Author/Authors :
Hadianfar, Ali Department of Epidemiology and Biostatistics - Mashhad University of Medical Sciences, Mashhad, Iran , Esmaily, Habibollah Department of Epidemiology and Biostatistics - Mashhad University of Medical Sciences, Mashhad, Iran , Ghayour-Mobarhan, Majid Biochemistry of Nutrition Research Center - Mashhad University of Medical Sciences, Mashhad, Iran , Aghajani, Hossein Department of Sustainable Development Urban and Regional - Academic Center for Education - Culture and Research (ACECR) - Khorasan Razavi Organization, Mashhad, Iran , Saki, Azadeh Department of Epidemiology and Biostatistics - Mashhad University of Medical Sciences, Mashhad, Iran , Tayefi, Maryam Endocrinology and Metabolism Research Center - Mashhad University of Medical Sciences, Mashhad, Iran , Hosseini, Fatemeh Department of Statistics - Semnan University, Semnan, Iran , Sabouri, Samaneh Department of Epidemiology and Biostatistics - Mashhad University of Medical Sciences, Mashhad, Iran
Abstract :
Background: Depression is one of the most common mental disorders and it has the third rank of the cause of disability and has been considered to increase the years of life with disability in Iran.
Objectives: The purpose of this study was to map the geographical distribution and find hot spots of depression and its relation to demographic and socioeconomic factors in Mashhad.
Methods: A population-based cross-sectional study was conducted in Mashhad in 2010. In this study, 9704 individuals aged 35 to 65 years old were evaluated using Beck’s depression inventory-II. A generalized linear mixed model with a logit link was fitted for the spatial modeling of depression. R and GIS software was used for spatial analysis and disease mapping, respectively.
Results: The prevalence of depression was di erent in geographical areas, ranging from 13.29% to 26.67%. The spatial correlation in the prevalence of depression was significant. The fitted spatial model showed that the spatial adjusted associations between gender (P < 0.001), marital status (P < 0.001), socioeconomic status (P < 0.001), and depression were significant.
Conclusions: The significant spatial correlation shows that depression is spatially contagious and it is important to find its hot spots in the population. Thus developing health policy for prevention, early diagnostics, and treatment programs is preferred in these resource-limited areas.
