Significant Outcomes
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The age-standardised point prevalence of major depressive disorder was 3322.1 per 100000 in the Middle East and North Africa region in 2019.
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In 2019, the highest burden of major depressive disorder was found in Palestine.
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The age-standardised point prevalence of major depressive disorder was highest in the 35-39 age group.
Limitations
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The burden of specific types of major depressive disorder was not reported in the present study.
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There is a risk of underestimation due to the sparse data used in the present study.
Introduction
Major depressive disorder (MDD), also known as clinical depression, is a mood disorder that is characterised by changes in mood, interests and concentration that lead to impairment in social and occupational functioning (Otte et al., Reference Otte, Gold, Penninx, Pariante, Etkin, Fava, Mohr and Schatzberg2016). MDD is a multifactorial disorder that is associated with genetic, epigenetic and environmental factors (World Health Organization (WHO), 2020; American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, F. E. D.- 2013). Although the specific pathophysiology of MDD is still unknown, some biological factors (e.g. dysfunction of the monoamine neurotransmitter system, hypothalamic-pituitary-adrenal axis changes, and inflammation) are known to contribute to its development (Malhi and Mann, Reference Malhi and Mann2018). In addition, MDD can increase the risk of suicide by approximately seven times (Moitra et al., Reference Moitra, Santomauro, Degenhardt, Collins, Whiteford, Vos and Ferrari2021). Furthermore, the economic burden of MDD among the adult population of the United States (U.S.) increased by 37.9% over the period 2010–2018 (Greenberg et al., Reference Greenberg, Fournier, Sisitsky, Simes, Berman, Koenigsberg and Kessler2021).
Depression and MDD are among the leading causes of disability worldwide (Friedrich, Reference Friedrich2017). Globally, in 2017 the age-standardised incidence rate of MDD was 3.0 per 1000, with an estimated annual percent change of 0.01 from 1990 to 2017 (Liu et al., Reference Liu, He, Yang, Feng, Zhao and Lyu2020b). In 2019, the age-standardised point prevalence of MDD was higher in the Middle East and North Africa (MENA) region than the worldwide average (3322.1 versus 2285.6 per 100,000) (GBD, 2019 Mental Disorders Collaborators, 2022). Furthermore, it has been estimated that an additional 53.2 million new cases of MDD, or a 27.6% increase in the prevalence of MDD, have occurred worldwide since the outbreak of the COVID-19 pandemic (Santomauro et al., Reference Santomauro, Mantilla Herrera, Shadid, Zheng, Ashbaugh, Pigott, Abbafati, Adolph, Amlag, aravkin, Bang-Jensen, Bertolacci, Bloom, Castellano, Castro, Chakrabarti, Chattopadhyay, Cogen, Collins, Dai, Dangel, Dapper, Deen, Erickson, Ewald, Flaxman, Frostad, Fullman, Giles, Giref, Guo, He, Helak, Hulland, Idrisov, Lindstrom, Linebarger, Lotufo, Lozano, Magistro, Malta, Månsson, Marinho, Mokdad, Monasta, Naik, Nomura, O'Halloran, Ostroff, Pasovic, Penberthy, Reiner, R., Reinke, Ribeiro, Sholokhov, Sorensen, Varavikova, Vo, Walcott, Watson, Wiysonge, Zigler, Hay, Vos, Murray, Whiteford and Ferrari2021). Moreover, the increased prevalence of MDD was higher in the MENA region than it was globally (37.2% versus 27.6%) (Santomauro et al., Reference Santomauro, Mantilla Herrera, Shadid, Zheng, Ashbaugh, Pigott, Abbafati, Adolph, Amlag, aravkin, Bang-Jensen, Bertolacci, Bloom, Castellano, Castro, Chakrabarti, Chattopadhyay, Cogen, Collins, Dai, Dangel, Dapper, Deen, Erickson, Ewald, Flaxman, Frostad, Fullman, Giles, Giref, Guo, He, Helak, Hulland, Idrisov, Lindstrom, Linebarger, Lotufo, Lozano, Magistro, Malta, Månsson, Marinho, Mokdad, Monasta, Naik, Nomura, O'Halloran, Ostroff, Pasovic, Penberthy, Reiner, R., Reinke, Ribeiro, Sholokhov, Sorensen, Varavikova, Vo, Walcott, Watson, Wiysonge, Zigler, Hay, Vos, Murray, Whiteford and Ferrari2021). MDD more commonly develops in women and has an onset age of about 25 years old (Otte et al., Reference Otte, Gold, Penninx, Pariante, Etkin, Fava, Mohr and Schatzberg2016).
Previous research has reported the burden of depression (Liu et al., Reference Liu, He, Yang, Feng, Zhao and Lyu2020b) and mental disorders (GBD, 2019 Mental Disorders Collaborators, 2022) at the global, regional and national levels using Global Burden of Disease (GBD) data. In addition, the burden of mental disorders has been reported in the Eastern Mediterranean Region between 1990 and 2015 (Charara et al., Reference Charara, El Bcheraoui, Khalil, Moradi-Lakeh, Afshin, Kassebaum, Collison, Krohn, Chew, Daoud, Charlson, Colombara, Degenhardt, Ehrenkranz, Erskine, Ferrari, Kutz, Leung, Santomauro, Wang, Whiteford, Abajobir, Abd-Allah, Abraha, Abu-Raddad, Ahmad Kiadaliri, Ahmadi, Ahmed, Ahmed, Al Lami, Alam, Alasfoor, Alizadeh-Navaei, Alkaabi, Al-Maskari, Al-Raddadi, Altirkawi, Anber, Ansari, Asayesh, Asghar, Atey, Awoke Ayele, Bärnighausen, Bacha, Barac, Barker-Collo, Baune, Bazargan-Hejazi, Bedi, Bensenor, Berhane, Beyene, Bhutta, Boneya, Borschmann, Breitborde, Butt, Catalá-López, Ciobanu, Danawi, Deribew, Dharmaratne, Doyle, Endries, Faraon, J., Faro, Farvid, Fekadu, Fereshtehnejad, Fischer, Gebrehiwot, Giref, Jakovljevic, James, Jonas, Kasaeian, Khader, Khan, Khoja, Khosravi, Khubchandani, Kim, Kim, Kokubo, Koyanagi, Defo and Larson2018). However, to the best of our knowledge no previous research has reported the burden of MDD in the MENA region. Moreover, there is substantial variation in the prevalence and incidence of MDD by region, age and sex (Ferrari et al., Reference Ferrari, Somerville, Baxter, Norman, Patten, Vos and Whiteford2013). Health policymakers require up-to-date information on the burden of MDD for planning purposes. Therefore, the aim of the present study was to report the prevalence, incidence and years lived with disability (YLDs) that were attributable to MDD in the MENA region from 1990 to 2019, by age, sex and socio-demographic index (SDI).
