Double Burden of Mild Behavioural Impairment and Frailty – Implications for Quality of Life and Cognition in a Southeast Asian Cohort
Bibliographic record
Abstract
BACKGROUND: While the independent associations of Mild Behavioural Impairment (MBI) and frailty with Quality of Life (QoL) and cognitive outcomes have been independently studied, their combined effects remain less understood, particularly in Southeast Asian populations. METHOD: Cross-sectional analysis of 1,500 participants from the Biomarkers and Cognition Study, Singapore (BIOCIS), including cognitively normal, subjective cognitive decline, mild cognitive impairment and mild dementia. Behavioural symptoms were assessed using the Mild Behavioural Impairment Checklist (MBI-C), with a cut-off score ≥5.5 indicating significant symptoms (MBI+). Frailty was defined by the Fried Frailty Phenotype, with ≥1 criterion indicating frailty (Frail+). Quality of Life (QoL) was measured via the Dementia Quality of Life Questionnaire (DEMQoL), global cognition with the Montreal Cognitive Assessment (MoCA), and domain-specific cognition (episodic memory, executive function, language, processing speed, visuospatial) using aggregated z-scores from standardised tests. Multiple linear regression models examined the effects of MBI-C Total and domain scores, as well as frailty, on DEMQoL, controlling for age, gender, ethnicity, years of education, ApoE4 status, marital status, employment status, hypertension, hyperlipidaemia, diabetes, and cognitive status. Stepwise regression was used to explore combined effects of MBI-C domains and frailty. Participants were cross-classified into four MBI/frailty groups, and cognitive outcomes (MoCA and domain-specific z-scores) were compared using Analysis of Covariance (ANCOVA) with Tukey Post-Hoc tests. RESULT: Higher MBI-C Score correlated with poorer DEMQoL (β=-6.2; p <0.001). MBI-C-domains emotional dysregulation (β=-9.4; p <0.001), impulsivity (β=-7.0; p <0.001), and apathy (β=-8.6; p <0.001) were associated with poorer QoL than frailty (β=-2.2; p <0.001). Individuals with both MBI and Frailty demonstrated the poorest cognitive performance across all domains (p <0.001) except visuospatial (p <0.05). CONCLUSION: Emotional dysregulation, impulsivity, and apathy are associated with substantially poorer QoL. Co-occurrence of MBI and frailty are associated with a greater cognitive decline than either condition alone.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".