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. 2014 Oct 6;9(10):e104368. doi: 10.1371/journal.pone.0104368

Prevalence of Suicidal Ideation in Chinese College Students: A Meta-Analysis

Zhan-Zhan Li 1, Ya-Ming Li 2,3, Xian-Yang Lei 3, Dan Zhang 2, Li Liu 2, Si-Yuan Tang 2, Lizhang Chen 1,*
Editor: Martin Voracek4
PMCID: PMC4186746  PMID: 25285890

Abstract

Background

About 1 million people worldwide commit suicide each year, and college students with suicidal ideation are at high risk of suicide. The prevalence of suicidal ideation in college students has been estimated extensively, but quantitative syntheses of overall prevalence are scarce, especially in China. Accurate estimates of prevalence are important for making public policy. In this paper, we aimed to determine the prevalence of suicidal ideation in Chinese college students.

Objective and Methods

Databases including PubMed, Web of Knowledge, Chinese Web of Knowledge, Wangfang (Chinese database) and Weipu (Chinese database) were systematically reviewed to identify articles published between 2004 to July 2013, in either English or Chinese, reporting prevalence estimates of suicidal ideation among Chinese college students. The strategy also included a secondary search of reference lists of records retrieved from databases. Then the prevalence estimates were summarized using a random effects model. The effects of moderator variables on the prevalence estimates were assessed using a meta-regression model.

Results

A total of 41 studies involving 160339 college students were identified, and the prevalence ranged from 1.24% to 26.00%. The overall pooled prevalence of suicidal ideation among Chinese college students was 10.72% (95%CI: 8.41% to 13.28%). We noted substantial heterogeneity in prevalence estimates. Subgroup analyses showed that prevalence of suicidal ideation in females is higher than in males.

Conclusions

The prevalence of suicidal ideation in Chinese college students is relatively high, although the suicide rate is lower compared with the entire society, suggesting the need for local surveys to inform the development of health services for college students.

Introduction

Suicide is usually not an isolated event, but a sequence of processes starting from death wishes, suicidal ideation, suicidal contemplation, suicide attempt, to suicide completion [1]–[2]. Suicidal ideation, which is defined as thoughts of self-harming or -killing [3] is a significant marker not only for mental-health problems but also for the suicide attempt and completed suicide among youths. Various suicidal cognitions (death wish, suicidal ideation, and suicide plan) and behaviors (suicide attempt, and commit suicide) are determined by common factors, such as personality characteristics, psychopathology, parenting style, family function, and substance [4]–[5]. Thus, it is imperative to identify the characteristics of suicidal ideation and to develop effective prevention and intervention programs.

Currently, suicide is the leading cause of death among 15- to 34-year-old in China, accounting for 19% of deaths in this age group [6]. Suicide has become an important public health issue. A tough challenge placed on top of China's higher education institutions is how to prevent college students from committing suicide and to early detect individuals at high risk of suicide. Given that about 30% of those with suicidal ideation (those who are seriously considering suicide) will attempt suicide, the first step is to determine the overall prevalence of suicidal ideation among college students [7].

Most college students in China are born after post-1980s when the “One-Child” policy switched from a promotive to a mandatory status. Consequently, the majority of them are from single-child families [8]. Hence, it has been becoming a primary argument regarding their relative impulsiveness and inability to withstand negative life events, compared with young adults with siblings. Despite many investigations into the prevalence of suicidal ideation in college students, quantitative syntheses of overall prevalence are scarce, especially in China. Primary prevention as the best and most important strategy requires a sensible plan of action for prevention and improving current policies against suicidal ideation in college students. Therefore, summarizing the prevalence of suicidal ideation in college students is the first step in developing research priorities. We performed a systematic review and meta-analysis of studies on suicidal ideation in Chinese college students with the aim to explore the prevalence of suicidal ideation in this area.

Materials and Methods

Literature Search Strategy

Databases including PubMed, Web of Knowledge, Chinese Web of Knowledge, Wangfang (Chinese database) and Weipu (Chinese database) were systematically reviewed to identify articles published between 2004 to July 2013, in either English or Chinese, reporting the estimates of suicidal ideation prevalence in Chinese college students. Articles were identified with search strategy “suicide” OR “suicidal ideation” OR “suicidal tendency” AND (“college student” OR “undergraduate”). The strategy also included a secondary search of reference lists of records retrieved from databases. Two authors screened the titles and abstracts and reviewed the full-text of the eligible articles.

Inclusion Criteria

The included studies met the following criteria: 1) an original epidemiological study aimed at Chinese college students; 2) with definition of criteria for screening methods and/or screening tools for suicidal ideation and with the provision of description of screening methods; 3) providing information about sample size and prevalence estimation for college students during the prior 12 months; 4) a cross-sectional study or a baseline survey of longitudinal study; 5) a sample size >500. 6) Language is limited to English and Chinese.

Data Extraction

Information was extracted from all selected publications by two investigators separately. Any disagreement was discussed and resolved by a third investigator. After the duplicates were removed, the following information was extracted from each article: first author, year of publication, region, area (South or North China), age range and mean age if possible, percent of males, major (medical student or not), screening method, screening tool, sample size, response rate, number of people with suicidal ideation, prevalence estimation, and sex-specific prevalence if possible.

Statistical Analysis

We first transformed proportions into a quantity (the Freeman-Tukey variant of the arcsine square root transformed proportion [9] suitable for the usual fixed and random effects summaries [10]), because the inverse variance weight in fixed-effects meta-analyses is suboptimum when dealing with binary data with low prevalence. Additionally, the transformed prevalence is weighted very slightly towards 50% and thus studies with prevalence of 0 can be included in the analysis. The pooled proportion is calculated as the back-transform of the weighted mean of the transformed proportions, using inverse arcsine variance weights for the fixed effect's model and DerSimonian-Laird weights for the random effect's model.

