Changes in insulin resistance indicators, IGFs, and adipokines in a year-long trial of aerobic exercise in postmenopausal women
Bibliographic record
Abstract
Physical activity is a known modifiable lifestyle means for reducing postmenopausal breast cancer risk, but the biologic mechanisms are not well understood. Metabolic factors may be involved. In this study, we aimed to determine the effects of exercise on insulin resistance (IR) indicators, IGF1, and adipokines in postmenopausal women. The Alberta Physical Activity and Breast Cancer Prevention Trial was a two-armed randomized controlled trial in postmenopausal, inactive, cancer-free women. A year-long aerobic exercise intervention of 225 min/week (n=160) was compared with a control group asked to maintain usual activity levels (n=160). Baseline, 6- and 12-month serum levels of insulin, glucose, IGF1, IGF-binding protein 3 (IGFBP3), adiponectin, and leptin were assayed, and after data collection, homeostasis model assessment of IR (HOMA-IR) scores were calculated. Intention-to-treat analyses were performed using linear mixed models. The treatment effect ratio (TER) of exercisers to controls was calculated. Data were available on 308 (96.3%) women at 6 months and 310 (96.9%) women at 12 months. Across the study period, statistically significant reductions in insulin (TER=0.87, 95% confidence interval (95% CI)=0.81-0.93), HOMA-IR (TER=0.86, 95% CI=0.80-0.93), and leptin (TER=0.82, 95% CI=0.78-0.87), and an increase in the adiponectin/leptin ratio (TER=1.21, 95% CI=1.13-1.28) were observed in the exercise group compared with the control group. No significant differences were observed for glucose, IGF1, IGFBP3, adiponectin or the IGF1/IGFBP3 ratio. Previously inactive postmenopausal women who engaged in a moderate-to-vigorous intensity exercise program experienced changes in insulin, HOMA-IR, leptin, and adiponectin/leptin that might decrease the risk for postmenopausal breast cancer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".