Prevalence of Dementia and Cognitive Impairment in East Africa Region: A Scoping Review of Population-Based Studies and Call for Further Research
Bibliographic record
Abstract
Background: Population-based research on the prevalence and determinants of dementia, Alzheimer's disease, and cognitive impairment is scarce in East Africa. Objective: To provide an overview of community- and population-based studies among older adults on the prevalence of dementia and cognitive impairment in East Africa, and identify research gaps. Methods: We carried out a literature search using three electronic databases (PubMed, Scopus, Google Scholar) using pertinent search terms. Results: After screening 445 publications, we identified four publications on the population-based prevalence of dementia, and three on cognitive impairment. Prevalence rates varied from 6- 23% for dementia, and 7- 44% for cognitive impairment, among participants aged≥50-70 years. Old age and a lower education level were risk factors for dementia and cognitive impairment. Physical inactivity, lack of a ventilated kitchen, and history of central nervous system infections and chronic headache were associated with increased odds of dementia. Female sex, depression, having no spouse, increased lifetime alcohol consumption, low income, rural residence, and low family support were associated with increased odds of cognitive impairment. Potential misclassification and non-standardized data collection methods are research gaps that should be addressed in future studies. Conclusions: Establishing collaborative networks and partnering with international research institutions may enhance the capacity for conducting population-based studies on dementia and cognitive impairment in East Africa. Longitudinal studies may provide valuable insights on incidence, as well as potential risk and protective factors of dementia and cognitive impairment, and may inform the development of targeted interventions including preventive strategies in the region.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.022 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".