U.S. Department of Justice

Office of Justice Programs

Office of Juvenile Justice and Delinquency Prevention 

December 2002

Access OJJDP publications online at ojjdp.ncjrs.org

J. Robert Flores, Administrator

and many of these risk factors suggest

opportunities for intervention.

The Bulletin includes background information, a brief theoretical discussion, study

methods and findings, conclusions, policy

implications, and suggestions for future

research.

Background

Statistical evidence suggests disproportionately high rates of violence by and

against juveniles. This evidence comes

both from surveys that ask about behaviors and victimization experiences and

from official records.

Surveys of self-reported behaviors of adolescents and young adults indicate high

rates of offending among these age groups

(Elliott et al., 1983; Lauritsen, Sampson,

and Laub, 1991). Similarly, surveys of victims’ perceptions of offender characteristics indicate that the most common age

group for offenders committing rape, robbery, and assault is youth ages 18–20, followed by juveniles ages 15–17 (Hindelang,

1981). Furthermore, Uniform Crime Report

data show that arrest rates for murder,

forcible rape, robbery, and aggravated

assault are higher for older teens than for

Violent Victimization as 

a Risk Factor for Violent

Offending Among Juveniles

Jennifer N. Shaffer and R. Barry Ruback

As a group, juveniles have high rates of violent victimization and violent offending, a

pattern suggesting that some juveniles are

both victims and perpetrators of violence.

To explore that hypothesis, this Bulletin

analyzes the relationships between violent

victimization and violent offending across

a 2-year period, using data for 5,003 juveniles who participated in the National Longitudinal Study of Adolescent Health. The

Bulletin looks at victimization and offending experiences in subgroups of juveniles

classified by age, gender, race, and level

of physical development. It also identifies

risk and protective factors for victimization and offending. Key conclusions and

policy implications include the following:

◆ Violent victimization is indeed a warning signal for future violent offending

among juveniles. Protecting juveniles

against violent victimization may, therefore, reduce overall levels of juvenile

violence. 

◆ Because some groups are at higher risk

than others for violent victimization,

policies and programs aimed at preventing victimization may be most effective

if they are focused on these groups.

◆ Violent victimization and violent offending share many of the same risk factors,

A Message From OJJDP

Compared with adults, juveniles are

disproportionately affected by high

rates of violence as both offenders

and victims. Understanding the relationship between victimization and

offending is therefore of critical

importance.

Examining data from the National

Longitudinal Study of Adolescent

Health, the authors of this Bulletin

found that victims of violence were

significantly more likely than nonvictims to become violent offenders.

They also found that violent victimization and violent offending share

many of the same risk factors, such

as previous violent victimization and

offending, drug and alcohol use, and

depression. These findings are particularly important because they suggest that interventions directed at

preventing victimization could also

reduce offending, and vice versa.

The analysis presented in this Bulletin provides evidence that peers and

adults can and do play important roles

in the lives of juveniles. Juveniles who

said that they had support from friends,

parents, teachers, and others were

less likely to commit a violent offense.

These findings underscore the need

for and value of mentoring, parenting,

and anger management programs

that provide opportunities for juveniles

to interact with caring adults. By identifying youth who are most at risk and

examining the links between victimization and offending, we can improve

our ability to intervene positively in

these juveniles’ lives.
2

victimization to the police (Finkelhor and

Ormrod, 1999).

Research findings are consistent with these

theoretical reasons for expecting that the

same individuals are often both victims

and offenders. Studies using British Crime

Survey data have found a strong positive

association between offending and personal victimization among adults (Hough and

Mayhew, 1983; Sampson and Lauritsen,

1990). Studies of juveniles in the United

States also show that the individuals most

likely to be victims of personal crime are

those who report the greatest involvement

in delinquent activities (Lauritsen, Sampson, and Laub, 1991). In addition, the

greater the variety of delinquent activities,

the greater the risk of victimization (e.g.,

Jensen and Brownfield, 1986; Esbensen

and Huizinga, 1991; Lauritsen, Sampson,

and Laub, 1991).

Data and Methods

Although earlier studies suggest that criminal victimization and criminal offending

are related, the nature of the relationship

is ambiguous. The present study investigates the nature of the relationship in a

sample of juveniles ages 11–17, addressing

three issues:

◆ How are violent victimization and violent offending related over time? Does

prior victimization predict subsequent

offending, does prior offending predict

subsequent victimization, or do they

both predict each other? In particular,

is victimization a significant risk factor

for subsequent offending?

◆ What individual-level factors might

explain the relationship between victimization and offending? Do the same

factors predict both violent victimization and violent offending?

◆ Does drug use affect the relationship

between victimization and offending?

The study focuses on violence among juveniles for three reasons. First, from a policy

standpoint, it makes sense to concentrate

on the most serious offenses, particularly

since less is known about the violent victimization of juveniles than about the 

violent victimization of adults. Second,

because many fewer juveniles engage in

violence than in property offending and in

minor deviant acts, it would be easier to

target interventions at this smaller group.

