Abstract P316: Very Low Prevalence of Ideal Cardiovascular Health in Young Adults Studying at the Universite de Sherbrooke
Bibliographic record
Abstract
Introduction: In 2010, the American Heart Association (AHA) published a special report to define and set national goals for cardiovascular health promotion and disease reduction (2020 Strategic Impact Goals). Ideal cardiovascular health was defined based on seven metrics including both ideal health behaviors (nonsmoking, body mass index < 25 kg/m2, physical activity at goal levels, and pursuit of a diet consistent with current guideline recommendations) and ideal health factors (untreated total cholesterol < 200 mg/dL [5.2 mmol/L], untreated blood pressure < 120/ < 80 mm Hg, and fasting blood glucose 8h of overnight fasting, using standardized procedures. Resting blood pressure was measured in the sitting position (twice, using the average for analyses). Physical activity was assessed by a validated questionnaire. Dietary intake was assessed by 3-day food diary; the average per day or the estimations per week were used accordingly to the specific dietary component recommendation. Results: The cohort was composed of young adults (20.6 ± 2.9 years old), mainly of European origin (97.8%), and 74.6% were female. Overall, only one participant (0.4%) achieved ideal cardiovascular health (all seven ideal health metrics). Very few participants (2.2%) achieved ideal healthy diet score (4-5 components /5). Investigating individual dietary component, our results showed that 9.4% consumed ≥ 4.5 cups/day of fruits and vegetables, 25.7% had ≥ two servings/week of fish, 14.5% reported ≥ three servings/day of fiber-rich whole grains, 8.0% consumed < 1500g/day of sodium, and 75.4% reported drinking < 36oz / week of sugar-sweetened beverages. Concerning the other health metrics, 22.8% achieved the recommended level of physical activity, 93.8% were non-smokers, 75.7% had a BMI < 25kg/m2, 42.4% had a blood pressure in the ideal range ( < 120/ < 80 mmHg), 99.6% had a normal fasting glucose ( < 5.6 mmol/L), and 42.4% had a total cholesterol < 5.2 mmol/L. Conclusions: The prevalence of ideal cardiovascular health is very low, even in a population of young adults interested in healthy lifestyle. The low prevalence is mainly dependent on the healthy dietary score where the biggest challenges seem to be consumption of fruits and vegetables, and limiting sodium intake. Public health actions are seriously needed to improve these health metrics.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".