Dose–Response Associations of Grip Strength and Gait Speed With Multidimensional Mental Health
Bibliographic record
Abstract
ABSTRACT Objectives We aimed to examine the dose–response associations of grip strength and gait speed with multidimensional mental health among Chinese adults. Methods Cross‐sectional data on 661 adults from the ZheJiang longitudinal Study of Healthy Aging (JASHA) were utilized. Grip strength and gait speed were measured during physical examinations. Multidimensional mental health, covering cognitive function (the Auditory Verbal Learning Test (AVLT), the Montreal Cognitive Assessment (MoCA) test, and the Digit Symbol Substitution Test (DSST)), depressive symptoms (the Center for Epidemiologic Studies Depression (CES‐D) Scale), and psychological distress (the Perceived Stress Scale (PSS)), were assessed via standard questionnaires. Multivariable linear regression models and restricted cubic splines were applied to examine these associations. Results We found linear dose–response associations of grip strength and gait speed with most dimensions of mental health. For instance, higher grip strength was positively associated with higher cognitive function scores (AVLT_N3: β = 0.084, standard error (SE) = 0.032; DSST: β = 0.246, SE = 0.073 for per unit increase in grip strength) and lower CES‐D scores ( β = −1.265, SE = 0.626). Similarly, higher gait speed was associated with higher cognitive function scores (AVLT_N3: β = 2.882, SE = 0.860; MoCA: β = 0.996, SE = 0.499 for per unit increase in gait speed), lower CES‐D scores ( β = −1.448, SE = 0.692), and lower PSS scores ( β = −2.808, SE = 0.938). Notably, the associations were more pronounced in females and older adults. Conclusions In this sample spanning a wide range of ages, we found linear significant associations of grip strength and gait speed with most dimensions of mental health. The finding unveils the intrinsic connections between musculoskeletal function and mental health, highlighting the potential of preserving musculoskeletal function, such as via maintaining regular physical exercise, to prevent mental health disorders, especially for females and older adults.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".