Third, the data source for the analyses

in this Bulletin included measures of nonviolent offending but not of nonviolent

victimization.

any other age group (Federal Bureau of

Investigation, 2000).

When asked about their victimization

experiences in the previous year, 18 percent of a large national sample of 8th, 10th,

and 12th grade students said they had

been injured by an attacker who did not

use a weapon, and 5 percent said they had

been injured by an attacker with a weapon

(Johnston, Bachman, and O’Malley, 2001).

Rates of serious violent victimization are

twice as high for juveniles ages 12–17 as

for adults age 18 or older, and rates of simple assault victimization are three times

higher (Snyder and Sickmund, 1999).

Theoretical Perspective

According to both lifestyle exposure theory

and routine activities theory (Hindelang,

Gottfredson, and Garofalo, 1978; Cohen

and Felson, 1979), individuals’ risk of

criminal victimization depends on their

exposure or proximity to offender populations, and exposure, in turn, depends on

individuals’ lifestyles and routine activities. Because individuals are most likely

to interact with those who are similar to

themselves, individuals’ victimization risk

is directly proportional to the number of

characteristics they share with offenders

(Hindelang, Gottfredson, and Garofalo,

1978). That is, offenders are more likely

than nonoffenders to become victims,

because their lifestyles frequently bring

them in contact with other offenders.

Offenders are also more likely than nonoffenders to use alcohol or illegal drugs,

which lowers their ability to protect themselves and their property, and to live in

neighborhoods characterized by high levels of population mobility, heterogeneity,

and social disadvantage (e.g., poverty and

unemployment), which increases their

exposure to other offenders (Sampson

and Lauritsen, 1994).

Offenders are also likely to be attractive

targets for crime because they can be victimized with little chance of legal consequences (Sparks, 1982). Offenders are

probably less likely than nonoffenders to

report victimization to the police because

they do not want to draw attention to their

own illegal behavior (e.g., starting the altercation in question or carrying illegal drugs)

and because, if they do file a report, the

police probably perceive them as less

credible than nonoffenders. Offenders’ reluctance to report their own victimization

might be especially true for violent juvenile offenders, because juveniles in general

are less likely than adults to report violent

Data Source

The findings reported in this Bulletin 

are based on statistical analyses of the

restricted-access contractual dataset from

the first two waves of the National Longitudinal Study of Adolescent Health (known

as the Add Health Study), which is a longitudinal study of a representative national

sample of juveniles in grades 7 through

12.1 The study used a clustered sampling

design based on a stratified sample of

80 high schools and 52 paired middle

schools.2 Students in these 132 schools

were asked to complete an in-school questionnaire. In addition, a subsample, stratified by grade and gender, was selected for

in-home interviews, which included information about family composition and

dynamics, substance use, criminal and

delinquent activities, and violent victimization. The in-home interviews, which

were conducted in 1995 (year 1) and again

in 1996 (year 2), are the basis for the analyses in this Bulletin.

The analyses reflect interview data for

5,003 juveniles: 2,402 males and 2,601

females; 2,768 non-Hispanic white juveniles and 2,235 minority juveniles;3 1,147

juveniles ages 11–14 and 3,856 ages 15–17

at the time of the second interview. The

analyses exclude respondents who did not

have complete data for all of the variables

included in the analyses, those whose second interview was conducted less than

11 months after their first interview,4 and

those who were age 18 or older at the

time of the second interview.5

Analytical Approach

First, the sample is described in terms of

the percentages who reported violent victimization, violent offending, and both victimization and offending, in year 1, year 2,

and both years; and the links between victimization and offending within each year

are summarized. Next, relationships between violent victimization and violent

offending over time are examined—i.e.,

between victimization in year 1 and victimization in year 2, offending in year 1 and

victimization in year 2, victimization in

year 1 and offending in year 2, and offending in year 1 and offending in year 2—for

the sample as a whole and for subgroups

based on demographic characteristics

(age, gender, and race) and level of physical development. Finally, through multivariate analyses, the effect of drug use on

these relationships is investigated, and

risk and protective factors associated with

victimization and offending are explored.6
3

Findings

Incidence

As indicated in table 1, the percentages of

offenders and victims were high in years 1

and 2. Forty percent of juveniles reported

violent offending in year 1, 23 percent in

year 2, and 17 percent in both years. Nineteen percent reported violent victimization

in year 1, 15 percent in year 2, and 9 percent in both years. Fifteen percent of juveniles reported both committing and being

the victim of a violent crime in year 1, 10

percent in year 2, and 6 percent in both

years. Generally, the percentages of juveniles reporting offending and victimization

were greater in year 1 than in year 2. This

decline is likely related to “telescoping,” 

or the tendency of survey respondents to

report events that occurred outside the

time period about which they were asked

(in this study, prior to year 1).8

As shown in table 2, there was a strong

link between violent offending and violent

victimization within each year. Within year

1, juveniles who offended were 5.3 times

more likely than nonoffenders to be victimized (37 percent versus 7 percent), and

those who were victimized were 2.4 times

more likely than nonvictims to offend (78

percent versus 32 percent). Within year 2,

juveniles who offended were 6 times more

likely than nonoffenders to be victimized

(42 percent versus 7 percent), and those

who were victimized were 4 times more

likely than nonvictims to offend (66 percent

versus 16 percent). It should be kept in

mind that, although the Add Health Study

data indicate a close temporal proximity

of offending and victimization, temporal

ordering of events within a year—i.e.,

whether a particular youth first was victimized and then offended, or vice versa—

cannot be determined from the data.

