Socioeconomic Inequities in Diet Quality and Nutrient Intakes among Australian Adults: Findings from a Nationally Representative Cross-Sectional Study
Bibliographic record
Abstract
Poor diet may represent one pathway through which lower socioeconomic position (SEP) leads to adverse health outcomes. This study examined the associations between SEP and diet quality, its components, energy, and nutrients in a nationally representative sample of Australians. Dietary data from two 24-h recalls collected during the cross-sectional Australian Health Survey 2011-13 (n = 4875; aged ≥ 19 years) were analysed. Diet quality was evaluated using the Dietary Guidelines Index (DGI). SEP was assessed by index of area-level socioeconomic disadvantage, education level, and household income. Linear regression analyses investigated the associations between measures of SEP and dietary intakes. Across all of the SEP indicators, compared with the least disadvantaged group, the most disadvantaged group had 2.5–4.5 units lower DGI. A greater area-level disadvantage was associated with higher carbohydrate and total sugars intake. Lower education was associated with higher trans fat, carbohydrate, and total sugars intake and lower poly-unsaturated fat and fibre intake. Lower income was associated with lower total energy and protein intake and higher carbohydrate and trans fat intake. Lower SEP was generally associated with poorer diet quality and nutrient intakes, highlighting dietary inequities among Australian adults, and a need to develop policy that addresses these 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".