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Background <p>Mental disorders are a major contributor to the global burden of disease, and poverty and income inequality are widely recognized as key social determinants of these conditions. In Iran, mental disorders rank as the second leading cause of disease burden. However, the association between economic indicators and mental disorders has not been sufficiently investigated. This study aimed to analyze the relationship between poverty, income inequality, and the prevalence of depression and anxiety across the 31 provinces of Iran.</p> Methods <p>This ecological, cross-sectional analysis utilized Iran’s provinces data in 2021. Poverty rates and income inequality (Gini coefficient) were derived from official national statistics, and age-standardized prevalence of depression and anxiety was obtained from Global Burden of Disease estimates. Nonlinear regression models were applied to examine potential curvilinear associations between economic conditions and mental health outcomes, and standard diagnostic procedures were used to assess model adequacy. All analyses were conducted in STATA 14.</p> Results <p>Income inequality was positively and significantly correlated with the prevalence of depression (ρ = 0.392, <i>p</i> = 0.029) and anxiety (ρ = 0.388, <i>p</i> = 0.031). Nonlinear regression analysis revealed a strong and positive association between poverty and both disorders (<i>p</i> &lt; 0.001), explaining 98.7% and 99.9% of the variance in depression and anxiety, respectively. Income inequality showed a significant nonlinear association with anxiety prevalence, while the gradient for depression was weaker and nonsignificant.</p> Conclusion <p>The results indicate that higher levels of poverty and income inequality are associated with greater prevalence of mental disorders in Iran. Based on these aggregate patterns, practical measures could include geographically targeted monitoring of mental health in provinces with high deprivation, prioritizing allocation of resources to regions with the steepest poverty–mental health gradients, and using the observed provincial disparities to guide the planning of social support and mental health programs in areas where economic disadvantage and mental health burden co-occur.</p>

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Social justice and mental health: nonlinear impacts of poverty and income inequality in Iran

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月31日

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  • Mahsa Mohammadalizadeh,
  • Mehdi Basakha,
  • Seyed Hossein Mohaqeqi Kamal,
  • Younes Akbari

摘要

Background

Mental disorders are a major contributor to the global burden of disease, and poverty and income inequality are widely recognized as key social determinants of these conditions. In Iran, mental disorders rank as the second leading cause of disease burden. However, the association between economic indicators and mental disorders has not been sufficiently investigated. This study aimed to analyze the relationship between poverty, income inequality, and the prevalence of depression and anxiety across the 31 provinces of Iran.

Methods

This ecological, cross-sectional analysis utilized Iran’s provinces data in 2021. Poverty rates and income inequality (Gini coefficient) were derived from official national statistics, and age-standardized prevalence of depression and anxiety was obtained from Global Burden of Disease estimates. Nonlinear regression models were applied to examine potential curvilinear associations between economic conditions and mental health outcomes, and standard diagnostic procedures were used to assess model adequacy. All analyses were conducted in STATA 14.

Results

Income inequality was positively and significantly correlated with the prevalence of depression (ρ = 0.392, p = 0.029) and anxiety (ρ = 0.388, p = 0.031). Nonlinear regression analysis revealed a strong and positive association between poverty and both disorders (p < 0.001), explaining 98.7% and 99.9% of the variance in depression and anxiety, respectively. Income inequality showed a significant nonlinear association with anxiety prevalence, while the gradient for depression was weaker and nonsignificant.

Conclusion

The results indicate that higher levels of poverty and income inequality are associated with greater prevalence of mental disorders in Iran. Based on these aggregate patterns, practical measures could include geographically targeted monitoring of mental health in provinces with high deprivation, prioritizing allocation of resources to regions with the steepest poverty–mental health gradients, and using the observed provincial disparities to guide the planning of social support and mental health programs in areas where economic disadvantage and mental health burden co-occur.