2020
DOI: 10.1016/s2542-5196(20)30027-9
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Interaction between residential greenness and air pollution mortality: analysis of the Chinese Longitudinal Healthy Longevity Survey

Abstract: Background Both air pollution and green space have been shown to affect health. We aimed to assess whether greenness protects against air pollution-related mortality. Methods We used data from the 2008 wave of the Chinese Longitudinal Healthy Longevity Survey. We calculated contemporaneous normalised difference vegetation index (NDVI) in the 500 m radius around each participant's residence. Fine particulate matter (PM 2•5) concentration was calculated using 3-year average concentrations in 1 km × 1 km grid res… Show more

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Cited by 131 publications
(82 citation statements)
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References 42 publications
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“…It combines remote sensing from National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometers, and Sea-viewing Wide eld-of-view Sensor satellite instruments; vertical pro les derived from the GEOS-Chem chemical transport model; and calibration to ground-based observations of PM 2.5 using geographically weighted regression. Annual PM 2.5 estimates were calculated from 2000 to 2014, at 1 km x 1 km spatial resolution, which was the longest and the highest resolution exposure dataset available [33,34]. Additionally, our estimations were highly consistent with out-of-sample crossvalidated concentrations from monitors (R²=0•81) and another exposure dataset in China (R²=0•79) [32].…”
Section: Methodssupporting
confidence: 58%
“…It combines remote sensing from National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometers, and Sea-viewing Wide eld-of-view Sensor satellite instruments; vertical pro les derived from the GEOS-Chem chemical transport model; and calibration to ground-based observations of PM 2.5 using geographically weighted regression. Annual PM 2.5 estimates were calculated from 2000 to 2014, at 1 km x 1 km spatial resolution, which was the longest and the highest resolution exposure dataset available [33,34]. Additionally, our estimations were highly consistent with out-of-sample crossvalidated concentrations from monitors (R²=0•81) and another exposure dataset in China (R²=0•79) [32].…”
Section: Methodssupporting
confidence: 58%
“…It combines remote sensing from National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometers, and Sea-viewing Wide eld-of-view Sensor satellite instruments; vertical pro les derived from the GEOS-Chem chemical transport model; and calibration to ground-based observations of PM 2.5 using geographically weighted regression. Annual PM 2.5 estimates were calculated from 2000 to 2014, at 1 km x 1 km spatial resolution, which was the longest and the highest resolution exposure dataset available [32,33]. Additionally, our estimations were highly consistent with out-of-sample crossvalidated concentrations from monitors (R²=0•81) and another exposure dataset in China (R²=0•79) [31].…”
Section: Assessment Of Pm 25 Exposuresupporting
confidence: 58%
“…Numerous studies have explained the protective effects of greenness exposure in decreasing PM 2.5 concentrations 65 , 66 and in reducing general health burdens and specific health burdens, such as respiratory diseases 28 , 67 . A cohort study conducted in China researched the interaction between residential greenness and mortality related to air pollution 68 . The study noted the synergistic effect of greenness and concluded that controlling air pollution helps to improve the public’s health and well-being 68 .…”
Section: Discussionmentioning
confidence: 99%
“…A cohort study conducted in China researched the interaction between residential greenness and mortality related to air pollution 68 . The study noted the synergistic effect of greenness and concluded that controlling air pollution helps to improve the public’s health and well-being 68 . Nonetheless, there were no significant associations in the Southeast Asian or Eastern Mediterranean regions regardless of greenness levels.…”
Section: Discussionmentioning
confidence: 99%