Geographic Variations in Cardiometabolic Risk Factors in Luxembourg
Bibliographic record
Abstract
Cardiovascular disease (CVD) and associated behavioural and metabolic risk factors constitute a major public health concern at a global level. Many reports worldwide have documented different risk profiles for populations with demographic variations. The objective of this study was to examine geographic variations in the top leading cardio metabolic and behavioural risk factors in Luxembourg, in order to provide an overall picture of CVD burden across the country. The analysis conducted was based on data from the nationwide ORISCAV-LUX survey, including 1432 subjects, aged 18-69 years. A self-reported questionnaire, physical examination and blood sampling were performed. Age and sex-adjusted risk profile maps were generated using multivariate Bayesian geo-additive regression models, based on Markov Chain Monte Carlo techniques and were used to evaluate the significance of the spatial effects on the distribution of a range of cardio metabolic risk factors, namely smoking, high body mass index (BMI), high blood pressure, high fasting plasma glucose, alcohol use, high total cholesterol, low glomerular filtration rate, and physical inactivity. Higher prevalence of smoking was observed in the northern regions, higher overweight/obesity and abdominal obesity clustered in the central belt, whereas hypertension was spotted particularly in the southern part of the country. Maps revealed that subjects residing in Luxembourg canton were significantly less likely to be hypertensive or overweight/obese, whereas they were less likely to practice physical activity of ≥8000 Metabolic Equivalent of Task (MET)-min/week. These patterns were also observed at the municipality level in Luxembourg. Statistically, there were non-significant spatial patterns regarding smoking, diabetes, total serum cholesterol and low glomerular filtration rate risk distribution. This comprehensive risk profile mapping showed remarkable geographic variations in cardio metabolic and behavioural risk factors. Considering the prominent burden of CVD this research provides opportunities for tailored interventions and may help to better fight against this escalating public health problem.
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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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".