Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

Clinical and sociodemographic correlates of suicidality in patients with major depressive disorder from six Asian countries

  • Ah-Young Lim1,
  • Ah-Rong Lee1,
  • Ahmad Hatim2,
  • Si Tian-Mei3,
  • Chia-Yih Liu4,
  • Hong Jin Jeon5,
  • Pichet Udomratn6,
  • Dianne Bautista7, 8,
  • Edwin Chan7, 8,
  • Shen-Ing Liu9,
  • Hong Choon Chua10,
  • Jin Pyo Hong1Email author and
  • the MD RAN
BMC Psychiatry201414:37

DOI: 10.1186/1471-244X-14-37

Received: 16 December 2013

Accepted: 5 February 2014

Published: 13 February 2014

Abstract

Background

East Asian countries have high suicide rates. However, little is known about clinical and sociodemographic factors associated with suicidality in Asian populations. The aim of this study was to evaluate the factors associated with suicidality in patients with major depressive disorder (MDD) from six Asian countries.

Methods

The study cohort consisted of 547 outpatients with MDD. Patients presented to study sites in China (n = 114), South Korea (n = 101), Malaysia (n = 90), Singapore (n = 40), Thailand (n = 103), and Taiwan (n = 99). All patients completed the Mini-International Neuropsychiatric Interview (MINI), the Montgomery–Asberg Depression Rating Scale (MADRS), the Global Severity Index(SCL-90R), the Fatigue Severity Scale, the 36-item short-form health survey, the Sheehan Disability Scale, and the Multidimensional Scale of Perceived Social Support (MSPSS). Patients were classified as showing high suicidality if they scored ≥6 on the MINI suicidality module. Multivariate logistic regression analysis was used to examine sociodemographic and clinical factors related to high suicidality.

Results

One hundred and twenty-five patients were classed as high suicidality. Unemployed status (adjusted odds ratio [OR] 2.43, p < 0.01), MADRS score (adjusted OR 1.08), p < 0.001, and GSI (SCL-90R) score (adjusted OR 1.06, p < 0.01) were positively related to high suicidality. Hindu (adjusted OR 0.09, p < 0.05) or Muslim (adjusted OR 0.21, p < 0.001) religion and MSPSS score (adjusted OR 0.82, p < 0.05) were protective against high suicidality.

Conclusions

A variety of sociodemographic and clinical factors were associated with high suicidality in Asian patients with MDD. These factors may facilitate the identification of MDD patients at risk of suicide.

Keywords

Suicide Major depressive disorder Risk factor Social support

Background

It is estimated that approximately 1 million people worldwide commit suicide annually, and about 60% of these people are from Asian countries [1, 2]. The suicide rate in East Asian countries, including South Korea, Japan, and China, is especially high. According to a 2011 report from the World Health Organization’s worldwide initiative for the prevention of suicide, Korea ranked third, Japan ranked ninth, and China ranked twenty-fourth out of 105 countries for suicide rate [3]. Despite such compelling figures, suicide is relatively under-researched, and preventive approaches in Asian countries are limited compared to those in European and American countries [46].

Studies have consistently reported that major depressive disorder (MDD) is closely related to suicide, suicidal ideation, suicide planning, and suicide attempts and is a significant risk factor for suicide [7, 8]. According to previous studies, severe or extended depression [912], advanced age [9], low level of education [13], low level of social support and occupational functioning [9, 11], lack of a partner [11, 12], current alcohol dependence or substance abuse [9, 11, 13], negative life events [14], and impulsivity and hostility [10, 15, 16] have all been reported to be risk factors for suicide attempts in MDD. However, the etiology of MDD is extremely complicated, and the generalization of suicide risk factors is difficult because of differences between studies in the populations studied and the methods employed. In particular, the profiles of risk and protective factors of suicide in Asian countries differ from those of Western countries [10].

Recently, we reported that melancholic features and hostility were associated with suicidal risk in MDD patients from six Asian countries [17]. However, the cited study mainly focused on melancholic features and did not examine important factors such as religion, functional impairment, and poor social support. Interestingly, the prevalence of MDD is lower in East Asian countries than in European and American countries, but suicide rates are higher [18, 19]. This suggests that in East Asian countries, various clinical, social, and cultural factors, including religious practices, may be related to suicide in addition to psychiatric disorders such as MDD.

Although several studies have provided information on the risk factors for suicide in Asian countries [2022], comprehensive examination on the characteristics of suicide in MDD by multi-country comparative analysis was few. Accordingly, the aim of the present study was to evaluate the sociodemographic and clinical factors related to suicidality in MDD patients from six Asian countries (China, South Korea, Malaysia, Singapore, Taiwan, and Thailand).

