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Prevalence of suicide attempt in individuals with major depressive disorder: a meta-analysis of observational surveys

Published online by Cambridge University Press:  04 September 2018

Min Dong ,
Liang-Nan Zeng ,
Li Lu ,
Xiao-Hong Li ,
Gabor S. Ungvari ,
Chee H. Ng ,
Ines H. I. Chow ,
Ling Zhang ,
Yuan Zhou  and
Yu-Tao Xiang
Min Dong
Affiliation:
Unit of Psychiatry, Faculty of Health Sciences, University of Macau, Macao SAR, China
Liang-Nan Zeng
Affiliation:
Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China
Li Lu
Affiliation:
Unit of Psychiatry, Faculty of Health Sciences, University of Macau, Macao SAR, China
Xiao-Hong Li
Affiliation:
The National Clinical Research Center for Mental Disorders, China & Center of Depression, Beijing Institute for Brain Disorders & Mood Disorders Center, Beijing Anding Hospital, Capital Medical University, Beijing, China
Gabor S. Ungvari
Affiliation:
University of Notre Dame Australia/Marian Centre, Perth, Australia
Chee H. Ng
Affiliation:
Department of Psychiatry, University of Melbourne, Melbourne, Victoria, Australia
Ines H. I. Chow
Affiliation:
Unit of Psychiatry, Faculty of Health Sciences, University of Macau, Macao SAR, China
Ling Zhang
Affiliation:
Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University & Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
Yuan Zhou
Affiliation:
CAS Key Laboratory of Behavioral Science & Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
Yu-Tao Xiang*
Affiliation:
Unit of Psychiatry, Faculty of Health Sciences, University of Macau, Macao SAR, China
*
Author for correspondence: Yu-Tao Xiang, E-mail: xyutly@gmail.com
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Abstract

Background

Suicide attempt (SA), which is one of the strongest predictors of completed suicide, is common in major depressive disorder (MDD) but its prevalence across epidemiological studies has been mixed. The aim of this comprehensive meta-analysis was to examine the pooled prevalence of SA in individuals with MDD.

Methods

A systematic literature search was conducted in PubMed, Embase, PsycINFO, Web of Science and Cochrane Library from their commencement date until 27 December 2017. Original studies containing data on prevalence of SA in individuals with MDD were analyzed.

Results

In all, 65 studies with a total of 27 340 individuals with MDD were included. Using the random effects model, the pooled lifetime prevalence of SA was 31% [95% confidence interval (CI) 27–34%], 1-year prevalence was 8% (95% CI 3–14%) and 1-month prevalence was 24% (95% CI 15–34%). Subgroup analyses revealed that the lifetime prevalence of SA was significantly associated with the patient setting, study region and income level, while the 1-month prevalence of SA was associated with only the patient setting.

Conclusion

This meta-analysis confirmed that SA was common in individuals with MDD across the world. Careful screening and appropriate interventions should be implemented for SA in the MDD population.

Keywords

Major depressive disordermeta-analysissuicide attempt

Information

Type
Original Articles
Information
Psychological Medicine , Volume 49 , Issue 10 , July 2019 , pp. 1691 - 1704
Copyright
Copyright © Cambridge University Press 2018 

Introduction

Major depressive disorder (MDD) is a common psychiatric disorder associated with functional impairment and disability (Ferrari et al., Reference Ferrari, Charlson, Norman, Patten, Freedman, Murray, Vos and Whiteford2013b). The estimated point prevalence of MDD is approximately 4.7% worldwide (Ferrari et al., Reference Ferrari, Somerville, Baxter, Norman, Patten, Vos and Whiteford2013a), but the prevalence varies greatly across countries. For example, the lifetime prevalence of MDD was estimated at 3.0% in Japan, 3.3% in China and 16.9% in the USA (Andrade et al., Reference Andrade, Caraveo-anduaga, Berglund, Bijl, Graaf, Vollebergh, Dragomirecka, Kohn, Keller and Kessler2003; Low et al., Reference Low, Azmi, Li, Yee, Abdat, Kalita, Ge and Milea2014).

