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Cambridge Prisms: Global Mental Health logoLink to Cambridge Prisms: Global Mental Health
. 2022 Jun 14;9:250–263. doi: 10.1017/gmh.2022.29

Prevalence of mental disorders in refugees and asylum seekers: a systematic review and meta-analysis

Martina Patanè 1,✉, Samrad Ghane 2, Eirini Karyotaki 1, Pim Cuijpers 1, Linda Schoonmade 3, Lorenzo Tarsitani 4, Marit Sijbrandij 1
PMCID: PMC9806970  PMID: 36618716

Abstract

Background

Studies have identified high rates of mental disorders in refugees, but most used self-report measures of psychiatric symptoms. In this study, we examined the percentages of adult refugees and asylum seekers meeting diagnostic criteria for major depressive disorder (MDD), post-traumatic stress disorder, bipolar disorder (BPD), and psychosis.

Methods

A systematic literature search in three databases was conducted. We included studies examining the prevalence of MDD, post-traumatic stress disorder, BPD, and psychosis in adult refugees according to a clinical diagnosis. To estimate the pooled prevalence rates, we performed a meta-analysis using the Meta-prop package in Stata (PROSPERO: CRD42018111778).

Results

We identified 7048 records and 40 studies (11 053 participants) were included. The estimated pooled prevalence rates were 32% (95% CI 26–39%; I2 = 99%) for MDD, 31% (95% CI 25–38%; I2 = 99.5%) for post-traumatic stress disorder, 5% (95% CI 2–9%; I2 = 97.7%) for BPD, and 1% (95% CI 1–2%; I2 = 0.00%) for psychosis. Subgroup analyses showed significantly higher prevalence rates of MDD in studies conducted in low-middle income countries (47%; 95% CI 38–57%, p = 0.001) than high-income countries studies (28%; 95% CI 22–33%), and in studies which used the Mini-International Neuropsychiatric Interview (37%; 95% CI 28–46% p = 0.05) compared to other diagnostic interviews (26%; 95% CI 20–33%). Studies among convenience samples reported significant (p = 0.001) higher prevalence rates of MDD (35%; 95% CI 23–46%) and PTSD (34%; 95% CI 22–47%) than studies among probability-based samples (MDD: 30%; 95% CI 21–39%; PTSD: 28%; 95% 19–37%).

Conclusions

This meta-analysis has shown a markedly high prevalence of mental disorders among refugees. Our results underline the devastating effects of war and violence, and the necessity to provide mental health intervention to address mental disorders among refugees. The results should be cautiously interpreted due to the high heterogeneity.

Key words: Mental disorders, meta-analysis, prevalence, refugees

Introduction

During the past decade, the trend of global displacement has been growing (UNHCR, 2020). In 2020, the United Nations High Commissioner for Refugees (UNCHR) estimated that more than 11 million people have been displaced throughout the year, and the proportion of this population has been continued to rise, despite the COVID-19 pandemic and closure of borders (UNHCR, 2020). Although refugees (people who, owing to a well-founded fear of persecution, are forced to escape from his or her country) and asylum seekers (people seeking protection from persecution or serious harm in a country other than their own) are defined in different ways (UNHCR, 2020), both groups may have been forced to face various stressors, such as persecution, violence, torture, detention, and the loss of homes and livelihoods. Such traumatic events may result in persistent mental health problems and overall decreased functioning (Steel et al., 2009; Marquez, 2016).

During the last years, several studies have examined the prevalence of mental disorders in refugees and asylum seekers. However, the resulting prevalence rates in this population present great variability (Fazel et al., 2005; Porter and Haslam, 2005; Bogic et al., 2015; Foo et al., 2018; Morina et al., 2018; Charlson et al., 2019; Blackmore et al., 2020), ranging from 5% (Fazel et al., 2005) to 80% (Bogic et al., 2015) for depression, from 4% (Charlson et al., 2019) to 88% (Morina et al., 2018) for PTSD, and from 1.5% (Blackmore et al., 2020) to 2% (Fazel et al., 2005) for psychosis. A systematic review on the prevalence of serious mental disorders in refugees resettled in high-income western countries reported weighted average rates of 5% for major depressive disorder (MDD), 9% for posttraumatic stress disorder (PTSD) and 2% for psychotic disorders (Fazel et al., 2005). A meta-analysis among refugees and asylum seekers residing outside their country of origin reported a prevalence of 31.5% for PTSD, of 31.5% for depression, and 1.5% for psychosis (Blackmore et al., 2020). Another meta-analysis that examined the prevalence of mental disorders in conflict settings showed estimated rates of 22.1% for any mental disorder (13% for depression and 4% for PTSD) (Charlson et al., 2019). The variability across studies could be explained by differences in the origins and background of the analysed populations, the sample size, the sampling methods, and the diagnostic tools used (e.g. self-report, semi-structured or structured clinical interview) (Westermeyer and Janca, 1997; de Jong et al., 2003; Fazel et al., 2005; Bogic et al., 2015; Giacco et al., 2018; Giacco and Priebe, 2018; Charlson et al., 2019). Furthermore, the nature of the displacement, the context of the emergency, as well as the aspects of the host country/environment are additional aspects to consider in the variability of these studies (Giacco and Priebe, 2018).