Methods

Study design and settings

This study uses data from the Study on the Aspects of Asian Depression (SAAD) [20]. The participants and method of the present study are the same as those of the Recognizing Ethnic Differences in Depression (REDD) study [17], a multi-country, cross-sectional, observational study of depression in clinical settings carried out during 2008–2011. Thirteen study sites were established across six Asian countries: China, South Korea, Malaysia, Singapore, Taiwan, and Thailand. The study sites were as follows: Beijing Anding Hospital (Beijing, China), Institute of Mental Health (Beijing, China), Shanghai Mental Health Center (Shanghai, China), Samsung Medical Center (Seoul, Korea), Asan Medical Center (Seoul, Korea), Kyungpook National University Hospital (Daegu, Korea), Inha University Hospital (Incheon, Korea), University of Malaya Medical Center (Kuala Lumpur, Malaysia), Institute of Mental Health Woodbridge Hospital (Singapore), Chung Gang Memorial Hospital (Taoyan county, Taiwan), McKay Memorial Hospital (Taipei City, Taiwan), Maharaj Nakorn Chiang Mai Hospital (Chiang Mai, Thailand), and Prince of Songkla University (Songkla, Thailand). All study sites provided psychiatric care for the public or private sector. The study was approved by the Institutional Review Board or Ethics Committee of Asan Medical Center and each respective site.

Participants

Participants were prospectively enrolled in the study and were recruited from outpatients who were seeking psychiatric treatment at a study site. Individuals presenting for an intake appointment were approached by a study coordinator and informed about the study. After the study details had been fully explained, written informed consent was obtained from each participant. The inclusion criteria were as follows: i) age 18–65 years; ii) a positive response (“yes”) to the Mini-International Neuropsychiatric Interview (MINI) [21] question A1 (depressed mood) and/or A2 (loss of interest); and iii) a diagnosis of MDD according to the DSM-IV criteria [22] that was assessed by the MINI. The exclusion criteria were as follows: i) unstable medical condition; ii) mood disorder due to medical conditions and/or substance abuse; iii) psychotic or bipolar disorder; iv) clinically significant cognitive impairment; v) treatment with psychotropic medication within the previous month; vi) treatment with a benzodiazepine within the previous week; and vii) treatment with a long-acting antipsychotic medication within the previous 3 months. All other psychiatric and comorbid conditions were permitted.

The following sociodemographic characteristics were recorded: age, sex, marital status (married or co-habiting; widowed or divorced; never married), work status (employed; homemaker or student; unemployed), and education (none or primary; secondary or vocational; college). The following clinical characteristics were recorded: age at first onset, length of illness, number of past psychiatric hospitalizations, and depression severity.

Assessment

Participants completed several self-report questionnaires in the presence of the study coordinator. A face-to-face diagnostic evaluation was then conducted with the site investigator before the participant met with their treating clinician. Data collection was accomplished in a single visit. Suicidality is the likelihood of an individual completing suicide and include suicidal ideation, self-injurious behavior, suicide attempts, and suicide despite their very different consequences for the patient. In the present study, the term “suicidality” includes the full spectrum of suicidal thoughts (thoughts about wanting to be dead) and suicidal acts (previous self-destructive behaviors [23] with at least some intent to end one’s life), in keeping with a previous study [23].

Suicidal ideation and behaviors were assessed with the MINI suicidality module [21]. The MINI suicidality module was used to rate the risk of suicide. The module comprises 6 questions about suicidal ideation and behavior: (1–5) In the past month, did you 1. think you would be better off dead or wish you were dead? (1 point), 2. want to harm yourself? (2 points), 3. think about suicide? (6 points), 4. have a suicide plan? (10 points), 5. attempt suicide? (10 points). 6. In your life, have you ever made a suicide attempt? (4 points). The total number of points is used to classify the current suicide risk on three levels. Scores ranging from 1 to 5 are considered low risk, from 6 to 9 are moderate, and above 10 are high. According to the previous study investigating predictive value of MINI suicidality module, the sensitivity and specificity for suicide attempts after 12 months in patients with moderate-risk MINI sum scores are 0.73 and 0.62, and with high-risk, the MINI sum scores are 0.61 and 0.75[24]. The positive and negative likelihood ratios for patients with moderate-risk sum scores are 1.9 (95% CI, 1.1-3.2) and 0.44 (95% CI, 0.26-0.74), respectively, and in patients with high-risk sum scores, they are 2.4 (95% CI, 1.9-3.0) and 0.52 (95% CI, 0.42-0.65) [24]. In this study, depression severity was assessed with the Montgomery-Asberg Depression Rating Scale (MADRS) [25], psychiatric symptoms were assessed with the Global Severity Index(GSI provided by SCL-90-R) [26], fatigue severity was assessed with the Fatigue Severity Scale (FSS) [27], health-related quality of life was assessed with the 36 item short form health survey (SF-36) [28], disability was assessed with the Sheehan Disability Scale (SDS) [29], and perceived social support was assessed with the Multidimensional Scale of Perceived Social Support (MSPSS) [30].

Statistical analysis

Participants were classified as low suicidality (score ≤5 on the MINI suicidality module) or high suicidality (score ≥6 on the MINI suicidality module). Country, religion, age group, sex, marital status, work status, and education were compared across low and high suicidality groups using Pearson’s chi-square tests. Age, age at first onset, length of illness, the number of past hospitalizations, MADRS score, GSI score, FSS score, SF-36’s total and subscales (bodily pain, emotional wellbeing, general health, role limitation due to emotional health, role limitation due to physical functioning, social functioning, vitality) score, SDS’s total and subscales (work and school, social and leisure, family life) score, and MSPSS’s total and subscales (family, friends, significant others) scores for low- and high-suicidality groups were compared using two-tailed Student’s t-tests for normally distributed variables and Mann–Whitney U-tests for non-normally distributed variables. A stratified logistic regression model was used to investigate predictors of high risk of suicide after controlling for age, sex, years of education, religion, work status, and total MADRS, GSI, FSS, and MSPSS scores. To account for collinearity, the country was not included as an independent variable but as a stratum in the stratified logistic regression model, because its association with other variables such as religion and educational background were high. Independent variables that were analyzed included age, sex, education, religion, work status, history of hospitalization, total MADRS score, GSI of SCL-90-R score, total FSS score, and total MSPSS score. Variables significant (p < 0.1) on univariate analysis were selected for inclusion in the multivariable model.

