Socioeconomic indicators and their impact on Mental Health: A Data-Driven Approach using Python and R

Background: Economic wealth is often thought to improve mental health; however, this relationship is complex and poorly understood. This study investigates how societal indices and economic variables influence mental health, challenging popular preconceptions.Methods: Using advanced statistical tools in Python and R, we analyzed associations between mental health metrics and key societal indices, including Gross Domestic Product (GDP), Human Development Index (HDI), Global Health Security Index (GHSI), Climate Change Performance Index (CCPI), and Multidimensional Poverty Index (MPI). Mental Health Quotient (MHQ) served as the primary outcome variable.Results: Our data showed that GDP, HDI, GHSI, and CCPI all had negative relationships with mental health. Furthermore, positive relationships were found between MPI and MHQ, implying that economic distress is not always associated with poor mental health.Conclusion: This study emphasizes the necessity of balanced societal advancement, which goes beyond economic and infrastructure growth. Social, economic, and environmental issues all influence mental health outcomes, necessitating a transformation in how societal development is assessed and sought.