Socioeconomic Inequalities in Dietary Intake in Chile: A Systematic Review
Bibliographic record
Abstract
Objective: Understanding the socioeconomic inequalities in dietary intake is crucial when addressing the socioeconomic gradient in obesity rates and non-communicable diseases. We aimed to systematically assess the association between socioeconomic position (SEP) and dietary intake in Chile. Design: We searched for peer-reviewed and grey literature from inception until 31st December 2019 in PubMed, Scopus, PsycINFO, Web of Sciences and LILACS databases. Observational studies published in English and Spanish, reporting the comparison of at least one dietary factor between at least two groups of different SEP in the general Chilean population, were selected. Two researchers independently conducted data searches, screening, extraction and assessed study quality using an adaptation of the Newcastle Ottawa Quality Assessment Scale. Results: Twenty-one articles (from 18 studies) were included. Study quality was considered low, medium, and high for 24, 52 and 24% of articles, respectively. Moderate-to-large associations indicated lower intake of fruit and vegetables, dairy products and fish/seafood and higher pulses consumption among adults of lower SEP. Variable evidence of association was found for energy intake and macronutrients, in both children and adults.Conclusions: Our findings highlight some socioeconomic inequalities in diets in Chile, evidencing an overall less healthy food consumption among the lower SEP groups. New policies to reduce these inequalities should tackle the unequal distribution of factors affecting healthy eating among the lower SEP groups. These findings also provide important insights for developing strategies to reduce dietary inequalities in Chile and other countries that have undergone similar nutritional transitions.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".