LIFESTYLE AND SOCIOECONOMIC DETERMINANTS OF BLOOD PRESSURE IN SCHOOL-AGED CHILDREN AND ADOLESCENTS: PP.37.506
Bibliographic record
Abstract
Objective: To examine the associations between childhood and adolescence lifestyle/socioeconomic status (SES) and blood pressure (BP). Design and Methods: We performed a cross-sectional, nation-wide survey of BP and SES in Poland. Study participants (children and adolescents 6.5–18.5 years of age) were randomly selected using two-stage sampling; schools were primary sampling units. Medical history, lifestyle and socioeconomic data were collected by a questionnaire obtained during the BP measurement. Systolic and diastolic BP (SBP, DBP) and mean arterial pressure (MAP) were measured in triplicate using oscillometric device Datascope Accutor Plus. BP (average of second and third measurement) was adjusted for age and sex by converting it into Z-scores with the use of internal standard. Crude BP Z-scores were adjusted for confounders: weight and BMI using multiple linear regression. Differences of mean Z-scores by categories of explanatory lifestyle/SES variables were analyzed using Student's t-test (in case of variable with two categories) or analysis of variance (ANOVA, in case of variable with more than two categories). Differences in SBP, DBP and MAP were tested separately. Results: There were 16 976 children and adolescents (8133 boys), aged 7–18 years, free of chronic diseases and medication, enrolled in the study from November 2007 to November 2009. Table 1 shows difference in BP according to SES characteristics.Ordinal lifestyle/SES explanatory variables having more than two categories: PA, mother/father education, income per capita showed dose-response type of association with BP: BP decreasing with improved socioeconomic status or increasing physical activity. Conclusions: A low family socioeconomic status and sedentary lifestyle are associated with higher BP in children and adolescents. There were no significant differences in BP in relation to family size, exposure to TV or computer in room, in which the child sleeps.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".