Prevalence and correlates of mental disorders among women: results from the Saudi National Mental Health Survey

Abstract

Background

Mental disorders account for a significant proportion of the world’s disease burden and are more significant among females than males. However, most global mental health research is sex neutral, including in the Kingdom of Saudi Arabia. This study, therefore, estimated the prevalence of mental disorders and investigated the sociodemographic correlates, sex disadvantage factors, and treatment-seeking in Saudi women concerning lifetime and 12-month mental disorders.

Method

The Saudi National Mental Health Survey is a stratified multistage clustered area probability design. Lifetime and 12-month mental disorders were assessed through the Composite International Diagnostic Interview (CIDI 3.0). The correlates considered for this study included age-at-interview, education, marital status, employment status, socioeconomic status (SES), any chronic condition and household characteristics (region, urbanicity, and income), as well as domestic violence, age at marriage and in a polygamous marriage. Data was analysed using PROC SURVEYFREQ procedure as well as logistic regression in SAS 9.2.

Results

Overall, 24.7% and 35.9% of Saudi women experienced at least one of the disorders in the prior 12 months and at least once in their lifetime, respectively. Anxiety disorders were the most frequently reported 12-month and lifetime disorders, followed by mood disorders. The region, urbanicity, chronic conditions, employment status, as well as certain sex disadvantage factors were significantly associated with both 12-month and lifetime disorders. Most women did not seek treatment for 12-month mental disorders (86.2%) and lifetime disorders (73.8%).

Conclusion

Our study confirms that mental health issues, particularly anxiety and mood disorders, are highly prevalent among Saudi women, influenced by chronic conditions and sex-related factors like domestic violence and polygamy. Future research should focus on improving mental health literacy, using rigorous study designs to explore female-specific variables, and investigating genetic and environmental factors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-024-20069-9.

Introduction

Mental disorders

Mental disorders account for a significant proportion of the world’s disease burden. According to the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) 2019, depressive and anxiety disorders are among the two most disabling mental disorders, ranking in the top 25 leading causes of worldwide burden [1]. Worldwide, an increased prevalence of mental disorders was observed among females compared to males. In particular, global Disability-Adjusted Life Year (DALY) rates for depressive disorders were 1019.0 for females, while for males, the rates were 670.6 [2].

These disorders affect both men and women equally; however, data from the World Mental Health (WMH) Surveys indicate a predominance of anxiety and major depression disorder among females [3, 4]. Arab women, are generally at a higher risk of experiencing depression, anxiety, and other mental health disorders compared to men [5]. In research conducted among community populations in the Arab world, studies have reported varying rates of depression, which range from 6 to 32% [6]. A cross-sectional study in Saudi Arabia indicated significant psychological distress, with 38.1% of participants exhibiting moderate to severe levels of distress [5].

It is necessary to recognize that these patterns could be explained by an array of mechanisms and associated factors. They could be due to biological causation secondary to hormonal differences or vulnerability of females to chronic conditions, including female-specific chronic conditions such as endometriosis, reproductive associations, perinatal psychiatric disorders, or socio-cultural factors [7–9].

Furthermore, various sociodemographic correlates were associated with poor mental health among women. Unemployment, low education levels, increased financial stress, and only engaging in home duties were presented with decreased mental health status [10, 11]. Researchers studying a female population in Jordan identified several psychosocial risk factors, including financial issues, serious health concerns, a history of separation, family difficulties, divorce or separation, work-related stress, and income levels [12].

Research on the relationship between chronic illnesses and mental health has demonstrated a reciprocal relationship. Chronic conditions such as cholesterol disease, kidney disease, coronary heart disease (CHD), and asthma—were found to have a significant connection to mental health issues. A meta-analysis examining Arab women, including Saudis, reported a significant association between diabetes and depression [13].

For the purpose of the paper, we identified domestic violence, number of children, age at marriage and polygamous marriages as sex-related disadvantage factors, which have been identified as key associated factors for common mental disorders among women [14]. Women exposed to domestic violence are at an increased odds of mental disorders; despite this, poor identification of these disorders persists [15]. Polygamous marriages are related to poor mental health among women, compared to monogamous marriages [16]. Domestic violence is prevalent in the Kingdom of Saudi Arabia, and a significant correlation exists between abused women and depression [17, 18].

