Socioeconomic and spatial distribution of depressive symptoms and access to treatment in Peru: A repeated nationwide cross-sectional study from 2014 to 2021

David Villarreal-Zegarra, Ali Al-kassab-Córdova*, Sharlyn Otazú-Alfaro, Baltica Cabieses

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Globally, evidence indicates that poverty and geographical setting influence the prevalence of depressive symptoms and access to treatment. Therefore, this study aimed to evaluate the socioeconomic and spatial distribution of depressive symptoms and treatment in Peru. Methods: We conducted an observational study based on the analysis of secondary data derived from the Peruvian Demographic and Health Surveys for 2014–2021. Using the Patient Health Questionnaire-9 on depressive symptoms, we estimated the Erreygers concentration index (ECI) to identify socioeconomic inequality in depressive symptoms and access to treatment. Spatial analyses were conducted using Global Moran's I, Kriging interpolation, hotspot analysis (Getis-Ord-Gi∗), and the Bernoulli-based Kulldorff spatial analysis. Results: The surveys included a total of 113,392 participants. Depressive symptoms exhibited only negative ECI values throughout the 2014–2021 period (pro-poor distribution), whereas access to treatment only displayed positive ECI values (pro-rich distribution). We identified two and four significant clusters in the southeastern areas of Peru in 2014 and 2021, respectively. Conclusions: Depressive symptoms were concentrated among the poorest, whereas access to treatment was remarkably concentrated among the wealthiest groups. A clustered spatial pattern was observed, and similar high-risk areas were identified. Social policies that address unequal socioeconomic and spatial distribution in depressive symptoms and treatment are required.

Original languageEnglish
Article number101724
JournalSSM - Population Health
Volume29
DOIs
StatePublished - Mar 2025

Keywords

  • Depression
  • Inequality
  • Peru
  • PHQ-9
  • Spatial analysis

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