Title:Decoding Mental Health: A Logistic Regression Analysis of Socio-Economic Indicators and Mental Health Quotient (MHQ) Across Nations
Volume: 3
Author(s): Sahab Kausar, Naurin Naqvi, Shabab Akbar, Sapna Ratan Shah, Kashif Abbas, Mudassir Alam*Nazura Usmani
Affiliation:
- Department of Biological Sciences, Indian Biological Sciences and Research Institute (IBRI), Noida, 201301, India
Keywords:
Global health security index, human development index, mental health, mental health quotient, logistic regression.
Abstract:
Introduction: This study aims to analyze the relationship between socio-economic
factors and mental health using data at a global index level. It examines how indicators such as
the Human Development Index (HDI), Global Health Security Index (GHSI), Climate Change
Performance Index (CCPI), and Multidimensional Poverty Index (MPI) influence the Mental
Health Quotient (MHQ).
Methods: Logistic regression models are employed to data from the Mental Health Million Project
(2021) and other socio-economic indices. The analysis investigates correlations between
MHQ and various factors, including economic participation, educational attainment, health and
survival , Political empowerment , GDP, HDI, GHSI, CCPI, and MPI.
Results: The results illustrate a positive relationship among MHQ and female economic participation
and opportunity ; it also implies mental health is connected to women workforce involvement.
However, educational attainment harms MHQ, probably because unmitigated pressure
leads to dim psychological health. Consequently, Health and Survival demonstrate positive connections
to MHQ, whereas political empowerment and principal development indicators (GDP,
HDI, GHSI, CCPI) show negative correlations. Belonging to MPI means a majority of the time,
the more MHQ, which denotes better mental health, is a reality but sometimes, even if you have
more MPI it does not mean worse mental health.
Discussion: Our analysis reveals that economic prosperity does not necessarily lead to better
mental or social well-being. Indicators like GDP, HDI, GHSI, and CCPI, which are often seen as
markers of national success, show a negative correlation with the MHQ. Interestingly, the MPI
exhibits a positive association with MHQ, suggesting that economic hardship does not always
equate to poorer mental health.
Conclusion: The study highlights the complex interplay between socio-economic development
and mental health. The results suggest that economic growth alone is insufficient to improve
mental well-being. Policymakers should adopt a holistic approach that balances economic, psychological,
and social factors to enhance global mental health outcomes.
