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Ann Epidemiol. 2016 Feb;26(2):93-99.e2. doi: 10.1016/j.annepidem.2015.11.002. Epub 2015 Nov 14.

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

Author information

1
CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; Mental Health Working Group, Universidad Peruana Cayetano Heredia, Lima, Peru.
2
CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; Department of Medicine, School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru. Electronic address: Jaime.Miranda@upch.pe.
3
CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; International Health Department, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD; Área de Investigación y Desarrollo, Asociación Benéfica PRISMA, Lima, Peru.
4
GIS and Health Informatics Laboratory, Department of Geography, Simon Fraser University, Burnaby, British Columbia, Canada.
5
CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru.
6
CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru.
7
CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; Department of Medicine, School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru; Department of Pediatrics, Instituto Nacional de Salud del Niño, Lima, Peru; Department of Pediatrics, School of Medicine, Universidad Nacional Mayor de San Marcos, Lima, Peru.
8
CRONICAS Centre of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; International Health Department, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD; Área de Investigación y Desarrollo, Asociación Benéfica PRISMA, Lima, Peru; Division of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, MD.

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 = 16.2%-17.8%). Three clusters with high prevalence of depressive symptoms (primary cluster: RR = 1.82; P = .003 and secondary: RR = 2.83; P = .004 and RR = 5.92; P = .01), and two clusters with significantly low prevalence (primary: RR = 0.23; P = .016 and secondary: RR = 0; P = .035), were identified. Further adjustment by potential confounders confirmed the high prevalence clusters but also identified newer ones.

CONCLUSIONS:

Screening strategies for depression, in combination with mapping techniques, may be useful tools to target interventions in resource-limited areas.

KEYWORDS:

Depression; Hotspot; Mental health; Peru; Spatial clustering

PMID:
26654102
PMCID:
PMC4792677
DOI:
10.1016/j.annepidem.2015.11.002
[Indexed for MEDLINE]
Free PMC Article

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