Suicide is a major global public health challenge and accounts for 1.4% of all-cause death (WHO, 2015). Over 90% of people who died by suicide had one or more psychiatric disorders, particularly MDD that accounted for 59–87% of all suicides (Rihmer and Kiss, Reference Rihmer and Kiss2002; Cavanagh et al., Reference Cavanagh, Carson, Sharpe and Lawrie2003; Nordentoft and Mortensen, Reference Nordentoft and Mortensen2011). Suicide attempt (SA), defined as a self-destructive act with at least some intent to end one's own life (Posner et al., Reference Posner, Oquendo, Gould, Stanley and Davies2007; Kao et al., Reference Kao, Liu, Cheng and Chou2012; Sudol and Mann, Reference Sudol and Mann2017), is common in MDD; for example, the risk of SA in MDD was found to be 5-fold higher than in the general population (Nock et al., Reference Nock, Hwang, Sampson and Kessler2010). SA is also one of the strongest predictors of future SA or completed suicide; of people with a previous SA, 10–15% died by suicide eventually (Berman et al., Reference Berman, Silverman and Bongar2000; Oquendo et al., Reference Oquendo, Galfalvy, Russo, Ellis, Grunebaum, Burke and Mann2004; Suominen et al., Reference Suominen, Isometsä, Suokas, Haukka, Achte and Lönnqvist2004; Yoshimasu et al., Reference Yoshimasu, Kiyohara and Miyashita2008).

The causes of suicide-related behaviours are complex and associated with biological, sociocultural and clinical factors (Coentre et al., Reference Coentre, Talina, Góis and Figueira2017, Gournellis et al., Reference Gournellis, Tournikioti, Touloumi, Thomadakis, Michalopoulou, Christodoulou, Papadopoulou and Douzenis2017, Sudol and Mann, Reference Sudol and Mann2017). Common risk factors of SA identified in depressed patients include high level of education, lower quality of life, childhood abuse, family history of psychiatric disorders, hopelessness, negative or stressful life events, psychiatric comorbidities and impulsive and aggressive behaviors (Corruble et al., Reference Corruble, Damy and Guelfi1999; Dumais et al., Reference Dumais, Lesage, Alda, Rouleau, Dumont, Chawky, Roy, Mann, Benkelfat and Turecki2005; Dervic et al., Reference Dervic, Grunebaum, Burke, Mann and Oquendo2006; Dieserud et al., Reference Dieserud, Gerhardsen, Van den Weghe and Corbett2010; Zayas et al., Reference Zayas, Gulbas, Fedoravicius and Cabassa2010; Hawton et al., Reference Hawton, Comabella, Haw and Saunders2013; Zhu et al., Reference Zhu, Zhang, Shi, Gao, Li, Tao, Zhang, Wang, Gao, Yang, Li, Shi, Wang, Liu, Zhang, Du, Jiang, Shen, Zhang, Liang, Sun, Hu, Liu, Wang, Miao, Meng, Li, Hu, Li, Huang, Li, Ha, Deng, Mei, Zhong, Gao, Sang, Zhang, Fang, Yu, Yang, Liu, Chen, Hong, Wu, Chen, Cai, Song, Pan, Dong, Pan, Zhang, Shen, Liu, Gu, Wang, Liu, Zhang, Li, Chen, Kendler, Flint and Liu2013; Nam et al., Reference Nam, Kim and Roh2016; Wei et al., Reference Wei, Li, Hou, Chen, Chen and Qin2017). There are also biological correlates of SA (Pawlak et al., Reference Pawlak, Dmitrzak-Weglarz, Wilkosc, Szczepankiewicz, Leszczynska-Rodziewicz, Zaremba, Kapelski, Rajewska-Rager and Hauser2016, Sudol and Mann, Reference Sudol and Mann2017), including smaller hippocampal volume (Colle et al., Reference Colle, Chupin, Cury, Vandendrie, Gressier, Hardy, Falissard, Colliot, Ducreux and Corruble2015), 5-HTR2A (Gonzalez-Castro et al., Reference Gonzalez-Castro, Tovilla-Zarate, Juarez-Rojop, Pool Garcia, Velazquez-Sanchez, Genis, Nicolini and Lopez Narvaez2013) and certain inflammatory processes (Arling et al., Reference Arling, Yolken, Lapidus, Langenberg, Dickerson, Zimmerman, Balis, Cabassa, Scrandis and Tonelli2009; Black and Miller, Reference Black and Miller2015; Courtet et al., Reference Courtet, Giner, Seneque, Guillaume, Olie and Ducasse2016).

