175 FITNESS DOES NOT MITIGATE WEIGHT GAIN-ASSOCIATED BLOOD PRESSURE INCREASES IN CHILDREN
Bibliographic record
Abstract
Background: : Both excessive weight and weight gain are associated with a disproportionate increase in blood pressure in children. The purpose of this analysis was to determine if physical fitness and/or activity could mitigate changes in blood pressure associated with obesity or excessive weight gain. Methods: This study was carried out from an analysis of the Health Hearts cohort, a group of school children who had been prospectively followed for cardiometabolic status in relation to physical activity, physical fitness and weight status. The current cohort represented a sub-set for whom data was available for three consecutive years, 2008–2010. Yearly fitness was measured by Leger shuttle run, activity by accelerometry, and blood pressure by automated device. Results: This study included 565 children ages 9–16; 315 boys and 250 girls. As expected both BMI and waist:hip ratio correlated with systolic blood pressure (SBP) (r = .49, p<.0001; r = .47, p < .0001, respectively). Change in BMI also correlated with change in SBP (r = .19, p < .0001). Categorically, change in weight status correlated with change in blood pressure status (p = .005). Higher levels of activity and fitness were associated with lower BMI and SBP independently. However, in covariate analysis, BMI determined SBP independent of activity/fitness. Similarly, after adjustment for adiposity, physical activity/fitness did not influence SBP. Conclusions: Blood pressure in children is significantly influenced by adiposity, and while physical activity and fitness can influence the latter, they do not seem to independently reduce the blood pressure-raising effects of weight gain or obesity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".