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归因于热应激的心血管发病风险:来自中国深圳的紧急救护车派遣数据的分析。

Cardiovascular morbidity risk attributable to thermal stress: analysis of emergency ambulance dispatch data from Shenzhen, China.

机构信息

Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, Hubei, 430030, China.

Children's Hospital of Nanjing Medical University, Nanjing, China.

出版信息

BMC Public Health. 2024 Oct 17;24(1):2861. doi: 10.1186/s12889-024-20144-1.

DOI:10.1186/s12889-024-20144-1
PMID:39420322
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11488127/
Abstract

BACKGROUND

Climate change has raised scientific interest in examining the associations of weather conditions with adverse health effects, while most studies determined human thermal stress using ambient air temperature rather than the thermophysiological index.

OBJECTIVES

To evaluate the association between emergency ambulance dispatches (EADs) related to cardiovascular causes and heat/cold stress in Shenzhen, a city in southern China, with the aim of providing new insights for local policymakers.

METHODS

A time series analysis using ambulance dispatch data of cardiovascular diseases in Shenzhen, China (2013-2019) was conducted. A quasi-Poisson nonlinear distributed lag model was applied to explore the relationship between emergency ambulance dispatches (EADs) due to cardiovascular causes and thermal stress (determined by Universal Thermal Climate Index, UTCI). Attributable fractions were estimated to identify which UTCI ranges have a greater health impact.

RESULTS

The relationship between UTCI and EADs due to cardiovascular diseases exhibits a reverse J-shaped curve. The effects of cold stress were immediate and long-lasting, whereas the effects of heat stress were non-significant. Compared with the optimal equivalent temperature (71st percentile of UTCI, 29.22 °C), the relative risks for cumulative (0-21 days) exposures to cold stress (1st percentile, - 0.13 °C; 5th percentile, 7.68 °C) were 1.55 (95%CI:1.28,1.88) and 1.44 (95%CI:1.22,1.69), respectively. Thermal (cold and heat) stress was responsible for 10.81% (95%eCI: 5.67%,15.43%) of EADs for cardiovascular diseases, with 9.46% (95%eCI: 3.98%,14.40%) attributed to moderate cold stress (2.5th ~ 71st percentile). Greater susceptibility to cold stress was observed for males and the elderly. Heat stress showed harmful effects in the warm season.

CONCLUSIONS

Our results demonstrated that cold exposure elevates the risk of EADs for cardiovascular causes in Shenzhen, and moderate cold stress cause the highest burden of ambulance dispatches. Health authorities should consider effective adaptation strategies and interventions responding to cold stress to reduce the morbidity of cardiovascular diseases.

摘要

背景

气候变化引发了科学界对天气条件与不良健康影响之间关联的研究兴趣,而大多数研究使用环境空气温度而非生理热指数来确定人体热应激。

目的

评估中国南方城市深圳与心血管疾病相关的紧急救护车派遣(EAD)与热/冷应激之间的关联,旨在为当地政策制定者提供新的见解。

方法

使用中国深圳(2013-2019 年)心血管疾病的救护车派遣数据进行时间序列分析。应用广义可加模型-分布滞后模型(GAM-DL)来探索因心血管疾病导致的紧急救护车派遣(EAD)与热应激(由通用热气候指数,UTCI 确定)之间的关系。估计归因分数以确定哪些 UTCI 范围具有更大的健康影响。

结果

UTCI 与心血管疾病相关的 EAD 之间呈反“J”形曲线关系。冷应激的影响是即时和持久的,而热应激的影响则不显著。与最佳等效温度(UTCI 的第 71 百分位数,29.22°C)相比,累积(0-21 天)冷应激暴露(第 1 百分位数,-0.13°C;第 5 百分位数,7.68°C)的相对风险分别为 1.55(95%CI:1.28,1.88)和 1.44(95%CI:1.22,1.69)。热(冷和热)应激导致心血管疾病 EAD 的 10.81%(95%eCI:5.67%,15.43%),其中 9.46%(95%eCI:3.98%,14.40%)归因于中度冷应激(第 25 百分位至第 71 百分位)。男性和老年人对冷应激的敏感性更高。在温暖季节,热应激会产生有害影响。

结论

我们的研究结果表明,在深圳,暴露于寒冷会增加因心血管疾病而导致 EAD 的风险,而中度冷应激会导致最高的救护车派遣负担。卫生当局应考虑采取有效的适应策略和干预措施来应对冷应激,以降低心血管疾病的发病率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1b1/11488127/1b444f549d75/12889_2024_20144_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1b1/11488127/79fa12c0d9c2/12889_2024_20144_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1b1/11488127/e899e8a676ed/12889_2024_20144_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1b1/11488127/1b444f549d75/12889_2024_20144_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1b1/11488127/79fa12c0d9c2/12889_2024_20144_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1b1/11488127/ba2d8c83d28f/12889_2024_20144_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1b1/11488127/e899e8a676ed/12889_2024_20144_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d1b1/11488127/1b444f549d75/12889_2024_20144_Fig4_HTML.jpg

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