According to the expected heterogeneity across studies, a random-effects model was used to calculate pooled prevalence and 95% confidence interval (CIs). Between-study heterogeneity was evaluated with the Cochran chi-square (χ2) and quantified with the I2 statistic, which will be used to estimate total variation across studies due to heterogeneity rather than chance (<25% is considered as low heterogeneity, 25%–50% as moderate, and >50% as high) [11], [12]. In order to understand the prevalence of suicidal ideation in different sex, mean age, study year, sample, area and major and also explore the potential heterogeneity between studies, dummy-coding is used for three or more categories variables. We conducted subgroups analysis. Then the effects of these covariates on the logit prevalence of the outcome were estimated using meta-regression. Each covariate was included separately in univariate analyses, and then a multivariable meta-regression model was constructed including all covariates. Publication bias was evaluated Begg's test, the modified Egger's linear regression test and Trim-and-fill approach. Significance was set at P<0.05. All statistical calculations were made using Stata 11.0 (College Station, Texas) and Statsdirect 2.7.9 (http://www.statsdirect.com).

Results

Study flow and characteristics

A total of 1908 studies were identified after initial search. After removal of duplicates and an initial screening, we reviewed 177 papers in full. After exclusion of ineligible reports, 41 studies [13]–[53] published between January 2004 and July 20, 2013 were finally included. The flow diagram of the search process is exhibited in Figure 1. The characteristics of studies on the prevalence of suicidal ideation among college students are shown in Table 1. The sample size of the reviewed studies ranged from 610 to 21072 (median 2374), with a total of 160339 college students. Among them, 28 (68.3%) reports reported data on male (n = 69701), 28 (68.3%) reports on female (n = 55140), and 13 (31.7%) reports included mixed sex population size (n = 35228). In the surveys with samples, more than 54% of the individuals were men. The age ranged from 16 to 25 years old. Among them, 29 (70.7%) reports were aimed at South China (n = 112706), 12 reports at North China (n = 47633), 16 (39.0%) at medical universities (n = 51645), and 25 (61.0%) at non-medical students (n = 108694). Table 1 shows details from the 41 selected studies. Questionnaire is used to collect the information in the most of studies. 18 use the self-made scale, 9 for beck scale for suicide ideation-Chinese version, 7 for university personality inventory, and the left use other scales.

Figure 1. Flow diagram of included/excluded studies.

Figure 1

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Table 1. Characteristic of Studies on the Prevalence of Suicidal Ideation among College Students.

