Cross‐cultural issues in AD risk factors and assessment: A Nigerian perspective
Bibliographic record
Abstract
Abstract Background Roles of demographics, anthropometry and metabolic syndrome (Mets) on cognition in mid adults from rural part of Nigeria were examined to determine their contribution to dementia. Method One hundred and seventy two (172) middle aged adults from a rural community in Anambra state Nigeria were recruited for the study. Their age range were between 50 – 70 years with a mean age of 57.48 and SD age of 5.48. The Montreal Cognitive Assessment (MoCA) Symbol Digit Modality Test (SDMT) and Digit Symbol Test (DST) were used to assess the participants’ cognition. The anthropometric measures assessed were the body mass index (BMI), height, weight and waist circumference while the Mets assessed were blood sugar level and total cholesterol and blood pressure. Gender, occupation and education were included as demographic factors assessed in the study. Result Findings show the BMI, weight and waist circumference as predictors of general cognition, but the blood pressure and height were not significant predictors. Equally, mixed findings were got on processing speed. The variables measured were not significant predictors of SDMT as a measure of processing speed while they to significant extent predicted processing speed when DST was used. Conclusion Contrary to findings from western world blood pressure as a cardiovascular marker did not predict general cognition and processing speed while mets had significant contribution on general cognition and processing speed.
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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 | 0.003 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".