Measures

The measures of offending and victimization used in the analyses were dichotomous measures based on juveniles’ yes/

no responses to multiple items.7 Two sets

of measures were used, reflecting the two

waves of data (i.e., years 1 and 2). The

measures of violent offending included

five items reflecting serious physical

offenses against other persons:

◆ Got into a serious physical fight.

◆ Hurt someone badly enough to need

bandages or care from a doctor or nurse.

◆ Used or threatened to use a weapon

to get something from someone.

◆ Shot or stabbed someone.

◆ Pulled a knife or gun on someone.

The measures of violent victimization

included four items reflecting serious

physical violence:

◆ Someone pulled a knife or gun on you.

◆ You were shot.

◆ You were cut or stabbed.

◆ You were jumped.

Juveniles were categorized as offenders if

they reported committing any of the listed

offenses and as nonoffenders if they reported not committing any of these offenses.

Juveniles were similarly categorized as

victims or nonvictims, based on whether

they reported having any of the listed acts

committed against them.

Juveniles were also categorized on the

basis of their reports of using any one 

of the following drugs:

◆ Marijuana.

◆ Cocaine.

◆ Inhalants.

◆ Other drugs, including LSD, PCP, ecstasy,

ice (crystal methamphetamine), heroin,

mushrooms, speed (amphetamines), or

pills without a doctor’s prescription.

Juveniles were categorized into one of four

groups: nonusers (no reported use of any

drug at either of the two interviews), desisters (reported use at first interview but

not at the second interview), new users

(reported use at the second interview but

not the first), and consistent users (reported use at both interviews). Juveniles were

similarly categorized on the basis of

reported alcohol use.

Table 1: Incidence of Violent Offending and Violent Victimization

Percentage of Juveniles Reporting*

Violent Violent Both Offending 

Year Offending Victimization and Victimization

Year 1 40 19 15

Year 2 23 15 10

Both years 17 9 6

* Sample size = 5,003.

Table 2: Relationship Between Violent Offending and Violent Victimization

Within Years: Total Sample

Year 1

Status in Year 1 Violent Offending (%) Violent Victimization (%)

All (N=5,003) 40 19

Offender 100 37

Nonoffender 0 7

Victim 78 100

Nonvictim 32 0

Year 2

Status in Year 2 Violent Offending (%) Violent Victimization (%)

All (N=5,003) 23 15

Offender 100 42

Nonoffender 0 7

Victim 66 100

Nonvictim 16 0
4

Because of this limitation, the rest of the

analyses presented in this Bulletin will

focus on the relationships between violent

victimization and offending across years.

Relationships Among

Variables

The data in tables 3–7 indicate relationships

between violent offending and violent victimization across years. Table 3 shows these

relationships for the total sample. Tables

4–7 show the relationships by age group,

gender, race, and level of physical development. In the discussion that follows, all

references to “significant” differences in

respondents’ likelihood of offending or

victimization (i.e., differences between

percentages reported in the tables) refer

to differences that are statistically significant at the p < .05 level, based on standard

chi-square tests. Readers should use caution when comparing estimates not explicitly discussed in the text; what may appear

to be a large difference may not be a statistically significant difference.

Total sample. Table 3 shows that, in the

total sample of 5,003 juveniles, those who

committed a violent offense or were victims of violence in year 1 had a significantly

increased likelihood of offending or being

victimized in year 2. Juveniles who offended in year 1 were 4.4 times more likely than

nonoffenders to offend in year 2 (44 percent versus 10 percent) and 4.7 times more

likely to be victimized in year 2 (28 percent

versus 6 percent). Juveniles who were victimized in year 1 were 3 times more likely

than nonvictims to offend in year 2 (52 percent versus 17 percent) and 6 times more

likely to be victimized in year 2 (47 percent

versus 8 percent).

By age. Juveniles were divided into two

groups according to their age in year 2:

11–14 and 15–17. As shown in table 4, the

total percentage of juveniles who were victims of violence in year 2 was significantly

greater for the older group; however, there

was no significant difference between the

two age groups in the percentages who

committed a violent offense in year 2. For

both age groups, juveniles who offended in

year 1 were significantly more likely than

nonoffenders to be victimized in year 2,

and those who were victimized in year 1

were significantly more likely than nonvictims to offend in year 2. These findings are

consistent with the pattern for all juveniles.

By gender. As shown in table 5, males were

significantly more likely than females to

commit a violent offense in year 2 and to be

victims of violence in year 2. For both males

and females, juveniles who offended in year

1 were significantly more likely than nonoffenders to be victimized in year 2, and

those who were victimized in year 1 were

significantly more likely than nonvictims to

offend in year 2. Again, these findings are

consistent with the pattern for all juveniles.