Many epidemiological studies use self-report instruments to estimate the prevalence of mental disorders in refugees because they are easily administered and cost effective. However, such instruments overestimate prevalence rates considerably (Domken et al., 1994; Fazel et al., 2005; Steel et al., 2009). In fact, self-report instruments have been shown to overestimate true PTSD-rates by a factor of about 3.5 (Engelhard et al., 2007). Similar results have been also shown in depression studies (Domken et al., 1994; Steel et al., 2009; Krebber et al., 2014). One of the reasons is that many self-report instruments are designed for quickly picking-up mental disorders while minimising false negatives, therefore cut-offs are set with high sensitivity. Therefore, they identify more patients who may have a mental disorder than those diagnosed with clinician-administered interviews (Thombs et al., 2018). Another reason could be that self-report tools usually do not take functional impairment due to symptoms into account (McKnight and Kashdan, 2009). Besides, translations of existing self-report instruments may not adequately measure psychiatric symptoms across cultures (Hunt and Bhopal, 2004). Finally, overestimation may occur as a consequence of the so-called over-endorsement bias, the tendency of respondents to generously claim different types of symptoms on a checklist (Kroenke, 2001). Thus, more rigorous instruments, such as clinical diagnostic interviews, are more appropriate to estimate the prevalence of mental health disorders in refugees and asylum seekers (Fazel et al., 2005; Steel et al., 2009). In addition, clinicians' experience in using structured interviews can increase the reliability of symptoms measurement and psychiatric diagnoses even among samples with different cultural backgrounds (Alarcon et al., 1999; Aboraya et al., 2006). Nevertheless, among the structured and semi-structured interviews there may also be some differences in accuracy. For example, studies have shown that the Mini-International Neuropsychiatric Interview – MINI, which has been designed as a briefer and quicker diagnostic screen than other interviews (Sheehan et al., 1997) identified more people as depressed than the Composite International Diagnostic Interview – CIDI, and the Structured Clinical Interview – SCID (Levis et al., 2018; Levis et al., 2019; Wu et al., 2021).

In the present study, we aimed to estimate the prevalence of diagnoses of serious mental disorders [MDD, PTSD, bipolar disorder (BPD), and psychosis] in refugees and asylum seekers from conflict-affected areas. Serious mental disorders are conditions resulting in serious functional impairment, which interferes with major life activities (NIH, 2019). Other definitions (Slade et al., 1997) take into account the duration and the disability they produce, for example in terms of the disability they are associated with. Within the Global Burden of Disease (GBD) study, the top-three mental disorders associated with the highest level of disability are MDD, BPD and psychosis (Kronenberg et al., 2017; James et al., 2018). Although not included in the GBD, PTSD is particularly relevant for refugees and asylum seekers since refugees may be exposed to multiple traumatic events, including interpersonal violence that may cause severe disability (Palic et al., 2016).

Similar to previous studies (Fazel et al., 2005; Blackmore et al., 2020), we included only studies that employed diagnostic interviews. Further, our study differs from previous studies in that we were able to include a larger number of studies than before since the number of studies increased during the past years. In addition, we were able to examine the prevalence of less common disorders such as BPD. Finally, due to the increased number of included studies, we could perform additional subgroup analyses, such as comparing the prevalence of serious mental disorders between refugees resettled in low-middle-income v. high-income countries, and among different kind of population sample (convenience samples v. probability-based samples).

Method

Search strategy and selection criteria

We report our meta-analysis according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement (www.prisma-statement.org) (Moher et al., 2009) (see online Supplementary materials).

The present study was registered in PROSPERO on 5th December 2018 under the number: CRD42018111778.

A comprehensive search was performed in the bibliographic databases PubMed, Embase.com and APA PsycInfo (via Ebsco) from inception to June 4, 2020, by a medical librarian. Search terms included controlled terms (MeSH in PubMed, Emtree in Embase and PsycINFO thesaurus terms) as well as free text terms. The following terms were used (including synonyms and closely related words) as index terms or free-text words: ‘refugees’ and ‘mental illnesses’. A search filter was used to limit the results to adults. The search was performed without date or language restrictions. Duplicate articles were excluded. The full search strategies for all databases can be found in the online Supplementary materials.

Studies were considered eligible for this meta-analysis if they examined (a) the prevalence of serious mental disorders (MDD, PTSD, BPD, and psychosis), (b) in an adult (⩾18 years) population of refugees and asylum seekers who had to cross their country borders, (c) according to the criteria of Diagnostic and Statistical Manual of Mental Disorders (DSM III, IV, or 5) or International Classification of Diseases (ICD 9 or10) (d) assessed with a structured or semi-structured clinical interview, such as the Structured Clinical Interview – SCID, Mini-International Neuropsychiatric Interview – MINI, or Composite International Diagnostic Interview – CIDI. No cut-off has been considered to evaluate the diagnosis' severity. Disorders have been evaluated serious according with the National Institute of Mental Health (NIH) and GBD considerations (Kronenberg et al., 2017; James et al., 2018; NIH, 2019).

The definitions of refugees (a person who, owing to a well-founded fear of persecution, is forced to escape from his or her country) and asylum seekers (a person who seeks protection from persecution or serious harm in a country other than their own) were in agreement with the UNHCR Master Glossary of Terms (UNHCR, 2006) and Asylum and Migration Glossary 6.0 (Network, 2018). No restrictions were applied to the origin of the studies. Cross-sectional studies, follow-up studies, cohort data studies and register-based studies were eligible. To reduce possible selection bias, we excluded studies conducted on samples selected in psychiatric services and concerning internally displaced people (IDPs) (UNHCR, 2006).

All title and abstracts were screened by two researchers independently (MP/MS or SG). We retrieved the full texts of all abstracts that seemed eligible for inclusion. Subsequently, we performed a full-text selection according to our pre-specified eligibility criteria. Disagreements between the reviewers were resolved by discussion.

