Schwarz Lara, Chen Chen, Castillo Quiñones Javier Emmanuel, Aguilar-Dodier L C, Hansen Kristen, Sanchez Jaime Reyes, González David J X, McCord Gordon, Benmarhnia Tarik
School of Public Health, San Diego State University, San Diego, CA, USA; Herbert Wertheim School of Public Health and Longevity Science, University of California San Diego, La Jolla, CA, USA; Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, CA, USA.
Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA.
Environ Int. 2025 Jan;195:109231. doi: 10.1016/j.envint.2024.109231. Epub 2024 Dec 20.
Understanding effects of extreme heat across diverse settings is critical as social determinants play an important role in modifying heat-related risks. We apply a multi-scale analysis to understand spatial variation in the effects of heat across Mexico and explore factors that are explaining heterogeneity. Daily all-cause mortality was collected from the Mexican Secretary of Health and municipality-specific extreme heat events were estimated using population-weighted temperatures from 1998 to 2019 using Daymet and WorldPop datasets. We analyzed the association between single-day extreme heat events defined at the 99th percentile of the same-day maximum temperature and mortality, and seven heat threshold metrics based on relative and absolute scales were considered as sensitivity analyses. A time-stratified case-crossover was applied to evaluate heat impacts across 32 states in Mexico. A within-community matched design with Bayesian Hierarchical model explored effects across 2456 municipalities. A random-effects meta-regression was applied to understand which municipality-level socio-demographic characteristics such as education, age and housing predicted observed spatial heterogeneity. Extreme heat increased the odds of mortality overall, and this was consistent across extreme heat thresholds. At the state level, extreme heat events showed highest impact on mortality in Tabasco [OR: 1.23, 95% CI: 1.17, 1.30]. The municipality-level spatial analysis showed substantial differences across regions with highest effects observed along the eastern, southwestern and Sonora coasts. Municipalities with older populations, higher marginalization, lower education, and poorer housing conditions were more vulnerable to heat effects. Understanding the differential risks of extreme heat events at varying scales is important to prioritize at-risk populations in action plans and policies to reduce their burden.
了解极端高温在不同环境中的影响至关重要，因为社会决定因素在改变与高温相关的风险方面发挥着重要作用。我们应用多尺度分析来了解墨西哥各地高温影响的空间变化，并探索解释异质性的因素。从墨西哥卫生部收集了每日全因死亡率，并使用Daymet和WorldPop数据集，根据1998年至2019年的人口加权温度估算了特定城市的极端高温事件。我们分析了在当日最高温度的第99百分位数定义的单日极端高温事件与死亡率之间的关联，并将基于相对和绝对尺度的七个高温阈值指标作为敏感性分析。应用时间分层病例交叉法来评估墨西哥32个州的高温影响。采用贝叶斯分层模型的社区内匹配设计探索了2456个城市的影响。应用随机效应元回归来了解哪些城市层面的社会人口特征（如教育、年龄和住房）预测了观察到的空间异质性。极端高温总体上增加了死亡几率，并且在不同的极端高温阈值下都是一致的。在州一级，极端高温事件对塔巴斯科州的死亡率影响最大[比值比：1.23，95%置信区间：1.17，1.30]。城市层面的空间分析显示，各地区存在显著差异，在东部、西南部和索诺拉海岸观察到的影响最大。人口老龄化、边缘化程度较高、教育程度较低和住房条件较差的城市更容易受到高温影响。了解不同尺度下极端高温事件的差异风险对于在行动计划和政策中优先考虑高危人群以减轻其负担非常重要。
