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Neighborhood Characteristics, Peer Networks, and Adolescent Violence

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Abstract

Although ecological researchers consistently find high rates of crime and violence within socioeconomically disadvantaged neighborhoods, there is little consensus as to why this pattern exists. To address this question, we use data from the National Longitudinal Study of Adolescent Health (n=12,747) to examine three related research questions. Are neighborhood characteristics associated with adolescent violence net of compositional and selection effects? Are neighborhood characteristics associated with adolescents’ exposure to violent and prosocial peers? Does peer exposure mediate the neighborhood characteristics–violence association? Results indicate that across a wide range of neighborhoods, socioeconomic disadvantage is positively related to adolescent violence net of compositional and selection effects. Additionally, neighborhood disadvantage is associated with exposure to violent peers, and peer exposure mediates part of the neighborhood disadvantage–violence association. Joining structural and cultural explanations for violence, our findings suggest that neighborhood disadvantage influences adolescent violence indirectly by increasing opportunities for youth to become involved in violent peer networks.

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Notes

  1. Despite Shaw and McKay’s (1969) formulation of social disorganization theory as including both structural and cultural aspects, research in this tradition has largely neglected the role of cultural influences (Warner 2003). Warner (2003) attributes this to the lack of theoretical clarity in Shaw and McKay’s discussion of culture as well as the conflicting theoretical assumptions of cultural deviance and social control models pointed out by Kornhauser (1978; see also Bursik 1988, 1993).

  2. Other research on rural areas suggests that socio-economic disadvantage also has detrimental effects on youth living in non-metropolitan areas (for example, see Simons et al. 1996; Osgood and Chambers 2000).

  3. Note that a cultural approach to the study of violence does not necessarily assume that a single oppositional culture is in effect. Neighborhoods also may vary in the strength of conventional values and the ability of these values to support local efforts at maintaining informal social control over youth (see Warner 2003; Kornhauser 1978 for a discussion of this point).

  4. Indeed, a vast body of research suggests that having delinquent friends is one of the most consistent and strongest correlates of delinquency (Agnew 1991; Elliott et al. 1985; Elliott and Menard 1996; Warr 1993a, b, 1996, 2002).

  5. In addition, Simons et al. (1996) used a rather indirect measure of affiliation with deviant peers based on mothers’ perceptions of the extent to which their children’s friends were “a good influence” and the extent to which their children’s friends tended to “get into trouble.” In contrast, the current study is based on a nationally representative sample of adolescents and measures peer behaviors directly by asking peers themselves about their involvement in violent behavior.

    Other studies have explored mechanisms linking disadvantage to delinquency and adolescent violence, but they too have been limited to data collected in one, two, or only a handful of cities, and have not involved data collected at multiple levels of analysis (e.g., Peeples and Loeber 1994). These limitations have resulted in restricted variation in the neighborhood disadvantage measures used, which likely accounts for the inconsistent findings across these works.

  6. Of the 80 high schools comprising the sample, 17 were located in the northeast region of the U.S., 27 in the south, 19 in the midwest, and 17 in the west. Metropolitan status is represented by 24 high schools in urban areas, 42 in suburban areas, and 14 in rural areas of the United States.

  7. Prior research has tended to focus almost exclusively on urban or rural samples without considering the role of neighborhood characteristics across a wide range of neighborhoods. Supplementary analyses examined whether associations among variables were dependent on metropolitan status. These analyses revealed associations similar to those presented for the full sample indicating that findings are not contingent upon metropolitan status.

  8. Comparing the means for the variables included in the study across the two waves of data indicates that bias due to attrition is minimal.

  9. An additional advantage of these data is that they were gathered using laptop computers that queried respondents directly using pre-recorded questions. Respondents entered their answers directly into the laptop computers. This method was used to enhance honesty in reporting sensitive information (Bearman et al. 1997). In this way, interviewer and 3rd party (i.e., parental) effects on adolescent responses were minimized.

  10. As a validity check, we replicated all of our analyses using neighborhood characteristics measured at the block-group level. These analyses (available from the authors) yielded virtually identical results to those reported below, suggesting that the block-group and census tract captured similar neighborhood-level dynamics with respect to adolescent violence.