Methods
Overview
The GBD project has estimated the burden of disease in 204 countries and territories and 21 regions over the period 1990–2019 and includes 369 diseases and injuries, and 87 risk factors (Murray et al., Reference Murray, Aravkin, Zheng, Abbafati, Abbas, Abbasi-Kangevari, Abd-Allah, Abdelalim, Abdollahi and Abdollahpour2020; Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020). The burden of MDD is a substantial public health problem that has not been comprehensively reported for all 21 regions of the world. The current study reports the burden of MDD, from 1990 to 2019, in the countries that make up the MENA region. The MENA region contains the following 21 countries: Afghanistan, Algeria, Bahrain, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Palestine, Qatar, Saudi Arabia, Sudan, the Syrian Arab Republic, Tunisia, Turkey, the United Arab Emirates and Yemen. A complete description of the methodologies used to estimate the MDD-attributable burden has been reported in the GBD capstone articles (Murray et al., Reference Murray, Aravkin, Zheng, Abbafati, Abbas, Abbasi-Kangevari, Abd-Allah, Abdelalim, Abdollahi and Abdollahpour2020; Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020) and the data used in the present research can be accessed using the following links: https://vizhub.healthdata.org/gbd-compare/ and http://ghdx.healthdata.org/gbd-results-tool.
Case definition and data sources
MDD can be defined as an episodic mood disorder that includes one or more major depressive episodes (MDE). Patients were included in the GBD disease modelling if they met the MDD diagnostic criteria, which used the Diagnostic and Statistical Manual of Mental Disorders (DSM) or the International Classification of Diseases (ICD) criteria. The cases included the DSM-IV-TR codes (296.21–24, 296.31–34), along with the ICD-10 codes (F32.0–9, F33.0–9), but did not include patients that presented with MDD that were due to a general medical condition or substance-induced disorders (Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020). The DSM-IV-TR criteria define MDD as the presence of at least one MDE, which is the experience of either a depressed mood for most of the day or a loss of interest/pleasure in all or most activities for at least two weeks. These symptoms should be observable, rather than self-reported, and cause clinically significant impairment in social, occupational, or other important areas of functioning. Furthermore, an MDD diagnosis requires at least four of the following seven symptoms: (1) significant change in eating, appetite and weight, (2) excessive sleeping or insomnia, (3) agitation or slow motor activity, (4) fatigue or loss of energy, (5) feelings of worthlessness or excessive guilt, (6) difficulty concentrating, and (7) recurrent thoughts of death (Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020).
A systematic literature review was performed for GBD 2019 to identify epidemiological studies about MDD that were published between September 2016 and December 2018. The Institute for Health Metrics and Evaluation conducted the literature screening in three stages, which involved searching the electronic databases (i.e. PsycInfo, Embase and PubMed), then the grey literature and finally consulting an expert in the area. As many studies group MDD, bipolar disorder and dysthymia together, these three search terms were included.
The inclusion criteria were as follows: (1) published on or after 1980, (2) cases were diagnosed using the clinical thresholds specified by the DSM or ICD, (3) adequate information about the methodology and sample characteristics to measure study quality, and (4) samples were representative of the general population.
A complete list of the data sources used and title of the studies included is available at the following website: https://ghdx.healthdata.org/gbd-2019/data-input-sources (Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020).
Data processing and disease model
All estimates with identified biases were adjusted/crosswalked prior to using DisMod-MR 2.1. The paired reference and alternative estimates were matched by year, age, sex and location for each crosswalk. A MR-BRT network meta-analysis used these pairs as data to generate a combined ratio between the reference and the alternative estimates, which was then used to adjust all alternative estimates in the dataset (Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020). There were four adjustment ratios used for modelling MDD, which were as follows:
1) All data which measured prevalence over the past year were adjusted to point/past-month prevalence.
2) All data derived from a symptom scale were adjusted to the level they would have been if the DSM or ICD criteria for MDD had been used.
3) All World Health Survey data, which collected data in almost 70 countries, were adjusted to the level they would have been if they had used DSM or ICD criteria for measuring MDD. Although these surveys collect useful information about the prevalence of depression, a symptom scale is not the same as the DSM or ICD criteria.
4) All prevalence estimates derived from data collected using trained lay interviewers were adjusted to the level they would have been if the interviewers had been clinically trained (i.e. a psychologist or psychiatrist). Interviews led by clinicians were thought to be more sensitive in identifying MDD than those using lay interviewers (Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020).
Furthermore, as MDD is a recognised risk factor for suicide, the data available on excess mortality were augmented with estimated suicide rates (by age, sex, year and location) that were attributable to MDD (Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020). In order to calculate MDD-attributable suicide estimates, the risk ratios of suicide due to MDD were obtained from a previous systematic review and meta-analysis (Ferrari et al., Reference Ferrari, Norman, Freedman, Baxter, Pirkis, Harris, Page, Carnahan, Degenhardt, Vos and Whiteford2014). Finally, to calculate the proportion of suicide cases attributable to MDD, the age, sex, year and location-specific population attributable fractions were multiplied by the GBD suicide rate.
Following these adjustments, the epidemiological data for MDD were then modelled using the GBD, 2019 decomposition structure in DisMod-MR 2.1. There were adjustments made to the model priors or data, where appropriate and when outliers were identified a decision to exclude/include them was made based on a reassessment of the study’s methodology and quality. Data across all epidemiological parameters were initially included in the modelling process. However, given that the few incidence data points available typically excluded cases of MDD at baseline, new MDEs in people with previous episodes were not counted and the incidence was underestimated. In this case, all raw incidence data in the final model were excluded and instead DisMod-MR calculated the incidence based on data from other parameters. There was assumed to be no MDD incidence and prevalence before 3 years of age. The minimum MDD onset age was developed after consulting the literature and feedback from an expert (Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020). In addition, the average remission rate for MDD and the maximum allowable duration of an episode were set at 1.45 and 0.65 of a year, respectively. In order to estimate the prevalence of MDD in locations with no available data, the following location-level covariates were used in the MDD DisMod-MR meta-regression model: (1) mean war mortality rate in the previous 10 years; (2) log-transformed age-standardised summary exposure value scalar for depression; (3) Gallup (negative experience index).
Years lived with disability
Table S1 presents the severity levels, lay descriptions and disability weights (DWs) of MDD (Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020). The DWs were sourced from the GBD disability weight survey (13). The years of life lost due to premature mortality and the years lived with disability (YLDs) were combined to form the disability-adjusted life year (DALY). As there was no mortality attributable to MDD, the YLD and DALY estimates were the same. The severity-specific prevalence estimates were multiplied with their corresponding DWs to estimate the YLDs due to MDD. Finally, 95% uncertainty intervals (UIs) were reported for all estimates. A thousand draws were undertaken at each computational step, which were combined with uncertainty from several sources (e.g. input data, corrections of measurement error, and estimates of residual non-sampling error). The 25th and 975th values of the ordered draws were used as the UIs (Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020).