Data extraction

For every eligible study, two reviewers independently (MP/MS or SG) extracted data related to the year of publication, the country of data collection, the country of the refugees' origins, the sample size of the population, the age, the gender, the time elapsed as refugees or asylum seekers, the diagnostic tool used. Finally, we extracted the prevalence rates of MDD (current episode and recurrent), PTSD, BPD and psychotic disorder. In the absence of absolute numbers and if allowed by the data reported, the percentages of prevalence rates were converted into numbers. The time since displacement was reported in three different categories: (1) people who have spent more than five years as refugees or asylum seekers (⩾5), (2) people who have spent between 5 years and 1 year as refugees or asylum seekers (>1 < 5) and (3) people who have spent less then 1 year as refugees or asylum seekers. Countries were categorised as low-, middle- (LMIC) and in high-income (HIC) based on the World Bank list of economies 2020 (WBC, 2020).

Quality assessment

Two reviewers (MP/MS or SG) evaluated the assessment of the methodological quality of individual studies using a modified version of the Joanna Briggs tool – JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data (Munn et al., 2015) based on five questions, which permitted a critical assessment of prevalence rates: (1) Were study participants recruited in an appropriate way? (2) Was the sample size adequate? (3) Were the study subjects and the setting described in detail? (4) Was the condition measured in a standard, reliable way for all participants? (5) Was the response rate adequate, and if not, was the low response rate managed appropriately?. The response categories per each question were yes, unclear, and no. Three or more unclear or negative answers were considered to define a study with a high risk of bias (see online Supplementary materials). Any disagreements were resolved through discussion or by involving a third reviewer (PC).

Data synthesis and statistical analysis

The prevalence rates of serious mental disorders were calculated by pooling the study-specific estimates. To stabilise the variance of binomial data, the Freeman-Tukey double arcsine transformation was used (Miller, 1978). Because we expected considerable heterogeneity between studies, we computed the pooled estimates under the random effects (DerSimonian and Laird) model based on the transformed values and their variance (Nyaga et al., 2014). The I2 was calculated as an indicator of the inter-study heterogeneity in percentages. Values of I2 are considered low, moderate and high when I2 equals 25, 50, and 75% respectively (Melsen et al., 2014). Based on previous meta-analyses on prevalence rates, we expected considerable heterogeneity in the prevalence estimates (Higgins, 2008; Charlson et al., 2019; Blackmore et al., 2020). To examine possible sources of heterogeneity between the included studies, we ran subgroups under the mixed-effects model with inverse-variance weights under the random-effects model (time since displacement ⩾ 5 years v. time since displacement >1 < 5years v. time since displacement <1year, MINI v. other diagnostic interviews, LMICs v. HICs, high risk of bias v. low risk of bias, convenience samples v. probability-based samples). Prevalence rates were calculated per each disorder separately. Pooled rates for subgroups were indicated, when at least three studies were present for each disorder. All statistical analyses were conducted using Meta-prop package in STATA/SE 16.1 for Mac (Nyaga et al., 2014).

Results

We initially identified 11 749 records. After exclusion of duplicates, 7048 records remained. We excluded 6705 studies based on titles and abstracts selection. We examined 343 full texts against our eligibility criteria and included 40 studies in the present meta-analysis (Fig. 1).

Fig. 1.

Fig. 1.

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Study identification, screening, and eligibility test, following the Preferred Reporting Items of Systematic Reviews (PRISMA).

Studies included were conducted across 18 countries, 7 LMICs (Van Ommeren et al., 2001a; Akinyemi et al., 2012; Llosa et al., 2014; Naja et al., 2016; Tekin et al., 2016; Kazour et al., 2017; Segal et al., 2018; Tekeli-Yesil et al., 2018; Ainamani et al., 2020; Bapolisi et al., 2020; Civan Kahve et al., 2020; Kaur et al., 2020; Sagaltici et al., 2020) (Lebanon, Malaysia, Nepal, Nigeria, Turkey, Syria and Uganda) and 11 HICs (Hinton et al., 1993; Cheung, 1994; Steel et al., 2002; Turner et al., 2003; Fenta et al., 2004; Laban et al., 2004; Momartin et al., 2004; Marshall et al., 2005; Bhui et al., 2006; Renner et al., 2006; Von Lersner et al., 2008; Maier et al., 2010; Eckart et al., 2011; Jakobsen et al., 2011; Bogic et al., 2012; Heeren et al., 2012; Rasmussen et al., 2012; Tay et al., 2013; Hocking et al., 2015; 2018; Wright et al., 2017; Kizilhan, 2018; Nose et al., 2018; Richter et al., 2018; Rees et al., 2019; Wulfes et al., 2019; Sundvall et al., 2020) (Australia, Austria, Canada, Germany, Italy, New Zealand, Norway, Switzerland, The Netherlands, United Kingdom and United States of America) and they reported the prevalence of mental disorders of 11 053 participants (5309 men – 48%). Of these 11 053 participants, 6897 (62.3%) had taken part in population-based representative surveys (PBR). The majority of the studies included have used MINI as diagnostic interview (Bhui et al., 2006; Von Lersner et al., 2008; Maier et al., 2010; Akinyemi et al., 2012; Bogic et al., 2012; Heeren et al., 2012; Llosa et al., 2014; Hocking et al., 2015, 2018; Naja et al., 2016; Kazour et al., 2017; Nose et al., 2018; Richter et al., 2018; Segal et al., 2018; Tekeli-Yesil et al., 2018; Rees et al., 2019; Bapolisi et al., 2020; Kaur et al., 2020; Sundvall et al., 2020). CIDI was used by 7 studies (Van Ommeren et al., 2001a; Steel et al., 2002; Fenta et al., 2004; Laban et al., 2004; Marshall et al., 2005; Jakobsen et al., 2011; Rasmussen et al., 2012), SCID by six studies (Hinton et al., 1993; Tay et al., 2013; Tekin et al., 2016; Wright et al., 2017; Kizilhan, 2018; Wulfes et al., 2019) and one study (Cheung, 1994) used the Diagnostic Interview Schedule – DIS. The Clinician-Administered PTSD Scale – CAPS and the PTSD Symptom Scale–Interview- PSS-I were used by six studies (Turner et al., 2003; Momartin et al., 2004; Renner et al., 2006; Eckart et al., 2011; Civan Kahve et al., 2020; Sagaltici et al., 2020) and one study (Ainamani et al., 2020) respectively (Table 1).

