ArticleInternational journal of environmental research and public health2022
Spatiotemporal Analysis of Gastrointestinal Tumor (GI) with Kernel Density Estimation (KDE) Based on Heterogeneous Background.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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1 citing paper in PubMed.
- Informing equitable urban health policy: a multi-source geospatial assessment of spatial mismatch in medical facility distribution across Chinese cities.Frontiers in public health · 2026Article
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5 authors.
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Abstract
The purpose of this study is to explore hotspots or clusters of gastrointestinal tumors (GI) and their spatiotemporal distribution characteristics and the changes over time in 293 villages and communities in Jianze County, central China, through the kernel density estimation (KDE) method based on the rarely considered heterogeneous background. The main findings were: (1) Heterogeneous background impact: there were substantial differences in the GI case rate among people of different ages and genders in Jianze County. Specifically, the GI case rate was significantly higher in the elderly population over 65 than in the population under 65, and higher in men than in women. (2) GI in Jianze County exhibited spatial specific and aggregated hotspots. The high-value spatial clusters were mainly located in Hujindian Town in the northern county, Wupu Town and Geputan Town in the middle, and Xiaxindian Town in the south. Some villages had persistent hot spots for multiple years. (3) Most GI hotspots in Jianze County were concentrated in areas with both high density of local chemical plants and with water systems in the neighbourhood. We expect that this study provides a scientific basis for exploring unknown risk factors of tumor occurrence from a spatial perspective in the future.
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