Influencing Factors of the Incidence of Pulmonary Tuberculosis in China: an Analysis Using the Geographically and Temporally Weighted Regression Model

Abstract

Background Most of the existing studies on the influencing factors of pulmonary tuberculosis incidence are based on temporal or spatial regression models, and the results are limited. Objective To explore the temporal and spatial heterogeneity of pulmonary tuberculosis in China, and to analyze the temporal and spatial correlations between the incidence of pulmonary tuberculosis and meteorological and air quality factors, offering a scientific reference for the development of measures containing tuberculosis. Methods Monthly statistical data of pulmonary tuberculosis in China from 2016 to 2018 were collected. After being tested with multicollinearity and spatial-autocorrelation between incidence of pulmonary tuberculosis and meteorological and air quality factors, the incidence of pulmonary tuberculosis was used as the dependent variable, and meteorological and air quality factors as independent variables to construct OLS, GWR and GTWR models, respectively. Then the goodness of the three models was evaluated, and the optimal model was selected to describe the incidence of pulmonary tuberculosis. Kernel density plot and spatio-temporal graph were used to describe the spatio-temporal specificity of the fitting coefficients of each variable. Results The overall incidence of pulmonary tuberculosis in China during 2016-2018 decreased annually, with clustered spatial distribution. The GTWR model had higher R2 value and lower AICc value compared to other two models, indicating that it had better performance in explaining the influence of meteorological and air quality factors on the incidence of pulmonary tuberculosis. The kernel density plot of each variable showed that the increase of wind speed was associated with decreased pulmonary tuberculosis incidence in most cities. But the increase of humidity and air pollutant concentration was associated with increased incidence of pulmonary tuberculosis, and the strength of association varied across cities. Conclusion Meteorological and air quality factors may significantly influence the incidence of pulmonary tuberculosis, and the influence had spatio-temporal specificity. So prevention methods for pulmonary tuberculosis should be developed according to region-specific factors influencing the disease.

Keywords

• tuberculosis, pulmonary|incidence|gtwr|meteorological factors|medical meteorology|air pollutants|root cause analysis