Lifestyle Behaviors, Subjective Health, and Quality of Life Among Chinese Men Living With Type 2 Diabetes
Bibliographic record
Abstract
The aim of the present study was to investigate the association between self-reported health (SRH) and quality of life (QoL) with five lifestyle-related behaviors including tobacco smoking, drinking alcohol, physical activity status, consumption of fruits, and consumption of vegetables among men diagnosed with type 2 diabetes. Participants were 786 Chinese men older than 40 years and living in urban households. Cross-sectional data on self-rated health, associated sociodemographics, and health-related behaviors were collected from the Study on Global AGEing and Health (Wave 1) of World Health Organization. Results of multivariable regression reported significant association with adherence to healthy lifestyle behavior and SRH but not QoL. According to the results, percentage of men who reported being in good SRH was overwhelmingly high (95.9%) compared with good QoL (5%). Adherence to healthy behavior was strongly associated with SRH in both bivariate and multivariate analysis, adjusted odds ratio (95% confidence interval) of good SRH for nonsmokers: 1.276 [1.055, 2.773], nondrinkers:1.351 [1.066, 3.923], taking physical exercise: 1.267 [1.117, 3.109], consuming at least five servings of fruits: 1.238 [1.034, 6.552], and vegetables: 1.365 [1.032, 3.885]. The current findings suggest that abstention from tobacco and alcohol, optimum consumption of fruits and vegetables, regular physical exercise could have marked impact on the health status of diabetic men.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".