Parent reported nutritional risk and laboratory indices of cardiometabolic risk and in preschool-aged children
Bibliographic record
Abstract
BACKGROUND: Eating habits formed during childhood may contribute to the increasing prevalence of cardiometabolic disorders. Assessing nutritional risk in young children may help to prevent later cardiometabolic disease. The objective of this study was to determine whether parent-reported nutritional risk in preschool-aged children was associated with laboratory indices of cardiometabolic risk, namely leptin and insulin. METHODS: In this cross-sectional study, the relationship between nutritional risk as determined by the parent-completed NutriSTEP® questionnaire was assessed and compared to the serum leptin and insulin concentrations, hormones involved in regulation of food intake and biomarkers of adiposity and cardiometabolic risk. The community-based primary care research network for children in Toronto, Canada (TARGet Kids!) was used. The participants were children aged 3-5 years recruited from TARGet Kids! A total of 1856 children were recruited from seven primary care practices. Of these, 1086 children completed laboratory testing. Laboratory data for leptin and insulin were available for 714 and 1054 of those individuals, respectively. RESULTS: The total NutriSTEP® score was significantly associated with serum leptin concentrations (p=0.003); for each unit increase in the total NutriSTEP® score, there was an increase of 0.01 ng/mL (95% confidence interval [CI] 0.004-0.018) in serum leptin concentrations after adjusting for potential confounders. The total NutriSTEP® score was not significantly associated with serum insulin concentration. CONCLUSIONS: Parent reported nutritional risk is associated with serum leptin, but not insulin, concentrations in preschool-aged children. The NutriSTEP® questionnaire may be an effective tool for predicting future cardiometabolic risk in preschool-aged children.
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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 | 0.003 |
| 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 | 0.001 | 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".