Table 1.

Studies meeting inclusion criteria

Study Country of study Country category Population Sample size, n PBR Age, n – M (s.d.) Gender, n Time since displacement (years) Questionnaire MDD, n MDD Recurrent ep, n PTSD,n Bipolar disorders, n Pychotic disorders, n (%) RoB
Ainamani et al. (2020) Uganda LMIC Congolese 325 No M 31.9
F 30.9		 M 143
F 182		 NR PSS-I NR NR 285/325 NR NR High
Akinyemi et al. (2012) Nigeria LMIC Liberian, Sierra Leonean, Togolese 444 Yes 34.8 (±12.8) M 263
F 181		 ⩾5 MINI 201/444 NR 150/444 114/444 NR Low
Bapolisi et al. (2020) Uganda LMIC Congolese, Burundian, Somali, Rwandese, Ethiopian, Eritrean, Sudanese 387 Yes 33.01 (±12.2) M 168
F 219		 >1 < 5 MINI 226/387 NR 260/387 NR NR Low
Bhui et al. (2006) UK HIC Somali 143 No ⩾18 M 71
F 72		 <1 MINI 38/143 13/143 20/143 0/143 1/143 Low
Bogic et al. (2012) Germany, Italy and UK HIC Former Yugoslavia 854 Yes 41.6 (±10.8) M 416
F 438		 ⩾5 MINI 292/851 132/846 282/854 16/850 11/854 High
Cheung (1994) New Zealand HIC Cambodian 223 Yes ⩾18 M 104
F 119		 >1 < 5 DIS NR NR 27/223 NR NR Low
Civan Kahve et al. (2020) Turkey LMIC Iraqi 101 No M 49
F 52		 >1 < 5 CAPS NR NR 9/101 NR NR Low
Eckart et al. (2011) Germany HIC Albanian, Kurdish, Romanian, Serbian, Turkish 52 No ⩾18 M 52
F 0		 NR CAPS
MINI		 17/52 NR 20/52 NR NR High
Fenta et al. (2004) Canada HIC Ethiopian 325 No 35.3 (±7.2) M 203
F 139		 ⩾5 CIDI 20/325 33/342 NR NR NR High
Heeren et al. (2012) Switzerland HIC African, Asian, European 86 No NR M 60
F 26		 NR MINI 27/86 NR 20/86 NR NR High
Hinton et al. (1993) USA HIC Vietnamese, Chinese 201 NR 33.2 (±12.0) M 96
F 105		 <1 SCID 11/201 NR 7/201 NR NR High
Hocking et al. (2015) Australia HIC Sri Lanka, Pakistan, Zimbabwe, Iraqi, Afghan, Iranian, Lebanon 98 No 34.6 (±10.6) M 87
F 11		 NR MINI 58/95 NR 49/94 NR NR High
Hocking et al. (2018) Australia HIC Asia 185 NR ⩾18 M 129
F 56		 >1 < 5 MINI 56/185 NR NR NR NR High
Jakobsen et al. (2011) Norway HIC Middle East, North African, Somali, Former Yugoslavia 64 No 33 (±11.6) M 34
F 30		 >1 < 5 CIDI 21/64 NR 29/64 NR NR Low
Kaur et al. (2020) Malaysia LMIC Rohingya 220 Yes 33.5 M 116
F 104		 >1 < 5 MINI 71/220 NR 84/220 NR NR Low
Kazour et al. (2017) Lebanon LMIC Syrian 452 No 35.05 (±12.3) M 200
F 252		 <1 MINI NR NR 123/452 NR NR High
Kizilhan (2018) Germany HIC Yazidi 296 No 23.72 (±2.62) F 296 >1 < 5 SCID 158/296 NR 144/296 NR NR High
Laban et al. (2004) The Netherlands HIC Iraqi 294 Yes ⩾18 M 190
F 104		 >1 < 5 CIDI 85/294 13/294 108/294 NR NR Low
Llosa et al. (2014) Lebanon LMIC Palestinian 194 Yes 41.5 (±15.1) M 56
F 138		 NR MINI 31/194 48/194 9/194 3/194 5/194 Low
Maier et al. (2010) Switzerland HIC Asian, African, European 78 No 29.9 (± 8.4) M 57
F 21		 >1 < 5 MINI 26/78 NR 19/78 NR NR High
Marshall et al. (2005) USA HIC Cambodian 490 Yes 52 (±13.4) M 171
F 319		 ⩾5 CIDI 248/490 NR 301/490 NR NR Low
Momartin et al. (2004) Australia HIC Bosnian 126 No 47 M 49
F 77		 NR CAPS NR NR 79/126 NR NR Low
Naja et al. (2016) Lebanon LMIC Syrian 310 No 18-65 M 120
F 189		 NR MINI 136/310 NR NR NR NR High
Nose et al. (2018) Italy HIC Pakistan, Afghan, African, Ex-Yugoslavia 109 No 30.0 (±7.60) M 109 >1 < 5 MINI 6/109 NR 9/109 NR NR Low
Rasmussen et al. (2012) USA HIC Mexican, South America, Chinese, Vietnamese 660 Yes ⩾18 M 345
F 315		 NR CIDI 97/660 NR 8/660 NR NR Low
Rees et al. (2019) Australia HIC Arabic countries, Sri Lanka, Sudan. 289 Yes 30.0 (±75.8) F 289 <1
>1 < 5
⩾5		 MINI 94/289 NR NR NR NR Low
Renner et al. (2006) Austria HIC Chechnya, Afghan, West African 150 No ⩾18 M 110
F 40		 NR CAPS NR NR 32/150 NR NR High
Richter et al. (2018) Germany HIC Iraninan, Russian, Iraqi, Afghan, Azerbaijan 125 No 31.9 (± 0.6) M 83
F 42		 <1 MINI 9/125 7/125 22/125 NR 1/125 High
Sagaltici et al. (2020) Turkey LMIC Syrian 342 Yes 33.7 (±10.0) M 163
F 179		 >1 < 5 CAPS NR NR 106/342 NR NR High
Segal et al. (2018) Lebanon LMIC Syrian, Palestinian 254 No 40.4 (±13.5) M 114
F 140		 >1 < 5 Modified-MINI NR NR 13/254 NR 2/254 High
Steel et al. (2002) Australia HIC Vietnamese 1161 Yes 41 (±14.2) M 472
F 689		 ⩾5 CIDI 29/1161 NR 51/1161 NR NR Low
Sundvall et al. (2020) Sweden HIC Iraqi 31 No 48 F 14
M 17		 ⩾5 MINI 9/30 NR 13/30 NR NR High
Tay et al. (2013) Australia HIC Afghan, Chinese, Ganese, Iranian, Zimbabwe 52 No 39 (±13.5) M 34
F18		 <1 SCID 30/52 NR 31/52 NR NR Low
Tekeli-Yesil et al. (2018) Turkey – Syria LMIC Syrian 285 No 34.19 (± 1.7) M 144
F 141		 >1 < 5 MINI 201/285 104/238 85/285 NR NR High
Tekin et al. (2016) Turkey LMIC Iraqi 238 Yes 32.70 (±11.8) M 105
F 133		 <1 SCID 94/238 NR 102/238 NR NR Low
Turner et al. (2003) UK HIC Kosovo 120 No 37.1 M 56
F 64		 NR CAPS NR NR 46/118 NR NR High
Van Ommeren et al. (2001a, 2001b) Nepal LMIC Bhutanese 810 Yes ⩾18 M 616
F 194		 ⩾5 CIDI 23/810 139/810 197/810 NR NR Low
von Lersner et al. (2008) Germany HIC former Yugoslavia, Turkhis 53 No 38.3 (±10.3) M 25
F 28		 ⩾5 MINI 27/53 NR 29/53 1/53 NR Low
Wright et al. (2017) USA HIC Iraqi 291 Yes 34.30 (±11.3) M 158
F 133		 NR SCID 8/291 NR 11/291 NR NR Low
Wulfes et al. (2019) Germany HIC Afghan, Iranian, Iraqi, Syrian, Sudan 118 No 32.9 (±13.1) M 76
F 42		 NR SCID 39/118 NR 35/118 NR NR High
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PBR, population-based representative surveys; CAPS, Clinician-Administered PTSD Scale; CIDI, Composite International Diagnostic Interview; DIS, Diagnostic Interview Schedule; HIC, High-income country; LMIC, Low middle-income country; MDD, Major depressive disorder; MINI, The Mini-International Neuropsychiatric Interview; NR, Not reported; PSS-I, PTSD Symptom Scale–Interview; SCID, The Structured Clinical Interview for DS.

