[Skip to Content]
[Skip to Content Landing]
Figure.
Location of Adolescent Homicide Cases (Red) and Matched Controls (Blue), Philadelphia, Pennsylvaina, 2010-2012
Location of Adolescent Homicide Cases (Red) and Matched Controls (Blue), Philadelphia, Pennsylvaina, 2010-2012
Table 1.  
Characteristics of the 157 Firearm Homicide Cases and 166 Controls Included in the Study
Characteristics of the 157 Firearm Homicide Cases and 166 Controls Included in the Study
Table 2.  
Individual-, Family-, and Neighborhood-Level Drug and Alcohol Exposures for All Adolescent Homicides and Adolescent Firearm Homicides
Individual-, Family-, and Neighborhood-Level Drug and Alcohol Exposures for All Adolescent Homicides and Adolescent Firearm Homicides
Table 3.  
Drug and Alcohol Exposures and Adolescent Firearm Homicide, Unadjusted and Adjusted Odds Ratios
Drug and Alcohol Exposures and Adolescent Firearm Homicide, Unadjusted and Adjusted Odds Ratios
1.
Web-based Injury Statistics Query and Reporting System (WISQARS) [Online]. National Center for Injury Prevention and Control, Centers for Disease Control and Prevention (producer). 2015. http://www.cdc.gov/ncipc/wisqars. Accessed September 28, 2015.
2.
White  N, Lauritsen  JL.  Violent crime against youth, 1994–2010. Washington, DC: US Department of Justice; 2012.
3.
Singh  GK, Azuine  RE, Siahpush  M, Kogan  MD.  All-cause and cause-specific mortality among US youth: socioeconomic and rural-urban disparities and international patterns.  J Urban Health. 2013;90(3):388-405.PubMedGoogle ScholarCrossref
4.
Carter  PM, Walton  MA, Newton  MF,  et al.  Firearm possession among adolescents presenting to an urban emergency department for assault.  Pediatrics. 2013;132(2):213-221.PubMedGoogle ScholarCrossref
5.
Cheng  TL, Schwarz  D, Brenner  RA,  et al.  Adolescent assault injury: risk and protective factors and locations of contact for intervention.  Pediatrics. 2003;112(4):931-938.PubMedGoogle ScholarCrossref
6.
Cunningham  RM, Carter  PM, Ranney  M,  et al.  Violent reinjury and mortality among youth seeking emergency department care for assault-related injury: a 2-year prospective cohort study.  JAMA Pediatr. 2015;169(1):63-70.PubMedGoogle ScholarCrossref
7.
Squeglia  LM, Jacobus  J, Tapert  SF.  The influence of substance use on adolescent brain development.  Clin EEG Neurosci. 2009;40(1):31-38.PubMedGoogle ScholarCrossref
8.
Warren  JC, Smalley  KB, Barefoot  KN.  Perceived ease of access to alcohol, tobacco and other substances in rural and urban US students.  Rural Remote Health. 2015;15(4):3397.PubMedGoogle Scholar
9.
Swendsen  J, Burstein  M, Case  B,  et al.  Use and abuse of alcohol and illicit drugs in US adolescents: results of the National Comorbidity Survey-Adolescent Supplement.  Arch Gen Psychiatry. 2012;69(4):390-398.PubMedGoogle ScholarCrossref
10.
Akers  RL.  Drugs, alcohol, and society: social structure, process, and policy. Belmont, CA: Wadsworth Publishing; 1992.
11.
Holder  HD, Wagenaar  AC.  Effects of the elimination of a state monopoly on distilled spirits’ retail sales: a time-series analysis of Iowa.  Br J Addict. 1990;85(12):1615-1625.PubMedGoogle ScholarCrossref
12.
Mosher  JF, Jernigan  DH.  Public action and awareness to reduce alcohol-related problems: a plan of action.  J Public Health Policy. 1988;9(1):17-41.PubMedGoogle ScholarCrossref
13.
Rivara  FP, Mueller  BA, Somes  G, Mendoza  CT, Rushforth  NB, Kellermann  AL.  Alcohol and illicit drug abuse and the risk of violent death in the home.  JAMA. 1997;278(7):569-575.PubMedGoogle ScholarCrossref
14.
Scribner  RA, Cohen  DA, Fisher  W.  Evidence of a structural effect for alcohol outlet density: a multilevel analysis.  Alcohol Clin Exp Res. 2000;24(2):188-195.PubMedGoogle ScholarCrossref
15.
Waksberg  J.  Sampling methods for random digit dialing.  J Am Stat Assoc. 1978;73(361):40-46.Google ScholarCrossref
16.
Branas  CC, Elliott  MR, Richmond  TS, Culhane  DP, Wiebe  DJ.  Alcohol consumption, alcohol outlets, and the risk of being assaulted with a gun.  Alcohol Clin Exp Res. 2009;33(5):906-915.PubMedGoogle ScholarCrossref
17.
The National Center for the Review and Prevention of Child Deaths. National CDR Case Reporting System. 2015; https://www.childdeathreview.org/resources/national-cdr-case-reporting-system/.
18.
Ewing  JA.  Detecting alcoholism. The CAGE questionnaire.  JAMA. 1984;252(14):1905-1907.PubMedGoogle ScholarCrossref
19.
Branas  CC, Culhane  D, Richmond  TS, Wiebe  DJ.  Novel linkage of individual and geographic data to study firearm violence.  Homicide Stud. 2008;12(3):298-320.PubMedGoogle ScholarCrossref
20.
The American Association for Public Opinion Research.  Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys. Lenexa, Kansas: AAPOR; 2006.
21.
Silverman  BW.  Density estimation for statistics and data analysis. Vol 26. New York, New York. CRC press; 1986.
22.
Fotheringham  AS, Brunsdon  C, Charlton  M.  Quantitative geography: perspectives on spatial data analysis. Thousand Oaks, California. Sage Publications. 2000.
23.
Waller  LA, Gotway  CA.  Applied spatial statistics for public health data. Vol 368. Hoboken, New Jersey. John Wiley & Sons; 2004.
24.
Culyba  AJ, Jacoby  SF, Richmond  TS, Fein  JA, Hohl  BC, Branas  CC.  Modifiable neighborhood features associated with adolescent homicide.  JAMA Pediatr. 2016;170(5):473-480.PubMedGoogle ScholarCrossref
25.
StataCorp.  Stata Statistical Software: Release 14. College Station, TX: StataCorp LP; 2015.
26.
Web-based Injury Statistics Query and Reporting System (WISQARS). National Center for Injury Prevention and Control, Centers for Disease Control and Prevention; 2016. http://www.cdc.gov/injury/wisqars/fatal.html. Accessed April 26, 2016.
