• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

开发和验证中国东部城市的时空空气质量健康指数。

Developing and validating intracity spatiotemporal air quality health index in eastern China.

机构信息

Institute of Social Development and Health Management, Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Wuhan University of Science and Technology, Wuhan 430065, China.

Department of Pediatrics, Hubei Provincial Clinical Research Center for Umbilical Cord Blood Hematopoietic Stem Cells, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, Hubei, China.

出版信息

Sci Total Environ. 2024 Nov 15;951:175556. doi: 10.1016/j.scitotenv.2024.175556. Epub 2024 Aug 15.

DOI:10.1016/j.scitotenv.2024.175556
PMID:39153638
Abstract

BACKGROUND

Recently pilot published city-level air quality health index (AQHI) provides a useful tool for communicating short-term health risks of ambient air pollution, but fails to account for intracity spatial heterogeneity in exposure and associated population health impacts. This study aims to develop the intracity spatiotemporal AQHI (ST-AQHI) via refined air pollution-related health risk assessments.

METHODS

A three-stage analysis was conducted through integrating province-wide death surveillance data and high-resolution gridded estimates of air pollution and climate factors spanning 2016-2019 in Jiangsu Province, eastern China. First, an individual-level case-crossover design was employed to quantify the short-term risk of nonaccidental mortality associated with residential exposure to individual pollutant (i.e., PM, NO, O, and SO). Second, we accumulated and scaled the excess risks arising from multiple pollutants to formulate daily gridded ST-AQHI estimates at 0.1° × 0.1°, dividing exposure-related risks into low (0-3), moderate (4-6), high (7-9), and extreme high (10+) levels. Finally, the effectiveness of ST-AQHI as composite risk communication was validated through checking the dose-response associations of individual ST-AQHI exposure with deaths from nonaccidental and major cardiopulmonary causes via repeating case-crossover analyses.

RESULTS

We analyzed a total of 1,905,209 nonaccidental death cases, comprising 785,567 from circulatory diseases and 247,336 from respiratory diseases. In the first-stage analysis, for each 10-μg/m rise in PM, NO, O, and SO exposure at lag-01 day, population risk of nonaccidental death was increased by 0.8% (95% confidence interval: 0.7%, 0.9%), 1.9% (1.7%, 2.0%), 0.4% (0.3%, 0.5%), and 4.1% (3.7%, 4.5%), respectively. Spatiotemporal distribution of ST-AQHI exhibited a consistent declining trend throughout the study period (2016-2019), with annual average ST-AQHI decreasing from 5.2 ± 1.3 to 4.0 ± 1.0 and high-risk days dropping from 15.8% (58 days) to 1.6% (6 days). Exposure associated health risks showed great intracity- and between-city heterogeneities. In the validation analysis, ST-AQHI demonstrated approximately linear, threshold-free associations with multiple death events from nonaccidental and major cardiopulmonary causes, suggesting excellent performance in predicting exposure-related health risks. Specifically, each 1-unit rise in ST-AQHI was significantly associated with an excess risk of 2.0% (1.8%, 2.1%) for nonaccidental mortality, 2.3% (2.1%, 2.6%) for overall circulatory mortality, and 2.7% (2.3%, 3.1%) for overall respiratory mortality, as well as 1.7%-3.0% for major cardiopulmonary sub-causes.

CONCLUSIONS

ST-AQHI developed in this study performed well in predicting intracity spatiotemporal heterogeneity of death risks related to multiple air pollutants, and may hold significant practical importance in communicating air pollution-related health risks to the public at the community scales.

摘要

背景

最近发布的城市空气质量健康指数(AQHI)为短期环境空气污染健康风险提供了一个有用的工具,但未能考虑到城市内部暴露的空间异质性及其对人群健康的影响。本研究旨在通过精细化空气污染相关健康风险评估来开发城市内时空空气质量健康指数(ST-AQHI)。

方法

通过整合江苏省 2016-2019 年全省死亡监测数据和高分辨率网格化空气污染及气候因素数据,采用三阶段分析方法。首先,采用个体水平病例交叉设计来量化与居民暴露相关的个体污染物(即 PM、NO、O 和 SO)的非意外死亡率的短期风险。其次,我们累加并放大了多种污染物的超额风险,以制定每日网格化 ST-AQHI 估计值,空间分辨率为 0.1°×0.1°,将暴露相关风险分为低(0-3)、中(4-6)、高(7-9)和极高(10+)水平。最后,通过重复病例交叉分析检查个体 ST-AQHI 暴露与非意外和主要心肺疾病死亡之间的剂量-反应关系,验证 ST-AQHI 作为综合风险沟通的有效性。