The null hypothesis was rejected at p < 0.05. The Statistical Package for the Social Sciences (SPSS) software, version 12.0, and SAS (version 9.3, Cary, NC) were used for all analyses.

Results

A total of 2,023 outpatients were screened for eligibility, and 637 (31.5%) were eligible. Of the 637 outpatients that were eligible, 556 were enrolled in the study. The remaining 81 outpatients were not enrolled for the following reasons: 1) refusal/unwillingness to cooperate (n = 58); 2) insufficient patience to be interviewed (n = 14); or 3) insufficient time to participate (n = 9). All participants were compensated for their time. The mean (SD) time taken for completion of the self-administered questionnaires was 35.8 (14.1) min, and for face-to-face interview was 38.1 (13.8) min. After the interviews, nine participants were excluded from further analysis because they had no MDD. The remaining 547 participants were included in the analysis. 125 (22.9%) were classed as high suicidality (score ≥6 on the MINI suicidality module) and 422 (77.1%) were classed as low suicidality (score ≤5 on the MINI suicidality module).

Univariate analysis of sociodemographic and clinical factors

There were significant differences in country (χ 2 = 45.62, p < 0.001), religion (χ 2 = 12.57, p = 0.028), sex (χ 2 = 4.13, p = 0.044), work status (χ 2 = 13.42, p = 0.001), and number of hospitalizations (t = 2.44, p = 0.016) between low and high suicidality groups (Table 1). The highest proportion of patients classed as high suicidality occurred in South Korea (42.6%), followed by Taiwan (31.3%), China (21.9%), and Singapore (17.5%). There were no significant differences in age, marital status, education, age at first onset, and length of illness between low and high suicidality groups (Table 1). The high-suicidality group had higher MADRS (t = 7.33, p < 0.001), GSI (t = 5.40, p < 0.001), FSS (Z = -3.191, p < 0.001), and SDS scores (t = 3.34, p = 0.001) and lower SF-36 (t = 5.09, p < 0.001) and MSPSS scores (t = 3.97, p < 0.001) than did the low-suicidality group (Table 2).
Table 1

Sociodemographic characteristics of major depressive disorder patients with low and high suicidality

 

Low suicidality ( n = 422)

High suicidality ( n = 125)

Comparison of low and high suicidality groups

 

n

%

n

%

χ 2

df

pvalue

Country

       

 China

89

78.1

25

21.9

45.62

5

<0.001*

 South Korea

58

57.4

43

42.6

   

 Malaysia

82

91.1

8

8.9

   

 Singapore

33

82.5

7

17.5

   

 Thailand

92

89.3

11

10.7

   

 Taiwan

68

68.7

31

31.3

   

Age group

       

 18–29 years

128

78.5

35

21.5

4.40

4

0.355*

 30–39 years

86

71.7

34

28.3

   

 40–49 years

76

74.5

26

25.5

   

 50–59 years

103

81.1

24

18.9

   

 60–65 years

29

82.9

6

17.1

   

Sex

       

 Male

160

82.1

35

17.9

4.13

1

0.044*

 Female

262

74.4

90

25.6

   

Marital status

       

 Married or co-habiting

254

73.8

64

26.3

2.90

2

0.235

 Widowed or divorced

50

79.9

18

20.1

   

 Never married

118

73.5

42

26.5

   

Work status

       

 Employed

216

84.0

41

16.0

13.42

2

0.001*

 Homemaker or student

132

72.1

51

27.9

   

 Unemployed

74

69.2

33

30.8

   

Education

       

 None or primary

67

83.8

13

16.3

3.30

2

0.192

 Secondary or vocational

236

74.7

80

25.3

   

 College

119

78.8

32

21.2

   

Past hospitalization

    

13.76

1

.001**

 None

394

93.8

104

83.2

   

 Presence

26

6.2

21

16.8

   

Religion

       

 No religion

159

73.3

58

26.7

12.57

5

0.028*

 Buddhist

152

v

39

20.4

   

 Christian

50

69.4

22

30.6

   

 Hindu

20

95.2

1

4.8

   

 Muslim

34

89.5

4

10.5

   

 Other

7

87.5

1

12.5

   
 

Mean (SD)

 

Mean (SD)

 

t

df

p value

Age (years)

39.9 (13.4)

 

38.7 (12.6)

 

0.89

545

0.376

Age at first onset (years)

36.9 (13.4)

 

34.8 (12.8)

 

1.56

544

0.119

Length of illness (weeks)

76.1 (159.3)

 

90.2 (174.8)

 

0.45

545

0.398

*P < 0.05.

