Are dietary inequalities among Australian adults changing? a nationally representative analysis of dietary change according to socioeconomic position between 1995 and 2011–13
Bibliographic record
Abstract
BACKGROUND: Increasing inequalities in rates of obesity and chronic disease may be partly fuelled by increasing dietary inequalities, however very few nationally representative analyses of socioeconomic trends in dietary inequalities exist. The release of the 2011-13 Australian National Nutrition and Physical Activity Survey data allows investigation of change in dietary intake according to socioeconomic position (SEP) in Australia using a large, nationally representative sample, compared to the previous national survey in 1995. This study examined change in dietary intakes of energy, macronutrients, fiber, fruits and vegetables among Australian adults between 1995 and 2011-13, according to SEP. METHODS: Cross-sectional data were obtained from the 1995 National Nutrition Survey, and the 2011-13 National Nutrition and Physical Activity Survey. Dietary intake data were collected via a 24-h dietary recall (n = 17,484 adults) and a dietary questionnaire (n = 15,287 adults). SEP was assessed according to educational level, equivalized household income, and area-level disadvantage. Survey-weighted linear and logistic regression models, adjusted for age, sex/gender and smoking status, examined change in dietary intakes over time. RESULTS: Dietary intakes remained poor across the SEP spectrum in both surveys, as evidenced by high consumption of saturated fat and total sugars, and low fiber, fruit and vegetable intakes. There was consistent evidence (i.e. according to ≥2 SEP measures) of more favorable changes in dietary intakes of carbohydrate, polyunsaturated and monounsaturated fat in higher, relative to lower SEP groups, particularly in women. Intakes of energy, total fat, saturated fat and fruit differed over time according to a single SEP measure (i.e. educational level, household income, or area-level disadvantage). There were no changes in intake of total sugars, protein, fiber or vegetables according to any SEP measures. CONCLUSIONS: There were few changes in dietary intakes of energy, most macronutrients, fiber, fruits and vegetables in Australian adults between 1995 and 2011-13 according to SEP. For carbohydrate, polyunsaturated and monounsaturated fat, more favorable changes in intakes occurred in higher SEP groups. Despite the persistence of suboptimal dietary intakes, limited evidence of widening dietary inequalities is positive from a public health perspective. TRIAL REGISTRATION: Clinical trials registration: ACTRN12617001045303 .
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".