Visceral adiposity and liver fat as mediators of the association between cardiorespiratory fitness and plasma glucose-insulin homeostasis
Bibliographic record
Abstract
Cardiorespiratory fitness (CRF) is positively associated with insulin sensitivity, whereas excessive levels of visceral adipose tissue (AT) and liver fat (LF) are both associated with insulin resistance and impaired plasma glucose-insulin homeostasis. To what extent levels of visceral AT and LF content contribute to the relationship between CRF and indices of plasma glucose-insulin homeostasis is uncertain. Our objective was to explore the interactions among CRF, visceral AT, and LF with glucose tolerance/insulin levels in asymptomatic and apparently healthy individuals. CRF was measured in 135 women and 177 men with a maximal treadmill graded exercise test. Indices of plasma glucose-insulin homeostasis were derived from a 3-h oral glucose tolerance test (OGTT) performed in the morning after a 12-h fast. Visceral AT levels and LF content were measured using magnetic resonance imaging and spectroscopy. For any given CRF level, women presented significantly lower visceral AT and LF than men as well as lower homeostasis model assessment of insulin resistance (HOMA-IR) and plasma glucose-insulin levels during the OGTT compared with men. In both sexes, there were significant negative correlations between CRF and HOMA-IR as well as glucose and insulin levels measured during the OGTT. Both glucose and insulin levels during the OGTT correlated positively with visceral AT and LF. In women and men, being in the top CRF tertile was associated with low levels of visceral AT and LF. Multivariable linear regression analyses suggested that visceral AT and LF were plausible mediators of the association between CRF and indices of plasma glucose-insulin homeostasis.
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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) | 0.000 | 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".