Effects of Aerobic Exercise Training on Estrogen Metabolism in Premenopausal Women: A Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Regular physical activity may alter estrogen metabolism, a proposed biomarker of breast cancer risk, by shifting metabolism to favor production of 2-hydroxyestrone (2-OHE1). Few studies, however, have examined this question using a randomized controlled trial. PURPOSE: To examine the effects of 12 weeks of aerobic exercise training on 2-OHE1 and 16alpha-hydroxyestrone (16alpha-OHE1) in premenopausal women. METHODS: Participants were healthy, regularly menstruating, Caucasian women, 20 to 35 years, body mass index of 18 to 29.9, not using pharmacologic contraceptives, with average or below average fitness [maximal oxygen consumption (VO(2max)), <40 mL/kg/min]. Following a baseline menstrual cycle, participants (N = 32) were randomly assigned to a 12-week aerobic exercise training intervention (n = 17) or usual lifestyle (n = 15). Height, body mass, body composition by dual-energy X-ray absorptiometry, and VO(2max) were measured at baseline and following the intervention. Urine samples were collected in the luteal phase of four consecutive menstrual cycles. RESULTS: The exercise group increased VO(2max) by 14% and had significant, although modest, improvements in fat and lean body mass. No significant between-group differences were observed, however, for the changes in 2-OHE1 (P = 0.944), 16alpha-OHE1 (P = 0.411), or the ratio of 2-OHE1 to 16alpha-OHE1 (P = 0.317). At baseline, there was an inverse association between body fat and 2-OHE1 to 16alpha-OHE1 ratio (r = -0.40; P = 0.044); however, it was the change in lean body mass over the intervention that was positively associated with a change in 2-OHE1 to 16alpha-OHE1 ratio (r = 0.43; P = 0.015). CONCLUSIONS: A 12-week aerobic exercise training intervention significantly improved aerobic fitness and body composition but did not alter estrogen metabolism in premenopausal women. Interestingly, an increase in lean body mass was associated with a favorable change in 2-OHE1 to 16alpha-OHE1 ratio.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".