关键词: 呼吸系统疾病, 气象要素, 主成分分析, 预测模型

Abstract: Under the background of global climate change, the impact of climate change on respiratory system diseases can not be ignored. Based on the death surveillance data, demographic data and meteorological data from 2004 to 2010 in Nanjing, the distribution characteristics of respiratory system diseases mortality and its response to meteorological elements in the study area were discussed by a principal component analysis method. A disease mortality prediction model was established. The results show that the patients’ mortalities of respiratory system diseases are the lowest in July and highest in January, and its change amplitude is greater in the first half year than in the second one. The climate is characterized by low pressure, high temperature, and more precipitation in summer half year and by great relative humidity, short duration in winter half year respectively, so the patients’ mortalities of respiratory system diseases are low in the first half year and in an increasing trend in the second one. The fitting coefficients of return test and prediction are 0.755 and 0.795 respectively, and both pass the significance test of 0.01 level. The fitting effect of the principal component regression model is good, which could provide references for the corresponding forecast.

Key words: Respiratory system disease, Meteorological element, Principal component analysis, Prediction model