Weak regulations threaten the safety of consumers from harmful weight-loss supplements globally: results from a pilot global policy scan
Bibliographic record
Abstract
OBJECTIVE: To pilot a global policy scan assessing how governments worldwide regulate weight-loss supplements (WLS). DESIGN: Experts on WLS policies from thirty countries that varied by World Bank income classification, with five from each of the six WHO regions, completed an online survey on WLS regulation in their country. The survey covered six domains: legal frameworks; pre-market requirements; claims, labelling, and advertisements; product availability; adverse events reporting; and monitoring and enforcement. Percentages were calculated for presence or absence of a type of regulation. SETTING: Experts were recruited through websites of regulatory bodies and professional LinkedIn networks and scientific article searches on Google Scholar. PARTICIPANTS: Thirty experts, one from each country (i.e. researchers, regulators, other experts in food and drug regulation). RESULTS: WLS regulations varied widely across countries, and a number of gaps were identified. One country (Nigeria) has a minimum legal age to purchase WLS. Thirteen countries reported independently evaluating the safety of a new WLS product sample. Two countries have limitations on where WLS can be sold. In eleven countries, reports on adverse events related to WLS are publicly available. In eighteen countries, safety of new WLS is to be established through scientific criteria. Penalties for WLS non-compliance with pre-market regulations exist in twelve countries and labelling requirements in sixteen countries. CONCLUSIONS: Results of this pilot study document wide variability in national WLS regulations globally, exposing many gaps in important components of consumer protection regulatory frameworks for WLS, which likely put consumer health at risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.045 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".