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Journal of Public Health Advance Access originally published online on April 8, 2008
Journal of Public Health 2008 30(4):487-493; doi:10.1093/pubmed/fdn025
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© The Author 2008, Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved

Prevalence and predictors of mental disorders among women in Sanliurfa, Southeastern Turkey



Zeynep Simsek, Research Associate1

Dilek Ak, Master Degree Student1

Abdurrrahman Altindag, Research Associate2

Mehmet Günes, Research Assistance2
1 Harran University Faculty of Medicine, Department of Public Health, 63100 Sanliurfa, Turkey
2 Harran University Faculty of Medicine, Department of Psychiatry, 63100 Sanliurfa, Turkey

Address correspondence to Zeynep Simsek, E-mail: zsimsek{at}harran.edu.tr

Background Mental health is one of the most important public health issues because of major contributor to the global burden of disease. In this study, we examined the prevalence and predictors of mental disorders among married women from 15 to 49 years of age and the need for mental health services in the primary health care settings.

Methods In this cross-sectional study, 270 women were selected using probability cluster sampling method at 95% confidence interval (91.5% response rate). The Structured Clinical Interview for DSM-IV (SCID-I) and women socio-demographic information form were used to collect data.

Results Although the prevalence of mental disorder was 25.9% (8.5% with one diagnosis; 17.4% were two or more diagnoses), 4.7% of these women had contacted a carer in the last year for psychological reasons. According to the SCID-I assessment, the most prevalent diagnoses were major depressive disorder (7.3%), phobic disorder (4.8%) and posttraumatic stress disorder (3.6%). In this study, comorbid diagnoses were present in 67.2% of patients. Logistic regression analyses revealed that domestic violence, history of previous trauma, anemia and cutaneous leishmaniasis were significant predictors of any mental disorders (P < 0.05).

Conclusions These findings highlight the need for systematic development of community-based mental health services in conjunction with primary health care services for the screening, early identification and treatment of women suffering from mental disorders, and the improvement of anemia and cutaneous leishmaniasis control programme.

Keywords: women, mental disorders, comorbidity, community mental health services


   Introduction
TOP
 Introduction
Methods
 Independent Variables
 Data Analysis
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
Mental disorders are widely recognized as a major contributor (14%) to the global burden of disease worldwide.1,2 According to recent World Health Organization estimates, nearly 25% of individuals develop one or more mental or behavioral disorders at some stage in their life, in both developed and developing countries and one-third of all years lived with disability worldwide can be attributed to neuropsychiatric conditions.3 Not only is the prevalence of mental disorders high but the fact that most conditions go untreated, are often chronic in course and thus interfere with the ability of the affected individual to lead a productive and satisfying life, means that mental disorders are associated with extremely high rates of ill-health and disability.4 Research highlights the importance of individual behavioral factors and physical, material, economic and psychological factors, and their complex reciprocal relationship, in determining mental health and mental disorders.5

In light of the universal acknowledgement of gender, women are more likely than men to be adversely affected by mental disorders, the most common being anxiety and depression disorders.6–11 By 2020, depression is predicted to be the major burden of disease for women.12 When rates of major depression at each site were standardized to the Epidemiologic Catchment Area five site household sample for the age group 18–64, and the result of The Turkish Mental Health Survey conducted a national representative sample, the female to male sex ratio ranged between 1.6 and 2.6.13,11 Data from the World Bank study revealed that depressive disorders accounted for close to 30% of the disability from neuropsychiatric disorders amongst women in developing countries but only 12.6% of that among men.11

Since gender is a measure of both biological/genetic and social differences, it is likely that the health inequalities between men and women discussed earlier reflect both sex-related biological and social factors, and the interplay between them.7,14 In terms of social factors, researchers pose two general hypotheses to account for gender-based inequalities in health. The differential exposure hypothesis suggests that women report higher levels of health problems because of their reduced access to the material and social conditions of life that foster health,6,15 and from the grater stress associated with their gender and marital roles. The differential vulnerability hypothesis, on the other hand, suggests that women report higher levels of health problems because they react differently than men to the material, behavioral and psychosocial conditions that foster health.16

As mentioned above, as women in many countries are approximately twice as likely as men to experience depression and it is the most prevalent psychiatric disorder, any significant reduction in the overrepresentation of women who are depressed would make an important contribution to lessening the global burden of disease. Therefore, women's mental health is a significant public health issue. Since the need for the effective promotion of good mental health for women and reduction of mental disorders, evidence-based research based on risk and protective factors should be done in every culture and community.

