Effect of a 24-Week Concurrent Exercise Intervention on Neck Adiposity and Its Distribution in Young Adults: The ACTIBATE Randomized Controlled Trial
Bibliographic record
Abstract
Neck adipose tissue (NAT) accumulation and neck circumference are independent predictors of cardiometabolic risk (CMR) and low-grade chronic inflammation in young adults. The present study examines whether a 24-week concurrent exercise intervention can reduce NAT volume and neck circumference in young adults, and whether any changes in these variables are related to changes in body composition, CMR, and the inflammatory profile. Seventy-four participants (51 women, age 22 ± 2 years) were included in the main analyses, after being randomly assigned to either a (a) control (n = 34), (b) moderate-intensity exercise (n = 19), or (c) vigorous-intensity exercise (n = 21) group. Participants in the exercise groups trained 3-4 days/week (endurance + resistance exercise training). NAT volume and NAT distribution across different depots were estimated using computed tomography before and after the intervention. Anthropometric variables, body composition (determined by dual-energy X-ray absorptiometry), and CMR/inflammatory markers were also recorded. The exercise intervention did not reduce the total NAT volume, nor was NAT distribution affected (p > .05). However, it did reduce neck circumference in the vigorous-intensity exercise group compared with the moderate-intensity exercise and control groups (by 0.8 and 1 cm, respectively, p ≤ .05). Changes in total NAT and neck circumference were positively, albeit weakly, related (adj. R2: .05-.21, all p ≤ .05) to changes in body weight and adiposity, leptin (only total NAT), and CMR (only neck circumference). Altogether 24 weeks of concurrent exercise does not appear to reduce NAT accumulation in young adults, but may slightly reduce neck circumference in those who partake in vigorous exercise.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".