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Suicidal ideation in a community-based sample of elementary school children: a multilevel and spatial analysis.

Suicide is the second leading cause of death in adolescents and young adults in Canada. (1) Approximately 800,000 to a million people globally per year, across all age groups, die from suicide; (2) this includes over 3,500 suicides each year in Canada. (3) Suicidal ideation is defined as, "thoughts of engaging in behaviour intended to end one's life", which is often under-evaluated or under-appreciated in evaluating children's health. An early study revealed evidence that adolescents who reported suicidal ideation at an early age were much more likely than their counterparts who denied suicidal ideation to later attempt suicide. (4) Therefore, an examination of childhood suicidal ideation is not only warranted but also timely for an early identification and remediation of suicidal ideation in adulthood.

Previous studies have identified a number of individual risk factors that could contribute to suicidal ideation in adolescents. The most important clinical risk factor for suicidal ideation and suicide attempts is depression. (5) Low self-esteem, anxiety, poor family environments and impaired parent-child relationships have also been connected with suicidal thoughts. (6-8) A number of studies have shown that the suicide rates within First Nations youth are alarmingly high; however, little research has examined suicide ideation in this group, nor the extent to which different factors contribute to suicidal thoughts or attempts. (9)

Victims of bullying in children and adolescence are also recognized as being at increased risk for suicidal ideation. (10) Bullying can take various forms, (11) traditionally including physical (e.g., assault), verbal (e.g., threats), relational bullying (e.g., social exclusion) and more recently, electronic bullying (e.g., e-mail, phone). (12) Although a number of studies provided evidence that being a victim of different types of bullying increases the risk of developing mental health problems and committing suicide later in life, (13,14) few such studies have focused on elementary school children.

This study adds to the ongoing understanding of suicidal ideation among elementary school children by identifying the most relevant predictors. It has also been suggested that suicidal ideation could be more common within schools or classrooms because associating with suicidal people has been shown to "spread" suicidal thoughts to others. (15,16) According to a major psychological theory--the ecological-transactional model (15,17)--social behaviours are also affected by ecological context, such as (in hierarchical order) neighbourhood, community, school, peer and family groups. Multilevel modelling allows us to explore the importance of social context by dividing the total variation into individuals and groups to be assessed separately. Young (15) found that the contribution of school in relation to suicidal attempts and behaviours is low (< 1%), but nevertheless important given the severity of the outcome. School classroom context was also examined in a multilevel analysis, (16) which found small variation was attributed to school classes after accounting for individual-level risk factors, but suicidal ideation is significantly associated with school class composition with regard to student gender and parental education. Multilevel analysis is therefore considered in this study, including the grade within school and school-level random effects, to give an enriched picture of the complexity of suicidal ideation.

The suicide rates among neighbouring regions are often close and typically exhibit spatial dependency, since the neighbourhoods where children reside typically reflect the socio-economic status and cultural peer-groups of their parents, which in turn can influence the contact networks and mental health of children. (18) Therefore, it is also often of interest to identify high-risk regions when designing an effective prevention program with regard to suicidal ideation. However, few such studies have been conducted in Canadian literature, particularly for school children.

As such, the purpose of the current study is twofold: a) to identify the most relevant predictors for suicidal ideation in a multilevel analysis and b) to identify high-risk neighbourhoods for the prevalence of suicidal ideation among the elementary school children in Saskatoon Health Region, Saskatchewan.



Data for this study were collected during the third round of the Student Health Survey from elementary school students in grades 5-8 in Saskatoon Health Region in 2010-2011. Consent was obtained from schools, parents and children. Ethics approval was provided by the Behavioural Research Ethics Board at the University of Saskatchewan. Research assistants, from Saskatoon Health Region, administered the survey. Students completed their survey during class time, enclosed and sealed it in an envelope and returned it to the research assistant. (19) There were 12,391 students registered in grades 5-8 in participating schools and the overall response rate was 46.7% (n = 5783).


