Adiponectin : distribution, and associations with age, sex, adiposity, lifestyle factors, family history and insulin resistance in children and adolescents
Bibliographic record
Abstract
Adiponectin is inversely related to obesity, insulin resistance and progression to type 2 diabetes in adults. However its distribution, determinants and its association with insulin resistance (IR) are less well studied in the pediatric population. The objectives of this study were to describe, in youth, the age- and sex-specific distribution of adiponectin concentrations, and its association with demographic, anthropometric, and lifestyle factors, parental diabetes, and markers of JR. This study was a secondary analysis of a sample of 1632 French Canadian youth aged 9, 13 and 16 years who participated in the Quebec Child and Adolescent Health and Social Survey, a province-wide school-based survey conducted in 1999. Boys had lower adiponectin concentrations than girls by 17% (p<0.0001). Adiponectin concentrations decreased by age-group to a greater extent in boys than girls over the age range studied (27.7% vs. 13.3%, pinteraction=0.009). Mean adiponectin decreased by 8.1% in boys and 11.2% in girls (p<0.0001) for every unit increase in BMI Z-score. Growth-related change in BMI explained half the age effect in boys and all the age effect in girls. Self-reported pubertal status, physical activity, smoking and parental diabetes were not independently associated with adiponectin. Fasting insulin and HOMA-IR were not associated with adiponectin concentration after adjusting for BMI. However, an interaction term for adiponectin and BMI Z-score was significant in a multiple linear regression model with fasting insulin as the dependent variable. In conclusion, male sex and changes in body fat may be major determinants of decreasing adiponectin concentrations in growing youth. There was no association between adiponectin and markers of 1R. The relationship between adiposity and markers of IR is attenuated in those with higher adiponectin concentrations, making adiponectin a potential intervention target or risk stratification marker for which the normative data presented herein may be useful.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".