**P < 0.01.

Table 2

Clinical characteristics of major depressive disorder patients with low and high suicidality

 

Low suicidality ( n = 422)

High suicidality ( n = 125)

Comparison of low and high suicidality groups

   

tor Z

df

pvalue

MADRS score

27.78 (7.96)

33.58 (7.14)

7.33

545

<0.001**

GSI (of SCL-90-R) score

0.13 (0.06)

0.17(0.07)

5.40

543

<0.001**

FSS score

4.92 (1.47)

5.42 (1.22)

-3.19

236.19

0.001**

SF-36 score

376.7 (124.1)

311.9 (126.8)

5.09

542

<0.001**

 Bodily pain†

59.19 (27.22)

55.94 (29.46)

-1.04

543

.294

 Emotional wellbeing

33.52 (18.15)

24.29 (16.89)

5.05

544

<0.001**

 General health

37.15 (20.42)

32.70 (23.06)

2.07

544

0.039*

 Role limitation due to emotional health†

41.45 (26.77)

30.17 (24.95)

-4.27

543

<0.001**

 Role limitations due to hysical health†

50.67 (28.73)

42.85 (28.17)

-2.70

544

<0.001**

 Physical functioning

79.83 (22.37)

69.82 (25.44)

-4.14

180.48

<0.001**

 Social functioning

46.77 (24.87)

40.02 (25.90)

-2.63

544

0.008*

 Vitality

28.41 (19.21)

16.63 (15.65)

-6.27

242.14

<0.001**

SDS score

16.52 (8.08)

19.22 (7.73)

3.34

545

0.001**

 Work/school

6.23 (2.29)

7.34 (2.55)

-3.46

203.59

0.001**

 Social/leisure

5.64 (3.00)

6.52 (2.84)

-2.92

544

0.003**

 Family life

5.24 (3.20)

6.35 (2.95)

-3.40

543

0.001**

MSPSS score

4.56 (1.40)

3.99 (1.42)

3.97

542

<0.001**

 Family

4.89 (1.65)

4.18 (1.87)

-3.64

180.60

<0.001**

 Friends

4.35 (1.59)

3.85 (1.56)

3.07

542

0.002**

 Significant others

4.71 (1.82)

4.18 (1.82)

-2.93

542

0.003**

†Reversely-coded variables. Higher score indicates better quality of life.

MADRS, Montgomery-Åsberg Depression Rating Scale; Global Severity Index(SCL-90-R, Symptoms Checklist Questionnaire-90-Revised); FSS, Fatigue Severity Scale; SF-36, Medical Outcome Survey Short Form-36; SDS, Sheehan Disability Scale; MSPSS, Multidimensional Scale of Perceived Social Support.

*P < 0.05.

**P < 0.01.

Multivariate analysis for high suicidality

In the logistic regression model religion, work status, MADRS score, and FSS scores were related to high suicidality in MDD patients (Table 3). Patients who were unemployed (adjusted odds ratio (OR) 2.50, 95% confidence interval (CI) 1.27-4.90), patient who had history of hospitalization(adjusted odds ratio (OR) 2.96, 95% confidence interval (CI) 1.41-6.20), patients who had high MADRS score (adjusted OR 1.11, 95% CI 1.07-1.15), and patients who had a high FSS score (crude OR 1.36, 95% CI 1.15–1.61) had increased odds of being in the high suicidality group. The MSPSS score (adjusted OR 0.83, 95% CI 0.70–0.98) was inversely associated with high suicidality. Age, sex, years of education, religion, and marital status were not significant in the model (Table 3).
Table 3

Stratified logistic regression model for high suicidality (stratum: country)

Values

Crude OR (95% CI)

Wald

p value

Adjusted OR† (95% CI)

Wald

p value

Age

0.98 (0.97–1.00)

3.390

0.066

0.99 (0.97–1.01)

1.783

0.182

Sex: Female

1.55 (0.98–2.45)

3.552

0.059

1.36 (0.80–2.30)

1.304

0.254

Education

      

 None or primary

1

2.704

0.259

   

 Secondary or vocational

1.78 (0.89–3.55)

2.651

0.104

   

 College

1.72 (0.81–3.69)

1.976

0.160

   

 Marital status

      

 Married or co-habiting

1

3.487

0.175

   

 Widowed or divorced

1.29 (0.68–2.45)

0.628

0.428

   

 Never married

1.56 (0.97–2.50)

3.406

0.065

   

Religion

      

 No religion

1

3.259

0.660

   

 Buddhist

1.39 (0.75–2.56)

1.099

0.294

   

 Christian

1.19 (0.61–2.36)

0.262

0.609

   

 Hindu

0.46 (0.05–3.91)

0.511

0.475

   

 Muslim

1.23 (0.33–4.60)

0.097

0.755

   

 Others

0.35 (0.04–2.99)

0.929

0.335

   

Work status

      

 Employed

1

6.565

0.038

1

7.397

0.025

 Homemaker or student

1.60 (0.96–2.66)

3.309

0.069

1.22 (0.69–2.16)

0.452

0.502

 Unemployed

2.03 (1.15–3.59)

5.920

0.015

2.54 (1.29–5.01)

