Neighborhood affluence is not associated with positive and negative valence processing in adults with mood and anxiety disorders: A Bayesian inference approach

Autor: Chunliang Feng, Katherine L. Forthman, Rayus Kuplicki, Hung-wen Yeh, Jennifer L. Stewart, Martin P. Paulus
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: NeuroImage: Clinical, Vol 22, Iss , Pp - (2019)
Druh dokumentu: article
ISSN: 2213-1582
DOI: 10.1016/j.nicl.2019.101738
Popis: Survey-based studies show that neighborhood disadvantage is associated with community reported mental health problems. However, fewer studies have examined whether neighborhood characteristics have measurable impact on mental health status of individuals in general and whether neighborhood characteristics impact positive/negative valence processing at both behavioral and brain levels. This study addressed these questions by investigating effects of census-based neighborhood affluence on self-reported symptoms, brain functions, and structures associated with positive/negative valence processing in a sample of individuals with mood and anxiety disorders (n = 262). Employing a Bayesian inference approach, our investigation demonstrates that neighborhood affluence fails to be associated with positive/negative valence processing measured across multiple modalities, with the only effects of neighborhood affluence identified in trait anxiety scores. These findings highlight that while community-based relationships between neighborhood characteristics and mental health problems are strong, it is much less clear that these characteristics have a measurable impact on the individual. Keywords: Neighborhood, Positive and negative valence systems, Mood and anxiety disorder, Bayes factor, Brain function and structure, Monetary incentive delay task
Databáze: Directory of Open Access Journals