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目的研究极端低温对人群呼吸系统疾病发病住院的影响,以及不同地区和人群对该影响的效应修饰作用。方法收集广东省经济发达地区广州市番禺区和欠发达地区梅州兴宁市2006—2011年的呼吸系统疾病住院病例数的时间序列资料和相应的气象资料,运用分布滞后非线性模型分析2个地区极端气温(低于日均气温分布的第5百分位)与呼吸系统疾病住院人数的关系,并按不同性别和年龄进行分层分析。结果 2006—2011年番禺地区的日均气温的均值为22.7℃,共有24 216人次因呼吸系统疾病而在番禺区中心医院住院,平均每天有11.1人次。兴宁地区日均气温的均值为21.9℃,共有19 934人次在兴宁市人民医院住院,平均每天有9.1人次。日均气温与呼吸系统疾病住院人数间呈非线性关系,低温对2个地区的呼吸系统疾病发病住院影响有明显的滞后,兴宁在6.4℃、滞后13 d时RR值达到最大,为1.04(95%CI:1.02~1.06);番禺在9.9℃、滞后10 d时RR值最大,为1.03(95%CI:1.02~1.04)。滞后25 d内的累计效应中,番禺区在研究期气温分布的第5%(10.9℃)、10%(14.3℃)和25%(18.2℃)处对应的RR值分别为1.48(95%CI:1.13~1.94)、1.45(95%CI:1.12~1.82)和1.29(95%CI:1.10~1.51);兴宁市在研究期气温分布的第5%(9.8℃)、10%(11.7℃)和25%(17.1℃)处对应的RR值则分别为1.61(95%CI:1.17~2.21)、1.45(95%CI:1.08~1.96)和1.11(95%CI:0.94~1.35)。极端低温对各人群影响效应(RR值)随滞后日的变化呈现比较一致的趋势,在暴露后2~4 d才出现效应,之后效应慢慢增大,达到一定高峰后慢慢回落,为倒“U”型的分布形状。经济欠发达地区兴宁市的老年人群受极端低温的影响最大,其RR值达1.86(95%CI:1.04~3.31)。结论极端低温对人群呼吸系统疾病发病住院有显著影响,其中对经济欠发达地区的老年人群影响更加明显。
Objective To study the effect of extreme hypothermia on the hospitalization of respiratory diseases in the population and the effects of different regions and populations on the effect of this effect. Methods The time series data and corresponding meteorological data of respiratory diseases in 2006 and 2011 in Panyu District of Guangzhou City and Xingning City, Meizhou, Guangdong Province, which are economically developed in Guangdong Province, were collected. Two models of non-linear distribution model The relationship between extreme temperatures (below the 5th percentile of the average daily temperature distribution) and the number of hospitalizations for respiratory diseases was stratified by sex and age. Results The average daily temperature of Panyu district from 2006 to 2011 was 22.7 ℃. A total of 24 216 people were hospitalized in Panyu Central Hospital due to respiratory diseases, with an average of 11.1 person-times daily. The average daily average temperature in Xingning is 21.9 ℃. A total of 19 934 people were hospitalized in Xingning People’s Hospital, with an average of 9.1 people daily. The average daily temperature and the number of hospitalized respiratory diseases showed a non-linear relationship between the low temperature on the incidence of respiratory disease in two areas of hospitalization significant lag, Xingning at 6.4 ℃, lag 13 d when the RR reached the maximum, 1.04 ( 95% CI: 1.02 ~ 1.06). Panyu had the highest RR at 1.03 (95% CI: 1.02-1.04) at 9.9 ℃ and lag 10 days. Among the cumulative effects within 25 days of lag, the corresponding RRs of Panyu District at the 5% (10.9 ℃), 10% (14.3 ℃) and 25% (18.2 ℃) of the study period were 1.48 (95% CI (95% CI: 1.12-1.82) and 1.29 (95% CI: 1.10-1.51) in the study period. In the study area, Xingning City was the first 5% (9.8 ℃), 10% (11.7 ℃ ) And 25% (17.1 ° C) were 1.61 (95% CI: 1.17-2.21), 1.45 (95% CI: 1.08-1.96) and 1.11 (95% CI: 0.94-1.35), respectively. The effect of extreme hypothermia on each population (RR value) showed a consistent trend with the change of lag days, and appeared only 2 ~ 4 days after exposure, and then the effect slowly increased after reaching a certain peak, “U ” type of distribution shape. In the underdeveloped area, Xingning City’s elderly population was the most affected by extreme hypothermia with an RR of 1.86 (95% CI: 1.04-3.31). Conclusions Extreme hypothermia has a significant impact on the hospitalization of respiratory diseases in the population, of which the impact on older people in economically underdeveloped areas is more obvious.