Workplace-Based Glucose Screening for Type 2 Diabetes in French Civil Servants: Prospective Observational Cohort Study
Bibliographic record
Abstract
Background: Type 2 diabetes (T2D) remains one of the most underdiagnosed chronic conditions worldwide, despite its major contribution to cardiovascular and metabolic morbidity. In 2024, an estimated 589 million adults were living with diabetes globally, more than 90% of whom had T2D, and the prevalence is projected to reach 853 million by 2050. In France, approximately 4.1 million adults are affected, and nearly 1 in 4 individuals with diabetes remain undiagnosed. Therefore, early detection is essential to prevent complications. Workplace prevention strategies could improve early detection, particularly among employed adults with limited access to regular medical screening. In France, a health prevention organization has implemented a systematic glucose screening program for civil servants to identify individuals at risk of T2D or prediabetes. As the French public service includes 5.7 million workers-approximately 1 in 5 of the national workforce-this setting provides a unique opportunity to reach large, diverse, and often underserved segments of the adult population. Objective: This study aimed to assess the effectiveness of a systematic diabetes screening program as a preventive public health measure by determining the rate of newly detected diabetes cases and characterizing associated cardiometabolic risk factors within a large population of French civil servants. Methods: A retrospective observational study was conducted using data from a glucose screening program between January 2022 and February 2025. Participants with postprandial blood glucose levels >1.40 g/L were included in a follow-up cohort. Sociodemographic, clinical, and biological data were collected. Comparisons were performed using the chi-square or Fisher exact test for categorical variables and the Student t test (2-tailed) for continuous variables (P<.05). Analyses were restricted to complete cases to ensure robust comparisons. Results: Among 16,785 screened participants, 981 (5.8%) had postprandial glucose levels >1.40 g/L and 134 (0.8%) were eligible for the follow-up cohort. Participants were 59.5% (n=78) women and 40.5% (n=53) men, with a mean age of 51.3 (SD 8.9) years. Overall, 37.6% (n=50) of participants were overweight, 25.4% (n=34) were obese, 61.6% (n=77) reported insufficient physical activity, and 63.2% (n=84) had a family history of diabetes. Of the 134 eligible individuals, 70 (52.2%) completed medical follow-up, and among them, 9 (12.9%) received a confirmed diagnosis of T2D. Newly diagnosed individuals were predominantly male (n=7, 78%; P=.04) and more likely to be overweight or obese (n=9, 89%; P=.04). No significant differences in age, sex, or BMI were observed between followed and lost-to-follow-up participants. Conclusions: Systematic glucose screening in occupational or social health context identifies individuals at risk of diabetes or prediabetes and supports its integration into preventive health strategies to enhance early detection and reduce long-term complications. Larger prospective or randomized studies are warranted to confirm long-term benefits on diagnosis, care engagement, and cardiometabolic outcomes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".