Sex differences for mental disorders have also been observed for treatment-seeking rates, where women were more likely to recognize the need for treatment [19–21]. Some studies in the Arab region argued that women were more likely to seek support of traditional healers rather than psychiatrists [6, 22].

Although research on mental disorders in the Kingdom of Saudi Arabia has increased in recent decades, their generalizability is limited to clinical populations [23]. To fill this gap in research, the Saudi National Mental Health Survey (SNMHS) was launched to provide nationally representative general population estimates of the epidemiology of mental disorders in the Kingdom of Saudi Arabia. The current report uses retrospective data collected from the first population-based study to examine mental disorders pertaining to women in the Saudi National Mental Health Survey. Specifically, this study aims to estimate the prevalence of mental disorders and investigates the sociodemographic correlates, sex disadvantage factors, and treatment-seeking in Saudi women concerning lifetime and 12-month mental disorders.

This research is a foundational step toward closing knowledge gaps in mental health disparities and promoting gender-specific care in Saudi Arabia. This study marks a significant step toward addressing the mental health needs of Saudi women and women globally, aiming to promote improved access to care and tailored support.

Methods

Sampling procedure and participant demographics

The survey utilized a stratified multistage clustered area probability design, creating Primary Sampling Units (PSUs) within each of the 11 administrative regions based on census data and updated maps from the Ministry of Economy and Planning [24, 25], A minimum number of PSUs were selected in smaller strata, and the remaining PSUs were allocated proportionately to the Saudi household population size from the 2010 Census. Households within PSUs were chosen systematically from an address-based sampling frame. One respondent of each gender was randomly selected from eligible individuals (Saudi citizens aged 15–65 who spoke Arabic) in each household. To account for the probability of selection variations, each respondent was assigned a weight based on the number of eligible individuals of the same gender in their household. Fieldwork was carried out between 2014 and 2016, with interruptions for Ramadan and summer heat. The sample consisted of 4,302 households from 11 of the 13 administrative areas, with Jazan and Najran excluded due to political conflict at the time [26].

Interviews were conducted face-to-face in the homes of the participants by the trained and certified interviewers. Each team consisted of a male, female, and a driver. Interviews were gender matched (a male interviewer interviewed a male respondent, while a female interviewer interviewed a female respondent). Interviewing began by having the interviewer team contact each sampled household, introduce the study to a household member serving as the “informant” for the household, and then obtain information from the informant about all noninstitutionalized, ambulatory Arabic-speaking Saudi nationals between the ages of 15 and 65 living in the household. The informant was then asked a series of basic questions about the extent to which these potential survey respondents had impairments that would make it difficult or impossible for them to be a survey respondent. One eligible male and one eligible female were then randomly selected from the household listing as the respondents after excluding household members designated as ineligible because of problems with health or cognition. The selected respondents were then invited to complete the interview for the SNMHS.

The interviews were administered in two parts. Part I included a core diagnostic assessment and was administered to all respondents in the SNMHS (n = 4004). Part II was administered to a subsample of respondents, who met criteria for a lifetime disorder and included questions about associated factors, other correlates, and assessments of additional disorders. From the SNMHS final sample, a total of n = 2106 women completed the Part I interview, and n = 1148 women were administered the Part II interview. Further details of sampling as well as weighting procedures can be found elsewhere [25]. Table 1 presents the weighted characteristics of the study sample.

Table 1.

