Publication type
Journal Article
Authors
Publication date
April 9, 2026
Summary:
Despite extensive attention on psychological distress and socioeconomic disadvantage, no study has mapped conditional associations between specific distress symptoms and disadvantage across both household and neighborhood levels. Here, we estimated a preregistered network analysis to examine the conditional associations between eight specific aspects of psychological distress on the one hand and 15 household- (e.g., household crowding, income, financial ability to keep house warm in winter) and neighborhood-level (e.g., area-level deprivation, perceptions of pollution, vandalism) disadvantage variables on the other, using the U.K. Household Longitudinal Study (N = 15,851). Limitations on social activities and daily roles as a result of emotional and physical health problems were most strongly interconnected with socioeconomic disadvantage while feeling depressed showed no conditional associations with disadvantage. Being unable to afford replacement of large electrical items was the disadvantage variable most associated with distress, including sleep loss and worthlessness. Distress variables were associated with aspects of disadvantage across both the neighborhood and household levels, although the latter associations were more frequent and stronger. Our findings highlight a core role for functional impairments due to emotional problems and underline the need to assess and address the psychological consequences of socioeconomic circumstances across multiple levels.
Published in
American Psychologist
DOI
https://dx.doi.org/10.1037/amp0001705
ISSN
0003066
Subjects
Notes
Online Early
© 2026 The Author(s)
Open Access
Open Access funding provided by University of Leicester: This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0; https://creativecommons.org/licenses/by/4.0). This license permits copying and redistributing the work in any medium or format, as well as adapting the material for any purpose, even commercially.
Code: The preregistration (including the variable selection approach and analysis plan) and R code to reproduce the results of this study are accessible on the Open Science Framework at https://osf.io/9aqkv/ (Bridger, 2025). Data from the UKHLS are openly accessible through the U.K. Data Service at https://ukdataservice.ac.uk/.
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