Greenness, air pollution, and temperature exposure effects in predicting premature mortality and morbidity: A small-area study using spatial random forest model

被引:4
作者
Labib, S. M. [1 ,2 ]
机构
[1] Univ Utrecht, Fac Geosci, Dept Human Geog & Spatial Planning, Utrecht, Netherlands
[2] Vening Meineszgebouw A,Princetonlaan 8A, NL-3584 CB Utrecht, Netherlands
关键词
Air pollution; Temperature; Exposure Assessment; Machine Learning; Greenness exposure; Public Health; SURROUNDING GREENNESS; SOCIAL DETERMINANTS; GREATER MANCHESTER; TIME-SERIES; LIFE LOST; HEALTH; GREENSPACE; POPULATION; ASSOCIATION; BURDEN;
D O I
10.1016/j.scitotenv.2024.172387
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Background: Although studies have provided negative impacts of air pollution, heat or cold exposure on mortality and morbidity, and positive effects of increased greenness on reducing them, a few studies have focused on exploring combined and synergetic effects of these exposures in predicting these health outcomes, and most had ignored the spatial autocorrelation in analyzing their health effects. This study aims to investigate the health effects of air pollution, greenness, and temperature exposure on premature mortality and morbidity within a spatial machine-learning modeling framework. Methods: Years of potential life lost reflecting premature mortality and comparative illness and disability ratio reflecting chronic morbidity from 1673 small areas covering Greater Manchester for the year 2008-2013 obtained. Average annual levels of NO2 concentration, normalized difference vegetation index (NDVI) representing greenness, and annual average air temperature were utilized to assess exposure in each area. These exposures were linked to health outcomes using non-spatial and spatial random forest (RF) models while accounting for spatial autocorrelation. Results: Spatial-RF models provided the best predictive accuracy when accounted for spatial autocorrelation. Among the exposures considered, air pollution emerged as the most influential in predicting mortality and morbidity, followed by NDVI and temperature exposure. Nonlinear exposure-response relations were observed, and interactions between exposures illustrated specific ranges or sweet and sour spots of exposure thresholds where combined effects either exacerbate or moderate health conditions. Conclusion: Air pollution exposure had a greater negative impact on health compared to greenness and temperature exposure. Combined exposure effects may indicate the highest influence of premature mortality and morbidity burden.
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页数:13
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