Prevalence of high blood pressure among Canadian Children: 2017 American Academy of Pediatrics guidelines with the Canadian Health Measures Survey
Bibliographic record
Abstract
BACKGROUND: We assess the impact of the 2017 American Academy of Pediatrics (AAP) guidelines on the prevalence of high blood pressure (BP) in generally healthy Canadian children and identify risk factors associated with high BP (elevated, stage 1, or stage 2 at a single visit). METHODS: A cohort of 7,387 children aged 6 to 18 years in the Canadian Health Measures Survey (CHMS, 2007 to 2015) had BPTru oscillometry with centiles and stages assigned using both the 2017 AAP guidelines and the 2004 Fourth Report from the National Institute of Health/National Heart Lung and Blood Institute (NIH/NHLBI). RESULTS: Although both shifted upwards significantly, mean population systolic BP and diastolic BP percentiles are now 24.2 (95% confidence interval: 23.3 to 25.2) and 46.4 (45.3 to 47.6). As a result, the population prevalence of high BP increased from 4.5% (3.9 to 5.2, NIH/NHLBI) to 5.8% (5.0 to 6.6, AAP), less than in US children measured by auscultation (14.2%, 13.4 to 15.0). Children with high BP were more likely to be overweight/obese, to be exposed to prenatal/household smoking, and to have hypertriglyceridemia, without differences in dietary salt, infant breastfeeding, neonatal hospitalizations, or exercise frequency. CONCLUSION: The 2017 AAP guidelines increase the prevalence of high BP in Canadian children; Canadian prevalence appears lower than in the USA. This may reflect differences in measurement methods or in the prevalence of childhood overweight/obesity between countries, that is, 31.1% (28.9 to 33.3) versus 40.6% (39.5 to 42.0), respectively. Those with high BP were more likely to have other cardiac risk factors, including overweight/obesity, prenatal/household smoking exposure, and hypertriglyceridemia.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".