Sociodemographic correlates of 12-month and lifetime DSM IV/WMH-CIDI disorders among women in the Saudi National Mental Health Survey

	12 Month Demo		Lifetime Demo
	OR	95% CL	OR	95% CL
Age
Age 15–24	2.0	(0.8–5.1)	1.0	(0.4–2.2)
Age 25–34	1.9	(0.9–4.2)	1.7	(0.9–3.4)
Age 35–49	1.4	(0.7–2.9)	1.1	(0.6–2.1)
Age 50+	1.0	-	1.0	-
Education
Low	0.4	(0.2–0.8)*	0.4	(0.2–0.7)**
Low Average	1.1	(0.7–1.9)	0.8	(0.5–1.3)
High Average	1.0	(0.6–1.4)	1.0	(0.7–1.4)
High	1.0	-	1.0	-
Marital Status
Married	1.0	-	1.0	-
Separated/Divorced/Widowed	1.7	(1.0–3.0)	1.8	(1.1–2.9)*
Never Married	0.9	(0.5–1.5)	0.8	(0.5–1.4)
Urbanicity
Rural	0.6	(0.4-1.0)	0.5	(0.3–0.8)*
Urban	1.0	-	1.0	-
Region
Central	1.0	-	1.0	-
Eastern	0.3	(0.2–0.5)**	0.6	(0.4-1.0)
Northern	0.3	(0.1–0.7)*	0.4	(0.2–0.9)*
Southern	0.8	(0.5–1.3)	0.7	(0.4–1.2)
Western	0.5	(0.4–0.8)**	0.6	(0.4–0.9)*
Income
Low	1.1	(0.7–1.7)	1.0	(0.7–1.5)
Low average	1.1`	(0.6-2)	1.0	(0.6–1.8)
High average	2.0	(1.2–3.4)*	1.8	(1.1–2.8)*
High	1.0	-	1.0	-
Chronic Conditions
Yes	1.0	-	1.0	-
No	0.4	(0.3–0.6)**	0.5	(0.3–0.7)**
Employment
Working	1.0	-	1.0	-
Student	0.6	(0.3–1.1)	1.0	(0.5–1.8)
Homemaker	0.6	(0.4–0.9)*	0.6	(0.4–0.9)*
Retired	0.5	(0.1–4.8)	0.8	(0.1–4.8)
OtherA	0.8	(0.4–1.6)	1.2	(0.6–2.2)

Part II sample was used (N = 1147)

** p < 0.001 & * p < 0.05

12 month disorder N = 419

Lifetime disorder N = 591

^AOther includes: Looking for work; Unemployed, Disabled, Refused to answer, Don’t know

Instrument

The SNMHS used the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI) version 3.0 [27], a fully structured lay administered interview that generates diagnoses according to the criteria of both the International Classification of Disease 10th Revision (ICD-10) and Diagnostic and Statistical Manual of Mental Disorders 4th Edition (DSM-IV) diagnostic system. The computerized version (CAPI) was translated and adapted into Arabic [28, 29].According to a clinical reappraisal study, CIDI diagnoses are valid, but conservative compared to diagnoses based on blinded clinical reappraisal interviews with the Structured Clinical Interview for DSM-IV [30].

Diagnostic assessment

DSM-IV diagnostic criteria were used and grouped as follows: anxiety disorders (panic disorder, generalized anxiety disorder, agoraphobia without panic disorder, social phobia, posttraumatic stress disorder, obsessive-compulsive disorder, separation anxiety disorder), mood disorders (major depressive disorder, bipolar disorder I or II), impulse control disorders (conduct disorder, attention-deficit/hyperactivity disorder, intermittent explosive disorder), substance use disorders (alcohol and drug abuse and dependence) and eating disorders (anorexia, binge eating disorder, bulimia). The DSM-IV organic exclusion rules and diagnostic hierarchy rules were applied to diagnoses, which are detailed elsewhere [31]. Retrospective age-at-onset information was obtained for all disorders by asking a series of questions designed to avoid recall bias and maximize response rates.

Assessment of sociodemographic correlates

The correlates considered for this study included age-at-interview, education, marital status, employment status, socioeconomic status (SES), any chronic condition and household characteristics (region, urbanicity and income). Age-at-interview was divided into four cohorts (15–24, 15–34, 35–49, ≥ 50). Education was divided into 4 categories of low (0–6 years of education i.e. completion of primary school), low-average (7–9 years of education i.e. completion of secondary school), high-average (10–15 years of education i.e. completion of high school and first 3 years of college), and high (16 + years of education i.e. completion of college and further higher education). Marital status was categorized as never married, married, or previously married (i.e. separated, divorced, or widowed).