27.
Branas  CC, Han  S, Wiebe  DJ.  Alcohol Use and Firearm Violence.  Epidemiol Rev. 2016;38(1):32-45.PubMedGoogle Scholar
28.
Walsh  C, MacMillan  HL, Jamieson  E.  The relationship between parental substance abuse and child maltreatment: findings from the Ontario Health Supplement.  Child Abuse Negl. 2003;27(12):1409-1425.PubMedGoogle ScholarCrossref
29.
Wolock  I, Magura  S.  Parental substance abuse as a predictor of child maltreatment re-reports.  Child Abuse Negl. 1996;20(12):1183-1193.PubMedGoogle ScholarCrossref
30.
Biederman  J, Faraone  SV, Monuteaux  MC, Feighner  JA.  Patterns of alcohol and drug use in adolescents can be predicted by parental substance use disorders.  Pediatrics. 2000;106(4):792-797.PubMedGoogle ScholarCrossref
31.
Yule  AM, Wilens  TE, Martelon  MK, Simon  A, Biederman  J.  Does exposure to parental substance use disorders increase substance use disorder risk in offspring? A 5-year follow-up study.  Am J Addict. 2013;22(5):460-465.PubMedGoogle ScholarCrossref
32.
Esbensen  F-A, Huizinga  D, Menard  S.  Family context and criminal victimization in adolescence.  Youth Soc. 1999;31(2):168-198.Google Scholar
33.
Culyba  AJ, Ginsburg  KR, Fein  JA, Branas  CC, Richmond  TS, Wiebe  DJ.  Protective effects of adolescent-adult connection on male youth in urban environments.  J Adolesc Health. 2016;58(2):237-240.PubMedGoogle ScholarCrossref
34.
Stewart  EA, Schreck  CJ, Simons  RL.  “I ain’t gonna let no one disrespect me”: does the code of the street reduce or increase violent victimization among african american adolescents?  J Res Crime Delinq. 2006;43(4):427-458.Google ScholarCrossref
35.
Taylor  TJ, Peterson  D, Esbensen  F-A, Freng  A.  Gang membership as a risk factor for adolescent violent victimization.  J Res Crime Delinq. 2007;44(4):351-380.Google ScholarCrossref
36.
Browning  S, Erickson  P.  Neighborhood disadvantage, alcohol use, and violent victimization.  Youth Violence Juv Justice. 2009;7(4):331-349.Google ScholarCrossref
37.
Wiebe  DJ, Richmond  TS, Guo  W,  et al.  Mapping activity patterns to quantify risk of violent assault in urban environments.  Epidemiology. 2016;27(1):32-41.PubMedGoogle ScholarCrossref
38.
Grubesic  TH, Pridemore  WA, Williams  DA, Philip-Tabb  L.  Alcohol outlet density and violence: the role of risky retailers and alcohol-related expenditures.  Alcohol Alcohol. 2013;48(5):613-619.PubMedGoogle ScholarCrossref
39.
Pridemore  WA, Grubesic  TH.  Alcohol outlets and community levels of interpersonal violence: spatial density, outlet type, and seriousness of assault.  J Res Crime Delinq. 2013;50(1):132-159.Google ScholarCrossref
40.
Resko  SM, Walton  MA, Bingham  CR,  et al.  Alcohol availability and violence among inner-city adolescents: A multi-level analysis of the role of alcohol outlet density.  Am J Community Psychol. 2010;46(3-4):253-262.PubMedGoogle ScholarCrossref
41.
Goldstein  PJ.  The drugs/violence nexus: A tripartite conceptual framework.  J Drug Issues. 1985;15(4):493-506.Google ScholarCrossref
42.
Axhausen  KW, Weis  C.  Predicting response rate: a natural experiment.  Surv Pract. 2010;3(2).Google Scholar
43.
Baruch  Y, Holtom  BC.  Survey response rate levels and trends in organizational research.  Hum Relat. 2008;61(8):1139-1160.Google ScholarCrossref
44.
Groves  RM.  Nonresponse rates and nonresponse bias in household surveys.  Public Opin Q. 2006;70(5):646-675.Google ScholarCrossref
45.
Peduzzi  P, Concato  J, Kemper  E, Holford  TR, Feinstein  AR.  A simulation study of the number of events per variable in logistic regression analysis.  J Clin Epidemiol. 1996;49(12):1373-1379.PubMedGoogle ScholarCrossref
46.
Myers  SR, Branas  CC, French  BC,  et al.  Safety in numbers: are major cities the safest places in the United States?  Ann Emerg Med. 2013;62(4):408-418.e3, e3.PubMedGoogle ScholarCrossref
47.
Nance  ML, Carr  BG, Kallan  MJ, Branas  CC, Wiebe  DJ.  Variation in pediatric and adolescent firearm mortality rates in rural and urban US counties.  Pediatrics. 2010;125(6):1112-1118.PubMedGoogle ScholarCrossref
48.
Krug  EG, Mercy  JA, Dahlberg  LL, Zwi  AB.  The world report on violence and health.  Lancet. 2002;360(9339):1083-1088.PubMedGoogle ScholarCrossref
49.
Sumner  SA, Mercy  JA, Dahlberg  LL, Hillis  SD, Klevens  J, Houry  D.  Violence in the United States: status, challenges, and opportunities.  JAMA. 2015;314(5):478-488.PubMedGoogle ScholarCrossref
50.
Crowley  RA, Kirschner  N; Health and Public Policy Committee of the American College of Physicians.  The integration of care for mental health, substance abuse, and other behavioral health conditions into primary care: executive summary of an American College of Physicians position paper.  Ann Intern Med. 2015;163(4):298-299.PubMedGoogle ScholarCrossref
51.
World Health Organization.  mhGAP intervention Guide for mental, neurological and substance use disorders in non-specialized health settings. 2016. http://apps.who.int/iris/bitstream/10665/44406/1/9789241548069_eng.pdf. Accessed: November 23, 2016.
52.
Cassidy  T, Inglis  G, Wiysonge  C, Matzopoulos  R.  A systematic review of the effects of poverty deconcentration and urban upgrading on youth violence.  Health Place. 2014;26:78-87.PubMedGoogle ScholarCrossref
53.
Heinze  JE, Reischl  TM, Bai  M,  et al.  A comprehensive prevention approach to reducing assault offenses and assault injuries among youth.  Prev Sci. 2016;17(2):167-176.PubMedGoogle ScholarCrossref
Original Investigation
Firearm Violence
March 2017

