Type 2 diabetes prevalence among Canadian adults — dietary habits and sociodemographic risk factors
Bibliographic record
Abstract
Patients with diagnosed diabetes receive recommendations by their healthcare providers about lifestyle modification, particularly on diet. The aim of this study was to determine the prevalence of type 2 diagnosed diabetes, undetected (undiagnosed) type 2 diabetes, and prediabetes of Canadian adults, and to evaluate whether individuals with diagnosed diabetes have different dietary intakes compared with the other groups. We used nationally representative data from Canadian Health Measures Survey Cycles 1 and 2 (n = 6807, representing estimated population of 23 022 890). We evaluated prevalence of diagnosed diabetes, undetected diabetes, and prediabetes and their distribution across sociodemographic and lifestyle factors. The intake from different food/food groups was compared between those with diagnosed diabetes and the rest of the population. Among Canadians 20–79 years of age, 12.4% had prediabetes, and 7.5% had diabetes. Among all diabetes cases, 37.3% were undiagnosed. All 3 diabetic categories were more prevalent among older age groups (60–79 years) compared with younger age (20–39 years) groups. Diagnosed diabetes and prediabetes were more prevalent among less educated individuals compared with the higher educated ones. Diagnosed diabetes was more common among individuals with lower-middle income level compared with the highest income level. Diagnosed diabetes individuals had lower intake from juice and ice cream and higher intake from potatoes and diet soft drinks compared with other groups. More than 600 000 adults were unaware of their diabetes status; the aware ones had lower intakes of sugar-containing foods. In evaluating the association between dietary intake and risk of chronic diseases in populations, diagnosed diabetes cases should be evaluated separately.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".