The prevalence of MDD was reported in 31 studies (Hinton et al., 1993; Van Ommeren et al., 2001a; Steel et al., 2002; Fenta et al., 2004; Laban et al., 2004; Marshall et al., 2005; Bhui et al., 2006; Von Lersner et al., 2008; Maier et al., 2010; Eckart et al., 2011; Jakobsen et al., 2011; Akinyemi et al., 2012; Bogic et al., 2012; Heeren et al., 2012; Rasmussen et al., 2012; Tay et al., 2013; Llosa et al., 2014; Hocking et al., 2015, 2018; Naja et al., 2016; Tekin et al., 2016; Wright et al., 2017; Kizilhan, 2018; Nose et al., 2018; Richter et al., 2018; Tekeli-Yesil et al., 2018; Rees et al., 2019; Wulfes et al., 2019; Bapolisi et al., 2020; Kaur et al., 2020; Sundvall et al., 2020): 23 reported only the prevalence of a current episode of MDD (Hinton et al., 1993; Steel et al., 2002; Marshall et al., 2005; Von Lersner et al., 2008; Maier et al., 2010; Eckart et al., 2011; Jakobsen et al., 2011; Akinyemi et al., 2012; Heeren et al., 2012; Rasmussen et al., 2012; Tay et al., 2013; Hocking et al., 2015, 2018; Naja et al., 2016; Tekin et al., 2016; Wright et al., 2017; Kizilhan, 2018; Nose et al., 2018; Rees et al., 2019; Wulfes et al., 2019; Bapolisi et al., 2020; Kaur et al., 2020; Sundvall et al., 2020) (MDD) and 8 reported also prevalence of recurrent episode of MDD (reMDD) (Van Ommeren et al., 2001a; Fenta et al., 2004; Laban et al., 2004; Bhui et al., 2006; Bogic et al., 2012; Llosa et al., 2014; Richter et al., 2018; Tekeli-Yesil et al., 2018) (Table 1). The pooled prevalence rate of MDD was 32% (95% CI 26–39%) with a very high heterogeneity between sample (I2 = 99.05%; p = 0.000) (Table 2 and figure 2.1). The random-effects pooled prevalence of reMDD was 16% (95% CI 10–22%) and the rates ranged from 4% to 44% (I2 = 96.3%; p = 0.000) (Table 2 and figure 2.2).

