A Study to Correlation of Socio-Demographic and Clinical Variables with Depression in Urban Population
Journal Title: Journal of Medical Science And clinical Research - Year 2018, Vol 6, Issue 6
Abstract
Background: Depression is disorder of enormous public health importance as it affects about 350 million people worldwide, by adversely impacting on their quality of life. Well-designed large scale community based research on the prevalence and socio demographic risk factors of depression in different regions of India is indispensable to formulate public health preventive programs and policy decisions. The present study was an effort to provide much needed information on the prevalence and correlates of depression in Sikkim, a North Eastern state of India where such data is scare. Methodology: A cross-sectional study was done among adults in the urban metropolitan area of Tadong, in the capital city of Gangtok, Sikkim from May 2013 to August 2014. Systematic randomized sampling design was chosen with every tenth house selected for the study. Total number of subjects were 400 included in this study. Sociodemographic variables like age, gender, marital and socio-economic status were collected. Clinical variables that were collected include past history of psychiatric illness, substance abuse, family history of psychiatric illness and comorbid chronic pain symptoms. Depressive episode was diagnosed clinically using ICD -10 criteria. Severity of depression was assessed using Hamilton rating scale (17 items) for depression. Statistical analysis using Chi square test for determining the association between categorical variables was performed using SPSS software. Results: A prevalence rate of 17.25% (n=69) with female to male gender ratio of 1.29:1 was found. This study estimated the prevalence of geriatric depression to be 18.75 (n=6). A significant association of depression with age (p=0.012) was found, with decreasing age associated with increasing prevalence of depression. A non- significant association was observed between depression and gender (p=0.322), marital status (p= 0.101) socio-economic status (p=0.063). Among the clinical variables assessed the results revealed a significant association of depression with family history of psychiatric illness (p=0.003) and chronic pain symptoms (p=0.010) and a non-significant association of depression with past history of psychiatric illness (p=0.006) and substance abuse (p=0.18). Conclusion: We concluded that regular screening programs and medical camps in the community should include psychiatric services or psychiatric screening instruments to identify patients with depression, especially patients with chronic somatic pain.
Authors and Affiliations
Dr Bhanu Pratap Singh
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