Incidental Physical Activity and Sedentary Behavior Are Not Associated With Abdominal Adipose Tissue in Inactive Adults
Bibliographic record
Abstract
The aim was to determine the association between objectively measured incidental physical activity (IPA) (i.e.,nonpurposeful activity accrued through activities of daily living) and sedentary behavior (SED) with abdominal obesity in a sample of inactive men and women. Participants were inactive, abdominally obese men (n = 42; waist circumference (WC) ≥102 cm) and women (n = 84; WC ≥88 cm) recruited from Kingston, Canada. Physical activity and SED were determined by accelerometry over 7 days and summarized as IPA (accelerometer counts per min (cpm) >100), light physical activity (LPA; cpm 100-1951), sporadic moderate-to-vigorous physical activity (MVPA; cpm ≥1,952, accumulated in bouts <10 consecutive minutes) and SED (cpm <100). Magnetic resonance imaging was used to acquire measures of abdominal obesity, visceral adipose tissue (VAT), and subcutaneous adipose tissue (ASAT). Participants spent on average 310.2 ± 102.6 min/d in IPA and 627.8 ± 86.9 min/d in SED. Neither IPA nor SED was associated with any measure of abdominal obesity (P > 0.1). Similarly, LPA was not a significant predictor of abdominal obesity whereas sporadic MVPA was negatively associated with VAT (P < 0.05) after control for age and sex. In this study, neither IPA nor SED was associated with abdominal obesity among inactive men and women.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".