Compilation of results
The relationship between the MDD-attributable YLDs and the SDIs for the 21 MENA countries was investigated using smoothing splines models (20). SDI is a composite measure of development that includes three items (gross domestic product per capita smoothed over the previous 10 years, mean years of schooling in those 15 years old and over, fertility rate in those younger than 25 years old) and ranges from 0 (least developed) to 1 (most developed). All statistical analyses and data visualisations were produced using R software (V. 3.5.2).
Results
The Middle East and North Africa region
In 2019, MDD was responsible for 20.2 million (95% UI: 17.0–23.8) prevalent cases in MENA, with an age-standardised point prevalence of 3.3 thousand (2.8–3.9) cases per 100,000 population (Table 1 and Table S2). In 2019, MDD accounted for 29.9 million (25.3–35.3) incident cases in MENA, with an age-standardised incidence rate of 4.9 thousand (4.2–5.8) cases per 100,000 (Table 1 and Table S3). Also in 2019, there were 4.1 million (2.8–5.8) YLDs due to MDD, with an age-standardised rate of 672.1 (457.8–934.0) per 100,000 (Table 1 and Table S4). However, the age-standardised point prevalence, incidence and YLD rates have not changed substantially since 1990 (Table 1 and Table S2, S3, and S4)
Prevalent cases, incident cases and YLDs due to major depressive disorder in 2019 and percentage change of age-standardised rates during 1990–2019
National level
In 2019, the national age-standardised point prevalence of MDD in MENA ranged from 2.6 to 5.3 thousand cases per 100,000 population. Palestine [5259.5 (4493.5–6188.4)], Morocco [4082.1 (3463.7–4843.6)] and Tunisia [4044.9 (3427.8–4791.0)] had the highest point prevalences, while the United Arab Emirates [2596.7 (2203.7–3099.0)], Iraq [2885.6 (2434.8–3382.2)] and Turkey [2888.1 (2444.5–3403.8)] had the lowest (Table S2). Fig. 1a presents the national age-standardised point prevalence of MDD for both sexes in 2019.
Age-standardised point prevalence ( a ), incidence ( b ) and YLDs ( c ) for major depressive disorder (per 100,000 population) in the Middle East and North Africa region in 2019, by sex and country. YLD, years lived with disability. (Data available from http://ghdx.healthdata.org/gbd-results-tool).
The national age-standardised incidence rate of MDD in 2019 ranged from 3.9 to 7.7 thousand cases per 100,000 population. Palestine [7687.7 (6546.1–9023.9)], Morocco [6013.0 (5100.4–7147.2)] and Tunisia [5961.3 (5020.7–7027.1)] had the highest age-standardised incidence rates. In contrast, the United Arab Emirates [3866.3 (3252.5–4604.7)], Iraq [4288.9 (3637.2–5046.8)] and Turkey [4294.9 (3644.7–5047.2)] had the lowest rates (Table S3). Fig. 1b illustrates the national age-standardised incidence rate of MDD for both sexes in 2019.
In 2019, the national age-standardised YLD rate of MDD in MENA ranged from 527.4 to 1060.2 cases per 100,000 population. Palestine [1060.2 (725.3–1494.3)], Morocco [825.2 (553.0–1154.0)] and Tunisia [820.3 (556.6–1151.0)] had the highest age-standardised YLD rates, while the United Arab Emirates [527.4 (352.2–736.3)], Iraq [582.4 (394.6–818.2)] and Turkey [586.3 (398.9–815.4)] had the lowest (Table S4). Fig. 1c illustrates the national age-standardised YLD rate of MDD for both sexes in 2019.
During the period 1990 to 2019, the age-standardised point prevalence of MDD only increased in Iran [5.4% (3.7–7.1)] and Libya [5.4% (0.2–11.4)], but decreased in four MENA countries. Bahrain [−12.9% (−19.1– −6.7)], Jordan [−11.7% (−18.4– −4.8)] and the United Arab Emirates [−8.6% (−14.3– −2.9)] had the largest decreases in the age-standardised point prevalence (Figure S1 and Table S2). The age-standardised incidence rate of MDD only increased, from 1990 to 2019, in Iran [5.4% (3.7–7.2)] and Libya [5.3% (0–11.2)], while the age-standardised incidence rate decreased in four of the MENA countries. Bahrain [−12.6% (−19.0– −6.2)], Jordan [−11.3% (−17.8– −4.7)] and the United Arab Emirates [−8.3% (−13.8– −2.4)] had the largest decreases in the age-standardised incidence rate (Figure S2 and Table S3). During the same time period, the age-standardised YLD rate only increased in Iran [5.5% (3.7–7.4)], but decreased in four of the MENA countries. Bahrain [−13.1% (−19.1– −6.5)], Jordan [−11.5% (−18.1– −4.3)] and the United Arab Emirates [−8.8% (−15.0– −2.2)] had the largest decreases in the age-standardised YLD rate (Figure S3 and Table S4).
Age and sex patterns
In 2019, the regional prevalence, incidence and YLD cases of MDD increased steeply up to the 20-24 age group, reached their peak in the 35-39 age group and then decreased with advancing age, in both sexes (Fig. 2a–c). Furthermore, the age-standardised point prevalence, incidence and YLD rates of MDD increased sharply up to the 20-24 age group in both sexes, but then for males there was a relatively steady slope for the remaining age groups. In contrast, females increased slightly up to the 55-59 age group, followed by a decrease with advancing age (Fig. 2a–c). In addition, there were no substantial sex differences in the number of prevalent, incident and YLD cases, or their corresponding rates.
Number of prevalent cases and prevalence ( a ), number of incident cases and incidence rate ( b ) and the number of YLDs and YLD rate ( c ) for major depressive disorder (per 100,000 population) in the Middle East and North Africa region, by age and sex in 2019; dotted and dashed lines indicate 95% upper and lower uncertainty intervals, respectively. YLD, years lived with disability. (Data available from http://ghdx.healthdata.org/gbd-results-tool).
In 2019, the MENA/Global YLD rate ratio of MDD started to increase from the 1–4 age group, peaked in the 5–9 age group, with a ratio of 2.2 for both sexes and then decreased with advancing age. In 2019, males had a higher YLD rate in all age groups, except for the 75–94 age groups, which were the same as the global rate. In 2019, females also had a higher YLD rate in all age groups, except for the 75–79 and 85–89 age groups, which were equal to the global rate, and the 80–84 age group, which was lower than the global rate. In comparison to 1990, the following age groups had lower YLD rates: males aged 5–14, males aged 65–69, females aged 1–19 and females aged 80–84 years old. In contrast, the following YLD rates were higher in 2019: males aged 25–34, males aged 40–49, males aged 95+, females aged 25–59 and females aged 90–94 years old (Fig. 3).