NO. First author Publication year Region Province Area Age (mean years) Male Percent (%) Medical student Screening method Screening tools Response Rate (%) Suicidal ideation Sample size Prevalence (%)
1 Wang [13] 2012 Mainland Henan Northern 17–22 44.2 No Q UPI 97.10 162 3850 4.21
2 Chen [14] 2010 Mainland Chongqing Southern 20.0 56.6 Yes Q SMQ 81.0 1279 9808 13.0
3 Xu [15] 2004 Mainland Hunan Southern - 53.4 Yes Q SMQ 97.9 89 610 14.6
4 Chen [16] 2008 Mainland Jilin Northern 21.3 67.1 Yes QI CIDI 98.9 97 1822 5.3
5 Liu [17] 2007 Mainland Yunnan Southern 21.2 50.4 No Q SMQ 97.4 437 3313 13.2
6 Chao [18] 2008 Mainland Jiangxi Southern - 51.8 No Q SMQ 84.2 113 1010 11.2
7 Shang [19] 2008 Mainland Gansu Northern 20.5 35.8 Yes Q SMQ 92.3 411 2678 15.4
8 Qian [20] 2008 Mainland Beijing Northern - 35.4 Yes Q SMQ 88.2 122 2199 5.6
9 Yang [21] 2013 Mainland Henan Southern 20.7 33.5 Yes Q UPI 92.2 110 1372 8.0
10 Zhang [22] 2007 Mainland Guangdong Southern - 52.8 Yes Q EPQ 99.3 1763 7189 24.5
11 Wang [23] 2011 Mainland Yunnan Southern 18.9 35.5 Yes Q SMQ 99.84 409 1850 22.1
12 Jiang [24] 2006 Mainland Fujian Southern - 56.3 Yes Q SMQ 90.4 171 1254 13.6
13 Li [25] 2009 Mainland Beijing Northern 25.1 64.4 No Q UPI 97.6 380 21072 1.8
14 Li [26] 2007 Mainland Zhejiang Southern 18.6 40.1 No Q SCL-90 95.0 800 8160 9.8
15 Bao [27] 2009 Mainland Anhui Southern 20.1 61.0 Yes Q BSSI 92.7 217 1529 14.2
16 Huang [28] 2007 Mainland Zhejiang Southern 18.85 64.0 No QI SCL-90 94.2 219 3564 6.1
17 Wang [29] 2011 Mainland Shanxi Northern 19.2 44.9 Yes Q SDSS 98.3 74 1177 6.3
18 Kong [30] 2012 Mainland Anhui Southern 20.4 42.9 Yes Q SMQ 91.8 444 3030 14.7
19 Song [31] 2010 Mainland Anhui Southern 21.8 55.9 Yes Q BSSI 95.9 210 2062 10.2
20 Sun [32] 2010 Mainland Shandong Northern 20.4 42.4 No Q BSSI 94.3 228 1886 12.1
21 Yang [33] 2010 Mainland Harbin Northern 21.3 51.1 No Q SMQ 87.8 479 5240 9.1
22 Yan [34] 2009 Mainland Guangdong Southern 21.2 46.8 No Q SMQ 87.2 57 772 7.4
23 Shi [35] 2007 Mainland Guangdong Southern 20.6 49.8 No Q SMQ 98.0 297 2564 11.6
24 Shi [36] 2013 Mainland Guangxi Southern 20.4 52.7 No Q BSSI 91.0 434 2730 15.9
25 Ran [37] 2006 Mainland Sichuan Southern - 70.6 No Q UPI 100.0 229 8850 2.6
26 Kan [38] 2013 Mainland Zhejiang Southern - 46.1 No Q UPI 99.9 263 10138 2.6
27 Zhao [39] 2011 Mainland Guangdong Southern 21.7 56.6 No Q SMQ 96.35 98 1450 6.8
28 Yin [40] 2009 Mainland Jiangsu Southern 21.3 36.4 No QI SMQ 95.7 90 670 13.4
29 Yang [41] 2007 Mainland Henan Northern 16–24 74.6 No Q SCL-90 93.9 705 3568 19.8
30 Liu [42] 2013 Mainland Guangdong Southern 14–25 58.5 No Q SPS 100.0 585 6154 9.5
31 Tu [43] 2013 Mainland Guangdong Southern 21.0 60.0 No Q UPI 100.0 144 11603 1.24
32 Liu [44] 2008 Mainland Beijing Northern - 42.5 Yes Q SMQ 91.4 125 1204 10.4
33 Li [45] 2008 Mainland Beijing Northern 20.0 55.6 No Q BSSI 97.6 166 2055 8.1
34 Cao [46] 2009 Mainland Anhui Southern 19.3 46.2 Yes QI BSSI 91.8 1669 10344 16.4
35 Fan [47] 2008 Mainland Anhui Southern 20.3 53.5 Yes Q BSSI 94.4 496 3517 14.1
36 Tang [48] 2011 Mainland Hubei Southern 10–24 54.7 No Q SMQ 100.0 178 2013 8.8
37 Zhang [49] 2012 Mainland Guangdong Southern 21.8 48.6 No Q SMQ 87.2 137 689 19.9
38 Zhu [50] 2011 Mainland Jiangsu Southern 19.6 47.1 No Q BSSI 98.1 430 2374 18.1
39 Zhao [51] 2012 Mainland Guangdong Southern 19.5 46.4 No Q BSSI 84.0 225 1168 19.3
40 Wang [52] 2010 Mainland Shanxi Northern 19.0 46.9 No Q UPI 93.0 46 882 5.6
41 Gau [53] 2008 Taiwan Taiwan Southern 19.4 48.5 No Q SMQ 79.2 759 2919 26.0
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Screen methods: Q, questionnaire distribution; QI, questionnaire-based interview. Screening tools: UPI, University Personality Inventory, SMQ, Self-made scale; CIDI, Composite International Diagnostic Interview; BSSI, Beck Scale for Suicide Ideation-Chinese Version.

Pooled analysis in different category

Overall prevalence

The point prevalence of suicidal ideation with the 41 individual study populations ranged between 1.24% and 26.00%, with an overall meta-analysis prevalence of 10.72% (95%CI: 8.41%–13.28%, Figure 2) and evident high-level heterogeneity between studies (I2 = 99.6%, P<0.0001).

Figure 2. Forest plot of prevalence of suicidal ideation for total people.

Figure 2

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Sex

Pooled prevalence of all subgroups of study year, population size, male percent, area, major and sex are presented in Table 2. The summarized prevalence of females (10.32%, 95%CI: 7.17%–13.97%, Figure 3) was higher than that of males (8.84%, 95%CI: 6.45%–11.57%, Figure 4). The prevalence estimates for studies with more than 50% males were lower than estimates of groups with less than 50% males (8.84%, 95%CI: 6.45%–11.57%).

Table 2. Prevalence of Suicidal Ideation among College Students According to Different Category.
Category Subgroup NO. of Studies Prevalence (95%CI)(%) N I2 (%) P Publication Bias Test
P(Begg's Test) P(Egger's Test)
Total 41 10.72[8.41–13.28] 160339 99.6 <0.0001 0.258 0.008
Study year 2004–2007 9 12.10[6.97–18.44] 39072 99.7 <0.0001 0.915 0.704
2008–2009 13 10.73[6.16–16.39] 51791 99.7 <0.0001 0.858 0.183
2010–2011 10 10.77[8.30–13.53] 28742 97.9 <0.0001 0.600 0.942
2012–2013 9 9.35[5.13–14.68] 47034 99.6 <0.0001 0.119 0.009
Sample size <2000 16 11.40[8.89–14.19] 19345 97.5 <0.0001 0.003 0.001
2000–4000 15 12.22[9.30–15.49] 42436 99.0 <0.0001 0.0001 0.0001
>4000 10 7.70[3.77–12.85] 98558 99.9 <0.0001 0.009 0.0001
Male percent <50% 20 11.67[8.63–15.10] 59926 99.3 <0.0001 0.186 0.388
≥50% 21 9.85[6.68–13.57] 100413 99.7 <0.0001 0.492 0.069
Area Northern 12 8.00[4.67–12.14] 47633 99.5 <0.0001 0.381 0.065
Southern 29 11.95[9.09–15.14] 112706 99.6 <0.0001 0.838 0.119
Medical students Yes 16 12.58[10.09–15.30] 51645 98.7 <0.0001 0.757 0.792
No 25 9.61[6.97–12.62] 108694 99.6 <0.0001 0.083 0.008
Sex Male 28 8.84 [6.45–11.57] 69701 99.3 <0.0001 0.570 0.0001
Female 28 10.32[7.17–13.97] 55140 99.4 <0.0001 0.101 0.422
Response rate 90%≤ 9 12.81[9.30–17.32] 25059 98.7 <0.0001 0.531 0.589
<90% 32 10.93[9.72–12.13] 135280 99.5 <0.0001 0.023 0.004
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Figure 3. Forest plot of prevalence of suicidal ideation for male.

