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Peter S. Bearman, PhD and James Moody, PhD

Peter S. Bearman is with the Sociology Department and the Institute for Social and Economic Research and Policy, Columbia University, New York, NY. James Moody is with the Department of Sociology, The Ohio State University, Columbus, Ohio.

Correspondence: Requests for reprints should be sent to Peter Bearman, PhD, Institute for Social and Economic Research and Policy, Suite 814, IAB, 420 W 118th St, Columbia University, New York, NY. (e-mail: psb17{at}columbia.edu).

	ABSTRACT

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Objectives. We investigated the relationship between friendships and suicidality among male and female adolescents.

Methods. We analyzed friendship data on 13 465 adolescents from the National Longitudinal Survey of Adolescent Health to explore the relationship between friendship and suicidal ideation and suicide attempts. We controlled for known factors associated with suicidality.

Results. Having had a friend who committed suicide increased the likelihood of suicidal ideation and attempts for both boys and girls. Socially isolated females were more likely to have suicidal thoughts, as were females whose friends were not friends with each other. Among adolescents thinking about suicide, suicide attempts appear largely stochastic, with few consistent risk factors between boys and girls.

Conclusions. The friendship environment affects suicidality for both boys and girls. Female adolescents’ suicidal thoughts are significantly increased by social isolation and friendship patterns in which friends were not friends with each other.

	INTRODUCTION

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Although suicide rates for most subpopulations tend to be stable over time, the suicide rate among adolescents has risen dramatically in recent years. Suicide is now the third leading cause of death among adolescents and young adults aged 15 to 24 years.¹ Although only 1 in 200 suicide attempts results in death, more than one third of all suicide attempts result in injuries serious enough to require professional treatment. Four percent of American adolescents reported at least 1 attempted suicide in the past year, and 13% of adolescents had seriously considered suicide at least once in the past year.² The broader impact of suicide on adolescents is substantial. Twenty percent of adolescents reported knowing a friend who had attempted suicide in the past year, and 60% reported knowing a teenager who had ever attempted suicide.^2,3 Because of this prevalence, it is critical that we understand the determinants of adolescent suicidality for effective identification of adolescents at risk.

Many of the basic risk factors for adolescent suicidality are well known; among these, the most important are depression,^2,4–6 exposure to suicide or suicide attempts by family or friends,^7,8 substance or alcohol abuse,⁹ and having guns in the home.^2,10,11 Furthermore, in light of the differential rates of suicidal ideation and suicide attempts for adolescent males and females, some studies have suggested different etiologies for girls and boys.^6,9,12–14 However, most of the previous studies of adolescent suicide have relied on small samples of psychiatric inpatients,^4,15 case–control designs,^16,17 or autopsy studies of completed suicides. Few longitudinal population-based studies have examined risk factors from multiple domains.

We used data from a nationally representative sample of adolescents in the United States and examined the relative importance of various risk factors associated with both suicidal ideation and suicide attempts. In addition to measuring previously identified risk factors, we assessed the potential role that friendship patterns play in shaping adolescent suicidality. Because our sample was large, we were able to compare the patterns of risks for boys and girls separately and to model the risks of both suicidal thoughts and suicide attempts.

Adolescent well-being is largely the product of interactions among the multiple contexts in which adolescents are embedded.² Central contexts for adolescents include family, school, friendships, romantic relationships, peer groups, and larger social networks. The National Longitudinal Study of Adolescent Health (Add Health) provides unique data on adolescents’ relationships with their friends, in that it is the only national level data set to provide information on network structure. These data allow for measurement of adolescent social network position, the quality of adolescents’ social relations with peers, and the structural position adolescents occupy in the adolescent social world. Bearman¹⁸ suggested that adolescent suicidality may be a product of network positions characterized by either relative isolation or structural imbalance (Moody J, unpublished data, 1999), and a growing body of research links social isolation to suicide.^18,19 Researchers have known for some time that isolation from peers leads to lower estimations of self-worth and self-confidence.^22,23

We examined 2 individual-level network factors. First, isolated adolescents have few or no ties to the remainder of the school. Students in such positions may internalize isolation as low self-worth and may be more likely to consider suicide. This hypothesis follows directly from Bearman’s extension of Durkheim^18,24 and previous evidence concerning sense of self.²² Second, cultural pressures for social balance,²⁵ particularly among youths,^26,27 suggest that one’s friends should be friends with each other. Adolescents whose friends are not friends with each other are subject to competing normative pressures that lower effective normative regulation and increase suicidal ideation.²² For the school as a whole, communities with many relations provide stronger moral integration and greater opportunities for monitoring, which likely results in lower suicidal ideation and suicide attempts, respectively.

