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. 2020 Aug 10:13:1079-1093.
doi: 10.2147/RMHP.S261221. eCollection 2020.

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

Zhiwei Wan #  1 , Yaqi Wang #  2 , Chunhong Deng  2
Affiliations

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

Zhiwei Wan et al. Risk Manag Healthc Policy. .

Abstract

Objective: The incidence of gynecological cancer is high in China, and the effects of related treatments and preventive measures need to be improved.

Methods: This 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.

Results: The 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.

Conclusion: The 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.

Keywords: GIS spatial analysis; cervical cancer; gynecological cancer; ovarian cancer; risk scanning; spatial pattern; spatiotemporal heterogeneity; uterine cancer.

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Conflict of interest statement

The authors declare that they have no conflicts of interest for this work.

Figures

Figure 1
Figure 1
Location map and administrative division of the study area.
Figure 2
Figure 2
Spatial distribution of gynecologic cancer incidence in northern Jiangxi Province from 2016 to 2018. (A) Cervical cancer. (B) Ovarian cancer. (C) Uterine cancer. (D) Total gynecological cancer.
Figure 3
Figure 3
Standard deviation ellipse of gynecological cancer in northern Jiangxi Province and the changing trend of the center of gravity.
Figure 4
Figure 4
Estimation map of the spatial distribution of kernel density in patients with gynecological cancer in northern Jiangxi Province.
Figure 5
Figure 5
Ripley’s L(d) function graph of gynecological cancer incidence in northern Jiangxi Province. (A) Cervical cancer. (B) Ovarian cancer. (C) Uterine cancer. (D) Total gynecological cancer.
Figure 6
Figure 6
Spatial distribution of cold and hotspots in the incidence of gynecological cancer in northern Jiangxi Province. (A) Cervical cancer. (B) Ovarian cancer. (C) Uterine cancer. (D) 2016–2018 gynecological cancer.
Figure 7
Figure 7
Spatial clustering and relative risk distribution of gynecological cancer incidence spatial SaTScan in northern Jiangxi Province. (A) Cervical cancer. (B) Ovarian cancer. (C) Uterine cancer. (D) Total gynecological cancer.
See this image and copyright information in PMC

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