Study on the Impact of Poverty on Mental Illness: A Mendelian Randomization Analysis Based on the UK Biobank

This article aims to explore the causal relationship between poverty and mental illness. Although many studies have shown an association between low socioeconomic status and mental illnesses, most studies have failed to determine whether poverty directly leads to mental illness or whether mental illness causes poverty. Through data from the UK Biobank and the Psychiatric Genomics Consortium, this paper analyzes the causal relationships between nine mental illnesses (Attention Deficit Hyperactivity Disorder (ADHD), Anorexia Nervosa (AN), Anxiety Disorder (ANX), Autism Spectrum Disorder (ASD), Bipolar Disorder (BD), Major Depressive Disorder (MDD), Obsessive-Compulsive Disorder (OCD), Post-Traumatic Stress Disorder (PTSD), and Schizophrenia (SZ)) and poverty.

Research Background

As early as 1958, Hollingshead and Redlich discovered that people with lower socioeconomic backgrounds had higher incidences of severe and persistent mental illnesses and fewer opportunities for treatment. Over the following 50 years, similar social conditions persisted, affecting global mental health. Epidemiological studies worldwide have also demonstrated the relationship between mental health and socioeconomic status (SES), with mental illnesses being more common among lower social strata. Furthermore, research shows that income fluctuations are accompanied by changes in mental health. These studies, while revealing a strong correlation between poverty and mental illness, cannot definitively establish whether poverty directly causes mental illness or vice versa due to causal and confounding factors. Understanding this causal relationship is crucial for public health policy formulation, as it may help identify critical aspects of poverty and improve public mental health.

Source of Article

This study was completed by Mattia Marchi and several other researchers, involving institutions such as the University of Modena and Reggio Emilia and Erasmus MC. The article was published in the journal Nature Human Behaviour in 2024.

Research Process

This paper uses the Mendelian Randomization method to study the causal relationship between poverty and mental illness. The research process is as follows:

1. Construct a Public Poverty Factor: Utilize indicators such as Household Income (HI), Occupational Income (OI), and Social Deprivation (SD) to generate a poverty common factor through Genomic Structural Equation Modelling.
2. Multivariable Genome-Wide Association Study (GWAS): Conduct a multivariable GWAS on the poverty common factor defined by genetic markers to evaluate its association with HI, OI, and SD. This process identified 90 significant independent loci.
3. Mendelian Randomization Analysis: Use the two-sample MR method to explore the causal relationships between the poverty common factor and the nine mental illnesses, adjusting for the impact of Cognitive Ability (CA).

Main Results

1. Causal Impact of Poverty on Mental Illness:

   • The poverty common factor shows significant causal effects on ADHD, anxiety disorder, MDD, PTSD, and SZ but shows negative correlation effects on AN and OCD.
   • Combining the separate analyses of HI, OI, and SD, the impact of poverty on certain mental illnesses is consistent. For example, when using HI as the poverty indicator, ADHD and SZ show bidirectional causal effects, while MDD and AN show unidirectional causal effects.

2. Reverse Causal Relationship:

   • ADHD and SZ show significant causal effects on the poverty common factor, especially in reverse analyses.
   • A similar bidirectional causal effect was found with OI and SD in relation to ADHD and SZ.

3. Role of Cognitive Ability:

   • In the multivariable MR model, results adjusted for CA show that the direct effect of the poverty common factor on mental illnesses is reduced, but the causal effects on ADHD, AN, and anxiety disorder still exist.
   • This indicates that most of the genetic effects between poverty and mental illness are mediated through CA, but there are also independent effects beyond CA.

Conclusion and Significance

Based on data from 18 GWAS studies, this research confirms the causal relationship between poverty and certain mental illnesses. The combination of Genomic Structural Equation Modelling and Mendelian Randomization methods provides evidence for the bidirectional causal relationship between poverty and ADHD and SZ. The results suggest that the role of poverty in the onset of mental illness is multifaceted, involving material, psychological, behavioral, and biological pathways.

These findings offer a deeper understanding of the relationship between socioeconomic inequality and mental health and highlight key areas of focus for future research and public health policy formulation. Particularly, improving education and cognitive ability may play a crucial role in enhancing socioeconomic status and mental health.

Additionally, these research results emphasize the need for further dissection of the roles of poverty and mental illness and utilizing these insights to enhance public mental health. Amidst increasing global income inequality and rising mental illness incidence, this research holds significant importance.

Research Highlights

• Novelty of Research Method: Combining Genomic Structural Equation Modelling and Mendelian Randomization methods provides strong evidence for the causal relationship between poverty and mental illness.
• Breadth and Diversity of Data: Utilizing large-scale data from the UK Biobank and the Psychiatric Genomics Consortium, covering various types of mental illnesses.
• Emphasis on the Role of Cognitive Ability: Highlights the role of cognitive ability in mediating the causal relationship between poverty and mental illness, providing a basis for future educational and cognitive interventions.

This research lays a solid foundation for further exploring the complex association between poverty and mental illness, providing important scientific evidence for future public health and socioeconomic policy formulation.