Association of Drug and Alcohol Use With Adolescent Firearm Homicide at Individual, Family, and Neighborhood Levels

Author Affiliations
  • 1Department of Epidemiology, School of Public Health, Rutgers, The State University of New Jersey, Piscataway
  • 2School of Criminal Justice, Rutgers University, Newark, New Jersey
  • 3Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
  • 4Department of Mathematics, School of Science, Hampton University, Hampton, Virginia
  • 5The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
  • 6Medical Examiner's Office, Philadelphia Department of Public Health, Philadelphia, Pennsylvania
JAMA Intern Med. 2017;177(3):317-324. doi:10.1001/jamainternmed.2016.8180
Key Points

Question  Is there a relationship between alcohol- and drug-related factors and adolescent firearm homicide at the individual, family, and neighborhood levels?

Findings  In a population-based, case-control study of 13- to 20-year-old residents of Philadelphia, Pennsylvania, we found that almost all adolescent homicides were firearm homicides. Drug use at all 3 levels and alcohol at the individual and neighborhood levels were associated with increased odds of adolescent firearm homicide.

Meaning  Expanding violence prevention efforts to target substance use at multiple levels within society may help to reduce the firearm violence that disproportionately affects minority populations in large US cities.

Abstract

Importance  Homicide is the third leading cause of death for adolescents in the United States and the leading cause of death for adolescents who are African American. Large cities have disproportionate homicide rates.

Objective  To determine the relationships between exposures to drugs and alcohol at the individual, family, and neighborhood levels and adolescent firearm homicide and to inform new approaches to preventing firearm violence.

Design, Setting, and Participants  Population-based case-control study from January 2010 to December 2012 of all 13- to 20-year-olds who were homicide victims in Philadelphia during the study period matched to randomly selected 13- to 20-year-old controls from the general population.

Exposures  Individual drug and alcohol use at the time of injury, history of drug and alcohol use, caregiver drug and alcohol use, and neighborhood availability of alcohol and illegal drugs. We also controlled for age, race, school suspensions, arrests, and neighborhood ethnicity.

Main Outcomes and Measures  Adolescent firearm homicide identified from police and medical examiner’s reports.

Results  We enrolled 161 adolescent homicide cases, including 157 (97.5%) firearm homicide cases and 172 matched controls, including 166 (96.5%) firearm homicide controls. Adolescents with a history of alcohol use (adjusted odds ratio [AOR], 4.1; 95% CI, 1.2-14.0) or drug use (AOR, 4.4; 95% CI, 1.7-11.6) had increased odds of firearm homicide. Adolescents whose caregiver had a history of drug use had increased odds of firearm homicide (AOR, 11.7; 95% CI, 2.8-48.0). Adolescents in neighborhoods with high densities of alcohol outlets (AOR, 3.2; 95% CI, 1.1-9.1) and moderate or high drug availability had increased odds of firearm homicide (AOR, 3.4; 95% CI, 1.1-10.3 vs AOR, 7.5; 95% CI, 2.2-25.8).

Conclusions and Relevance  Almost all adolescent homicides in Philadelphia between 2010 and 2012 were committed with a firearm. Substance use at the individual, family, and neighborhood levels was associated with increased odds of adolescent firearm homicide; drug use was associated at all 3 levels and alcohol at the individual and neighborhood levels. Expanding violence prevention efforts to target drug and alcohol use at multiple levels may help to reduce the firearm violence that disproportionately affects adolescents in minority populations in large US cities.