Ratio of the Middle East and North Africa region YLD rate to the global YLD rate of major depressive disorder by age group and sex, 1990–2019. YLD, years lived with disability. (Data available from http://ghdx.healthdata.org/gbd-results-tool).
Association with the socio-demographic index (SDI)
The association between the YLD rate and SDI in MENA, from 1990 to 2019, was slightly negative, and the burden of MDD decreased slightly with increasing SDI. In countries such as Bahrain, Morocco, Palestine and Tunisia, the burden of MDD was higher than expected. In contrast, countries such as Algeria, Egypt, Iraq, Sudan, Turkey and the Syrian Arab Republic had lower-than-expected burdens (Fig. 4).
Age-standardised YLD rates of major depressive disorder for the 21 countries and territories in 2019, by SDI; expected values based on the socio-demographic index and disease rates in all locations are shown as the black line. Each point shows the observed age-standardised YLD rate for each country in 2019. YLD, years lived with disability. SDI, socio-demographic index (Data available from http://ghdx.healthdata.org/gbd-results-tool).
Discussion
The current study is the first to report the prevalence, incidence, YLDs and age-standardised rates for MDD, from 1990 to 2019, in the 21 countries located in the MENA region. In 2019, there were 20.2 million prevalent cases, 29.9 million incident cases and 4.1 million YLDs attributable to MDD in MENA. However, there have been no substantial changes in the age-standardised prevalence, incidence and DALY rates since 1990. Palestine, Morocco and Tunisia had the highest age-standardised prevalence, incidence and YLD rates, while the United Arab Emirates, Iraq and Turkey had the lowest. In addition, the attributable burden of MDD increased up to the 20-24 age group and then remained relatively steady for the remaining age groups, with no substantial differences between the two sexes. Furthermore, the MDD-attributable YLD rate in the MENA region was higher than the global average in most of the age groups. Finally, the burden of MDD decreased slightly with increasing SDI.
Although no previous study has reported the burden of MDD in MENA, there has been one global (Liu et al., Reference Liu, He, Yang, Feng, Zhao and Lyu2020a) and several national studies (Topuzoğlu et al., Reference Topuzoğlu, Binbay, Ulaş, Elbi, Tanik, Zağli and Alptekin2015; Sharifi et al., Reference Sharifi, Amin-Esmaeili, Hajebi, Motevalian, Radgoodarzi, Hefazi and Rahimi-Movaghar2015; Oneib et al., Reference Oneib, Sabir, Abda and Ouanass2015; Al-Hamzawi et al., Reference Al-Hamzawi, Bruffaerts, Bromet, Alkhafaji and Kessler2015; Gharraee et al., Reference Gharraee, Zahedi Tajrishi, Sheybani, Tahmasbi, Mirzaei, Farahani and Naserbakht2019; Salari et al., Reference Salari, Mohammadi, Vaisi-Raygani, Abdi, Shohaimi, Khaledipaveh, Daneshkhah and Jalali2020; Badrasawi and Zidan, Reference Badrasawi and Zidan2021, Karacetin et al., Reference Karacetin, Arman, Fis, Demirci, Ozmen, Hesapcioglu, Oztop, Tufan, Tural, Aktepe, Aksu, Ardic, Basgul, Bilac, Coskun, Celik, Demirkaya, Dursun, Durukan, Fidan, Gencoglan, Gokcen, Gokten, Gorker, Gormez, Gundogdu, Gurkan, Herguner, Kandemir, Kilic, Kilincaslan, Mutluer, Nasiroglu, Ozcan, Ozturk, Sapmaz, Suren, Sahin, Tahiroglu, Toros, Unal, Vural, Yazici, Yazici, Yildirim, Yulaf, Yuce, Yuksel, Akdemir, Altun, Ayik, Bilgic, Bozkurt, Cakir, Ceri, Demir, Dinc, Irmak, Karaman, Kinik, Mazlum, Memik, Ozdemir, Sinir, Tasdelen, Taskin, Ugur, Uran, Uysal, Uneri, Yilmaz, Yilmaz, Acikel, Aktas, Alaca, Alic, Almbaidheen, Ari, Aslan, Atabay, Ay, Aydemir, Ayranci, Babadagi, Bayar, Bayhan, Bayram, Bektas, Berberoglu, Bostan, Cakan, Canli, Cansiz, Ceylan, Coskun, Coskun, Demir, Demir, Demirdogen and Dogan2018, Khaled, Reference Khaled2019) published. In 2017, a telephone survey was conducted in Qatar with the aim of estimating the prevalence of subthreshold depressive episodes (SUBDE) and MDE (Khaled, Reference Khaled2019). A total of 2424 participants were surveyed, which included low-income migrants, high-income migrants and Qatari nationals, using the nine-item Physician Health Questionnaire (PHQ-9) (Khaled, Reference Khaled2019). The prevalence of SUBDE and MDE was estimated to be 5.5% (4.4–6.8) and 3.6% (2.8–4.5), respectively (Khaled, Reference Khaled2019). Furthermore, females had a higher prevalence of MDE than males (Khaled, Reference Khaled2019). Although the prevalence of MDE and the pattern of gender differences were similar to our findings, it should be noted that they assessed MDE in the past two weeks using the PHQ-9 screening test without age-standardisation, which could have led to an overestimate. In 2019, a meta-analysis of 30 studies (n = 37,867) estimated the prevalence of MDD in the general population of Iran (Gharraee et al., Reference Gharraee, Zahedi Tajrishi, Sheybani, Tahmasbi, Mirzaei, Farahani and Naserbakht2019). All studies that were included in the meta-analysis, published between 1995 and 2015, used clinical interviews and various measurement tools for diagnosing MDD (Gharraee et al., Reference