Acute Glucose Tolerance in Response to Lower- and Higher-Load Resistance Exercise in Postmenopausal Women: Contribution of Aerobic Capacity and Body Composition
Bibliographic record
Abstract
ABSTRACT: Paquin, J, St-Martin, P, Lord, S-E, Gendron, P, Brochu, M, and Dionne, IJ. Acute glucose tolerance in response to lower- and higher-load resistance exercise in postmenopausal women: Contribution of aerobic capacity and body composition. J Strength Cond Res 39(6): e749-e757, 2025-Glucose tolerance (GT), fat-free mass (FFM), and V̇o2peak are known to decline after menopause. Exercise recommendations advise ageing adults to perform heavy weights and low repetitions (HWLR) resistance exercise (RE). However, the most efficient RE parameters to improve acute GT in postmenopausal women (PMW) are unclear. Our aim was to determine how acute GT is influenced by 2 RE sessions of different loads (HWLR vs. low-weight and higher repetitions, LWHR), compared with a control condition, and examine potential contributors. After measuring baseline oral glucose tolerance (OGTT), FFM (DXA), and V̇o2peak (metabolic cart), 12 PMW underwent additional OGTTs (area under the curve-AUC; 2-h glucose) after 3 randomized experimental conditions (control, HWLR, and LWHR). Session volume was defined as the total weight lifted. The Cederholm's index was calculated to derive insulin sensitivity. There was a significant effect of RE on glucose AUC (1,109 ± 234 vs. 954 ± 149 and 974 ± 194 mmol/L × 120 minutes for control, HWLR, and LWHR; p < 0.005) and 2-h glucose (8.8 ± 2.5 vs. 7.0 ± 1.6 and 7.4 ± 2.0 mmol/L for control, HWLR, and LWHR; p < 0.04) with no difference between HWLR and LWHR. A greater volume was achieved with LWHR (4,292.1 ± 1,143.4 vs. 3,888.1 ± 1,042.1 kg, p < 0.05), although it was not significantly associated with post-RE GT. Fat-free mass was significantly associated with Cederholm's index at baseline only (r = 0.6, p < 0.05). Significant correlations were also found between V̇o2peak and glucose AUC for all conditions (all r ≤ -0.6 to 0.8; p < 0.05). We conclude that HWLR and LWHR both acutely improve GT in PMW, whereas V̇o2peak may be a stronger contributor than FFM.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".