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* Department of General Pediatrics and Adolescent Medicine, Children’s National Medical Center, Washington, DC
Children’s Research Institute, Washington, DC
George Washington University School of Medicine, Washington, DC
|| Department of Emergency Medicine, Children’s National Medical Center, Washington, DC
¶ National Institutes of Child Health and Human Development, Bethesda, MD
# Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
** Department of Trauma Surgery, MedSTAR, Washington, DC
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ABSTRACT |
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 TOP ABSTRACT METHODSRESULTSDISCUSSIONREFERENCES |
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Objective. 1) To assess risk and protective factors for adolescent assault injury compared with 2 control groups of youth with unintentional injuries and noninjury complaints presenting to the emergency department and 2) to assess locations of contact with assault-injured youth for prevention programs.
Methods. Face-to-face and phone interviews were conducted with systematic samples of youth aged 12 to 19 years presenting to the emergency department with assault injury, unintentional injury, and noninjury complaints. Youth with intentional injuries were matched to youth in the 2 control groups on age ±1 year, gender, race, and residency.
Results. One hundred forty-seven 147 assault-injured youth completed interviews. One hundred thirty-three assault-injured youth were matched to 133 unintentionally injured and 133 noninjured youth presenting to the emergency department. Compared with the 2 control groups, assault-injured youth were more likely to have had more fights in the past year (odds ratio [OR]: 3.91; 95% confidence interval [CI]: 2.02, 7.58; OR: 4.00; 95% CI: 2.23, 7.18) and fights requiring medical treatment (OR: 35.49; 95% CI: 8.71, 144.68; OR: 80.00; 95% CI: 11.13, 574.80). Eighty percent of assault-injured youth had been in 1 or more fights in the last 12 months compared with 55% and 46% in unintentional and noninjured controls, respectively. Assault-injured youth were more likely to have had previous weapon injuries (OR: 9.50; 95% CI: 3.39, 26.6; OR: 8.50; 95% CI: 3.02, 23.95) and have seen someone shot (OR: 2.00; 95% CI 1.12, 3.58; OR: 2.00; 95% CI: 1.12, 3.58). Eighty-six percent of assault-injured youth had a regular health care provider with 82% reporting a visit within the last year. There were no differences between cases and controls with regard to physician contact, extracurricular activity involvement, school or church attendance, police contact, weapon access or weapon-carrying, or witnessing nonweapon-related violence.
Conclusions. Fighting was common among all groups. Assault-injured youth were more likely to have had previous weapon injuries and were high-risk for future injury. Past fights, past fight injuries, and seeing someone else shot were markers associated with assault injury. Health providers do have access to at-risk teens for clinical risk assessment and intervention.
Key Words: adolescent injury • violence • assault • case-control studies
Abbreviations: ED, emergency department
Improved public health and medical care have markedly reduced the impact of common childhood infections and other medical conditions. However, injuries and violence have come to occupy an increasingly prominent role in the mortality and morbidity of children and adolescents. This is especially true in the United States where the leading causes of death in youth aged 10 to 19 include unintentional injury, suicide, and homicide.1,2 Although the number of youth dying from violent injuries is alarming, it represents only a fraction of violent injuries that occur in this age group. For every death attributable to violent injury in youth in the District of Columbia, there were 8 hospitalizations and 108 emergency department (ED) visits.3 To reduce morbidity and mortality attributable to violence, we must first study risk and protective factors for adolescent assault injury and determine potential sites for intervention.
Much is known about general risk factors for adolescent injury and delinquency, but less is known about injury among youth presenting to care for intentional injuries. High rates of injury are associated with behavior patterns and risk factors common to adolescent development. These include male gender, previous injuries, alcohol/drug use, conflict with parents, pattern of parental supervision, weapon-carrying, delinquency, and pubertal development.4–16 Co-varying risk factors for violent behavior are similar: male gender, poor mental health, drug use, lack of parental affection and support, weapon-carrying, school drop-out, exposure to violence, victimization, and delinquency.17–21 Careful attention must be given to the context in which injuries occur, with focus on interventions targeted at factors that may be modifiable.
