Difficult Family Relationships, Residential Greenspace, and Childhood Asthma
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Both the social environment and the physical environment are increasingly recognized as important to childhood diseases such as asthma. This study tested a novel hypothesis: that living in areas high in greenspace may help buffer the effects of difficult family relationships for children with asthma. METHODS: A total of 150 children (ages 9–17), physician-diagnosed with asthma, participated in this study. To assess difficulties in parent-child relationships, parents and children completed measures of harsh/inconsistent parenting and parental hostility. Residential greenspace was calculated by using satellite-derived Normalized Difference Vegetation Index with a buffer of 250 m around the residential address. Outcomes included both clinical and biological measures: asthma control and functional limitations, as well as airway inflammation (fractional concentration of exhaled nitric oxide) and glucocorticoid receptor expression in T-helper cells. RESULTS: After controlling for potential confounding variables, including family income, child demographics, and child medical variables, few main effects were found. However, interactions between residential greenspace and difficult family relationships were found for asthma control (P = .02), asthma functional limitations (P = .04), airway inflammation (P = .007), and the abundance of glucocorticoid receptor in T-helper cells (P = .05). These interactions were all in a direction such that as the quality of parent-child relationships improved, greenspace became more strongly associated with better asthma outcomes. CONCLUSIONS: These findings suggest synergistic effects of positive environments across the physical and social domains. Children with asthma appear to benefit the most when they both live in high greenspace areas and have positive family relationships.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".