Evidence map›Paper›PMID 37584062›Full record

ArticlePreventive medicine reports2023

Analysis of spatial characteristics and geographic weighted regression of tuberculosis prevalence in Kashgar, China.

Xiaodie Chen, Mawlanjan Emam, Li Zhang, Ramziya Rifhat, Liping Zhang, Yanling Zheng

Open access · goldAbstract read
In one paragraph

Article in Preventive medicine reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.3field-weighted citation impact, top 7% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 17 citations in OpenAlex.

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    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Xiaodie ChenCollege of Public Health, Xinjiang Medical University, Urumqi 830017, China.
Mawlanjan EmamCenter for Disease Control and Prevention, Kashgar 844000,China.
Li ZhangFirst Affiliated Hospital of Xinjiang Medical University, Urumqi 830011, Xinjiang, China.
Ramziya RifhatCollege of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830017, China.
Liping ZhangCollege of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830017, China.
Yanling ZhengCollege of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830017, China.
Xinjiang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Number of cases of tuberculosis (TB) was higher than that of the national level in Kashgar, China. This study aimed to analyze the spatial and temporal distribution of TB and the relationship between TB and social factors, which can provide a reference for the prevention and control of TB. We applied spatial autocorrelation analysis to study the distribution of tuberculosis in Kashgar. We used a geographically weighted regression (GWR) model to analyze the relationship between TB and social factors. A total of 100,330 cases of TB in Kashgar from 2016 to 2021 were analyzed. The number of TB cases in Kashgar was higher in the east, lower in the west, and most elevated in the center. The highest cumulative number of cases was found in Shache county. Global Moran's I ranged from -0.212 to -0.549, and local spatial autocorrelation analysis identified four clusters. According to our analysis, the incidence of tuberculosis was negatively correlated among the regions of Kashgar, and the related causes need to be analyzed in depth in future studies. Per capita gross domestic product (GDP), number of medical institutions per capita, and total population influenced the incidence of tuberculosis in Kashgar. Based on our findings, we suggest some effective measures to reduce the risk of TB infection, such as improving the living standard, developing the regional economy, and distributing health resources rationally.

Indexed as

Geographically weighted regressionMoran's ISpatial autocorrelationTuberculosis

Identifiers

PMID37584062
PMCPMC10424202
OpenAlexW4385577491

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.