ArticleBMC infectious diseases2019
Spatiotemporal epidemiology of, and factors associated with, the tuberculosis prevalence in northern China, 2010-2014.
Article in BMC infectious diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis 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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Geo-spatial high-risk clusters of Tuberculosis in the global general population: a systematic review.BMC public health · 2023Pooled it
- Tuberculosis incidence and mortality trends in mainland China, 2004-2024: control program and elimination progress.Tropical medicine and health · 2026Article
- Prevalence of Tuberculosis in Central Asia and Southern Caucasus: A Systematic Literature Review.Diagnostics (Basel, Switzerland) · 2025Review
- Sentinel-Site-Based Surveillance ofAntibiotics (Basel, Switzerland) · 2025Article
- Spatial autocorrelation with environmental factors related to tuberculosis prevalence in Nepal, 2020-2023.Infectious diseases of poverty · 2025Article
- Latent tuberculosis infection in China, 1990-2050: GBD-informed projections for age-targeted screening.Frontiers in public health · 2025Article
- Predicting Tuberculosis Risk in Cattle, Buffaloes, Sheep, and Goats in China Based on Air Pollutants and Meteorological Factors.Animals : an open access journal from MDPI · 2024Article
- Epidemiological characteristics of tuberculosis incidence and its macro-influence factors in Chinese mainland during 2014-2021.Infectious diseases of poverty · 2024Article
- Ecological-level factors associated with tuberculosis incidence and mortality: A systematic review and meta-analysis.PLOS global public health · 2024Article
- 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
- Spatial Co-Clustering of Tuberculosis and HIV in Ethiopia.Diseases (Basel, Switzerland) · 2022Article
- A study of risk factors for tuberculous meningitis among patients with tuberculosis in China: An analysis of data between 2012 and 2019.Frontiers in public health · 2022Article
- Variation of tuberculosis prevalence across diagnostic approaches and geographical areas of Indonesia.PloS one · 2021Article
- Notifiable Respiratory Infectious Diseases in China: A Spatial-Temporal Epidemiology Analysis.International journal of environmental research and public health · 2020Article
- Spatio-temporal co-occurrence of hotspots of tuberculosis, poverty and air pollution in Lima, Peru.Infectious diseases of poverty · 2020Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
backgroundTuberculosis (TB) is an important public health issue worldwide. However, evidence concerning the impact of environmental factors on TB is sparse. We performed a retrospective analysis to determine the spatiotemporal trends and geographic variations of, and the factors associated with, the TB prevalence in Inner Mongolia.
methodsWe performed a retrospective analysis of the epidemiology of TB. A Bayesian spatiotemporal model was used to investigate the spatiotemporal distribution and trends of the TB prevalence. A spatial panel data model was used to identify factors associated with the TB prevalence in the 101 counties of Inner Mongolia, using county-level aggregated data collected by the Inner Mongolia Center for Disease Control and Prevention.
resultsFrom January 2010 to December 2014, 79,466 (6.36‱) incident TB cases were recorded. The TB prevalence ranged from 4.97‱ (12,515/25,167,547) in 2014 to 7.49‱ (18,406/ 24,578,678) in 2010; the majority of TB cases were in males, and in those aged 46-60 years; by occupation, farmers and herdsmen were the most frequently affected. The Bayesian spatiotemporal model showed that the overall TB prevalence decreased linearly from 2010 to 2014 and occupation-stratified analyses yielded similar results, corroborating the reliability of the findings. The decrease of TB prevalence in the central-western and eastern regions was more rapid than that in the overall TB prevalence. A spatial correlation analysis showed spatial clustering of the TB prevalence from 2011 to 2014 (Moran's index > 0, P < 0.05); in the spatial panel data model, rural residence, birth rate, number of beds, population density, precipitation, air pressure, and sunshine duration were associated with the TB prevalence.
conclusionsThe overall TB prevalence in Inner Mongolia decreased from 2010 to 2014; however, the incidence of TB was high throughout this period. The TB prevalence was influenced by a spatiotemporal interaction effect and was associated with epidemiological, healthcare, and environmental 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.