Effect modification of greenness on temperature-mortality relationship among older adults: A case-crossover study in China.
Effect modification of greenness on temperature-mortality relationship among older adults: A case-crossover study in China.
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绿色环境对老年人温度 - 死亡率关系的效应修正：中国的一项病例交叉研究
DOI：
10.1016/j.envres.2021.111112
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发表时间：
2021-06
影响因子：
8.3
通讯作者：
Bell ML
中科院分区：
文献类型：
--
作者：
Qiu C;Ji JS;Bell ML
气候变化加剧了与温度相关的死亡率，但影响可能因地理特征而异。我们假设，较高的绿色度可能会减轻温度相关的死亡率，并且这种效果在不同地区可能会有所不同。我们研究了2000-2014年中国老年人的死亡率与温度的关系，以及地理位置和住宅绿化如何调节这种关系。我们使用的健康数据来自中国健康长寿纵向调查（CLHLS），气象数据来自国家气候数据中心的全球地表日摘要（GSOD）产品。我们采用病例交叉研究设计和分布式非线性模型来估计与温度相关的死亡风险，并通过绿色度的四分位数进行分层分析。绿度由归一化植被指数（NDVI）从遥感图像估计。除了全国性的分析，我们还评估了三个省（江苏、广东和辽宁），以检查气候区域的差异。极端温度与较高的死亡率有着显著的关联，但存在地区差异。来自全国分析的结果表明，处于绿色暴露最低四分位数的个人的相对风险比（RRR）为1.38（0.79，2.42）在极端炎热的日子里，第95百分位数的死亡风险与第50百分位数的死亡风险相比，与最高四分位数的死亡风险相比，这意味着那些居住在绿色度最低四分位数的人比居住在绿色度最高四分位数的人的RR高38%，其中RR指的是与第50百分位数的天数相比，第95百分位数的天数的死亡风险。与第50百分位数相比，极寒天死亡风险的绿色度最高至最低四分位数的RRR为2.08（0.12，36.2）。在江苏和广东，最高绿度四分位数的热效应和冷效应均最低，辽宁的结果不显著，表明不同区域绿度对温度-死亡率关系的调节效应不同。我们阐明了一种途径，通过这种途径，绿色通过减少极端高温的影响而有益于健康。绿色的影响因气候地区而异。决策者应在气候变化和健康的背景下考虑植被问题。
Climate change exacerbates temperature-related mortality, but effects may vary by geographic characteristics. We hypothesize that higher greenness may mitigate temperature-related mortality, and that the effect may vary in different areas. We examined how mortality among older adults in China was associated with temperature for 2000–2014, and how geolocation and residential greenness may modulate this association. We used health data from the China Longitudinal Healthy Longevity Survey (CLHLS), and meteorological data from the Global Surface Summary of Day (GSOD) product by National Climate Data Center. We used a case-crossover study design with distributed nonlinear modeling to estimate mortality risks in relation to temperature, and stratified analysis by quartile of greenness. Greenness was estimated by Normalized Difference Vegetation Index (NDVI) from remote-sensed imagery. In addition to the national analysis, we also assessed three provinces (Jiangsu, Guangdong, and Liaoning) to examine differences by climatic regions. Extreme temperatures had a significant association with higher mortality, with regional differences. Findings from the national analysis suggest that individuals in the lowest quartile of greenness exposure had a ratio of relative risks (RRR) of 1.38 (0.79, 2.42) for mortality risk on extreme hot days at the 95th percentile compared to those at the 50th percentile, compared to those in the highest quartile, which means those residing in the lowest quartile of greenness had a 38% higher RR than those residing in the highest quartile of greenness, where RR refers to the risk of mortality on days at the 95th percentile of temperature compared to days at the 50th percentile. The RRR for the highest to lowest quartiles of greenness for mortality risk on extreme cold days at the 5th percentile compared to the 50th percentile was 2.08 (0.12, 36.2). In Jiangsu and Guangdong provinces, both the heat effects and cold effects were the lowest in the highest greenness quartile, and the results in Liaoning province were not statistically significant, indicating different regional effects of greenness on modulating the temperature-mortality relationship. We elucidated one pathway through which greenness benefits health by decreasing impact from extreme high temperatures. The effects of greenness differed by climatic regions. Policymakers should consider vegetation in the context of climate change and health.
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DOI：
10.1136/bmj.k4306
发表时间：
2018-10-31
期刊：
BMJ (Clinical research ed.)
影响因子：
--
作者：
Chen R;Yin P;Wang L;Liu C;Niu Y;Wang W;Jiang Y;Liu Y;Liu J;Qi J;You J;Kan H;Zhou M
通讯作者：
Zhou M
DOI：
10.1186/s12940-016-0103-6
发表时间：
2016-03-08
期刊：
Environmental health : a global access science source
影响因子：
--
作者：
Salmond JA;Tadaki M;Vardoulakis S;Arbuthnott K;Coutts A;Demuzere M;Dirks KN;Heaviside C;Lim S;Macintyre H;McInnes RN;Wheeler BW
通讯作者：
Wheeler BW
影响因子：
8.3
作者：
Son, Ji-Young;Lane, Kevin J.;Lee, Jong-Tae;Bell, Michelle L.
通讯作者：
Bell, Michelle L.
影响因子：
5.8
作者：
Gasparrini, Antonio
通讯作者：
Gasparrini, Antonio
DOI：
10.1097/ede.0b013e318190ee08
发表时间：
2009-03
期刊：
Epidemiology (Cambridge, Mass.)
影响因子：
--
作者：
Anderson BG;Bell ML
通讯作者：
Bell ML