Predictors of Weight Loss in Young Adults
Bibliographic record
Abstract
BACKGROUND: Increased understanding of weight loss among healthy young people in naturalistic settings could inform the development of effective weight control programs. The aim of this study was to describe loss in BMI over 7 years in a population-based sample of healthy young adolescents (mean age 17 years at beginning of follow-up) and identify determinants of BMI loss. DESIGN AND METHOD: Data were available for 681 participants in the Nicotine Dependence in Teens Study (1999-2012), a longitudinal investigation of adolescents in Montreal (Canada). Loss in BMI was assessed between age 17 and 24 years. Potential predictors of BMI loss including age, sex, mother's education, worry about weight, physical activity, screen time, and cigarette smoking were studied in multivariable logistic regression. RESULTS: Males and females gained 2.0 and 1.4 BMI units, respectively, on average, between age 17 and 24 years. However, 9% of males and 14% of females experienced a loss in BMI ≥1.0 unit. Female sex and a higher BMI at age 17 were associated with a higher probability of BMI loss, but none of age, mother's education, physical activity, screen time, or cigarette smoking were associated with BMI loss between ages 17 and 24. CONCLUSIONS: Whereas BMI increased on average between age 17 and 24 years in a population-based sample of healthy young people, 12% of participants experienced a loss in BMI ≥1 unit. Weight loss was highest among the heaviest persons and did not affect the prevalence of underweight. No single behavior at age 17 stands out as associated with predicting BMI loss.
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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 | 0.000 | 0.000 |
| 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".