Known risk/protective factors for involvement in violence and injury may be viewed as associations that identify at-risk individuals or as contributing mediators or co-factors to the outcome.22 Regardless of the degree of causality, ascertainment of epidemiologically-associated factors can identify a subgroup at risk for violence and its adverse consequences. Many advocate a proactive, preventive approach that identifies risk and escalating problem behavior early for interruption and intervention. The literature and the 2001 Surgeon General’s Report on Youth Violence strongly suggest that a multitude of factors contribute to an individual’s propensity to behave aggressively.23,24 An acknowledgment of this multifactorial reality forms the conceptual basis for our assessment of multiple risk and protective factors. Unfortunately, many studies assessing markers for violent injury are cross-sectional without comparison groups. Identifying these predictive factors is an important step in approaching prevention.
The American Academy of Pediatrics25,26and other organizations have advocated that health professionals be involved in the identification of youth at risk for perpetration or victimization of violence. It has been proposed that primary care providers address violence prevention in child health supervision. It is not known, however, whether assault-injured youth access primary care and what locations of contact might be appropriate for prevention programs. To guide strategies, we conducted a case-control study with 2 objectives: 1) to explore risk and protective factors associated with assault injury, and 2) to identify locations or populations of at-risk adolescents for intervention.
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METHODS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
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Control recruitment was designed to enroll adolescents who would have come to the same facility if they had an assault injury. Cases were matched to youth in the 2 control groups on age ±1 year, gender, race, and residency (District of Columbia or Maryland). The unintentional injury control group included patients with discharge diagnoses of unintentional injuries. The uninjured control group included adolescents with nontraumatic conditions (eg, fever, sore throat, appendicitis, first asthma episode). We excluded patients with chronic medical conditions or sexual complaints because we wished to assess primary care use and sexual risk behavior. For ED patients, cases and controls were enrolled on an ongoing basis and were matched with controls at the time of analysis. All hospitalized patients were recruited. After enrollment of a hospitalized case, the next appropriately matched control was recruited. We attempted to match all hospitalized cases 1-to-1 with hospitalized controls.
Study Procedures
Adolescents were approached by a research assistant who screened their eligibility for the study. Written informed consent was obtained. If the adolescent was a minor (<18 years), parental consent (in person or by phone) and adolescent assent were obtained. If the adolescent was of legal age, their written consent was obtained.
The interview consisted of 2 components: a verbal response component and an audiotape (Walkman, Sony Corporation, Japan) component. For the audiotape component, subjects listened to questions asked on the Walkman and wrote numeric answers on an answer sheet that did not have the printed questions. For phone interviews, we sought to complete the interview as quickly as possible after the injury event to minimize the likelihood of recall bias. For the audiotape component, questions were asked over the phone and participants answered by pressing the appropriate button on the touch tone keypad that was interpreted by the interviewer using Digit Grabber dialed digit meter (model TPM-32; Metro Tel Corporation; Jericho, NY). Adolescents were given an audiotape player (Walkman) in appreciation of their participation. Quality control was maintained by extensive training and close supervision of research assistants by senior investigators.
Measures
Development of the interview included 16 initial focus groups with adolescents on injury and violence,27 review of the literature on adolescent injury, and adaptation of models on adolescent risk-taking behavior.8,28,29 Risk and protective factors assessed included: 1) social and community factors (including individual and family demographics, school and church attendance, primary health care contact, and extracurricular activity involvement); 2) behavioral factors (including substance use, sexual activity, behavioral and emotional problems, and suicidal ideation); and 3) violence factors (including past violent injury, fighting frequency, weapon-carrying, weapon access, police contact, and exposure to violence).
