ArticleDiseases (Basel, Switzerland)2025
Combined Effects of Social and Behavioral Factors on Stress and Depression.
Article in Diseases (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Article
- When stress Meets severity: dual pathways to depression among people with disabilities.Social psychiatry and psychiatric epidemiology · 2026Article
- Targeting the Neuro-Immune Axis in Next-Generation Oncology: Discovery and Validation of βOncology research · 2026Review
- Individual Health Management (IHM) for Stress-A Randomised Controlled Trial (TALENT II Study).Healthcare (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
backgroundChronic stress, driven by the persistent activation of the body's stress response system-including the sympathetic nervous system and hypothalamic-pituitary-adrenal (HPA) axis-has far-reaching effects on both physical and mental health. This study examines the combined effects of social and behavioral factors on a latent variable consisting of stress and depressive symptoms, using a comprehensive framework to explore the complex interactions of these factors.
methodsLeveraging data from the United States Centers for Disease Control and Prevention's (CDC's) National Health and Nutrition Examination Survey (NHANES), we operationalized allostatic load-a measure of cumulative physiological stress-through 10 biomarkers spanning cardiovascular, inflammatory, and metabolic systems. Depressive symptoms were measured via the Patient Health Questionnaire-9 (PHQ-9), and a latent variable capturing the shared variance between stress and depressive symptoms was derived using factor analysis. To assess the influence of social (income and education) and behavioral (alcohol consumption and smoking) factors on this latent variable, we employed Bayesian Kernel Machine Regression (BKMR), allowing us to examine potential non-linear and interactive effects among these predictors.
resultsOur results revealed a significant positive association between allostatic load and depressive symptoms across the sample, regardless of ethnic background. Alcohol consumption emerged as a key behavioral factor, with significant positive associations with stress. Conversely, education showed a protective effect, with higher education levels associated with decreased stress and depressive symptoms.
conclusionsThese findings underscore the importance of addressing both social determinants and behavioral risk factors in mitigating the cumulative impacts of stress and depressive symptoms. By highlighting the roles of alcohol consumption and education, this study provides insights that can inform public health strategies aimed at promoting resilience and reducing stress-related health disparities.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.