The outcome variable, suicidal ideation, was assessed using the following question: "In the past year (12 months), did you seriously consider suicide?" Potential risk factors included socio-demographic variables: gender (male vs. female), age (years) and ethnicity (Aboriginal vs. other), as well as psychological factors, including depression, anxiety levels and self-esteem. Depression was measured according to the 12-item shortened version of Centre for Epidemiological Studies Depression scale (CES-D); (20) students with scores of 0-11 were considered as having low depression, 12-20 moderate and [greater than or equal to] 21 high. Anxiety levels were measured using a 7-item scale: (19) students with scores of 0-7 were considered as having low anxiety levels, 8-14 moderate and [greater than or equal to] 15 high. Self-esteem was determined using a 5-item scale: (19) students with scores of 0-6 were considered as having low self-esteem, 7-13 moderate, and [greater than or equal to] 14 high. Quality of relationships with parents and friends was also evaluated as a potential risk factor in this study based on a set of questions, responses to which were categorized into poor, moderate and good relationship. (19) The questionnaire also includes reported experiences involving physical, verbal, social and electronic bullying (weekly, once or more vs. none).

The deprivation index reflecting the socio-economic inequalities in health at an area level was also measured based on the average income, education, employment levels, living arrangements, marital status, and proportion of single-parent families. It divides a population into five categories by quintiles. (19) Deprivation index scores were not available for the rural students; hence, all rural students were grouped into a single category in this analysis.

Multilevel analaysis

Multilevel logistic regression models with random intercepts were used to examine to what extent suicidal ideation varied among students clustered together within grades and schools. In this study, 34.9% of the participants were rural students and could not be assigned a neighbourhood, so we first considered adding neighbours as another hierarchical level in the multilevel analysis excluding the rural students and the resulting neighbourhood variation is close to zero. Therefore, to preserve sample size for gaining statistical power, we did not consider neighbourhood as a hierarchical level in the multilevel analysis.

In the first step, we built a model including only the random effect terms, to investigate variation in the prevalence of suicidal ideation at the grade and school levels before considering individual student attributes. The importance of each random effect was evaluated using variance partition coefficients (VPC), (21) which describe the percentage of variation in the data that is attributed to a particular organizational level.

To screen the covariates, we examined the univariable association between each risk factor and the outcome. Variables where the p-value was <0.2, based on the likelihood ratio test, were retained for consideration in building the final model. Choice of p < 0.2 as the threshold is recommended to avoid excluding important variables from the model. Manual backward selection was used to develop a main effects model, retaining only variables where p < 0.05. In the final step, all the covariates remaining in the final model were tested for significant interactions.

The association between main effects and the outcome in the final model were reported as adjusted odds ratios (AOR) with 95% confidence intervals (95% CI) and p-values. Multilevel analyses were carried out using maximum likelihood estimation in glmer from the lme4 package in the R Statistical Software (Foundation for Statistical Computing, Vienna, Austria).

Bayesian spatial analysis

To examine neighbourhood risk for suicidal ideation, we conducted a secondary data analysis based on the aggregated counts of suicidal ideation in over 62 neighbourhoods in Saskatoon. Rural students were not included in this analysis, as there was no location information available that was the equivalent of neighbourhood other than the previously considered school.

The number of cases of suicidal ideation from the sth neighbourhood is denoted as [y.sub.s], s = 1, ..., S, which is assumed to follow a Poisson distribution, i.e., [y.sub.s] ~ Poisson ([[mu].sub.s]), with mean [[mu].sub.s] = [n.sub.s][r.sub.s], where [n.sub.s] is the total number of school children from the sth neighbourhood in the study sample and rs represents the relative risk. A Poisson random effects model was used: log([[mu].sub.s]) = [[alpha].sub.0] + log([n.sub.s]) + [b.sub.s] + [h.sub.s], where [[alpha].sub.0] is the intercept, [b.sub.s] is the spatially correlated random effect term, which follows a conditional autoregressive prior distribution (22) and hs is the spatially uncorrelated random effect term that follows a normal distribution. To identify the neighbourhoods where school children are at a higher risk of suicidal ideation, posterior exceedance probabilities, P([r.sub.s] > 1), were calculated as the proportion of Markov chain Monte Carlo (MCMC) simulations for neighbourhoods that had a relative risk of suicidal ideation greater than 1.

