Examining Nutrient Intakes of Canadian Adults With Diabetes Using the Diabetes Canada Clinical Practice Guidelines Nutrient Profile Model
Bibliographic record
Abstract
The Diabetes Canada Clinical Practice (DCCP) Guidelines provide dietary recommendations for Canadians at risk and with diabetes to help lower risk and for self-management of diabetes. The DCCP nutrient profile model was developed to classify foods based on their adherence to the DCCP Guidelines. The objective of the study was to examine the nutrient intakes of Canadian adults with diabetes using the DCCP nutrient profile model. Using one-day 24-hour dietary recall from the 2015 Canadian Community Health Survey-Nutrition, nutrient intakes of Canadian adults with self-reported status of diabetes were examined. Foods were categorized by the DCCP nutrient profile model as “least”, “partially”, or “most” aligned with the DCCP Guidelines. Mean nutrient intakes were estimated and standard errors were calculated using balanced repeated replication with 500 bootstrap weighted replicates. Mean estimates were adjusted for age, sex, energy intake, and misreporting status using least squares regression. Canadian adults with diabetes (n = 1,249) consumed 14% (341 kcal/d [95% CI: 254,428]), 54% (1,291 kcal/d [1112,1470]), and 31% (682 kcal/d [613,751]) of total calories from foods that are “least”, “partially”, and “most” aligned with the DCCP Guidelines, respectively. The proportion of total fat, carbohydrate, and protein intakes from foods that are “least”, “partially”, and “most” aligned with the DCCP Guidelines were similar to their caloric contribution. However, 49% of added sugar intakes (24.1 g/d [20.8, 27.4]) were consumed from foods “least” aligned with the DCCP Guidelines. Over 60% sodium (1,746 mg/d [1,578, 1,915]) and saturated fat (18.7 g/d [16.1, 21.4]) intakes were consumed from foods “partially” aligned with the DCCP Guidelines. More than half of the fiber intakes (11.2 g/d [10.2, 12.2]) were consumed from foods “most” aligned with the DCCP Guidelines. Despite the low caloric contribution of foods “least” aligned with the DCCP Guidelines, these foods contributed to disproportionate intakes of added sugar and saturated fat among Canadian adults with diabetes. The use of the DCCP nutrient profile model can help Canadians with diabetes improve their nutrient intakes. CIHR Project Grant; Sanofi-Pasteur International Collaboration; CIHR-Doctoral Award (JJL).
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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".