Gender differences in the impact of poverty on health: disparities in risk of diabetes‐related amputation
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Bibliographic record
Abstract
AIMS: To assess the combined impact of socio-economic status and gender on the risk of diabetes-related lower extremity amputation within a universal healthcare system. METHODS: We conducted a population-based cohort study using administrative health databases from Ontario, Canada. Adults with pre-existing or newly diagnosed diabetes (N = 606 494) were included and the incidence of lower extremity amputation was assessed for the period 1 April 2002 to 31 March 2009. Socio-economic status was based on neighbourhood-level income groups, assigned to individuals using the Canadian Census and their postal code of residence. RESULTS: Low socio-economic status was associated with a significantly higher incidence of lower extremity amputation (27.0 vs 19.3 per 10,000 person-years in the lowest (Q1) vs the highest (Q5) socio-economic status quintile. This relationship persisted after adjusting for primary care use, region of residence and comorbidity, and was greater among men (adjusted Q1:Q5 hazard ratio 1.41, 95% CI 1.30-1.54; P < 0.0001 for all male gender-socio-economic status interactions) than women (hazard ratio 1.20, 95% CI 1.06-1.36). Overall, the incidence of lower extremity amputation was higher among men than women (hazard ratio for men vs women: 1.87, 95% CI 1.79-1.96), with the greatest disparity between men in the lowest socio-economic status category and women in the highest (hazard ratio 2.39, 95% CI 2.06-2.77 and hazard ratio 2.30, 95% CI 1.97-2.68, for major and minor amputation, respectively). CONCLUSIONS: Despite universal access to hospital and physician care, we found marked socio-economic status and gender disparities in the risk of lower extremity amputation among patients with diabetes. Men living in low-income neighbourhoods were at greatest risk.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it