Can policy ameliorate socioeconomic inequities in obesity and obesity‐related behaviours? A systematic review of the impact of universal policies on adults and children
Bibliographic record
Abstract
This systematic review examined the impact of universal policies on socioeconomic inequities in obesity, dietary and physical activity behaviours among adults and children. PRISMA-Equity guidelines were followed. Database searches spanned from 2004 to August 2015. Eligible studies assessed the impact of universal policies on anthropometric, dietary or physical activity-related outcomes in adults or children according to socioeconomic position. Thirty-six studies were included. Policies were classified as agentic, agento-structural or structural, and their impact on inequities was rated as positive, neutral, negative or mixed according to the dominant associations observed. Most policies had neutral impacts on obesity-related inequities regardless of whether they were agentic (60% neutral), agento-structural (68% neutral) or structural (67% neutral). The proportion of positive impacts was similar across policy types (10% agentic, 18% agento-structural and 11% structural), with some differences for negative impacts (30% agentic, 14% agento-structural and 22% structural). The majority of associations remained neutral when stratified by participant population, implementation level and socioeconomic position measures and by anthropometric and behavioural outcomes. Fiscal measures had consistently neutral or positive impacts on inequities. Findings suggest an important role for policy in addressing obesity in an equitable manner and strengthen the case for implementing a broad complement of policies spanning the agency-structure continuum.
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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 | 0.012 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".