Department of Epidemiology and Biostatistics, School of Public Health, MRC Centre for Environment and Health, Imperial College London, Norfolk Place, London, W2 1PG, UK.
Protection Research Unit in Chemical and Radiation Threats and Hazards, Department of Epidemiology and Biostatistics, School of Public Health, National Institute for Health Research Health, Imperial College London, Norfolk Place, London, W2 1PG, UK.
J Urban Health. 2022 Dec;99(6):1012-1026. doi: 10.1007/s11524-022-00695-7. Epub 2022 Nov 10.
Exposure to non-optimal temperatures remains the single most deathful direct climate change impact to health. The risk varies based on the adaptation capacity of the exposed population which can be driven by climatic and/or non-climatic factors subject to fluctuations over time. We investigated temporal changes in the exposure-response relationship between daily mean temperature and mortality by cause of death, sex, age, and ethnicity in the megacity of São Paulo, Brazil (2000-2018). We fitted a quasi-Poisson regression model with time-varying distributed-lag non-linear model (tv-DLNM) to obtain annual estimates. We used two indicators of adaptation: trends in the annual minimum mortality temperature (MMT), i.e., temperature at which the mortality rate is the lowest, and in the cumulative relative risk (cRR) associated with extreme cold and heat. Finally, we evaluated their association with annual mean temperature and annual extreme cold and heat, respectively to assess the role of climatic and non-climatic drivers. In total, we investigated 4,471,000 deaths from non-external causes. We found significant temporal trends for both the MMT and cRR indicators. The former was decoupled from changes in AMT, whereas the latter showed some degree of alignment with extreme heat and cold, suggesting the role of both climatic and non-climatic adaptation drivers. Finally, changes in MMT and cRR varied substantially by sex, age, and ethnicity, exposing disparities in the adaptation capacity of these population groups. Our findings support the need for group-specific interventions and regular monitoring of the health risk to non-optimal temperatures to inform urban public health policies.
暴露于非最佳温度仍然是对健康最致命的直接气候变化影响。风险因暴露人群的适应能力而异，适应能力可能受到气候和/或非气候因素的驱动，这些因素随时间而波动。我们研究了巴西圣保罗大都市因每日平均温度和死因、性别、年龄和种族而导致的暴露-反应关系的时间变化（2000-2018 年）。我们拟合了一个具有时变分布滞后非线性模型（tv-DLNM）的拟泊松回归模型，以获得年度估计值。我们使用了两个适应指标：年度最低死亡率温度（MMT）的趋势，即死亡率最低的温度，以及与极寒和极热相关的累积相对风险（cRR）。最后，我们分别评估了它们与年平均温度和年极端寒冷和炎热的关联，以评估气候和非气候驱动因素的作用。我们总共研究了 447.1 万例非外部原因导致的死亡。我们发现 MMT 和 cRR 指标都存在显著的时间趋势。前者与 AMT 的变化脱钩，而后者与极寒和极热显示出一定程度的一致性，这表明气候和非气候适应驱动因素都发挥了作用。最后，MMT 和 cRR 的变化在性别、年龄和种族方面存在很大差异，这表明这些人群群体的适应能力存在差异。我们的研究结果支持针对特定群体的干预措施和对非最佳温度健康风险的定期监测的必要性，以为城市公共卫生政策提供信息。
