Public health burden of pre-diabetes and diabetes in Luxembourg: finding from the 2013–2015 European Health Examination Survey
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to determine the burden and risk factors of prediabetes and diabetes in the general adult population of Luxembourg. DESIGN: Cross-sectional survey between 2013 and 2015. SETTING: Data were collected as part of the European Health Examination Survey in Luxembourg (EHES-LUX). PARTICIPANTS: 1451 individuals were recruited in a random sample of the 25-64-year-old population of Luxembourg. OUTCOMES: Diabetes was defined by a glycaemic biomarker (fasting plasma glucose (FPG) ≥7.0 mmol/L), self-reported medication and medical diagnosis; prediabetes by a glycaemic biomarker (FPG 5.6-6.9 mmol/L), no self-reported medication and no medical diagnosis. Undiagnosed diabetes was defined only from the glycaemic biomarker; the difference between total and undiagnosed diabetes was defined as diagnosed diabetes. Odds of diabetes and prediabetes as well as associated risk factors were estimated. RESULTS: The weighted prevalence of prediabetes and diabetes was 25.6% and 6.5%, respectively. Nearly 4.8% (men: 5.8%; women: 3.8%) were diagnosed diabetes and 1.7% (men: 2.6%; women: 0.7%) were undiagnosed diabetes. The multivariable-adjusted OR (MVOR) for diabetes risk were: age 1.05 (95% CI 1.01 to 1.09), family history of diabetes 3.24 (1.95-5.38), abdominal obesity 2.63 (1.53-4.52), hypertension 3.18 (1.76-5.72), one-unit increase of triglycerides 1.16 (1.10-1.22) and total cholesterol 0.74 (0.64-0.86). The MVOR for prediabetes risk were: age 1.04 (95% CI 1.02 to 1.06), male sex 1.84 (1.30-2.60), moderate alcohol consumption 1.38 (1.01-1.89), family history of diabetes 1.52 (1.13-2.05), abdominal obesity 1.44 (1.06-1.97), second-generation immigrants 0.61 (0.39-0.95) and a one-unit increase of serum high-density lipoprotein cholesterol 0.70 (0.54-0.90). CONCLUSIONS: In Luxembourg, an unexpectedly high number of adults may be affected by prediabetes and diabetes. Therefore, these conditions should be addressed as a public health priority for the country, requiring measures for enhanced detection and surveillance, which are currently lacking, especially in primary care settings.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".