Educational Attainment as a Super Determinant of Diet Quality and Dietary Inequities
Bibliographic record
Abstract
Inequities in diet quality are evident worldwide and reflect structural disadvantages. There is increasing evidence that dietary inequities may be most meaningful in relation to educational attainment, a finding that contradicts the common belief that dietary inequities are primarily attributable to material disadvantage (i.e. inadequate incomes). Moreover, diet quality declines with each step down the educational ladder, and therefore, these educational inequities affect all of society. The purpose of this perspective is to posit that educational attainment is a key structural stratifier of diet quality and dietary inequities-what we term a super determinant-and that greater research attention should be given to interrogating pathways through which educational attainment shapes diet quality. To inform our perspective, we conducted extensive keyword searches in PubMed and Google Scholar to identify concepts, theories, and empirical data pertaining to educational inequities in diet quality, health, and mortality, followed by a conceptual synthesis of findings. On the basis of these findings, we first describe pathways through which educational attainment shapes diet quality. We then demonstrate that educational inequities in diet quality are often much larger than they are for income. For instance, absolute gaps and gradients in Healthy Eating Index-2015 scores between the most and least educated adults were 7-11 points in Canada, whereas they were just 2-5 points in relation to household income. We provide converging evidence related to large and growing educational inequities in diet quality, health, and mortality internationally. We subsequently consider an important counterfactual-that the affordability of a healthy diet is the key determinant of dietary inequities-and empirically demonstrate that economic factors are not primary drivers of socioeconomic inequities in diet quality. We conclude that attributing dietary inequities primarily to the higher costs of healthy foods is overly simplistic and ignores the critical role of educational attainment as a structural stratifier of dietary inequities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".