Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, LMU Munich, Munich, Germany.
Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, LMU Munich, Munich, Germany.
Lancet Planet Health. 2022 Oct;6(10):e784-e792. doi: 10.1016/S2542-5196(22)00195-4.
As the climate changes, it is crucial to focus not only on mitigation measures but also on building climate change resilience by developing efficient adaptation strategies. Although population adaptation is a major determinant of future climate-related health burden, it is not well accounted for in studies that project the health impact of climate change. We propose a methodological framework for temperature-related mortality that incorporates two simultaneous adaptation-sensitivity pathways: the physiological pathway, considering both heat adaptation and cold sensitivity, and the socioeconomic pathway, which is influenced by changes in future adaptive capacities. To demonstrate its utility we apply the framework to a case study mortality time-series dataset from Bavaria, Germany.
In this modelling framework, we used extrapolated location-specific and age-specific baseline exposure-response functions and propose different future scenarios of cold sensitivity and heat adaptation on the basis of varying slopes of these exposure-response functions. We also incorporated future socioeconomic adaptation in the exposure-response functions using projections of gross domestic product under the respective shared socioeconomic pathways. Future adaptable fractions, representing the deaths avoided under each of the future scenarios, are projected under combinations of two climate change scenarios (shared socioeconomic pathway [SSP]1-2.6 and SSP3-7.0) and the respective plausible population projection scenarios (SSP1 and SSP3), also incorporating the future changes in demographic age structure and mortality. The case study for this framework was done for five districts in Bavaria, for both total non-accidental mortality and cardiovascular disease mortality. The baseline data was obtained for the period 1990-2006, and the future period was defined as 2083-99.
In our Bavaria case study, average temperature was projected to increase by 2099 by an average of 1·1°C under SSP1-2.6 and by 4·1°C under SSP3-7.0. We observed the adaptable fraction to be largely influenced by socioeconomic adaptation for both total mortality and cardiovascular disease mortality, and for both climate change scenarios. For example, for total mortality, the highest adaptable fraction of 18·56% (95% empirical CI 10·77-23·67) was observed under the SSP1-2.6 future scenario, in the presence of socioeconomic adaptation and under the highest heat adaptation (10%) provided the cold sensitivity remains 0%. The cold adaptable fraction is lower than the heat adaptable fraction under all scenarios. In the absence of socioeconomic adaptation, population ageing will lead to higher temperature-related mortality.
Our developed framework helps to systematically understand the effectiveness of adaptation mechanisms. In the future, socioeconomic adaptation is estimated to play a major role in determining temperature-related excess mortality. Furthermore, cold sensitivity might outweigh heat adaptation in the majority of locations worldwide. Similarly, population ageing is projected to continue to determine future temperature-related mortality.
EU Horizon 2020 (EXHAUSTION).
随着气候变化,不仅要关注减排措施,还要通过制定有效的适应策略来建立气候变化适应能力,这一点至关重要。尽管人口适应是未来与气候相关的健康负担的主要决定因素,但在预测气候变化对健康影响的研究中并没有很好地考虑到这一点。我们提出了一种与温度相关的死亡率的方法框架,该框架纳入了两个同时发生的适应敏感性途径:生理途径,同时考虑热适应和冷敏感;社会经济途径,受未来适应能力变化的影响。为了展示其实用性,我们将该框架应用于来自德国巴伐利亚的一个死亡率时间序列案例研究数据集。
在这个建模框架中,我们使用了外推的特定位置和特定年龄的基线暴露-反应函数,并根据这些暴露-反应函数的斜率变化提出了冷敏感和热适应的不同未来情景。我们还通过各自的共享社会经济途径下的国内生产总值预测,在暴露-反应函数中纳入了未来的社会经济适应。未来适应分数代表在每个未来情景下避免的死亡人数,根据两个气候变化情景(共享社会经济途径[SSP]1-2.6 和 SSP3-7.0)和各自的人口预测情景(SSP1 和 SSP3)的组合进行预测,同时还考虑了未来人口年龄结构和死亡率的变化。该框架的案例研究是针对巴伐利亚的五个区进行的,包括总非意外死亡率和心血管疾病死亡率。基线数据是在 1990-2006 年期间获得的,未来时期定义为 2083-99 年。
在我们的巴伐利亚案例研究中,到 2099 年,预计在 SSP1-2.6 情景下平均气温将上升 1.1°C,在 SSP3-7.0 情景下上升 4.1°C。我们观察到,对于总死亡率和心血管疾病死亡率,以及对于两种气候变化情景,社会经济适应对适应分数的影响很大。例如,对于总死亡率,在 SSP1-2.6 未来情景下,在存在社会经济适应的情况下,最高的适应分数为 18.56%(95%经验置信区间 10.77-23.67),同时假设热适应最高(10%),而冷敏感保持在 0%。在所有情景下,冷适应分数都低于热适应分数。在没有社会经济适应的情况下,人口老龄化将导致与温度相关的死亡率上升。
我们开发的框架有助于系统地了解适应机制的有效性。在未来,社会经济适应预计将在确定与温度相关的超额死亡率方面发挥主要作用。此外,在世界大多数地区,冷敏感可能超过热适应。同样,预计人口老龄化将继续决定未来与温度相关的死亡率。
欧盟地平线 2020(EXHAUSTION)。