Gharraee, Zahedi Tajrishi, Sheybani, Tahmasbi, Mirzaei, Farahani and Naserbakht2019). The overall point prevalence of MDD in Iran was 4.1% (3.1–6.6), and similar to the current study, a higher prevalence was found among women (Gharraee et al., Reference Gharraee, Zahedi Tajrishi, Sheybani, Tahmasbi, Mirzaei, Farahani and Naserbakht2019). In 2014, a national study (n = 5842) was conducted in Turkey, as a part of the 2014 Epidemiology of Childhood Psychopathology in Turkey research (Karacetin et al., Reference Karacetin, Arman, Fis, Demirci, Ozmen, Hesapcioglu, Oztop, Tufan, Tural, Aktepe, Aksu, Ardic, Basgul, Bilac, Coskun, Celik, Demirkaya, Dursun, Durukan, Fidan, Gencoglan, Gokcen, Gokten, Gorker, Gormez, Gundogdu, Gurkan, Herguner, Kandemir, Kilic, Kilincaslan, Mutluer, Nasiroglu, Ozcan, Ozturk, Sapmaz, Suren, Sahin, Tahiroglu, Toros, Unal, Vural, Yazici, Yazici, Yildirim, Yulaf, Yuce, Yuksel, Akdemir, Altun, Ayik, Bilgic, Bozkurt, Cakir, Ceri, Demir, Dinc, Irmak, Karaman, Kinik, Mazlum, Memik, Ozdemir, Sinir, Tasdelen, Taskin, Ugur, Uran, Uysal, Uneri, Yilmaz, Yilmaz, Acikel, Aktas, Alaca, Alic, Almbaidheen, Ari, Aslan, Atabay, Ay, Aydemir, Ayranci, Babadagi, Bayar, Bayhan, Bayram, Bektas, Berberoglu, Bostan, Cakan, Canli, Cansiz, Ceylan, Coskun, Coskun, Demir, Demir, Demirdogen and Dogan2018). MDD was diagnosed using the DSM-III-R and DSM-IV criteria and impairment was assessed by interviewing parents and teachers using a 3-point Likert scale (Karacetin et al., Reference Karacetin, Arman, Fis, Demirci, Ozmen, Hesapcioglu, Oztop, Tufan, Tural, Aktepe, Aksu, Ardic, Basgul, Bilac, Coskun, Celik, Demirkaya, Dursun, Durukan, Fidan, Gencoglan, Gokcen, Gokten, Gorker, Gormez, Gundogdu, Gurkan, Herguner, Kandemir, Kilic, Kilincaslan, Mutluer, Nasiroglu, Ozcan, Ozturk, Sapmaz, Suren, Sahin, Tahiroglu, Toros, Unal, Vural, Yazici, Yazici, Yildirim, Yulaf, Yuce, Yuksel, Akdemir, Altun, Ayik, Bilgic, Bozkurt, Cakir, Ceri, Demir, Dinc, Irmak, Karaman, Kinik, Mazlum, Memik, Ozdemir, Sinir, Tasdelen, Taskin, Ugur, Uran, Uysal, Uneri, Yilmaz, Yilmaz, Acikel, Aktas, Alaca, Alic, Almbaidheen, Ari, Aslan, Atabay, Ay, Aydemir, Ayranci, Babadagi, Bayar, Bayhan, Bayram, Bektas, Berberoglu, Bostan, Cakan, Canli, Cansiz, Ceylan, Coskun, Coskun, Demir, Demir, Demirdogen and Dogan2018). The prevalence of MDD was found to be 1.06% and there was no significant difference between males and females (Karacetin et al., Reference Karacetin, Arman, Fis, Demirci, Ozmen, Hesapcioglu, Oztop, Tufan, Tural, Aktepe, Aksu, Ardic, Basgul, Bilac, Coskun, Celik, Demirkaya, Dursun, Durukan, Fidan, Gencoglan, Gokcen, Gokten, Gorker, Gormez, Gundogdu, Gurkan, Herguner, Kandemir, Kilic, Kilincaslan, Mutluer, Nasiroglu, Ozcan, Ozturk, Sapmaz, Suren, Sahin, Tahiroglu, Toros, Unal, Vural, Yazici, Yazici, Yildirim, Yulaf, Yuce, Yuksel, Akdemir, Altun, Ayik, Bilgic, Bozkurt, Cakir, Ceri, Demir, Dinc, Irmak, Karaman, Kinik, Mazlum, Memik, Ozdemir, Sinir, Tasdelen, Taskin, Ugur, Uran, Uysal, Uneri, Yilmaz, Yilmaz, Acikel, Aktas, Alaca, Alic, Almbaidheen, Ari, Aslan, Atabay, Ay, Aydemir, Ayranci, Babadagi, Bayar, Bayhan, Bayram, Bektas, Berberoglu, Bostan, Cakan, Canli, Cansiz, Ceylan, Coskun, Coskun, Demir, Demir, Demirdogen and Dogan2018). The most obvious reason for the lower prevalence in the Turkish study is that they only included students between the second and fourth grades. In 2006, another study was conducted in Iraq, as part of the World Health Organization Mental Health Surveys (Al-Hamzawi et al., Reference Al-Hamzawi, Bruffaerts, Bromet, Alkhafaji and Kessler2015). A total of 4332 adults were screened for MDE using the DSM-IV criteria and in accordance with the Composite International Diagnostic Interview, version 3.0 (Al-Hamzawi et al., Reference Al-Hamzawi, Bruffaerts, Bromet, Alkhafaji and Kessler2015). The 12-month prevalence of MDE was 4%, while the lifetime prevalence was 7.4% (Al-Hamzawi et al., Reference Al-Hamzawi, Bruffaerts, Bromet, Alkhafaji and Kessler2015), which were higher than our estimates.
Several studies have estimated the prevalence of MDD in countries from the MENA region, and there were some discrepancies between their results and ours. One of the reasons for these discrepancies is the fact that the present study reported age-standardised values, whereas the previous studies reported the prevalence of MDD in a specific age range or reported non-standardised findings. Another possible reason is selection bias, since previous studies did not include participants from all possible areas of the country they were studying. Furthermore, MDD patients might not be willing to participate in an investigation, which will lead to an underestimation. Although the DSM-5 has similar diagnostic performance in several languages, ethnicities and cultures (Kendler et al., Reference Kendler, Aggen, Li, Lewis, Breen, Boomsma, Bot, Penninx and Flint2015), a previous study highlighted the impact of culture on the presentation of MDD with somatic symptoms, which can lead to a misdiagnosis (Raguram et al., Reference Raguram, Weiss, Keval and Channabasavanna2001).
