Is dynapenia associated with the onset and persistence of depressive and anxiety symptoms among older adults? Findings from the Irish longitudinal study on ageing
Bibliographic record
Abstract
OBJECTIVES: The aim of the current study was to assess the associations between dynapenia and the onset and persistence of depression and anxiety among older adults. METHODS: = 5271; 51.1% females) aged ≥ 50 years (mean age = 63.2, standard deviation = 9.0) from The Irish Longitudinal Study on Aging (TILDA), Ireland. At baseline, participants completed a handgrip assessment. Depression was defined by a score ≥ 16 in the Center of Epidemiology Studies Depression (CES-D) tool and anxiety was considered when participants scored ≥ 8 on the anxiety section of the Hospital Anxiety and Depression Scale (HADS). Outcomes were incident and persistent depression and anxiety at two years follow-up. Multivariable logistic regression models were built for each outcome. RESULTS: After controlling for age, sex, education, marital status, employment status, smoking, body mass index, number of chronic conditions, physical activity, and cognitive function, low handgrip strength indicative of dyapenia (< 30 Kg for men and < 20 Kg for women) was associated with a greater likelihood for incident depressive (OR = 1.44; 95%CI: 1.08-1.92) as well as for persistent depressive (OR = 1.61; 95% CI: 1.01-2.58) and anxiety (OR = 1.61; 95% CI: 1.20-2.14) symptoms. CONCLUSIONS: Dynapenia was associated with a higher odds of developing depressive symptoms as well as a greater likelihood to persistent depressive and anxiety symptoms among older adults. Our data suggest that interventions targeting muscle strength may prevent the onset of late-life depression and also may hold promise as novel therapeutic opportunities for depression and anxiety in later life.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".