Table 2.

Prevalence rates of serious mental disorders

Mental disorder Prevalence rate (%) Prevalence rates Heterogeneity (I2) (%) p
Random pooled ES (95% CI)
MDD 32 26–39% 99.05 0⋅000
MDD (outliers removed) 33 31–35% 0.0 0.64
MDD recurrent episode 16 10–22% 96.3 0⋅000
PTSD 31 25–38% 99.3 0⋅000
PTSD (outliers removed) 32 30–35% 50.2 0.05
BPD 5 2–9% 97.7 0⋅000
Psychosis 1 1–2% 0.00 0⋅000
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MDD, Major depressive disorder; PTSD, Post-traumatic stress disorder; BPD, Bipolar disorder.

The prevalence of PTSD was reported in 36 studies (Hinton et al., 1993; Cheung, 1994; Van Ommeren et al., 2001b; Steel et al., 2002; Turner et al., 2003; Laban et al., 2004; Momartin et al., 2004; Marshall et al., 2005; Bhui et al., 2006; Renner et al., 2006; Von Lersner et al., 2008; Maier et al., 2010; Eckart et al., 2011; Jakobsen et al., 2011; Akinyemi et al., 2012; Bogic et al., 2012; Heeren et al., 2012; Rasmussen et al., 2012; Tay et al., 2013; Llosa et al., 2014; Hocking et al., 2015; Tekin et al., 2016; Kazour et al., 2017; Wright et al., 2017; Kizilhan, 2018; Nose et al., 2018; Richter et al., 2018; Segal et al., 2018; Tekeli-Yesil et al., 2018; Wulfes et al., 2019; Ainamani et al., 2020; Bapolisi et al., 2020; Civan Kahve et al., 2020; Kaur et al., 2020; Sagaltici et al., 2020; Sundvall et al., 2020) (Table 1). The random-effects pooled prevalence of PTSD was 31% (95% CI 25–38%) and the rates ranged from 1% to 88%. The heterogeneity between samples was high (I2 = 99.3%; p = 0.000) (Table 2 and figure 2.3).

The prevalence of BPD was reported in five articles (Bhui et al., 2006; Von Lersner et al., 2008; Akinyemi et al., 2012; Bogic et al., 2012; Llosa et al., 2014) (Table 1) and the random-effects pooled prevalence was 5% (95% CI 2–9%; I2 = 97.7%) (Table 2 and figure 2.4).

The prevalence of psychotic disorders was reported in five articles (Bhui et al., 2006; Bogic et al., 2012; Llosa et al., 2014; Richter et al., 2018; Segal et al., 2018) (Table 1). The random-effects pooled prevalence of the psychosis was 1% (95% CI 1–2%; I2 = 0.00%) (Table 2 and figure 2.5).

To reduce the high heterogeneity and confirm our prevalence rates, we also ran analyses without the outliers when it was possible. The analysis showed a prevalence of 33% of MDD and 32% of PTSD (Table 2 and online Supplementary materials).

Subgroups analysis showed a significant prevalence rates difference (p = 0.001) of MDD between studies conducted in refugees resettled in LMICs (Akinyemi et al., 2012; Llosa et al., 2014; Naja et al., 2016; Tekin et al., 2016; Tekeli-Yesil et al., 2018; Bapolisi et al., 2020; Kaur et al., 2020) (47%; 95% CI 38–57%) and those in HICs (Hinton et al., 1993; Van Ommeren et al., 2001a; Steel et al., 2002; Fenta et al., 2004; Laban et al., 2004; Momartin et al., 2004; Marshall et al., 2005; Bhui et al., 2006; Von Lersner et al., 2008; Maier et al., 2010; Eckart et al., 2011; Jakobsen et al., 2011; Bogic et al., 2012; Heeren et al., 2012; Rasmussen et al., 2012; Tay et al., 2013; Hocking et al., 2015, 2018; Wright et al., 2017; Kizilhan, 2018; Nose et al., 2018; Richter et al., 2018; Rees et al., 2019; Wulfes et al., 2019; Sundvall et al., 2020) (28%; 95% CI 22–33%) (Table 3 and figure 3.1). Besides, a significant (p = 0.05) higher prevalence rate of MDD (37%; 95% CI 28–46%) has been reported in studies (Bhui et al., 2006; Von Lersner et al., 2008; Maier et al., 2010; Eckart et al., 2011; Akinyemi et al., 2012; Bogic et al., 2012; Heeren et al., 2012; Llosa et al., 2014; Hocking et al., 2015, 2018; Naja et al., 2016; Nose et al., 2018; Richter et al., 2018; Tekeli-Yesil et al., 2018; Rees et al., 2019; Bapolisi et al., 2020; Kaur et al., 2020; Sundvall et al., 2020) conducted using the MINI as compared to studies that used others diagnostic interviews (Hinton et al., 1993; Van Ommeren et al., 2001a; Steel et al., 2002; Fenta et al., 2004; Laban et al., 2004; Momartin et al., 2004; Marshall et al., 2005; Jakobsen et al., 2011; Rasmussen et al., 2012; Tay et al., 2013; Tekin et al., 2016; Wright et al., 2017; Kizilhan, 2018; Wulfes et al., 2019) (26%; 95% CI 20–33%) (Table 3 and figure 3.2). In addition, studies (Turner et al., 2003; Fenta et al., 2004; Momartin et al., 2004; Bhui et al., 2006; Renner et al., 2006; Von Lersner et al., 2008; Maier et al., 2010; Eckart et al., 2011; Jakobsen et al., 2011; Heeren et al., 2012; Tay et al., 2013; Naja et al., 2016; Kazour et al., 2017; Hocking et al., 2018; Kizilhan, 2018; Nose et al., 2018; Richter et al., 2018; Segal et al., 2018; Tekeli-Yesil et al., 2018; Wulfes et al., 2019; Ainamani et al., 2020; Civan Kahve et al., 2020; Sundvall et al., 2020) which included participants from a convenience samples showed significant (p = 0.001) higher prevalence of MDD and PTSD (MDD: 35%; 95% CI 23–46%; PTSD: 34%; 95% CI 22–47%) than studies (Cheung, 1994; Van Ommeren et al., 2001a; Steel et al., 2002; Laban et al., 2004; Marshall et al., 2005; Akinyemi et al., 2012; Bogic et al., 2012; Rasmussen et al., 2012; Llosa et al., 2014; Tekin et al., 2016; Wright et al., 2017; Rees et al., 2019; Bapolisi et al., 2020; Kaur et al., 2020; Sagaltici et al., 2020) conducted among probability-based samples (MDD: 30%; 95% CI 21–39%; PTSD: 28% 95% CI 19–37%) (Table 3 and figure 3.3). The heterogeneity between samples was high in all the subgroup analyses (I2 = 99.05%). The other analyses of the MDD, reMDD and PTSD subgroups, showed no significant differences among prevalence rates and high heterogeneity (Table 3 and online Supplementary materials). For psychotic disorders and BPD subgroup analyses were not conducted due to the limited number of studies.

