THE RELATION OF CARDIOVASCULAR HEALTH WITH PROFESSIONAL OCCUPATION (ESSE-RF IN KEMEROVO REGION)
Bibliographic record
Abstract
Aim. Analysis of the prevalence of cardiovascular diseases and risk factors depending on occupation.Material and methods. Under the multicenter epidemiological study ESSE-RF (Epidemiology of Cardiovascular Diseases and their Risk Factors in Russian Federation) the questioning performed and 1627 persons investigated in Kemerovo Region at the age 25-64 y.o. Two comparison groups were created: employed (n=1214), unemployed (n=413). The data obtained on the occupation and cardiovascular risk factors: smoking, alcohol consumption, obesity, cholesterol level, lipoproteids, glucose, anamnesis of cardiovascular diseases and real presence of arterial hypertension, ischemic heart disease (IHD) by Minnesota criteria, and angina pectoris by Rose score. In statistical processing, with the aim to relieve age differences of the groups we standardized by the age via direct method, and in regression analysis there was a parameter "age".Results. In employed men there was statistically significant lower prevalence of smoking — among workers 40,2%, unemployed 52,6% (p=0,011). CHD in anamnesis in 5,4% and 11,9%, resp. (p=0,0047), arterial hypertension — 47,9% and 57,1%, resp. (p=0,043), angina by Rose score — 5,3% and 13,6%, resp. (p=0,00001), CHD by Minnesota code — 5,0% and 9,2%, resp. (p=0,048), CHD by 3 epidemiological criteria — 9,4% and 20,4%, resp. (p=0,00020). In women employment was related to lower prevalence of smoking — 15,4% among workers, 22,4% — unemployed (p=0,038) and CHD by Minnesota code —5,4% and 9,6%, resp. (p=0,019). Occupational status for men leads to the decrease of arterial pressure by 3,4 mmHg in average (p=0,051), increase of total cholesterol concentration by 0,231 mmol/L (p=0,041), and in women — increase of HDL by 0,135 mmol/L (p=0,0024).Conclusion. Better cardiovascular health do have employed people comparing to unemployed: tendency is stronger in men. The results reflect common tendency of the higher level of health among employed young inhabitants comparing to unemployed.
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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 | 0.000 |
| 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".