollutants and socioeconomic factors. Methods: We conducted a time--series ecological study across 379 basic health areas (ABS) during summer months. Mortality data from the Spanish National Statistics Institute were linked with meteorological and air pollution data. A hierarchical Bayesian spatiotemporal model, incorporating structured and unstructured random effects, was used to account for spatial and temporal dependencies, as well as observed socioeconomic confounders. Results: In total, 730,634 deaths occurred, with 216,989 in…
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Taxonomy
TopicsClimate Change and Health Impacts · Air Quality and Health Impacts · Thermoregulation and physiological responses
