Abstract
Psychosis is associated with many forms of adversity, deprivation and living in urban areas. To investigate whether psychosis is part of a syndemic of multiple adversities. Drawing on UK Biobank (UKBB) data (Project ID: 57601), we sought to understand mechanisms by which childhood, recent/contemporary and place-based adversities might cluster and interact to be implicated in pathways by which psychoses evolve. We investigated the associations between adversities, potential mediating inflammatory markers and ICD-10 diagnoses (F20-F31) of psychotic disorders. We fitted logistic regression models initially including all relevant candidate variables and used backwards deletion to retain theoretically plausible and statistically significant (P < 0.05) associations with psychotic disorders. The candidate variables were entered in a partial least squares structural equation model (PLS-SEM) to test for syndemic interactions between risk factors. We tested whether the findings were sensitive to demographics, gender and ethnicity. We fitted a PLS-SEM including psychosis as a syndemic outcome, and identified three latent constructs: lifetime adversity, current adversity and biomarkers. Factor loadings were above 0.30, and all structural paths were significant (P < 0.05). There were moderate associations between lifetime adversity and current adversity (standardised coefficient s.c. = 0.178) and between current adversity and biomarkers (s.c. = 0.227). All three latent constructs showed small but significant associations with psychosis (s.c. < 0.04). Lifetime adversity and current adversity were more strongly associated among ethnic minorities (combined) than White British people. Our findings stress the importance of interactions between childhood and contemporary adversities in preventive and therapeutic interventions for psychotic disorders, especially among ethnic minorities.
Highlights
Psychosis is associated with many forms of adversity, deprivation and living in urban areas
The authors argued that ethnic minority and other marginalised groups are more likely to live in lower income households, often concentrated in relatively deprived areas affected by these unfavourable socioeconomic conditions. We explored such findings at a national level through a combined measure representing childhood adversity, low household income, adverse health behaviour in addition to biomarkers as possible intermediate mechanisms associated with psychosis
Our study has shown one possible way that synergies between components comprising measures of adversity and relatively high biomarker values may increase a person’s risk of transition to a clinical diagnosis of psychosis
Summary
Biobank (UKBB) data (Project ID: 57601), we sought to understand mechanisms by which childhood, recent/ contemporary and place-based adversities might cluster and interact to be implicated in pathways by which psychoses evolve. We investigated the associations between adversities, potential mediating inflammatory markers and ICD-10 diagnoses (F20–F31) of psychotic disorders. We fitted logistic regression models initially including all relevant candidate variables and used backwards deletion to retain theoretically plausible and statistically significant (P < 0.05) associations with psychotic disorders. The candidate variables were entered in a partial least squares structural equation model (PLS-SEM) to test for syndemic interactions between risk factors. We tested whether the findings were sensitive to demographics, gender and ethnicity
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