Disability Clusters and Socioeconomic Factors in Myanmar: Identifying Spatial Patterns and Associations.

Authors

W M Thi, U E Sandar, K M Htike, U Yy Than

Published in

Kathmandu University medical journal (KUMJ). Volume 23. Issue 92. Pages 441-448.

Abstract

Background Despite persons affected by disability are expected to increase, limited support services and disparities in resource allocation exist in Myanmar which hinder persons with disabilities in accessing essential needs. This highlights the urgent need for spatial analysis through Geographic Information System (GIS) to better understand distribution of disability, socioeconomic correlations, and inform targeted policy interventions. Objective To provide hotspot clusters of disability prevalence across all districts of Myanmar and examine their distribution based on socioeconomic status along with the spatial autocorrelation patterns using Geographic Information System. Method District Level Report of 2019 of Myanmar Intercensal Survey was used. The data were processed and analysed using Quantum Geographic Information System and GeoDa programmes. Univariate and bivariate spatial analysis were performed using Global and Local Moran's I statistics along with Local Indicators of Spatial Association to identify spatial clusters of disability rates. Result The overall prevalence of disability was 12.9 per 100 population in Myanmar. Seven hotspots were identified along the Western Region of Myanmar (Moran's I value of 0.318). In bivariate Local Indicators of Spatial Association analysis, the literacy rate (Moran's I: 0.216), child dependency ratio (Moran's I: 0.137) and old dependency ratio (Moran's I: 0.259) exhibited significant association with disability prevalence. Conclusion This study demonstrated the demographic disparities in distribution of disability prevalence. Moreover, the spatial relationships between socioeconomic factors and disability were identified, offering a foundational understanding for necessary interventions and demonstrating the value of spatial analysis in shaping healthcare strategies.

PMID:
42318719
Bibliographic data and abstract were imported from PubMed on 19 Jun 2026.

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