ArticleGlobal health action2014
Exploration of ecological factors related to the spatial heterogeneity of tuberculosis prevalence in P. R. China.
Article in Global health action, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.
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Who cites it
35 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review.BMC medicine · 2018Pooled it
- Socio-Demographic Predictors and Distribution of Pulmonary Tuberculosis (TB) in Xinjiang, China: A Spatial Analysis.PloS one · 2015Trial
- Healthcare system preparedness as a mediating factor in climate-driven tuberculosis outcomes: an ecological study.BMC health services research · 2026Article
- Environmental-demographic determinants associated with tuberculosis prevalence in seven African countries: an aggregated dataset analysis.EClinicalMedicine · 2026Article
- Spatiotemporal epidemiology and associated risk factors of tuberculosis incidence and mortality in Indonesia 2017-2022: a nationwide space-time hierarchical analysis.Population health metrics · 2026Article
- Investigation of tuberculosis incidence and particulate matter concentration in the middle east.Scientific reports · 2025Article
- Pathogen Detection in Spinal Infections: Next-Generation Sequencing Versus Conventional Microbiological Methods.Current medical science · 2025Article
- Exploring the influencing factors of scrub typhus in Gannan region, China, based on spatial regression modelling and geographical detector.Infectious Disease Modelling · 2025Article
- The impact of meteorological factors on tuberculosis incidence in Spain: a spatiotemporal analysis.Epidemiology and infection · 2024Article
- Ecological-level factors associated with tuberculosis incidence and mortality: A systematic review and meta-analysis.PLOS global public health · 2024Article
- Tuberculosis disease burden in China: a spatio-temporal clustering and prediction study.Frontiers in public health · 2024Article
- Spatiotemporal Distribution of Tuberculosis in the Oromia Region of Ethiopia: A Hotspot Analysis.Tropical medicine and infectious disease · 2023Article
- Machine Learning Prediction Model of Tuberculosis Incidence Based on Meteorological Factors and Air Pollutants.International journal of environmental research and public health · 2023Article
- Article
- Global, regional, and national prevalence of diabetes mellitus in patients with pulmonary tuberculosis: a systematic review and meta-analysis.Diabetology & metabolic syndrome · 2021Article
- Spatio-temporal variation in tuberculosis incidence and risk factors for the disease in a region of unbalanced socio-economic development.BMC public health · 2021Article
- The association between extreme temperature and pulmonary tuberculosis in Shandong Province, China, 2005-2016: a mixed method evaluation.BMC infectious diseases · 2021Article
- Influential factors and spatial-temporal distribution of tuberculosis in mainland China.Scientific reports · 2021Article
- Spatial-temporal analysis of tuberculosis in Chongqing, China 2011-2018.BMC infectious diseases · 2020Article
- Clinical evaluation of the T-SPOT.TB test for detection of tuberculosis infection in northeastern Guangdong Province, China.The Journal of international medical research · 2020Article
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8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe current prevalence of tuberculosis (TB) in the People's Republic of China (P. R. China) demonstrates geographical heterogeneities, which show that the TB prevalence in the remote areas of Western China is more serious than that in the coastal plain of Eastern China. Although a lot of ecological studies have been applied in the exploration on the regional difference of disease risks, there is still a paucity of ecological studies on TB prevalence in P. R. China.
objectiveTo understand the underlying factors contributing to the regional inequity of TB burden in P. R. China by using an ecological approach and, thus, aiming to provide a basis to eliminate the TB spatial heterogeneity in the near future.
designLatent ecological variables were identified by using exploratory factor analysis from data obtained from four sources, i.e. the databases of the National TB Control Programme (2001-2010) in P. R. China, the China Health Statistical Yearbook during 2002-2011, the China Statistical Yearbook during 2002-2011, and the provincial government websites in 2013. Partial least squares path modelling was chosen to construct the structural equation model to evaluate the relationship between TB prevalence and ecological variables. Furthermore, a geographically weighted regression model was used to explore the local spatial heterogeneity in the relationships.
resultsThe latent ecological variables in terms of 'TB prevalence', 'TB investment', 'TB service', 'health investment', 'health level', 'economic level', 'air quality', 'climatic factor' and 'geographic factor' were identified. With the exception of TB service and health levels, other ecological factors had explicit and significant impacts on TB prevalence to varying degrees. Additionally, each ecological factor had different impacts on TB prevalence in different regions significantly.
conclusionEcological factors that were found predictive of TB prevalence in P. R. China are essential to take into account in the formulation of locally comprehensive strategies and interventions aiming to tailor the TB control and prevention programme into local settings in each ecozone.
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