Why Are Individuals With Diabetes Less Active? The Mediating Role of Physical, Emotional, and Cognitive Factors
Bibliographic record
Abstract
BACKGROUND: Despite the key role of physical activity in the management of diabetes, many individuals with diabetes do not engage in the recommended levels of physical activity. However, our knowledge of the mechanisms underlying the relationship between diabetes and physical inactivity is limited. PURPOSE: To investigate the associations between diabetes and the levels and evolution of physical activity across aging, and to determine whether physical, emotional, and cognitive factors mediate these associations. METHODS: Data from 105,622 adults aged 50-96 years from the Survey of Health, Ageing and Retirement in Europe (SHARE) were used in adjusted linear mixed models to examine whether diabetes was associated with physical activity levels and variations across aging. The potential mediators were subjective energy, muscle strength, physical and cognitive disability, sleep problems, depressive symptoms, and cognitive functions. The variables were measured up to seven times over a 13-year period. RESULTS: Individuals with diabetes demonstrated a lower level and a steeper decrease in physical activity across aging than individual without diabetes. Mediators explained ~53% and 94% of the association of diabetes with the level of physical activity and with the linear evolution of physical activity across aging, respectively. All mediators were significantly associated with physical activity. Physical and cognitive disability as well as depressive symptoms were the strongest mediators, while sleep was the lowest one. CONCLUSIONS: These findings suggest that the etiology of physical inactivity in individuals with diabetes can result from several physical, emotional, and cognitive changes associated with the emergence of this disease.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".