基于分布滞后非线性模型的青岛市温度与肾综合征出血热的剂量反应关系

doi:10.6040/j.issn.1671-7554.0.2017.597

摘要/Abstract

摘要： 目的研究青岛市温度对肾综合征出血热(HFRS)发病风险的影响。方法收集2007年1月1日至2013年12月31日青岛市报告的HFRS发病数据及同期气象数据,利用分布滞后非线性模型分别分析日平均气温、最高气温和最低气温与HFRS发病风险的剂量反应关系。结果以0 ℃为参照,日平均气温、最高气温及最低气温较低时(<0 ℃),温度对HFRS发病风险均存在即时效应,随着温度升高,滞后20 d左右时HFRS风险较大,相对危险度(RR)分别为1.06(95% CI: 1.02~1.11)、1.05(95% CI: 1.00~1.10)、1.07(95% CI: 1.03~1.12)。综合各因素,平均气温、最高气温及最低气温均处于最低时,HFRS的发病风险最大,累积相对危险度(CRR)分别为5.71(95% CI: 1.74~18.76)、4.19(95% CI: 1.62~10.83)、4.72(95% CI: 1.19~18.65)。随着温度升高(>0 ℃),CRR值呈先增大后减小趋势,高温时最低。此外,平均气温在10 ℃~20 ℃、最高气温<0 ℃、最低气温<20 ℃范围内,HFRS发病风险均较大(P<0.05)。结论日平均气温、最高气温及最低气温与HFRS发病风险的剂量反应关系及变化趋势基本一致。温度对HFRS的影响存在滞后效应,低温时发病风险最大。

关键词: 分布滞后非线性模型, 肾综合征出血热, 温度, 剂量反应关系

Abstract: Objective To investigate the effects of temperature on the onset risk of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City. Methods The daily HFRS cases and meteorological variables in Qingdao City were collected from 1st January 2007 to 31st December 2013. Distributed lag non-linear models were used to analyze the exposure-response relationships between HFRS onset risk and daily mean temperature, maximum temperature and minimum temperature, respectively. Results With the reference temperature of 0 ℃, when the daily mean temperature, maximum temperature and minimum temperature were low(<0 ℃), they had an immediate effect on HFRS onset risk. With the increase of temperature and lag days, the onset risk of HFRS was higher at about 20 days lag, and RR values were 1.06(95% CI: 1.02-1.11), 1.05(95% CI: 1.00-1.10)and 1.07(95% CI: 1.03-1.12), respectively. On the whole, the highest onset risk of HFRS occurred with CRR values being 5.71(95% CI: 1.74-18.76)at mean temperature -8.8 ℃, 4.19(95% CI: 1.62-10.83)at maximum temperature -6.4 ℃, and 4.72(95% CI: 1.19-18.65)at minimum temperature -11.1 ℃. With the increase of temperature(>0 ℃), CRR values firstly increased, then decreased, and the lowest value occurred at the highest temperature. In addition, when the mean temperature ranged in 10 ℃ and 20 ℃, maximum temperature was <0 ℃ and minimum temperature was <20 ℃, HFRS had the greater onset risks(all P<0.05). 山东大学学报 (医学版)56卷1期 -许勤勤,等.基于分布滞后非线性模型的青岛市温度与肾综合征出血热的剂量反应关系 \=- Conclusion The effects of temperature variables on the onset risks of HFRS are consistent and lagged. The risk of HFRS is greatest at the lowest temperature.

Key words: Distributed lag non-linear model, Renal syndrome hemorrhagic fever, Temperature, Exposure-response relationships

中图分类号:

R512.8

许勤勤,李润滋,刘娅飞,孙苑潆,郑兆磊,王珮竹,王志强,李秀君. 基于分布滞后非线性模型的青岛市温度与肾综合征出血热的剂量反应关系[J]. 山东大学学报 (医学版), 2018, 56(1): 90-96.

XU Qinqin, LI Runzi, LIU Yafei, SUN Yuanying, ZHENG Zhaolei, WANG Peizhu, WANG Zhiqiang, LI Xiujun. Effects of temperature on hemorrhagic fever with renal syndrome based on the distributed lag non-linear models in Qingdao City[J]. Journal of Shandong University (Health Sciences), 2018, 56(1): 90-96.

