Familial Aggregation of Amount and Distribution of Subcutaneous Fat and Their Responses to Exercise Training in the HERITAGE Family Study
Bibliographic record
Abstract
OBJECTIVE: Investigate the familial aggregation of amount and distribution of subcutaneous fat and their changes in response to endurance training. RESEARCH METHODS AND PROCEDURES: A total of 483 sedentary subjects from 99 nuclear families were recruited, trained for 20 weeks of exercising on cycle ergometers, and measured before and after training for the following indicators of subcutaneous fat and fat distribution: trunk fat (TRUNK = sum of abdominal, subscapular, suprailiac, and midaxillary skinfolds), extremity fat (EXTREM = sum of biceps, triceps, thigh, and calf skinfolds), subcutaneous fat (SF8 = sum of the eight skinfolds), the trunk to extremity skinfolds ratio adjusted for SF8 (TER) and waist girth adjusted for body mass index (WAIST). The familial aggregation of the age- and sex-adjusted baseline phenotypes and their responses to training (delta) after adjustment for the baseline values was investigated using a familial correlation model. RESULTS: Significant familial aggregation was observed for all the phenotypes measured at baseline and for deltaTRUNK and deltaWAIST. Transmissibility estimates reached about 30% to 35% for TRUNK, EXTREM, and SF8 and 50% for TER and WAIST. The transmissibilities of the response phenotypes were lower, ranging from 0% for deltaWAIST to 21% for deltaTRUNK and the pattern of familial correlations suggested a greater within- than between-generation resemblance in the response. DISCUSSION: This study suggests that the amount and distribution of subcutaneous fat strongly aggregates in families, whereas the response to exercise training is characterized by a moderate and more complex pattern of familial resemblance. We conclude that familial/genetic factors are more important in determining the amount and distribution of subcutaneous fat than their responses to exercise training.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".