A review of implementation and evaluation of Pan American Health Organization's policies to prevent childhood obesity in Latin America
Bibliographic record
Abstract
Rationale: To inform future policies, the study objectives were to determine to what extent the policies included in the 5-year Plan of Action for the Prevention of Obesity in Children and Adolescents-proposed by Pan American Health Organization (PAHO) and signed by 19 Latin America countries in 2014-have been implemented and evaluated. Methods: A scoping review of the Governmental websites for Latin American countries and a literature review was conducted to identify whether policies have been implemented and evaluated. Key information was abstracted. Results: The review identified 115 PAHO policies/interventions implemented (43% implemented after signing the proposed plan in 2014). Nearly all (18/19) countries implemented food guidelines or school feeding programs, but fiscal and marketing policies were less commonly implemented (6/19). Through the review, 44 evaluations of PAHO policies were identified of which 23% were qualitative and 77% quantitative. The results of these evaluations were in general positive (e.g., decrease in sugar-sweetened beverages consumption following tax implementation) but no studies evaluated the outcome of reduced obesity. Conclusions: PAHO recommended policies have been implemented to various degrees in Latin America since 2014 and more research is required to understand their impacts on child and adolescent obesity.
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 | 0.027 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".