By race. The data were analyzed separately for white and minority juveniles (see

endnote 3 for racial groups included in the

minority category). As indicated in table 6,

both the total percentage of juveniles who

committed a violent offense in year 2 and

the total percentage who were victims of

violence in year 2 were greater for the minority category. For both minorities and

Key Findings

◆ Juveniles who were victims of violence in year 1 were significantly

more likely than nonvictims to commit a violent offense in year 2 and

to be victims of violence in year 2.

◆ Juveniles who committed a violent

offense in year 1 were significantly

more likely than nonoffenders to

commit a violent offense in year 2

and to be victims of violence in

year 2.

◆ In general, these patterns were

true regardless of age, gender,

race, level of physical development, or drug use.

Table 3: Relationship Between Violent Offending and Violent Victimization

Across Years: Total Sample

Year 2

Status in Year 1 Violent Offending (%) Violent Victimization (%)

All (N=5,003) 23 15

Offender 44 28

Nonoffender 10 6

Victim 52 47

Nonvictim 17 8

Table 4: Relationship Between Violent Offending and Violent Victimization

Across Years, by Age Group

Year 2

Status in Year 1 Violent Offending (%) Violent Victimization (%)

Ages 11–14

All (n=1,147) 23 13

Offender 42 23

Nonoffender 12 6

Victim 56 37

Nonvictim 18 8

Ages 15–17

All (n=3,856) 22 16

Offender 45 30

Nonoffender 9 7

Victim 51 50

Nonvictim 16 7

Note: Because the analysis focuses on predicting outcomes for juveniles in year 2, the age measure

reflects age at year 2. Thus, juveniles in the 11–14 age group were ages 10–13 in year 1, and juveniles in the 15–17 age group were ages 14–16 in year 1.
5

whites, juveniles who offended in year 1

were significantly more likely than nonoffenders to be victimized in year 2 and to

offend in year 2, and juveniles who were

victimized in year 1 were significantly more

likely than nonvictims to offend in year 2

and to be victimized in year 2. Again, these

findings are consistent with the pattern for

all juveniles.

By level of physical development. The

data were also analyzed separately by

juveniles’ level of physical development.

Juveniles were categorized as “more

physically developed” or “less physically developed,” based on their responses

to the following questions at the second

interview:9

◆ For males:

❖ How much hair is under your arms?

❖ How thick is the hair on your face?

❖ How much lower is your voice than

when you were in grade school?

❖ How advanced is your physical

development compared to other

boys your age?

◆ For females:

❖ How much more developed are your

breasts than when you were in

grade school?

❖ How much more curvy is your body

compared to when you were in

grade school?

❖ How advanced is your physical

development compared to other

girls your age?

As shown in table 7, the total percentage of

juveniles who committed a violent offense

in year 2 and the total percentage who were

victims of violence in year 2 were significantly greater for more physically developed juveniles. For both groups, juveniles

who offended in year 1 were significantly

more likely than nonoffenders to be victimized in year 2, and those who were victimized in year 2 were significantly more likely

than nonvictims to offend in year 2. Again,

these findings are consistent with the pattern for all juveniles.

Effects of Drug Use

Drug use and its influence on the relationship between violent victimization and offending were also examined. In both years,

the percentage of juveniles reporting drug

use was significantly greater among juveniles ages 15–17 than juveniles ages 11–14

but was not significantly different for males

and females or for minorities and whites.

To determine the influence of drug use on

the relationship between victimization and

offending, multivariate analysis was performed within each of the four drug use

categories defined on page 3: nonusers

(n=3,270); desisters (n=481), new users

(n=455), and consistent users (n=797). In

general, drug use did not influence the

victimization-offending relationship: violent victimization increased the risk of 

violent offending and violent offending

increased the risk of violent victimization,

regardless of drug use.10

Table 5: Relationship Between Violent Offending and Violent Victimization

Across Years, by Gender

Year 2

Status in Year 1 Violent Offending (%) Violent Victimization (%)

Males

All (n=2,402) 30 22

Offender 48 32

Nonoffender 14 9

Victim 56 51

Nonvictim 23 11

Females

All (n=2,601) 15 19

Offender 38 20

Nonoffender 7 4

Victim 44 5

Nonvictim 12 9

Table 6: Relationship Between Violent Offending and Violent Victimization

Across Years, by Race

Year 2

Status in Year 1 Violent Offending (%) Violent Victimization (%)

Minority juveniles

All (n=2,235) 25 20

Offender 42 32

Nonoffender 13 12

Victim 50 53

Nonvictim 20 11

White juveniles

All (n=2,768) 21 12

Offender 45 25

Nonoffender 9 4

Victim 54 43

Nonvictim 16 6
6

Risk and Protective Factors

Multivariate analyses were also used to

identify risk and protective factors for violent offending and victimization (i.e., factors that independently predict offending

or victimization in year 2 after statistical

controls for other factors are introduced

into the model). Tables 8 and 9 present

the results of the analyses, and the sidebar on page 8 discusses the methodology

used in the analyses.