Introduction

Homicide is the third leading cause of death for adolescents in the United States and the leading cause of death for African-American adolescents,1 with young men of color dying at rates more than 20 times their white counterparts.2 Large cities have disproportionate rates of homicide compared with other areas of the country.3

Adolescents engage in behaviors every day that increase their risk for violent injury such as fighting, carrying guns, and drug and alcohol use.4-6 Drugs and alcohol create substantial problems owing to their accessibility and effects on youth during critical periods of development.7,8 In the United States, adolescents use and abuse substances at relatively high rates with lifetime prevalence estimates showing 60% have had the opportunity to use illicit drugs, 24% have used illicit drugs, 60% have used alcohol, and 25% regularly use alcohol.9

Research in adults indicates that there is an elevated risk of becoming a victim of homicide associated with drug and alcohol use as well as a substantial homicide risk for those living with substance users.10-14 Thus, many adolescents may be at risk simply by being in a family or a neighborhood environment where alcohol and drugs are present, regardless of personal consumption. In Philadelphia, where almost all adolescent homicides are firearm homicides, we conducted a citywide population-based case-control study to determine alcohol and drug-related risk factors for becoming a homicide victim at the individual, family, and neighborhood levels.

Methods

Institutional review boards at the University of Pennsylvania and the Philadelphia Department of Public Health approved the study. Interviewers obtained verbal consent for participation from control respondents 18 years and older and verbal consent from a parent or guardian and assent from those aged 13 to 17 years. After completion of the interview, control participants were mailed a $20 gift card as compensation for their participation.

Participant Identification and Matching

We rapidly ascertained cases of adolescent homicide and randomly selected adolescent controls. Cases were adolescents, ages 13 to 20 years, residing in Philadelphia County who died following an intentional assault in the county between January 2010 and December 2012. Based on daily monitoring of reports from the Philadelphia Medical Examiner’s Office and Police Department, we identified new, fatally injured adolescents. Data coordinators forwarded relevant information (homicide date and time, victim age and sex, and resident status) to an independent survey research firm, DataStat, Inc, which then initiated recruitment of matched controls. This identification and matching process allowed quick identification of controls from a risk set at the time each case was fatally injured.

The control group included residents of Philadelphia County, ages 13 to 20 years, recruited through random digit dialing.15 We used incidence density sampling with a caliper match of 3 hours prior to and after the index case’s time of injury to control for potential temporal and seasonal confounders. Controls were pair-matched to cases based on sex and indoor/outdoor location at the time of each index case’s fatal injury. Matching criteria were selected based on prior research to avoid the likelihood of mismatches and very small numbers within any matching strata.16

Case to control recruitment at a 1:1 sampling ratio was based on prior power calculations and sample size estimations. For timely identification of controls, multiple interviewers simultaneously completed control interviews; 12 homicide case participants had more than 1 matched control. All were retained in the final analysis.

Data and Measures

We obtained detailed case information from the Philadelphia Child Death Review Team Case Reporting System in the Medical Examiner’s Office. This database contains information from an interdisciplinary team of professionals representing several municipal departments and hospitals that jointly compile records pertaining to all deaths of Philadelphia children (0-21 years).17 Child death review data included information on the decedent, their family, and other contextual characteristics, such as history of drug or alcohol abuse and family drug or alcohol use (1 or more caregivers having a history of drug or alcohol abuse). The Medical Examiner's office provided the results of toxicology tests that identified case alcohol and drug use (such as cocaine, marijuana, methamphetamine, and opiates). The Police Department provided data on the address and circumstances of each homicide as well as decedent characteristics, including prior arrests.

Participants in the control group were interviewed by phone using a structured questionnaire containing information on individual and household demographics, education, employment, and delinquency. They were asked questions about drug and alcohol consumption and access (if they had used any alcohol or drugs not prescribed for them around the time of each case incident, whether they drank alcohol at any time before or during the time of case incident), history of drug use (the last time they used drugs that were not prescribed for them or not purchased at a store), history of alcohol abuse (indicated by a yes response to 2 of the 4 CAGE screening questions for alcoholism: Cutting down, Annoyance by criticism, Guilty feeling, and Eye-openers),18 and family drug and alcohol use (1 or more caregivers drinking alcohol every day, 1 or more caregivers ever using drugs that were not prescribed to them or purchased at a store).

Interviewers had those in the control group acknowledge that they were in a safe place and could have uninterrupted interview time. Interviewers used prompts to help participants accurately recall information about their address location, activities, and exposures at the time of their matched case’s index injury. Interviews were conducted within a median time of 11 days of their match’s index injury. DataStat used multiple recruitment strategies to maximize participation and reduce bias.16,19 Based on formula put forward by the American Association for Public Opinion Research20 to standardize the calculation of response and cooperation rates in random sample surveys, the cooperation rate for control participants was 73.4% and the response rate was 52.3%. After completion of the interview, control participants were mailed a $20 gift card.

Neighborhood data pertaining to alcohol and illicit drug sales markets came from multiple sources. The Police Department provided address location of crime incidents for narcotics manufacture, possession, and sales. The Pennsylvania Liquor Control Board provided access to a list of licenses for retail sales of alcohol in Philadelphia, including information such as business name, address, and type of business. We used 2010 to 2012 alcohol outlet data and crime data to create a kernel density summary variable of alcohol outlets per square mile, as well as a variable for narcotics sales incidents per square mile.21-23 We created 3 equal groups for narcotic crime densities: low (0-21.93 per square mile), moderate (21.94-54.06 per square mile), and high (54.37-320.40 per square mile) and alcohol outlet densities: low (0-16.96 per square mile), moderate (17.27-30.58 per square mile), and high (30.59-442.33 per square mile). Alcohol sales (visible bars, taverns, beer stores, and corner stores) and advertisements were also assessed using a series of 360-degree, high-resolution panorama field photographs of the immediate environments of our cases and controls. The protocols used to create and code these photographs were part of a related study,24 which examined the association between environmental neighborhood features, such as streets, buildings, and natural surroundings, and adolescent homicide. That study used a subsample of the same youth in the current study but focused on the data collected through photographs of the outdoor locations of case and controls.

