热指数对阜南地区呼吸系统疾病的影响
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摘要
选取安徽省阜阳市阜南县14个乡镇2013年1月1日-2016年12月31日呼吸系统疾病日住院就诊资料50 881例,在Spearman相关性分析的基础上,用分布滞后非线性模型与广义相加模型相结合,对呼吸系统疾病住院人数与各气象要素的相关性进行了分析,其与平均气温、相对湿度和热指数呈负相关,与平均气压、平均风速呈正相关.结果表明,热指数是比温度、湿度等单独作用更全面的气象指标.引起呼吸系统疾病发病风险增高的主要原因是低热指数,低热指数对呼吸系统疾病住院人数的影响表现为长期效应,滞后6～8 d是主要发病时间.不同季节热指数滞后效应的结果不同,夏季的低热指数易导致患病风险增加;冬季高热指数滞后8 d时易增加患病风险.
Clinic data(50 881 cases) on the diseases of the respiratory system from 2013 to 2016 were collected from 14 villages in Funan county. Based on the Spearman's correlation analysis, the distributed lag nonlinear model and generalized additive model were employed to quantitatively analyze the impact of meteorological factors on the number of in-patients. The number series was negatively correlated with the mean temperature, relative humidity and heat index, but positively correlated with the mean air pressure and mean wind speed. The results also reflected that the heat index was a more comprehensive meteorological factor. The main cause of respiratory system diseases was a low heat index, and it had a longterm effect on the number of in-patients, and a lag of 6-8 days was the main onset time. The lag effect of heat index changed with seasons, with the low heat index in summer being easy to increase the risk; andthe effect of high temperature index in winter was obvious for 8 lag days.
Clinic data(50 881 cases) on the diseases of the respiratory system from 2013 to 2016 were collected from 14 villages in Funan county. Based on the Spearman's correlation analysis, the distributed lag nonlinear model and generalized additive model were employed to quantitatively analyze the impact of meteorological factors on the number of in-patients. The number series was negatively correlated with the mean temperature, relative humidity and heat index, but positively correlated with the mean air pressure and mean wind speed. The results also reflected that the heat index was a more comprehensive meteorological factor. The main cause of respiratory system diseases was a low heat index, and it had a longterm effect on the number of in-patients, and a lag of 6-8 days was the main onset time. The lag effect of heat index changed with seasons, with the low heat index in summer being easy to increase the risk; andthe effect of high temperature index in winter was obvious for 8 lag days.
引文
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[16]马盼,黎檀实,宁贵财,等.北京市上呼吸道感染与气象环境关系及其冬季天气分型初探[J].兰州大学学报:自然科学版, 2015, 51(1):79-86.
[2] Shen Dan-dan, Zhu Neng. Influence of the temperature and relative humidity on human heat acclimatization during training in extremely hot environments[J]. Building&Environment, 2015, 94(2):1-11.
[3] Schwartz J. Air pollution and hospital admissions for respiratory disease[J]. Epidemiology, 1996, 7(1):20-28.
[4] Larsson K, Tornling G, Gavhed D, et al. Inhalation of cold air increases the number of inflammatory cells in the lungs in healthy subjects[J]. European Respiratory Journal, 1998, 12(4):825-830.
[5] Rothfusz L P, Headquarters N W. The heat index equation(or, more than you ever wanted to know about heat index)[M]. Fort Worth:National Oceanic and Atmospheric Administration, National Weather Service, Office of Meteorology, 1990:9023.
[6] Wei Huang, Tan Jian-guo, Kan Hai-dong, et al. Visibility,air quality and daily mortality in Shanghai, China[J].Science of the Total Environment, 2009, 407(10):3295-3314.
[7] Wood S N, Augustin N H. GAMs with integrated model selection using penalized regression splines and applications to environmental modelling[J]. Ecological Modelling, 2002, 157(2):157-177.
[8] Gasparrini A. Distributed lag linear and non-linear models in R:the package dlnm[J]. Journal of Statistical Software, 2011, 43(8):1-20.
[9]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):772-773.
[10]卢志刚,王亚利,张明泉,等.秋冬季节对健康大鼠肺组织表面活性蛋白和白细胞介素表达的影响[J].中国组织工程研究与临床康复, 2010, 14(11):2000-2003.
[11] Welliver-Rc S. Temperature, humidity, and ultraviolet B radiation predict community respiratory syncytial virus activity[J]. Pediatric Infectious Disease Journal, 2007,26(11):S29-S35.
[12] Lowen A C, Mubareka S, Steel J, et al. Influenza virus transmission is dependent on relative humidity and temperature[J]. PLoS Pathogens, 2007, 3(10):1470-1476.
[13] Gaspareini A, Leone M. Attributable risk from distributed lag models[J]. BMC Medical Research Methodology, 2014, 14(1):55-67.
[14] Gaspareini A, Guo Y, Hashizume M, et al. Mortality risk attributable to high and low ambient temperature:a multicountry observational study[J]. The Lancet, 2015,386(9991):369-375.
[15]岳海燕,申双和.呼吸道和心脑血管疾病与气象条件关系的研究进展[J].气象与环境学报, 2009, 25(2):57-61.
[16]马盼,黎檀实,宁贵财,等.北京市上呼吸道感染与气象环境关系及其冬季天气分型初探[J].兰州大学学报:自然科学版, 2015, 51(1):79-86.