Figure 3

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Figure 4. Forest plot of prevalence of suicidal ideation for female.

Figure 4

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Periods

The pooled prevalence estimate decreased over time. Between 2004 and 2007, the pooled prevalence estimate was 12.10% (95%CI: 6.97%–18.44%), which decreased to 10.73% (95%CI: 6.16%–16.39%) between 2008 and 2009. The estimate was 10.77% (95%CI: 8.30%–13.53%) in 2010 to 2011, and 9.35% (95%CI: 5.13%–14.68%) in 2012 to 2013.

Major and area

The prevalence for the non-medical group (9.61%, 95%CI: 6.97%–12.62%) was smaller than medical group (12.58 95%CI: 10.09%–15.30%). Prevalence among college students from South and North China were 11.95% (95%CI: 9.09%–15.14%) and 8.00% (95%CI: 4.67%–12.14%) respectively.

Population size and response rate

Regarding population size, the pooled prevalence was 11.40% (95%CI: 8.89%–14.19%) for population size <2000, 12.22% (95%CI: 9.30%–15.49%) and 7.70% (95%CI: 3.77%–12.85%) for population size >4000. Table 2 shows information about heterogeneity and publication bias. The pooled prevalence for response rate ≤90% was 12.81% (95%CI: 9.30–17.32) and 10.93 (95%CI: 9.72–12.13) for response rate >90%.

Meta-regression analysis, assessment of publication bias

We noted significant heterogeneity within studies and subgroups (P<0.001, I2 = 97.9%–99.0%). In the univariate meta-regression analyses (Table 3), year of publication, male percent and major used to define suicidal ideation did not modify the estimate of prevalence. In three population size groups (<2000, 2000–4000, >4000), the prevalence estimates in population size >4000 were significantly lower compared with the other two groups. Mean age (P = 0.017) and response rates (P = 0.012) were significantly associated with the prevalence estimates. A meta-regression model was constructed including male ratio, response rate and population size (2000–4000). This model explained much of the heterogeneity between studies (R2 = 52.85%, P = 0.016, Table 3). We noted the prevalence of suicidal ideation decrease with response rate and male rate increase in the proportion and increase with the sample size increase. Then bias of publication was assessed using Begg's funnel plot and Egger's test. Significant publication bias was indicated by Begg's test (P = 0.008), but not by the modified Egger's linear regression test (P = 0.258). The funnel plot an apparent asymmetry that suggested the presence of a potential publication bias (Figure 5). Trim-and-Fill analyses was also used to assess publication bias. The pooled estimations for fixed and random models were −2.10 (95%CI: −2.17 to −2.02) and −2.21 (95%CI: −2.45 to −1.97). After estimated missing study was included into the meta-analysis, the pooled estimations for fixed and random models were −2.40 (95%CI: −2.47 to −2.33) and −2.43 (95%CI: −2.68 to −2.17). The estimated missing number of study is eight, which suggested the presence of publication bias.

Table 3. Results of Meta-regression for Prevalence among Chinese College Students.

Covariate Meta-regression coefficient 95%CI P value Variance explained (%)
Univariate analyses
Year of publication
2004–2007 0.176 −0.356 to 0.709 0.507 −1.40
2008–2009 0.015 −0.460 to 0.492 0.946 −2.55
2010–2011 0.078 −0.437 to 0.594 0.759 −2.31
2012–2013 −0.281 −0.809 to 0.246 0.288 0.41
Male percent −0.235 −0.672 to 0.202 0.283 0.46
Sample size
<2000 0.192 −0.258 to 0.642 0.394 −0.64
2000–4000 0.283 −0.168 to 0.734 0.212 1.51
>4000 −0.604 −1.082 to −0.126 0.015 12.16
Area 0.392 −0.077 to 0.863 0.099 4.43
Mean age −0.230 −0.417 to −0.044 0.017 16.2
Screening tool −0.435 −0.859 to −0.010 0.045 7.26
Response rate −0.050 −0.088 to −0.011 0.012 13.01
Medical student 0.359 −0.080 to 0.799 0.106 4.16
Multivariable analyses 0.016 52.85
Response rate −0.057 −0.10 to −0.014 0.011
Male rate −0.030 −0.055 to −0.004 0.024
Sample size(2000–4000) 0.778 0.210 to 1.346 0.010
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Figure 5. Funnel plot of studies included in the synthesis.

Figure 5

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Discussion

There is a lack of nationwide data regarding prevalence of suicidal ideation in Chinese college students at present. This is the first report attempting to synthesize the prevalence estimations of suicidal ideation among Chinese college students using meta-analysis. This comprehensive systematic review with meta-analysis of observational studies done in China in the last decade included 41 reports and more than 160 thousand college students. Therefore, it was possible to provide a reliable estimate of prevalence. This meta-analysis indicates that the prevalence of suicidal ideation in Chinese college students is 10.72% (95%CI: 8.41%–13.28%), which was close to previously reported rates [31] and fell in the range of 6%–39.2% reported in other countries [54]–[56].

Suicidal ideation among college students is associated with various factors, which can be categorized into several domains, including physiology, suicide attitude, psychological health status, stress, and social support.

