Unravelling cognitive decline among elderly in rural communities: A cross-sectional study.
Pratyaksha Pandit, Reema Kumari, Adarsh Tripathi, Prabhakar Mishra, Sugandhi Sharma
Abstract
Open AccessBackground: Dementia is a major cause of disability among older adults. The global burden of dementia is expected to triple by 2050, with developing countries, witnessing a sharp increase. Early detection and management through screening programs can mitigate the progression of cognitive decline. Objectives: This study aimed to determine the prevalence and predictors of cognitive impairment among older adults residing in rural areas. Methods: An analytical cross-sectional study was conducted among older individuals residing in rural communities. A three-stage cluster sampling method was employed to select 350 participants. Cognitive screening was performed using the Hindi Mental State Examination, with a score ≤23 indicating cognitive impairment. Data on socio-demographics, clinical parameters, and functional abilities were collected and analyzed using SPSS version 26. Results: The prevalence of cognitive impairment (CI) was 24.9% (n = 87), with the majority presenting with mild CI (87.4%). CI was significantly higher among females (33.9%) (AOR: 3.2, 1.7-6.01). Key predictors of CI included advanced age (AOR: 3.4, 1.8-6.7), widowhood (AOR: 2.2, 1.5-4.1), and functional limitations [activities of daily living and instrumental ADL (ADL and IALD)] (AOR: 9.71 and 11.22, respectively). A significant positive correlation was found between overall Hindi mental state examination (HMSE) score and anthropometric measures, with the strongest association observed with height (r = 0.47, P < 0.001), followed by weight (r = 0.37, P < 0.001). Conclusion: Cognitive impairment is the highly prevalent among the elderly in rural areas, with multiple socio-demographic and behavioral factors contributing to its occurrence. Implementing routine cognitive screening and promoting physical activity, social engagement, and healthy lifestyle practices are essential for early detection and intervention.