参考文献

[1] Li Q, Cai Y, Wei Y, et al. Genovariation study of Hantavirus in main endemic areas of hemorrhagic fever with renal syndrome in Hebei Province, China[J]. PLoS One, 2016, 11(7): e0159731. doi:10. 1371/journal.pone.0159731.
[2] 陈化新,罗成旺. 中国肾综合征出血热监测[J]. 中华流行病学杂志, 2002, 23(1):63-66. doi:10. 3760/j. issn:0254-6450. 2002.01.018.
[3] 李金梅,张海林,邓淑珍. 肾综合征出血热流行病学研究进展[J]. 中国热带医学, 2008, 8(4):666-669. LI Jinmei, ZHANG Hailin, DENG Shuzhen. Advance in epidemiological research of hemorrhagic fever with renal syndrome[J]. China Tropical Medicine, 2008, 8(4):666-669.
[4] Wang L, Wang T, Cui F, et al. Hemorrhagic fever with renal syndrome, Zibo City, China, 2006-2014[J]. Emerg Infect Dis, 2016, 22(2):274-276.
[5] 张永振,肖东楼,王玉,等. 中国肾综合征出血热流行趋势及其防制对策[J]. 中华流行病学杂志, 2004, 25(6):466-469. ZHANG Yongzhen, XIAO Donglou, WANG Yu, et al. The epidemic characteristics and preventive measures of hemorrhagic fever with syndromes in China[J]. Chin J Epidemiol, 2004, 25(6):466-469.
[6] 黄晓霞,殷红梅,闫磊,等. 中国大陆2006~2010年肾综合征出血热流行特征分析[J]. 西太平洋区域监测与反应杂志, 2012, 3(1):12-18. doi:10. 5365/wpsar. 2011. 2. 2. 007. HUANG Xiaoxia, YIN Hongmei, YAN Lei, et al. Epidemiologic characteristics of hemorrhagic fever with renal syndrome in Mainland China from 2006 to 2010[J]. Western Pacific Surveillance and Response Journal, 2012, 3(1):12-18. doi:10. 5365/wpsar. 2011. 2. 2. 007.
[7] 刘勇,刘静,翟文济,等. 2008~2011年山东省肾综合征出血热流行状况及其防治对策[J]. 预防医学论坛, 2012,18(2):107-109. LIU Yong, LIU Jing, ZHAI Wenji, et al. The prevalence of hemorrhagic fever with renal syndrome and countermeasuresin Shandong Province, 2008-2011[J]. Preventive Medicine Tribune, 2012, 18(2):107-109.
[8] 吴伟,郭军巧,关鹏,等. 辽宁省2005~2007年肾综合征出血热流行特征及环境危险因素分析[J]. 中国媒介生物学及控制杂志, 2014, 25(1):39-42. WU Wei, GUO Junqiao, GUAN Peng, et al. Analysis of epidemiological features of hemorrhagic fever with renal syndrome and associated environmental risk factors in Liaoning province, China during 2005-2007[J]. Chinese Journal of Vector Biology and Control, 2014, 25(1):39-42.
[9] 刘静,王洁贞,薛付忠,等. 肾综合征出血热发病率与气象因素关系的研究[J]. 中国卫生统计, 2006, 23(4):326-329. LIU Jing, WANG Jiezhen, XUE Fuzhong, et al. Association between incidence of hemorrhagic fever with renal syndrome(HFRS)and meteorological factors[J]. Chinese Journal of Health Statistics, 2006, 23(4):326-329.
[10] 王智宇,刘如春,陈田木. 气候因素对长沙市肾综合征出血热发病影响研究[J]. 中国热带医学, 2015, 15(8):955-957. WANG Zhiyu, LIU Ruchun, CHEN Tianmu. Influence of climatic factors on haemorrhagic fever with renal syndrome in Changsha[J]. China Tropical Medicine, 2015, 15(8):955-957.
[11] 李芳,董倩,蔡鹏,等. 济宁地区肾综合征出血热发病的气象因素分析[J]. 现代预防医学, 2016, 43(15):2835-2839. LI Fang, DONG Qian, CAI Peng, et al. Meteorological factors on the incidence of hemorrhagic fever with renal syndrome in Jining[J]. Modern Preventive Medicine, 2016, 43(15): 2835-2839.
[12] 杨军,欧春泉,丁研,等. 分布滞后非线性模型[J]. 中国卫生统计, 2012, 29(5): 772-777.
[13] Gasparrini A, Armstrong B, Kenward MG. Distributed lag non-linear models[J]. Stat Med, 2010, 29(21): 2224-2234.
[14] 李月,孟郁洁,陈倩倩,等. 亳州市疟疾发病与气象因素关系的研究[J]. 环境与健康杂志, 2014, 31(11): 988-992. LI Yue, MENG Yujie, CHEN Qianqian, et al. Association between meteorological factor and incidence of malaria in Bozhou city, Anhui province[J]. Journal of Environment and Health, 2014, 31(11): 988-992.
