Epidemiology, risk areas and macro determinants of gastric cancer: a study based on geospatial analysis

Abstract

Background: Both incidence and mortality of gastric cancer in Gansu rank first in china, this study aimed to describe the recent prevalence of gastric cancer and explore the social and environmental determinants of gastric cancer in Gansu Province.

Methods: The incidence of gastric cancer in each city of Gansu Province was calculated by utilizing clinical data from patients with gastric cancer (2013-2021) sourced from the medical big data platform of the Gansu Province Health Commission, and demographic data provided by the Gansu Province Bureau of Statistics. Subsequently, we conducted joinpoint regression analysis, spatial auto-correlation analysis, space-time scanning analysis, as well as an exploration into the correlation between social and environmental factors and GC incidence in Gansu Province with Joinpoint_5.0, ArcGIS_10.8, GeoDa, SaTScan^TM_10.1.1 and GeoDetector_2018.

Results: A total of 75,522 cases of gastric cancer were included in this study. Our findings suggested a significant upward trend in the incidence of gastric cancer over the past nine years. Notably, Wuwei, Zhangye and Jinchang had the highest incidence rates while Longnan, Qingyang and Jiayuguan had the lowest. In spatial analysis, we have identified significant high-high cluster areas and delineated two high-risk regions as well as one low-risk region for gastric cancer in Gansu. Furthermore, our findings suggested that several social and environmental determinants such as medical resource allocation, regional economic development and climate conditions exerted significant influence on the incidence of gastric cancer.

Conclusions: Gastric cancer remains an enormous threat to people in Gansu Province, the significant risk areas, social and environmental determinants were observed in this study, which may improve our understanding of gastric cancer epidemiology and help guide public health interventions in Gansu Province.

Keywords: Epidemiology; Gastric cancer; Risk areas; Social and environmental factors; Spatial analysis.

Fig. 1

The age composition of patients included

Fig. 2

The mean age, median age and the trend of age proportion of patients included (A, mean age and median age. B, the trend of age proportion.)

Fig. 3

The gastric cancer incidence for different gender in different cities (1/100,000)

Fig. 4

The cases and incidence of gastric cancer in rural and urban regions(A, cases. B, incidence.)

Fig. 5

Time trends of incidences of gastric cancer in Gansu province from 2013 to 2021 (A, Incidence. B, Joinpoint regression for ASR.)

Fig. 6

The prevalence map of gastric cancer in Gansu

Fig. 7

Global auto-correlation analyses (A, Moran`s index scatter plot. B, Permutation test.)

Fig. 8

Hot spot analysis of gastric cancer incidence in Gansu province

Fig. 9

Local auto-correlation analysis (A, Clustering map. B, Significance map)

Fig. 10

Purely spatial clusters map of GC in Gansu province

Fig. 11

Natural environmental data of Gansu province. (A, regional rainfall. B, ambient temperature data. C, ambient humidity data. D, diurnal temperature variation data. E, altitude data. F, slope data. G, topography data. H, agrotype data. I, vegetational form data.)

Fig. 12

Interactive impact of risk factors on gastric cancer incidence in Gansu (X1, GDP; X2, Output value of first industry; X3, Output value of second industry; X4, Output value of third industry; X5, GDP per capita; X6, Number of medical institutions per 10,000 people; X7, Number of hospital beds per 10,000 people; X8, Number of health technical staffs per 10,000 people; X9, Altitude; X10, Slope; X11, Topography; X12, Agrotype; X13, Vegetational form; X14, Regional rainfall; X15, Ambient temperature; X16, Diurnal temperature variation; X17, Ambient humidity)