The association between road traffic noise exposure and blood pressure among children in Germany: The GINIplus and LISAplus studies
Bibliographic record
Abstract
Studies examining the association between road traffic noise and blood pressure in children are scarce. Nighttime noise levels and window orientations have not been considered in most previous studies. Investigate the association between road traffic noise exposure and blood pressure among children, and investigate the impact of bedroom window direction on this association. We measured blood pressure in 605 children aged 10 years from two Munich cohorts. Demographic and health information was collected by parent completed questionnaires. Road traffic noise levels were assessed by day-evening-night noise indicator "Lden" and night noise indicator "Lnight". Minimum and maximum levels within a 50 m buffer around child's home address were derived. Generalized additive models were applied to explore effect of noise levels on systolic and diastolic blood pressure (SBP and DBP). The orientation of child's bedroom window was considered in sensitivity analyses. DBP was significantly associated with the minimum level of noise during 24 h (Lden_min) and nightime (Lnight_min). Specifically, DBP increased by 0.67 and 0.89 mmHg for every 5 A-weighted decibels increase in Lden_min and Lnight_min. After adjusting for Lden_min (Lnight_min), DBP of children whose bedroom window faced the street was 1.37 (1.28) mmHg higher than those whose bedroom window did not, these children showed statistically significant increased SBP for Lden_min (3.05 mmHg) and Lnight_min (3.27 mmHg) compared to children whose bedroom window did not face the street. Higher minimum levels of weighted day-evening-night noise and nighttime noise around the home residence may increase a child's blood pressure.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".