7.247

0.007

Past hospitalization

      

 None

1

     

 Presence

3.39 (1.76–6.54)

13.305

<0.001

2.90 (1.38–6.07)

7.948

0.005

MADRS score

1.13 (1.09–1.17)

51.005

<0.001

1.10 (1.06–1.14)

22.354

<0.001

GSI (of SCL-90-R) score

1.11 (1.07–1.15)

30.439

<0.001

1.04 (1.00–1.09)

3.269

0.071

FSS score

1.36 (1.15–1.61)

12.827

<0.001

1.09 (0.90–1.32)

0.813

0.367

MSPSS score

0.78 (0.67–0.91)

9.993

0.002

0.84 (0.71–1.00)

3.748

0.053

OR, odds ratio; CI, confidence interval; MADRS, Montgomery-Åsberg Depression Rating Scale; Global Severity Index (SCL-90-R, Symptoms Checklist Questionnaire-90-Revised excluding the depression subscale); FSS, Fatigue Severity Scale; MSPSS, Multidimensional Scale of Perceived Social Support.

*P < 0.05.

**P < 0.01.

†Adjusted variables: p < 0.1 in univariate analysis.

Discussion

In the current study, MDD patients were categorized as low or high suicidality according to their score on the MINI suicidality module. Country, religion, sex, work status, depression severity (measured using MADRS), and the number of past hospitalizations differed between patients with low and high suicidality, but age, marital status, education level, age at first onset of MDD, and length of illness were similar in the two groups. In Malaysia and Thailand, about 10% of MDD patients were classed as high suicidality, whereas in South Korea over 40% of MDD patients were classed as high suicidality. This is consistent with recent epidemiological studies on national suicide rates. The World Health Organization reported that suicide rates in East Asian countries such as South Korea and China were much higher than in Malaysia and Thailand [3], and the prevalence of suicidal behavior has consistently been reported to be high in South Korea [31]. Differences in the suicide rates in Asian countries are related to various factors including climate, religion, financial status, and availability of suicide methods [2]. For instance, South Korea and China experience more drastic weather changes than Thailand or Malaysia, and such changes may contribute to the high suicide rate [32]. Furthermore, the abrupt social changes and economic recession in East Asian countries is likely to have influenced the suicide rate.

In the present study, there was a significant relationship between religion and suicidality. Patients who were Hindu or Muslim had a lower suicidality, which was shown to be consistent with previous reports that practicing a religion that forbids suicide, such as Islam, contributes to low suicide rates [2, 5]. However, the relationship between religion and suicidality was not significant after stratifying the effect of country; thus, no independent effect of religion on suicidality was evident. There was a higher proportion of females than males in the high suicidality group [3336]. Previous studies have revealed higher suicidality in females in Asian countries than in females in countries such as the United States and Australia [3336]. This difference could be related to the low socioeconomic status of women, presence of abusive family relationships, and the frequent use of violent suicide methods in Asian countries [3336]. Unemployed persons had a 2.5 times higher risk of being in the high suicidality group than employed persons. This indicates a need for social structural efforts to improve employment stability in addition to clinical interventions to lower the suicide rate [37].

The high suicidality group had more severe depression, indicated by higher MADRS scores, than the low suicidality group, and reported a greater number of psychiatric. This corresponds with existing arguments that depression severity and other comorbid conditions are crucial risk factors for suicide [912, 18]. Further, perceived social support, assessed using the MSPSS, served as a protective factor for suicidality. According to the present results, patients who perceived a low level of support from family, friends, and significant others had a higher risk of being in the high suicidality group. The importance of social support for suicide prevention has been suggested many times in previous studies [9, 11, 38], and may be particularly important in the family-oriented Asian culture, where individuals with mental illness have a tendency to be hidden and isolated from society because the stigma of mental illness affects the entire family [39]. Social support should therefore be regarded as an important factor for preventing suicide, and interventions based on social relationships should be expanded in Asian countries. It is interesting that although perceived social support was a protective factor for suicidality, marital status had no significant influence on suicidality. Existing research has shown that marital status or the presence of a partner is not a protective factor for suicide in Asian countries because of the characteristics of the family system in Asian countries [2, 40]. Many Asians tend to stay married due to gender inequalities and the negative perception of divorce in Asian society, but stressful martial relationships may worsen depression or increase the suicidality [2, 40].

Age [9], education [13], and sex, which have all been found to be risk factors in previous studies, were not significantly related to suicidality in the logistic regression. This inconsistency may be due to the differences in subject characteristics, ethnicities and assessment tools. Age effects could not be detected as they are not linear within the range of age reported.

