Do disparities exist between national food group recommendations and the dietary intakes of contemporary young adults?
Bibliographic record
Abstract
AIM: The aim of this study was to compare food and nutrient intakes of young Australian adults (18-24 years) to national recommendations as per the Australian Guide to Healthy Eating and Nutrient Reference Values. METHODS: Dietary intake of 18 to 24 year olds (n = 1005) participating in the Advice, Ideas, and Motivation for My Eating (Aim4Me) study was self-reported using the 120-item Australian Eating Survey Food Frequency Questionnaire. Median daily servings of Australian Guide to Healthy Eating food groups, macronutrients and micronutrients were compared to recommendations in the Australian Guide to Healthy Eating and Nutrient Reference Values using t-tests or Kruskal-Wallis tests (P < .05). RESULTS: None of the young adults met all Australian Guide to Healthy Eating recommendations. The highest adherence [% meeting recommendations, median (IQR)] was for meat/alternatives [38%, 2.1(1.8)] and fruit [32%, 1.5(1.6)], with <25% meeting remaining food-group recommendations. The majority (76%) exceeded recommendations for the consumption of discretionary foods [4.0(3.3) vs 0-3 serves] and 81% had excessive saturated fat intakes. Young adults who met all key Nutrient Reference Values (dietary fibre, folate, iodine, iron, calcium and zinc) (18%) consumed a higher number of serves of all food groups, including discretionary foods. CONCLUSIONS: Dietary intakes of contemporary young adults do not align with Australian Guide to Healthy Eating targets, while meeting Nutrient Reference Values is achieved by a higher consumption of all food groups, including discretionary foods. Strategies to increase consumption of nutrient-dense foods in young adults to achieve the Nutrient Reference Values are warranted.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".