	METHODS

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Data were drawn from Add Health, a longitudinal study of American adolescents in grades 7 through 12. All students who attended a nationally representative sample of middle schools and high schools completed in-school questionnaires during the fall of 1994 and the spring of 1995 (n = 90 118). The in-school questionnaire measured the social and demographic characteristics, parental background, household structure, risk behaviors, visions of the future, self-esteem, health status, friendships, extracurricular activities, and consequences of health risk behaviors of respondents.

The primary sampling frame for Add Health was derived from information provided by Quality Education Data Inc (Denver, Colorado). From this frame, Add Health selected a stratified sample of 80 high schools with probability proportional to size. For each high school, Add Health identified and recruited one of its feeder schools (typically a middle school) with probability proportional to its student contribution to the high school, yielding one school pair for each of 80 different communities. Schools varied in size from < 100 students to > 3000 students. The Add Health sample includes private, religious, and public schools located in urban, suburban, and rural areas. Overall, 79% of the schools that were contacted agreed to participate in the study. Each in-school instrument administration occurred on a single day within one 45–60 minute class period. Students not attending school on the day of administration did not complete the in-school instrument. Detailed design specifications are available at: http://www.cpc.unc.edu/addhealth/focus.html.

Approximately 1 year after the in-school survey, Add Health officials interviewed 20 745 adolescents in their homes. Data collected during the in-home phase of Add Health provided measurement of sensitive health risk behaviors, such as drug and alcohol use, sexual behavior, and criminal activities, in addition to detailed measurement of health status, health care utilization, peer networks, decisionmaking, family dynamics, aspirations, and attitudes. The adolescent in-home interview was conducted with automated computer-assisted interviewing (ACASI) technology for all sensitive health status and health risk behavior questions. Adolescents listened to questions through earphones and entered their responses directly into a laptop computer, thereby minimizing interviewer or parental effects on their responses. Add Health was one of the first national surveys to use ACASI technology with an adolescent population.²⁸ No paper questionnaires were used during the in-home adolescent interviews.

The data for our analyses were drawn from both the in-school surveys and the in-home adolescent interviews. Of the 20 745 students who completed an in-home interview, sample weights required for national estimates were available for 18 924; 5459 adolescents did not complete the in-school interview, were not on the school network roster, or attended schools for which friendship data were not included. The resultant sample of 13 465 adolescents was used in all of our analyses. We used multiple imputation^29,30 to correct for missing values on individual questionnaire items.

Models
We used logistic regression to model the determinants of adolescent suicidal ideation and suicide attempts. We modeled suicidality separately for boys and girls, thereby capturing gender differences in the pattern of covariates. Each model regressed suicidal thoughts or suicide attempts for adolescent social-demographic characteristics, characteristics of the adolescents’ school and community, adolescent religiosity, measures of family and household characteristics (including distance from parents, household structure, experience with suicide in the family, and parental supervision), adolescent friendships and experience with friends’ suicide attempts, and adolescent personal characteristics.

Many of the risk factors, including network position, troublesome behavior, self-esteem, and depression, were measured 1 year prior to our measurements of suicidality. Hence, problems associated with the endogeneity of these risk factors were lessened. Because Add Health used a stratified clustered sample design, we adjusted for potential design effects with the Survey Logistic Regression procedure in Stata (Stata Corp, College Station, Tex), which corrected for school clustering and strata based on grade range, school size, ethnic mix, region, and urbanization.

Variables
Table 1 shows the definition, mean, SD, and range for all variables used in our analyses.

Independent Variables
Demographics. Demographic controls included age, binary indicators of race/ethnicity (White was the omitted category), and parental socioeconomic status.

School and community. We distinguished between junior high school and senior high school, anticipating lower rates of suicidality in junior high schools. Measured for the school as a whole, the relative density of the school friendship network captured the extent to which the school provided a focal point for adolescent relationships. In schools with low density, the effect of isolation in the school community and the effect of attitudes and behaviors of other adolescents in the community are likely to be lower than in schools where the relational network linking adolescents is more dense. For individuals, attachment to school captured the extent to which an adolescent reported feeling a member of the school community. Attachment—a critical component of school climate (Moody J, unpublished data, 1999) —was hypothesized to be negatively associated with suicidality. Additionally, we controlled for community type (suburban is the omitted category).