It is possible that suicidality was underestimated due to bias in self-reports, as patients may be embarrassed to admit suicidal behavior and mental problems. Additionally, the samples may not have been representative of each country as a whole, as they comprised clinical samples drawn from tertiary care centers. Recruitment was biased toward MDD patients who used health care institutions, and there may be differences in health care systems among the six countries that participated in the study. Also, This study was cross-sectional in design, making it impossible to identify a casual relationship between the identified risk factors and suicidality. Specific risk factors that contributed to the national differences in suicidality risk among MDD patients were not examined. Finally, while impact of country and religion were investigated in the present study, influence of ethnicity was not explored due to homogeneity in terms of ethnicity in most countries. A recent epidemiological study in Malaysia (n = 20,552) by Maniam et al. (2013) showed that suicidal ideation was significantly associated with Indian ethnicity (especially among those who were Hindu) compared with Malays and Chinese [41, 42]. Further study about the influence of ethnicity on suicidality may be needed in the clinical as well as the general population. Despite these limitations, the present study revealed that a variety of sociodemographic and clinical factors were associated with high suicidality in MDD patients from six Asian countries. In particular, as with severity of MDD, non-clinical features such as social support from various sources were found to be associated with suicidality. This association with cultural and social factors may explain the limited relationship between MDD rate and suicidality in Asian countries. Further, identification of these factors may facilitate the identification of MDD patients at risk of suicide and the provision of suicide prevention guidelines.

Conclusion

It is well-known that Asian countries have high suicide rates. In addition, the profiles of risk and protective factors of suicide in Asian countries may differ from those of Western countries. However, comprehensive investigation of the characteristics of suicide in the countries was relatively few. This study aimed to examine the sociodemographic and clinical factors associated with suicidality in MDD patients from six Asian countries. The high suicidality group was found to have higher depressive symptoms, general psychopathology and disability scores and lower quality of life and social support scores than the low suicidality group. Moreover, some religion, unemployment and past psychiatric hospitalization were associated with high suicidality in MDD patients in Asian countries. These findings point to the need for a careful evaluation of the risk factors for the suicidality in Asian countries. These factors may facilitate the identification of MDD patients at risk of suicide.

Declarations

Acknowledgements

This study was supported by an unrestricted research grant from H.Lundbeck A/S and from the Duke-National University of Singapore Office of Clinical Research. This study was also supported by a grant of the Korean Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea (A120051). This study is the work of the MD RAN (The Mood Disorders Research: Asian & Australian Network), which comprises the following members (in alphabetical order of family name [in capital letters]): Jae Nam BAE (Korea), Dianne BAUTISTA (Singapore), Edwin CHAN (Singapore), Sung-man CHANG (Korea), Chia-hui CHEN (Taiwan), CHUA Hong Choon (Singapore), Yiru FANG (China), Tom GEORGE (Australia), Ahmad HATIM (Malaysia), Yanling HE (China), Jin Pyo HONG (Korea), Hong Jin JEON (Korea), Augustus John RUSH (Singapore), Tianmei SI (China), Manit SRISURAPANONT (Thailand), Pichet UDOMRATN (Thailand) and Gang WANG (China).

Disclosure statement

Dr Hatim has received the grant and support for travel from Lundbeck for this study; lecture fee from Eli Lilly, Pfizer, Janssen, Sanofi Aventis, Lundbeck and Astra Zeneca. He has served as a advisory board member for Pfizer and Otsuka; grants from Lundbeck and Pfizer; Dr CY Liu has served a advisory board member for Eli Lilly. And she has received grants from Eli Lully and Otsuka; speaker fee, travel expense and payment for development of educational presentation from Astrazeneca, Eli Lilly, Janssen, Otsuka, Pfizer. Dr Uomratn has received the support for travel from Lundbeck for this study. Dr Bautista has received research grant from Singapore national medical research council; travel support from Lundbeck for this study; lecture fee from Merck. Dr. Chan has received research grant from Singapore national medical research council, travel support from Lundbeck. Dr. Tian-mei has received the support for travel from Lundbeck for this study. Dr Chua has received the support for travel from Lundbeck for this study. Dr Hong has received the grant and support for travel from Lundbeck for this study. He has served a consultant for Servier; the grant from Lundbeck, GlaxoSmithKline, Pfizer. For all remaining authors, no conflicts of interest exist.

Authors’ Affiliations

(1)
Department of Psychiatry, Asan Medical Center, Ulsan University College of Medicine
(2)
Department of Psychological Medicine, Faculty of Medicine, University of Malaya
(3)
Peking University Institute of Mental Health
(4)
Department of Psychiatry, Chang Gung Medical Center and Chang Gung University
(5)
Department of Psychiatry, Depression Center, Samsung Medical Center, Sungkyunkwan University School of Medicine
(6)
Department of Psychiatry, Faculty of Medicine, Prince of Songkla University
(7)
Singapore Clinical Research Institute
(8)
Duke-National University of Singapore
(9)
Department of Psychiatry, Mackay Memorial Hospital
(10)
Institute of Mental Health, Woodbridge Hospital

