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利用2004年1月-2009年12月南京市呼吸系统疾病死亡资料和2003年12月-2009年12月南京地面气象观测站逐日气象资料,分析呼吸系统疾病死亡人数与同期和前期气象因素的关系,通过逐步回归按月份建立南京市呼吸及系统疾病逐日死亡人数的预测方程,利用2010年的资料检验预测效果,得出了以下结论:过去2~7 d气温平均值、过去3~7 d气压平均值与死亡人数之间的相关程度均通过了α=0.001水平的相关显著性检验,过去6~7 d的气温48、72 h变幅与死亡人数之间的相关程度也通过了α=0.001水平的相关显著性检验;死亡人数对气温平均值的最强响应在滞后6 d,气压平均值在滞后5 d,风速平均值在滞后1~2 d,过去72 h变温在滞后1~2 d,过去48、72 h气温变幅在滞后6~7 d.回归方程预测的死亡人数与实际死亡人数平均相差2人左右,预测效果优于按季节建立的模型.气象要素及其变化与呼吸系统疾病逐日死亡人数呈显著相关,气象要素对死亡人数的影响具有累积效应,并存在滞后性.
Using the data of death from respiratory diseases in Nanjing from January 2004 to December 2009 and the daily meteorological data of Nanjing meteorological observatory from December 2003 to December 2009, we analyzed the relationship between the death toll of respiratory diseases and the meteorological factors in the same period and the previous period , The regression equation was established by stepwise regression to establish the predictive equation of the number of daily respiratory and systemic diseases deaths in Nanjing. The data of 2010 were used to test the prediction results. The following conclusions were drawn: the average temperature in the past 2 ~ 7 days, the pressure in the past 3 ~ 7 days The correlation between the mean and the number of deaths passed the significance test of α = 0.001, and the correlation between the luffing temperature and the number of deaths at 48 and 72 h in the past 6 ~ 7 d also passed α = 0.001 The correlation between the number of deaths and the average air temperature was lagged 6 days, mean air pressure lagged 5 days, mean wind speed lagged 1 ~ 2 days, and temperature lagged for 1 ~ 2 days in the past 72 hours , The past 48 and 72 h temperature fluctuations in the lag 6 to 7 days.Regression equation predicted the number of deaths and the actual number of deaths on average about two people, the prediction effect is better than the seasonal model.Meteorological elements and its changes and respiratory system Disease by There was a significant correlation between the number of daily deaths and the cumulative effect of meteorological factors on the death toll, which lags behind.