Associations between added sugar (solid vs. liquid) intakes, diet quality, and adiposity indicators in Canadian children
Bibliographic record
Abstract
Little is known about the influence of different forms of added sugar intake on diet quality or their association with obesity among youth. Dietary intake was assessed by three 24-h recalls in 613 Canadian children (aged 8-10 years). Added sugars (mean of 3-day intakes) were categorized according to source (solid or liquid). Dietary intake and the Canadian Healthy Eating Index (« HEI-C ») were compared across tertiles of solid and liquid added sugars separately as were adiposity indicators (body mass index (BMI), fat mass (dual-energy X-ray absorptiometry), and waist circumference). Cross-sectional associations were examined in linear regression models adjusting for age, sex, energy intake, and physical activity (7-day accelerometer). Added sugar contributed 12% of total energy intake (204 kcal) on average, of which 78% was from solid sources. Higher consumption of added sugars from either solid or liquid source was associated with higher total energy, lower intake of micronutrients, vegetables and fruit, and lower HEI-C score. Additionally liquid sources were associated with lower intake of dairy products. A 10-g higher consumption of added sugars from liquid sources was associated with 0.4 serving/day lower of vegetables and fruit, 0.4-kg/m(2) higher BMI, a 0.5-kg higher fat mass, and a 0.9-cm higher waist circumference whereas the associations of added sugars from solid sources and adiposity indicators tended to be negative. In conclusion, higher consumption of added sugar from either solid or liquid sources was associated with lower overall diet quality. Adiposity indicators were only positively associated with added sugars from liquid sources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".