Sleep duration and blood pressure in Spanish children with obesity
Bibliographic record
Abstract
Abstract Introduction: Hypertension is a public health problem and its prevalence in children is on the rise, often continuing into adulthood and increasing the risk related cardiovascular complications. Sleep plays an essential role in children's growth and several studies suggest that insufficient sleep duration is associated with hypertension in adults. However, few studies have evaluated this association in children. Thus, the aim of the study is to ascertain whether the sleep duration is a risk factor for elevated blood pressure (BP) in children. Methods: We studied 776 children (5–18 years old), (46.7% male, 78.8% 5–13 years, 73.6% overweight/obesity). Weight and height were measured and body mass index (BMI) was calculated. BP was measured with an electronic manometer to find a 25.3% of children with an elevated systolic BP (SBP, > P90 th ) and 14% with an elevated diastolic BP (DBP, > P90 th ) (Task Force 2017). Sleep duration was assessed by asking the parents “¿How many hours does your child sleep in a typical weekday?”. Weekday sleep hours were considered since they are more representative of children's routines than weekend hours. Hours were converted into a dichotomous variable based on the fulfillment or not of the “Canadian 24-Hour Movement Guidelines for Children and Youth recommendations”: 9–11 hours for 5- to 13-year-olds; 8–10 hours for 14- to 17-year-olds. A spearman correlation analysis was performed between sleep duration, SBP and DBP. Then, a general linear model analysis adjusted for BMI Z-score was done to evaluate differences in SBP and DBP between children following the sleep recommendations. Analyses were stratified by sex and age range (5–13 and 14–17). Results: In girls 5–13 years, we found a significant negative correlation between sleep duration and body mass index (BMI) (r = -0.226, p = 0.000) and between sleep and systolic BP (r = -0.188, p = 0.001). Girls 5–13 years not following sleep recommendations showed significantly higher SBP values than those who followed the recommendations (112 ± 11 mmHg vs. 106 ± 12 mmHg, p = 0.007), independently of BMI. No significant differences were observed in girls 14–17 years nor in males. Discussion: In the present study, we show that girls 5–13 years with shorter sleep duration show increased SBP values independently of BMI, in contrast to previous studies which showed similar associations that disappeared when adjusting for BMI. Our results support the need for wider strategies in population education so that sleep recommendations are followed by children in the general population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".