The Bayesian computation was implemented using publicly available software (WinBUGs version 1.4). (23) Two chains with different initial values were constructed to assess convergence. To ensure the representative samples were drawn for posterior inference, the first 10,000 iterations were discarded as burn-in, and the next 10,000 iterations were used as samples. Convergence was checked by visual inspection of the iterative series using the Gelman-Rubin diagnostic plot. (23)


Of the 5,783 grade 5-8 students who completed the survey, 5,340 (92.3%) from 109 elementary schools responded to the question regarding suicide ideation; 340 (6.4%) of these students indicated they had considered suicide at least once in the previous 12 months.

In the null model including only the random intercepts for grade and school, the variation identified among grades within schools was 0.03 [+ or -] 0.18 and among schools was 0.24 [+ or -] 0.49. The VPC for grade was 0.8% and for school was 6.7%. In the univariate analysis, there was no significant difference in reported suicidal ideation between males and females or among students of different ages, or from rural and urban schools (Table 1). Almost 13% of the Aboriginal students reported suicidal ideation, compared to 5.5% of non-Aboriginal students. Children who reported higher depression, higher anxiety, lower self-esteem, poorer relationships with friends or parents, as well as those who were more frequently bullied and were from more deprived areas were also more likely to have suicidal thoughts in unconditional models.

In the final multivariable multilevel model, the variation among grades within school and among schools was almost completely accounted for by the individual-level covariates. There was almost no remaining variation among grades within schools (2.7e-10 [+ or -] 1.6e-5), and the variation among schools was also substantially reduced (0.017 [+ or -] 0.13). The VPC for grade was 0.0% and for school was 4.9%. Aboriginal status, depression, anxiety, self-esteem, parental relationship, verbal bullying and electronic bullying were associated with suicidal ideation in the final multivariable model (Table 2). There was no difference among the urban students residing in different deprivation quintiles or compared with the rural students (p = 0.73). We also tested the interactions for the variables remaining in the main effects models and whether gender modifies the effects of those covariates; none were significant and are not presented. Future studies with larger samples are warranted, so that we have enough statistical power to sort out the interaction among the variables.

After accounting for other risk factors in the final model (Table 2), Aboriginal students were more likely to report suicidal ideation than non-Aboriginal students (AOR=1.74). Students who suffered from a high level of depressed symptoms were more likely to report suicidal ideation than those with low depressed symptoms (AOR = 4.79). Likewise, the odds of suicidal ideation increased as the anxiety level increased from low to moderate (AOR=2.43) and low to high (AOR=3.36). Students who considered themselves to have an excellent relationship with their parents had a lower prevalence of suicidal ideation (AOR = 0.33). The odds of suicidal ideation were also lower for those reporting a moderate relationship with their parents, as compared to those with poor relationships with their parents (AOR = 0.46). Students who were frequently verbally or electronically bullied had higher odds of having suicidal thoughts, as compared to those who were less frequently verbally or electronically bullied. For example, students who reported being verbally or electronically bullied weekly had a significantly higher prevalence of suicidal ideation than those who had never been verbally or electronically bullied (verbal bullying: AOR=1.82; electronic bullying: AOR= 2.14).

Of the 5,340 school children who responded to the question of suicidal ideation, 3,506 (65.7%) urban school students provided their residential postal codes. Children who attended rural schools were not asked for their residential postal codes. The relative risks of suicidal ideation at the residential neighbourhood level, based on the Bayesian spatial model, were illustrated in Figures 1 and 2. The posterior exceedance probabilities show that high-risk neighbourhoods were primarily located on the west side of Saskatoon (Figure 1). The estimated posterior means of the relative risks shown in Figure 2 indicate that children from the neighbourhoods on the west side of Saskatoon are at higher risk of suicide ideation than those on the east. We also compared our model with the models including only either [b.sub.s] or [h.sub.s] term and the results indicated that the difference in the deviance information criterion (24) is negligible, so different covariance structure would not impact much on the model fit and the resulting estimates on the exceedance probability.