We used 2010 US Census tract and block group data to calculate inverse distance weighted neighborhood metrics of household income, unemployment, race, and ethnicity for case and control address locations at the time of the case incident.

Statistical Analyses

Data were summarized using mean and median for continuous variables and frequency percentages for nominal variables. Bivariate comparisons were made between cases and controls for baseline characteristics using t tests, Wilcoxon rank sum tests, and χ2 tests, as appropriate.

We modeled the associations between separate individual-level, family-level, and neighborhood-level alcohol and drug exposures and adolescent homicide. We produced odds ratios (ORs) using conditional logistic regression that accounted for case to control pair-matching. Adjusted ORs (AORs) accounted for individual (age in years, race, school suspensions, history of prior arrest) and neighborhood characteristics (percent of the population that was Hispanic).

We tested all models for collinearity and variance inflation factors were less than 5 in all instances. A 2-sided P value less than .05 was considered statistically significant. All analyses were performed with STATA statistical software (version 14, STATACorp).25

Results

We enrolled 161 adolescent homicide cases, including 157 (97.5%) firearm homicides, and 172 controls, including 166 (96.5%) firearm homicide controls. Firearm homicide cases and controls showed no significant differences in sex or whether they were indoors or outdoors at the time of the homicides. On average, compared with the controls, cases were older, more often identified as black, had more suspensions in their last year of school, and had more arrests (Table 1). Cases and controls had similar unemployment and school absences and were geographically represented in every major section of Philadelphia (Figure).

Individual and Family-Level Exposures

Table 2 shows individual, family, and neighborhood level drug and alcohol exposures for all adolescent homicides and for firearm homicides. Because analyses ran with all homicide cases and those restricted to firearm homicides showed no meaningful differences (data not shown) we present results for firearm homicide cases and controls.

Table 3 shows unadjusted and adjusted ORs for firearm homicide and alcohol and drug exposure at the individual, family, and neighborhood levels. Adolescents who had been using drugs at the time of the event had an increased odds of firearm homicide (OR, 3.8; 95% CI, 1.6-8.7). After adjustment, this association was no longer significant. We found no significant associations between alcohol use at the time of the event and firearm homicide in either unadjusted or adjusted analyses. Adolescents having a history of prior drug use (AOR, 4.4; 95% CI, 1.7-11.6) or alcohol abuse (AOR, 4.1; 95% CI, 1.2-14.0) had increased odds of firearm homicide.

In the unadjusted model, having a caregiver who frequently used alcohol was associated with increased odds of firearm homicide (OR, 3.4; 95% CI, 1.4-8.6); after adjusting for covariates, this relationship was no longer significant. Adolescents with a caregiver who had a history of reported drug use had increased odds of firearm homicide (AOR, 11.7; 95% CI, 2.8-48.0).

Neighborhood-Level Exposure

The overall density of alcohol outlet licensees and the odds of firearm homicide were associated (Table 3). Compared with low-density locations, the unadjusted odds of firearm homicide was 2.8 (95% CI, 1.5-5.1) in locations with moderate density of alcohol outlets and 3.0 (95% CI, 1.6-5.5) in locations with high density. In adjusted analyses, the odds of firearm homicide was 3.2 (95% CI, 1.1-9.1) in locations with high density of alcohol outlets and the relationship was no longer significant in locations with moderate density. The trend for increasing density was not significant. In the unadjusted but not the adjusted models, firearm homicide was associated with locations where beer stores and corner stores were visible, as indicated by the photograph coding of each location. Visible bars or taverns and alcohol advertisements were not associated with firearm homicide risk.

The density of narcotics sales and the odds of firearm homicide were also associated (Table 3). Compared with locations with low levels of narcotic sales, in unadjusted analyses the odds of firearm homicide was 4.0 (95% CI, 2.0-8.1) in locations with moderate levels of sales and 8.8 (95% CI, 4.2-18.6) in locations with high levels of sales. In adjusted analyses, these associations remained significant: moderate sales (AOR, 3.4; 95% CI, 1.1-10.3) and high sales (AOR, 7.5; 95% CI, 2.2-25.8). The trend for increasing density was not significant.

Discussion

Between January 2010 and December 2012, 97.5% of all adolescent homicides in Philadelphia were committed with a firearm, compared with 86% of adolescent homicides nationally during the same period.26 We found increased odds of adolescent firearm homicide associated with substance use at the individual, family, and neighborhood levels: drug exposures were associated at all 3 levels and alcohol exposures were associated at the individual and neighborhood levels.

Substance use may be linked to an increased risk of adolescent homicide through: (1) difficulty identifying social cues or risky people and places owing to cognitive impairment; (2) an inability to defend or remove oneself from risky situations; and (3) being identified as an easy target for predators. However, we found no relationship between alcohol or drug consumption at the time of the incident and adolescent homicide. Although it is possible that a larger study with more cases and controls might have found significant associations, our findings are consistent with the findings of case-control studies of adult shooting victims.16,27 Our findings suggest that prevention efforts for adolescent firearm homicide may need to expand their focus to include broader social and contextual factors that are external to the individual.