As MDD is one of the major contributing factors of SA and most suicides occur in the first attempt (Isometsa and Lonnqvist, Reference Isometsa and Lonnqvist1998; Shibre et al., Reference Shibre, Hanlon, Medhin, Alem, Kebede, Teferra, Kullgren, Jacobsson and Fekadu2014), better understanding of SA patterns is critical to develop and implement effective suicide preventing strategies in patients with MDD. Although there are numerous studies of SA in MDD patients, the prevalence of SA varies greatly, and demographic and clinical contributing factors of SA in MDD are diverse. Therefore, the worldwide pattern of SA in patients with MDD and associated factors are still unclear. To date, we could not locate published meta-analysis on the prevalence of SA in adult patients with MDD.

We performed a comprehensive meta-analysis to estimate the pooled prevalence of SA in individuals with MDD and its associated factors.

Methods

Search strategy and selection criteria

This meta-analysis was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) and Meta-analysis of Observational Studies in Epidemiology (MOOSE) recommendations (Stroup et al., Reference Stroup, Berlin, Morton, Olkin, Williamson, Rennie, Moher, Becker, Sipe and Thacker2000). The protocol has been registered in the International Prospective Register of Systematic Reviews (PROSPERO) and the registration number is CRD42018086243. Two investigators (MD and LNZ) independently searched the literature in PubMed, Embase, PsycINFO, Web of Science and Cochrane Library from their commencement date until 27 December 2017. The search terms were as follows: ((attempted suicide) OR (suicide attempt) OR (suicide attempt*)) AND (major depressi*) AND (epidemiology OR (cross-sectional study) OR prevalence OR rate OR (cohort study) OR percentage). In the search term ‘depressi*’, the asterisk is a commonly used wildcard symbol that broadens the search by finding words that start with the same letters ‘depressi’. The titles and abstracts were independently screened by the two investigators, and the full texts of eligible studies were then identified. In addition, the relevant reviews were checked to identify the studies that might be missed in the first literature search. Any uncertainty about study identification was resolved by a discussion with a third investigator (XYT). The process of identifying eligible studies is shown in Fig. 1.

Fig. 1.

Flowchart of study selection.

Inclusion and exclusion criteria

Two investigators (MD and LNZ) independently assessed the literature for their eligibility for inclusion. The inclusion criteria according to the PICOS acronym were as follows: Participants (P): individuals with MDD by international or local diagnostic criteria, such as the Diagnostic and Statistical Manual of Mental Disorders (DSM), the International Statistical Classification of Diseases and Related Health Problems (ICD) systems or China's mental disorder classification and diagnosis standard (CCMD) diagnostic system (Chen, Reference Chen2002). Intervention (I): not applicable; Comparison (C): not applicable; Outcomes (O): not applicable and Study design (S): cross-sectional or cohort studies (only the baseline data were extracted) reporting prevalence of SA or relevant data that could generate prevalence of SA. The timeframe of prevalence was reported, such as lifetime, 1 year, 1 month or from the onset of MDD. Exclusion criteria included: (1) studies conducted in special populations, such as adolescent or the elderly and (2) data extracted from medical records. Several studies on major depressive episode (MDE) included individuals with dysthymia, such as Seo et al., Reference Seo, Jung, Jeong, Kim, Lee, Kim, Yim and Jun2014 and Park et al., Reference Park, Hong, Jon, Hong and Jung2017 or bipolar depressive episode, such as Serafini et al., Reference Serafini, Pompili, Innamorati, Fusar-Poli, Akiskal, Rihmer, Lester, Romano, de Oliveira, Strusi, Ferracuti, Girardi and Tatarelli2011 and Wakefield and Schmitz, Reference Wakefield and Schmitz2016, therefore these studies were excluded with the exception of those which included only individuals with MDD (following confirmation by the corresponding authors). If more than one paper based on the same dataset were published, only the paper with the largest sample was included.

Data extraction and quality assessment

The data extraction was independently conducted by two investigators (MD and LNZ). The following information was extracted from each study using a standardized data collection form: the first author, year of publication and survey, study location, study design, sampling method, patient setting (inpatients, outpatients or mixed), diagnostic criteria of MDD, sample size, proportion of males, mean age, number of individuals with SA, assessment of SA and timeframe.

The quality of included studies was assessed with the 22-item Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) (Von Elm et al., Reference Von Elm, Altman, Egger, Pocock, Gøtzsche, Vandenbroucke and Initiative2007). Studies with a total score >11 were considered as ‘good quality’ (Cao et al., Reference Cao, Zhong, Xiang, Ungvari, Lai, Chiu and Caine2015).

