Abstract

The mental health of slum residents is under-researched globally, and depression is a significant source of worldwide morbidity. Brazil's large slum-dwelling population is often considered part of a general urban-poor demographic. This study aims to identify the prevalence and distribution of depression in Brazil and compare mental health inequalities between slum and non-slum populations. Data were obtained from Brazil's 2019 National Health Survey. Slum residence was defined based on the UN-Habitat definition for slums and estimated from survey responses. Doctor-diagnosed depression, Patient Health Questionnaire (PHQ-9)-screened depression and presence of undiagnosed depression (PHQ-9-screened depression in the absence of a doctor's diagnosis) were analysed as primary outcomes, alongside depressive symptom severity as a secondary outcome. Prevalence estimates for all outcomes were calculated. Multivariable logistic regression models were used to investigate the association of socioeconomic characteristics, including slum residence, with primary outcomes. Depressive symptom severity was analysed using generalised ordinal logistic regression. Nationally, the prevalence of doctor diagnosed, PHQ-9 screened and undiagnosed depression were 9.9% (95% confidence interval (CI): 9.5-10.3), 10.8% (95% CI: 10.4-11.2) and 6.9% (95% CI: 6.6-7.2), respectively. Slum residents exhibited lower levels of doctor-diagnosed depression than non-slum urban residents (8.6%; 95% CI: 7.9-9.3 v. 10.7%; 95% CI: 10.2-11.2), while reporting similar levels of PHQ-9-screened depression (11.3%; 95% CI: 10.4-12.1 v. 11.3%; 95% CI: 10.8-11.8). In adjusted regression models, slum residence was associated with a lower likelihood of doctor diagnosed (adjusted odds ratio (adjusted OR): 0.87; 95% CI: 0.77-0.97) and PHQ-9-screened depression (adjusted OR: 0.87; 95% CI: 0.78-0.97). Slum residents showed a greater likelihood of reporting less severe depressive symptoms. There were significant ethnic/racial disparities in the likelihood of reporting doctor-diagnosed depression. Black individuals were less likely to report doctor-diagnosed depression (adjusted OR: 0.66; 95% CI: 0.57-0.75) than white individuals. A similar pattern was observed in Mixed Black (adjusted OR: 0.72; 95% CI: 0.66-0.79) and other (adjusted OR: 0.63; 95% CI: 0.45-0.88) ethnic/racial groups. Slum residents self-reporting a diagnosis of one or more chronic non-communicable diseases had greater odds of exhibiting all three primary depression outcomes. Substantial inequalities characterise the distribution of depression in Brazil including in slum settings. People living in slums may have lower diagnosed rates of depression than non-slum urban residents. Understanding the mechanisms behind the discrepancy in depression diagnosis between slum and non-slum populations is important to inform health policy in Brazil, including in addressing potential gaps in access to mental healthcare.

Highlights

  • Mental health morbidities, including major depressive disorder, account for an ever-increasing proportion of the global disease burden (Liu et al, 2020)

  • Most individuals were under age 45, with 18.6% younger than 25

  • The prevalence of Patient Health Questionnaire-9 (PHQ-9)-screened depression was higher at 10.8%

Read more

Summary

Introduction

Mental health morbidities, including major depressive disorder (depression), account for an ever-increasing proportion of the global disease burden (Liu et al, 2020). Depression is estimated to affect nearly 280 million people globally (Global Burden of Disease Collaborative Network, 2020). This burden is predominantly focused in low- and middle-income countries In 2019 the World Health Organization (WHO) launched a ‘Special Initiative for Mental Health’ (World Health Organization, 2019) aimed at expanding health coverage for common mental disorders, including depression, as a necessity for achieving Universal Health Coverage

Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call