  11. Eight hundered and twenty-three cases were deleted due to missing data. Deleted cases were more likely to be non-white than those included in the study (44.6% vs. 54.3%) and were less likely to come from two-parent households (49.6% vs. 72%). Deleted cases also tended to engage in more violence during the follow-up period (14.7% vs. 10.9%). Due to these differences, results were replicated with missing values imputed. Because results using the full sample with imputed values did not differ from those for the subsample excluding cases with missing values, only the results for the subsample with complete data are presented.

  12. We also ran our analyses without percent black included in the disadvantage index. Results were virtually identical to those obtained including percent black. We include percent black in the index not because we believe that race reflects disadvantage per se, but rather because we believe that race picks up aspects of disadvantage that are not easily measured using census data, such as social isolation resulting from racial segregation (Massey and Denton 1993).

    In addition, because many of the items in this index were skewed across neighborhoods, we re-ran all of our analyses with a re-computed index derived from log-transformed versions of each item. The index based on the log-transformed items was correlated at 0.90 with the non-transformed index and yielded results identical to those produced using the non-transformed index. For the sake of simplicity, we present results using the non-transformed index.

  13. In supplementary analyses we explored one additional neighborhood characteristic: neighborhood informal social control. This measure is based on responses that parents gave to a question that asked them: “if you saw a neighbor’s child getting into trouble, would you tell your neighbor about it?” Responses ranged from 1=definitely would not, to 5=definitely would. Parents’ response to this question were aggregated up to the census tract level to generate a measure of neighborhood informal social control. Supplementary analyses indicated that this measure was unassociated with either peer networks or adolescent violence. This lack of support for neighborhood social control in our study is inconclusive since data aggregation necessary to create the measure likely introduced error and the measure only captures one dynamic of collective efficacy as described by Sampson et al. (1997).

  14. Recall that only a portion of the in-school sample was interviewed during the in-home surveys. Thus, many of the nominated friends did not have the opportunity to report on serious violence involvement.

  15. Family income was not included in our SES measure because of a high level of missing data on this item. However, results incorporating family income (based on a subsample of adolescents whose parents provided income data) revealed similar results to those found for the larger sample of adolescents.

  16. Respondents who were coded as 0 include those parents who said that this was not a reason for their living in their present neighborhood.

  17. Preliminary analyses indicated this curvilinear effect of age on violence but not on exposure to peer behaviors reported in Table 1.

  18. The lack of a significant association between residential instability and violence is consistent with recent research by Silver (2000) and Warner and Pierce (1993) who note that residential instability may no longer operate as a structural factor that increases violence in disorganized neighborhoods because such neighborhoods have become places of last resort where residents reside for long periods of time, not because they choose to, but because they are unable to relocate elsewhere.

  19. We conducted these supplementary analyses since an appropriate test of the difference between coefficients (for instance, comparing the disadvantage coefficient in model 1 vs. model 2) is not currently available for survey data (see Allison 1995). We believe that our supplementary path analyses and our moderate interpretation of the mediation results suggests that peer networks are playing an important if modest role in the disadvantage–violence association.

  20. Experimental research data are currently being gathered to address the role of neighborhood influences on adolescent outcomes. In particular, the “Moving To Opportunity” experiments sponsored by HUD are anticipated to better disentangle the causal pathways through which neighborhoods affect adolescent outcomes (see Katz et al. 2001 for further details).

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Authors and Affiliations

  1. Department of Sociology, The Ohio State University, 300 Bricker Hall, 190 N. Oval Mall, Columbus, OH, 43210, USA

    Dana L. Haynie

  2. The Pennsylvania State University, University Park, PA, 16802, USA

    Eric Silver

  3. University of Akron, Akron, OH, 44325, USA

    Brent Teasdale

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  1. Dana L. Haynie
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  2. Eric Silver
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Correspondence to Dana L. Haynie.

Additional information

Special thanks go to Eric P. Baumer, Paul Bellair, Chris Browning, Glenn Firebaugh, and Scott J. South for their helpful comments on an earlier draft of this work. This research uses data from Add Health, a program project designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris, and funded by a grant P01-HD31921 from the National Institute of Child Health and Human Development, with cooperative funding from 17 other agencies. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Persons interested in obtaining data files from Add Health should contact Add Health, Carolina Population Center, 123 W. Franklin Street, Chapel Hill, NC 27516-2524 (www.cpc.unc.edu/addhealth/contract.html).

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Haynie, D.L., Silver, E. & Teasdale, B. Neighborhood Characteristics, Peer Networks, and Adolescent Violence. J Quant Criminol 22, 147–169 (2006). https://doi.org/10.1007/s10940-006-9006-y

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