An epidemiological survey of psychiatric disorders in Iran: Kermanshah

Shirzadi, Maryam; Jozanifard, Yazdan; Eskandari, Soudabeh; Farhang, Sara; Khazaei, Habibollah

doi:10.1016/j.ajp.2019.04.004

Cited by 13 publications

(12 citation statements)

References 4 publications

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“…In an epidemiological study of psychiatric disorders in 2001, the prevalence of depression among Iran's general population was 3.31% (2.2% among men) (Mohammadi et al, 2005). In an epidemiological survey of psychiatric disorders in Kermanshah province, the prevalence of MDD was 8.3% (Shirzadi et al, 2019). The prevalence of MDD in Iran seems to be within the range of the figures reported for other countries.…”

Section: Discussionmentioning

confidence: 68%

The prevalence of depression among iran‐iraq war veterans, combatants and former prisoners of war: A systematic review and meta‐analysis

et al. 2021

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B y exposing individuals to trauma, wars can cause a host of psychiatric disorders. This study aimed to collect and compare the studies conducted to estimate the prevalence of depression among veterans, former prisoners of war (POWs) and military personnel in the Iran-Iraq war (1980)(1981)(1982)(1983)(1984)(1985)(1986)(1987)(1988). In this systematic review, a search was conducted using relevant keywords in major national and international databases, personal archives and national academic libraries. We screened 135 records using their abstracts and selected a total of 56 studies for full-text review. Eventually, 19 studies were included in our systematic review and meta-analysis. The estimated pooled prevalence of depression among Iranian veterans and POWs was 22.4% (95% confidence interval = 15.0-32.0). Although the results indicated disparities in the prevalence of depression among veterans and POWs, the aggregate estimated prevalence was much higher than what has been reported for military personnel. Effective policies and strategies are required for prevention and treatment of depression and related psychiatric complications among veterans and former POWs.

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Section: Discussionmentioning

confidence: 68%

The prevalence of depression among iran‐iraq war veterans, combatants and former prisoners of war: A systematic review and meta‐analysis

et al. 2021

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“…Iran is a Middle Eastern country in which the majority of its population, particularly those living in urban areas, have experienced a rapid nutrition transition in recent years, characterized by adopting Western-style unhealthy dietary patterns (i.e., high-fat dairy products, refined grains, red or processed meats, sweets, salty snacks, and fried potatoes) instead of traditional healthy ones (i.e., diets rich in fruits, vegetables, nuts and legumes, low-fat dairy products, and whole grains) ( Ghassemi et al, 2002 ; Mehio Sibai et al, 2010 ). Notably, during this period, there was a rapid rise in the prevalence of major diet-related non-communicable diseases, such as obesity, cardiovascular disease, and diabetes mellitus among Iranian adults ( Mohammadi et al, 2005 ; Esteghamati et al, 2009 ; Mehio Sibai et al, 2010 ; Sharifi et al, 2015 ; Shirzadi et al, 2019 ).…”

Section: Discussionmentioning

confidence: 99%

The Relationship between Functional Constipation and Major Dietary Patterns in Iranian Adults: Findings from the Large Cross-Sectional Population-Based SEPAHAN Study

Gholizadeh

Keshteli

Esmaillzadeh

et al. 2021

Prev. Nutr. Food Sci.

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Although associations between dietary patterns and risk of chronic conditions have recently received increased attention, few studies have examined the relationship between major dietary patterns and risk of constipation. We collected dietary data using a validated dish-based, 106-item semi-quantitative Food Frequency Questionnaire on 4,763 adults aged 18∼55 years. Data on anthropometric measures were collected through self-administered questionnaires. Functional constipation was defined based on the Iranian validated version of Rome III. Factor analysis followed by a varimax rotation was applied to derive major dietary patterns from 39 predefined food groups, and logistic regression was used for association analysis. Three major dietary patterns were extracted: traditional (TD), fruit and vegetables dominant (FVD), and Western (WD). The association between TD and constipation was not significant for both genders and for the total sample. However, in the crude model and the fully adjusted model, poor adherence to the FVD was associated with a higher risk of constipation in men and in the total sample. In addition, we observed a significantly lower risk of constipation in the total sample and in female participants with low adherence to WD; however, this was not significant for male participants. Further studies in other populations, and future prospective studies, are required to reiterate these results.

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“…According to a World Health Organization (WHO) report, 450 million people worldwide suffered from mental or behavioral disorders in 2001 [ 4 , 5 ]. In Iran, the prevalence of mental disorders is reported to range between 10.8 and 39.1% [ 6 – 8 ]. Although many factors contribute to mental health disorders [ 3 ], they may occur due to genetic, social, and psychological factors and various stressors.…”

Section: Introductionmentioning

confidence: 99%

“…Among employed people, the prevalence of mental disorders in all groups working in a hospital setting is high due to special working conditions [ 18 – 20 ]. Mental disorders could evaluate using various tools such as the General Health Questionnaire (GHQ), Symptom Checklist-90 (SCL), or diagnostic tools such as the Diagnostic and Statistical Manual of Mental Disorders (DSM) or the International Classification of Diseases (ICD) [ 6 , 21 – 24 ].…”

Section: Introductionmentioning

confidence: 99%

Applying Artificial Neural-network Model to Predict Psychiatric Symptoms

Allahyari¹,

Roustaei²

2022

BioMedicine

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Introduction Mental disorders result in mental disabilities and discomfort in the affected person as they affect both thinking and behavior. Therefore, more vulnerable people must first be identified to improve the psychological level of society. Aim This study aims to determine the importance of gender, employment, education, place of residence, and age in predicting mental disorders using artificial neural network modeling. Methods The pattern held between variables in this study will be identified using multilayer feed-forward back-propagation neural networks with five inputs and 10 outputs. To determine the neural network with the least sum of square errors, we evaluated the performance of all neural networks with varying algorithms and different numbers of neurons in the hidden layer. Data were analyzed for 380 people aged 10–82 years using the SPSS software. Results The optimal neural network model was effective in predicting mental disorders. In this model, the variables of the place of residence, education, age, gender, and employment were important in fitting the optimal model with 34.08, 20.11, 18.93, 14.55, and 12.33%, respectively. The accuracy rate for the neural network model was 99.2%. Conclusion To achieve further results in improving mental health problems, it is better to focus more on employed, rural, and younger people with a non-tertiary education level.

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An epidemiological survey of psychiatric disorders in Iran: Kermanshah

Cited by 13 publications

References 4 publications

The prevalence of depression among iran‐iraq war veterans, combatants and former prisoners of war: A systematic review and meta‐analysis

The prevalence of depression among iran‐iraq war veterans, combatants and former prisoners of war: A systematic review and meta‐analysis

The Relationship between Functional Constipation and Major Dietary Patterns in Iranian Adults: Findings from the Large Cross-Sectional Population-Based SEPAHAN Study

Applying Artificial Neural-network Model to Predict Psychiatric Symptoms

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