Violent offending. The results presented

in table 8 indicate that, even after other

factors related to violent offending were

controlled statistically, being a victim of a

violent crime in year 1 was still a significant risk factor for committing a violent

offense in year 2. Only violent offending in

year 1 had a greater influence. The analysis also revealed an important protective

factor against violent offending in year 2:

juveniles who reported greater support

from important people in their lives, such

as friends, parents, and teachers, were less

likely to commit a violent offense in year 2.

Violent victimization. The results presented in table 9 indicate that, when all other

risk factors were controlled statistically,

committing a violent offense in year 1 was

still a significant risk factor for being the

victim of a violent crime in year 2. Only the

effects of violent victimization in year 1,

being male, being a consistent drug user,

and being a new drug user had a greater

influence. Finally, violent victimization was

significantly less likely among white juveniles than among minority juveniles,11

among juveniles who resided in two-parent

households than among those with other

family structures, and among juveniles

who resided in households with higher

socioeconomic status than among those

with lower socioeconomic status.

Conclusions

The analyses suggest three major

conclusions:

Violent victimization is an important risk

factor for subsequent violent offending.

The percentage of year 1 victims who

committed a violent offense in year 2 (52

percent) was significantly higher than 

the percentage of year 1 nonvictims who

committed a violent offense in year 2 (17

percent). The figure on page 7 (which

reflects the percentages in table 3) illustrates this finding.

Table 7: Relationship Between Violent Offending and Violent Victimization

Across Years, by Level of Physical Development

Year 2

Status in Year 1 Violent Offending (%) Violent Victimization (%)

More physically 

developed juveniles

All (n=2,449) 25 17

Offender 50 32

Nonoffender 10 7

Victim 57 52

Nonvictim 19 8

Less physically 

developed juveniles

All (n=2,554) 20 13

Offender 38 25

Nonoffender 9 4

Victim 47 42

Nonvictim 15 7

Table 8: Factors Predicting Violent Offending in Year 2

Predictor* Logistic Coefficient† Odds Ratio‡

Violent offending in year 1 1.39 (.09) 4.01

Violent victimization in year 1 0.86 (.11) 2.36

Male 0.71 (.11) 2.03

Consistent drug user 0.62 (.16) 1.86

New alcohol user 0.59 (.15) 1.80

Consistent alcohol user 0.56 (.13) 1.75

New drug user 0.36 (.17) 1.43

More physically developed 0.30 (.10) 1.35

Depression 0.23 (.11) 1.26

Support from significant others –0.26 (.09) 0.77

Household socioeconomic status –0.19 (.06) 0.83

Note: See sidebar on page 8 for methodological notes.

* Only significant (p < .05) predictors are reported here. The sidebar on page 8 includes a complete

list of the variables analyzed.

† The logistic coefficient represents the effect of a given predictor variable (e.g., violent offending in

year 1) on the log odds of the outcome (i.e., violent offending in year 2). Positive numbers indicate 

risk factors; negative numbers indicate protective factors. Standard errors are in parentheses.

‡ The odds ratio indicates the proportional change in the odds of violent offending in year 2, per 

one-unit increase in the predictor variable. The greater the difference from one, the greater the 

effect of the variable on violent offending.
7

Repeat offending is more common than

repeat victimization. The relationship of

violent offending in year 1 to violent offending in year 2 was stronger than the

relationship of violent victimization in

year 1 to violent victimization in year 2.

Approximately twice as many juveniles

committed an offense in both years as

were victimized in both years.

Violent victimization and violent offending share many of the same risk factors.

Shared risk factors include previous violent

victimization and offending, use of drugs or

alcohol, being male, depression, and having a high level of physical development.

Policy Implications

The findings of this analysis have at least

four policy implications:

Some groups are at higher risk than 

others for violent victimization. The

percentage of juveniles who were victims

of violent crime in this sample was high:

26 percent were victimized at least once

during the 2-year study period and 9 percent were victimized at least twice. Significantly higher rates of violent victimization

were found among juveniles with certain

characteristics—those who used drugs

consistently or began to use drugs, those

who were depressed, members of racial

minority groups, and older juveniles who

committed violent offenses. These findings suggest that victimization prevention

programs may be most effective if they

are focused on these groups. Because of

the strong association between drug use

and victimization, drug use prevention

and treatment programs might be promising strategies for decreasing juveniles’ risk

of violent victimization.