Results from our study support much of the existing work on suicide ideation, (6-10) but also extend the research in some important areas, which are detailed below. Our study affirmed the relationship between suicidal ideation and various psychosocial factors, such as depression, anxiety, self-esteem and parent-child relationships, after accounting for experiences with bullying. Our study also found that the association between being a victim of verbal or electronic bullying and suicidal ideation is significant. We have also identified that Aboriginal students were more likely to have suicidal thoughts, which demonstrates a need for culturally appropriate interventions to improve the mental health status of Aboriginal elementary school children.

The literature on gender effect on suicidal ideation in adolescence is complex and partly paradoxical. (25) While some studies showed either a higher rate either among boys (7) or among girls, (15,26) our study found gender difference is insignificant, which was also found in other studies. (8,27,28) Rhodes et al. (25) presented a comprehensive discussion on the reasons and timing of the gender effects in the prevalence and lethality of suicidal behaviours. The inconsistent findings might be partially explained by the shift in the interactive social network during adolescent development. Early adolescents may be influenced more by adults (parents, teachers), later adolescents more by their peers. (29) This may also help partially explain our null findings on friend relationship in the final model, but significant association between parental relationship and suicidal ideation, given our study sample focussing on early adolescents.

After adjusting for the individual-level risk factors, very little variation in suicidal ideation was attributable to grouping of students within grades or schools. To examine whether context variables at the grade within school and school level can explain the variation, we created variables summarizing the proportions of males, Aboriginal students, students reporting psychosocial problems, and students reporting different types of bullying experiences, for each grade within a school and for each school in the study sample, but none of those variables were significantly associated with suicidal ideation in the multivariable analysis, so the results are not presented.

Finally, this study investigated the geographic patterns of suicidal ideation among elementary school children. Although the neighbourhood-level analysis does not consider confounding by individual attributes, it is useful for initial targeting of programs to high-risk areas of the city that were not clearly identified by individual student attributes alone. Further research will need to consider the potential for geographic differences in the needs of rural students.


While this study had a relatively large sample size for school-based research, the study also has some limitations, including the cross-sectional nature of the survey. This limits potential inferences about causal relationships between suicidal ideation and some of the risk factors examined. Additionally, clustering within families is also worth serious consideration and such information should be collected in the student's mental health survey, as siblings from the same family typically have extensive and close contact with each other. As well, the response rate was low (46.7%), as the questionnaire was self-completed by the school children. The set of non-respondents may differ from the respondents. For example, students with mental health problems may be more likely to respond due to their interests in this topic. Alternatively, such students may be less motivated to participate because of psychological problems. To address the possibility of such biases, non-respondent adjustments (30) should be conducted in the future based on a survey using different recruitment strategy invoking greater incentives among randomly selected non-respondents. Also, in cases where children have missed reporting either intentionally or inadvertently on any of the questions asked, we have used the commonly used technique of listwise deletion, which deletes the cases containing missing data in the variables that are relevant to the analysis being carried out. This is done to avoid potential bias in our analysis. These limitations need to be taken into consideration when generalizing our results.


Our study is unique in expanding the research area on suicidal ideation in adolescence to the early adolescence period. The findings provide evidence that early adolescent peer aggression must be taken seriously. An integrated preventive intervention strategy, including parenting education programs, mental health services for youth with depression, anxiety and low self-esteem as well as bullying prevention programs, should increase the effectiveness of suicidal ideation prevention efforts. Geographical targeting could also be employed, which may be important for optimizing prevention strategies and enhancing treatment for suicidal ideation.


