分位数回归模型在新疆涂阳肺结核报告率生态学影响因素的应用分析
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摘要
目的探讨分位数回归模型在新疆地区涂阳肺结核报告率与生态学相关因素关联分析中的应用价值。方法基于2011-2015年新疆103个区县涂阳肺结核报告率的面板数据,描述与分析其地区分布现况,分析人口密度、人均GDP、年平均温度、年总降水量及年平均相对湿度与涂阳肺结核报告率的关联性,应用分位数回归模型,探讨影响因素随涂阳肺结核报告率变化其效应变化趋势。结果新疆不同地区涂阳肺结核报告率存在地区差异,南疆地区高于北疆、东疆及中部地区,2011-2015年报告率呈小幅波动但整体下降趋势。经典线性模型显示人均GDP越高、年总降水量越高,涂阳肺结核报告率越低,关联有统计学意义(P <0. 05);分位数回归模型进一步提示:随着涂阳肺结核报告率的增加,人均GDP的效应大小呈倒"U"型趋势,年总降水量的影响效应呈递增趋势。结论相比经典线性回归模型,分位数回归模型可提供更加丰富细致的信息,在传染病时空面板数据中具有一定的应用价值。
Objective To explore the application value of the quantile regression model in the correlation analysis of the reported rate of smear-positive pulmonary tuberculosis with ecological related factors in Xinjiang. Methods Based on the panel data of the reported rate of smear-positive pulmonary tuberculosis in 103 counties of Xinjiang from 2011 to 2015,the situation of regional distribution and the correlation of the reported rate of smear-positive pulmonary tuberculosis with the population density,per capita GDP,annual average temperature,annual total rainfall and annual average relative humidity were described and analyzed. The quantile regression model was used to explore the trend of the influencing factors with the reported rate of smear-positive pulmonary tuberculosis. Results There were regional differences in the reported rate of smear-positive pulmonary tuberculosis in different regions of Xinjiang. The reported rate of southern was higher than northern,eastern and central in Xinjiang. From 2011 to 2015,the reported rate showed a slight fluctuation,but the overall trend was downward. The classical linear model showed that the higher per capita GDP and total annual rainfall,the lower reported rate of smear-positive pulmonary tuberculosis,and the correlation was statistically significant( P < 0. 05). The quantile regression model further suggested that with the increase of the reported rate of smear-positive pulmonary tuberculosis,the effect of per capita GDP showed an inverted"U"trend,and the effect of annual total rainfall showed an increasing trend. Conclusion Compared with the classical linear regression model,the quantile regression model can provide more detailed information and has application value in the time and space panel data of infectious diseases.
Objective To explore the application value of the quantile regression model in the correlation analysis of the reported rate of smear-positive pulmonary tuberculosis with ecological related factors in Xinjiang. Methods Based on the panel data of the reported rate of smear-positive pulmonary tuberculosis in 103 counties of Xinjiang from 2011 to 2015,the situation of regional distribution and the correlation of the reported rate of smear-positive pulmonary tuberculosis with the population density,per capita GDP,annual average temperature,annual total rainfall and annual average relative humidity were described and analyzed. The quantile regression model was used to explore the trend of the influencing factors with the reported rate of smear-positive pulmonary tuberculosis. Results There were regional differences in the reported rate of smear-positive pulmonary tuberculosis in different regions of Xinjiang. The reported rate of southern was higher than northern,eastern and central in Xinjiang. From 2011 to 2015,the reported rate showed a slight fluctuation,but the overall trend was downward. The classical linear model showed that the higher per capita GDP and total annual rainfall,the lower reported rate of smear-positive pulmonary tuberculosis,and the correlation was statistically significant( P < 0. 05). The quantile regression model further suggested that with the increase of the reported rate of smear-positive pulmonary tuberculosis,the effect of per capita GDP showed an inverted"U"trend,and the effect of annual total rainfall showed an increasing trend. Conclusion Compared with the classical linear regression model,the quantile regression model can provide more detailed information and has application value in the time and space panel data of infectious diseases.
引文
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[3]Beyerlein A.Quantile regression-opportunities and challenges from a user’s perspective[J].American Journal of Epidemiology,2014,180(3):330-331.
[4]米白冰,李强,党少农,等.研究健康相关生命质量影响因素的分位数回归分析[J].中国卫生统计,2016,33(2):190-193.
[5]陈伟,夏愔愔,李涛,等.2015年全球及中国结核病疫情形势分析[J].结核病与肺部健康杂志,2016,5(1):32-36.
[6]靳圆圆,王微,闫慈,等.扫描统计与空间自相关分析在新疆结核聚集性研究中的应用[J].现代预防医学,2016,43(7):1156-1161.
[7]郭培军.山东省烟台市2009-2014年结核病流行及空间分布特征[D].济南:山东大学,2017.
[8]张向阳,顾晓芬,李豫凯.基于区域聚类的新疆卫生资源配置均衡性研究[J].中国卫生事业管理,2013,30(8):593-596.
[9]Beiranvand R,Karimi A,Delpisheh A,et al.Correlation assessmen of climate and geographic distribution of tuberculosis using geographical information system(GIS)[J].Iranian Journal of Public Health,2016,45(1):86-93.
[10]施雯慧,陈伟.结核病发病影响因素研究进展[J].中华流行病学杂志,2012,33(12):1296-1300.
[11]黄勇,邓特,于石成,等.空间面板数据模型在传染病监测数据分析中的应用[J].中华疾病控制杂志,2013,17(4):277-281.
[12]Servi F,Momenian S,Khodadost M,et al.The examination of relationship between socioeconomic factors and number of tuberculosis using quantile regression model for count data in Iran2010-2011[J].Medical Journal of the Islamic Republic of Iran,2016,30(1):399.