Evidence map›Paper›PMID 41984302›Full record

ArticleEcoHealth2026

Spatial Distribution and Determinants of Kashin-Beck Disease in Gansu Province, China.

Shaolun Yang, Xiaoyan Chen, Xiaoning Liu

Abstract read
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In one paragraph

Article in EcoHealth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Shaolun Yang *Department of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Donggang West Road 199, Lanzhou, 730000, Gansu, China.
Xiaoyan Chen *Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China.
Xiaoning LiuDepartment of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Donggang West Road 199, Lanzhou, 730000, Gansu, China. liuxn@lzu.edu.cn.

Funding

Innovation and Entrepreneurship Talent Project of Lanzhou 2021-RC-110Scientific Research Project of Gansu Provincial Administration of Traditional Chinese Medicine GZKG-2024-68
6 · The paper itself

Abstract

Kashin-Beck disease (KBD) is an endemic disease characterized by its complex etiology and severe impact on human health. It is also regarded as one of the most serious endemic disease in China. This study aimed to investigate the spatial correlation and determinants of this disease. Monitoring data of children and possible influencing factors were collected from 37 KBD regions in Gansu Province. The spatial autocorrelation method was used to describe the spatial aggregation of KBD, and the spatial regression analysis was used to explore the natural environment and socioeconomic factors influencing KBD incidence. The results showed that the X-ray detection rate of KBD demonstrated a significant negative spatial correlation, with Kangle county and its neighboring areas located in southcenter of Gansu Province were hot spots of KBD. The spatial lag model revealed that rainfall, the proportion of afforestation in cultivated land, and population density had negative effects on the X-ray detection rate of KBD. The prevalence of KBD in Gansu Province is determined by a combination of natural environment and socioeconomic factors. Precision prevention and control should be implemented by the specific conditions of each diseased region.

Indexed as

Kashin-Beck DiseaseChildChinaEndemic DiseasesEnvironmentHumansIncidenceSocioeconomic FactorsSpatial AnalysisKBDSpatial correlationSpatial lag modelX-ray detection rate

Identifiers

What OpenQuestion holds

Textmetadata
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Registered trials

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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.