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Received: September 24, 2015

Accepted: December 20, 2015

Cindy Xin Feng, PhD, [1] Cheryl Waldner, PhD, [2] Jennifer Cushon, PhD, [3] Kimberly Davy, MPH, [4] Cory Neudorf, PhD [5]

Author Affiliations

[1.] School of Public Health, University of Saskatchewan, Saskatoon, SK

[2.] Large Animal Clinical Sciences and School of Public Health, University of Saskatchewan, Saskatoon, SK

[3.] Saskatoon Health Region, Saskatoon, SK

[4.] School of Public Health, University of Saskatchewan, Saskatoon, SK

[5.] Chief Medical Health Officer, Saskatoon Health Region, Community Health and Epidemiology, University of Saskatchewan, Saskatoon, SK

Correspondence: Cindy Xin Feng, School of Public Health, University of Saskatchewan, Saskatoon, SK S7N 5E5, Tel: 306-966-1948, E-mail: cindy.feng@

Acknowledgements: We thank the Saskatoon Public School Board, the Greater Saskatoon Catholic School Board, the Saskatoon Tribal Council and the Saskatoon Health Region for supporting this research. We also acknowledge the Canadian Institutes of Health Research as the funding source for the original survey.

Conflict of Interest: None to declare.

Table 1.
Descriptive statistics for variables used in model building computed
from the univariable analysis in grade 5 to 8 school children
accounting for clustering within grade and school

Characteristic                        Total (%)    Suicidal

                                                    Yes (%)


Gender              Male             2523 (47.7)   144 (43.1)
(n = 5291)          Female           2768 (52.3)   190 (56.9)

Age, years          <11               971 (18.5)    60 (18.0)
(n = 5257)          11               1324 (25.2)    72 (21.6)
                    12               1344 (25.6)    74 (22.2)
                    13               1203 (22.9)    88 (26.4)
                    >13               415 (7.9)     39 (11.7)
Ethnicity           Aboriginal        537 (10.5)    70 (21.7)
(n = 5109)          Non-Aboriginal   4572 (89.5)   253 (78.3)

Type of school      Rural            1355 (25.6)    85 (25.2)
(n = 5299)          Urban            3944 (74.4)   252 (74.8)

Deprivation         1 (most          1155 (24.1)    54 (18.1)
index                 affluent)
(n = 4793)          2                 810 (16.9)    37 (12.4)
                    3                 538 (11.2)    40 (13.4)
                    4                 499 (10.4)    42 (14.1)
                    5 (least          436 (9.1)     40 (13.4)
                    Rural            1355 (28.3)    85 (28.5)

Mental health
Anxiety             Low              1963 (41.0)    29 (9.8)
(n = 4784)          Moderate         1712 (35.8)    73 (24.6)
                    High             1109 (23.2)   195 (65.7)

Self-esteem         Low              1103 (21.2)   193 (59.8)
(n = 5192)          Moderate         3059 (58.9)   103 (31.9)
                    High             1030 (19.8)    27 (8.4)

Depression          Low              4039 (83.8)   124 (39.6)
(n = 4821)          Moderate          662 (13.7)   132 (42.2)
                    High              120 (2.5)     57 (18.2)

Social relation

Parent              Poor             1083 (23.3)   192 (63.6)
relationship        Moderate         2567 (55.3)    94 (31.1)
(n = 4642)          Excellent         992 (21.4)    16 (5.3)

Friend              Few              1051 (25.2)   151 (60.2)
relationship        Some             1685 (40.3)    51 (20.3)
(n = 4176)          Many             1440 (34.5)    49 (19.5)


Physical            Never            4102 (78.6)   178 (53.6)
(n = 5216)          Once or twice     945 (18.1)   112 (33.7)
                    Weekly            169 (3.2)     42 (12.7)

Verbal              Never            3111 (59.8)    99 (30.4)
(n = 5202)          Once or twice    1563 (30.1)   119 (36.5)
                    Weekly            528 (10.1)   108 (33.1)