Sex may significantly affect the prevalence of suicidal ideation. A national representative population-based study from Korea found the prevalence of suicidal ideation was significantly higher among females: about 19% of females and 11% of males reported suicidal ideation [57]. In Kampala (Uganda), the prevalence of suicidal ideation was significantly higher in girls (34%) than boys (23.2%) [58]. However, other studies did not report the sex difference for suicidal ideation [59]. This meta-analysis showed that 8.84% of males and 10.32% of females had suicidal ideation, and this difference can be partially explained by the following reasons. According to the gender role socialization theory, males are expected to be independent and decisive, and display masculinity (e.g. engagement in risky behaviors). In contrast, females are expected to be dependent and indecisive, and express their stress via rumination. So females have a higher rate of suicide attempts than males, while males have a higher rate of mortality from suicide than females [60]. In China, fatal suicide rate for male was higher than females. But fatal suicide rate for females was still higher than males among population aged 15 to 34 (including college student) [61]. Suicidal ideation pattern in this meta-analysis may be similar to the pattern of fatal suicide.

Psychological health status exerts an implicit, deep and fundamental influence on suicidal ideation. About 50%–75% of children and adolescents who have suicidal ideation suffered from emotional disturbance, especially severe depression; about 1/4–2/3 of adolescents with suicidal ideation have a history of drug dependence and abuse [62]. Personality disorder in adults with suicidal ideation is more common than adolescents, indicating that adolescents with personality disorder are easily addicted to drug abuse and more likely to develop suicidal ideation [63]. Sexual orientation will greatly affect the suicidal ideation and suicidal behaviors of the youths, which is regulated by depression, hopelessness and drug abuse [64]–[65].

Negative life events that are a direct source of stimulation inducing suicidal ideation. College students who experience more negative life events are at increased risk for suicidal ideation. Associations between suicidal ideation and failure in love, financial problems, and divorce/separation of parents have been reported [71]. Findings also suggest that negative life events may be associated with suicidal ideation among adolescent, depressive symptoms were associated with suicidality and depressive symptoms may mediate the association of minor negative life events with suicidality [66].

Higher levels of family cohesion and family support were associated with lower levels of suicidal ideation and depression [67]. Living alone increased the risk for suicidal ideation among college students [68], suggesting that facilitating access to support resources might reduce the risk for suicidal behavior among college students. In addition, friends are also an important source of support and may be an even greater resource than the family [69]. Therefore, evaluating the support system of friends may provide further information that can help prevent suicide.

There are other factors of suicidal ideation such as cultural orientation [70], religious belief [51], history of family suicide [36], and social-economic status [46]. The factors affecting suicidal ideation in college students are not single, but multifaceted. Depression fully mediated the relationship between physical illness, interpersonal conflict and suicidal ideation, but not the relationship between financial problem and suicidal ideation [71]. Another study confirmed the hypothesis that family cohesion and social self-concept were significant moderators for children and adolescents [70]. In sum, on an individual basis, one or all three factors could work, and even accidental factors may also contribute to suicidal ideation.

For the reasons given above, some effective measures should be taken. It is suggested that the experience of violence had a significant negative direct effect and peer support had a significant positive direct effect on their happiness. Happiness had a significant negative effect and the experience of violence had a significant positive effect on suicidal ideation. These findings demonstrate the fundamental importance of reducing exposure of violence to the youth, and that increasing peer support and their happiness may be the key to adolescent suicidal ideation prevention [72]. Sakamoto et al found that watching the video had substantial psych educational effects, which could be considered as prevention measures [73]. What is more, the lack of mental health services is an urgent problem of campus populations in China. More mental health counselors are needed [74]. College students would benefit greatly by attention to this measures.

Although this meta-analysis includes 41 studies encompassing a larger sample size than individual studies, there are still some limitations. First, the heterogeneity of both total population and subgroup was high. Most of the included studies had large sample sizes that produced very precise estimates. Meta-regression analysis showed that male ratio, sample size and response rate may be associated with the prevalence of suicidal ideation, which explained about the half of the heterogeneity between studies. But non-theory-guided selection of predictors based on an algorithm may lead to replication difficulties in future studies. We noted the prevalence of suicidal ideation decrease with response rate and male rate increase in the proportion and increase with the sample size increase. The difference of screening methods may have an influence on the heterogeneity. But this result should be carefully explained. Because some variable are associated with outcome variables in a single, and not associated with outcome variable after being combined. We call this aggregation bias, ecological bias, ecological confounding or ecological fallacy. It is acknowledged that there must be some factors affecting the heterogeneity. According to the present data, we cannot further identify the source of heterogeneity. Second, results from Begg's funnel plot and Egger's test are different but the funnel plot and Trim and Fill methods suggested the presence of a potential publication bias, a language bias, and inflated estimates by a flawed methodological design in smaller studies. The available studies had important methodological limitations, particularly related to college students with suicidal ideation selection and recruitment, which may have led to subjects included in studies differing in important ways from those excluded or ineligible for analyses, and that may have unpredictably affected prevalence estimates. Finally, the studies with a sample size less than 500 subjects were not included on the basis of the sake of representativeness of survey samples. The information bias may still affect the pooled results, although we restricted sampling methods in inclusion criteria.

In conclusion, the prevalence of suicidal ideation in Chinese college students is relatively high, although the suicide rate is lower than that of the entire society. Considering the policy of enrollment expansion of higher education in China is implemented, It is sincerely hoped that this meta-analysis synthesized within the past decade will serve as a “wake-up” call to university administration alike. The results should encourage not only more needed research in terms of the college student group as a distinct population unto itself, but also prompt colleges, society and family to develop and implement programs to address, educate and prevent those college students who are most at risk for suicidal ideation.