Religion. We included a binary indicator of whether the adolescent attended religious services at least once a week, because previous studies have suggested that religiosity is negatively related to suicide ideation and attempts.³¹

Family and household. Parental distance captured the extent to which parents were involved in their adolescent child’s life. High values indicate greater distance and fewer shared activities. Social closure measured the extent to which parents have met the friends and the parents of their adolescents’ friends. Higher values indicate greater parental connection with the adolescent’s social world. We compared the effects of stepfamilies and single-parent families on suicidality (2 biological parents [60%] is the omitted category). We also assessed the impact of guns in the household and of previous suicides in the family, both of which have previously been identified as significant correlates of adolescent suicidality.

Relationships. In addition to self-report of having a friend who has attempted suicide in the past year, we included 2 individual-level measures of social network position that provide insight into the relational world of adolescents: social isolation and network intransitivity.

As part of the in-school survey, each student was asked to name his or her 5 best female and 5 best male friends. Students could name friends from both inside and outside the school, although only in-school names could be matched to one another. We used these nominations to construct social network variables that captured the pattern and the structure of networks at multiple levels of observation, including the composition of individual networks, student membership in peer groups, and student position and popularity in the school.³²

Approximately 16% of the adolescents had limited social relations. Social isolation refers to those adolescents who had no friends to name, received no friendship nominations from others, or named as a friend a person who had no other friends. This variable captured the extent to which individual social relations were absent or were severely limited. Social isolation and school density correlated at -0.14.

Network intransitivity measured the structure of the extended social networks in which adolescents were embedded. Consider 3 adolescents: if i names j as a friend, and j names k as a friend, then i and k are 2 friendship steps apart. If i also names k as a friend, the resultant triad (i, j, k) is transitive. If i does not nominate k, despite j’s friendship with i and k, then the triad is intransitive. Transitive relations reflect closed, dense friendship groups, in which an individual’s friends are friends with one another. Intransitivity indicates dissonant relations, where an individual’s friendship circle spans multiple disconnected members. The intransitivity index measured the proportion of an individual’s friends’ friends who were not also the individual’s friends. Intransitivity and school density correlated at 0.19.

Personal characteristics. Depression, self-esteem, frequency of drunkenness, and grade point average in school were drawn from the in-school survey that was administered 1 year before the in-home survey. Sexual experience, homosexual attraction, experience of forced sexual relations (for females only), and body mass index were drawn from the in-home interview. Sexual experience, homosexual attraction, and forced sexual experience items were reported during the ACASI section of the survey.

	RESULTS

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To assess the relative impact of social factors on the suicide risk of adolescent males and females, we estimated all our models separately for each gender. This method is equivalent to running a global interaction with gender in a pooled model.

Suicidal Thoughts
Table 2 shows the odds ratios and 95% confidence intervals for models that regressed suicidal ideation on the full set of explanatory variables. The overall model fits were quite good (F = 17.08 for males, F = 16.28 for females; P < .0001 for both males and females). Close examination of the odds ratios reveals that although some general similarities exist in the pattern of risk factors by gender, striking differences are also evident.

In addition to revealing these general risk factors, the models of suicidal ideation showed marked differences by gender. Specifically, although we found no age effect for boys, younger girls were more likely than older girls to think about suicide (OR = 0.89). Beyond the age effect, however, we found important gender differences in the effect of social network and relational variables. For girls, being socially isolated from peers (OR = 2.01) or having intransitive friendships (OR = 2.19) substantially increased the odds of thinking about suicide. Additionally, being in a school with dense social networks lowered the risk of suicidal ideation for girls (OR = 0.333). Social network effects for girls overwhelmed other variables in the model and appeared to play an unusually significant role in adolescent female suicidality. These variables did not have a significant impact on the odds of suicidal ideation among boys.

Additionally, for girls, having experienced forced sexual relations (OR = 1.87), having gotten into more fights in the past year (OR = 1.14), and having a higher body mass index (OR = 1.03) all increased the odds of suicidal thoughts. None of these factors increased the likelihood of thinking about suicide for boys. In general, differences in model coefficients (as indicated by nonoverlapping confidence intervals) suggest a different suicidal ideation process for boys and girls.

Suicide Attempts
Table 3 shows the additional impact of selected variables on the likelihood of attempting suicide among those adolescents who reported having suicidal thoughts in the past year. As for suicidal thoughts, separate models were estimated for adolescent males and females. Both models suggest that it is relatively difficult to identify factors that distinguish adolescents who think about suicide from those who attempt it. Nevertheless, some significant differences between boys and girls in the patterning of risk factors remain.