References

  1. Beautrais AL: Suicide in Asia. Crisis. 2006, 27 (2): 55-57.View ArticlePubMedGoogle Scholar
  2. Chen YY, Wu KC, Yousuf S, Yip PS: Suicide in Asia: opportunities and challenges. Epidemiol Rev. 2012, 34 (1): 129-144. 10.1093/epirev/mxr025.View ArticlePubMedGoogle Scholar
  3. Mental health - Suicide prevention (SUPRE). http://www.who.int/mental_health/prevention/suicide_rates/en/,
  4. Yip PSF: Suicide in Asia: causes and prevention. 2008, Hong Kong: Hong Kong University PressView ArticleGoogle Scholar
  5. Hendin H, Vijayuakumar L, Bertolote J, Wang H, Phillips M, Pirkis J: Epidemiology of Suicide in Asia. Suicide and suicide prevention in Asia. edn. Edited by: Hendin H, Phillips M, Vijayakumar L, Pirkis J, Wang H, Yip P, Wasserman D, Bertolote J, Fleischmann A. 2008, Geneva: Dept. of Mental Health and Substance Abuse, World Health Organization, 7-18.Google Scholar
  6. World Health Organization: Towards evidence-based suicide prevention programmes. 2010, Manila, Philippines: World Health Organization, Western Pacific RegionGoogle Scholar
  7. Bradvik L, Mattisson C, Bogren M, Nettelbladt P: Long-term suicide risk of depression in the Lundby cohort 1947–1997–severity and gender. Acta Psychiatr Scand. 2008, 117 (3): 185-191. 10.1111/j.1600-0447.2007.01136.x.View ArticlePubMedGoogle Scholar
  8. Isometsa ET, Henriksson MM, Aro HM, Heikkinen ME, Kuoppasalmi KI, Lonnqvist JK: Suicide in major depression. Am J Psychiatry. 1994, 151 (4): 530-536.View ArticlePubMedGoogle Scholar
  9. Sokero TP, Melartin TK, Rytsala HJ, Leskela US, Lestela-Mielonen PS, Isometsa ET: Suicidal ideation and attempts among psychiatric patients with major depressive disorder. J Clin Psychiatry. 2003, 64 (9): 1094-1100. 10.4088/JCP.v64n0916.View ArticlePubMedGoogle Scholar
  10. Malone KM, Haas GL, Sweeney JA, Mann JJ: Major depression and the risk of attempted suicide. J Affect Disord. 1995, 34 (3): 173-185. 10.1016/0165-0327(95)00015-F.View ArticlePubMedGoogle Scholar
  11. Sokero TP, Melartin TK, Rytsala HJ, Leskela US, Lestela-Mielonen PS, Isometsa ET: Prospective study of risk factors for attempted suicide among patients with DSM-IV major depressive disorder. Br J Psychiatry. 2005, 186: 314-318. 10.1192/bjp.186.4.314.View ArticlePubMedGoogle Scholar
  12. Holma KM, Melartin TK, Haukka J, Holma IA, Sokero TP, Isometsa ET: Incidence and predictors of suicide attempts in DSM-IV major depressive disorder: a five-year prospective study. Am J Psychiatry. 2010, 167 (7): 801-808. 10.1176/appi.ajp.2010.09050627.View ArticlePubMedGoogle Scholar
  13. Suppapitiporn S: The predictors of suicidal attempt in depressed patients. 2002, Bangkok: Chulalongkorn UniversityGoogle Scholar
  14. Chan LF, Maniam T, Shamsul AS: Suicide attempts among depressed inpatients with depressive disorder in a Malaysian sample. Psychosocial and clinical risk factors. Crisis. 2011, 32 (5): 283-287.View ArticlePubMedGoogle Scholar
  15. Perroud N, Baud P, Mouthon D, Courtet P, Malafosse A: Impulsivity, aggression and suicidal behavior in unipolar and bipolar disorders. J Affect Disord. 2011, 134 (1–3): 112-118.View ArticlePubMedGoogle Scholar
  16. Fava M, Rosenbaum JF, Pava JA, McCarthy MK, Steingard RJ, Bouffides E: Anger attacks in unipolar depression, Part 1: Clinical correlates and response to fluoxetine treatment. Am J Psychiatry. 1993, 150 (8): 1158-1163.View ArticlePubMedGoogle Scholar
  17. Jeon HJ, Peng D, Chua HC, Srisurapanont M, Fava M, Bae JN, Man Chang S, Hong JP: Melancholic features and hostility are associated with suicidality risk in Asian patients with major depressive disorder. J Affect Disord. 2013, 148 (2–3): 368-374.View ArticlePubMedGoogle Scholar
  18. Jeon HJ: Epidemiologic studies on depression and suicide. J Korean Med Assoc. 2012, 55 (4): 322-328. 10.5124/jkma.2012.55.4.322.View ArticleGoogle Scholar
  19. Alonso J, Angermeyer MC, Bernert S, Bruffaerts R, Brugha TS, Bryson H, de Girolamo G, Graaf R, Demyttenaere K, Gasquet I, et al: Prevalence of mental disorders in Europe: results from the European Study of the Epidemiology of Mental Disorders (ESEMeD) project. Acta Psychiatr Scand Suppl. 2004, 420: 21-27.PubMedGoogle Scholar
  20. Srisurapanont M, Hong JP, Tian-Mei S, Hatim A, Liu CY, Udomratn P, Bae JN, Fang Y, Chua HC, Liu SI, et al: Clinical features of depression in Asia: results of a large prospective, cross-sectional study. Asia-Pacific Psychiatry. 2013, 5 (4): 259-267. 10.1111/appy.12104.View ArticlePubMedGoogle Scholar
  21. Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, Hergueta T, Baker R, Dunbar GC: The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998, 59 (Suppl 20): 22-33. quiz 34–57PubMedGoogle Scholar