Supporting Information

Checklist S1

PRISMA 2009 Checklist.

(DOC)

Click here for additional data file. (64.5KB, doc)
Diagram S1

PRISMA 2009 Flow Diagram.

(DOC)

Click here for additional data file. (62.5KB, doc)

Funding Statement

This study was supported by Hunan Province Science and Technology Project (2014FJ3093). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1. Jiang M, Hu Z, Cao Y (2007) Suicide deaths concentrated in Beijing universities. Am J Psychiatry 164: 1758. [DOI] [PubMed] [Google Scholar]
  • 2. Perez WV (2005) The relationship between seriously considering, planning, and attempting suicide in the youth risk behavior survey. Suicide and Life-threatening Behavior 35: 35–49. [DOI] [PubMed] [Google Scholar]
  • 3.National Research Council (2002) Reducing Suicide: A National Imperative. Washington, DC: The National Academies Press. [PubMed] [Google Scholar]
  • 4. Beautrais AL (2000) Risk factors for suicide and attempted suicide among young people. Aust N Z J Psychiatry 34: 420–436. [DOI] [PubMed] [Google Scholar]
  • 5. Kuo PH, Yang HJ, Soong WT, Chen WJ (2002) Substance use among adolescents in Taiwan: associated personality traits, incompetence, and behavioral/emotional problems. Drug Alcohol Depend 67: 27–39. [DOI] [PubMed] [Google Scholar]
  • 6. Phillips MR, Li X, Zhang Y (2002) Suicide rates in China, 1995–99. Lancet 359: 835–840. [DOI] [PubMed] [Google Scholar]
  • 7. Kirmayer LJ, Fraser SL, Faurus V, Heather Clarke MA, Saucier Jean-François, et al. (2009) Cultural and Mental Health Research Unit working paper 14. Montreal, Quebec: 2009. Current approaches to Aboriginal youth suicide prevention [Google Scholar]
  • 8. Luo MY (2010) Social Assessment and Subdividing of After-1980s. China Youth Study 11: 32–35. [Google Scholar]
  • 9.Stuart A, Ord JK (1994) Kendall's Advanced Theory of Statistics (6th edition). London: Edward Arnold. [Google Scholar]
  • 10. DerSimonian R, Laird N (1986) Meta-analysis in Clinical Trials. Controlled Clinical Trials 7: 177–188. [DOI] [PubMed] [Google Scholar]
  • 11. Brittain EH, Fay MP, Follmann DA (2012) A valid formulation of the analysis of noninferiority trials under random effects meta-analysis. Biostatistics 13: 637–649. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12. Chootrakool H, Shi JQ, Yue R (2011) Meta-analysis and sensitivity analysis for multi-arm trials with selection bias. Stat Med 30: 1183–1198. [DOI] [PubMed] [Google Scholar]
  • 13. Wang BW (2012) Psychological health condition and its influence factors among freshmen with suicidal ideation. Chin J Public Health 28: 1086–1088. [Google Scholar]
  • 14. Chen JM, Ai M, Kuang L, Wang MJ, Shen Y, et al. (2010) Suicide ideation among college students in Chongqing. Chin J Epidemiol 31: 290–293. [PubMed] [Google Scholar]
  • 15. Xu HL, Xiao SY, Feng SS, Chen XX (2004) Risk factors for suicide attempt among college students at Central South University. Chin J Epidemiol 25: 288–291. [PubMed] [Google Scholar]
  • 16. Chen YF, Kou CG, Zhang D, Xie B, Yu YQ, et al. (2008) Analysis on suicide tendency and its risk factors of undergraduate students[J]. Chin J Dis Control Prev 12: 450–453. [Google Scholar]
  • 17. Liu QQ, Li H, Fang XY (2007) An investigation of suicidal ideation and suicide attempts of undergraduate in Yunnan province with their self-esteem and mental health status. China Journal of Health Psychology 15: 57–58. [Google Scholar]
  • 18. Chao XC (2008) Different personality of undergraduate students with and without suicide ideation [J]. Health Medicine Research and Practice 5: 42–44. [Google Scholar]
  • 19. Shang YX, Dong GQ, Liu T (2008) Analysis on prevalence of suicidal ideation and depression and its influence factors among undergraduate students in Yinchuan. Chin J Public Health 24: 934–936. [Google Scholar]
  • 20. Qian WC, Liu BH, Huang YQ, Hao WL, Li WYTN (2008) Study on risk factors for suicidal ideation among undergraduate of medical college. Chin J Public Health 24: 1285–1286. [Google Scholar]
  • 21. Yang CW, Shi SC, Liu JX, Jia RR, Chui WW, et al. (2013) Analysis on suicide ideation and its risk factors among medical college students. Chin J Social Medicine 30: 193–195. [Google Scholar]
  • 22. Zhang XY, Yu SY, Zhao JB (2007) Correlation between suicidal ideation and personality, internal-external locus of control, self-esteem in medical college students. J Fourth Mil Med Univ 28: 747–749. [Google Scholar]
  • 23. Wang T, Jiang RS, Zhou M, Huang YY, Di YX (2011) A study on influencing factors of the undergraduate suicide ideation. Journal of Kunming Medical University 12: 44–47. [Google Scholar]
  • 24. Wang XL, Xu NF, Xue HT, Jiang DW, Yang DH (2006) Analysis on suicide ideation and its factors among medical undergraduate students. Chin J Public Health 22: 653–655. [Google Scholar]
  • 25. Li H, Huang YQ (2009) Study on the related factors of suicide ideation among graduate students in national research institutions. China Journal of Health Psychology 17: 963–966. [Google Scholar]
  • 26. Li FH, Dai WL (2007) Analysis on suicide ideation and its factors among college students in Wenzhou. Chin J School Doctor 21: 290–291. [Google Scholar]