MDD is a mood disorder with one or more MDE and is characterised by experiencing a depressed mood or a loss of interest/pleasure for almost every day over at least a two-week period (American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 2013). Also, during the MDE there must be a deviation from an individual’s baseline mood and impaired functioning must be observed in the social, occupational and other important domains (American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 2013). Although the pathogenesis of MDD remains largely unknown, several biopsychosocial factors play a role. These biological factors include genetics (Sullivan et al., Reference Sullivan, Neale and Kendler2000; Kendler et al., Reference Kendler, Gatz, Gardner and Pedersen2006; Hyde et al., Reference Hyde, Nagle, Tian, Chen, Paciga, Wendland, Tung, Hinds, Perlis and Winslow2016; Howard et al., Reference Howard, Adams, Shirali, Clarke, Marioni, Davies, Coleman, Alloza, Shen, Barbu, Wigmore, Gibson, Hagenaars, Lewis, Ward, Smith, Sullivan, Haley, Breen, Deary and Mcintosh2018; Kendler et al., Reference Kendler, Ohlsson, Lichtenstein, Sundquist and Sundquist2018), female gender (Kendler et al., Reference Kendler, Gatz, Gardner and Pedersen2006; Kendler et al., Reference Kendler, Ohlsson, Lichtenstein, Sundquist and Sundquist2018; Hasin et al., Reference Hasin, Sarvet, Meyers, Saha, Ruan, Stohl and Grant2018), preterm birth (Nosarti et al., Reference Nosarti, Reichenberg, Murray, Cnattingius, Lambe, Yin, Maccabe, Rifkin and Hultman2012), early menarche (Mendle et al., Reference Mendle, Ryan and Mckone2018) and underlying medical disorders (Li, Reference Li and Levenson2011). Although genetics is an important contributory factor, twin studies have estimated that less than half of monozygotic twins were both diagnosed with MDD (Sullivan et al., Reference Sullivan, Neale and Kendler2000; Kendler et al., Reference Kendler, Gatz, Gardner and Pedersen2006; Kendler et al., Reference Kendler, Ohlsson, Lichtenstein, Sundquist and Sundquist2018), highlighting the importance of non-genetic factors. Moreover, the heritability of MDD in females is higher than among males (Kendler et al., Reference Kendler, Gatz, Gardner and Pedersen2006; Hasin et al., Reference Hasin, Sarvet, Meyers, Saha, Ruan, Stohl and Grant2018; Kendler et al., Reference Kendler, Ohlsson, Lichtenstein, Sundquist and Sundquist2018), which may be due to differences in gene expression between the sexes (Seney et al., Reference Seney, Huo, Cahill, French, Puralewski, Zhang, Logan, Tseng, Lewis and Sibille2018). Underlying comorbidities, such as diabetes (van Dooren et al., Reference Van Dooren, Nefs, Schram, Verhey, Denollet and Pouwer2013; Wu et al., Reference Wu, Hsu and Wang2020), cardiovascular disorders (Goldstein et al., Reference Goldstein, Carnethon, Matthews, Mcintyre, Miller, Raghuveer, Stoney, Wasiak and Mccrindle2015; Worcester et al., Reference Worcester, Goble, Elliott, Froelicher, Murphy, Beauchamp, Jelinek and Hare2019) and stroke (Cai et al., Reference Cai, Mueller, Y.J., Shen and Stewart2019), can be important risk factors for MDD and are associated with poorer prognoses and higher medical costs (Moussavi et al., Reference Moussavi, Chatterji, Verdes, Tandon, Patel and Ustun2007; Taylor et al., Reference Taylor, Meader, Bird, Pilling, Creed and Goldberg2011). In addition, the association between depression and other medical conditions appears to be bidirectional (Golden et al., Reference Golden, Lazo, Carnethon, Bertoni, Schreiner, Diez Roux, Lee and Lyketsos2008; Beurel et al., Reference Beurel, Toups and Nemeroff2020), meaning that depression can be a risk factor for other medical conditions. Psychosocial contributory factors include childhood adversity (Green et al., Reference Green, Mclaughlin, Berglund, Gruber, Sampson, Zaslavsky and Kessler2010), childhood maltreatment (Nelson et al., Reference Nelson, Klumparendt, Doebler and Ehring2017; Younes et al., Reference Younes, Hallit and Obeid2021), stressful life events (Dworkin et al., Reference Dworkin, Menon, Bystrynski and Allen2017), poor social support (Rosenquist et al., Reference Rosenquist, Fowler and Christakis2011; Teo et al., Reference Teo, Choi and Valenstein2013; Gariépy et al., Reference Gariépy, Honkaniemi and Quesnel-Vallée2016) and job strain (Rosenquist et al., Reference Rosenquist, Fowler and Christakis2011; Teo et al., Reference Teo, Choi and Valenstein2013). Several studies have investigated the risk of MDD among adults who had experienced childhood adversity or maltreatment and reported a reliable higher future risk of MDD (Green et al., Reference Green, Mclaughlin, Berglund, Gruber, Sampson, Zaslavsky and Kessler2010; Nelson et al., Reference Nelson, Klumparendt, Doebler and Ehring2017; Younes et al., Reference Younes, Hallit and Obeid2021). Unfortunately, studies in the MENA countries have reported a high prevalence of childhood adversity or maltreatment among several groups of people (Panter-Brick et al., Reference Panter-Brick, Goodman, Tol and Eggerman2011; Saed et al., Reference Saed, Talat and Saed2013; Itani et al., Reference Itani, Haddad, Fayyad, Karam and Karam2014; Karam et al., Reference Karam, Fayyad, Farhat, Pluess, Haddad, Tabet, Farah and Kessler2019; Salem et al., Reference Salem, Dargham, Kamal, Eldeeb, Alyafei, Lynch, Mian and Mahfoud2020; Ustuner Top and Cam, Reference Ustuner Top and Cam2021). However, there is not enough research investigating the prevalence of childhood adversity or maltreatment in MENA countries, which makes it difficult to predict the attributable burden of childhood adversity and maltreatment in MENA. In addition, the populations of countries dealing with social unrest and war, such as Afghanistan, Sudan and Yemen, are more vulnerable to experience the psychosocial risk factors and developing MDD.
Individuals with MDD have a mortality rate that is more than two times higher than among those without MDD, and MDD reduces life expectancy by 14 years in men and 10.1 years in women (Laursen et al., Reference Laursen, Musliner, Benros, Vestergaard and Munk-Olsen2016), with men experiencing a higher excess mortality rate (Cuijpers et al., Reference Cuijpers, Vogelzangs, Twisk, Kleiboer, J. and Penninx2014). In addition, an increased likelihood of suicide attempts has also been linked to a history of MDD (Hawton and van Heeringen, Reference Hawton and Van Heeringen2009). Furthermore, the increases in the U.S. suicide rate that occurred from 2000 to 2017 were also associated with a corresponding increase in the prevalence of MDD over the same time period (Twenge et al., Reference Twenge, Cooper, Joiner, Duffy and Binau2019; Miron et al., Reference Miron, Yu, Wilf-Miron and Kohane2019). Moreover, individuals with MDD are at a higher risk of homicide (Crump et al., Reference Crump, Sundquist, Winkleby and Sundquist2013) and accidental death (Crump et al., Reference Crump, Sundquist, Winkleby and Sundquist2013). Depression causes a significant burden of disease where the quality-adjusted life expectancy in depressed people is 28.9 years lower than among non-depressed people (Jia et al., Reference Jia, Zack, Thompson, Crosby and Gottesman2015).
