ArticlePloS one2022
Spatial analysis and influencing factors of pulmonary tuberculosis among students in Nanning, during 2012-2018.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 16 citations in OpenAlex.
- Spatiotemporal patterns, associated factors, and forecasting of pulmonary tuberculosis: a 19-year township-level case study in Zigong City, China.BMC public health · 2026Article
- Multiscale geographically weighted modeling of tuberculosis incidence in China: integrating geographic perspectives into epidemiological analysis.International journal of health geographics · 2025Article
- Surveillance of tuberculosis incidence and mortality through spatio-temporal analysis in Oyo State, Nigeria.PloS one · 2025Article
- Epidemiological characteristics of tuberculosis incidence and its macro-influence factors in Chinese mainland during 2014-2021.Infectious diseases of poverty · 2024Article
- Spatial spillover effect of environmental factors on the tuberculosis occurrence among the elderly: a surveillance analysis for nearly a dozen years in eastern China.BMC public health · 2024Article
- Rapid detection of multidrug resistance in tuberculosis using nanopore-based targeted next-generation sequencing: a multicenter, double-blind study.Frontiers in microbiology · 2024Article
- Article
- Spatial-temporal analysis of pulmonary tuberculosis among students in the Zhejiang Province of China from 2007-2020.Frontiers in public health · 2023Article
- Spatial Effect of Ecological Environmental Factors on Mumps in China during 2014-2018.International journal of environmental research and public health · 2022Article
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7 authors at 1 institution in 1 country.
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Abstract
backgroundEconomically underdeveloped areas in western China are hotspots of tuberculosis, especially among students. However, the related spatial and temporal patterns and influencing factors are still unclear and there are few studies to analyze the causes of pulmonary tuberculosis in students from the perspective of space.
methodsWe collected data regarding the reported incidence of pulmonary tuberculosis (PTB) among students at township level in Nanning, from 2012 to 2018. The reported incidence of pulmonary tuberculosis among students in Nanning was analyzed using spatial autocorrelation and spatial scan statistical analysis to depict hotspots of PTB incidence and spatial and temporal clustering. Spatial panel data of the reported incidence rates and influencing factors at district and county levels in Nanning were collected from 2015 to 2018. Then, we analyzed the spatial effects of incidence and influencing factors using the spatial Durbin model to explore the mechanism of each influencing factor in areas with high disease prevalence under spatial effects.
resultsFrom 2012 to 2018, 1609 cases of PTB were reported among students in Nanning, with an average annual reported incidence rate of 14.84/100,000. Through the Joinpoint regression model, We observed a steady trend in the percentage of cases reported each year (P>0.05). There was spatial autocorrelation between the annual reported incidence and the seven-years average reported incidence from 2012 to 2018. The high-incidence area was distributed in the junction of six urban areas and spread to the periphery, with the junction at the center. The population of college students, per capita financial expenditure on health, per capita gross domestic product, and the number of health technicians per 1,000 population were all influencing factors in the reported incidence of PTB among students.
conclusionWe identified spatial clustering of the reported incidence of PTB among students in Nanning, mainly located in the urban center and its surrounding areas. The clustering gradually decreased from the urban center to the surrounding areas. Spatial effects influenced the reported incidence of PTB. The population density of college students, per capita health financial expenditure, gross domestic product (GDP) per capita, and the number of health technicians per 1,000 were all influencing factors in the reported incidence of PTB among students.
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