  • 27. Bao DX, Fan YG, Ye DQ (2009) Correlation between suicidal ideation and Life events and social support among medical college students of Wanxi. Chin J Sch Health 30: 939–941. [Google Scholar]
  • 28. Huang QR, Liu B, Feng TL (2007) The relationship between life event and suicide attempts among college students. China J Health Psychology 15: 210–213. [Google Scholar]
  • 29. Wang H, Wang MX, Chu XP (2011) Study on the factors of suicidal ideation and its influences among undergraduates in Shanxi province. Foreign medical science section of med geography 32: 188–191. [Google Scholar]
  • 30. Kong G, Sun YH, Yang LS, Zhou CX (2012) Investigation of psychosocial factors of suicide attitude among the students in a medical college. J Bengbu Med Coll 37: 1240–1243. [Google Scholar]
  • 31. Song YM, Wan YH, Pan FM, Ye DQ (2010) Analysis on suicide ideation and its risk factors among medical college students. Chinese Journal of Health Statistics 27: 178–179. [Google Scholar]
  • 32. Sun AY, Sun YM, Xu HL (2010) Analysis on suicide ideation and its risk factors among college students in Liao cheng. Journal of Qilu Nursing 16: 55–56. [Google Scholar]
  • 33. Yang YJ, Qiu XH, Yang XX, Qiao ZX, Han D, et al. (2010) Study on the influencing factors of suicidal ideation among university students in Harbin. Chin J Epidemiology 31: 1103–1106. [PubMed] [Google Scholar]
  • 34. Yan HH, Liu ZM, Wang SY, Yang G, Chen LF, et al. (2009) Study on the relationship between life events and suicidal ideation among undergraduates in Guangzhou. Modern Preventive Medicine 36: 476–479. [Google Scholar]
  • 35. Shi WJ, Ma SB, Wang SY (2007) Study on prevalence of suicidal ideation and its related factors in college students in Guangzhou. Chin J Sch Health 28: 999–1000. [Google Scholar]
  • 36. Shi XL, Liu YY, Liu SY, Zhao WS, Jiang CL (2013) Analysis of suicidal ideation and relationship with depressive disorder of Guangxi college students countermeasures research. Popular science and technology 15: 114–117. [Google Scholar]
  • 37. Ran CF, Zhang YQ, Wang W, Tian S, Wei J, et al. (2006) Suicide-preventive and suicide-intervening mechanism for vocational college students. J Prev MedInf 22: 548–552. [Google Scholar]
  • 38. Kan SY, Zheng XF (2013) Relationship between suicide ideation and family environment among university students. Chin J Public Health 29: 167–168. [Google Scholar]
  • 39. Zhao GX, Jin CX, Wang SY, Chen QS, Liu GN, et al. (2011) Analysis on influencing factors of suicide ideation among college students: a structural equation model study. Chin J Behv Med Brain Sci 20: 357–359. [Google Scholar]
  • 40. Yi L (2009) Analysis on influencing factors of suicide ideation among college students. Chin J School Doctor 23: 388–390. [Google Scholar]
  • 41. Yang XH, Zhou H, Wang SM (2007) Epidemiological investigation of suicidal ideation in college students. Chin J Sch Health 28: 527–528. [Google Scholar]
  • 42. Liu GH, Zhang GY (2013) The relationship between personality factors and suicide ideation of undergraduates. China Journal of Health Psychology 21: 456–457. [Google Scholar]
  • 43. Tu YM, Zhang QJ (2013) The relationship between life events, coping style and suicide ideation of undergraduates. Educational circles 15: 60. [Google Scholar]
  • 44. Liu BH, Huang YQ, Niu WY, Lv ZZ, Wang PY, et al. (2008) Study on the factors influencing suicidal ideation among medical students in Beijing. Chin J Epidemiol 29: 128–131. [PubMed] [Google Scholar]
  • 45. Li XN, Liu HY, Liu ZR, Guo Q, Huang YQ (2008) A cross-sectional study on related factors of suicidal ideation among college students. Chinese Mental Health Journal 22: 806–815. [Google Scholar]
  • 46. Cao HY, Sun YH, Yao YS, Zhou CX, Yang LS (2009) Suicide behavior and its factors among medical undergraduates in Anhui province. Chin J Sch Health 30: 38–39. [Google Scholar]
  • 47.Fan YG (2008) Study on the influencing factors of suicide ideation among underrates in Anhui Provinces. Anhui: Anhui Medical University, 2008. [Google Scholar]
  • 48. Tang J, Yu Y, Wu Y, Du YK, Ma Y, et al. (2011) Association between non-suicidal self-injuries and suicide attempts in Chinese adolescents and college students: a cross-section study. PLoS One 6: e17977. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49. Zhang X, Wang H, Xia Y (2012) Stress, coping and suicide ideation in Chinese college students. J Adolesc 35: 683–690. [DOI] [PubMed] [Google Scholar]
  • 50. Zhu XH, Wang CD, Zhou Q, Zhaou HF, Yang YJ, et al. (2011) Study on the factors influencing suicidal ideation among 2374 college students. Chin J Behav and Brain Sci 20: 461–462. [Google Scholar]
  • 51. Zhao J, Yang X, Xiao R, Zhang X, Aguilera D, et al. (2012) Belief system, meaningfulness, and psychopathology associated with suicidal among Chinese college students: a cross-sectional survey. BMC Public Health 12: 668. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52. Wang Y, Guo XL (2010) Survey and analysis of psychological health in 882 higher vocational freshmen. Chin J Sch Doctor 24: 202–204. [Google Scholar]