MDD has also been found to cause a significant economic burden in many countries. The direct and indirect cost-of-illness for depressed adults were 158% and 128% higher than for non-depressed adults, respectively (König et al., Reference König, König and Konnopka2019). More specifically, the annual cost in the United States was USD 92.2 billion in 2017 (Zhdanava et al., Reference Zhdanava, Pilon, Ghelerter, Chow, Joshi, Lefebvre and Sheehan2021), and in Iran, this figures was USD 5.3 billion in 2020 (Keshavarz et al., Reference Keshavarz, Hedayati, Rezaei, Goudarzi, Moghimi, Rezaee and Lotfi2022). Data from the Mental Health Atlas 2014 survey, conducted by World Health Organisation, estimated that most low- and middle-income countries spend less than USD 2 per person per year for the prevention and treatment of mental disorders. In contrast, high-income countries spend more than USD 50 per person per year (WHO, 2014). Despite the high economic burden of MDD, the estimated benefits of scaled-up treatment were 4.2, 5.7, 5.4 and 5.3 times higher than the associated costs of investment in low-, lower-middle-, upper-middle- and high-income countries, respectively, hopefully encouraging governments to invest more in depression-control programmes (Chisholm et al., Reference Chisholm, Sweeny, Sheehan, Rasmussen, Smit, Cuijpers and Saxena2016).
A combination of pharmacotherapy and psychotherapy is the recommended starting treatment for MDD patients (Cuijpers et al., Reference Cuijpers, Dekker, Hollon and Andersson2009). However, administrating pharmacotherapy or psychotherapy individually is a reasonable alternative to combination therapy (Kupfer et al., Reference Kupfer, Frank and Phillips2012). Although the treatment benefits after quitting psychotherapy last longer than pharmacotherapy (Parikh et al., Reference Parikh, Segal, Grigoriadis, Ravindran, Kennedy, Lam and Patten2009), pharmacotherapy with antidepressants is more common due to convenience in usage, availability, and cost. However, several studies have found that digital-based psychotherapy is as effective as traditional face-to-face psychotherapy and using this medium could reduce some of traditional psychotherapy’s drawbacks (Carlbring et al., Reference Carlbring, Andersson, Cuijpers, Riper and Hedman-Lagerlöf2018; Cuijpers et al., Reference Cuijpers, Noma, Karyotaki, Cipriani and Furukawa2019; Torous, Reference Torous2021; Araya et al., Reference Araya, Menezes, Claro, Brandt, Daley, Quayle, Diez-Canseco, Peters, Vera Cruz, Toyama, Aschar, Hidalgo-Padilla, Martins, Cavero, Rocha, Scotton, De Almeida Lopes, Begale, Mohr and Miranda2021).
Depression is the most prevalent mental health disorder in primary healthcare settings (Roca et al., Reference Roca, Gili, Garcia-Garcia, Salva, Vives, Garcia Campayo and Comas2009). Although first contact with mentally ill patients occurs in primary healthcare settings (King et al., Reference King, Nazareth, Levy, Walker, Morris, Weich, Bellón-Saameño, Moreno, Svab, Rotar, Rifel, Maaroos, Aluoja, Kalda, Neeleman, Geerlings, Xavier, De Almeida, Correa and Torres-Gonzalez2008), almost half of depressed patients are not diagnosed (Mitchell et al., Reference Mitchell, Vaze and Rao2009; Mitchell et al., Reference Mitchell, Rao and Vaze2010). Few depressed patients talk about their symptoms (John Williams, Reference John Williams2022) and almost two-thirds of depressed patients present with somatic symptoms, leading to underdiagnosis (Simon et al., Reference Simon, Vonkorff, Piccinelli, Fullerton and Ormel1999; Tylee and Gandhi, Reference Tylee and Gandhi2005). The somatic symptoms of depression are usually more common in women who are pregnant, older adults, specific ethnicities, people from low-income countries and patients with other concurrent diseases (Tylee and Gandhi, Reference Tylee and Gandhi2005). It has been reported that in high-income countries the treatment rate of depressed patients is one in five, whereas in low- and middle-income countries the rate is one in 27 (Thornicroft et al., Reference Thornicroft, Chatterji, Evans-Lacko, Gruber, Sampson, Aguilar-Gaxiola, Al-Hamzawi, Alonso, Andrade, Borges, Bruffaerts, Bunting, De Almeida, Florescu, De Girolamo, Gureje, Haro, He, Hinkov, Karam, Kawakami, Lee, Navarro-Mateu, Piazza, Posada-Villa, Galvis, Y. and Kessler2017). Thus, MDD is a serious and under-treated public health issue in the MENA region, which is mostly comprised of low- and middle-income countries.
Several studies have reported negative attitudes and the stigmatisation of those with mental illnesses (Eghtesad et al., Reference Eghtesad, Mohammadi, Shayanrad, Faramarzi, Joukar, Hamzeh, Farjam, Zare Sakhvidi, Miri-Monjar, Moosazadeh, Hakimi, Rahimi Kazerooni, Cheraghian, Ahmadi, Nejatizadeh, Mohebbi, Pourfarzi, Roozafzai, Motamed-Gorji, Montazeri, Masoudi, Amin-Esmaeili, Danaie, Mirhafez, Hashemi, Poustchi and Malekzadeh2017; AlAteeq et al., Reference Alateeq, Aldaoud, Alhadi, Alkhalaf and Milev2018; Mannarini and Rossi, Reference Mannarini and Rossi2018; Alsubaie et al., Reference Alsubaie, Almathami, Alkhalaf, Aboulyazid and Abuhegazy2020; AH et al., Reference Ah, Alshammari, Alshammari, Althagafi and Alharbi2021), which results in the underdiagnosis and undertreatment of these conditions (Fung et al., Reference Fung, Tsang, Corrigan, Lam and Cheung2007). Previous studies in the MENA region have found that a large proportion of people feel embarrassed to use psychiatric services (Eghtesad et al., Reference Eghtesad, Mohammadi, Shayanrad, Faramarzi, Joukar, Hamzeh, Farjam, Zare Sakhvidi, Miri-Monjar, Moosazadeh, Hakimi, Rahimi Kazerooni, Cheraghian, Ahmadi, Nejatizadeh, Mohebbi, Pourfarzi, Roozafzai, Motamed-Gorji, Montazeri, Masoudi, Amin-Esmaeili, Danaie, Mirhafez, Hashemi, Poustchi and Malekzadeh2017), hide their psychiatric illness from others (AlAteeq et al., Reference Alateeq, Aldaoud, Alhadi, Alkhalaf and Milev2018), have mystical beliefs about depression (AlAteeq et al., Reference Alateeq, Aldaoud, Alhadi, Alkhalaf and Milev2018; AH et al., Reference Ah, Alshammari, Alshammari, Althagafi and Alharbi2021) and negative attitudes toward mental illness (Alsubaie et al., Reference Alsubaie, Almathami, Alkhalaf, Aboulyazid and Abuhegazy2020). Consequently, the governments of the MENA countries should increase public awareness and empower communities to overcome the negative attitudes and stigma associated with depression and other mental illnesses.