Statistical analysis

The data analyses were conducted with STATA version 12.0 (Stata Corporation, College Station, Texas, USA) and Comprehensive Meta-Analysis (CMA) Version 2.0 (Biostat Inc., Englewood, New Jersey, USA). The pooled prevalence and its 95% confidence interval (95% CI) was calculated with the random effects model. Heterogeneity across studies was assessed with I 2 statistic; I 2 > 50% was defined as high heterogeneity (Higgins et al., Reference Higgins, Thompson, Deeks and Altman2003). Subgroup analyses, meta-regression and sensitivity analyses were performed to explore the possible sources of heterogeneity. Subgroup analyses were performed according to the following variables: year of survey and sample size (using the median splitting method), patient setting, income level classified by the World Bank (low/middle/high) (Worldbank, 2017), broad WHO regional classification (Africa/Americas/Eastern Mediterranean/Europe/South East Asia/Western Pacific) (Chen et al., Reference Chen, Shi, Bao, Sun, Lin, Que, Vitiello, Zhou, Wang and Lu2018) and study design. Meta-regression analyses were performed in lifetime prevalence of SA based on sample size and percentage of males. Publication bias was estimated with funnel plots and Begg's test (Begg and Mazumdar, Reference Begg and Mazumdar1994). The statistical significance was considered as p < 0.05 (two sided).

Results

Search results and study characteristics

Table 1 shows the characteristics of the included studies. Altogether 5255 articles were retrieved and finally 65 studies with 27 340 individuals that fulfilled the study criteria were included in the meta-analysis. The sample size ranged from 17 to 6008 individuals. The mean age ranged from 20.2 to 54.9 years. Of the 65 studies, 57 studies with 23 620 individuals reported the lifetime prevalence of SA, five studies with 3099 individuals reported 1-year prevalence of SA, nine studies with 1476 individuals reported 1-month prevalence of SA and one study reported prevalence of SA from the onset of MDD. Of the included studies, there were 51 cross-sectional studies and 14 cohort studies. The majority of studies (n = 60) used the DSM system, two studies used ICD, two studies used DSM or/and ICD and one study used the Research Diagnostic Criteria (RDC) (Spitzer et al., Reference Spitzer, Endicott and Robins1978). The quality assessment score ranges from 13 to 20, and all were considered high quality.

Table 1.

Characteristics of the studies included in the meta-analysis

DSM, Diagnostic and Statistical Manual of Mental Disorders; ICD, International Statistical Classification of Diseases and Related Health Problems; M, month; NA, not applicable; RDC, Research Diagnostic Criteria; SA, suicide attempt; Y, years.

a 2 weeks.

b 24–48 h.

c 1 week.

d 24 h.

e 6 days.

Overall prevalence of SA

The pooled lifetime prevalence of SA was 31% (95% CI 27–34%; I 2 = 97.2%) (Fig. 2a), 1-year prevalence was 8% (95% CI 3–14%; I 2 = 92.4%) (Fig. 2b) and 1-month prevalence was 24% (95% CI 15–34%; I 2 = 95.2%) (Fig. 2c). The prevalence of SA since the onset of MDD was 39.5% (Nam et al., Reference Nam, Kim and Roh2016).

Fig. 2.

Forest plot of prevalence of SA. (a) Lifetime prevalence of SA. (b). 1-year prevalence of SA. (c) 1-month prevalence of SA.

Sensitivity analysis and publication bias

The sensitivity analysis of lifetime prevalence of SA showed that after removing each study sequentially, the pooled prevalence did not change significantly. The funnel plot showed slight asymmetry by visual inspection (Fig. 3), but did not reach significant level in the Begg's test (z = 1.07, p = 0.28) which indicated that there was no publication bias in lifetime prevalence of SA.

Fig. 3.

Funnel plot of publication bias for lifetime prevalence of SA.

Subgroup analyses and meta-regression

Table 2 shows the results of subgroup analyses. Inpatient, middle/high-income countries and geographic regions of Eastern Mediterranean, South-East Asia and Americas were significantly associated with higher lifetime prevalence of SA. In the meta-regression analyses, smaller sample size (B = −0.00007, z = −11.77, p < 0.001) was negatively associated, while proportion of males was positively associated with higher lifetime prevalence of SA (B = 0.006, z = 6.56, p < 0.001).

Table 2.

Subgroup analyses of prevalence of SA

SA, suicide attempt.

Bolded values: p < 0.05.

a Test of heterogeneity within subgroups.

b Test of prevalence of SA across subgroups.

Sample size was significantly associated with 1-year prevalence of SA while patient setting was significantly associated with 1-month prevalence of SA.