Our findings also suggest that drug use by a caregiver should be considered an important risk factor for an adolescent to become a victim of a firearm homicide. Parental substance use has been directly associated with negative outcomes for youth in both the short and long term. Parental substance abuse is significantly associated with child maltreatment,28,29 and exposure to parental substance use disorders in adolescence has been shown to increase the risk of a substance use disorder in the adolescent.30,31

Family factors that are predictive of violence against adolescents include parental problem behavior, adolescent social isolation from the family, limited parental monitoring, and possibly prior parental victimization.32 Absence of adolescent-adult connections33 and poor-quality relationships with parents or peers have been shown to increase risks for violent injury.34,35 Caregiver substance use might increase adolescent homicide owing to lack of supervision, poorly modeled behavior, or a disruptive family environment. The presence of caregivers who do not use illicit drugs may be important for protecting adolescents from intentional and unintentional injuries, including serious forms of violence, during this critical period when they develop autonomy.

Prior research has shown that the association between alcohol use and becoming a victim of violence varies by neighborhood social and physical context,36 and specific characteristics of neighborhood environments, such as disorder (eg, the presence of vacant or vandalized properties), where adolescents spend time can increase their risk for violent injury.24,37 Previous research has also demonstrated a relationship between alcohol outlet density and violence in adults16,38,39 as well as youth.40 This relationship may reflect increased alcohol consumption owing to greater availability, poor recognition of intoxicated individuals by people who are serving alcohol, and consumption of alcohol in outdoor spaces where consumption is prohibited by law.16 Goldstein41 theorized 3 pathways through which illegal drugs and violence might be related: psychopharmacological, economic compulsive, and systemic. Our findings related to illegal drug activity at the neighborhood level may be explained by the systemic pathway, whereby violent patterns of behavior emerge owing to the broad illegality of the drug trade and the absence of a legal system to monitor and resolve disputes.

Limitations

The limitations of our study should be noted. Our cooperation and response rates for control participants are similar to other representative, random sample surveys conducted during the same period42-44 and suggest enrollment of a reasonably representative sample of Philadelphia youth; still selection bias is possible. Case-control studies are more feasible and efficient when studying rare outcomes such as adolescent homicide. However, case-control studies are prone to bias, confounding, and issues of reverse causation. We adjusted for multiple covariates in an effort to limit confounding.45 Still, differences between cases and controls may persist in other, unmeasured factors that we could not include. Studies using measures collected through interviews are prone to recall bias. We sought to reduce this bias by selecting and interviewing controls within a short time period and using prompts to promote and anchor recall. Exposures may have been classified differently between cases and controls. Adolescents may have responded in a socially desirable way when questioned about substance use behaviors or had limited knowledge about household substance use. We minimized the potential for such misclassifications by creating a safe interview structure with interview techniques to promote honest and complete responses. Finally, our findings might not generalize to nonurban areas whose adolescent injury risks can be substantially different.46,47

Conclusions

Our findings suggest that public health approaches to prevent firearm homicides among adolescents should address risk factors for violence at multiple levels.48 The oldest and most tested approaches to reducing youth violence focus on changing individual behavior and family environments.49 Efforts are under way to encourage the integration of substance use disorder treatment with general medical care for adults50,51; perhaps creating opportunities to also address youth violence in families. Recent violence reduction initiatives are focused on changing the physical and social characteristics of neighborhood (eg, improving physical infrastructure or building youth engagement).52,53 Interventions targeting drug and alcohol exposures at the neighborhood level could expand these efforts. Multi-level approaches should form the basis for future research and interventions to reduce the burden of firearm violence that disproportionately affects adolescents in minority populations in large US cities.

Back to top
Article Information

Corresponding Author: Bernadette C. Hohl, PhD, MPH, Department of Epidemiology, School of Public Health, Rutgers, The State University of New Jersey, 683 Hoes Lane W, Piscataway, NJ 08854 (bernadette.hohl@rutgers.edu).

Accepted for Publication: November 7, 2016

Published Online: January 3, 2017. doi:10.1001/jamainternmed.2016.8180

Author Contributions: Drs Hohl and Branas had full access to all data in the study and take responsibility for data integrity and the accuracy of the data analysis.

Concept and design: Hohl, Wiebe, Culyba, Branas.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Hohl, Wiley, Branas.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Hohl, Wiley, Culyba, Branas.

Obtained funding: Branas.

Administrative, technical, or material support: Drake, Branas.

Conflict of Interest Disclosures: None reported.

Funding/Support: This work was supported in part by National Institutes of Health (grant numbers R01AA016187, R01AA014944, and T32HD043021); and the Centers for Disease Control and Prevention (grant number R49CE002474).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

