Persistent disparities in insulin pump uptake despite a universal pump programme for type 1 diabetes in Ontario, Canada
Bibliographic record
Abstract
AIM: To evaluate associations between social disadvantage and insulin pump use among adults with type 1 diabetes (T1D) in the context of a universal publicly funded insulin pump programme in Ontario, Canada, and to ascertain whether social disparities in insulin pump programme enrolment have decreased over time. METHODS: Population-based cross-sectional studies were conducted using administrative healthcare data in Ontario, Canada. First, among adults aged older than 18 years diagnosed with T1D before 31 March 2021, logistic regression was used to assess the association between neighbourhood social disadvantage (Ontario marginalization index quintiles) and insulin pump use. Second, among all paediatric and adult applicants to the insulin pump programme from 1 September 2006 to 31 March 2022, ordinal logistic regression was used to evaluate associations between year of insulin pump initiation and social disadvantage. RESULTS: Among 27 453 adults with T1D, 60% used insulin pumps. Greater social disadvantage was associated with lower odds of insulin pump use (adjusted odds ratio [OR] 0.44 [95% confidence interval {CI} 0.39-0.48] for greatest vs. lowest social disadvantage quintile). Among 21 002 paediatric and adult applicants to the insulin pump programme, social disparities in pump use decreased in the first 3 years of the programme, plateaued until 2020, then increased from 2020 to 2022, with no change in the odds of being in a higher social deprivation quintile for 2022 relative to 2007 (OR 1.09 [95% CI 0.83-1.44]). CONCLUSIONS: Despite a universal pump programme for individuals with T1D, disparities by social disadvantage persist. Residual financial and non-financial barriers must be addressed to promote equitable insulin pump uptake.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".