Association Between Neighborhood-Level Deprivation and Disability in a Community Sample of People With Diabetes
Bibliographic record
Abstract
OBJECTIVE: The objective of the present study was to analyze the association between neighborhood deprivation and self-reported disability in a community sample of people with type 2 diabetes. RESEARCH DESIGN AND METHODS: Random digit dialing was used to select a sample of adults with self-reported diabetes aged 18-80 years in Quebec, Canada. Health status was assessed by the World Health Organization Disability Assessment Schedule II. Material and social deprivation was measured using the Pampalon index, which is based on the Canadian Census. Potential risk factors for disability included sociodemographic characteristics, socioeconomic status, social support, lifestyle-related factors (smoking, physical activity, and BMI), health care-related problems, duration of diabetes, insulin use, and diabetes-specific complications. RESULTS: There was a strong association between disability and material and social deprivation in our sample (n = 1,439): participants living in advantaged neighborhoods had lower levels of disability than participants living in disadvantaged neighborhoods. The means +/- SD disability scores for men were 7.8 +/- 11.8, 12.0 +/- 11.8, and 18.1 +/- 19.4 for low, medium, and high deprivation areas, respectively (P < 0.001). The disability scores for women were 13.4 +/- 12.4, 14.8 +/- 15.9, and 18.9 +/- 16.2 for low, medium, and high deprivation areas, respectively (P < 0.01). Neighborhood deprivation was associated with disability even after controlling for education, household income, sociodemographic characteristics, race, lifestyle-related behaviors, social support, diabetes-related variables, and health care access problems. CONCLUSIONS: The inclusion of neighborhood characteristics might be an important step in the identification and interpretation of risk factors for disability in diabetes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".