References
1.
Web-based Injury Statistics Query and Reporting System (WISQARS) [Online]. National Center for Injury Prevention and Control, Centers for Disease Control and Prevention (producer). 2015. http://www.cdc.gov/ncipc/wisqars. Accessed September 28, 2015.
2.
White  N, Lauritsen  JL.  Violent crime against youth, 1994–2010. Washington, DC: US Department of Justice; 2012.
3.
Singh  GK, Azuine  RE, Siahpush  M, Kogan  MD.  All-cause and cause-specific mortality among US youth: socioeconomic and rural-urban disparities and international patterns.  J Urban Health. 2013;90(3):388-405.PubMedGoogle ScholarCrossref
4.
Carter  PM, Walton  MA, Newton  MF,  et al.  Firearm possession among adolescents presenting to an urban emergency department for assault.  Pediatrics. 2013;132(2):213-221.PubMedGoogle ScholarCrossref
5.
Cheng  TL, Schwarz  D, Brenner  RA,  et al.  Adolescent assault injury: risk and protective factors and locations of contact for intervention.  Pediatrics. 2003;112(4):931-938.PubMedGoogle ScholarCrossref
6.
Cunningham  RM, Carter  PM, Ranney  M,  et al.  Violent reinjury and mortality among youth seeking emergency department care for assault-related injury: a 2-year prospective cohort study.  JAMA Pediatr. 2015;169(1):63-70.PubMedGoogle ScholarCrossref
7.
Squeglia  LM, Jacobus  J, Tapert  SF.  The influence of substance use on adolescent brain development.  Clin EEG Neurosci. 2009;40(1):31-38.PubMedGoogle ScholarCrossref
8.
Warren  JC, Smalley  KB, Barefoot  KN.  Perceived ease of access to alcohol, tobacco and other substances in rural and urban US students.  Rural Remote Health. 2015;15(4):3397.PubMedGoogle Scholar
9.
Swendsen  J, Burstein  M, Case  B,  et al.  Use and abuse of alcohol and illicit drugs in US adolescents: results of the National Comorbidity Survey-Adolescent Supplement.  Arch Gen Psychiatry. 2012;69(4):390-398.PubMedGoogle ScholarCrossref
10.
Akers  RL.  Drugs, alcohol, and society: social structure, process, and policy. Belmont, CA: Wadsworth Publishing; 1992.
11.
Holder  HD, Wagenaar  AC.  Effects of the elimination of a state monopoly on distilled spirits’ retail sales: a time-series analysis of Iowa.  Br J Addict. 1990;85(12):1615-1625.PubMedGoogle ScholarCrossref
12.
Mosher  JF, Jernigan  DH.  Public action and awareness to reduce alcohol-related problems: a plan of action.  J Public Health Policy. 1988;9(1):17-41.PubMedGoogle ScholarCrossref
13.
Rivara  FP, Mueller  BA, Somes  G, Mendoza  CT, Rushforth  NB, Kellermann  AL.  Alcohol and illicit drug abuse and the risk of violent death in the home.  JAMA. 1997;278(7):569-575.PubMedGoogle ScholarCrossref
14.
Scribner  RA, Cohen  DA, Fisher  W.  Evidence of a structural effect for alcohol outlet density: a multilevel analysis.  Alcohol Clin Exp Res. 2000;24(2):188-195.PubMedGoogle ScholarCrossref
15.
Waksberg  J.  Sampling methods for random digit dialing.  J Am Stat Assoc. 1978;73(361):40-46.Google ScholarCrossref
16.
Branas  CC, Elliott  MR, Richmond  TS, Culhane  DP, Wiebe  DJ.  Alcohol consumption, alcohol outlets, and the risk of being assaulted with a gun.  Alcohol Clin Exp Res. 2009;33(5):906-915.PubMedGoogle ScholarCrossref
17.
The National Center for the Review and Prevention of Child Deaths. National CDR Case Reporting System. 2015; https://www.childdeathreview.org/resources/national-cdr-case-reporting-system/.
18.
Ewing  JA.  Detecting alcoholism. The CAGE questionnaire.  JAMA. 1984;252(14):1905-1907.PubMedGoogle ScholarCrossref
19.
Branas  CC, Culhane  D, Richmond  TS, Wiebe  DJ.  Novel linkage of individual and geographic data to study firearm violence.  Homicide Stud. 2008;12(3):298-320.PubMedGoogle ScholarCrossref
20.
The American Association for Public Opinion Research.  Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys. Lenexa, Kansas: AAPOR; 2006.
21.
Silverman  BW.  Density estimation for statistics and data analysis. Vol 26. New York, New York. CRC press; 1986.
22.
Fotheringham  AS, Brunsdon  C, Charlton  M.  Quantitative geography: perspectives on spatial data analysis. Thousand Oaks, California. Sage Publications. 2000.
23.
Waller  LA, Gotway  CA.  Applied spatial statistics for public health data. Vol 368. Hoboken, New Jersey. John Wiley & Sons; 2004.
24.
Culyba  AJ, Jacoby  SF, Richmond  TS, Fein  JA, Hohl  BC, Branas  CC.  Modifiable neighborhood features associated with adolescent homicide.  JAMA Pediatr. 2016;170(5):473-480.PubMedGoogle ScholarCrossref
25.
StataCorp.  Stata Statistical Software: Release 14. College Station, TX: StataCorp LP; 2015.
26.
Web-based Injury Statistics Query and Reporting System (WISQARS). National Center for Injury Prevention and Control, Centers for Disease Control and Prevention; 2016. http://www.cdc.gov/injury/wisqars/fatal.html. Accessed April 26, 2016.
27.
Branas  CC, Han  S, Wiebe  DJ.  Alcohol Use and Firearm Violence.  Epidemiol Rev. 2016;38(1):32-45.PubMedGoogle Scholar
28.
Walsh  C, MacMillan  HL, Jamieson  E.  The relationship between parental substance abuse and child maltreatment: findings from the Ontario Health Supplement.  Child Abuse Negl. 2003;27(12):1409-1425.PubMedGoogle ScholarCrossref