Employment status was classified as follows: employed, looking for work/unemployed/laid off, homemaker, student, and retired/medical leave/ disabled/other/refused/don’t know. Socioeconomic status was determined based on the interviewers’ observation and description of the respondents’ neighbourhood, categorized as low, middle, and high. Household regions were divided into Central, Western, Eastern, Northern and Southern regions based on the distribution of administrative areas in KSA.

Urbanicity of a household was coded as either urban or rural. The household income was calculated using the total family household income, respondent income and spouse income to generate the ‘Income per capita’ for each household; this was further divided by the median of income per capita of the whole survey sample (n = 4,004) to create the income variable that was categorized as low, low-average, high-average, and high.

Identification of chronic health conditions

The endorsement of any chronic conditions included any medical condition (stroke, heart attack, heart disease, high blood pressure, asthma, tuberculosis, other chronic lung disease, diabetes, ulcer, HIV/AIDS, epilepsy, cancer), any pain condition (arthritis, chronic back or neck pain, frequent or severe headaches, other chronic pain), and any physical condition (any condition in either the medical or pain category).

Assessment of sex-related disadvantage factors

Domestic violence, age at marriage and in a polygamous marriage were also assessed. Respondents who are married were asked to report how frequently they were exposed to domestic violence, specifically physical aggression such as being pushed, shoved, hit, or having objects thrown at them. They were also asked to indicate their own involvement in physical aggression towards others by selecting one of four categories: never, rarely, sometimes, or often. Polygamy was reported as a binary variable of “yes” and “no”.

Seeking treatment

All Part II respondents were asked whether they had ever received treatment from any of 14 different types of professionals for issues related to emotions, nerves, mental health, or substance use. If they responded affirmatively, they were further asked about the age when they first sought treatment, whether they had received treatment in the past 12 months, and, if so, the number of visits to each type of professional. Separate summary measures were created for 12-month treatment in the healthcare and non-healthcare sectors. Healthcare sector treatment was divided into treatment in the general medical sector (family physicians, general practitioners, and other medical doctors, such as cardiologists or gynecologists, nurses, occupational therapists, and other general healthcare professionals) and the mental health specialty sector (psychiatrists and other mental health professionals such as psychologists, counselors, psychotherapists, mental health nurses, and social workers in a mental health specialty setting). Non-healthcare sector was classified into human services (including social workers in any setting other than a specialty mental health setting, and religious or spiritual advisors, such as a minister, priest, or rabbi) and complementary-alternative medicine (CAM) (including internet use, self-help groups, any other healer, such as an herbalist, a chiropractor, or a spiritualist, and other alternative therapy). We did not differentiate between inpatient and outpatient care; however, all inpatient treatment was coded as mental health specialty treatment.

Statistical analysis and model specification

The sociodemographic characteristics of the respondents and the prevalence of both lifetime and 12-month disorders were obtained using a frequency table with part 1 weights and part 2 weights. The education and employment variables in the socio demographics had missing data. The frequency table was generated using PROC SURVEYFREQ procedure in SAS 9.2 (SAS Institute Inc., Cary, NC, USA).

Logistic regression models were created to find the association among sociodemographic variables, sex disadvantage factors, other associated factors, and mental disorders. Separate models were created for lifetime and 12-month disorders. All the logistic regression models were used to report odds ratios and 95% confidence intervals (CI) with statistical significance at p < 0.05. The logistic regression models were created using the PROC LOGISTIC procedure. The prevalence of treatment among women with mental disorders were obtained by a frequency table generated using the PROC SURVEYFREQ procedure.

Results

Prevalence of mental disorders among women

About 24.7% of the sample had experienced at least one of the disorders in the prior 12-months, whereas 35.9% had had at least one lifetime disorder. Anxiety disorders were the most frequently reported disorders among both 12-month (15.9%) and lifetime (26.2%) cases, followed by any mood disorder (8.7% and 11.5%, respectively). Separation anxiety was the most common individual disorder, occurring in 5.1% in the prior 12-months, and 12.7% ever in lifetime. Major depressive disorder was also prevalent, occurring in 6.1% in the prior 12-months, and in 8.9% ever in lifetime (Supplementary Table 1) (Fig. 1).

