Spatial autoregressive modeling of risk factors associated with chronic diseases among geriatric people

Chronic diseases represent a significant public health challenge among the elderly, particularly in lower-middle-income countries like Bangladesh, where the aging population is rapidly growing. This study aimed to assess the prevalence, spatial distribution, and risk factors of chronic diseases among elderly individuals in Sylhet, Bangladesh. A cross-sectional study was conducted among 543 participants aged 60 years and above, selected using multistage cluster sampling. A spatial autoregressive model with a negative binomial regression was employed to analyze the data, accounting for spatial autocorrelation and over-dispersion. The overall prevalence of chronic diseases was 98.7%. The most common conditions included musculoskeletal disorders (75.0%), digestive diseases (59.3%), and hypertension (44.4%). Significant spatial autocorrelation was observed (Moran’s I = 0.169, p < 0.01), indicating geographic clustering. Males had a 24% lower risk of multiple chronic diseases compared to females (IRR = 0.76, 95% CI: 0.66—0.87). Protective factors included caregiving support from family members (IRR = 0.73, 95% CI: 0.61—0.87), occasional red meat consumption (IRR = 0.89, 95% CI: 0.80—1.00), and consumption of white rice or flour (IRR = 0.80, 95% CI: 0.67—0.96). Conversely, risk factors included passive smoking (IRR = 1.26, 95% CI: 1.14—1.39), regular fast-food consumption (IRR = 1.19, 95% CI: 1.03—1.38), tooth loss (IRR = 1.15, 95% CI: 1.03—1.28), and a history of major surgery (IRR = 1.19, 95% CI: 1.06—1.33) were associated with a higher risk of multiple chronic disease. These findings highlight the urgent need for targeted interventions promoting healthy diets, reducing tobacco exposure, and enhancing family caregiving to mitigate the chronic disease burden among older adults in Sylhet.