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全球变暖导致气象灾害频发,尤其是极端天气事件。极端温度对公共健康的影响已成为当今研究的热点问题之一。相比于发达国家,中国在该领域研究起步较晚。虽然已有出色的成果,但在以下3个方面还略显不足:(1)大多数研究基于一个城市或几个城市,缺乏基于大量数据的区域尺度的研究;(2)已有研究往往按地理因素或行政单位来划分区域,而忽视区域内部温度的异质性;(3)相比高温热浪,鲜少有研究关注低温冷害的影响。针对上述问题,本文收集了中国疾病预防控制中心2007-2012年全国127个站点的数据,利用分布式滞后非线性模型,探究了中国5个温度带温度与居民非意外死亡之间的暴露-反应曲线。在此基础上,定义当地温度分布1%处的温度为极端低温,根据温度-死亡风险曲线,计算了冷害造成的死亡风险。结果表明,不同温度带的温度-死亡关系曲线呈现U型或J型。极端低温对北亚热带影响最小,其相对风险为1.27(95%CI:0.94-1.72);对中亚热带影响最大,其相对风险为1.93(95%CI:1.08-3.60)。随着温度带温度的升高,低温冷效应的影响呈现“M”型,这一特征与不同温度带经济发展有关。因此,不同地区的政府除了应着力提高地区经济发展外,还应根据地区特征,采取更积极有效的措施来应对低温冷害可能给当地公共健康造成的威胁。
Global warming has led to frequent meteorological disasters, especially extreme weather events. The impact of extreme temperature on public health has become one of the hot issues in current research. Compared to the developed countries, China started research lately in this field. Although there have been excellent results, there are still a few deficiencies in the following three aspects: (1) Most studies are based on one city or several cities and lack of large-scale data-based regional scale studies; (2) Geographical factors or administrative units to divide the region, while ignoring the heterogeneity of the temperature within the region; (3) Few studies focused on the impact of chilling injury compared to heat and heat waves. In response to the above problems, this paper collects the data of 127 sites in China from 2007 to 2012 by CDC, and uses the distributed lag nonlinear model to explore the relationship between temperature and resident non-accidental death-exposure in China curve. Based on this, the temperature at 1% of the local temperature distribution is defined as extremely low and the risk of death from chilling injury is calculated from the temperature-mortality risk curve. The results show that the temperature-death curves of different temperature zones show U-shape or J-shape. The extreme low temperature has the least impact on the northern subtropical zone, with a relative risk of 1.27 (95% CI: 0.94-1.72) and the highest impact on the Central Asian subtropical zone, with a relative risk of 1.93 (95% CI: 1.08-3.60). With the increase of the temperature, the effect of the cold temperature effect is “M”, which is related to the economic development of different temperature zones. Therefore, in addition to efforts to improve regional economic development, governments in different regions should take more active and effective measures to deal with the possible threat to local public health caused by chills.