National Health Interview Survey questions on demographics, primary care source, past injuries, and use of medical and mental health services were included. The questions on extracurricular activity involvement and police contact were adapted from the Denver Youth Survey and Boston City Hospital Interview.30,31 We used questions on fighting, past injury, weapon-carrying, and behavioral factors from the middle school version of the Youth Risk Behavior Survey, which has been found to have good test-retest reliability.32 A measure of exposure to violence developed by Richters and Martinez was modified for this study.33,34 The interview instrument underwent 2 phases of pretesting and 2 months of pilot testing.
Data Analysis
Data were entered into Microsoft Access (Microsoft Corporation, Bellevue, WA) and analyzed using SAS (SAS Institute, Cary, NC).
Assessment of Sampling Bias
Cases were compared with unmatched cases and refusers on age, sex and race/ethnicity. Comparisons were assessed using analysis of variance for continuous variables and 
2 for categorical variables. The Kruskal-Wallis rank order test was used for variables that were not normally distributed.
Case-Control Comparison
In an effort to increase the study efficiency, individual cases were 1-to-1 matched with 1) a youth in the unintentional injury control group and 2) a youth in the noninjured control group. Matching variables included those demographic factors that may be associated with the outcome variable and thus confound the analysis of risk factors. These included gender, race, age, and state of residency. Risk and protective factors included the social and community, behavioral, and violence factors described above. The association between each risk or protective factor and intentional injury outcome was measured using odds ratios (ORs) with 95% confidence intervals (CIs). Where necessary, interview item results were dichotomized to allow calculation of the OR. Two ORs were calculated for each variable using the cases as a referent group compared with each of the 2 control groups, respectively. These paired comparisons take advantage of the 1-to-1 matching between groups and compared each patient to his or her matched control subject. The database was maintained using Microsoft Access, and the SAS logistic regression program was used to obtain ORs and CIs. Pearson 2 analysis was used to evaluate with whom the youth predominately lived.
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RESULTS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
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Case-Control Comparisons
Age, race, gender, and residency were matching criteria. Case and control participants had a mean age of 15 years. Ninety-five percent were black, 69% were male, and 77% lived in the District of Columbia. Of cases, 37% (49/133) were injured by a weapon (E-codes 965, 966, and 968.2). Cases were more likely than controls in the 2 groups to live in a group home and were much more likely to live without parental presence (P = .0046) as seen in Table 3.
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For violence risk factors, assault injury was associated with more lifetime fights, fights in the past year, fight injuries, been shot or injured with a weapon compared with both control groups. For fights in the past year >1, sample size of 133 per group had 80% power to detect a 15% difference between groups (
= 0.10; 2-tailed). Cases were more likely to have seen someone shot or attacked with a knife. There were no significant differences between cases and controls on weapon-carrying, weapon access, gang involvement (
3%), police involvement, history of being threatened, violent injury or death of family or friends, or witnessing someone threatened, mugged, or sexually assaulted.
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DISCUSSION |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
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Limitations
Potential limitations include validity of self-report data and 2 modes of interviewing, bias related to convenience sampling, nonparticipation, exclusion criteria, and control group selection issues. The validity of self-report data is a persistent concern in behavioral research. There was face validity and internal consistency in participant responses in extensive pretesting and study interviewing. Research on the use of the Walkman audiotape and DigitGrabber interviewing has suggested greater confidentiality and validity of these modes of interviewing.35,36 Others have found that the more efficient telephone interviewing is as accurate as face-to-face interviews.37,38 It is possible that there existed bias in convenience sampling and nonparticipation; however, our refusal rate was low and there were few differences noted between those who did or did not enroll as shown in Table 2.
