Lifestyle Factors and 5‐Year Abdominal Fat Accumulation in a Minority Cohort: The IRAS Family Study
Bibliographic record
Abstract
The objective of this study was to examine whether lifestyle factors were associated with 5-year change in abdominal fat measured by computed tomography (CT) in the Insulin Resistance and Atherosclerosis (IRAS) Family Study. We obtained abdominal CT scans at baseline and at 5 years, from African Americans (AA) (N = 339) and Hispanic Americans (N = 775), aged 18-81 years. Visceral (VAT) and subcutaneous (SAT) adipose tissue was measured at the L4/L5 vertebral level. Physical activity was documented by self-report of vigorous activity and a 1-year recall instrument. Dietary intake was assessed at follow-up using a semi-quantitative food frequency questionnaire referencing the previous year. Generalized linear models, accounting for family structure, were used to assess the associations between percent change in fat accumulation and smoking, physical activity, total calories, polyunsaturated, monounsaturated, protein, and saturated fat intake, percent of calories from sweets, and soluble and insoluble fiber. Soluble fiber intake and participation in vigorous activity were inversely related to change in VAT, independent of change in BMI. For each 10 g increase in soluble fiber, rate of VAT accumulation decreased by 3.7% (P = 0.01). Soluble fiber was not associated with change in SAT (0.2%, P = 0.82). Moderately active participants had a 7.4% decrease in rate of VAT accumulation and a 3.6% decrease in rate of SAT accumulation versus less active participants (P = 0.003 and P = 0.01, respectively). Total energy expenditure was also inversely associated with accumulation of VAT. Soluble fiber intake and increased physical activity were related to decreased VAT accumulation over 5 years.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".