  • 53. Gau S S, Chen YY, Tsai FJ, Li MB, Qiu YN, et al. (2008) Risk factors for suicide in Taiwanese college students. J Am Coll Health 57: 135–142. [DOI] [PubMed] [Google Scholar]
  • 54. Arria AM, O'Grady KE, Caldeira KM, Vincent KB, Wilcox HC, et al. (2009) Suicide ideation among college students: a multivariate analysis [J]. Arch Suicide Res 13: 230–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55. Garlow SJ, Rosenberg J, Moore JD, Haas AP, Koestner B, et al. (2008) Depression, desperation, and suicidal ideation in college students: results from the American Foundation for Suicide Prevention College Screening Project at Emory University. Depress Anxiety 25: 482–488. [DOI] [PubMed] [Google Scholar]
  • 56. Mackenzie S, Wiegel JR, Mundt M, Brown D, Saewyc E, et al. (20111) Depression and suicide ideation among students accessing campus health care. Am J Orthopsychiatry 81: 101–108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57. Park S (2013) Gender-specific factors of suicide ideation among adolescents in the Republic of Korea: a nationally representative population-based study. Arch Psychiatr Nurs 27: 253–262. [DOI] [PubMed] [Google Scholar]
  • 58. Swahn MS, Palmier JB, Kasirye R, Yao H (2012) Correlates of Suicide Ideation and Attempt among Youth Living in the Slums of Kampala. Int J Environ Res Public Health 9: 596–609. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59. Ellis JB, Lamis DA (2007) Adaptive characteristics and suicidal behavior: a gender comparison of young adults. Death Stud 31: 845–854. [DOI] [PubMed] [Google Scholar]
  • 60. Canetto SS, Sakinofsky I (1998) The gender paradox in suicide. Suicide Life Threat Behav 14: 1–23. [PubMed] [Google Scholar]
  • 61. Cai Y, Hu N, Liu WN, Wang LJ (2012) Current situation of suicide deaths among Chinese population in 2010. Chin Pre Med 13: 480–482. [Google Scholar]
  • 62. Gunn J R, Lester D, Mcswain S (2011) Testing the warning signs of suicidal behavior among suicide ideators using the 2009 National survey on drug abuse and health. Int J Emerg Ment Health 13: 147–154. [PubMed] [Google Scholar]
  • 63. Sharp C1, Green KL, Yaroslavsky I, Venta A, Zanarini MC, et al. (2012) The incremental validity of borderline personality disorder relative to major depressive disorder for suicidal ideation and deliberate self-harm in adolescents. J Pers Disord 26: 927–938. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64. Hiramura H, Shono M, Tanaka N, Nagata T, Kotamura T, et al. (2008) Prospective study on suicidal ideation among Japanese undergraduate students: correlation with stressful life events, depression, and depress genic cognitive patterns. Arch Suicide Res 12: 238–250. [DOI] [PubMed] [Google Scholar]
  • 65. Silenzio VM, Pena JB, Duberstein PR, Cerel J, Kerry L, et al. (2007) Sexual orientation and risk factors for suicidal ideation and suicide attempts among adolescents and young adults. Am J Public Health 97: 2017–2019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66. Hardt J, Johnson JG (2010) Suicidality, depression, major and minor negative life events: a mediator model. Psychosoc Med 7: c5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67. Harris TL, Molock SD (2000) Cultural orientation, family cohesion, and family support in suicide ideation and depression among African American college students. Suicide Life Threat Behav 30: 341–53. [PubMed] [Google Scholar]
  • 68. Lee HS, Kim S, Choi I, Lee KU (2008) Prevalence and Risk Factors Associated with Suicide Ideation and Attempts in Korean College Students. Psychiatry Investig 5: 86–93. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69. Dubow EF, Tisak J, Causey D, Hryshko A, Reid G (1991) A two-year longitudinal study of stressful life events, social support, and social problem-solving skills: contributions to children's behavioral and academic adjustment. Child Dev 62: 583–599. [DOI] [PubMed] [Google Scholar]
  • 70. Au AC, Lau S, Lee MT (2009) Suicide ideation and depression: the moderation effects of family cohesion and social self-concept. Adolescence 44: 851–868. [PubMed] [Google Scholar]
  • 71. Wu J, Wu YT, Feng SX, Meng H, Chen H (2012) Mediating effects on depression regarding the relationship between negative life events and suicide ideation among college students. Chin J Epidem 33: 1111–1115. [PubMed] [Google Scholar]
  • 72. Choi JH, Yu M, Kim KE (2014) Suicidal ideation in adolescents: A structural equation modeling approach. Nurs Health Sci doi: 10.1111/nhs.12142. [DOI] [PubMed] [Google Scholar]
  • 73. Sakamoto S, Tanaka E, Kameyama A, Takizawa T, Takizawa S, et al. (2014) The effects of suicide prevention measures reported through a psychoeducational video: A practice in Japan. Int J Soc Psychiatry Epub ahead of print. [DOI] [PubMed] [Google Scholar]
  • 74. Iang M, Hu Z, Cao Y (2007) Suicide deaths concentrated in Beijing universities. Am J Psychiatry 164: 1758. [DOI] [PubMed] [Google Scholar]

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Supplementary Materials

Checklist S1

PRISMA 2009 Checklist.

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Diagram S1

PRISMA 2009 Flow Diagram.

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