Economic and equity evaluation of age restrictions on over-the-counter diet pills and muscle-building supplements
Bibliographic record
Abstract
Over-the-counter diet pills and muscle-building supplements are linked to increased eating disorder diagnoses, especially among youth. With limited regulatory oversight, minors may unknowingly consume harmful substances leading to other adverse effects. Massachusetts has proposed restricting sales to individuals under 18 years. However, concerns about health equity and unintended consequences arise when proposing new policies. We conducted a cost-effectiveness analysis of the proposed age-restriction policy compared to the status quo, focusing on 2 closed cohorts of males and females aged 0-17 years in Massachusetts over a 30-year time horizon. We evaluated the impact from both societal and health systems' perspectives and further assessed equity implications by modeling 3 racial/ethnic subgroups. The policy is projected to prevent 57 034 eating disorder cases and over 46 000 additional adverse medical events (eg, liver injuries). It would yield 51 749 quality-adjusted life years and generate healthcare savings of $14 million and societal savings of $30 million annually. The Latine subpopulation would see the highest per capita health benefits followed by Black and White residents, respectively. Restricting the sale of these supplements to minors offers both health and economic benefits. These findings underscore the policy's effectiveness, fiscal responsibility, and positive equity impacts, providing confidence for policymakers and the public.
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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 | 0.024 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".