Uninjured adolescents with sexual complaints were excluded because of our interest in exploring the association of assault injury and risk behavior including sexual risk behavior. Exclusion of these patients in the control group may have resulted in a lower risk uninjured control group. Nonetheless, there were surprisingly few factors that differentiated the case and control groups. This exclusion may have overestimated the specific association between assault injury and sexual risk behavior that did reach statistical significance (ever had sex OR: 2.00; 95% CI: 1.08, 3.72; lifetime sexual partners OR: 2.13; 95% CI: 1.15, 3.94). However, there were statistically significant differences in sexual behavior in the assault-injured group compared with the unintentional control group as well (pregnancy: OR: 2.71; 95% CI: 1.14, 6.46; lifetime sexual partners: OR: 1.93; 95% CI: 1.01, 3.68).
Other limitations include the fact that the 2 chosen control groups may not have been appropriate for assessment of risk and protective factors and locations of contact with youth. It has been postulated that injured youth with intentional and unintentional injuries share behavioral risk and protective factors that lead to injury. If this is true, we may have overmatched. This study was able to test this hypothesis of shared risk and protective factors and confirms similar profiles on many factors with few exceptions.
Our second control group, uninjured patients, may not have been representative of the community, but representative of the community that uses EDs for primary care. It has been reported that adolescents who utilize EDs for acute illness may be a high-risk group without a regular source of health care or without insurance.39,40 Though it is possible that they are a high-risk group, in our study the noninjured group were just as likely as the injured group to have a regular health care provider and have had a regular checkup in the last year.
Finally, the study was conducted in a high-risk community,3 and the results may not be generalizable to other regions.
Study Implications
One objective of this study was to assess locations for intervention with assault-injured youth. The American Academy of Pediatrics and others have suggested that primary care providers take an active role in violence risk assessment.25,26 For this strategy to be effective, it is critical to know whether assault-injured youth utilize primary care providers for risk assessment and intervention. We found that the majority of assault-injured youth and controls had a regular health care provider and had had a checkup in the past year. Thus, health care providers in primary care and in the ED may have opportunities for intervention. Group homes and schools are other locations of potential contact.
Although it is possible that the majority of assault-injured youth may be reached in primary care or in schools, in our study a notable proportion of youth did not have a regular health care provider (14%) and were not enrolled in school (9%). Though this was not significantly different across cases and controls, it highlights the need to explore other venues to reach these potentially high-risk adolescents and young adults.
The unique combinations of risk and protective factors of the injured individual may influence the likelihood of future violence and injury. Our study found that group home residents, living apart from parents, history of many fights, fight or weapon injuries, or witnessing weapon injuries were all possible risk factors for assault injury presenting to an ED. Few studies have had the benefit of control groups to assess the usefulness of these risk factors for screening. One longitudinal study followed a sample of youth over time (median: 5.2 years) and found that school status, drug use, and fighting history were most predictive of violence-related injuries.41 Our study confirms the association of fighting history with assault injury, but in our population, associations with school status and drug and alcohol use were inconsistent at best.
We queried a variety of social and community factors, behavioral factors, and violence factors that have been discussed in the literature. Surprisingly, only a small number of risk factors and no protective factors tested consistently differentiated assault-injured youth from controls. There could be many explanations for this finding including inappropriate control groups as discussed above, lack of sensitivity of our measures to detect differences (especially for protective factors), and the high risk of the community studied. Our case and control populations may have been from communities of such high risk and high violence exposure that predictive factors previously reported in lower-risk communities were not applicable. The high levels of violence exposure in both the cases and controls suggest that many youth were at-risk. The risk and protective factors that we tested were only those of individual risk behavior and exposure. Other social and community factors such as school performance and connectedness, family relations, and community connectedness were not examined and may offer greater insight into risk for assault injury.
Although there were inconsistent differences between cases and the 2 control groups there is a suggestion that a higher proportion of assault-injured youth were involved in other high-risk behavior including trying cigarettes, marijuana, and increased sexual activity. This is consistent with literature and theory on problem behavior. More than 2 decades ago Jessor and Jessor28 articulated the theory that a cluster of co-varying problem behaviors contribute to and comprise a pattern of risk and this has been confirmed by the Centers for Disease Control and Prevention’s Youth Risk Behavior Survey42 and the World Health Organization’s survey Health Behavior in School Children.43 Jessor44 points out that a number of structural factors (biological characteristics, personality, and social environment) are related and interact with adolescent risk behaviors in both risk-enhancing and protective ways. This study suggests that fighting behavior and assault injury may be part of this constellation of problem behaviors.
