CT-derived abdominal adiposity: Distributions and better predictive ability than BMI in a nationwide study of 59,429 adults in China
Bibliographic record
Abstract
Background Although abdominal adiposity is associated with an altered cardiometabolic risk profile, the specific contribution of abdominal adipose tissue distribution remains not fully understood. Computed tomography (CT) is a well-established and precise method to measure abdominal adipose tissue distribution. The present study investigated abdominal adiposity assessed by CT in a large-scale Chinese population. Method A total of 59,429 adults who underwent a low dose chest CT for lung cancer screening at one of 13 health checkup centers throughout China were evaluated. Abdominal visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) areas were measured at the center of the 2nd lumbar vertebra with Mindways quantitative CT software using the existing CT dataset without any additional radiation exposure. The ratio of visceral to total adipose tissue (TAT) areas (VAT/TAT ratio) was calculated and expressed as a percentage. Anthropometric indices including body mass index (BMI) and waist circumference were also obtained. Results BMI, waist circumference, VAT area, SAT area, and the VAT/TAT ratio were 25.0 ± 3.0 kg/m 2 , 90 ± 8 cm, 194 ± 77 cm 2 , 85 ± 41 cm 2 , and 69.5 ± 9.1%, respectively, in men and 23.3 ± 3.1 kg/m 2 , 79 ± 8 cm, 120 ± 57 cm 2 , 123 ± 53 cm 2 , and 48.9 ± 9.7% in women. With increasing age, VAT area and the VAT/TAT ratio increased in both sexes whereas SAT area decreased in men (P < 0.001 for all). After adjustment for BMI and waist circumference, older individuals showed higher VAT area and higher VAT/TAT ratio than younger subjects (P < 0.001 for all). Adjusted VAT areas in participants aged 75 or older was 45 cm 2 (95% confidence interval [CI]: 41 cm 2 , 50 cm 2 ) higher in men and 43 cm 2 (95% CI: 37 cm 2 , 49 cm 2 ) higher in women compared with participants aged 31–44 years. Additionally, differences in VAT area across age groups increased as BMI or waist circumference increased. VAT and SAT areas, but not the VAT/TAT ratio, were positively associated with BMI and waist circumference in every age group. Conclusion In a nationwide study conducted in China, distributions of CT-derived measures of visceral and subcutaneous adiposity were found to vary significantly between sex and age groups. Our study also revealed that the proportion of VAT (an important driver of cardiometabolic risk) could not be predicted from BMI in a Chinese population.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".