Determinants of quality of life in adults with type 1 and type 2 diabetes
Bibliographic record
Abstract
BACKGROUND: Limited evidence exists on the determinants of quality of life (QoL) specific to adults with type 1 diabetes (T1D). Further, it appears no study has compared the determinants of QoL between T1D and type 2 diabetes (T2D) groups. The objectives of this study were to examine: (1) determinants of QoL in adults with T1D; and, (2) differences in QoL determinants between T1D and T2D groups. METHODS: The Alberta Longitudinal Exercise and Diabetes Research Advancement (ALEXANDRA) study, a longitudinal study of adults with diabetes in Alberta, Canada. Adults (18 years and older) with T1D (N = 490) and T2D (N = 1,147) provided information on demographics (gender, marital status, education, and annual income), personality (activity trait), medical factors (diabetes duration, insulin use, number of comorbidities, and body mass index), lifestyle behaviors (smoking habits, physical activity, and diet), health-related quality of life (HRQL) and life satisfaction. Multiple regression models identified determinants of HRQL and life satisfaction in adults with T1D. These determinants were compared with determinants for T2D adults reported in a previous study from this population data set. Factors significantly associated with HRQL and life satisfaction in either T1D or T2D groups were further tested for interaction with diabetes type. RESULTS: In adults with T1D, higher activity trait (personality) score (β = 0.28, p < 0.01), fewer comorbidities (β = -0.27, p < 0.01), lower body mass index (BMI)(β = -0.12, p < 0.01), being a non-smoker (β = -0.14, p < 0.01), and higher physical activity levels (β = 0.16, p < 0.01) were associated with higher HRQL. Having a partner (β = 0.11, p < 0.05), high annual income (β = 0.16, p < 0.01), and high activity trait (personality) score (β = 0.27, p < 0.01) were significantly associated with higher life satisfaction. There was a significant age × diabetes type interaction for HRQL. The T2D group had a stronger positive relationship between advancing age and HRQL compared to the T1D group. No interaction was significant for life satisfaction. CONCLUSIONS: Health services should target medical and lifestyle factors and provide support for T1D adults to increase their QoL. Additional social support for socioeconomically disadvantaged individuals living with this disease may be warranted. Health practitioners should also be aware that age has different effects on QoL between T1D and T2D adults.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".