High prevalence of hypertension among Iranian children and adolescents
Bibliographic record
Abstract
BACKGROUND: High blood pressure in children is a public health problem and the most important risk factor for cardiovascular disease at an older age. Several preliminary studies have been published regarding the prevalence of high blood pressure in which there was significant disparity. OBJECTIVE: This study aimed to estimate the prevalence of hypertension in Iranian children using the meta-analysis approach. METHODS: A systematic search of national and international databases was conducted through September 30, 2015, for population studies providing estimates on the prevalence of hypertension in Iranian children and adolescents. From the extracted prevalence rates, the heterogenic index of the studies was determined using Cochran's (Q) and Chi-squared (I2) tests, and on the basis of the heterogenetic results, a fixed or random effects model was employed to estimate the pooled prevalence rate of hypertension. Meta-regression was performed to determine those factors suspected of generating heterogeneity. RESULTS: Of 2360 articles initially identified, 17 were considered eligible. The meta-analyses included 79 231 children and adolescents aged between 3 and 18 years. The pooled prevalence of hypertension among children and adolescents was estimated to be 8.9% [95% confidence interval (95% CI): 7.5-10.3] in overall, 10.3% (95% CI: 7.5-12.6) in males and 9.1% (95% CI: 7.4-10.7) in females. The prevalence rates of high DBP and SBP were estimated at 6.6% (95% CI: 3.9-9.2) and 6.9% (95% CI: 5.6-8.2), respectively. CONCLUSION: There is a high prevalence of hypertension among Iranian children and adolescents. Although it is slightly higher among boys than girls, the difference was not statistically significant.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".