Font Size: a A A

Spatial-temporal Distribution And Influencing Factors Of Tuberculosis In Inner Mongolia,2016~2018

Posted on:2024-07-28Degree:MasterType:Thesis
Country:ChinaCandidate:C M JingFull Text:PDF
GTID:2544307127977199Subject:Epidemiology and Health Statistics
Abstract/Summary:PDF Full Text Request
Objective:This study aims to analyze the distribution of pulmonary tuberculosis in Inner Mongolia from 2016 to 2018,and to explore the temporal and spatial aggregation of tuberculosis incidence in Inner Mongolia.The influencing factors of pulmonary tuberculosis were explored from the perspective of ecology,analyzing the distribution of population,social economy,health care and meteorological index and other potential factors on the effect of tuberculosis incidence in Inner Mongolia.To provide new ideas and theoretical basis for tuberculosis prevention and control in Inner Mongolia.Methods:In this study,103 banner counties in Inner Mongolia Autonomous Region were taken as research units.To collect data on tuberculosis cases reported in the region from 2016to 2018,and corresponding demographic,socio-economic,medical resources and meteorological indicators,to establish a database of tuberculosis incidence and influencing factors in Inner Mongolia Autonomous Region.In this study,the incidence of pulmonary tuberculosis in Inner Mongolia from 2016 to 2018 was described in three spatial distributions.Seasonal index method,three-dimensional trend surface analysis and spatial autocorrelation method were used to analyze the spatial and temporal distribution and aggregation of the incidence of pulmonary tuberculosis,and spatio-temporal scanning analysis was used to explore the risk areas of the incidence of pulmonary tuberculosis.Factor detection and interaction detection in geographic detector were used to analyze the driving factors of tuberculosis occurrence in Inner Mongolia,and the multi-scale geographical weighted regression model was further used to analyze the correlation and regional differences between demographic information,socio-economic level,medical and health level,climate factors and tuberculosis incidence in Inner Mongolia from 2016 to 2018.Result:(1)A total of 35687 cases of tuberculosis were reported in Inner Mongolia from 2016to 2018,and the incidence increased from 416,500 to 556,300.The number of male cases was1.99 times that of female cases,and the onset of pulmonary tuberculosis was rapid after 15years old.The majority of male cases were 40-69 years old,and the majority of female cases were 45-79 years old.The incidence of tuberculosis is seasonal,and the peak period is from March to June and November every year.(2)The incidence rate first decreased and then increased from west to east and south to north in a"U"shape,with the highest in eastern Inner Mongolia.The highest three-year average incidence rate was in Hinggan League(69.97/100000),followed by Tongliao(66.34/100 000),Chifeng(59.99/100 000)and Hulunbuir(52.39/100 000).Among the 103 banner counties,the highest three-year average incidence was reported in New Barhu Left Banner,followed by New Barhu Right Banner,Naiman Banner,Alashan Right Banner and Horqin Right Middle Banner,with the annual incidence greater than 100/100,000.(3)There was a spatial clustering of tuberculosis in the three years,and the relationship was positive(2016Moran’s I=0.3003,2017Moran’s I=0.3630,2018Moran’s I=0.3637,P=0.001),and the clustering type changed dynamically in each year.However,high values were clustered in the eastern region and low values were clustered near the central region.The spatio-temporal scanning results showed that the main clusters were mainly 31 counties in eastern Inner Mongolia in 2018(RR=1.67,P<0.001).(4)The population factors,economic factors and climate indicators in Inner Mongolia have obvious spatial clustering,which had spatial influence on the incidence of tuberculosis;The factor detection results of geo-detector indicated that urban per capita disposable income(explanatory power:21.73%),number of medical institutions(18.92%),population density(17.82%),gross regional product(17.14%),proportion of secondary industry(16.20%),proportion of working-age population(14.07%),and proportion of rural population(13.65%)and PM2.5 concentration(10.84%)had good explanatory power for pulmonary tuberculosis(P<0.05).Interaction indicates that the interaction between any two influencing factors has a stronger explanatory power on the incidence of pulmonary tuberculosis than a single factor test,which was double factor enhanced or non-linear enhanced,and there was no interaction factor that played a role alone or had weakened explanatory power on the incidence of tuberculosis.(5)The results of MGWR model showed that the fitting degree of MGWR model(R~2=0.625)was better than that of GWR model(R~2=0.265),and the disposable income of urban population had a significant negative effect on the incidence of tuberculosis in Inner Mongolia(regression coefficient-0.289 to-0.260).The proportion of working-age population(regression coefficient-0.139~0.341),the proportion of rural population(regression coefficient-0.377~0.538),and the second industry weight(regression coefficient 0.002~0.204)had a significant positive effect on the eastern region.PM2.5 concentration(regression coefficient-0.114~0.425)had a significant positive effect on the western region.Conclusion:From 2016 to 2018,the incidence of tuberculosis in Inner Mongolia was still at the national medium high level,and the incidence showed an increasing trend.The incidence of tuberculosis was higher among middle-aged and elderly males.The incidence of pulmonary tuberculosis in Inner Mongolia was clustered in temporal and spatial distribution,and the eastern region was the main cluster with high incidence.Population density,proportion of working-age population,proportion of rural population,urban per capita disposable income,proportion of secondary industry,PM2.5 concentration,number of medical institutions and other factors are influencing factors of tuberculosis incidence in Inner Mongolia.
Keywords/Search Tags:tuberculosis, epidemic characteristics, geographic detectors, multiscale geographically weighted regression
PDF Full Text Request
Related items