Women Living Alone Have an Increased Risk to Develop Diabetes, Which Is Explained Mainly by Lifestyle Factors
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to assess the role of household conditions for the progression to diabetes in women with impaired glucose tolerance (IGT). RESEARCH DESIGN AND METHODS: A total of 461 women, aged 50-64 years, with IGT defined by an oral glucose tolerance test, had baseline advice on physical exercise, diet, smoking, and alcohol habits. Physical examination, blood tests, and questionnaires were completed at baseline and after 2.5 years. Household status was categorized into living alone or with a partner, other adults, or children. RESULTS: Women living alone had a 2.68-fold increased risk (95% CI 1.02-7.05) of developing diabetes after adjustments for biological risk factors. Further stepwise adjustments for education, occupation, subjective mental health, exercise, diet, and alcohol showed remaining significant odds ratios (ORs), decreasing from 3.26 (1.19-8.96) to 3.03 (1.02-8.99). However, when smoking status was added, the OR became nonsignificant, 2.07 (0.62-6.88). More women who lived alone smoked and did not reduce their daily cigarette consumption compared with women in other household conditions. At follow-up, women living alone had reduced their alcohol consumption and were more often abstainers and fewer had healthy dietary habits or had improved their diet. Physical exercise did not differ among the groups. Separate analyses of any other household status did not show any excess risk for development of diabetes. CONCLUSIONS: Women living alone had a higher risk to progress from IGT to diabetes, mostly explained by smoking, alcohol, and dietary habits. Household conditions should be accounted for when assessing future risk for diabetes.
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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 | 0.000 | 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) | 0.003 | 0.001 |
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".