Arthritis is associated with high nutritional risk among older Canadian adults from the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
This study assessed the association between arthritis, functional impairment, and nutritional risk (NR). Cross-sectional data were from the Canadian Longitudinal Study on Aging, a nationally representative sample of 45-85-year-old community-dwelling Canadians (n = 41,153). The abbreviated Seniors in the Community: Risk Evaluating for Eating and Nutrition II (SCREEN II-AB) Questionnaire determined NR scores (continuous), and high NR (score < 38); the Older American Resources and Services scale measured functional impairment. NR scores and status (low/high) were modelled using multiple linear and logistic regressions, respectively. Analyses adjusted for demographic characteristics, functional impairment, and health (body mass index, self-rated general and mental health). Additional analyses stratified the models by functional impairment. People with arthritis had poorer NR scores (B: - 0.35, CI - 0.48, - 0.22; p < 0.05) and increased risks of high NR (OR 1.11, 95% CI 1.06, 1.17). Among those with functional impairment, the likelihood of high NR was 31% higher in people with arthritis compared to those without arthritis (95% CI 1.12, 1.53). Among those with no functional impairment, the likelihood of high NR was 10% higher in people with arthritis compared to those without (95% CI 1.04, 1.16). These relationships differed based on the type of arthritis. Arthritis is associated with high NR in community-dwelling older adults, both with and without functional impairment. Findings highlight the need for further research on these relationships to inform interventions and improve clinical practices.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 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) | 0.002 | 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".