School children have leading risk factors for cardiovascular disease and diabetes: the Wausau SCHOOL project.
Bibliographic record
Abstract
INTRODUCTION: Risk factors for cardiovascular disease and diabetes acquired in childhood commonly persist in later life and are particularly strong predictors of subclinical atherosclerosis in young adults. A rising tide of obesity and other lifestyle-related risk factors threatens to negate much of the success achieved in the prevention and treatment of these diseases. The SCHOOL project (School Children Have Leading Risk Factors for Cardiovascular Disease and Diabetes), was designed to measure the prevalence and magnitude of known risk factors in school-age children in Wausau, Wis. METHODS: Demographic data, anthropomorphic measures, family health history, diet and activity indices, and numerous laboratory measures were collected from a representative sample of students in grades 2, 5, 8, and 11. RESULTS: Clinically important disturbances of lipid metabolism were very common, even in the youngest participants. Of the children studied, 39% had at least 1 lipid abnormality and 22% had 2 or more. Abnormal blood pressure, overweight, and cigarette smoking were present in 29%, 16%, and 11% respectively. While elevated fasting glucose levels were uncommon, insulin resistance was noted in 25% of the sampled population and nearly 50% of sampled children with a body mass index greater than the 85th percentile in this survey. The number of children with multiple risk factors rose dramatically with age. By 11th grade, 38% of those surveyed had 2 or more risk factors and 23% had 3 or more. CONCLUSIONS: Using conservative definitions, significant abnormalities of lipid metabolism and other risk factors for cardiovascular disease and diabetes were common in our children. Risk profiles in older adolescents were worse than in the younger students and similar to what would be expected for adults with known coronary heart disease. In our community there is a growing consensus that we must take advantage of the multiple opportunities that exist to favorably alter the lifestyle patterns that put our children at risk.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".