ArticleInternational journal of environmental research and public health2015
A spatial, social and environmental study of tuberculosis in China using statistical and GIS technology.
Article in International journal of environmental research and public health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
48 citing papers in PubMed, 2 syntheses or guidelines pooled it, 103 citations in OpenAlex.
- Small-scale spatiotemporal epidemiology of notifiable infectious diseases in China: a systematic review.BMC infectious diseases · 2022Pooled it
- Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review.BMC medicine · 2018Pooled it
- Polymorphisms in Toll-Like Receptor 10 and Tuberculosis Susceptibility: Evidence from Three Independent Series.Frontiers in immunology · 2018Trial
- Optimizing Tuberculosis Incidence Prediction: A Systematic Review of Hybrid Modeling Approaches and Machine Learning Techniques.Public health challenges · 2026Review
- Environmental-demographic determinants associated with tuberculosis prevalence in seven African countries: an aggregated dataset analysis.EClinicalMedicine · 2026Article
- Investigation of tuberculosis incidence and particulate matter concentration in the middle east.Scientific reports · 2025Article
- Spatiotemporal analysis of pulmonary tuberculosis in the central region of the Zhejiang Province, China (2016-2024).Frontiers in public health · 2025Article
- A study on the spatial distribution of life expectancy and its air pollution factors in China based on geographically weighted regression.Frontiers in public health · 2025Article
- Interacting particle models on the impact of spatially heterogeneous human behavioral factors on dynamics of infectious diseases.PLoS computational biology · 2024Article
- A retrospective study of tuberculosis prevalence and associated factors among HIV-positive key populations in Nigeria.PLOS global public health · 2024Article
- Ecological-level factors associated with tuberculosis incidence and mortality: A systematic review and meta-analysis.PLOS global public health · 2024Article
- Population impact of fine particulate matter on tuberculosis risk in China: a causal inference.BMC public health · 2023Article
- Self-efficacy and self-management mediate the association of health literacy and quality of life among patients with TB in Tibet, China: a cross-sectional study.International health · 2023Article
- Geographical evolutionary pathway of global tuberculosis incidence trends.BMC public health · 2023Article
- Spatiotemporal Changes in Pulmonary Tuberculosis Incidence in a Low-Epidemic Area of China in 2005-2020: Retrospective Spatiotemporal Analysis.JMIR public health and surveillance · 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
- Spatial-temporal analysis of pulmonary tuberculosis in Hubei Province, China, 2011-2021.PloS one · 2023Article
- Influence of the Demographic, Social, and Environmental Factors on the COVID-19 Pandemic-Analysis of the Local Variations Using Geographically Weighted Regression.International journal of environmental research and public health · 2022Article
- Investigating Spatial Patterns of Pulmonary Tuberculosis and Main Related Factors in Bandar Lampung, Indonesia Using Geographically Weighted Poisson Regression.Tropical medicine and infectious disease · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tuberculosis (TB) remains a major public health problem in China, and its incidence shows certain regional disparities. Systematic investigations of the social and environmental factors influencing TB are necessary for the prevention and control of the disease. Data on cases were obtained from the Chinese Center for Disease and Prevention. Social and environmental variables were tabulated to investigate the latent factor structure of the data using exploratory factor analysis (EFA). Partial least square path modeling (PLS-PM) was used to analyze the complex causal relationship and hysteresis effects between the factors and TB prevalence. A geographically weighted regression (GWR) model was used to explore the local association between factors and TB prevalence. EFA and PLS-PM indicated significant associations between TB prevalence and its latent factors. Altitude, longitude, climate, and education burden played an important role; primary industry employment, population density, air quality, and economic level had hysteresis with different lag time; health service and unemployment played a limited role but had limited hysteresis. Additionally, the GWR model showed that each latent factor had different effects on TB prevalence in different areas. It is necessary to formulate regional measures and strategies for TB control and prevention in China according to the local regional effects of specific factors.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.