Fat, Sugar or Both ? A Prospective Analysis of Dietary Patterns and Adiposity in Children
Bibliographic record
Abstract
The roles of dietary sugar and fat in childhood obesity are the subject of recent debate. We investigated dietary patterns (DP) characterized by these macronutrients and their longitudinal associations with adiposity in children. Participants were 6722 children in the UK Avon Longitudinal Study of Parents and Children. A 3-d food diary was completed at 7, 10 and 13 y of age. DP were identified according to % total energy intake (%E) from non-milk extrinsic sugars, %E from total fat, dietary energy density and fibre, using reduced rank regression. Fat mass was measured at 11, 13 and 15 y. Longitudinal models adjusted for dietary misreporting, physical activity and maternal factors. Two major DP were identified: DP1 was high in sugar, fat, energy density and low in fibre; DP2 was high in sugar but low in fat and energy density. A 1 SD increase in z-score for DP1 was associated with an average increase in fat mass index of 0.04 SD units (95%CI 0.01-0.07) and greater odds of excess adiposity (OR=12%, 95%CI 1-25%). DP2 was not significantly associated with adiposity. An energy-dense DP high in both fat and sugar is longitudinally associated with greater adiposity in childhood. This DP consists of low intakes of fruit, vegetables and wholegrains, and high intakes of sweets, cakes, sugary drinks, low-fibre cereals and breads. This provides food-based dietary guidance to prevent obesity in children that may be more meaningful to consumers than nutrient prescriptions. Funding: Medical Research Council, Wellcome Trust.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".