Social              Never            3710 (71.4)   134 (41.5)
(n = 5193)          Once or twice    1109 (21.4)   103 (31.9)
                    Weekly            374 (7.2)     86 (26.6)

Electronic          Never            4664 (90.0)   229 (70.9)
(n = 5184)          Once or twice     408 (7.9)     61 (18.9)
                    Weekly            112 (2.2)     33 (10.2)

Characteristic                        Suicidal

                                       No (%)      p-value


Gender              Male             2379 (48.0)    0.083
(n = 5291)          Female           2578 (52.0)

Age, years          <11               911 (18.5)    0.057
(n = 5257)          11               1252 (25.4)
                    12               1270 (25.8)
                    13               1115 (22.6)
                    >13               376 (7.6)
Ethnicity           Aboriginal        467 (9.8)    <0.001
(n = 5109)          Non-Aboriginal   4319 (90.2)

Type of school      Rural            1270 (25.6)    0.65
(n = 5299)          Urban            3692 (74.4)

Deprivation         1 (most          1101 (24.5)    0.006
index                 affluent)
(n = 4793)          2                 773 (17.2)
                    3                 498 (11.1)
                    4                 457 (10.2)
                    5 (least          396 (8.8)
                    Rural            1270 (28.3)

Mental health
Anxiety             Low              1934 (43.1)   <0.001
(n = 4784)          Moderate         1639 (36.5)
                    High              914 (20.4)

Self-esteem         Low               910 (18.7)   <0.001
(n = 5192)          Moderate         2956 (60.7)
                    High             1003 (20.6)

Depression          Low              3915 (86.8)   <0.001
(n = 4821)          Moderate          530 (11.8)
                    High               63 (1.4)

Social relation

Parent              Poor              891 (20.5)   <0.001
relationship        Moderate         2473 (57.0)
(n = 4642)          Excellent         976 (22.5)

Friend              Few               900 (22.9)   <0.001
relationship        Some             1634 (41.6)
(n = 4176)          Many             1391 (35.4)


Physical            Never            3924 (80.3)   <0.001
(n = 5216)          Once or twice     833 (17.1)
                    Weekly            127 (2.6)

Verbal              Never            3012 (61.8)   <0.001
(n = 5202)          Once or twice    1444 (29.6)
                    Weekly            420 (8.6)

Social              Never            3576 (73.4)   <0.001
(n = 5193)          Once or twice    1006 (20.7)
                    Weekly            288 (5.9)

Electronic          Never            4435 (91.2)   <0.001
(n = 5184)          Once or twice     347 (7.1)
                    Weekly             79 (1.6)

Table 2. Results of multivariable regression analysis assessing the
risk factors associated with suicidal ideation in grade 5 to 8 school
children (n = 3872) accounting for clustering within grade and school

Independent           AOR      95% CI     p-value

  Aboriginal          1.73   1.18-2.54    <0.001
  Low (reference)
  Moderate            2.27   1.55-3.34    <0.005
  High                4.79   2.66-8.62    <0.001
  Low (reference)
  Moderate            2.43   1.45-4.08    <0.001
  High                3.36   1.93-5.85    <0.001
Parent relationship
  Poor (reference)
  Moderate            0.46   0.33-0.65    <0.001
  Excellent           0.33   0.17-0.62    <0.001
  Low (reference)
  Moderate            0.48   0.34-0.68    <0.001
  High                0.73   0.41-1.31     0.29
Verbal bullying
  None (reference)
  Once or twice       1.46   1.03-2.08     0.034
  Weekly              1.82   1.18-2.79     0.006
Electronic bullying
  None (reference)
  Once or twice       1.38   0.92-2.06     0.12
  Weekly              2.14   1.12-4.07     0.02
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Author:Feng, Cindy Xin; Waldner, Cheryl; Cushon, Jennifer; Davy, Kimberly; Neudorf, Cory
Publication:Canadian Journal of Public Health
Article Type:Report
Geographic Code:1CANA
Date:Jan 1, 2016
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