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[目的]研究细菌性痢疾发病与气象因素的关系;探讨主成分回归分析在细菌性痢疾发病与气象因素关系中的应用。[方法]将成都市1999～2005年细菌性痢疾发病情况进行描述性分析,其月发病数和同期气象因素资料进行相关分析、主成分回归分析。[结果]细菌性痢疾发病率有明显的季节性,病例以夏秋季(5到10月份)较多。相关分析表明细菌性痢疾月发病率与气温、降雨量呈正相关(r1=0.930,P1﹤0.05;r2=0.896,P2﹤0.05),与雾日呈负相关(r=-0.585,P﹤0.05);主成分回归分析建立了菌痢发病与气象因素的预测方程,对细菌性痢疾发病率影响较大的气象因素有风速、气温和降雨量。[结论]高温高湿易引起细菌性痢疾的高发;主成分回归建立的方程可对细菌性痢疾的月发病率进行预测。
[Objective] To study the relationship between the incidence of bacterial dysentery and meteorological factors and to explore the application of principal component regression analysis in the relationship between the incidence of bacterial dysentery and meteorological factors. [Method] A descriptive analysis of the incidence of bacterial dysentery in Chengdu from 1999 to 2005 was conducted. Correlation analysis was made between the monthly incidence and meteorological factors data of the same period. The principal component regression analysis was carried out. [Results] The incidence of bacterial dysentery was obviously seasonal, with more cases in summer and autumn (May to October). Correlation analysis showed that the monthly incidence of bacterial dysentery was positively correlated with temperature and rainfall (r1 = 0.930, P1 <0.05; r2 = 0.896, P2 <0.05) The principal component regression analysis established the prediction equation of the incidence of dysentery and the meteorological factors. The meteorological factors that have a great impact on the incidence of bacterial dysentery were wind speed, temperature and rainfall. [Conclusion] High-temperature and high-humidity easily caused the high incidence of bacillary dysentery. The principal component regression established the equation to predict the monthly incidence of bacterial dysentery.