Big Mother or Small Baby: Which Predicts Hypertension?
Bibliographic record
Abstract
According to the Barker hypothesis, intrauterine growth restriction and premature delivery adversely affect cardiovascular health in adult life. The association of childhood hypertension as a cardiovascular risk factor and birth weight has been understudied. In a prospective cohort study, the authors evaluated the effect of birth weight, gestational age, maternal prepregnancy body mass index (BMI), and child BMI z score at the time of enrollment on the systolic and diastolic blood pressure (BP) z score in 3024 (1373 women) consecutive outpatient clinic patients aged 2.05 to 18.58 years. The latest National Health and Nutrition Examination Survey (NHANES III) was used to calculate the age-dependent z scores. The median z scores of BMI (+0.48, range -6.96-6.64), systolic BP (+0.41, range -4.50-6.73), and diastolic BP (+0.34, range -3.15-+6.73) were all significantly greater than the NHANES III reference population. Systolic BP z score did not correlate with birth weight or gestational age, but did correlate with maternal prepregnancy BMI (r=.090, P<.0001) and BMI z score (r=.209, P<.0001). Diastolic BP z score positively correlated with birth weight (0.037, P=.044), gestational age (r=.052, P=.005), BMI z score(r=.106, P<.0001), and maternal prepregnancy BMI (r=.062, P=.0007). In contrast to what would be expected from the Barker hypothesis, the authors found no negative correlation between BP z score and birth weight or gestational age. This study suggests that a high BMI, a big mom, and a high birth weight are more important risk factors for hypertension during childhood than low birth weight or gestational age.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".