Long-term exposure and health risk assessment from air pollution: impact of regional scale mobility.

IF 3 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH International Journal of Health Geographics Pub Date : 2023-05-19 DOI:10.1186/s12942-023-00333-8
Lorenza Gilardi, Mattia Marconcini, Annekatrin Metz-Marconcini, Thomas Esch, Thilo Erbertseder
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引用次数: 4

Abstract

Background: The negative effect of air pollution on human health is widely reported in recent literature. It typically involves urbanized areas where the population is concentrated and where most primary air pollutants are produced. A comprehensive health risk assessment is therefore of strategic importance for health authorities.

Methods: In this study we propose a methodology to perform an indirect and retrospective health risk assessment of all-cause mortality associated with long-term exposure to particulate matter less than 2.5 microns (PM2.5), nitrogen dioxide (NO2) and ozone (O3) in a typical Monday to Friday working week. A combination of satellite-based settlement data, model-based air pollution data, land use, demographics and regional scale mobility, allowed to examine the effect of population mobility and pollutants daily variations on the health risk. A Health Risk Increase (HRI) metric was derived on the basis of three components: hazard, exposure and vulnerability, utilizing the relative risk values from the World Health Organization. An additional metric, the Health Burden (HB) was formulated, which accounts for the total number of people exposed to a certain risk level.

Results: The effect of regional mobility patterns on the HRI metric was assessed, resulting in an increased HRI associated with all three stressors when considering a dynamic population compared to a static one. The effect of diurnal variation of pollutants was only observed for NO2 and O3. For both, the HRI metric resulted in significantly higher values during night. Concerning the HB parameter, we identified the commuting flows of the population as the main driver in the resulting metric.

Conclusions: This indirect exposure assessment methodology provides tools to support policy makers and health authorities in planning intervention and mitigation measures. The study was carried out in Lombardy, Italy, one of the most polluted regions in Europe, but the incorporation of satellite data makes our approach valuable for studying global health.

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空气污染的长期暴露和健康风险评估:区域规模流动的影响。
背景:最近的文献中广泛报道了空气污染对人类健康的负面影响。它通常涉及人口集中、主要空气污染物产生最多的城市化地区。因此,全面的健康风险评估对卫生当局具有战略重要性。方法:在本研究中,我们提出了一种方法,对典型的周一至周五工作周内长期暴露于2.5微米以下颗粒物(PM2.5)、二氧化氮(NO2)和臭氧(O3)的全因死亡率进行间接和回顾性健康风险评估。基于卫星的定居数据、基于模型的空气污染数据、土地利用、人口统计和区域规模的流动性相结合,可以检验人口流动和污染物日变化对健康风险的影响。健康风险增加(HRI)指标是根据三个组成部分得出的:危害、暴露和脆弱性,并利用世界卫生组织的相对风险值。制定了一个额外的指标,即健康负担(HB),它说明了暴露在一定风险水平下的总人数。结果:评估了区域流动模式对HRI指标的影响,与静态人群相比,在考虑动态人群时,导致与所有三种压力源相关的HRI增加。污染物的日变化效应仅对NO2和O3有影响。对于这两种情况,HRI指标导致夜间的数值明显更高。关于HB参数,我们确定人口的通勤流量是最终指标的主要驱动因素。结论:这种间接接触评估方法为支持决策者和卫生当局规划干预和缓解措施提供了工具。这项研究是在意大利伦巴第进行的,伦巴第是欧洲污染最严重的地区之一,但卫星数据的结合使我们的方法对研究全球健康有价值。
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来源期刊
International Journal of Health Geographics
International Journal of Health Geographics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH -
CiteScore
10.20
自引率
2.00%
发文量
17
审稿时长
12 weeks
期刊介绍: A leader among the field, International Journal of Health Geographics is an interdisciplinary, open access journal publishing internationally significant studies of geospatial information systems and science applications in health and healthcare. With an exceptional author satisfaction rate and a quick time to first decision, the journal caters to readers across an array of healthcare disciplines globally. International Journal of Health Geographics welcomes novel studies in the health and healthcare context spanning from spatial data infrastructure and Web geospatial interoperability research, to research into real-time Geographic Information Systems (GIS)-enabled surveillance services, remote sensing applications, spatial epidemiology, spatio-temporal statistics, internet GIS and cyberspace mapping, participatory GIS and citizen sensing, geospatial big data, healthy smart cities and regions, and geospatial Internet of Things and blockchain.
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