Table 3.

Subgroups analysis results

Major Depression Disorder (MDD)
Subgroup Categories Random pooled ES (95% CI) p
Time since displacement (⩾5) 27 (16–37) 0.55
(>1 < 5) 36 (20–51)
(<1) 26 (11–42)
Diagnostic interviews MINI 37 (28–46) 0.05
Others* 26 (20–33)
Country categories LMICs 47 (38–57) 0.001
HICs 28 (22–33)
Risk of bias Low 31 (24–39) 0.74
High 34 (22–45)
Population Probability-based samples 30 (21–39) 0.001
Convenience samples 35 (23–46)
Recurrent episode of MDD (reMDD)
Time since displacement (⩾5) NP NP
(>1 < 5)
(<1)
Diagnostic interviews MINI 20 (9–30) 0.168
Others* 10 (3–8)
Country categories LMICs NP NP
HICs
Risk of bias Low 14 (5–22) 0.507
High 18 (7–29)
Population Probability-based samples 15 (8–23) 0.834
Convenience samples 17 (4–30)
Post-traumatic stress disorder
Time since displacement (⩾5) 35 (17–53) 0.908
(>1 < 5) 31 (20–42)
(<1) 27 (13–41)
Diagnostic interviews MINI 30 (21–39) 0.961
Others* 33 (23–42)
Country categories LMICs 34 (17–52) 0.641
HICs 30 (23–36)
Risk of bias Low 30 (23–38) 0.757
High 33 (19–46)
Population Probability-based samples 28 (19–37) 0.001
Convenience samples 34 (22–47)
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*

Others: (CAPS, Clinician-Administered PTSD Scale; CIDI, Composite International Diagnostic Interview; DIS, Diagnostic Interview Schedule; SCID, The Structured Clinical Interview for DSM); MINI, The Mini-International Neuropsychiatric Interview; (⩾5): people who have spent more than five years as refugees or asylum seekers; (>1 < 5): people who have spent between 5 years and 1 year as refugees or asylum seekers; (<1): people who have spent less than 1 year as refugees or asylum seekers; HICs, High-income countries; LMICs, Low middle-income countries; NP, The aggregate prevalence of random effects was not allowed due to the limited number of the sample.

Discussion

This systematic review and meta-analysis provide the most recent and extensive overview of the prevalence rates of serious mental disorders across refugees and asylum-seeking populations. A comprehensive search was performed from inception to June 4, 2020 and was not intentionally updated to avoid interference caused by the effect of COVID-19 pandemic in this population. We included 40 studies in 11 053 participants, and all diagnoses were established with diagnostic interviews. Our study revealed that the most prevalent serious mental disorder in refugees and asylum seekers was MDD (32%), followed by PTSD (31%), recurrent episode of MDD (16%), and BPD (5%). The prevalence of psychotic disorders was 1%. Subgroup analyses showed that MDD appeared to be more prevalent (47%) among studies conducted in LMICs than in HICs (28%), and when the MINI (37%) has been used, compared to other diagnostic instruments (26%). PTSD and MDD showed higher prevalence rates (34% and 35% respectively) in studies where participants were from convenience samples in comparison to studies that used probability-based samples. PTSD and MDD were the most frequently evaluated disorders with 36 studies and 32 studies respectively, as opposed to BPD and psychosis of which we had only a few studies.

