Multivariate Meta-Analysis of Temperature-Related Mortality in Mexican Metropolitan Areas: Socioeconomic and Geographical Vulnerabilities

Background: A substantial share of deaths is associated with non-optimal temperatures, a burden expected to grow with climate change. Geographic and socioeconomic inequalities shape these risks, but their relative importance remains unclear in middle-income countries. Mexico, with marked geographic differences and uneven development, offers a natural setting to examine how temperature-related mortality varies across metropolitan areas and which determinants matter most. 

Methods: We conducted a three-stage analysis for 89 Mexican metropolitan areas (1998-2019). First, we estimated city-specific temperature-mortality associations using time-series quasi-Poisson regression with distributed lag non-linear models. Second, we applied multivariate meta-regression to pool exposure–response functions, derive best linear unbiased predictions, and compute city-level attributable fractions. Third, we examined effect modification by geographic factors, household-level adaptation, and indicators of socioeconomic context. 

Findings: Temperature-attributable mortality presented geographic differences, with cold-attributable fractions increasing and heat-attributable fractions decreasing at higher altitudes, reflecting shifts in local exposure distributions. Low prevalence of household heating and lower tree cover were associated with higher cold-attributable fractions. The highest heat-attributable fractions occurred in areas with higher air-conditioning prevalence, representing adaptation demand in areas with greatest heat exposure. When stratified by climate zones, effect modification by contextual socioeconomic indicators was attenuated and generally not statistically significant. 

Interpretation: In Mexico, temperature-related mortality is shaped primarily by geography. Contextual socioeconomic indicators add limited additional explanatory power at the metropolitan level once geographic factors are considered. Household adaptation interventions reflect demand but do not completely mitigate temperature-related risks, emphasising climate as the key determinant.