Violent victimization is a warning signal

for future violent victimization. About

one-half of the juveniles who reported

being victims of violence during year 1

also reported being victimized during year

2. These repeat victims might be especially suitable for interventions to prevent

future victimization. Other research has

shown that crime victims are more likely

than nonvictims to experience depression,

anxiety, and physical health problems

(Kilpatrick et al., 1985). Studies have also

shown that the greater the severity of the

victimization (e.g., a higher level of violence), the more severe the symptoms

(Bard and Sangrey, 1985; Riggs, Rothbaum,

and Foa, 1995). The current study found

Table 9: Factors Predicting Violent Victimization in Year 2

Predictor* Logistic Coefficient† Odds Ratio‡

Violent victimization in year 1 1.74 (.13) 5.70

Male 0.91 (.13) 2.48

Consistent drug user 0.85 (.18) 2.34

New drug user 0.77 (.19) 2.16

Violent offending in year 1 0.69 (.12) 1.99

Depression 0.52 (.12) 1.68

Consistent alcohol user 0.47 (.16) 1.60

Easy access to gun in home 0.40 (.16) 1.49

More physically developed 0.29 (.13) 1.34

Time spent hanging out with friends 0.17 (.06) 1.19

White –0.53 (.14) 0.59

Two-parent household –0.43 (.13) 0.65

Household socioeconomic status –0.23 (.07) 0.79

Note: See sidebar on page 8 for methodological notes.

* Only significant (p < .05) predictors are reported here. The sidebar on page 8 includes a complete

list of the variables analyzed.

† The logistic coefficient represents the effect of a given predictor variable (e.g., violent victimization in

year 1) on the log odds of the outcome (i.e., violent victimization in year 2). Positive numbers indicate

risk factors; negative numbers indicate protective factors. Standard errors are in parentheses.

‡ The odds ratio indicates the proportional change in the odds of violent victimization in year 2, per

one-unit increase in the predictor variable. The greater the difference from one, the greater the effect

of the variable on violent victimization.

0

10

20

30

40

50

60

Violent offending in year 2 Violent victimization in year 2

No violent

victimization

Violent

victimization

No violent

offenses

Violent

offender

Status in Year 1

Percentage of Juveniles

Percentage of Juveniles Who Offended or Were Victimized in Year 2,

by Status in Year 1
8

that the higher the level of juveniles’ depression, the greater their likelihood of

becoming victims of violence. This finding

suggests that focusing counseling and

other victim services on juvenile victims of

violent crime—especially repeat victims—

may be particularly important.

Violent victimization is a warning signal

for future violent offending. The finding

that being a victim of a violent crime predicted violent offending suggests that victimization is itself a risk factor for offending or is correlated with some factor or

process that is a risk factor. This implication, in turn, suggests that protecting juveniles against violent victimization may

reduce overall levels of juvenile violence.

Because juveniles are probably more likely to admit victimization than offending,

interventions focused on victims might be

easier to accomplish than interventions

focused on offenders. The finding that

the effect of violent victimization on offending appears to be stronger within years

than across years (see tables 2 and 3)

suggests that interventions may be most

successful in preventing future offending

if they are applied relatively soon after

the victimization.

Many of the risk factors associated with

juvenile violence suggest opportunities

for intervention. A number of the risk

factors presented in tables 8 and 9 involve

the behavior of juveniles and people who

are important in their lives; as such, these

factors are appropriate points for intervention. Because the majority of risk factors predicted both violent offending and

violent victimization, it may be possible

for interventions to simultaneously reduce

juveniles’ risk of both.

Future Research

This study suggests several areas for

future research:

The links by which offending and victimization affect each other should be explored. The findings of this study suggest

both that offending increases juveniles’

risk of victimization and that victimization

increases juveniles’ risk of offending. Future research should examine links that

might explain these two processes. For

example, being victimized might increase

juveniles’ use of drugs, and drug use might

make them more vulnerable to victimization because they are less able to protect

themselves. Research should also focus

on the extent to which victimization affects

juveniles’ mental and physical health.

The role of delinquent peers should be

investigated. Because in most crimes the

victim and the offender know each other,

association with delinquent peers may

explain not only juveniles’ offending

(Hawkins et al., 2000) but also their victimization. Previous research suggests

that some of the relationship between

offending and victimization and between

victimization and offending is explained

by the delinquency of juveniles’ peers

(Lauritsen, Sampson, and Laub, 1991;

Fagan, Piper, and Cheng, 1987). However,

the effect of peers has not been isolated

from the effects of juveniles’ own prior

offending and victimization. A related finding of the present study—that time spent

in unstructured activity with peers (i.e,

“hanging out with friends”) was a significant risk factor for violent victimization—

offers some evidence to support victimization theories based on routine activities

and lifestyle exposure. Future research

should provide more rigorous tests of

measures of routine activities to explain

the relationship between offending and

victimization in juveniles.

The reciprocal nature of the relationship

between victimization and offending

needs clarification. The present study

found some evidence that the relationships

between victimization and offending in

juveniles may be more simultaneous than

the cross-year relationships that were the

focus of the study. Future research should

explore the possibility that violent victimization and offending may have stronger

short-term than long-term influences on

each other.

For Further Information

To obtain data files from the National Longitudinal Study of Adolescent Health, contact Jo Jones, Carolina Population Center,

123 West Franklin Street, Chapel Hill, NC

27516–3997 (e-mail jo_jones@unc.edu).

Methodology for Analyses of Risk and Protective Factors

The multivariate analyses of risk and protective factors used cross-lag logistic regression techniques. For each outcome variable at year 2, the statistical model

included a term controlling for the effect of that variable at year 1. For example, the

model predicting the log odds of being a violent offender in year 2 included a control for status as a violent offender in year 1. For reasons similar to those explained

in endnote 10, the results of multivariate analyses presented in tables 8 and 9 are

based on models that excluded all interaction terms for age, gender, and race.

