Insulin Resistance, Low Cardiorespiratory Fitness, and Increased Exercise Blood Pressure
Bibliographic record
Abstract
Individuals with insulin resistance and low cardiorespiratory fitness are frequently found to have an increased waist circumference and high exercise blood pressure. We tested the hypothesis that the relationships among insulin resistance, low cardiorespiratory fitness, and increased exercise blood pressure may be mediated by an elevated waist circumference. This study included 317 apparently healthy men and women (mean age: 34.8±12.8 years; mean body mass index: 26.1±5.2 kg/m(2)). Exercise blood pressure values were measured using a submaximal ergometer test evaluating physical working capacity. Plasma insulin and glucose levels were measured during a 3-hour oral glucose tolerance test. Multivariate regression analyses showed that waist circumference accounted for 32.8% (P<0.0001) and 45.1% (P<0.0001) of the variance in exercise systolic blood pressure in men and women, respectively. Participants were classified into tertiles according to either insulin response, measured during the oral glucose tolerance test, or fitness levels and then further subdivided into 2 subgroups using sex-specific waist circumference thresholds. Individuals with an increased waist circumference (≥94 cm and ≥80 cm for men and women, respectively) had higher exercise systolic blood pressure compared with individuals with low waist circumference, irrespective of their level of insulin resistance (10.6 versus 6.8, 12.2 versus 7.7, and 13.2 versus 8.7 mm Hg/metabolic equivalent, respectively, for the low, intermediate, and high tertiles; P<0.05) or fitness levels (13.1 versus 8.2, 12.0 versus 7.9, and 10.6 versus 7.1 mm Hg/metabolic equivalent, respectively, for the low, intermediate, and high tertiles; P<0.05). Individuals with a higher waist circumference have elevated exercise systolic blood pressure, regardless of their insulin sensitivity or level of cardiorespiratory fitness.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".