Can targeted policies reduce obesity and improve obesity‐related behaviours in socioeconomically disadvantaged populations? A systematic review
Bibliographic record
Abstract
This review synthesized evidence from controlled studies pertaining to the impact of targeted policies on anthropometric, dietary and physical activity outcomes amongst socioeconomically disadvantaged children and adults. Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Equity guidelines were followed. Eligible studies were published from 2004 to August 2015 and examined the impact of targeted policies on anthropometric, dietary and physical activity outcomes amongst socioeconomically disadvantaged populations. Twenty articles (18 studies) were included. Eight studies examined organizational policies within multi-component interventions in schools. Common elements of successful policy-containing interventions included nutritional standards, enhancements to physical education, additional physical activity opportunities, school self-assessments, and nutrition and physical activity education. Of the 10 studies of government policies, policies providing information/education and fruit and vegetable subsidies had positive impacts amongst children, but no impact amongst adults. Policies involving changes to built environments yielded nearly uniformly null findings in children and adults. Overall, the largest quantity of high-quality evidence of effectiveness was for comprehensive interventions that included school policies, and government policies targeting disadvantaged children in schools. None of the government policies targeting disadvantaged adults proved effective. Interventions during childhood may ameliorate negative obesity-related manifestations of socioeconomic disadvantage. Gaps in knowledge remain surrounding effective policies in adults, adolescents and very young children.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".