Role of visceral adiposity in the relationship between cardiorespiratory fitness and liver fat in asymptomatic adults
Bibliographic record
Abstract
Excess liver fat (LF) is associated with low cardiorespiratory fitness (CRF), low physical activity, and a deteriorated cardiometabolic health profile including increased visceral adipose tissue (VAT). Whether the association between LF and CRF is mediated by visceral adiposity is unknown. We studied the contribution of VAT to the relationship between CRF and LF in asymptomatic women and men. The sample included 320 participants (43% women) who underwent LF quantification by magnetic resonance spectroscopy. VAT was measured by magnetic resonance imaging, CRF using maximal cardiorespiratory exercise testing, and moderate-to-vigorous intensity physical activity (MVPA) using a 3-day journal. Mean age was 50.3 ± 8.6 years, waist circumference was 89.3 ± 11.4 cm, and LF content was 4.3 ± 5.7%. LF was inversely correlated with CRF ( p < 0.0001), MVPA ( p < 0.05) and cardiometabolic health score ( p < 0.0001), and positively related with VAT ( p < 0.0001) in both sexes. Significantly higher levels of VAT ( p < 0.0001) and subcutaneous adipose tissue ( p < 0.0001) and a worsening cardiometabolic health score ( p < 0.05) and CRF ( p = 0.0001) were found across increasing sex-specific tertiles of LF levels. Lower levels of LF ( p < 0.01) and VAT ( p < 0.0001) and a higher cardiometabolic health score ( p < 0.0001) and MVPA ( p < 0.05) were noted across increasing sex-specific CRF tertiles. Multivariable regression analyses showed that visceral adiposity explained the majority of the variance in LF in both sexes ( p < 0.0001). Finally, serial mediation analyses revealed that VAT but not body fat percentage was a mediator in the relationship between CRF and LF in both sexes. Thus, visceral adiposity appears to be an important mediator in the relationship between CRF and LF, even after controlling for total adiposity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".