Individual and community-level income and the risk of diabetes rehospitalization among women and men: a Canadian population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Marked disparities by socioeconomic status in the risk of potentially avoidable hospitalization for chronic illnesses have been observed in many contexts, including those with universal health coverage. Less well known is how gender mediates such differences. We conducted a population-based cohort study to describe associations between household and community-level income and rehospitalizations for types 1 and 2 diabetes mellitus among Canadian women and men. METHODS: Our cohorts were drawn from respondents to the 2006 mandatory long-form census linked longitudinally to 3 years of nationally standardized hospital records. We included adults 30-69 years hospitalized with diabetes at least once during the study period. We used logistic regressions to estimate odds ratios for 12-month diabetes rehospitalization associated with indicators of household and community-level income, with separate models by gender, and controlling for a range of other sociodemographic characteristics. Since diabetes may not always be recognized as the main reason for hospitalization, we accounted for disease progression through consideration of admissions where diabetes was previously identified as a secondary diagnosis. RESULTS: Among persons hospitalized at least once with diabetes (n = 41,290), 1.5% were readmitted within 12 months where the initial admission had diabetes as the primary diagnosis, and 1.8% were readmitted where the initial admission had diabetes as a secondary diagnosis. For men, being in the lowest household income quintile was associated with higher odds of rehospitalization in cases where the initial admission listed diabetes as either the primary diagnosis (OR = 2.21; 95% CI = 1.38-3.51) or a secondary diagnosis (OR = 1.51; 95% CI = 1.02-2.24). For women, we found no association with income and rehospitalization, but having less than university education was associated with higher odds of rehospitalization where diabetes was a secondary diagnosis of the initial admission (OR = 1.88; 95% CI = 1.21-2.92). We also found positive, but insignificant associations between community-level poverty and odds of rehospitalization. CONCLUSIONS: Universal health coverage remains insufficient to eliminate socioeconomic inequalities in preventable diabetes-related hospitalizations, as illustrated in this Canadian context. Decision-makers should tread cautiously with gender-blind poverty reduction actions aiming to enhance population health that may inadequately respond to the different needs of disadvantaged women and men with chronic illness.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".