Early life risk factors of being overweight at 10 years of age: results of the German birth cohorts GINIplus and LISAplus
Bibliographic record
Abstract
OBJECTIVE: To develop a prediction model that quantifies the risk of being overweight at 10 years of age. SUBJECTS/METHODS: In total, 3121 participants from the GINIplus (German Infant Nutritional Intervention plus environmental and genetic influences on allergy development) and LISAplus (Influences of Lifestyle-Related Factors on the Immune System and the Development of Allergies in Childhood plus Air Pollution and Genetics) German birth cohorts were recruited. We predicted standardized body mass index (BMI) at 10 years of age using standardized BMIs from birth to 5 years. Parental education, family income and maternal smoking during pregnancy were considered as covariates. Linear and logistic regression models were used to evaluate the impact of risk factors on BMI and on being overweight at 10 years of age, respectively. RESULTS: Birth weight, standardized BMI at 5 years (60-64 months) (β=0.77; 95% confidence interval (CI): 0.73-0.81) and maternal smoking during pregnancy were positively associated with standardized BMI at 10 years of age. Standardized BMI and overweight at 5 years were strongest predictors of being overweight at 10 years. Conversely, high parental education conferred a protective effect (β=-0.15; 95% CI: -0.29 to -0.01). Being overweight at 5 years (60-64 months) increased the risk of being overweight at 10 years of age with odds ratios above 10. Among children who were predicted to be overweight at 10 years, cross-validation results showed that 76.8% of female subjects and 68.1% of male subjects would be overweight at 10 years of age. CONCLUSION: BMI and being overweight at 5 years of age are strong predictors of being overweight at 10 years of age. The effectiveness of targeted interventions in children who are overweight at 5 years of age should be explored.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".