Impact of price reductions, subsidies, or financial incentives on healthy food purchases and consumption: a systematic review and meta-analysis
Bibliographic record
Abstract
Poor diets are a global concern and are linked with various adverse health outcomes. Healthier foods such as fruit and vegetables are often more expensive than unhealthy options. This study aimed to assess the effect of price reductions for healthy food (including fruit and vegetables) on diet. We performed a systematic review and meta-analysis on studies that looked at the effects of financial incentives on healthy food. Main outcomes were change in purchase and consumption of foods following a targeted price reduction. We searched electronic databases (MEDLINE, EconLit, Embase, Cinahl, Cochrane Library, and Web of Science), citations, and used reference screening to identify relevant studies from Jan 1, 2013, to Dec 20, 2021, without language restrictions. We stratified results by population targeted (low-income populations vs general population), the food group that the reduction was applied to (fruit and vegetables, or other healthier foods), and study design. Percentage price reduction was standardised to assess the effect in meta-analyses. Study quality was assessed using the Cochrane Risk of Bias tool and Newcastle-Ottawa Scale. 34 studies were eligible; 15 took place in supermarkets and eight took place in workplace canteens in high-income countries, and 21 were targeted at socioeconomically disadvantaged communities. Pooled analyses of 14 studies showed a price reduction of 20% resulted in increases in fruit and vegetable purchases by 16·62% (95% CI 12·32 to 20·91). Few studies had maintained the price reduction for over 6 months. In conclusion, price reductions can lead to increases in purchases of fruit and vegetables, potentially sufficient to generate health benefits, if sustained.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".