[15] 杨培荣,田辉,严钏元,等. 宝鸡市区气象因素与手足口病的滞后效应研究[J]. 公共卫生与预防医学, 2014, 25(2): 21-23. YANG Peirong, TIAN Hui, YAN Chuanyuan, et al. Study on lag effect of meteorological factors and Hand-foot-mouth disease(HFMD)in Baoji city[J]. J of Pub Health and Prev Med, 2014, 25(2): 21-23.
[16] Zhang Y, Li C, Feng R, et al. The short-term effect of ambient temperature on mortality in Wuhan, China: atime-series study using a distributed lag non-linear model[J]. Int J Environ Res Public Health, 2016, 13(7): 722.
[17] Liang Z, Yan L, Ma Y, et al. The association between ambient temperature and preterm birth in Shenzhen, China: a distributed lag non-linear time series analysis[J]. Environ Health, 2016, 15(1): 84.
[18] Zhao D, Zhang X, Xu Z, et al. Impact of short-term temperature variability on emergency hospital admissions for schizophrenia stratified by season of birth[J]. Int J Biometeorol, 2017, 61(4): 589-599.
[19] Ye Q, Fu J, Mao J, et al. Haze is a risk factor contributing to the rapid spread of respiratory syncytial virus in children[J]. Environ Sci Pollut Res Int, 2016, 23(20): 20178-20185.
[20] Zhang WY, Guo W, Fang LQ, et al. Climate variability and hemorrhagic fever with renal syndrome transmission in Northeastern China[J]. Environ Health Perspect, 2010, 118(7): 915-920.
[21] 邱波,苏航. 青岛市1979~2004年肾综合征出血热流行动态分析[J]. 疾病监测, 2005, 20(12): 635-637. QIU Bo, SU Hang. Dynamic analysis on epidemic of hemorrhagic fever with renal syndrome from 1979 to 2004 in Qingdao[J]. Diseases Surveillance, 2005, 20(12): 635-637.
[22] 田咏梅,马艳,于进付,等. 气候变化背景下青岛地区气候环境特征分析[J]. 海洋湖沼通报, 2012(4):10-15. TIAN Yongmei, MA Yan, YU Jinfu, et al. Characteristics of Qingdao City climate under the background of global climate change[J]. Transactions of Oceanology and Limnology, 2012(4): 10-15.
[23] 韩占英,张艳波,许永刚,等. 河北省肾综合征出血热流性特征及防控策略探讨[J]. 中国媒介生物学及控制杂志, 2006, 17(2): 139-141. HAN Zhanying, ZHANG Yanbo, XU Yonggang, et al. Epidemiological characteristics and prevention strategies of hemorrhagic fever with renal syndrome in Hebei province[J]. Chin J Vector Bio & Control, 2006, 17(2): 139-141.
[24] 康殿民,阮玉华,傅继华,等. 山东省肾综合征出血热流行特征及其变化研究[J]. 中国公共卫生, 2001, 17(4): 341-342. KANG Dianmin, RUAN Yuhua, FU Jihua, et al. Epidemiological changes of hemorrhage fever with renal syndrome in Shandong Province, 1990-1998[J]. Chinese Journal of Public Health, 2001, 17(4): 341-342.
[25] Fang LQ, Wang XJ, Liang S, et al. Spatiotemporal trends and climatic factors of hemorrhagic fever with renal syndrome epidemic in Shandong Province, China[J]. PLoS Negl Trop Dis, 2010, 4(8): e789. doi: 10. 1371/journal. pntd. 0000789.
[26] Zhang S, Wang S, Yin W, et al. Epidemic characteristics of hemorrhagic fever with renal syndrome in China, 2006-2012[J]. BMC Infect Dis, 2014, 14(1): 384.
[27] Li Q, Zhao W, Wei Y, et al. Analysis of incidence and related factors of hemorrhagic fever with renal syndrome in Hebei Province, China[J]. PLoS One, 2014, 9(7): e101348. doi: 10. 1371/journal. pone. 0101348.
[28] Gasparrini A. Distributed lag linear and non-linear models in R: the package dlnm[J]. J Stat Softw, 2011, 43(8): 1-20.

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