Factors associated with cognitive performance among urban older adults of Dodoma City, central Tanzania: a cross-sectional study

Abstract

BACKGROUND: Cognitive performance among older adults globally shows varied trends, with high-income countries reporting improved outcomes due to enhanced education and healthcare. In contrast, sub-Saharan Africa faces rising rates of cognitive impairment, particularly among older people. Existing research in Tanzania has predominantly focused on rural populations, leaving a significant gap regarding urban older residents. ​This study addresses this gap by examining the factors that influence cognitive performance among older urban residents in Dodoma City. METHODS: We conducted an analytical cross-sectional study that included 435 older adults. Random sampling was applied to recruit study participants. Cognitive performance was assessed using the Montreal Cognitive Assessment (MoCA). Data were analysed using descriptive statistics and univariate and multivariate linear regression in SPSS version 29, with a statistical significance level set at p < 0.05 to determine cognitive performance and associated factors. RESULTS: The mean score on the cognitive performance test was 11.9, with a standard deviation of 7.564. Factors associated with cognitive performance were; Age, for every 9-year age difference (β: - 0.09; 95% CI - 0.15 to - 0.03), primary and secondary education (β: 2.73; 95% CI 1.51-3.94) and (β: 6.99; 95% CI 4.79-9.20) respectively. Self-employment (β: - 3.49; 95% CI - 5.05 to - 1.92), homemaker (β: - 4.91; 95% CI - 6.23 to - 3.56), unable to work (β: - 4.59; 95% CI - 6.26 to - 2.92), widowed participants (β: - 1.60; 95% CI - 2.70 to - 0.51), reported middle income (β: 7.29; 95% CI 1.59-12.79), Family size with fewer dependents (β: 2.82; 95% CI 1.73-3.90). Additionally, alcohol consumption (β: - 2.08; 95% CI - 3.27 to - 0.88), an increase in 6 units on geriatric depressive symptoms scores (β: - 0.15; 95% CI - 0.24 to - 0.05), and an increase in 2.5 units in IADL scores (β: 0.84; 95% CI 0.57-1.12). CONCLUSION: The findings indicate a complex interplay of demographic, educational, economic, and behavioural factors that significantly influence the low score in cognitive performance. The associated factors mentioned above should be addressed to increase cognitive performance. Overall, promoting educational and socioeconomic opportunities, along with addressing mental health issues, could play a crucial role in enhancing cognitive function in the aging population.