Projecting future minimum mortality temperature in China

Minimum mortality temperature (MMT) increases with global warming due to climate adaptation, which is crucial for the precise assessment of mortality burden attributed to climate change. Nevertheless, forecasting future MMT poses a challenge given the unavailability of future mortality data. Here, we attempted to develop a novel approach to project future MMT. First, we estimated the MMT of 334 locations in China using a distributed lag nonlinear model. Then, meta regression models were applied to investigate the associations between MMT and several temperature variables(Most Frequent Temperature(MFT), average daily mean temperature, average daily minimum temperature, average daily maximum temperature and percentiles of temperature from 1st to 100th). A generalized linear regression model was employed to investigate whether significant differences existed in the relationships between MMT and temperature from the 1st to the 100th percentile. Finally, an optional indicator of MMT for projecting future values was identified. Our results indicated that temperatures in the 85th to 89th percentiles were closely associated with MMT, with the 88th percentile temperature serving as the most effective indicator, as confirmed by meta-regression models. Using the 88th percentile of temperature as alternative indicator of MMT, compared with the period of 2006-2015, the projected MMT in most districts and counties in China tended to rise under three representative concentration pathways (RCPs) in the 2030 s (2030-2039), 2060 s (2060-2069), and 2090 s (2090-2099). Our findings provide some insight to project future MMT for assessing mortality burden related to temperature change driven by global warming.

Authors

Institutions

Publication Details

Journal
Ecotoxicology and Environmental Safety
Published
2024-10-19
DOI
https://doi.org/10.1016/j.ecoenv.2024.117192
Citations
1
Primary Topic
Climate Change and Health Impacts
Type
article
Field-Weighted Citation Impact
0.31

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Projecting future minimum mortality temperature in China

Jianpeng Xiao, Biao Huang, Zhulin Hou, Guanhao He et al.
1 citations
Ecotoxicology and Environmental Safety
Climate Change and Health Impacts
0.31
article

Projecting future minimum mortality temperature in China

Jianpeng Xiao, Biao Huang, Zhulin Hou, Guanhao He, Wenbiao Hu, Chunliang Zhou, Zhoupeng Ren, Cunrui Huang, Ruilin Meng, Jianxiong Hu, Xiaojun Xu, Lifang Luo, Tao Liu, Haoming Zhang, Weiwei Gong, Min Yu, Mingfang Qin, Wenjun Ma, Yize Xiao, Zuhua Rong
article en
1 citations

Abstract

Minimum mortality temperature (MMT) increases with global warming due to climate adaptation, which is crucial for the precise assessment of mortality burden attributed to climate change. Nevertheless, forecasting future MMT poses a challenge given the unavailability of future mortality data. Here, we attempted to develop a novel approach to project future MMT. First, we estimated the MMT of 334 locations in China using a distributed lag nonlinear model. Then, meta regression models were applied to investigate the associations between MMT and several temperature variables(Most Frequent Temperature(MFT), average daily mean temperature, average daily minimum temperature, average daily maximum temperature and percentiles of temperature from 1st to 100th). A generalized linear regression model was employed to investigate whether significant differences existed in the relationships between MMT and temperature from the 1st to the 100th percentile. Finally, an optional indicator of MMT for projecting future values was identified. Our results indicated that temperatures in the 85th to 89th percentiles were closely associated with MMT, with the 88th percentile temperature serving as the most effective indicator, as confirmed by meta-regression models. Using the 88th percentile of temperature as alternative indicator of MMT, compared with the period of 2006-2015, the projected MMT in most districts and counties in China tended to rise under three representative concentration pathways (RCPs) in the 2030 s (2030-2039), 2060 s (2060-2069), and 2090 s (2090-2099). Our findings provide some insight to project future MMT for assessing mortality burden related to temperature change driven by global warming.

Ecotoxicology and Environmental SafetyVol. 286
Jinan University (CN), Queensland University of Technology (AU), Hunan Provincial Center for Disease Control and Prevention (CN), Health Commission of Jilin Province (CN), Yunnan Center for Disease Control And Prevention (CN), Weihai Maternal and Child Health Hospital (CN), Zhejiang Center for Disease Control and Prevention (CN), Guangdong Provincial Center for Disease Control and Prevention (CN), Institute of Geographic Sciences and Natural Resources Research (CN), Tsinghua University (CN)
National Natural Science Foundation of China, Chinese Academy of Sciences, Natural Science Foundation of Guangdong Province, Guangzhou Municipal Science and Technology Project, National Key Research and Development Program of China
Openalex Percentile: Top 37%
Climate Change and Health Impacts
0.31
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.