Fig. 1.

Prevelence of mental disorders among women

Associated factors related to 12-month and lifetime mental disorders among women

The factors statistically associated with 12-month and lifetime mental disorders among women were education, marital status, urbanicity, region, income, chronic conditions and employment.

In terms of education, those with low levels compared to those with high levels of education were significantly less likely to report both 12-month (OR = 0.4) and a lifetime disorder (OR = 0.4) (Table 1). In contrast, respondents who were separated/divorced/widowed were significantly more likely than those who were married to report a lifetime mental disorder (OR = 1.8). In terms of urbanicity, respondents in rural regions were significantly less likely to report lifetime disorders (OR = 0.5) compared to those in urban regions. Compared to the Central region, those in the Northern and Western regions were significantly less likely to report both 12-month and lifetime disorders. Moreover, those in the Eastern region were less likely to report 12- month disorders, compared to the Central region.

Participants with a high average income were more likely to report both 12-month and lifetime mental disorders compared to high income individuals (ORs ranging from 1.8 to 2).

Respondents who did not report a chronic condition were significantly less likely to report both lifetime (OR = 0.5) and 12-month mental disorders (OR = 0.4) compared to those who had chronic conditions. In terms of employment, homemakers were significantly less likely to report a 12-month mental disorder (OR = 0.4) and a lifetime disorder (OR = 0.6) than those employed.

Sex disadvantage factors associated with mental disorders among women

Several sex disadvantage factors were associated with mental disorders; domestic violence and polyamorous marriages (see Table 2). Exposure to domestic violence significantly increased the odds of mental disorders. Compared with women who never experienced domestic violence, those who reported ‘rarely’ experience domestic violence were more than twice as likely to have an increased odds of lifetime mental disorder (OR = 2.6), and nearly three times more likely to have an increased odds of 12-months mental disorder (OR = 2.9). Whereas women who ‘sometimes’ experienced domestic violence were four times more likely to experience both a 12-month mental disorder and a lifetime mental disorder compared to women that have never experienced domestic violence (OR = 4.2 and OR = 4.0, respectively).

Table 2.

Association of sex disadvantage factors related to 12-month and lifetime mental disorders

	12 Month Demo		Lifetime Demo
	OR	95% CL	OR	95% CL
Domestic Violence on Women
Never	1.0	-	1.0	-
Rarely	2.9	(1.5–5.6)	2.6	(1.4–4.8)*
Often	2.6	(0.9–7.3)	2.9	(1.0–8.0)
Sometimes	4.2	(2.0-8.5)**	4.0	(2.0-8.1)**
Refused/Don’t Know	4.7	(0.5–48.0)	7.8	(0.7–91.6)
Domestic Violence by Women
Never	1.0	-	1.0	-
Rarely	2.4	(1.2–4.7)*	2.3	(1.2–4.3)*
Often	15.4	(2.9–80.8)*	10.6	(1.8–63.8)*
Sometimes	1.6	(0.7–3.4)	2.0	(1.0-4.3)
Refused/Don’t Know	1.6	(0.2–13.1)	1.4	(0.2–12.1)
In a Polygamous marriage
Yes	1.0	-	1.0	-
No	0.7	(0.3–1.3)	0.6	(0.3–1.1)
Age of Marriage
12 to 24	1.1	(0.6–2.1)	0.9	(0.5–1.5)
25–34	1.0	-	1.0	-
35+	1.9	(0.5–6.4)	0.9	(0.3–2.9)

Part II sample was used (N = 1147)

** p < 0.001 & * p < 0.05

Similarly, domestic violence offenders had a significantly increased odds of mental disorders. Compared to women who never engaged in domestic violence, those who reported ‘rarely’ were more than twice as likely to develop an increased odds of both 12-month and lifetime mental disorders (ORs ranging from 2.3 to 2.4); while those who reported ‘often’ had significantly increased odds of a 12-month mental disorder and a lifetime disorder (ORs ranging from 10.6 to 15.3).

