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The association between internal migration and pulmonary tuberculosis in China, 2005–2015: a spatial analysis

BACKGROUND: Internal migration places individuals at high risk of contracting tuberculosis (TB). However, there is a scarcity of national-level spatial analyses regarding the association between TB and internal migration in China. In our research, we aimed to explore the spatial variation in cases o...

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Autores principales: Liao, Wei-Bin, Ju, Ke, Gao, Ya-Min, Pan, Jay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7025414/
https://www.ncbi.nlm.nih.gov/pubmed/32063228
http://dx.doi.org/10.1186/s40249-020-0621-x
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author Liao, Wei-Bin
Ju, Ke
Gao, Ya-Min
Pan, Jay
author_facet Liao, Wei-Bin
Ju, Ke
Gao, Ya-Min
Pan, Jay
author_sort Liao, Wei-Bin
collection PubMed
description BACKGROUND: Internal migration places individuals at high risk of contracting tuberculosis (TB). However, there is a scarcity of national-level spatial analyses regarding the association between TB and internal migration in China. In our research, we aimed to explore the spatial variation in cases of sputum smear-positive pulmonary TB (SS + PTB) in China; and the associations between SS + PTB, internal migration, socioeconomic factors, and demographic factors in the country between 2005 and 2015. METHODS: Reported cases of SS + PTB were obtained from the national PTB surveillance system database; cases were obtained at the provincial level. Internal migration data were extracted from the national population sampling survey and the census. Spatial autocorrelations were explored using the global Moran’s statistic and local indicators of spatial association. The spatial temporal analysis was performed using Kulldorff’s scan statistic. Fixed effects regression was used to explore the association between SS + PTB and internal migration. RESULTS: A total of 4 708 563 SS + PTB cases were reported in China between 2005 and 2015, of which 3 376 011 (71.7%) were male and 1 332 552 (28.3%) were female. There was a trend towards decreasing rates of SS + PTB notifications between 2005 and 2015. The result of global spatial autocorrelation indicated that there were significant spatial correlations between SS + PTB rate and internal migration each year (2005–2015). Spatial clustering of SS + PTB cases was mainly located in central and southern China and overlapped with the clusters of emigration. The proportions of emigrants and immigrants were significantly associated with SS + PTB. Per capita GDP and education level were negatively associated with SS + PTB. The internal migration flow maps indicated that migrants preferred neighboring provinces, with most migrating for work or business. CONCLUSIONS: This study found a significant spatial autocorrelation between SS + PTB and internal migration. Both emigration and immigration were statistically associated with SS + PTB, and the association with emigration was stronger than that for immigration. Further, we found that SS + PTB clusters overlapped with emigration clusters, and the internal migration flow maps suggested that migrants from SS + PTB clusters may influence the TB epidemic characteristics of neighboring provinces. These findings can help stakeholders to implement effective PTB control strategies for areas at high risk of PTB and those with high rates of internal migrants.
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spelling pubmed-70254142020-02-24 The association between internal migration and pulmonary tuberculosis in China, 2005–2015: a spatial analysis Liao, Wei-Bin Ju, Ke Gao, Ya-Min Pan, Jay Infect Dis Poverty Research Article BACKGROUND: Internal migration places individuals at high risk of contracting tuberculosis (TB). However, there is a scarcity of national-level spatial analyses regarding the association between TB and internal migration in China. In our research, we aimed to explore the spatial variation in cases of sputum smear-positive pulmonary TB (SS + PTB) in China; and the associations between SS + PTB, internal migration, socioeconomic factors, and demographic factors in the country between 2005 and 2015. METHODS: Reported cases of SS + PTB were obtained from the national PTB surveillance system database; cases were obtained at the provincial level. Internal migration data were extracted from the national population sampling survey and the census. Spatial autocorrelations were explored using the global Moran’s statistic and local indicators of spatial association. The spatial temporal analysis was performed using Kulldorff’s scan statistic. Fixed effects regression was used to explore the association between SS + PTB and internal migration. RESULTS: A total of 4 708 563 SS + PTB cases were reported in China between 2005 and 2015, of which 3 376 011 (71.7%) were male and 1 332 552 (28.3%) were female. There was a trend towards decreasing rates of SS + PTB notifications between 2005 and 2015. The result of global spatial autocorrelation indicated that there were significant spatial correlations between SS + PTB rate and internal migration each year (2005–2015). Spatial clustering of SS + PTB cases was mainly located in central and southern China and overlapped with the clusters of emigration. The proportions of emigrants and immigrants were significantly associated with SS + PTB. Per capita GDP and education level were negatively associated with SS + PTB. The internal migration flow maps indicated that migrants preferred neighboring provinces, with most migrating for work or business. CONCLUSIONS: This study found a significant spatial autocorrelation between SS + PTB and internal migration. Both emigration and immigration were statistically associated with SS + PTB, and the association with emigration was stronger than that for immigration. Further, we found that SS + PTB clusters overlapped with emigration clusters, and the internal migration flow maps suggested that migrants from SS + PTB clusters may influence the TB epidemic characteristics of neighboring provinces. These findings can help stakeholders to implement effective PTB control strategies for areas at high risk of PTB and those with high rates of internal migrants. BioMed Central 2020-02-17 /pmc/articles/PMC7025414/ /pubmed/32063228 http://dx.doi.org/10.1186/s40249-020-0621-x Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Liao, Wei-Bin
Ju, Ke
Gao, Ya-Min
Pan, Jay
The association between internal migration and pulmonary tuberculosis in China, 2005–2015: a spatial analysis
title The association between internal migration and pulmonary tuberculosis in China, 2005–2015: a spatial analysis
title_full The association between internal migration and pulmonary tuberculosis in China, 2005–2015: a spatial analysis
title_fullStr The association between internal migration and pulmonary tuberculosis in China, 2005–2015: a spatial analysis
title_full_unstemmed The association between internal migration and pulmonary tuberculosis in China, 2005–2015: a spatial analysis
title_short The association between internal migration and pulmonary tuberculosis in China, 2005–2015: a spatial analysis
title_sort association between internal migration and pulmonary tuberculosis in china, 2005–2015: a spatial analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7025414/
https://www.ncbi.nlm.nih.gov/pubmed/32063228
http://dx.doi.org/10.1186/s40249-020-0621-x
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