When we limited the analysis to the population of adolescents who had suicidal thoughts, there were few identifiable risk factors that significantly increased the likelihood of a suicide attempt. For both boys and girls, having a friend who had attempted suicide continued to have an impact. For girls, self-esteem still played a significant role, as did frequent drunkenness. Characteristics of the school social network exerted powerful effects on boys. Adolescent males who had contemplated suicide and who attended schools in which the friendship network was dense and interlocked were much less likely to attempt suicide than were comparable boys who attended socially disconnected schools.

	CONCLUSIONS

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Previous research on adolescent suicidality has identified many of the risk factors associated with suicidal ideation and suicide attempts, yet only a few of these studies can generalize on the basis of a nationally representative sample of adolescents. None had access to the detailed social network and friendship data available in Add Health for a sufficient number of respondents to allow for robust measurement of the determinants of attempted suicide among those experiencing suicidal ideation.

Our findings revealed significant social network effects on suicidal ideation for adolescent females, after we controlled for previously identified correlates of suicidal ideation. Adolescent females who are isolated from the adolescent community or whose social relationships are intransitive and likely dissonant¹⁸ are at greater risk for suicidal thoughts than are girls who are embedded in cohesive friendship groups. Health care providers can assess this risk for girls through simple screens that allow adolescents to describe the relational world in which they are embedded. Adolescent males are more impervious to social context than are adolescent females.

The transition from ideation to action appears largely stochastic; health providers, parents, and teachers gain little predictive power from observations of relatively stable personal and contextual factors. This inability to predict suicide likely stems from the strongly opportunistic nature of suicide among adolescents, because feelings about suicide require a unique constellation of opportunity factors to be realized. For adolescent females, the social network variables that shaped suicidal ideation fail to predict suicide attempts. For adolescent males who had contemplated suicide, those who attended schools with few social ties were at increased risk relative to those attending schools with tightly knit friendship networks, perhaps because of increased peer-monitoring capacity in schools with dense social relationships. For both boys and girls, knowing a friend (but not a family member) who had attempted suicide was a significant predictor of moving from thought to action. Also, for both boys and girls, having a gun in the household increased ideation, perhaps because an available weapon may function as a tool to extend self-destructive thoughts. Possibly, males’ well-established general preference for lethal means of suicide increases the odds of suicide attempts by males if a gun is available in the house.

Our inability to identify a clear and consistent set of predictor variables that can distinguish between adolescents who consider suicide and those who attempt suicide has specific policy implications. If the transition from thought to action is stochastic and insensitive to structural or personal characteristics, health care providers, parents, and teachers need to rapidly respond to all reports of suicidal ideation, because a false positive is preferable to a false negative. For girls, the most effective interventions are those that transform the structure of their friendships with other adolescents. Changing schools, joining clubs and new extracurricular activities, and participating in more activities with parents are interventions that are likely to have a major effect.

Evidence of a substantial social-network effect on adolescent girls’ suicidal ideation suggests specific indicators for heightened suicidality that health providers can watch for and respond to with appropriate interventions. The determinants of suicidality are different for boys and girls, that female suicidality is strongly shaped by the relational networks in which adolescent girls are embedded, and that some of the correlates of suicide attempts identified in the literature as important are of less significance than previously thought. Physician interventions directed toward identifying adolescents at heightened risk should focus on adolescents isolated from, or in a dissonant relationship to, the larger peer community surrounding them.

	Acknowledgments

 
Data for this paper were drawn from the National Longitudinal Study of Adolescent Health (Add Health), a project designed by J. Richard Udry and Peter Bearman and funded by grant HD31921 from the National Institute of Child Health and Human Development to the Carolina Population Center, University of North Carolina at Chapel Hill, with cooperative funding from 17 other agencies. Persons interested in obtaining data files from Add Health should contact Add Health, Carolina Population Center, 123 W. Franklin St, Chapel Hill, NC 27516-2524 (www.cpc.unc.edu/addhealth/contract.html).

The authors thank Chris Bachrach, Katherine Stovel, and J. Richard Udry for their helpful comments on previous drafts.

Human Participant Protection
No protocol approval was needed for this study.

	Footnotes

 
Contributors
Both authors contributed equally to this article.

Peer Reviewed

Accepted for publication September 6, 2002.

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This Article Abstract Full Text (PDF) Submit a response Purchase Article View Shopping Cart Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (35) Citing Articles via Google Scholar Google Scholar Articles by Bearman, P. S. Articles by Moody, J. Search for Related Content PubMed PubMed Citation Articles by Bearman, P. S. Articles by Moody, J. Related Collections Family Health Adolescent Health Mental Health Prevention Socioeconomic Factors