Compared to women in a polygamous marriage, those in monogamous marriage were less likely to report mental disorders; however, this was only seen for lifetime disorders and is not statistically significant (OR = 0.5). Age at marriage was not significantly associated with mental disorders.

Treatment seeking among women with mental disorders

Table 3 shows the prevalence of treatment seeking among respondents with both 12-month and lifetime mental disorders. Most respondents did not seek treatment for neither 12-month mental disorders (86.2%) nor lifetime disorders (73.8%).

Table 3.

Prevalence of treatment seeking among women with 12- month and lifetime mental disorder

Treatment	12-Month Disorder		Lifetime Disorder
	N	%	N	%
Any Healthcare	50	11.9	132	20.2
Any Non-Healthcare	23	4.2	81	10.4
Any Treatment	66	13.8	180	26.2
No Treatment	353	86.2	412	73.8

Part 2 Sample was used (n = 971)

Any lifetime disorder (n = 592), Any 12-month disorder (n = 419)

Discussion

This study is the first population-based study in the Kingdom of Saudi Arabia that examines lifetime and 12-month mental disorder data pertaining to women and determines the levels of treatment seeking, presence of chronic conditions, as well as the effect of domestic violence and polyamorous marriages on women with mental disorders.

Prevalence of mental disorders

Our estimates of both lifetime and 12-month mental disorders, were 35.9% and 24.7%, respectively. These estimates are comparable to data of 13 countries that looked at general non-specific classifications of common mental disorders and indicated a prevalence range between 9.6% and 69.3% [9]. In terms of DSM-IV classifications, our estimates are higher than the 24.4% and 10.4% lifetime and 12-month prevalence of mental disorders respectively in Italy; and similar to the lifetime estimate in Australia, which was 37.8% [32, 33]. The variation in the prevalence rates of mental disorders may be attributed to various factors specific to each country studied, including, cultural, economic, social influence, as well as characteristics of the populations studied.

Disaggregation from our study showed that the most frequently reported disorders among women in both 12-month and lifetime rates are anxiety disorders, followed by mood disorders. This is consistent with data from cross-national WMH Surveys which indicated that women had more anxiety and mood disorders than men [4]. Separation anxiety disorder, in specific, was the most common 12-month and lifetime disorder, followed by major depressive disorders. Previous literature has indicated that separation anxiety disorder is more common in females, with genetic evidence having shown factors of heritability [34, 35]. Moreover, the construct of maternal separation anxiety disorder indicates that mothers experience worries, sadness, or guilt when separated from their children, making women a vulnerable category within the general population, especially among first-time mothers experiencing early parenting difficulties [36, 37].

Sociodemographic correlates

Lifetime mental disorders are significantly associated with education and marital status, where those with lower levels of education were less likely to report mental disorders and those who were married were less likely to have these disorders. In terms of education, this is an interesting finding as the literature argues that a higher education level is significantly associated with less reporting of mental health problems [44]. As opposed to our findings, a study in Australia indicated that higher education levels lead to a higher overall state of wellbeing and reduced psychological distress among women [45]. In terms of marital status, data from 15 countries in the WMH survey indicated that marriage for both sexes was associated with reduced odds of mental disorders [46]. Research has also shown that marital distress is an associated factor for mental disorders in both men and women; however, women are more likely to experience it [47].

Furthermore, women residing in urban areas had higher odds of developing lifetime disorders than those living in rural environments. Overall, this is generally clarified by previous literature regardless of sex, where generally, the odds of mental illness was higher in cities compared to rural areas [38]. A study conducted in Sao Paolo, an alpha global city in Brazil, indicated higher odds of mental disorders among women compared to men [39]. Undoubtedly, a deeper analysis of the structural determinants of these cities should be considered, as many mega-cities are exposed to poverty.

