Geospat Health. 2026 Jul 23;21(2). doi: 10.4081/gh.2026.1486. Epub 2026 Oct 5.
ABSTRACT
Stroke is a leading cause of mortality and disability worldwide; however, its burden is unevenly distributed across geographical areas. This systematic review aimed to synthesise studies examining the spatial distribution of stroke incidence, prevalence and mortality, with a review of geospatial analytical approaches used to identify these patterns. A systematic literature search identified 29 studies that applied spatial analysis or spatial modelling techniques to stroke-related outcomes. The included studies demonstrated heterogeneity in geographical scale, spatial units, outcome measures and covariate selection. Methodological quality was assessed using a modified Joanna Briggs Institute (JBI) critical appraisal tool. Overall, stroke incidence and mortality were consistently found to be non-randomly distributed in space, with significant spatial autocorrelation and clustering observed across multiple spatial scales. These spatial patterns were closely associated with area-level factors, including population ageing, socioeconomic conditions and urban-rural characteristics. Environmental exposures and disparities in the spatial distribution of healthcare resources and access to care were also reported to contribute to geographical differences in stroke outcomes. Geospatial methods commonly employed included GIS-based mapping, spatial autocorrelation analyses, spatial regression models and Bayesian disease mapping. Although most studies demonstrated moderate to high methodological quality, variation remained in the justification of spatial unit selection and the control of covariates. In conclusion, the burden of stroke exhibits pronounced spatial heterogeneity shaped by structural, environmental and healthcare accessibility factors. Future geospatial research should adopt evidence-based spatial units and integrated analytical approaches to support place-based stroke prevention strategies and inform health policy development.
PMID:42831453 | DOI:10.4081/gh.2026.1486