Air pollution is associated with elevated HPA-Axis response to stress in anxious adolescent girls
Bibliographic record
Abstract
Research suggests that exposure to fine particulate air pollution (PM2.5) increases hypothalamic-pituitary-adrenal (HPA) axis activation in adults; it is unclear, however, whether PM2.5 is associated with HPA-axis functioning in psychosocial contexts, such as during the experience of social stress. One recent study of adolescents found that PM2.5 was associated with heightened autonomic reactivity to a social stress task, and that this association was strongest for adolescents with more severe internalizing symptoms. Here, we sought to replicate and extend these findings to HPA-axis stress responsivity in an independent sample of adolescent girls (N = 130). We estimated PM2.5 concentrations at each participant’s address using data from nearby air quality monitoring stations, and assessed participants’ anxiety symptoms. We measured salivary cortisol in response to a social stress task and characterized HPA-axis functioning by computing area under the curve with respect to ground (AUCg) and with respect to increase (AUCi). Controlling for demographic factors, we found that PM2.5 was associated with heightened HPA-axis stress responsivity (both AUCg and AUCi) for girls who reported more severe levels of anxiety. We did not find a main effect of PM2.5 on HPA-axis functioning. These findings suggest that anxious adolescents are particularly vulnerable to the adverse effects of PM2.5 exposure on biological sensitivity to social stress.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".