Determinants of a decline in a nutrition risk measure differ by baseline high nutrition risk status: targeting nutrition risk screening for frailty prevention in the Canadian Longitudinal Study on Aging (CLSA)
Bibliographic record
Abstract
OBJECTIVES: Nutrition risk is a key component of frailty and screening, and treatment of nutrition risk is part of frailty management. This study identified the determinants of a 3-year decline in nutrition risk (measured by SCREEN-8) for older adults stratified by risk status at baseline. METHODS: Secondary data analysis of the comprehensive cohort sample of the Canadian Longitudinal Study on Aging (CLSA) (n = 5031) with complete data for covariates at baseline and 3-year follow-up. Using a conceptual model to define covariates, determinants of a change in nutrition risk score as measured by SCREEN-8 (lower score indicates greater risk) were identified for those not at risk at baseline and those at high risk at baseline using multivariable regression. RESULTS: Models stratified by baseline nutrition risk were significant. Notable factors associated with a decrease in SCREEN-8 for those not at risk at baseline were mental health diagnoses (- 0.83; CI [- 1.44, -0.22]), living alone at follow-up (- 1.98; CI [- 3.40, -0.56]), and lack of dental care at both timepoints (- 0.91; CI [- 1.62, -0.20]) and at follow-up only (- 1.32; CI [- 2.45, -0.19]). For those at high nutrition risk at baseline, decline in activities of daily living (- 2.56; CI [- 4.36, -0.77]) and low chair-rise scores (- 1.98; CI [- 3.33, - 0.63]) were associated with lower SCREEN-8 scores at follow-up. CONCLUSION: Determinants of change in SCREEN-8 scores are different for those with no risk and those who are already at high risk, suggesting targeted approaches are needed for screening and treatment of nutrition risk in primary care.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".