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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2020
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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. |
format | Online Article Text |
id | pubmed-7025414 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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