Association of Nutritional Risk and Depressive Symptoms with Physical Performance in the Elderly: The Quebec Longitudinal Study of Nutrition as a Determinant of Successful Aging (NuAge)
Bibliographic record
Abstract
OBJECTIVE: Depressive symptoms and poor nutritional status have been associated with declines in physical capacity. However, it is not clear whether they exert independent effects and potential for interaction among these two variables has not been studied. The purpose of this report is to clarify the relationships between depressive symptoms and nutritional risk and physical capacity. METHODS: Baseline data from community-living and well functioning men and women (n = 1,755) participating in the longitudinal study NuAge (Quebec, Canada), aged 67-84 years were used for this study. Physical performance (PP) was defined as the summary score of 4 tests of physical capacity [Standing Balance, Walking Speed, Chair Stands, and Timed "Up &Go"]. Depressive symptoms were measured with the Geriatric Depression Scale (GDS), and nutritional risk by the Elderly Nutrition Screening (ENS(c)) tool. RESULTS: Prevalence of mild depression (GDS score >or=11 and <or= 20) was 12% in women and 7.6% in men (p = 0.002). Higher PP was observed among subjects without nutritional risk or mild depression (mean score: 10.45 +/- 3.45) as compared to those with both risk factors (8.66 +/- 3.59; p < 0.001). In multiple linear regression analysis, both depressive symptoms and nutritional risk scores were independently associated with PP score after adjustment for age, sex, educational level, income, burden of disease, body mass index and physical activity. There was no interaction of nutritional risk and depressive symptoms in relation to PP. The overall adjusted multiple regression model explained 34% of the observed variance in physical performance score. CONCLUSIONS: Nutritional risk and depressive symptoms are both potentially modifiable independent correlates of PP but there is no synergistic effect of the two risk factors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".