  22. American Psychiatric Association: Diagnostic and statistical manual of mental disorders. 1994, Washington, DC: American Psychiatric Press, 4Google Scholar
  23. Ahrens B, Linden M, Zäske H, Berzewski H: Suicidal behavior—symptom or disorder?. Compr Psychiatry. 2000, 41 (2): 116-121.View ArticlePubMedGoogle Scholar
  24. Roaldset JO, Linaker OM, Bjorkly S: Predictive validity of the MINI suicidal scale for self-harm in acute psychiatry: a prospective study of the first year after discharge. Arch Suicide Res. 2012, 16 (4): 287-302. 10.1080/13811118.2013.722052.View ArticlePubMedGoogle Scholar
  25. Montgomery SA, Asberg M: A new depression scale designed to be sensitive to change. Br J Psychiatry. 1979, 134: 382-389. 10.1192/bjp.134.4.382.View ArticlePubMedGoogle Scholar
  26. Derogatis L: SCL-90-R (revised) version manual I. Clinical Psychometric Research Unit. 1997, Baltimore, MD: John Hopkins University School of MedicineGoogle Scholar
  27. Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD: The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol. 1989, 46 (10): 1121-1123. 10.1001/archneur.1989.00520460115022.View ArticlePubMedGoogle Scholar
  28. Ware JE, Snow KK, Kosinski M, Gandek B, New England Medical Center Hospital: Health I: SF-36 health survey : manual and interpretation guide. 1993, Boston: Health Institute, New England Medical CenterGoogle Scholar
  29. Sheehan DV, Harnett-Sheehan K, Raj BA: The measurement of disability. Int Clin Psychopharmacol. 1996, 11 (Suppl 3): 89-95.View ArticlePubMedGoogle Scholar
  30. Zimet GD, Dahlem NW, Zimet SG, Farley GK: The multidimensional scale of perceived social support. J Personality Assess. 1988, 52 (1): 30-41. 10.1207/s15327752jpa5201_2.View ArticleGoogle Scholar
  31. Jeon HJ, Lee JY, Lee YM, Hong JP, Won SH, Cho SJ, Kim JY, Chang SM, Lee D, Lee HW, et al: Lifetime prevalence and correlates of suicidal ideation, plan, and single and multiple attempts in a Korean nationwide study. J Nerv Ment Dis. 2010, 198 (9): 643-646. 10.1097/NMD.0b013e3181ef3ecf.View ArticlePubMedGoogle Scholar
  32. Vyssoki B, Praschak-Rieder N, Sonneck G, Bluml V, Willeit M, Kasper S, Kapusta ND: Effects of sunshine on suicide rates. Compr Psychiatry. 2012, 53 (5): 535-539. 10.1016/j.comppsych.2011.06.003.View ArticlePubMedGoogle Scholar
  33. Meng L: Rebellion and revenge: the meaning of suicide of women in rural China. Int J Soc Welfare. 2002, 11 (4): 300-309. 10.1111/1468-2397.00239.View ArticleGoogle Scholar
  34. Ji J, Kleinman A, Becker AE: Suicide in contemporary China: a review of China's distinctive suicide demographics in their sociocultural context. Harv Rev Psychiatry. 2001, 9 (1): 1-12. 10.1080/hrp.9.1.1.12.View ArticlePubMedGoogle Scholar
  35. Moller-Leimkuhler AM: The gender gap in suicide and premature death or: why are men so vulnerable?. Eur Arch Psychiatry Clin Neurosci. 2003, 253 (1): 1-8. 10.1007/s00406-003-0397-6.View ArticlePubMedGoogle Scholar
  36. Yip PS, Liu KY: The ecological fallacy and the gender ratio of suicide in China. Br J Psychiatry. 2006, 189: 465-466. 10.1192/bjp.bp.106.021816.View ArticlePubMedGoogle Scholar
  37. Phillips MR, Yang G, Zhang Y, Wang L, Ji H, Zhou M: Risk factors for suicide in China: a national case–control psychological autopsy study. Lancet. 2002, 360 (9347): 1728-1736. 10.1016/S0140-6736(02)11681-3.View ArticlePubMedGoogle Scholar
  38. Center for Suicide Research and Prevention: Final Report of the Centre of Suicide Research and Prevention. 2006, Hong Kong: The University of Hong KongGoogle Scholar
  39. Lauber C, Rossler W: Stigma towards people with mental illness in developing countries in Asia. International review of psychiatry. 2007, 19 (2): 157-178. 10.1080/09540260701278903.View ArticlePubMedGoogle Scholar
  40. Gururaj G, Isaac MK, Subbakrishna DK, Ranjani R: Risk factors for completed suicides: a case–control study from Bangalore. India. Inj Control Saf Promot. 2004, 11 (3): 183-191. 10.1080/156609704/233/289706.View ArticlePubMedGoogle Scholar
  41. MANiAM T, Chan L: Half a century of suicide studies-a plea for new directions in research and prevention. Sains Malaysiana. 2013, 42 (3): 399-402.Google Scholar
  42. Maniam T, Chinna K, Mariapun J: Suicide prevention program for at-risk groups: pointers from an epidemiological study. Preventive Medicine. 2013, 57: S45-S46.View ArticlePubMedGoogle Scholar
  43. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-244X/14/37/prepub

Copyright

© Lim et al.; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Advertisement