Multidimensional predictors of cognitive impairment among community-dwelling older adults in Klang Valley, Malaysia
Bibliographic record
Abstract
Cognitive decline and cognitive impairment among older adults is a rising public health concern. It is a costly condition that affects individuals, families and countries which often associated with increased risk of dementia, disability and mortality. Numerous risk factors associated with cognitive impairment have been identified but early identification of cognitive impairment is rare and little is known about the risk profile among Malaysians. There is lack of multidimensional risk model, which synthesizes information from known risk factors of cognitive impairment, particularly the modifiable lifestyle-related risk factors. This study was conducted to determine the risk factors and predictors of cognitive impairment from multidimensional approach, based on a representative sample of the community-dwelling older adult Malaysian population. This study was conducted through a cross-sectional household survey in the Klang Valley using multi-stage sampling. A total of 698 respondents aged 60 years old and above, living in community participated in the study. Multivariate logistic regression analysis was performed to determine the predictors of cognitive impairment. Age, being female, Malay or Indian, education, aerobic activity and physical function were the six predictors identified for cognitive impairment after controlling for other factors including socio-demographic, cardiovascular risk, lifestyle-related risks and psychosocial factors. While advancing age, being female, Malay or Indian were found as the risk factors for cognitive impairment, increasing years of education, aerobic activity and better physical function were associated with the reduced risk of cognitive impairment at p<0.05 level of significance. The predictors for cognitive impairment identified in the study provided a hierarchy of priorities for the development of policies, strategies, programmes and interventions. In view of that, it is crucial to identify individuals who are at higher risk of cognitive impairment and targeted them to encourage lifestyle changes by using life course approach to preserve cognitive function, prevent or delay the onset of cognitive impairment.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".