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Spatial analysis and influencing factors of pulmonary tuberculosis among students in Nanning, during 2012–2018
BACKGROUND: Economically 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 f...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9129035/ https://www.ncbi.nlm.nih.gov/pubmed/35609085 http://dx.doi.org/10.1371/journal.pone.0268472 |
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author | Yang, Dan-ling Li, Wen Pan, Meng-hua Su, Hai-xia Li, Yan-ning Tang, Meng-ying Song, Xiao-kun |
author_facet | Yang, Dan-ling Li, Wen Pan, Meng-hua Su, Hai-xia Li, Yan-ning Tang, Meng-ying Song, Xiao-kun |
author_sort | Yang, Dan-ling |
collection | PubMed |
description | BACKGROUND: Economically 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. METHODS: We 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. RESULTS: From 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. CONCLUSION: We 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. |
format | Online Article Text |
id | pubmed-9129035 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-91290352022-05-25 Spatial analysis and influencing factors of pulmonary tuberculosis among students in Nanning, during 2012–2018 Yang, Dan-ling Li, Wen Pan, Meng-hua Su, Hai-xia Li, Yan-ning Tang, Meng-ying Song, Xiao-kun PLoS One Research Article BACKGROUND: Economically 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. METHODS: We 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. RESULTS: From 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. CONCLUSION: We 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. Public Library of Science 2022-05-24 /pmc/articles/PMC9129035/ /pubmed/35609085 http://dx.doi.org/10.1371/journal.pone.0268472 Text en © 2022 Yang et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Yang, Dan-ling Li, Wen Pan, Meng-hua Su, Hai-xia Li, Yan-ning Tang, Meng-ying Song, Xiao-kun Spatial analysis and influencing factors of pulmonary tuberculosis among students in Nanning, during 2012–2018 |
title | Spatial analysis and influencing factors of pulmonary tuberculosis among students in Nanning, during 2012–2018 |
title_full | Spatial analysis and influencing factors of pulmonary tuberculosis among students in Nanning, during 2012–2018 |
title_fullStr | Spatial analysis and influencing factors of pulmonary tuberculosis among students in Nanning, during 2012–2018 |
title_full_unstemmed | Spatial analysis and influencing factors of pulmonary tuberculosis among students in Nanning, during 2012–2018 |
title_short | Spatial analysis and influencing factors of pulmonary tuberculosis among students in Nanning, during 2012–2018 |
title_sort | spatial analysis and influencing factors of pulmonary tuberculosis among students in nanning, during 2012–2018 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9129035/ https://www.ncbi.nlm.nih.gov/pubmed/35609085 http://dx.doi.org/10.1371/journal.pone.0268472 |
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