The multivariate analyses of victimization and offending in year 2 included the following independent variables: time spent hanging out with friends; drug use; alcohol use; tobacco use; race; depression (a standardized, composite index reflecting

juveniles’ mean score on 14 psychosomatic symptoms and 5 emotional symptoms

commonly associated with depression); support from others (a standardized, composite index of 7 items reflecting juveniles’ perceptions of how much adults, friends,

and teachers care about them); age (in years); age squared; easy access to a firearm in the home; whether the juvenile lived in a home with two parental figures

during both years; and household socioeconomic status (a standardized mean of

parental occupational prestige and parental education). Variables that were not

significant predictors are excluded from tables 8 and 9.

The models predicting victimization in year 2 included controls for juveniles’ property offending and minor deviance and delinquency. This was done to ensure that

the observed effects of violent offending on violent victimization reflected only the

effect of violence and not the tendency of juveniles who commit violent crimes to

also commit property crimes and to be involved in other delinquent and deviant

activities. The measure of property offending was a dichotomous variable based

on six activities reflecting involvement in property offending. The measure of minor

deviance and delinquency was also a dichotomous variable and was based on five

activities reflecting involvement in minor crimes (e.g., disorderly conduct) and status offenses (e.g., running away from home).
9

Endnotes

1. The Add Health Study is being conducted by the Carolina Population Center at the

University of North Carolina at Chapel Hill

under a grant from the National Institute

of Child Health and Human Development.

Approval to use the data was granted by

the Carolina Population Center, the Population Research Institute at Pennsylvania

State University, and the Pennsylvania

State University Institutional Review Board.

2. In the Add Health Study, clusters were

sampled with unequal probability. Although

this method reduced the costs of data

collection, the design complicated the statistical analysis because the observations

were not independent and identically distributed. Correct analysis of the data requires the use of special survey software

packages capable of handling observations

that are not independent and not identically distributed (Chantala and Tabor, 1999).

3. The minority racial category (about 45

percent of the sample) includes the following groups: African Americans (22 percent of the sample); Asians (6 percent),

American Indians (2 percent), Hispanic

whites (7 percent), and other racial or 

ethnic groups (8 percent).

4. For a large group of respondents, the

second interview took place less than 12

months after the initial interview. Because

the majority of the measures used in the

analyses asked respondents about “the

last 12 months,” those whose second interview took place less than 11 months after

the initial interview were excluded from

the analyses.

5. Some households had more than one

child represented in the sample. To eliminate the bias that would otherwise result

from the fact that responses from children

within the same household were correlated, only the youngest child in each household was included in the analyses. If a

household had two children of the same

age, one was randomly selected for the

analyses.

6. All of the analyses and statistical tests

for this Bulletin were conducted using the

survey estimation procedures in Stata

Release 7, a publicly available statistical

package capable of handling complex survey designs such as that of the Add

Health Study.

7. The response alternatives for offending

and victimization were “never,” “once,”

and “more than once.” For the analyses

presented here, these responses were

recoded to “yes” (once or more than

once) or “no” (never). It is important to

keep in mind that most of the measures

discussed in this Bulletin necessarily rely

on the willingness and accuracy of the

juvenile respondents’ self-reports. Analyses of the National Crime Victimization

Survey (NCVS) indicate that juveniles

are less likely than adults to report violent victimization to the police, although

juveniles and adults are equally likely

to report theft offenses (Finkelhor and

Ormrod, 1999). In addition, the Add Health

Study interview did not include the special rapport-building and screener questions currently used in the NCVS to capture violent crimes against women. Finally,

the Add Health Study survey instrument

did not specifically ask juveniles about victimization in the home (e.g., child abuse)

or about property victimization.

8. In this study, telescoping could have occurred only for year 1, because the information for year 2 was bounded by the

interview for year 1. In the first interview,

even though respondents were asked about

events that occurred during the prior 12

months, they might have reported events

that occurred before that period. Examination of research with the NCVS data has

suggested that victimization rates were

higher for unbounded interviewees (those

who were not interviewed 6 months earlier) than for bounded interviewees (those

who were interviewed 6 months earlier)

(Murphy and Cowan, 1982).

9. The physical development criteria listed on page 5 were standardized, used 

to create separate scales for males and

females, and then recombined into a single scale. Juveniles who scored in the 50th

percentile or higher were coded as more

physically developed, and those who

scored below the 50th percentile were

coded as less physically developed.

10. The analysis of relationships between

violent offending and victimization for the

four categories of drug use also explored

variations by age, gender, and race. Saturated models, which included all possible

interactions between these three variables

and offending and victimization, were tested. The number of significant interactions

was smaller than would be expected to

occur by chance, and the few significant

interactions had no clear pattern within or

across the categories of drug use. Moreover, within the specific distribution cells

(e.g., female consistent drug users), the

sample sizes were quite small, resulting in

less stable estimates and lower statistical

power for detecting significant effects.

