气候变化领域集成服务门户(CCPortal): The joint effects of mixture exposure to multiple meteorological factors on step count: A panel study in China

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DOI	10.1016/j.envpol.2024.123469
	The joint effects of mixture exposure to multiple meteorological factors on step count: A panel study in China
	Lin, Ziqiang; Wang, Mengmeng; Ma, Junrong; Liu, Yingyin; Lawrence, Wayne R.; Chen, Shirui; Zhang, Wangjian; Hu, Jianxiong; He, Guanhao; Liu, Tao; Zhang, Ming; Ma, Wenjun
发表日期	2024
ISSN	0269-7491
EISSN	1873-6424
起始页码	346
卷号	346
英文摘要	The public health burden of increasing extreme weather events has been well documented. However, the influence of meteorological factors on physical activity remains limited. Existing mixture effect methods cannot handle cumulative lag effects. Therefore, we developed quantile g-computation Distributed lag non-linear model (QG-DLNM) by embedding a DLNM into quantile g-computation to allow for the concurrent consideration of both cumulated lag effects and mixture effects. We gathered repeated measurement data from Henan Province in China to investigate both the individual impact of meteorological factor on step counts using a DLNM, and the joint effect using the QG-DLNM. We projected future step counts linked to changes in temperature and relative humidity driven by climate change under three scenarios from the sixth phase of the Coupled Model Intercomparison Project. Our findings indicate there are inversed U-shaped associations for temperature, wind speed, and mixture exposure with step counts, peaking at 11.6 C in temperature, 2.7 m/s in wind speed, and 30th percentile in mixture exposure. However, there are negative associations between relative humidity and rainfall with step counts. Additionally, relative humidity possesses the highest weights in the joint effect (49% contribution). Compared to 2022s, future step counts are projected to decrease due to temperature changes, while increase due to relative humidity changes. However, when considering both future temperature and humidity changes driven by climate change, the projections indicate a decrease in step counts. Our findings may suggest Chinese physical activity will be negatively influenced by global warming.
英文关键词	Mixture exposure; Joint effect; Meteorological factors; Physical activity; Quantile g-computation distributed lag non; linear model
语种	英语
WOS研究方向	Environmental Sciences & Ecology
WOS类目	Environmental Sciences
WOS记录号	WOS:001194075200001
来源期刊	ENVIRONMENTAL POLLUTION
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/289740
作者单位	Jinan University; Shenzhen University; State University of New York (SUNY) System; State University of New York (SUNY) Albany; Sun Yat Sen University; Jinan University
推荐引用方式 GB/T 7714	Lin, Ziqiang,Wang, Mengmeng,Ma, Junrong,et al. The joint effects of mixture exposure to multiple meteorological factors on step count: A panel study in China[J],2024,346.
APA	Lin, Ziqiang.,Wang, Mengmeng.,Ma, Junrong.,Liu, Yingyin.,Lawrence, Wayne R..,...&Ma, Wenjun.(2024).The joint effects of mixture exposure to multiple meteorological factors on step count: A panel study in China.ENVIRONMENTAL POLLUTION,346.
MLA	Lin, Ziqiang,et al."The joint effects of mixture exposure to multiple meteorological factors on step count: A panel study in China".ENVIRONMENTAL POLLUTION 346(2024).