Global Inequities in Diabetes Technology and Insulin Access and Glycemic Outcomes
Bibliographic record
Abstract
Importance: Advanced diabetes technologies such as continuous glucose monitoring (CGM), continuous subcutaneous insulin infusion (insulin pumps [CSII]), and glucometers alongside insulin access represent the criterion standard for managing type 1 diabetes (T1D) in children. Global disparities in their access and reimbursement may be associated with glycemic outcomes. Objective: To describe how accessibility and reimbursement of advanced diabetes technologies and insulin are associated with glycated hemoglobin (HbA1c) levels in centers participating in the SWEET initiative, an international pediatric diabetes registry. Design, Setting, and Participants: This global multicenter cross-sectional study collected data from 81 centers in 56 countries. Web-based questionnaires were distributed to representatives of all 121 pediatric diabetes centers participating in the SWEET initiative from March 1 to May 31, 2024, and used to map accessibility of and reimbursement for CGM, CSII, glucometers, and insulin. Reimbursement data were compared with HbA1c levels using the SWEET Study dataset. Participants included 42 349 children with T1D. Exposures: Responses were categorized into 4 groups based on the extent of reimbursement for diabetes technologies and insulin. Main Outcomes and Measures: Mean HbA1c levels across centers calculated from measurements current as of December 31, 2023, analyzed by categories of accessibility of and reimbursement for diabetes technologies and insulin. Results: Data collected from 81 of 121 SWEET centers (67%) across 56 countries included HbA1c levels from 42 349 children with T1D (22 021 male [52%]; mean [SD] age, 14.3 [4.4] years; mean [SD] diabetes duration, 6.0 [4.2] years). Universal access with complete reimbursement for all technologies and insulin was reported by 32 centers from 19 countries, while 8 countries reported no reimbursement for any technologies or insulin. Centers with full reimbursement for CSII, CGM, glucometers, and insulin showed mean HbA1c levels of 7.62% (95% CI, 7.59%-7.64%) to 7.75% (95% CI, 7.73%-7.77%) compared with 9.65% (95% CI, 9.55%-9.71%) to 10.49% (95% CI, 10.40%-10.58%) in centers with no reimbursement and/or no availability (P < .001 for all items). Conclusions and Relevance: This cross-sectional study found that HbA1c levels were associated with the accessibility of modern diabetes technologies and insulin. Efforts to ensure universal accessibility are required to reduce global inequities and glycemic outcomes for children with T1D.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".