Thus, the results presented here are based

on models that excluded all interaction

terms.

11. In the analyses of risk and protective

factors for both offending and victimization, it is important to interpret findings

regarding juveniles’ race cautiously. The

analyses presented here did not include

controls for juveniles’ neighborhoods, and

it is possible that the observed effects for

race would be reduced, or even disappear,

if adequate controls for neighborhood

type were included in the model.

References

Bard, M., and Sangrey, D. 1986. The Crime

Victim’s Book, 2nd ed. New York, NY:

Bruner/Mazel Publishers.

Chantala, K., and Tabor, J. 1999. Strategies

To Perform a Design-Based Analysis Using

the Add Health Data. Chapel Hill, NC: Carolina Population Center, University of North

Carolina at Chapel Hill. Copies may be

viewed or printed at www.cpc.unc.edu/

projects/addhealth/strategies.html.

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activity approach. American Sociological

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10

Fagan, J., Piper, E.S., and Cheng, Y. 1987.

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Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention.

Hawkins, J.D., Herrenkohl, T.I., Farrington,

D.P., Brewer, D., Catalano, R.F., Harachi,

T.W., and Cothern, L. 2000. Predictors of

Youth Violence. Bulletin. Washington, DC:

U.S. Department of Justice, Office of Justice Programs, Office of Juvenile Justice

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Hindelang, M.J. 1981. Variations in sexrace-age-specific incidence rates of offending. American Sociological Review 46(4):

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Hindelang, M.J., Gottfredson, M.R., and

Garofalo, J. 1978. Victims of Personal Crime:

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Jensen, G.F., and Brownfield, D. 1986. Gender, lifestyles, and victimization: Beyond

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P.M. 2001. Monitoring the Future: Questionnaire Responses From the Nation’s High

School Seniors, 1998. Ann Arbor, MI: Institute for Social Research, University of

Michigan.

Kilpatrick, D., Best, C., Veronen, L., Amick,

A., Villeponteaux, L., and Ruff, G. 1985.

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Lauritsen, J.L., Sampson, R.J., and Laub,

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Murphy, L.R., and Cowan, C.D. 1982. Effects

of bounding on telescoping in the National

Crime Survey. In The National Crime Survey:

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Skogan, Washington, DC: U.S. Department

of Justice, Office of Justice Programs,

Bureau of Justice Statistics, pp. 83–89.

Riggs, D., Rothbaum, B., and Foa, F. 1995.

A prospective examination of symptoms

of posttraumatic stress disorder in victims

of nonsexual assault. Journal of Interpersonal Violence 10(4):201–214. 

Sampson, R.J., and Lauritsen, J.L. 1990.

Deviant lifestyles, proximity to crime, and

the offender-victim link in personal violence. Journal of Research in Crime and

Delinquency 27(2):110–139.

Sampson, R.J., and Lauritsen, J.L. 1994.

Violent victimization and offending:

Individual-, situational-, and communitylevel risk factors. In Understanding and

Preventing Violence, vol. 3, edited by A.J.

Reiss and J.A. Roth. Washington, DC:

National Academy Press, pp. 1–114.

Snyder, H.N., and Sickmund, M. 1999. Juvenile Offenders and Victims: 1999 National

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Printing Office.

Preparation of this Bulletin was funded by the

National Center for Juvenile Justice’s National

Juvenile Justice Data Analysis Project, which is

supported by cooperative agreement number

99–JN–FX–K002 with the Office of Juvenile

Justice and Delinquency Prevention, Office of

Justice Programs, U.S. Department of Justice.

The Office of Juvenile Justice and Delinquency

Prevention is a component of the Office of

Justice Programs, which also includes the

Bureau of Justice Assistance, the Bureau of

Justice Statistics, the National Institute of

Justice, and the Office for Victims of Crime.
11

Acknowledgments

Jennifer N. Shaffer is a doctoral candidate at the Pennsylvania State University and a predoctoral fellow at

the National Consortium on Violence

Research. R. Barry Ruback is Professor of Crime, Law, and Justice

and Sociology at the Pennsylvania

State University.

This research is based on data from

the Add Health project, a program

designed by J. Richard Udry (principal investigator) and Peter Bearman

and funded by grant P01–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 participation by the National Cancer Institute; the National Institute of Alcohol

Abuse and Alcoholism; the National

Institute of General Medical Sciences;

the National Institute of Mental Health;

the National Institute of Nursing Research; the Office of AIDS Research,

National Institutes of Health (NIH);

the Office of Behavior and Social

Science Research, NIH; the Office 

of the Director, NIH; the Office of

Research on Women’s Health, NIH;

the Office of Population Affairs, U.S.

Department of Health and Human

Services (HHS); the National Center

for Health Statistics, Centers for Disease Control and Prevention, HHS;

the Office of Minority Health, Centers for Disease Control and Prevention, HHS; the Office of Minority

Health, Office of the Assistant Secretary for Health, HHS; the Office of

the Assistant Secretary for Planning

and Evaluation, HHS; and the National Science Foundation.

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