Impact of a moderate-intensity walking program on cardiometabolic risk markers in overweight to obese women
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to examine the effect of brisk walking on cardiometabolic risk profile and on the gene expression (ie, messenger RNA [mRNA] levels) of inflammatory and thrombotic markers in abdominal and femoral subcutaneous adipose tissues (SATs) among sedentary overweight to obese women with different menopause statuses. METHODS: Sixteen late premenopausal (mean [SD] age, 49 [3] y; mean [SD] body mass index, 31.9 [3.0] kg/m) and 14 early postmenopausal (53 [2] y; 30.8 [1.9] kg/m) women were involved in a 16-week walking program (three sessions of 45 min/wk at 60% of heart rate reserve). Glucose-insulin homeostasis, lipid-lipoprotein profile, and inflammatory (tumor necrosis factor-α, interleukin-6 [IL-6], and adiponectin) and thrombotic (plasminogen activator inhibitor-1) SAT mRNA and plasma levels were measured before and after the intervention. RESULTS: Glucose area under the curve was reduced in all participants (P = 0.03) after the walking program. Increases in plasma tumor necrosis factor-α were observed in both groups (P = 0.001), whereas increases in plasminogen activator inhibitor-1 levels were found in postmenopausal women only (P = 0.014). However, plasma IL-6 and adiponectin levels remained unchanged after the intervention (0.07 < P < 0.98). Although femoral SAT adiponectin mRNA levels decreased in postmenopausal women only (P = 0.008), abdominal SAT IL-6 mRNA levels were reduced in both groups (P = 0.01). CONCLUSIONS: Taken together, our results show that, despite a reduced abdominal SAT IL-6 expression, brisk walking does not seem to exert a favorable impact on the cardiometabolic risk profile of overweight to obese women, irrespective of their menopause status.
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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 | 0.000 |
| 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) | 0.001 | 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".