The aims of this study were: (i) to describe the prevalence of mental disorders in women in a Primary Healthcare Center Area in Sanliurfa, (ii) to examine the relationship between background risk factors and mental disorders and (iii) to determine the mental health needs of women in our community.


   Methods
TOP
 Introduction
 Methods
Independent Variables
 Data Analysis
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
This cross-sectional study surveyed persons enrolled at the catchment area of a community-based Primary Healthcare Center in Sanliurfa of Turkey in 2006. This Healthcare Center serves ~1 05 000 persons of all ages, and ~15% of were female aged 15–49 years. We calculated to reach 270 women at 95% confidence level, using the probability cluster sampling method (every cluster included average ten houses). Cluster selection was done from household records kept and updated every year by the Healthcare Center. It contained a list of dwelling units with their whole addresses (quarter, area, avenue, street, building and door number). A sampling list was created from these records. Random selection was employed at every stage. A household was defined as a person or a group of persons living together and sharing a common source of food. The sample consisted of 247 women (91.5% of those were eligible) from 15 to 49 years of age and nonpregnant women living in the catchment area. Of the 270 women in the sample, 11 refused to participate for various reasons and 12 were pregnant.

Two bilingual (Turkish and Kurdish) research assistants (trained mental health professionals) did all home visits. Interviewers introduced themselves, read a standardized set of paragraphs explaining the study and informed potential participants that all information was anonymous. Study participants provided verbal informed consent for their participation. After the study period all patients diagnosed with any mental disorders were directed to Harran University Faculty of Medicine Department of Psychiatry for their treatment and follow-up. The first part of the survey consisted of questions pertaining to sociodemographic and clinical variables, the next sections included The Turkish version of the Structured Clinical Interview for Axes I of the DSM-IV (SCID-I).17


   Independent Variables
TOP
 Introduction
 Methods
 Independent Variables
Data Analysis
 Results
 Discussion
 Funding
 Acknowledgements
 References
 
Social determinants of health were categorized here into three broad groups; social structural, behavioral and psychosocial. Social structure was measured by age, size of household, family type, education and economic condition.

Multiple indicators were also used to measure physical health and health related behaviors such as body mass index (BMI), anemia, history of cutaneous leishmaniasis and smoking. The BMI was calculated by dividing weight in kilograms by height in meters squared, those with a BMI score of <18.5 are categorized as having insufficient weight, 18.6–24.9 acceptable weight, 25–29.9 some excess weight and >30 overweight. Anemia was defined according to the World Health Organization criterion (Hb <12.0 g/dl).18

We asked about trauma experiences (i.e. accident, losses, economic difficulties) in the 12 months prior to the interview, domestic violence such as physical, verbal and economic, participation in decision-making at home and social support were defined as psychosocial determinants.

In the end, age, first marriage age, size of household and number of living children are treated as continuous variables in the analyses. All other independent variables are treated as categorical data, and therefore entered in the analysis as sets of dummy variables.


   Data Analysis
TOP
 Introduction
 Methods
 Independent Variables
 Data Analysis
Results
 Discussion
 Funding
 Acknowledgements
 References
 
Data were analysed using the SPSS statistical package. Bivariate analyses were used to begin to examine relationships between risk factors and mental health status. The statistical differences between percentages were examined with the chi-square test, and differences between mean scores were assessed by a t-test. Predictive factors were included in the subsequent models if they were significantly associated at the P < 0.05 level with any outcome variable in the bivariate analysis. Logistic regression model of outcome were estimated to determine independent associations of these risk factors with the mental disorders and for controlling confounders. Statistical significance is defined as a P-value of 0.05 or lower; logistic regression models present 95% confidence intervals.


   Results
TOP
 Introduction
 Methods
 Independent Variables
 Data Analysis
 Results
Discussion
 Funding
 Acknowledgements
 References
 
Characteristics of sample
The mean age of participants was 33.3 ± 9.4 years, and participants ranged in age from 15 to 49 years and mean first marriage age of them was 17.9 ± 3.1. The average number of household members was 5.8 ± 2.4 and the mean of total living children was 3.4 ± 2.5. Most (74.5%) participants reported that Kurdish or Arabic were the primary language spoken at home. The majority (68%) of the sample was illiterate and 16.2% of them had completed only primary school education. Only 1.6% was employed, others were housewives; 22.3% of participants reported that they had a bad economic condition.