We also found that those residing in the central region of the Kingdom had higher odds of 12-month mental disorders compared to other regions. This is an interesting finding as Riyadh city, the capital and the largest city of the Kingdom is in the central region with up to seven and a half million residents, which is consistent with the previously discussed point of the possible influence of increased urbanicity and its effect on mental health. Furthermore, a study conducted specifically in Riyadh city concluded that 41.7% of women reported ill-being or were likely to have depression [40].

In our study, we found that women who had a high average income were more likely to develop 12-months and lifetime mental disorders compared to those who have a high income; this finding is contradictory to what is well-known in previous literature, which indicates low household income levels are associated with several 12 month and lifetime mental disorders [41]. However, on a country level, cross-national surveys indicate a higher prevalence of anxiety disorders in high-income countries [42]. It could be argued that since Saudi Arabia is a high-income country, the significance lies in the high income.

Additionally, homemakers were less likely to have 12-month and lifetime mental disorders. In this regard, the effect of multiple roles that women play in their daily lives, marriage, mothers, caretakers, and employees must be considered. A Canadian study that examined role overload in women described the perceptions of role overload was related to poor mental health. This emphasizes the need of social support for working women e.g. supportive partner, paid maternity leave and child care services. However, working women and women with the highest household incomes reported better mental health [43].

Chronic health conditions

Our results showed that those who reported chronic conditions had higher odds of both 12-month and lifetime mental disorders. This was in line with Mendenhall et al. (2013) who found a high co-morbid prevalence of physical disease and psychological distress among South African women. It may be argued that this is because many physical comorbidities pertain to women only, who are a minority group. Although we didn’t explore sex-specific chronic conditions, studies found that endometriosis, reproductive risk, and postnatal psychiatric disorders are all sex-specific conditions to which women are vulnerable [7, 8]. Regardless of sex-specific conditions, the chronic conditions finding from our study was consistent with previous Arab studies, which indicated a significant association between diabetes and higher rates of depression among Arab women, including Saudis [13].

Sex disadvantage factors

In the Kingdom of Saudi Arabia, the prevalence of mental disorders among women could be explained by certain sex related factors mostly related to marriage: like domestic violence and polyamorous marriages. Our results showed that those who reported “rarely” or “sometimes” exposed to domestic violence had higher odds of having mental disorders. Studies in the kingdom indicate the high prevalence of domestic violence, and a significant correlation between depression and abused women [17, 18]. Wali et al. (2020) found that the prevalence of domestic abuse in Jeddah, Kingdom of Saudi Arabia was 33.24%, where psychological abuse was the most prevalent (48.47%). International studies also found similar results; in Delhi, India as well as Bosnia and Herzegovina, women who had experienced domestic violence were more prone to suicidal tendencies and poor mental health status [48, 49]. Our data showed an increased odds of mental disorders in female domestic offenders, where those who reported “rarely” or “sometimes” were twice as likely to develop an increased odds of mental disorders. There is an ongoing debate discussing the theory of women being as aggressive as men. A study indicated that women who were arrested for domestic violence had more mood disorders and personality dysfunction symptoms than men [50].

Although not statistically significant, according to our results, women in polygamous marriages were more likely to report lifetime mental disorders A previous meta-analysis examining studies from multiple countries, which demonstrated psychopathological issues among women in polyamorous marriages compared to monogamous marriages and discussed the “first wife syndrome,” which explained various somatic issues and severe anxiety and tension among the first wives in these marriages [16]. Another meta-analysis indicated that women in polygamous marriages were 2.25 more likely to experience depression than those in monogamous marriages [51]. Polygamous marriage might be traumatizing for women affecting her self-esteem and socialization which might make her feel lonely. It might also negatively impact the family dynamic and economic resources [51].

