Factors associated with early insulin initiation in Type 2 diabetes: a Canadian cross‐sectional study
Bibliographic record
Abstract
AIM: To examine the patient characteristics associated with early initiation of insulin after a diagnosis of Type 2 diabetes. METHODS: We analysed cross-sectional data from the 2012 Canadian Community Health Survey conducted by Statistics Canada. Multivariable logistic regression was used to explore the association between patient sociodemographic and health status characteristics and initiating insulin within 1 year of a diagnosis of Type 2 diabetes (early insulin use). RESULTS: Weighted estimates for the Canadian population showed that 32% of patients with Type 2 diabetes initiated insulin within 1 year of their diagnosis. Of the insulin initiators, 52% were female and 68% were aged ≥60 years. Factors strongly associated with early initiation of insulin were age (60-69 years: adjusted odds ratio 1.89, 95% CI 1.84-1.94; ≥ 70 years, odds ratio 2.08, 95% CI 2.01-2.15, both vs 40-49 years); smoking (smoker vs never: odds ratio 2.39, 95% CI 2.32-2.46); geography (Western Canada: odds ratio 2.75, 95% CI 2.69-2.81; Quebec: odds ratio 2.20, 95% CI 2.13-2.27, both vs Ontario); mental health (poor vs excellent: odds ratio 1.98, 95% CI 1.92-2.04); BMI (overweight vs normal/underweight: odds ratio 1.63, 95% CI 1.58-1.67); oral antidiabetic medication use (yes vs no: odds ratio 0.66, 95% CI 0.65-0.68); and alcohol use (regular vs non-drinker: odds ratio 0.66, 95% CI 0.65-0.68). CONCLUSION: One-third of the study population with Type 2 diabetes initiated insulin within their first year of diagnosis. Age, smoking status, geographical location, mental health, BMI, education, oral antidiabetic medication use, employment, physical activity, language, doctor visits and alcohol consumption were associated with timing of insulin initiation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".