Discussion

The results showed that the pooled lifetime prevalence of SA (31%) was higher than the 1-year (8%) and 1-month (24%) prevalence of SA. The 1-year prevalence of SA is lower than the 1-month prevalence probably due to the limited number of studies reporting 1-year prevalence; therefore the result is unstable. The lifetime prevalence of SA is substantially higher than the epidemiological surveys in general populations in China (0.8%) (Cao et al., Reference Cao, Zhong, Xiang, Ungvari, Lai, Chiu and Caine2015), USA (4.6%) (Kessler et al., Reference Kessler, Borges and Walters1999) and Europe (1.3%) (Bernal et al., Reference Bernal, Haro, Bernert, Brugha, de Graaf, Bruffaerts, Lepine, de Girolamo, Vilagut, Gasquet, Torres, Kovess, Heider, Neeleman, Kessler and Alonso2007).

The lifetime and 1-month prevalence of SA in inpatient settings were significantly higher than in other settings. This is not surprising given that inpatients suffering from MDD usually present with more severe depressive symptoms and psychotic symptoms, which are closely associated with SA (Witte et al., Reference Witte, Timmons, Fink, Smith and Joiner2009; Holma et al., Reference Holma, Melartin, Haukka, Holma, Sokero and Isometsä2010). Further, the risk of SA in patients during current MDD episode was found to be 7.5 times higher than in patients who had fully remitted (Sokero et al., Reference Sokero, Melartin, Rytsala, Leskela, Lestela-Mielonen and Isometsa2005). Also, psychotic features are associated with a two-fold higher risk of SA during the current depressive episode (Coryell et al., Reference Coryell, Pfohl and Zimmerman1984; Maj et al., Reference Maj, Pirozzi, Magliano, Fiorillo and Bartoli2007; Gournellis et al., Reference Gournellis, Tournikioti, Touloumi, Thomadakis, Michalopoulou, Christodoulou, Papadopoulou and Douzenis2017). Moreover, inpatients usually need hospitalization due to insufficient treatment response, which could further increase the suicide risk in MDD (Souery et al., Reference Souery, Oswald, Massat, Bailer, Bollen, Demyttenaere, Kasper, Lecrubier, Montgomery and Serretti2007).

The meta-analysis found that socioeconomic factors were significantly associated with the risk of SA; individuals with MDD in middle- and high-income countries had a higher rate of SA than in low-income countries. However, a WHO report indicated that suicidal behaviors are more likely to occur in low and middle income countries (WHO, 2015), and low income and high unemployment were risk factors of SA (Beautrais, Reference Beautrais2000). The lack of consistency could be related to the possibility that psychiatric disorders may play a less important role in suicidal behaviors in low- and middle-income countries compared to high-income countries (Phillips et al., Reference Phillips, Yang, Zhang, Wang, Ji and Zhou2002; Vijayakumar, Reference Vijayakumar2004). In addition, only two studies were conducted in low-income countries, which could affect the reliability of the results. The critical lack of research in SA in MDD patients in low-income countries needs to be urgently addressed.

The relative high lifetime prevalence of SA in Eastern Mediterranean (58.5%) and South-East Asia (44.0%) could be due to the small number of studies, i.e. only one study was done in each region respectively. The lifetime rate of SA in Americas (36.3%) and Europe (27.5%) was higher than the Western Pacific (19.8%) and Africa (9.2%) regions. This appears consistent with the different prevalence of MDD across countries, for example, the prevalence of MDD in the USA (16.9%) was much higher than in China (3.3%) (Andrade et al., Reference Andrade, Caraveo-anduaga, Berglund, Bijl, Graaf, Vollebergh, Dragomirecka, Kohn, Keller and Kessler2003; Low et al., Reference Low, Azmi, Li, Yee, Abdat, Kalita, Ge and Milea2014). It is likely that the discrepancy in health resources and economic and sociocultural factors may contribute to the different SA rates across regions (Cao et al., Reference Cao, Wang, Zhong, Zhang, Ungvari, Ng, Li, Chiu, Lok, Lu, Jia and Xiang2017).