结果

我们分析了总共 1905209 例非意外死亡病例,其中循环系统疾病 785567 例,呼吸系统疾病 247336 例。在第一阶段分析中,对于 PM、NO、O 和 SO 暴露每增加 10μg/m,滞后 01 天的非意外死亡人群风险分别增加 0.8%(95%置信区间:0.7%,0.9%)、1.9%(1.7%,2.0%)、0.4%(0.3%,0.5%)和 4.1%(3.7%,4.5%)。ST-AQHI 的时空分布在整个研究期间呈一致下降趋势,2016-2019 年的年均 ST-AQHI 从 5.2±1.3 降至 4.0±1.0,高危天数从 15.8%(58 天)降至 1.6%(6 天)。暴露相关健康风险呈现出明显的城市内和城市间异质性。在验证分析中,ST-AQHI 与非意外和主要心肺疾病死亡的多个事件呈近似线性、无阈值关联,表明其在预测暴露相关健康风险方面表现良好。具体而言,ST-AQHI 每增加 1 个单位,非意外死亡率的超额风险增加 2.0%(1.8%,2.1%),整体循环系统死亡率增加 2.3%(2.1%,2.6%),整体呼吸系统死亡率增加 2.7%(2.3%,3.1%),主要心肺疾病亚病因增加 1.7%-3.0%。

结论

本研究开发的 ST-AQHI 能够很好地预测与多种空气污染物相关的死亡风险的城市内时空异质性,在社区层面上向公众传达与空气污染相关的健康风险方面具有重要的实际意义。

相似文献

1
Developing and validating intracity spatiotemporal air quality health index in eastern China.开发和验证中国东部城市的时空空气质量健康指数。
Sci Total Environ. 2024 Nov 15;951:175556. doi: 10.1016/j.scitotenv.2024.175556. Epub 2024 Aug 15.
2
Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE): Phase 2.低暴露环境下死亡率与空气污染关联研究(MAPLE):第二阶段。
Res Rep Health Eff Inst. 2022 Jul;2022(212):1-91.
3
Multicity study of air pollution and mortality in Latin America (the ESCALA study).拉丁美洲空气污染与死亡率的多城市研究(ESCALA研究)。
Res Rep Health Eff Inst. 2012 Oct(171):5-86.
4
Effects of short-term exposure to air pollution on hospital admissions of young children for acute lower respiratory infections in Ho Chi Minh City, Vietnam.越南胡志明市短期暴露于空气污染对幼儿急性下呼吸道感染住院率的影响。
Res Rep Health Eff Inst. 2012 Jun(169):5-72; discussion 73-83.
5
Social Susceptibility to Multiple Air Pollutants in Cardiovascular Disease.社会对心血管疾病多种空气污染物的易感性。
Res Rep Health Eff Inst. 2021 Jul;2021(206):1-71.
6
Mortality and Morbidity Effects of Long-Term Exposure to Low-Level PM, BC, NO, and O: An Analysis of European Cohorts in the ELAPSE Project.长期暴露于低水平 PM、BC、NO 和 O 对死亡率和发病率的影响:ELAPSE 项目中欧洲队列的分析。
Res Rep Health Eff Inst. 2021 Sep;2021(208):1-127.
7
Effects of long-term exposure to traffic-related air pollution on respiratory and cardiovascular mortality in the Netherlands: the NLCS-AIR study.长期暴露于交通相关空气污染对荷兰呼吸道和心血管疾病死亡率的影响:荷兰长期队列空气污染研究(NLCS-AIR研究)
Res Rep Health Eff Inst. 2009 Mar(139):5-71; discussion 73-89.
8
Communicating air pollution-related health risks to the public: an application of the Air Quality Health Index in Shanghai, China.向公众传达与空气污染有关的健康风险:中国上海空气质量健康指数的应用。
Environ Int. 2013 Jan;51:168-73. doi: 10.1016/j.envint.2012.11.008. Epub 2012 Dec 12.
9
Air quality health index (AQHI) based on multiple air pollutants and mortality risks in Taiwan: Construction and validation.基于多种空气污染物和死亡风险的空气质量健康指数 (AQHI) 在台湾的构建和验证。
Environ Res. 2023 Aug 15;231(Pt 2):116214. doi: 10.1016/j.envres.2023.116214. Epub 2023 May 22.
10
Part 2. Association of daily mortality with ambient air pollution, and effect modification by extremely high temperature in Wuhan, China.第二部分. 中国武汉每日死亡率与环境空气污染的关联以及极高温度的效应修正
Res Rep Health Eff Inst. 2010 Nov(154):91-217.