29.
Wolock  I, Magura  S.  Parental substance abuse as a predictor of child maltreatment re-reports.  Child Abuse Negl. 1996;20(12):1183-1193.PubMedGoogle ScholarCrossref
30.
Biederman  J, Faraone  SV, Monuteaux  MC, Feighner  JA.  Patterns of alcohol and drug use in adolescents can be predicted by parental substance use disorders.  Pediatrics. 2000;106(4):792-797.PubMedGoogle ScholarCrossref
31.
Yule  AM, Wilens  TE, Martelon  MK, Simon  A, Biederman  J.  Does exposure to parental substance use disorders increase substance use disorder risk in offspring? A 5-year follow-up study.  Am J Addict. 2013;22(5):460-465.PubMedGoogle ScholarCrossref
32.
Esbensen  F-A, Huizinga  D, Menard  S.  Family context and criminal victimization in adolescence.  Youth Soc. 1999;31(2):168-198.Google Scholar
33.
Culyba  AJ, Ginsburg  KR, Fein  JA, Branas  CC, Richmond  TS, Wiebe  DJ.  Protective effects of adolescent-adult connection on male youth in urban environments.  J Adolesc Health. 2016;58(2):237-240.PubMedGoogle ScholarCrossref
34.
Stewart  EA, Schreck  CJ, Simons  RL.  “I ain’t gonna let no one disrespect me”: does the code of the street reduce or increase violent victimization among african american adolescents?  J Res Crime Delinq. 2006;43(4):427-458.Google ScholarCrossref
35.
Taylor  TJ, Peterson  D, Esbensen  F-A, Freng  A.  Gang membership as a risk factor for adolescent violent victimization.  J Res Crime Delinq. 2007;44(4):351-380.Google ScholarCrossref
36.
Browning  S, Erickson  P.  Neighborhood disadvantage, alcohol use, and violent victimization.  Youth Violence Juv Justice. 2009;7(4):331-349.Google ScholarCrossref
37.
Wiebe  DJ, Richmond  TS, Guo  W,  et al.  Mapping activity patterns to quantify risk of violent assault in urban environments.  Epidemiology. 2016;27(1):32-41.PubMedGoogle ScholarCrossref
38.
Grubesic  TH, Pridemore  WA, Williams  DA, Philip-Tabb  L.  Alcohol outlet density and violence: the role of risky retailers and alcohol-related expenditures.  Alcohol Alcohol. 2013;48(5):613-619.PubMedGoogle ScholarCrossref
39.
Pridemore  WA, Grubesic  TH.  Alcohol outlets and community levels of interpersonal violence: spatial density, outlet type, and seriousness of assault.  J Res Crime Delinq. 2013;50(1):132-159.Google ScholarCrossref
40.
Resko  SM, Walton  MA, Bingham  CR,  et al.  Alcohol availability and violence among inner-city adolescents: A multi-level analysis of the role of alcohol outlet density.  Am J Community Psychol. 2010;46(3-4):253-262.PubMedGoogle ScholarCrossref
41.
Goldstein  PJ.  The drugs/violence nexus: A tripartite conceptual framework.  J Drug Issues. 1985;15(4):493-506.Google ScholarCrossref
42.
Axhausen  KW, Weis  C.  Predicting response rate: a natural experiment.  Surv Pract. 2010;3(2).Google Scholar
43.
Baruch  Y, Holtom  BC.  Survey response rate levels and trends in organizational research.  Hum Relat. 2008;61(8):1139-1160.Google ScholarCrossref
44.
Groves  RM.  Nonresponse rates and nonresponse bias in household surveys.  Public Opin Q. 2006;70(5):646-675.Google ScholarCrossref
45.
Peduzzi  P, Concato  J, Kemper  E, Holford  TR, Feinstein  AR.  A simulation study of the number of events per variable in logistic regression analysis.  J Clin Epidemiol. 1996;49(12):1373-1379.PubMedGoogle ScholarCrossref
46.
Myers  SR, Branas  CC, French  BC,  et al.  Safety in numbers: are major cities the safest places in the United States?  Ann Emerg Med. 2013;62(4):408-418.e3, e3.PubMedGoogle ScholarCrossref
47.
Nance  ML, Carr  BG, Kallan  MJ, Branas  CC, Wiebe  DJ.  Variation in pediatric and adolescent firearm mortality rates in rural and urban US counties.  Pediatrics. 2010;125(6):1112-1118.PubMedGoogle ScholarCrossref
48.
Krug  EG, Mercy  JA, Dahlberg  LL, Zwi  AB.  The world report on violence and health.  Lancet. 2002;360(9339):1083-1088.PubMedGoogle ScholarCrossref
49.
Sumner  SA, Mercy  JA, Dahlberg  LL, Hillis  SD, Klevens  J, Houry  D.  Violence in the United States: status, challenges, and opportunities.  JAMA. 2015;314(5):478-488.PubMedGoogle ScholarCrossref
50.
Crowley  RA, Kirschner  N; Health and Public Policy Committee of the American College of Physicians.  The integration of care for mental health, substance abuse, and other behavioral health conditions into primary care: executive summary of an American College of Physicians position paper.  Ann Intern Med. 2015;163(4):298-299.PubMedGoogle ScholarCrossref
51.
World Health Organization.  mhGAP intervention Guide for mental, neurological and substance use disorders in non-specialized health settings. 2016. http://apps.who.int/iris/bitstream/10665/44406/1/9789241548069_eng.pdf. Accessed: November 23, 2016.
52.
Cassidy  T, Inglis  G, Wiysonge  C, Matzopoulos  R.  A systematic review of the effects of poverty deconcentration and urban upgrading on youth violence.  Health Place. 2014;26:78-87.PubMedGoogle ScholarCrossref
53.
Heinze  JE, Reischl  TM, Bai  M,  et al.  A comprehensive prevention approach to reducing assault offenses and assault injuries among youth.  Prev Sci. 2016;17(2):167-176.PubMedGoogle ScholarCrossref
×