RE-EVALUATION OF TEMPERATURE-MORTALITY MODEL USING AUTOMATED METEOROLOGICAL DATA AQUISITION SYSTEM

使用自动气象数据采集系统重新评估温度-死亡率模型

• 批准号: 11670334
• 负责人: HONDA Yasushi
• 金额: $ 1.79万
• 依托单位: UNIVERSITY OF TSUKUBA
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 1999
• 资助国家: 日本
• 起止时间: 1999 至 2000
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-11670334/
• 关键词: AMeDAS; TEMPARATURE; MORTALITY; EPIDEMIOLOGY; 地域気象観測システム; 気象; 死亡率

(1) Correspondence between the meteorological data and city (The word city referred here represents village or town as well as city) : We decided to take the points of Automated Meteorological Data Acquisition System (AMeDAS) within 15km of the barycenter of the city, and to set the calculated average of daily maximum temperature measurements of these points as the city measurement. We used 15km because 10km or 5km left some cities without AMeDAS points.(2) Preparation of data for the analysis : Prime Minister's Office provided the computerized population data by age and sex for each city, Ministry of Health and Welfare provided the computerized death certificate file, and Meteorological Agency provided AMeDAS data. We used city number assigned by Japanese government to combine the above three types of data, and calculated number of deaths, number of person-days by daily maximum temperature category for each city.(3) Comparison between city-based analysis and prefecture-based analysis : In the city-based analysis, we construct prefectural number of deaths and person-days by combining all the cities in the prefecture. On the other hand, in the prefecture-based analysis, we used only one measurement point for each prefecture, which is located in the capital cities. Thus, if there is a difference between the temperature in the capital city and that in other cities, misclassification of deaths and person-days would occur. In this analysis, we used the data in 1995 and restricted the subjects to 65+years old.(4) Result : The misclassification pattern of deaths was so similar to that of person-days that the mortality rates were not biased. This suggests that the prefecture-based analyses studied previously were valid. However, we need to use city-based data in projecting the number of deaths by multiplying mortality rate with corresponding person-days, because the temperature-specific number of person-days is biased.

(1)气象数据与城市的对应关系（这里的城市一词代表村庄或城镇，也代表城市）：我们决定取城市重心15公里范围内的自动气象数据采集系统（AMeDAS）点，并将这些点的日最高气温测量值的计算平均值设置为城市测量值。我们使用15公里，因为10公里或5公里离开一些城市没有AMeDAS点。(2)为分析准备数据：首相办公室提供了每个城市按年龄和性别分列的计算机化人口数据，卫生和福利部提供了计算机化死亡证明文件，气象厅提供了AMeDAS数据。我们使用日本政府指定的城市编号，将上述三类数据联合收割机合并，计算出各城市按日最高气温类别的死亡人数、人日数。(3)基于城市的分析和基于县的分析的比较：在基于城市的分析中，我们通过合并县内所有城市来构建县的死亡人数和人日。另一方面，在以都道府县为单位的分析中，我们只对每个都道府县使用了一个测量点，该测量点位于首都城市。因此，如果首都的气温与其他城市的气温有差异，就会发生死亡和人日的错误分类。在这项分析中，我们使用了1995年的数据，并将受试者限制在65岁以上。(4)结果：死亡误分类模式与人日误分类模式相似，死亡率无偏倚。这表明，以前研究的基于省的分析是有效的。然而，我们需要使用基于城市的数据，通过将死亡率乘以相应的人-天来预测死亡人数，因为特定温度的人-天数量是有偏差的。