Assessing and targeting key lifestyle cardiovascular risk factors at the workplace: Effect on hemoglobin A1c levels
Bibliographic record
Abstract
PURPOSE: Despite the key role played by lifestyle habits in the epidemic of type 2 diabetes (T2D), nutritional quality and physical activity are not systematically considered in clinical practice. The project was conducted to verify whether assessing/targeting lifestyle habits could reduce hemoglobin A1c (HbA1c) levels of employees. METHODS: The intervention consisted of a 3-month competition among teams of five employees to favor peer-based support in the adoption of healthier lifestyle habits (Eat better, Move more, and Quit smoking) (n = 900). A comprehensive cardiometabolic/cardiorespiratory health assessment was conducted before and after the contest (nutrition/physical activity questionnaires, blood pressure, anthropometric measurements, lipid profile, HbA1c, fitness). HbA1c levels were used to identify individuals with prediabetes (5.7%-6.4%) or T2D (≥6.5%). RESULTS: At baseline, 51% of the employees had increased HbA1c levels (≥5.7%). The HbA1c levels were associated with waist circumference, independently of body mass index. Subjects with prediabetes showed a higher waist circumference as well as a more deteriorated cardiometabolic profile compared to workers with normal HbA1c levels. After the intervention, employees with elevated HbA1c significantly reduced their HbA1c levels. CONCLUSION: Results suggest that assessing/targeting key lifestyle correlates of the cardiometabolic profile represents a relevant approach to target abdominal obesity and fitness with a significant impact on HbA1c levels.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".