Change in total sugars consumption among Canadian children and adults.
Bibliographic record
Abstract
BACKGROUND: Free sugars are nutrients of public health concern that have been associated with negative health outcomes, including dental caries in children and excess weight gain. Since national-level free sugars data are not currently available for Canadians, total sugars intake was examined to understand sugars intake in the population. The objective of this analysis was to describe and compare total sugars consumption among Canadians in 2004 and 2015. DATA AND METHODS: Data are from the 2004 and 2015 Canadian Community Health Survey-Nutrition. Separate descriptive analyses of total sugars for children aged 2 to 18 (n=13,919) and adults aged 19 and older (n=31,156) were conducted by year and by misreporting status (under-, plausible and over-reporters), and the top sources of total sugars were identified. Misreporting status was studied to better understand differences in sugars intakes between survey years. T-tests were used to determine significant differences between survey years. RESULTS: In 2015, the average daily total sugars consumption was 101 grams (24 teaspoons) for children aged 1 to 8, 115 grams (27 teaspoons) for children aged 9 to 18, and 85 grams (20 teaspoons) for adults. Sugary beverages, taken together, were the top source of sugars for all age groups. Total sugars consumption decreased from 2004 to 2015 overall, although not by misreporting status. Total sugars from food alone increased from 2004 to 2015, and total sugars from beverages alone decreased, regardless of age or misreporting status. DISCUSSION: The overall decrease in total sugars consumption from 2004 to 2015 may be explained by changes in misreporting. Total sugars from food alone increased, while total sugars from beverages alone decreased. This was true for all age groups and for plausible reporters.
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) | 0.000 | 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".