Previous trauma events experienced by 36% of the women including traffic accidents, loss of a family member, illness and trouble with children or a family member. Two in three (60.3%) women aged 15–49 years reported at least one type of domestic violence, at least once, in their lifetime. The lifetime prevalence for specific types of violence in our sample for each category: 30% of women were physically abused, 29.1% experienced verbal violence at least one time and about one of three women (27.9%) experienced economic violence.

Prevalence of mental disorders by SCID-I
In the sample, 64 (25.9%) patients met the established SCID-I criteria for any mental disorders. Of patients, 8.5% of them were diagnosed only one mental disorder and 17.4% were diagnosed two or more mental disorders. The most common mental disorder was major depressive disorder (7.3%). The prevalence of phobic disorders, posttraumatic stress disorder, obsessive-compulsive disorder, anxiety due to general medical condition, dysthymic disorder and panic disorder were 4.8, 3.6, 3.2, 2.2, 1.6 and 1.2%, respectively. In this study, comorbid diagnoses were present in 67.2% of the patients.

Bivariate analyses
Table 1 presents the mean scores of independent variables including the age of women and husbands, age at first marriage, first motherhood age, number of living children and number of household members according to the mental health situation. The factors of husband's education, number of living children and size of the household showed significant relation with the mental disorders (P < 0.05). No significant relationship was found between mental disorder and the independent variables listed (P > 0.05) (as shown in Table 1; age of women/husband, first marriage age, motherhood age and women education).


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  		Table 1 Mean and SD of continuous variables according to the mental health status

 
As shown in Table 2, the frequency of any mental disorder was significantly different according to the history of previous trauma, anemia, history of leishmaniasis, domestic violence including physical, verbal and economic, economic situation and participate to the decision at home (P < 0.05). There were no significant differences according to the family type, ethnicity, social support and smoking (P > 0.05).


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  		Table 2 Prevalence of any mental disorders according to the independent categorical variables

 
In a logistic regression analysis with forced entry of all variables, those variables that showed significant relations in our previous analyses were examined. Results of logistic regression analyses are depicted in Table 3. Domestic violence, previous trauma experiences, anemia and cutaneous leishmaniasis at baseline were the strongest of the predictors in multivariate analyses; women who experienced domestic violence, previous trauma, anemia and cutaneous leishmaniasis were more likely to suffer from mental disorder than women who did not, with odds ratios of 2, 3.9, 1.1 and 1.2, respectively. Education of husband, economic situation, participation in decision-making at home and demographic variables such as number of living children and size of household were not significant in the analyses.


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  		Table 3 Results of logistic regression analyses

 
Mental health need
While 25.9% of women diagnosed with any mental disorder, only 4.7% of these women received mental health services.


   Discussion
TOP
 Introduction
 Methods
 Independent Variables
 Data Analysis
 Results
 Discussion
Funding
 Acknowledgements
 References
 
Main findings of this study
In our community sample, the prevalence of any mental disorder among 15–49 years aged women was 25.9%. The most common mental disorder was major depressive disorder (7.3%). Comorbid diagnoses were very high (67.2%). Another notable result of our study was that although a considerable proportion of women are diagnosed to have any mental disorder, very few (4.7%) had ever received care from mental health services. This alarming finding underscores the urgent need for improving the mental health services into the primary healthcare services. Although a diverse array of potential risk factors emerged in bivariate analyses, multivariate modeling demonstrated that previous trauma experiences, having cutaneous leishmaniaisis and anemia and experiencing domestic violence at baseline predicted the mental disorder; the odds were between ~2–7.8, 1.3–7.3, 1.01–3.0 and 1.2–4.3, respectively.

