Fitness and Health Status among German Senior Managers: A Cross-sectional Analysis
Bibliographic record
Abstract
Epidemiological research on the general population demonstrated that physical activity and aerobic fitness significantly lowered cardiovascular risk.The objective of this study was to specify medical data on the broad basis of various psycho-physiological parameters concerning health and fitness among senior managers.This retrospective cross-sectional analysis of 110 managers includes the assessment of medical data, blood tests, a bicycle exhaustion test, a health questionnaire and the calculation of the cardiovascular risk score.Subjects had an average BMI of 26.1 kg/m2 (51% overweight), 43% arterial hypertension and 12% presented a metabolic syndrome.No subject had manifest diabetes, however 41% were prediabetic.The majority had a sufficient cardiopulmonary capacity.Health questionnaires mostly revealed positive selfestimations.Managers revealed a low-risk for future cardiovascular events with mean Carrisma risk values (based on Procam) of 2.6%.The self-estimated health status and measured personal fitness significantly influenced Carrisma with 23%, measured via a stepwise regression model.Except for hypertension, prediabetes and overweight values in some individuals, the cohort of this study revealed a good health and fitness status compared to the overall population in Germany, yet demonstrated the need for systematic screening programs in high-performing managers.Longitudinal studies are required to further investigate this research topic.
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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".