The effects of physical activity on adipokines in individuals with overweight/obesity across the lifespan: A narrative review
Bibliographic record
Abstract
This narrative review summarizes current knowledge on the effects of physical activity (PA) on adipokine levels in individuals with overweight and obesity. Approximately 90 investigations including randomized control, cross-sectional and longitudinal studies that reported on the effects of a single session of PA (acute) or long-term PA (chronic) on adipokine levels in individuals with overweight/obesity were reviewed. The findings support the notion that there is consensus on the benefits of chronic exercise training-regardless of the mode (resistance vs. aerobic), intensity and cohort (healthy vs. diabetes)-on adipokine levels (such as tumour necrosis factor-alpha, interleukin-6, adiponectin, visfatin, omentin-1 and leptin). However, several confounding factors (frequency, intensity, time and type of exercise) can alter the magnitude of the effects of an acute exercise session. Available evidence suggests that PA, as a part of routine lifestyle behaviour, improves obesity complications by modulating adipokine levels. However, additional research is needed to help identify the most effective interventions to elicit the most beneficial changes in adipokine levels in individuals with overweight/obesity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".