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Abstract
Objective: Genetic and neurobiological factors are considered to be the major causes of major depressive disorder (MDD). However, over last few years study results revealed that socio-demographic factors contribute a significant role in abnormal functional activity and recognized as major causative factors to the pathogenesis and severity of MDD. The aim of this study was to assess the socio-demographic characteristics of Bangladeshi MDD patients and to discover their role on the severity of disease. Material and Methods: A retrospective review of the case notes of psychiatry outpatients at Bangabandhu Sheikh Mujib Medical University (BSMMU) was carried out between Sep-Nov 2016. A total of 234 MDD patients (aged 18 to 60 years) were randomly recruited. Relevant information was obtained by collection of prescription details from the patients or their relatives by face to face interview. Results: Mean age and body mass index (BMI) were found 34.734 years (SEM ± 0.842) and 22.014 kg/m2 respectively. Among all respondents, 56% (133) were male and 44% (106) were female where mean income was 26.84 KBDT (Kilo Bangladeshi Taka) (SEM ± 0.749). Roughly 46% (111) patients were found to be below secondary level of education. Married people (56%) had a tendency to develop depression compare to unmarried people (36%). Urban residents (64%) are more prone to suffer from depression than rural residents (36%). There was mild depression in 28% (68), moderate in 37% (157), and severe in 14% (34) patients. Correlation analysis shows that age, sex, marital status, education, family income, and area of residence (p-values 0.004, 0.001, 0.000, 0.011, 0.000 and 0.000, respectively) are associated with the severity of disease. Moreover, among all significant correlations age, marital status and area of residence were positively correlated with the severity of MDD (r = 0.184, r = 0.238 and r = 0.256) while sex, education and family income were negatively correlated with the severity of depression (r = ﹣0.207, r = ﹣0.164 and r = ﹣0.722). Conclusion: Current study shows that age, gender, marital status, education, family income, and area of residence are associated with the severity of depression. Age, marital status and residence of MDD patients are positively correlated with the severity of disease while gender, education and family income are negatively correlated with the severity of depression. It is predicted that this study will be helpful for the management and assortment of MDD patients with more accuracy based on their socio-demographic features.
Highlights
Major depressive disorder (MDD) is considered as a persistent feeling of hopelessness or a lack of interest in external drives which is accompanied by low selfesteem and loss of pleasure or interest in daily events that unfavorably disturbs a person’s family, effort and personal life [1]
Current study shows that age, gender, marital status, education, family income, and area of residence are associated with the severity of depression
Marital status and residence of MDD patients are positively correlated with the severity of disease while gender, education and family income are negatively correlated with the severity of depression
Summary
Major depressive disorder (MDD) is considered as a persistent feeling of hopelessness or a lack of interest in external drives which is accompanied by low selfesteem and loss of pleasure or interest in daily events that unfavorably disturbs a person’s family, effort and personal life [1]. Medical journal Neuron mentioned that she reedited as a fundamental cause of depression with almost 3-fold increased risk in the first-degree relatives of persons with MDD compare to general population [2]. This means that the single biggest determining factor for depression is family tree, but there is a significant physiological and anatomical basis [3]. Risk factors for depressive illness in the elderly can be grouped into psychosocial, biological, personality characteristics, medication and socio-demographic factors [5]. Socio-demographic factors related with depression are low socio-economic status, poor educational background, and widowhood [10]
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