Some predictors of assault injury included previous number of lifetime physical fights, fights in the last year, and fight injuries. Unfortunately, among cases the wording of the fight questions did not clearly exclude the fight that brought them into the ED, thus limiting the predictive value of this screening question. However, after conservatively eliminating the current fight or injury among cases, there remained a significant difference between cases and controls on history of a weapon injury and fight-related injury (noninjured controls OR: 2.00; 95% CI: 0.60, 6.64). The vast majority of youth in all groups had been in at least 2 physical fights in their lifetime (92% assault-injured, 78% unintentionally injured, 71% noninjured). In the past year, most had had at least 1 fight (80% assault-injured, 55% unintentionally injured, 46% noninjured). These data support claims that fighting is normative in some communities. Interventions need to focus not only on decreasing numbers of fights, but also increasing ways to save face and disengage from fights and decreasing injury potential. Although fighting may be normative, our study suggests that an increased number and severity of past fights are associated with increased risk for injury.
A strong risk factor for assault injury was previous weapon injury and witnessing weapon injury. In our assault-injured group, 37% had been injured by a weapon. Twenty-nine percent of the assault-injured youth stated that they had been injured with a weapon in the past 12 months which was 8.5 to 9.5 times higher than the 2 control groups (unintentional control group OR: 9.50; 95% CI: 3.39, 26.60; noninjured control group OR: 8.50; 95% CI: 3.02, 23.95). Even subtracting those with weapon injuries that brought them into the study, 16% of the assault-injured group had had a previous weapon injury in the last year, 2.4 to 3.5 times higher than controls (unintentional OR: 3.51; 95% CI: 1.37–9.29; noninjured OR: 2.39; 95% CI: 1.13, 5.06). Interestingly, ability to get a gun, access to a weapon in the home, and report of weapon-carrying were not significantly different among the groups. Clearly, decreasing injury potential by decreasing access to and use of weapons are critical for prevention. Focus on individuals with previous weapon injury is warranted and screening for this risk in health care settings may assist in management.
Violence risk screening protocols have been developed for use in primary care. For example, the FISTS pneumonic developed by Sege45 assesses risk using (F) previous fights, (I) previous injuries, (S) history of sexual violence, (T) threats of violence, and (S) self-defense strategies including weapon access. Our data support a limited number of the components of this pneumonic in this population (previous fights and injuries) and suggest that in high-risk populations, screening for risk may be difficult and a universal prevention strategy may be needed. To guide prevention, knowledge of the strength of predictive factors is critical in choosing a targeted or universal approach. Finally, identifying settings of contact with at-risk adolescents who may or may not attend school is another crucial factor in designing programs. This study suggests that primary care sites, EDs, and group homes may be locations of contact for intervention.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address correspondence to Tina L. Cheng, MD, MPH, 9616 Accord Dr, Potomac, MD. E-mail: tcheng2{at}jhmi.edu
Dr Cheng’s current affiliation is: Division of General Pediatrics and Adolescent Medicine, Johns Hopkins University, Baltimore, Maryland.
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REFERENCES |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONREFERENCES |
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This article has been cited by other articles:
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  E. Aisenberg and T. Herrenkohl Community Violence in Context: Risk and Resilience in Children and Families J Interpers Violence, March 1, 2008; 23(3): 296 - 315. [Abstract] [PDF]
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 S B Johnson, S Frattaroli, J L Wright, C B Pearson-Fields, and T L Cheng Urban youths' perspectives on violence and the necessity of fighting Inj. Prev., October 1, 2004; 10(5): 287 - 291. [Abstract] [Full Text] [PDF]
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