Associations between abdominal adiposity, exercise, morbidity, and mortality
Bibliographic record
Abstract
The increasing prevalence of abdominal obesity worldwide poses a serious public health problem and thus presents a target for research designed to improve the assessment or treatment of abdominal obesity. Specifically, the first study in this thesis investigated the influence of age and gender on visceral (VAT) and abdominal (ASAT) subcutaneous adipose tissue for a given waist circumference (WC) in 481 men and women varying widely in age and body mass index (BMI). Significant gender differences in VAT and ASAT for a given WC were observed; however, only the relationship between WC and VAT was substantially influenced by age. The second study examined whether the associations between VAT, ASAT, and the metabolic syndrome (MetS) were altered depending on the measurement methodology used to assess VAT and ASAT. The odds ratio (OR) for MetS was higher for total VAT volume (OR = 7.26), and for partial volumes at T12–L1 (OR = 7.46) and L1–L2 (OR = 8.77) compared with the classic L4–L5 (OR = 3.94) measurement. The OR for MetS was not substantially different among the ASAT measures (OR∼2.6). Measurement site for VAT, but not ASAT, has a substantial influence on the magnitude of the association with MetS. The third study examined the independent associations between VAT, ASAT, liver fat, and all-cause mortality in 291 men (97 decedents and 194 controls, mortality follow-up of 2.2 ± 1.3 y). In a model including VAT, ASAT, liver fat, age, and length of follow-up, only VAT (1.93 (1.15–3.23)) remained a significant predictor of mortality. We concluded that VAT is a strong, independent predictor of all-cause mortality in men. The purpose of the final study was to determine the effect of aerobic exercise dose (energy expenditure) on WC in sedentary, overweight or obese postmenopausal women (n = 424). The women were randomly assigned to a control group or one of three aerobic exercise groups that exercised at energy expenditures of 4, 8, or 12 kcal·kg body mass–1·week–1. On comparison with controls, there were significant reductions in WC in the exercise groups (~3 cm, p < 0.05), which were independent of weight loss. However, the amount of exercise performed was not associated with reductions in WC in a dose-dependent manner.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".