Physical activity, cardiorespiratory fitness, and metabolic syndrome in young Mexican and Mexican-American women
Bibliographic record
Abstract
Young adult women have had the greatest increase in prevalence of metabolic syndrome (MetS) over time, and prevalence is highest in Hispanic women, compared with women of other ethnicities. Factors contributing to the high prevalence of MetS in Hispanic women are unknown. This study was conducted to determine if physical activity or fitness were associated with individual features of MetS in young Mexican and Mexican-American women, and if the associations were independent of fat mass. Sixty young Mexican and Mexican-American women participated in the study. MetS was defined according to the Adult Treatment Panel III. A fasting blood sample was drawn for the measurement of glucose, insulin, high-density lipoprotein cholesterol (HDL-c), and triglycerides. Physical activity was assessed by questionnaire and accelerometer. Fitness was assessed by progressive treadmill test to exhaustion and ventilatory threshold. Body composition was assessed with Bod Pod. Multivariate regression was used to establish the independent contributions of physical activity and fitness to the individual features of MetS. After controlling for fat mass and fat-free mass, physical activity was found to be independently related to HDL-c and fitness was found to be independently related to triglycerides (p < 0.05). The independent associations between physical activity, fitness, and features of MetS were mediated by, rather than independent of, fat mass. Fat mass was independently related to triglycerides, systolic blood pressure, and diastolic blood pressure. Although physical activity and fitness were related to features of MetS, these associations were not independent of fat mass.
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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) | 0.000 | 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 | 0.000 |
| 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".