Leptin, vitamin D, and cardiorespiratory fitness as risk factors for insulin resistance in European adolescents: gender differences in the HELENA Study
Bibliographic record
Abstract
The purpose of this study was to identify the relevance of a set of risk factors for insulin resistance in adolescents from Europe and to consider their possible gender-specific associations. The Healthy Lifestyle in Europe by Nutrition in Adolescence Cross-Sectional Study (HELENA-CSS) was conducted in 1053 European adolescents (mean age, 14.9 years) in a school setting in 9 countries. Three anthropometric markers of body fat and a dietary index were calculated. Total energy intake was estimated from a questionnaire. C-reactive protein, leptin, and vitamin D were assessed, and physical activity, cardiorespiratory fitness, and muscular strength were measured. Center, socioeconomic status, pubertal status, and season were used as potential confounders. The main outcome was the homeostasis model assessment used as a marker of insulin resistance. Correlations, analyses of covariance, and logistic regression models were used. In males, leptin was the only risk factor for insulin resistance after adjusting for confounders including markers of body fat (odds ratios (ORs) from 1.49 to 1.60). In females, leptin, vitamin D, and fitness were the remaining independent risk factors for insulin resistance after adjustments (OR 2.11; 95% confidential interval (CI) 1.29-3.45; OR 0.50, 95% CI 0.31-0.80; and OR 0.54, 95% CI 0.33-0.87, respectively). Our observations suggest a gender dimorphism in the identification of risk factors for high insulin resistance. Preventive strategies should focus on improving modifiable factors such as cardiorespiratory fitness and on ensuring vitamin D sufficiency. Randomized controlled trials focusing on these strategies are necessary to test their efficacy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".