Treatment seeking

Finally, the lack of treatment-seeking among women is strikingly high for both 12-month (86.2%) and lifetime mental disorders (73.8%). In contrast to our results, previous data from the 10 European countries participating in WMH surveys indicated that women are more likely to utilize mental health services than men, depending on the type or severity of the disorder [52]. Researchers theorized that higher treatment rates among women are possibly elucidated by women’s ability to pinpoint feelings of distress into recognition of having a mental health problem and decreased perception of stigma compared to men [53]. Another argument is that women are generally perceived to be able to express themselves emotionally and care for their health; these traits are considered more feminine, whereas men were observed not to want to end up in a subordinate relationship to the healthcare provider [54]. The Kingdom of Saudi Arabia is greatly influenced by social, cultural and religious factors that would affect treatment seeking especially among women. For example, women in the Kingdom are more likely to keep their mental struggles a secret due to the perception of it affecting their marital prospects. Or the fact that most women – for religious reasons - would avoid visiting male psychiatrists and are more likely to be accompanied by a relative during their visits than males [55].

Strengths and limitations

The study’s main strength is that it is the first population-based study in the Kingdom of Saudi Arabia that examines lifetime and 12-month mental disorder data related to women. It provides a baseline for further research opportunities. On a national level, this study acts as a first step to creating healthcare policies to fulfil the need for more sex-based treatment approaches and interventions, and examine the inequalities of sex disadvantages. This paper will also add value to the Arab region with a similar sociocultural context to the Kingdom of Saudi Arabia.

However, this study has some limitations. The first is related to the issue of study design; a cross-sectional design was used, which focused on the co-occurrence of mental disorders among women, and sociodemographic factors and sex disadvantages, which did not allow us to determine the temporality or causation of events. Another limitation was that we did not consider potential female-specific associated factors that could potentially affect the relationship between variables, such as menstrual, perinatal and menopause issues as well as other female-focused diagnoses. In addition, the study did not assess some important psychosocial etiological factors of psychiatric disorders e.g. childhood experiences, personality traits, traumatic life events, and lifestyle. However, these factors will be further studies in a future paper. Finally, there could be potential underreporting by study participants about mental disorders, given the perception of public stigma and embarrassment related to mental disorders [56].

Conclusion and recommendations

Our study results support the existing literature that mental health among women requires. In this first population-based nationally representative sample of Saudi women aged 15–65, we found that among both 12-month and lifetime mental disorders, anxiety and mood disorders were highly prevalent. The presence of chronic conditions and sex related factors such as domestic violence and polygamy were associated factors for mental disorders in women. Our results gave us a glimpse into this phenomenon and highlights the vulnerability of women with regard to mental disorders; however, it raises the question of what future studies should examine.

In line with our findings, we recommend that future research focus on:

• enhancing overall mental health literacy in the general public and among women specifically and educating them on treatments availability and accessibility.

• more rigorous study design such as conducting a prospective study and examine more female-specific variables; thereby adding value and enriching the current body of research and developing sex-based approaches to mental health services.

• exploring genetic factors and predisposing factors that make women more vulnerable to mental disorders and consider the gene versus environment argument.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Author contributions

Yasmin A Altwaijri: Conceptualization, Methodology, Investigation, Writing - Original Draft Nouf K Al-Saud: Writing - Original Draft, Writing - Review and Editing, Data Curation, Validation Lisa Bilal: Writing – Review and Editing, Supervision, Project administration Deemah A. Alateeq: Writing - Review & Editing Maggie Aradati: Writing - Review & Editing Mohammad Talal Naseem: Formal analysis Abdullah AlSubaie: Writing - Review & Editing, Conceptualization AbdulHameed Al-Habeeb: Writing- Review & Editing, Resources.

Funding

The Saudi National Mental Health Survey was conducted by the King Salman Center for Disability Research; funded by Saudi Basic Industries Corporation, King Abdulaziz City for Science and Technology, Ministry of Health (Saudi Arabia), and King Saud University. Funding in-kind was provided by King Faisal Specialist Hospital & Research Center, and Ministry of Economy & Planning, General Authority for Statistics, Riyadh. The funders had no role in study design, data collection, data analysis, data interpretation, or writing of the report. All authors had full access to the data of the study, and were responsible for the final decision to submit for publication.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

Informed consent from the participants was obtained before each interview. The study protocol complied with the international standards set by the Declaration of Helsinki and was approved by the Institutional Review Board at King Faisal Specialist Hospital and Research Centre, Riyadh.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.