Eating at food outlets and leisure places and “on the go” is associated with less-healthy food choices than eating at home and in school in children: cross-sectional data from the UK National Diet and Nutrition Survey Rolling Program (2008–2014)
Bibliographic record
Abstract
Background: Where children eat has been linked to variations in diet quality, including the consumption of low-nutrient, energy-dense food, a recognized risk factor for obesity. Objective: The aim of this study was to provide a comprehensive analysis of consumption patterns and nutritional intake by eating location in British children with the use of a nationally representative survey. Design: Cross-sectional data from 4636 children (80,075 eating occasions) aged 1.5-18 y from the UK National Diet and Nutrition Survey Rolling Program (2008-2014) were analyzed. Eating locations were categorized as home, school, work, leisure places, food outlets, and "on the go." Foods were classified into core (considered important or acceptable within a healthy diet) and noncore (all other foods). Other variables included the percentage of meals eaten at home, sex, ethnicity, body mass index, income, frequency of eating out, takeaway meal consumption, alcohol consumption, and smoking. Results: The main eating location across all age groups was at home (69-79% of eating occasions), with the highest energy intakes. One-third of children from the least-affluent families consumed ≤25% of meals at home. Eating more at home was associated with less sugar and takeaway food consumption. Eating occasions in leisure places, food outlets, and "on the go" combined increased with age, from 5% (1.5-3 y) to 7% (11-18 y), with higher energy intakes from noncore foods in these locations. The school environment was associated with higher intakes of core foods and reduced intakes of noncore foods in children aged 4-10 y who ate school-sourced foods. Conclusions: Home and school eating are associated with better food choices, whereas other locations are associated with poor food choices. Effective, sustained initiatives targeted at behaviors and improving access to healthy foods in leisure centers and food outlets, including food sold to eat "on the go," may improve food choices. Home remains an important target for intervention through family and nutrition education, outreach, and social marketing campaigns. This trial was registered with the ISRTCN registry (https://www.isrctn.com) as ISRCTN17261407.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".