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. 2019 Mar 15:247:1-10.
doi: 10.1016/j.jad.2019.01.005. Epub 2019 Jan 5.

The prevalence, comorbidity and socio-demographic factors of depressive disorder among Iranian children and adolescents: To identify the main predictors of depression

Mohammad Reza Mohammadi  1 , Seyyed Salman Alavi  2 , Nastran Ahmadi  3 , Ali Khaleghi  4 , Koorosh Kamali  5 , Ameneh Ahmadi  6 , Zahra Hooshyari  7 , Fathola Mohamadian  8 , Nasrin Jaberghaderi  9 , Marzieh Nazaribadie  10 , Zahra Sajedi  11 , Zahra Farshidfar  12 , Nahid Kaviani  13 , Reza Davasazirani  14 , Abdulrahim Jamshidzehi Shahbakhsh  15 , Mahboubeh Roshandel Rad  16 , Koroush Shahbazi  17 , Rohollah Rostami Khodaverdloo  18 , Leyla Noohi Tehrani  19 , Mahdie Nasiri  20 , Fatemeh Naderi  21 , Arezou Kiani  22 , Mahboobeh Chegeni  23 , Seiedeh Maryam Hashemi Nasab  24 , Mahnaz Ghaneian  25 , Hosein Parsamehr  26 , Neda Nilforoushan  27 , Shahrokh Amiri  28 , Mahbod Fadaei Fooladi  29 , Soleiman Mohammadzadeh  30 , Ahmad Ahmadipour  31 , Nasrin Sarraf  32 , Seyed Kaveh Hojjat  33 , Mehriar Nadermohammadi  34 , Seyed-Ali Mostafavi  35 , Hadi Zarafshan  36 , Maryam Salmanian  37 , Alia Shakiba  38 , Simin Ashoori  39
Affiliations

The prevalence, comorbidity and socio-demographic factors of depressive disorder among Iranian children and adolescents: To identify the main predictors of depression

Mohammad Reza Mohammadi et al. J Affect Disord. .

Abstract

Background: Depressive disorders are a major public health problem in developed and developing countries. Recently, several risk factors have been described for depressive disorders in children and adolescents. The aim of the present study was to identify the main risk factors that can affect the incidence of depression in Iranian children and adolescents.

Methods: A total of 30,546 children and adolescents (between 6 and 18 years of age) participated in a cross-sectional study to identify the predictors of depressive disorders. Depressive disorders were assessed using the Persian version of the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS-PL). In addition, a demographic characteristics questionnaire was completed by parents of the participants. The data was analyzed using the SPSS22 software via performing the descriptive analysis and the multiple logistic regression analysis methods. P-values less than 0.05 were considered statistically significant.

Results: Results showed that a higher age (15-18), being female, and the father's unemployment were associated with an increased odds ratio for depressive disorders. The age of 10-14 (OR = 2.1; 95% CI, 1.57-2.81), the age of 15-18 (OR = 4.44; 95% CI, 3.38-5.83), female gender (OR = 1.44; 95% CI, 1.2-1.73) and the father's unemployment (OR = 1.59; 95% CI, 1.01-2.5) were significant positive predictors, whereas, the mother's job (as a housewife) (OR = 0.66; 95% CI, 0.45-0.96) and a history of psychiatric hospitalization of the father and mother (OR = 0.34; 95% CI, 0.15-0.78 and OR = 0.34; 95% CI, 0.14-0.84) were negative predictors for depressive symptoms.

Conclusion: Depressive symptoms are common in children and adolescents and are correlated with age and gender. The assessment of the prevalence of psychiatric disorders, especially the depressive disorders and their comorbidities, may help to prevent mood disorders in children and adolescents.

Keywords: Children and adolescents; Comorbidity; Depressive symptoms; Prevalence.

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