Non-linear Associations Between Visceral Adipose Tissue Distribution and Anthropometry-Based Estimates of Visceral Adiposity
Bibliographic record
Abstract
Background: Recent evidence suggests that excess visceral adipose tissue (VAT) is associated with future loss of subcutaneous adipose tissue (SAT) and skeletal muscle (SM) with aging. In clinical settings (abdominal) circumferences are commonly used to estimate body composition (BC). We aimed to study the linearity of VAT distribution ratios (i.e., VAT/SAT ratio and VAT/SM ratio), waist-to-hip ratio (WHR) and waist circumference (WC) with age and the relationship of VAT distribution ratios with anthropometry (i.e., WHR and WC). Materials and Methods: . Linear and non-linear regression analysis was used to examine the linearity of VAT distribution ratios and anthropometry from 18 to 88 years. The relation between VAT distribution ratios and anthropometry was assessed separately. Results: In both sexes non-linear relationships were found between BC estimates and age, and between BC measures mutually. The ratios of VAT/SAT and VAT/SM showed quadratic relationships with age. VAT distribution ratios showed exponential or quadratic relationships with anthropometry with coefficients of determination ranging between 18 and 55%. Conclusion: In both sexes, VAT distribution ratios showed curvilinear relationships with age and with anthropometry. Given the sex differences in VAT distribution ratios, WHR and WC represent different BC proportions in men and women. These results emphasize the challenge when interpreting changes in BC based upon linear extrapolations in clinical practice.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".