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Sci Total Environ. 2016 Jan 1;539:576-582. doi: 10.1016/j.scitotenv.2015.09.027. Epub 2015 Sep 16.
2
Nonlinear and threshold of the association between meteorological factors and bacillary dysentery in Beijing, China.中国北京气象因素与细菌性痢疾关联的非线性及阈值
Epidemiol Infect. 2015 Dec;143(16):3510-9. doi: 10.1017/S0950268815001156. Epub 2015 Jun 1.
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Mortality risk attributable to high and low ambient temperature: a multicountry observational study.高低环境温度所致的死亡风险:一项多国观察性研究。
Lancet. 2015 Jul 25;386(9991):369-75. doi: 10.1016/S0140-6736(14)62114-0. Epub 2015 May 20.
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Spatial-temporal pattern and risk factor analysis of bacillary dysentery in the Beijing-Tianjin-Tangshan urban region of China.中国京津唐城市地区细菌性痢疾的时空模式及危险因素分析
BMC Public Health. 2014 Sep 25;14:998. doi: 10.1186/1471-2458-14-998.
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Associations between extreme precipitation and childhood hand, foot and mouth disease in urban and rural areas in Hefei, China.极端降水与中国合肥市城乡地区儿童手足口病的关联。
Sci Total Environ. 2014 Nov 1;497-498:484-490. doi: 10.1016/j.scitotenv.2014.08.006. Epub 2014 Aug 23.
6
Spatiotemporal pattern of bacillary dysentery in China from 1990 to 2009: what is the driver behind?1990年至2009年中国细菌性痢疾的时空分布模式:其背后的驱动因素是什么?
PLoS One. 2014 Aug 5;9(8):e104329. doi: 10.1371/journal.pone.0104329. eCollection 2014.
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Temperature and atmospheric pressure may be considered as predictors for the occurrence of bacillary dysentery in Guangzhou, Southern China.温度和大气压可被视为中国南方广州地区细菌性痢疾发生的预测因子。
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Attributable risk from distributed lag models.分布滞后模型的归因风险。
BMC Med Res Methodol. 2014 Apr 23;14:55. doi: 10.1186/1471-2288-14-55.
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Meteorological variables and bacillary dysentery cases in Changsha City, China.中国长沙市气象变量与细菌性痢疾病例。
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环境温度对中国合肥城乡细菌性痢疾负担的影响。

Impacts of ambient temperature on the burden of bacillary dysentery in urban and rural Hefei, China.

作者信息

Cheng J, Xie M Y, Zhao K F, Wu J J, Xu Z W, Song J, Zhao D S, Li K S, Wang X, Yang H H, Wen L Y, Su H, Tong S L

机构信息

Department of Epidemiology and Health Statistics,School of Public Health, Anhui Medical University,Hefei,Anhui 230032,China.

Hefei Center for Disease Control and Prevention of Anhui Province,Hefei,Anhui 230061,China.

出版信息

Epidemiol Infect. 2017 Jun;145(8):1567-1576. doi: 10.1017/S0950268817000280. Epub 2017 Mar 15.

DOI:10.1017/S0950268817000280
PMID:28294081
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9203284/
Abstract

Bacillary dysentery continues to be a major health issue in developing countries and ambient temperature is a possible environmental determinant. However, evidence about the risk of bacillary dysentery attributable to ambient temperature under climate change scenarios is scarce. We examined the attributable fraction (AF) of temperature-related bacillary dysentery in urban and rural Hefei, China during 2006-2012 and projected its shifting pattern under climate change scenarios using a distributed lag non-linear model. The risk of bacillary dysentery increased with the temperature rise above a threshold (18·4 °C), and the temperature effects appeared to be acute. The proportion of bacillary dysentery attributable to hot temperatures was 18·74% (95 empirical confidence interval (eCI): 8·36-27·44%). Apparent difference of AF was observed between urban and rural areas, with AF varying from 26·87% (95% eCI 16·21-36·68%) in urban area to -1·90% (95 eCI -25·03 to 16·05%) in rural area. Under the climate change scenarios alone (1-4 °C rise), the AF from extreme hot temperatures (>31·2 °C) would rise greatly accompanied by the relatively stable AF from moderate hot temperatures (18·4-31·2 °C). If climate change proceeds, urban area may be more likely to suffer from rapidly increasing burden of disease from extreme hot temperatures in the absence of effective mitigation and adaptation strategies.

摘要

细菌性痢疾仍然是发展中国家的一个主要健康问题,环境温度可能是一个环境决定因素。然而,关于气候变化情景下环境温度导致细菌性痢疾风险的证据很少。我们研究了2006 - 2012年中国合肥城乡与温度相关的细菌性痢疾归因分数(AF),并使用分布滞后非线性模型预测了气候变化情景下其变化模式。当温度升高超过阈值(18.4°C)时,细菌性痢疾的风险增加,且温度效应似乎较为急性。高温导致的细菌性痢疾比例为18.74%(95%经验置信区间(eCI):8.36 - 27.44%)。城乡之间观察到AF存在明显差异,城市地区AF为26.87%(95% eCI 16.21 - 36.68%),农村地区为 - 1.90%(95% eCI - 25.03至16.05%)。仅在气候变化情景下(气温上升1 - 4°C),极端高温(>31.2°C)导致的AF将大幅上升,同时中度高温(18.4 - 31.2°C)导致的AF相对稳定。如果气候变化持续,在缺乏有效缓解和适应策略的情况下,城市地区可能更容易遭受极端高温导致的疾病负担迅速增加。