| 谷少华,王爱红,边国林,贺天锋,易波,陆蓓蓓,李晓海,许国章.宁波市气象条件与中暑的关联性分析[J].Chinese journal of Epidemiology,2016,37(8):1131-1136 |
| 宁波市气象条件与中暑的关联性分析 |
| Relationship between weather factors and heat stroke in Ningbo city |
| Received:January 18, 2016 |
| DOI：10.3760/cma.j.issn.0254-6450.2016.08.016 |
| KeyWord: 中暑 气象因素 气温 湿度 阈值 交互作用 |
| English Key Word: Heat stroke Weather factor Temperature Humidity Threshold Interaction |
| FundProject:浙江省医药卫生科技计划项目（2014KYA202）；宁波市科技局创新团队项目（2012B82018） |
| Author Name | Affiliation | E-mail | | Gu Shaohua | Ningbo Municipal Center for Disease Control and Prevention, Ningbo 315010, China | | | Wang Aihong | Ningbo Municipal Center for Disease Control and Prevention, Ningbo 315010, China | | | Bian Guolin | Ningbo Municipal Center for Disease Control and Prevention, Ningbo 315010, China | | | He Tianfeng | Ningbo Municipal Center for Disease Control and Prevention, Ningbo 315010, China | | | Yi Bo | Ningbo Municipal Center for Disease Control and Prevention, Ningbo 315010, China | | | Lu Beibei | Ningbo Municipal Center for Disease Control and Prevention, Ningbo 315010, China | | | Li Xiaohai | Ningbo Municipal Center for Disease Control and Prevention, Ningbo 315010, China | | | Xu Guozhang | Ningbo Municipal Center for Disease Control and Prevention, Ningbo 315010, China | xugz@nbcdc.org.cn |
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| Abstract: |
| 目的 分析影响人群中暑的主要气象因素。方法 收集2011-2014年宁波市中暑报告病例，采用分段回归模型、分布滞后非线性模型和反应面模型等方法，分析引起中暑的气温阈值、气象因素的滞后效应和交互作用等。结果 气温和湿度与中暑病例的相关性强于其他气象因素。多种模型均显示，日均气温对中暑病例的拟合效果优于日最高气温和日最低气温，其阈值为29.1（95% CI：28.7～29.5）℃，超过该阈值后中暑病例明显增多且效应可持续0～1 d；日均气温从第10百分位升至第90百分位时，中暑累积2 d的RR值为14.05（95% CI：7.23～27.31）。日均相对湿度对中暑的影响呈非线性，低湿度（RH：60%）在滞后1～4 d时可造成中暑发病增多，而高湿度（RH：93%）的效应则无统计学意义；两者造成中暑累积5 d的RR值分别为2.35（95% CI：1.27～4.33）和0.86（95% CI：0.40～1.85）。研究提示气温和湿度对中暑的影响具有交互作用，高温低湿条件下中暑发病风险最高。结论 宁波市人群中暑与气温和湿度有明确的关联，引起中暑的平均气温阈值为29.1℃，高温低湿条件下中暑发病风险最高。 |
| English Abstract: |
| Objective To explore the main effects of weather factors on heat stroke. Methods Data from case report on heat stroke was collected in Ningbo city during 2011 to 2014. Temperature threshold, lag effects and interaction of weather factors on heat stroke had been analyzed, using the piecewise regression model, distributed lag non-linear model, response surface model and other methods. Results Results showed that temperature and humidity were more correlated with heat stroke than other weather-related factors. Through different models, daily average temperature always presented a better role in predicting the heat stroke, rather than maximum or minimum temperature. Positive association between daily average temperature and heat stroke was obvious, especially at lag 0-1 days, with its threshold as 29.1 (95%CI:28.7-29.5)℃. The cumulative RR of heat stroke at 90th percentile of daily average temperature versus 10th percentile was 14.05 (95%CI:7.23-27.31) in lag 0-1 days. The effects of daily relative humidity on heat stroke appeared nonlinear, with low humidity showing a negative effect on heat stroke and could lag for 1-4 days. However, the effect of high humidity was not significant, with the cumulative RR of low humidity and high humidity as 2.35 (95%CI:1.27-4.33) and 0.86 (95%CI:0.40-1.85) in lag of 0-4 days, respectively. We also noticed that there was an interactive effect of both temperature and humidity on heat stroke. Under high temperature and low humidity, the risk of heat stroke showed the highest. Conclusions Temperature and humidity showed obvious relationship with heat stroke in Ningbo city, with the threshold temperature as 29.1℃. Under high temperature and low humidity, the risk of heat stroke became the highest. |
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