Weight Goals, Disordered Eating Behaviors, and BMI Trajectories in US Young Adults
Bibliographic record
Abstract
Abstract Background Community sample data indicate that weight control efforts in young adulthood may have associations with greater increases in body mass index (BMI) over time. Objective To determine the prospective associations between weight goals and behaviors in young adults and BMI trajectories over 15-year follow-up using a nationally representative sample. Design Longitudinal cohort data collected from 2001 to 2018 of the National Longitudinal Study of Adolescent to Adult Health. Participants Young adults aged 18–26 years old at baseline stratified by gender and BMI category. Main Measures Predictors: weight goals, any weight loss/maintenance behaviors, dieting, exercise, disordered eating behaviors. Outcomes: BMI at 7- and 15-year follow-up. Key Results Of the 12,155 young adults in the sample (54% female, 32% non-White), 33.2% reported a goal to lose weight, 15.7% to gain weight, and 14.6% to maintain weight. In unadjusted models, all groups have higher mean BMI at 7- and 15-year follow-up. In mixed effect models, goals to lose weight in men with BMI < 18.5 (5.94 kg/m2; 95% CI 2.58, 9.30) and goals to maintain weight in men with BMI ≥ 25 (0.44; 95% CI 0.15, 0.72) were associated with greater BMI increase compared to no weight goal. Engaging in disordered eating behaviors was associated with greater BMI increase in men with BMI < 18.5 (5.91; 2.96, 8.86) and women with 18.5 ≤ BMI < 25 (0.40; 0.16, 0.63). Dieting (− 0.24; − 0.41, − 0.06) and exercise (− 0.31; − 0.45, − 0.17) were associated with lower BMI increase in women with 18.5 ≤ BMI < 25. In women with BMI < 18.5, dieting was associated with greater BMI increase (1.35; 0.33, 2.37). Conclusions Weight control efforts may have variable effects on BMI over time by gender and BMI category. These findings underscore the need to counsel patients on the effectiveness of weight control efforts and long-term weight management.
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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 | 0.002 |
| 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 | 0.000 |
| 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".