The early diagnosis and treatment of MDD can lead to improvements in baseline symptoms, a lower risk of recurrence and suicide, as well as a better response to antidepressants (Bukh et al., Reference Bukh, Bock, Vinberg and Kessing2013). Aside from the benefits of early diagnosis and treatment, the difficulties in diagnosing MDD and the high prevalence of MDD highlight the importance of population screening (John Williams, Reference John Williams2022). Screening for psychiatric symptoms during routine health visits is recommended (John Williams, Reference John Williams2022, Rubenstein Lv et al., Reference Rubenstein Lv and Danz2019), as it is cost-effective (Jiao et al., Reference Jiao, Rosen, bellanger, Belkin and Muennig2017) and without any adverse consequences (Siu et al., Reference Siu, Bibbins-Domingo, Grossman, Baumann, Davidson, Ebell, García, Gillman, Herzstein, Kemper, Krist, Kurth, Owens, Phillips, Phipps and Pignone2016). A screening approach using the PHQ-2 as a verbal pre-screening exam before using the PHQ-9 screening tool, where needed, has been found to be efficient and easy for clinicians to use (John Williams, Reference John Williams2022). In addition to screening, administering preventive psychological interventions for subthreshold depressed individuals has also been found to be effective, leading to a 21% reduction in the incidence of depressive disorders (van Zoonen et al., Reference Van Zoonen, Buntrock, Ebert, Smit, Reynolds, Beekman and Cuijpers2014).
Collaborative care, which consists of a primary care clinician, a case manager and a mental health specialist, is an efficient method for delivering psychiatric treatment in a primary healthcare setting (Archer et al., Reference Archer, Bower, Gilbody, Lovell, Richards, Gask, Dickens and Coventry2012). Several studies have reported that collaborative care, compared to standard care, had a higher remission rate (Sighinolfi et al., Reference Sighinolfi, Nespeca, Menchetti, Levantesi, Belvederi Murri and Berardi2014), better response rate (Archer et al., Reference Archer, Bower, Gilbody, Lovell, Richards, Gask, Dickens and Coventry2012), and the positive results were more enduring (Archer et al., Reference Archer, Bower, Gilbody, Lovell, Richards, Gask, Dickens and Coventry2012; Richards et al., Reference Richards, Bower, Chew-Graham, Gask, Lovell, Cape, Pilling, Araya, Kessler, Barkham, Bland, Gilbody, Green, Lewis, Manning, Kontopantelis, Hill, Hughes-Morley and Russell2016). Although collaborative care costs more than standard care, integrating psychiatric treatment with primary health care is more cost-effective (van Steenbergen-Weijenburg et al., Reference Van Steenbergen-Weijenburg, Van Der Feltz-Cornelis, Horn, Van Marwijk, Beekman, Rutten and Hakkaart-Van Roijen2010). Nonetheless, studies investigating the performance of collaborative care in the MENA countries are rare (Amini et al., Reference Amini, Shakiba, Sharifi, Shirazi, Sadeghi, Abolhasani and Hajebi2016) and further studies are needed to investigate the effectiveness of this approach in the MENA region.
Study strengths and limitations
The current study provided the first and most up-to-date estimation of the burden of MDD in the MENA region, and its constituent countries, between 1990 and 2019. In order to overcome some of the underestimated burden of MDD, the estimates were modified based on the calculation of excess mortality from suicides attributable to MDD (Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020). Moreover, in order to model the most accurate estimations, four adjustment ratios were used for modelling MDD, including a recall bias ratio, symptom scale ratio, the World Health Survey ratio and the lay interviewer ratio (Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020). However, this study has several methodological limitations, which have been described in previous GBD publications (Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020; Murray et al., Reference Murray, Aravkin, Zheng, Abbafati, Abbas, Abbasi-Kangevari, Abd-Allah, Abdelalim, Abdollahi and Abdollahpour2020). Firstly, due to the low number of epidemiological studies about MDD in low-income countries and in countries dealing with social unrest and war, such as Afghanistan, Sudan and Yemen, these estimations should be interpreted with some degree of caution (Vos et al., Reference Vos, Lim, Abbafati, Abbas, Abbasi, Abbasifard, Abbasi-Kangevari, Abbastabar, Abd-Allah and Abdelalim2020). Secondly, MDD has several specifiers (such as MDD with mixed features, with melancholic features, atypical features, etc.) with differences in epidemiological values (American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 2013), while in the current study the burden of each specifier was not calculated. Thirdly, only the regional burden of MDD was estimated, while the attributable risk factors in individual countries were not reported. Finally, depressive disorders were classified as MDD and dysthymia in the GBD project, while the present study only evaluated the burden of MDD. Therefore, future research needs to investigate the overall burden of depressive disorders combined.
Conclusions
The burden of MDD in the MENA region did not change significantly from 1990 to 2019. However, considering the high prevalence, along with the substantial economic and epidemiological burden of the disease, MDD remains a serious public health issue for both patients and their communities. The findings of our research highlight the unmet need for regularly updated health data, together with the development of appropriate guidelines and regulations to aid in the early detection and successful treatment of MDD in all MENA countries.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/neu.2023.42.
Availability of data and materials
The data used for these analyses are all publicly available at http://ghdx.healthdata.org/gbd-results-tool.
Acknowledgements
The authors acknowledge the Institute for Health Metrics and Evaluation staff and their collaborators who prepared these publicly available data. We would also like to thank the Clinical Research Development Unit of Tabriz Valiasr Hospital, Tabriz University of Medical Sciences, Tabriz, Iran for their assistance in this research.
Author contributors
SS, AAK and RSF designed the study. SS analysed the data and performed the statistical analyses. SEM, SAN, MN, MJMS and SS drafted the initial manuscript. All authors reviewed the drafted manuscript for critical content. All authors approved the final version of the manuscript.
Financial support
The Bill and Melinda Gates Foundation, who were not involved in any way in the preparation of this manuscript, funded the GBD study. The Shahid Beheshti University of Medical Sciences, Tehran, Iran (Grant No. 43003740), also supported the present report.
Competing interests
None.
Ethics approval
The present study was approved by the ethics committee of the Shahid Beheshti University of Medical Sciences (IR.SBMU.RETECH.REC.1401.851).