According to previous studies, the world-wide prevalence rate reported for MDD is 4.4% (WHO, 2017), the lifetime prevalence of PTSD in World Mental Health Surveys has been calculated between 3.9% and 5.6% (Koenen et al., 2017) and the prevalence rates of psychosis and BPD in the general population are 0.4% (Moreno-Kustner et al., 2018) and 2.5%, respectively (Carta and Angst, 2016). Comparing our results with the prevalence of the same disorders in the general population, suggests that MDD is seven times more likely in refugees and PTSD is 4 to 5 times more prevalent than in the general population (Koenen et al., 2017; WHO, 2017). Although BPD and psychosis are much rarer than MDD or PTSD, our study also indicated that externally displaced refugees and asylum seekers are two times more likely to be diagnosed with BPD and with psychosis than the general population (Carta and Angst, 2016; Moreno-Kustner et al., 2018). Studies have highlighted the role of trauma and stress experienced by minorities, social defeat, and discrimination as important risk factors for psychosis in refugees (Brandt et al., 2019; Duggal et al., 2020; Selten et al., 2020).

Our results are in line with the prevalence rates of the Blackmore and colleagues (Blackmore et al., 2020) study, who found a prevalence rates of 31.4% (95% CI 24.43–38.5) for PTSD, of 31.5% (95% CI 22.64–40.38) for depression, and 1.5% (95% CI 0.63–2.40) for psychosis. In addition, our study reports the random-effects pooled prevalence for BPD which has never examined before. Compared to the 2005 systematic review findings (Fazel et al., 2005), our rates prevalence showed an increase of serious mental disorders prevalence among refugees and asylum seekers from 5% (Fazel et al., 2005) to 32% for MDD, and from 9% (Fazel et al., 2005) to 31% for PTSD. One of the reasons for the discrepancy between these results could be the LMICs exclusion in Fazel and colleagues' systematic review. Furthermore, it might be explained by increased exposure to adverse events, increased financial hardship, social isolation, decreased access to adequate health care, as well as the lack of appropriate policies and investments in the last 15 years.

Our study methodology has several strengths, among which strict inclusion and exclusion criteria, a large number of included studies, and updated statistical methods. However, due to the low number of studies that examine refugees and asylum seekers separately, a limitation of this study was to consider these two groups together. Further, we found a large variability of prevalence rates and a high level of heterogeneity between studies. While high heterogeneity is very common in meta-analyses on prevalence rates (Higgins, 2008), we examined possible sources of heterogeneity between the included studies. Running the analyses without outliers did not alter the main results. Upon inspection of the pattern of outliers, no systematic differences between outlier studies from the rest of the studies were identified that might explain the high heterogeneity. However, due to the limit number of studies greater caution is required in interpreting the prevalence rates of BP and psychosis. In addition, we analysed subgroups under the mixed-effects model with inverse-variance weights under the random-effects model. The results of these subgroup analyses showed that significantly higher prevalence rates of MDD and PTSD in studies conducted among convenience samples than in studies that used probability-based samples. This result highlights the importance of having an adequate statistically representative sample of participants to avoid overestimating prevalence rates in a population as various and difficult to study as that of refugees and asylum seekers.

Furthermore, higher prevalence rates of MDD were found in LMICs than in HICs. This difference was not found for PTSD, where the prevalence rate was comparable between refugees and asylum seekers resettled in LMICs and HICs. The higher prevalence of MDD in refugees resettled in LMICs may be driven by higher exposure to post-migration living difficulties. Feelings of hopelessness, the failure of the migration project, and difficulties in integration may promote higher levels of depression (Steel et al., 2009; Charlson et al., 2019). Further, refugees resettled in LMICs can have a higher risk of developing MDD because of the lack of integration programs and mental health care due to the low investments in mental health care that unfortunately characterises the majority of these countries (Patel, 2007). On the other hand, compared to MDD, PTSD may have a stronger association with trauma exposure in the country of origin, which may not differ significantly between refugees in LMICs and HICs.

Another interesting finding was that we found a higher rate for MDD for studies conducted with the MINI than in studies that used different diagnostic interviews. This may be explained by the fact that the MINI may be administered by non-clinicians (similar to the CIDI, but dissimilar to the SCID I/P), and that its administration is shorter and its outcomes therefore potentially less precise.

Despite the high heterogeneity and methodological limitations of included studies, a high prevalence of serious mental disorders was found in refugees and asylum seekers diagnosed through structured clinical interviews. However, specific instruments culturally adapted for use across different local cultures and contexts for refugees would be advisable, since no one of the diagnostic instruments currently in use has been developed for the non-western populations, who represent the highest sample of refugees. For this reason, to reduce the high heterogeneity, more rigorous studies, using representative samples and culturally adapted instruments, to measure cultural concepts of distress would be recommended. Moreover, to strengthen the evidence base concerning the more serious mental disorders, further research on the prevalence of psychosis and BPD is imperative. To follow this goal, international and government investments in mental health research, population screening, and specific interventions on asylum seekers and refugees are warranted. However, until we have more rigorous studies and adequate diagnostic tools, due to the high heterogeneity between these studies, our results should be considered with caution.

Conclusion

In sum, our systematic review and meta-analysis show that it is imperative that governments and actors across the world acknowledge the devastating effect of war and prosecution on individuals' mental health. In order to prevent cycles of violence and victimisation, effective public mental health responses may be put in place to address worldwide suffering.

Data

All the data involved have been included in Tables and Figures of this paper, including online Supplementary materials.

Acknowledgements

None.

Supplementary material

For supplementary material accompanying this paper visit https://doi.org/10.1017/gmh.2022.29.

S2054425122000292sup001.docx (3.4MB, docx)

click here to view supplementary material

Financial support

This work was supported by Ayala Scholarship of Sapienza Foundation of Rome in Italy. Ayala Scholarship of Sapienza Foundation of Rome did not participate in any part of the process of the study (study design, data collection, data analysis, data interpretation, or writing the paper). The corresponding author had full access to all study data and had final responsibility for the decision to submit the paper for publication.

Conflicts of interest

None.

Ethical standards

Not applicable.

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