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极端温度与突发事件的关系:中国深圳的时间序列分析。

The relationship between extreme temperature and emergency incidences: a time series analysis in Shenzhen, China.

机构信息

Environment and Health Department, Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, Guangdong, China.

Key Laboratory of Molecular Biology, Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, Guangdong, China.

出版信息

Environ Sci Pollut Res Int. 2018 Dec;25(36):36239-36255. doi: 10.1007/s11356-018-3426-8. Epub 2018 Oct 26.

Abstract

Extreme temperature has been reported to be associated with an increase in acute disease incidence in several cities. However, few similar studies were carried out in Shenzhen, which is a subtropical city located in the southern China. This study explored the relationship between the emergency incidences and extreme temperatures, and investigated the role of air pollutants played in the temperature-related effects on human health in Shenzhen. We conducted a distributed lag nonlinear model study on the effect of extreme temperatures on emergency incidences in Shenzhen city during 2013-2017. Here, only the total emergency incidences, emergency incidences for respiratory diseases, and cardiovascular diseases were taken into consideration. Air pollution, subgroups, and seasons were adjusted to investigate the impacts of extreme temperatures on emergency incidences. Relative risk (RR) and 95% confidence intervals were calculated with the R software. From lag 0 to 21 days, the RR of temperature-total emergency department visits, temperature-cardiovascular, and temperature-respiratory diseases was 1.09 (95% CI: 0.98-1.20), 1.22 (95% CI: 0.96-1.56), and 1.06 (95% CI: 0.70-1.60) at extremely low temperature (first percent of temperature, 10 °C), respectively. During the same lag days, the RR was 1.02 (95 % CI: 0.92-1.14), 0.64 (95% CI: 0.49-0.86), and 0.92 (95% CI: 0.56-1.53) between extremely high temperature and total emergency department visits, cardiovascular, and respiratory diseases, respectively. The cumulative effects gradually went up with time for all types of emergency incidences in warm seasons (5 days moving average of temperature < 22 °C). However, the cumulative effects of total emergency incidences and Cvd emergency incidences were increased within the first lag 5 days, and then decreased until lag 21 in hot seasons (5 days moving average of temperature ≥ 22 °C). The cumulative effects of Res emergency incidences showed a declined trend from lag 0 to lag 21. The elderly (≥ 65, P1: RR = 1.49, 95% CI (1.30, 1.71); P99: RR = 0.86, 95% CI (0.71, 1.04)) and men (P1: RR = 1.27, 95% CI (1.14, 1.42)) seemed to be more vulnerable to extreme temperature than the younger (≤ 64, P1: RR = 1.19, 95% CI (1.08, 1.32); P99: RR = 1.00, 95% CI (0.89, 1.12)) and women (P1: RR = 1.17, 95%CI (1.06, 1.30)). The effects of extremely low temperature on all types of emergency incidences were stronger than those of extremely high temperature in the whole year. In addition, impacts of cold weather lasted about several days while those of hot weather were acute and rapid. An increased frequency of emergency incidences is predicted by rising temperatures variations. These results have clinical and public health implications for the management of emergency incidences.

摘要

已有研究报道,在多个城市中,极端温度与急性疾病发病率的增加有关。然而,位于中国南部亚热带地区的深圳,类似的研究却很少。本研究旨在探讨深圳市极端温度与急诊发病率之间的关系,并研究大气污染物在温度对人类健康相关效应中的作用。我们对 2013-2017 年深圳市极端温度对急诊发病率的影响进行了分布式滞后非线性模型研究。这里仅考虑了总急诊发病率、呼吸疾病急诊发病率和心血管疾病急诊发病率。调整了空气污染、亚组和季节,以调查极端温度对急诊发病率的影响。使用 R 软件计算相对风险(RR)和 95%置信区间。从滞后 0 到 21 天,极低温度(温度第 1%,10°C)下,温度-总急诊就诊、温度-心血管疾病和温度-呼吸疾病的 RR 分别为 1.09(95%CI:0.98-1.20)、1.22(95%CI:0.96-1.56)和 1.06(95%CI:0.70-1.60)。在相同的滞后天数内,极高温度与总急诊就诊、心血管疾病和呼吸疾病的 RR 分别为 1.02(95%CI:0.92-1.14)、0.64(95%CI:0.49-0.86)和 0.92(95%CI:0.56-1.53)。在温暖季节(温度<22°C 的 5 天移动平均值),所有类型的急诊发病率的累积效应随时间逐渐增加。然而,在炎热季节(温度≥22°C 的 5 天移动平均值)中,总急诊发病率和心血管疾病急诊发病率的累积效应在前 5 天的第一个滞后时间增加,然后在第 21 天减少。呼吸疾病急诊发病率的累积效应从滞后 0 到滞后 21 呈下降趋势。老年人(≥65 岁,P1:RR=1.49,95%CI(1.30,1.71);P99:RR=0.86,95%CI(0.71,1.04))和男性(P1:RR=1.27,95%CI(1.14,1.42))似乎比年轻人群(≤64 岁,P1:RR=1.19,95%CI(1.08,1.32);P99:RR=1.00,95%CI(0.89,1.12))和女性(P1:RR=1.17,95%CI(1.06,1.30))更容易受到极端温度的影响。在全年中,极低温度对所有类型的急诊发病率的影响均强于极高温度。此外,寒冷天气的影响持续数天,而炎热天气的影响则是急性和迅速的。随着温度变化频率的增加,预计急诊发病率将会增加。这些结果对急诊发病率的管理具有临床和公共卫生意义。

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