摘要
目的查找适用于研究痢疾发病率和气象因素之间关系的科学方法 ,探讨邯郸市痢疾的气象流行病学特征。方法收集1991—2010年邯郸市痢疾疫情资料、气象资料和人口资料,采用EpiData3.0进行"双重录入",用SPSS17.0统计分析软件建立数据库,对数据进行统计分析。结果①气象参数的共线性诊断结果显示,本组气象因子数据容差最小为0.014,方差膨胀因子最大达73.264。②采用Spearman相关分析结果显示,痢疾月发病率与月平均气压呈负相关,与其他9个气象因素均呈正相关(P<0.01)。其中月极端最低气温与痢疾月发病率之间的相关系数最大(r=0.698)。③痢疾月发病率呈对数模型曲线,R2值为0.501,F值为103.303,P<0.01,方程为Y=2 002.554+2.820ln(X)。④痢疾月发病率和月极端最低气温的曲线拟合效果较理想,得到曲线拟合方程=3.272+0.235X+0.011X2。⑤气象参数的KMO和Bartlett检验结果显示,本文中的气象参数非常适合做因子分析,通过做主成分多元线性回归分析得到方程Y=5.368+2.724Z1+1.856Z2(P<0.01)。结论①邯郸市10个气象参数之间存在严重的多重共线性。②月极端最低气温是影响痢疾发病的主要气象因素。③非自然水因因子对痢疾发病的影响程度大于自然水因因子的影响。
Objective To explore the scientific method which could apply to study the relationships between dysentery incidence and the meteorological factors, and to investigate the meteorological epidemiology characteristics of dysentery. Methods The profiles of dysentery plagues, meteorological parameters and population from 1991 to 2010 in Handan were collected and input to EpiData 3.0 by two separate data managers. This was followed by the es- tablishment of database by using SPSS17.0 statistical analysis software. Results Co-linearity diagnostic results of meteorological parameters showed that the minimal tolerance was 0.012 and the maximal variance inflation factor was 73.264. The Spearman's correlation analysis indicated that the monthly incidence of dysentery was negatively corre- lated with monthly average air pressure and positively correlated with nine miscellaneous factors (all P〈0.01). The most prominent correlation coefficient was that of dysentery and monthly extreme minimal temperature (0.698). The monthly incidence of dysentery best assumed the logarithmic curve model, with the R2 of 0.501 and the F value of 103.303 (both P〈0.01), respectively, resulting in an equation of Y=2002.554+2.8201n(X). The monthly incidence of dysentery and monthly extreme minimal temperature was ideally fitted, corresponding to the curve fitting equation of =3.272+0.235X+0.011X2. The results of KMO and Bartlett's test showed that the meteorological parameters employed in the present study were suitable for factor analysis and that the equation derived from the principal component mul- tivariate linear regression analysis was Y=5.368+2.724Zl+l.856Z2 (P〈O.O1). Conclusion There was a marked multi- ple co-linearity of 10 meteorological parameters in Handan. The monthly extreme minimal temperature was the main meteorological factors influencing the incidence of dysentery. Compared with the natural hydrometric factors, the non- natural hydrometric factors conferred a greater magnitude of influence on the incidence of dysentery.
出处
《中国药物与临床》
CAS
2014年第2期171-173,共3页
Chinese Remedies & Clinics
关键词
痢疾
气象因素
流行病学
Dysentery
Meteorological factors
Epidemiology