Prevalence and Patterns of Cognitive Impairment in a Sample of Community Dwelling Older People in Nigeria
Bibliographic record
Abstract
Objective: Prevalence and patterns of cognitive impairment were studied in older people from Nigeria. Method: Four hundred and forty one participants (263 females; age: 60-87) were recruited from community dwelling adults in Anambra state Nigeria. Five domains of cognition were tested using the Uniform Data Set Version 3 (UDS-3). Result: Prevalence: 49.7% were classified as normal cognition, 34% as borderline, 12.9% as MCI (2.72% with amnesic MCI) and 3.4% as dementia. We showed in descending order in that 13% of the participants were impaired on visual-spatial index; 6.8% on memory index; 5.2% on attention/concentration index; 2.7% were impaired on executive function index and 34.80% (based on mean) of the participants were impaired on processing speed index. There were significant interaction effects for gender and education on visual spatial and attention domains respectively. Significant effects of education were seen on executive function and processing speed while interaction effect was found on executive function alone. 8% scored 1.5 SD below the mean on MoCA. There was a significant effect of education on MoCA with the pairwise comparison showing a significant difference between tertiary education and other two levels of education. The groups did differ significantly for hypertension on MoCA. Conclusion: This study showed a high prevalence of cognitive impairment among older adult population from Nigeria. A significant proportion of the sample were impaired on the visual spatial domain and at least half of the participants were impaired on one cognitive domain. Hypertensive participants performed significantly poor on MoCA compared to non-hypertensive group.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".