Race and Sex Similarities in Exercise-Induced Changes in Blood Lipids and Fatness
Bibliographic record
Abstract
PURPOSE: This study explores sex and race differences in the association between changes in fat mass (FM), abdominal visceral fat (AVF), and abdominal subcutaneous fat (ASF) on blood lipid changes consequent to aerobic exercise training. METHODS: The sample included 613 participants (428 white and 185 black, 46% men) from the HERITAGE Family Study. Total FM was determined by densitometry, whereas AVF and ASF cross-sectional areas were determined by computed tomography at the L4-L5 level. Blood lipid measurements included total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), and the TC/HDL-C ratio, which were obtained before and after 20 wk of supervised aerobic exercise. Canonical correlation was used to determine the multivariate associations between body fatness and blood lipids at baseline and the changes induced by exercise training. RESULTS: Body fat accounted for 26-36% of the variance in baseline blood lipids, and changes in body fat accounted for 7-21% of the variance in changes in blood lipids with exercise training. The pattern of loadings indicated similar relationships between body fatness and blood lipids at baseline, and their respective changes with exercise training among the four sex-by-race groups. Greater fat loss, characterized by loss of FM, AVF, and ASF, was associated with a greater blood lipid response characterized by an increase in HDL-C and decreases in LDL-C, TG, TC, and TC/HDL-C. Although the pattern of loadings was similar in all groups, the strength of the association was stronger in blacks than in whites. CONCLUSION: The multivariate associations among fat loss and changes in blood lipids consequent to aerobic exercise training are similar in black and white men and women.
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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 | 0.000 | 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) | 0.003 | 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".