Spatial distribution of individuals with symptoms of depression in a periurban area in Lima: an example from Peru

Abstract

Purpose
To map the geographical distribution and spatial clustering of depressive symptoms cases in an area of Lima, Peru.
Methods
Presence of depressive symptoms suggesting a major depressive episode was assessed using a short version of the Center for Epidemiologic Studies Depression Scale. Data were obtained from a census conducted in 2010. One participant per selected household (aged 18 years and above, living more than 6 months in the area) was included. Residence latitude, longitude, and elevation were captured using a GPS device. The prevalence of depressive symptoms was estimated, and relative risks (RRs) were calculated to identify areas of significantly higher and lower geographical concentrations of depressive symptoms.
Results
Data from 7946 participants, 28.3% male, mean age 39.4 (SD, 13.9) years, were analyzed. The prevalence of depressive symptoms was 17.0% (95% confidence interval 1⁄4 16.2%e17.8%). Three clusters with high prevalence of depressive symptoms (primary cluster: RR 1⁄4 1.82; P 1⁄4 .003 and secondary: RR 1⁄4 2.83; P 1⁄4 .004 and RR 1⁄4 5.92; P 1⁄4 .01), and two clusters with significantly low prevalence (primary: RR 1⁄4 0.23; P 1⁄4 .016 and secondary: RR 1⁄4 0; P 1⁄4 .035), were identified. Further adjustment by potential confounders confirmed the high prevalence clusters but also identified newer ones.
Conclusion
Screening strategies for depression, in combination with mapping techniques, may be useful tools to target interventions in resource-limited areas.

Publication
Annals of Epidemiology
Gabriel Carrasco-Escobar
Gabriel Carrasco-Escobar
Assistant Professor

My research interests include infectious diseases epidemiology, causal inference, global health, Climate Change, Data Science, Urban Health, and Geospatial modeling & viz.

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