ArticleSSM - population health2025
Socioeconomic and spatial distribution of depressive symptoms and access to treatment in Peru: A repeated nationwide cross-sectional study from 2014 to 2021.
Article in SSM - population health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Pathways Between Family Socioeconomic Status and Early Childhood Development: Evidence From Andean Peru.Developmental science · 2026Article
- Adaptation to San Martín Quechua and psychometric analysis of the Patient Health Questionnaire (PHQ-9) in Peruvian adults.BMC psychology · 2026Article
- Spatial patterns and determinants of anxiety, depressive symptoms and their co-occurrence among currently married women of reproductive age in Bangladesh.Global mental health (Cambridge, England) · 2026Article
- Urban riverbank green spaces as therapeutic environments: Examining the psychosocial benefits of square dance in aging populations in China.SSM - population health · 2025Article
- Introduction to the special issue collection, How and why are health inequalities changing over time?SSM - population health · 2025Article
- Trends and economic inequalities in obesity prevalence in Ghana: a cross-sectional study spanning 2008-2022.Journal of health, population, and nutrition · 2025Article
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Authors and funding
4 authors.
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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.
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