ArticleRisk management and healthcare policy2020
Application of GIS Spatial Analysis and Scanning Statistics in the Gynecological Cancer Clustering Pattern and Risk Screening: A Case Study in Northern Jiangxi Province, China.
Article in Risk management and healthcare policy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Scientometric Analysis of Articles on Spatial Epidemiology of Cancer in Iran: A Systematic Review.Iranian journal of medical sciences · 2023Pooled it
- Spatiotemporal dynamics and prevention strategies of cervical cancer incidence in Addis Ababa, Ethiopia: an ecological study.BMJ open · 2025Article
- Nomograms for Predicting Overall and Cancer-Specific Survival Among Second Primary Endometrial Cancer in Primary Colorectal Carcinoma Patients.Risk management and healthcare policy · 2024Article
- Geographic Characteristics of Various Cancers in Yogyakarta Province, Indonesia: A Spatial Analysis at the Community Level.Asian Pacific journal of cancer prevention : APJCP · 2022Article
- Exploring the relationship between spiritual well-being and death anxiety in patients with gynecological cancer: a cross-section study.BMC palliative care · 2021Article
- The spatial distribution of colorectal cancer relative risk in Iran: a nationwide spatial study.Gastroenterology and hepatology from bed to bench · 2020Article
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Abstract
objectiveThe incidence of gynecological cancer is high in China, and the effects of related treatments and preventive measures need to be improved.
methodsThis study uses GIS spatial analysis methods and a scanning statistical analysis to study the major gynecological cancers in northern Jiangxi Province from 2016 to 2018.
resultsThe incidence and spatial pattern of cervical cancer, ovarian cancer, and uterine cancer had agglomeration characteristics and changes during the study period. The gynecological cancer had a spatial autocorrelation and agglomeration in its spatial pattern. The Moran's Index of the overall gynecological cancer incidence rate was 0.289 (p = 0.005). Ripley's L(d) function showed that the agglomeration radius was between 51.40 and 52.82 km. The results of the kernel density estimation showed that the cases of gynecological cancer were concentrated in the central and northeastern areas of the study area. The overall county-level incidence of gynecological cancer varied from 0.26 to 11.14 per 100,000. The results of the gravity center analysis showed that the spatial distribution of the gravity center point of gynecological cancer had moved toward the east during the past three years. The results of a hotspot analysis showed that there were five hotspot areas that had gynecological cancers. The most likely clusters of gynecological cancer at the county level in northern Jiangxi Province were distributed in the adjacent areas of Jiujiang, Yichun, and Nanchang, with a relative risk of 1.85.
conclusionThe research shows that GIS can display the distribution of cancer cases and can use spatial analysis methods and scanning statistical techniques to obtain key areas of cancer incidence. These results can provide data and key areas for the formulation of regional public health policies and provide recommendations for cancer screening and the rational allocation of health resources.
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