Back

Longitudinal change in cognition in older adults in Uganda: a prospective population study

Prynn, J. E.; Davey, C.; Davis, D. E.; Kuper, H.; Mugisha, J.; Seeley, J.

2022-04-16 epidemiology
10.1101/2022.04.13.22273824 medRxiv
Show abstract

IntroductionDementia is an important and growing issue in sub-Saharan Africa, but epidemiological data are lacking. Risk factors may differ from other regions due to high stroke incidence and HIV prevalence. Understanding the epidemiology of cognition in older adults in Africa is crucial for informing public health strategies to improve the lives of people with dementia and their carers. MethodsThe Wellbeing of Older People Study in Uganda is an open cohort of adults aged 50+ with and without HIV, established in 2009. Detailed socio-demographic and health data have been collected at four waves spanning 10 years, including cognitive assessment using internationally validated WHO-recommended tests: verbal recall, digit span, and verbal fluency. Mortality data was collected until the end of the fourth wave (2019). We examined associations of low baseline cognition scores and cognitive decline over time, care needs of people with lower cognition, and the relationship between cognition and mortality. ResultsData were collected on 811 participants. Older age, lower educational attainment, lower socio-economic position, and extremes of BMI were associated with lower cognition scores. Cognition declined faster at older ages, but rate of decline was not associated with cardiovascular disease or HIV. People with lower cognition required more assistance with Activities of Daily Living, but mortality rates were similar across the range of cognition. ConclusionsThe crucial next step will be investigating the determinants of low cognition scores and clinical dementia, to better understand the clinical relevance of these findings to inform public health planning in sub-Saharan Africa.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.