ArticleCureus2026
An Exploratory Assessment of Geographic Variation and Disease Clustering of Multimorbidity Among Older Adults in Odisha, India.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundMultimorbidity among older adults is a significant public health issue in India, yet its regional distribution within states remains poorly understood. Most existing research focuses on overall prevalence or individual risk factors, with less emphasis on district-level differences, spatial heterogeneity, and disease clustering. This study aimed to assess the prevalence, geographic variation, and disease co-occurrence patterns of multimorbidity among older adults in six selected districts of Odisha, India. MATERIALS AND
methodsA community-based cross-sectional study involving 1,072 adults aged 60 and above was carried out across six districts of Odisha: Khordha, Cuttack, Balasore, Sundargarh, Ganjam, and Sambalpur. Multimorbidity was defined as the presence of two or more self-reported physician-diagnosed chronic conditions in the same participant. The prevalence was estimated for each district, and multivariable binary logistic regression was used to analyze factors linked to multimorbidity. Spatial heterogeneity was evaluated using Global Moran's I, and district-specific disease-pair clustering was examined using Jaccard similarity matrices.
resultsA total of 677 participants had multimorbidity, representing a prevalence of 63.2%. The burden varied widely across districts, from 54.2% in Khordha to 74.8% in Cuttack. Sundargarh also exhibited a high prevalence of 73.6%. Spatial analysis revealed significant heterogeneity in the distribution of multimorbidity, with a Global Moran's I of -0.5082, suggesting that high-burden areas were unevenly distributed across the selected districts. Cuttack and Sundargarh stood out as key high-burden regional outliers. In the adjusted analysis, factors such as district of residence, multiple medication use, and living arrangements were linked to multimorbidity. Older adults living only with children had higher odds than those living with both a spouse and children. Jaccard similarity analysis identified district-specific morbidity patterns, including stronger respiratory-musculoskeletal clustering in Khordha and a consistent hypertension-diabetes clustering across districts.
conclusionMultimorbidity among older adults in Odisha shows clear regional variations and specific disease groupings. These results imply that a uniform approach may not be sufficient for managing geriatric multimorbidity across different district contexts. Instead, tailored district-level integrated care, regular medication reviews, and locally adapted multimorbidity management strategies could lead to more sustainable elderly care in Odisha.
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