Community Violence Exposure and Stress Reactivity in African American and Non-Latino White Adolescents With Overweight/Obesity
Bibliographic record
Abstract
Adolescents who experience community violence are exposed to toxic stressors at a critical period of growth and development. The purpose of this study was to examine the relationship between community violence exposure and stress reactivity in African American and non-Latino white adolescents with overweight/obesity. Fifty-one adolescents (47% female, 55% African American; aged 14–19) participated in this study. Community violence was assessed using the Survey of Children’s Exposure to Community Violence. Stress reactivity was assessed via salivary cortisol and alpha-amylase area under the curve (AUC) during a Trier Social Stress Test (TSST). Race was a significant predictor of alpha-amylase reactivity (β = 10740±3665, p = 0.0006), with a higher alpha-amylase AUC observed in African American compared to non-Latino white adolescents. There was also a significant difference in the relationship between community violence exposure and alpha-amylase AUC by race (β = −3561±1226, p = 0.007). At similar increases in violence exposure, African Americans demonstrated a significant decline in alpha-amylase AUC while non-Latino whites demonstrated a significant increase in alpha-amylase AUC. Neither race nor violence exposure were significant predictors of cortisol AUC and there were no significant differences in the relationship between community violence exposure and cortisol AUC by race (all p ’s > .05). These preliminary findings suggest exposure to community violence may act to exacerbate autonomic dysregulation in African American adolescents with overweight/obesity. Longitudinal studies are needed to confirm the mechanisms by which community violence exposure differentially impacts stress responses by race.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".