Similar to other meta-analysis (Cao et al., Reference Cao, Wang, Zhong, Zhang, Ungvari, Ng, Li, Chiu, Lok, Lu, Jia and Xiang2017), meta-regression and subgroup analyses revealed that higher lifetime and 1-year prevalence of SA was associated with studies with small sample size, the results of which are relatively more unstable. Male gender was positively associated with lifetime prevalence of SA, which is consistent with previous findings. For example, most deaths in MDD due to suicide occurred in men (Henriksson et al., Reference Henriksson, Aro, Marttunen, Heikkinen, Isometsa, Kuoppasalmi and Lonnqvist1993; Blair-West et al., Reference Blair-West, Cantor, Mellsop and Eyeson-Annan1999) and male gender is a major risk factor of suicide in both depressed patients (Hawton et al., Reference Hawton, Comabella, Haw and Saunders2013) and general populations (Nock et al., Reference Nock, Borges, Bromet, Alonso, Angermeyer, Beautrais, Bruffaerts, Chiu, De Girolamo and Gluzman2008; Cao et al., Reference Cao, Zhong, Xiang, Ungvari, Lai, Chiu and Caine2015). More severe stigma (Griffiths et al., Reference Griffiths, Christensen and Jorm2008), higher levels of aggression and impulsivity (Dumais et al., Reference Dumais, Lesage, Alda, Rouleau, Dumont, Chawky, Roy, Mann, Benkelfat and Turecki2005) and higher unemployment rate in men (Osváth et al., Reference Osváth, Kelemen, Erdös, Vörös and Fekete2003) are also associated with increased risk of suicidal behaviors.

As one of the strongest predictors of suicide (Harris and Barraclough, Reference Harris and Barraclough1997), SA is shown to be associated with male gender, acute disorders occurring in the week preceding death and inadequate pharmacotherapy in patients with severe psychiatric disorders including MDD (Shibre et al., Reference Shibre, Hanlon, Medhin, Alem, Kebede, Teferra, Kullgren, Jacobsson and Fekadu2014). The association between male gender and SA was confirmed in the meta-regression analyses. The possible reason could be that male patients with MDD were more likely to present with impulsive and aggressive behaviors and have alcohol abuse, all of which could increase the risk of suicide-related behaviors including SA (Dumais et al., Reference Dumais, Lesage, Alda, Rouleau, Dumont, Chawky, Roy, Mann, Benkelfat and Turecki2005).

The strengths of this meta-analysis include the large number of studies across many countries and the large sample size. However, several methodological limitations need to be noted. First, publication bias was not assessed for 1-year and 1-month prevalence of SA since the number of eligible studies with available data were <10 (Wan et al., Reference Wan, Hu, Li, Jiang, Du, Feng, Wong and Li2013). Second, certain variables related to SA were unavailable, such as medical and psychiatric comorbidities, treatment sought from professionals for MDD, treatment type, urban or rural residence, illness severity and psychiatric comorbidities (Vickers and McNally, Reference Vickers and McNally2004; Dumais et al., Reference Dumais, Lesage, Alda, Rouleau, Dumont, Chawky, Roy, Mann, Benkelfat and Turecki2005; Sher, Reference Sher2006; Nepon et al., Reference Nepon, Belik, Bolton and Sareen2010; Hawton et al., Reference Hawton, Comabella, Haw and Saunders2013). Third, heterogeneity could not be avoided in the meta-analysis of epidemiological studies (Winsper et al., Reference Winsper, Ganapathy, Marwaha, Large, Birchwood and Singh2013; Long et al., Reference Long, Huang, Liang, Liang, Chen, Xie, Jiang and Su2014) although subgroup analyses have been conducted. The heterogeneity could be attributed to different socioeconomic contexts, sampling methods, depression severity and antidepressant treatments. Fourth, the possibility of recall bias in SA could not be excluded.

This meta-analysis confirmed that SA was very common in individuals with MDD worldwide, especially among inpatient populations and those living in high-income countries. It is critical to develop and implement effective screening and appropriate interventions for SA in the MDD population.

Acknowledgements

This study was supported by the University of Macau (MYRG2015-00230-FHS and MYRG2016-00005-FHS), the National Key Research & Development Program of China (no. 2016YFC1307200), the Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support (no. ZYLX201607) and Beijing Municipal Administration of Hospitals’ Ascent Plan (no. DFL20151801).

Conflict of interest

None.

Footnotes

*

These authors contributed equally to this work.

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Figure 0

Fig. 1. Flowchart of study selection.

Figure 1

Table 1. Characteristics of the studies included in the meta-analysis

Figure 2

Fig. 2. Forest plot of prevalence of SA. (a) Lifetime prevalence of SA. (b). 1-year prevalence of SA. (c) 1-month prevalence of SA.

Figure 3

Fig. 3. Funnel plot of publication bias for lifetime prevalence of SA.

Figure 4

Table 2. Subgroup analyses of prevalence of SA