Prevalence of Mild Cognitive Impairment Among Older People in Kazakhstan and Potential Risk Factors
Bibliographic record
Abstract
BACKGROUND: There have been no epidemiological studies of mild cognitive impairment (MCI) in Central Asia. OBJECTIVE: The objective of this study was to describe the prevalence of, and risk factors for, MCI in an urban population in Kazakhstan. METHODS: Adults aged 60 years and over were randomly selected from registers of 15 polyclinics in Almaty. Of 790 eligible people, 668 agreed to participate (response rate 85%). Subjects were screened using the Montreal Cognitive Assessment (MoCA). Those who scored 26 or lower on the MoCA were assessed by a multidisciplinary team and a diagnosis of normal cognition, MCI or dementia was made. RESULTS: The median MoCA score was 22 and the prevalence of MCI was 30%. MoCA scores were lower, and MCI prevalence was higher, among those with less education and those with older age. There was no difference in MoCA scores or MCI prevalence by sex or ethnic group (Kazakh or Russian). High blood pressure, older age, and lower education were associated with increased odds of MCI in crude analyses but only age and education remained statistically significant in an adjusted logistic regression model. CONCLUSIONS: The prevalence of MCI in Kazakhstan is high. Higher levels of education may lead to lower prevalence of MCI in the future.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 teacher head, 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".