What is already known on this topic
Women are at heightened risk for common mental disorders: a female to male sex ratio of 1.5 to 2.0 is typical.2 Kilic, Küey and WHO reported that the prevalence of mental disorders of women was 22.4, 20 and 25%, respectively, and majority of them had not contacted a carer in the last year for psychological reasons.11,19,20 Reasons for not seeking mental health treatment were inaccessibility of health care, unawareness of mental health problems, stigmatization, economic condition and cultural characteristics.21

The prevalence of pure major depressive disorder (7.3%) and depression and anxiety disorder comorbidity was 11.3% in this sample which was comparable to the prevalence noted previously in studies conducted in community based samples (i.e. 6.1–12.9%).22 Depression is the most prevalent women's mental health problem and it is likely to be accompanied by other psychological disorders which are more common with anxiety disorders.1,9,13,23,24 Numerous studies show that people exposed to traumatic life events are at greater risk of psychological distress and psychiatric disorders.20

The majority of the women (60.3%) experienced physical (30.0%), verbal (29.1%) or economic (27.9%) domestic violence in their life in this study. Intimate partners (95.9%) are most commonly the perpetrators of violence against women as consistent with this study.25 Violence against women is a public health problem in the world that has received increased attention from researchers and health care providers.26,27 In the WHO study, the proportion of women who had ever suffered physical violence by a male partner ranged from 13% in Japan to 61% in provincial Peru.4 Around the world, mental health problems and emotional distress are common among women who have suffered partner violence.25 Although poor mental health can be a risk factor for violence,28–30 mental disorders can result from assault experiences.31,32 Good mental health may be a protective factor against revictimization.33 Therefore, it is necessary to set up community-based primary, secondary and tertiary prevention services with collaboration with health-related sectors such as education, social services, religion affairs and media, and to give community health education for prevention of domestic violence.

Many studies have indicated that persons with a cutaneous disease experience a high prevalence of psychiatric disorder.34,35 Cutaneous leishmaniasis is an infection disease caused by a protozoan parasite and transmitted by insect bites. The disease produces chronic ulcerative lesions on exposed parts of the body, such as the face, arms and legs. Cutaneous leishmaniasis leads to permanently disfiguring scars and creates a lifelong stigma.36,37 Cutaneous leishmaniasis has long been endemic in Sanliurfa and is called ‘beauty scar’. The patients with cutaneous leishmaniasis had significantly higher anxiety and depression subscale scores than the control groups, as consistent with our findings. Developing sustainable control programme of cutaneous diseases may be one of the effective measures for controlling mental disorders.

In this study, like mentioned above, another important predictor was anemia. It is the most common and widespread nutritional disorder in the world. WHO estimates the number of anemic people worldwide to be a staggering two billion and that ~50% of all anemia can be attributed to iron deficiency. The negative consequences of iron deficiency anemia on cognitive and physical health and work productivity of adults have been well documented.18. Although anemia has been recognized as a major health problem for many years, a few study has been reported the relation between mental disorders and anemia. Corwin and his colleagues (2003) reported that there was a significant relation between postpartum depression and anemia.38

What this study adds
This study draws together previous research on women's mental health, unmet mental health need and risk factors. Mental health services for women have not been developed and addressed in Turkey. Our findings make some contributions to the debate about mental health services. Mental health awareness needs to be integrated into all elements of health and social policy, health system planning and health care delivery. These findings highlight the urgent need for systematic development of community-based mental health services in conjunction with primary healthcare services for the screening, early identification and treatment of women suffering from mental disorders and the improvement of anemia and cutaneous leishmaniasis control programme.

Limitations of this study
The results of the present study should be interpreted in the light of a number of limitations. First, as this study involved a cross-sectional household interview survey, it may be impossible to draw conclusions about the nature of the putative causal relationship between mental disorders and noted physical and psychosocial variables. Despite the limitation in the design of this study however, the results of this study has immediate practical implications for improvement of the assessment and intervention conditions for women who have experienced a range of deprivation experiences. The identification of risk and protective factors regarding the mental disorders of women in community settings can directly assist health professionals in identifying essential interventions and setting priorities. Secondly, additional analytic epidemiological research is needed to replicate these findings and to investigate the potential underlying mechanisms that explain the differential association of mental disorders and predictive variables.


   Funding
TOP
 Introduction
 Methods
 Independent Variables
 Data Analysis
 Results
 Discussion
 Funding
Acknowledgements
 References
 
Funding for this project was provided by the Harran University Scientific Research Commission grant 472.


   Acknowledgements
TOP
 Introduction
 Methods
 Independent Variables
 Data Analysis
 Results
 Discussion
 Funding
 Acknowledgements
References
 
We would like to express our gratitude to all women who gave their time for interviews and completing the forms.


   References
TOP
 Introduction
 Methods
 Independent Variables
 Data Analysis
 Results
 Discussion
 Funding
 Acknowledgements
 References
 

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