Factores de riesgo cardiovascular en comunidades urbana y rural: Tinaquillo, Venezuela
Bibliographic record
Abstract
OBJECTIVE: To compare the frequency of major clinical, biochemical and anthropometric cardiovascular risk factors between a rural community and an urban community from Tinaquillo, Venezuela. METHOD: 118 individuals older than 18 years (52 of the urban community and 66 of the rural community) were included; their weight, height, waist circumference, blood pressure, blood glucose and lipid profile were assessed. A survey to measure personal history of cardiovascular disease and lifestyle was applied. RESULTS: About 60 % of the individuals of the rural community were either obese or overweight; similar figures were obtained in the urban community with no statistically significant differences. Almost half of the participants had abdominal obesity, and also a significant frequency of individuals with low HDLc (greater than 70 %) was observed. It should be noted that although low percentages of hypertriglyceridemia were obtained, they were significantly higher in the rural community (chi-square=4.82, p=0.0281). The opposite occurs with the frequency of smoking, which is statistically higher in the urban community (chi-square=4.48, p=0.0342). CONCLUSIONS: The results show a high prevalence of cardiovascular risk factors in both communities. Consequently, health promotion programs should reach out to rural communities, as the risk of cardiovascular disease is similar to that of the urban community, who are equally prone to acquire unhealthy habits.
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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 | 0.001 |
| 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) | 0.002 | 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".