Spatiotemporal analysis of gastric cancer incidence in Iran from 2014 to 2018: a geospatial epidemiological study

Gastric cancer (GC) is a well-known tumor with global implications. Previous studies in Iran have provided valuable insights into national incidence trends, but there is still a paucity of precise spatiotemporal analysis based on population-level cancer registry data. This gap in scientific knowledge needs correction through the use of modern geospatial approaches, which have the ability to provide localized preventative strategies. As a result, the primary goal of this research is to thoroughly examine the regional and temporal dynamics underpinning GC incidence in Iran.

Age-standardized GC incidence rates were computed utilizing Iranian population-based cancer registry data from 2014 to 2018 across provinces and demographic strata. Global Moran's I assessed spatial autocorrelation and local indicators of spatial association cluster analysis delineated concentrated high and low-incidence clusters. Using space-time cube representations, emerging hot spot analysis highlighted spatiotemporal dynamics.

The analysis revealed significant inter-provincial inequalities, with Ardabil had the greatest incidence rate (34.2 per 100,000), whereas Hormozgan had the lowest (7.1 per 100,000). Males were shown to be more vulnerable across the board. While national incidence rates remained relatively stable from 2014 to 2018, the analyses revealed substantial provincial variation, with some regions showing intensifying high-incidence clusters (e.g., Gilan) and others displaying declining trends (e.g., Zanjan). Emerging Hot Spot Analysis revealed persistent pattern of high-incidence clustering in Ardabil, whereas Zanjan exhibited a diminishing hot spot trend, reflecting declining spatial significance over time.

This geospatial analysis provides crucial insights into Iran's significant yet geographically variable GC burden. These findings underscore the importance of spatially-informed cancer surveillance and support further investigation into the underlying drivers of geographic variation in GC incidence. While not intended to guide direct interventions, the patterns observed may help shape future epidemiologic studies or hypothesis-driven screening strategies.