Among a long list of issues facing the American public, guns are third only to gay marriage and abortion in terms of people who report that they are “not willing to listen to the other side.” In concert with this cultural rift, scholarly discussion over guns has been similarly contentious.1 Although scholars and the public agree that the roughly 100 000 shootings each year in the United States are a clear threat to health, uncertainty remains as to whether civilians armed with guns are, on average, protecting or endangering themselves from such shootings.2–4

Several case–control studies have explored the relationship between homicide and having a gun in the home,5,6 purchasing a gun,7,8 or owning a gun.9 These prior studies were not designed to determine the risk or protection that possession of a gun might create for an individual at the time of a shooting and have only considered fatal outcomes. This led a recent National Research Council committee to conclude that, although the observed associations in these case–control studies may be of interest, they do little to reveal the impact of guns on homicide or the utility of guns for self-defense.3,10

However, the recent National Research Council committee also concluded that additional individual-level studies of the association between gun ownership and violence were the most important priority for the future.3 With this in mind, we conducted a population-based case–control study in Philadelphia, Pennsylvania, to investigate the relationship between being injured with a gun in an assault and an individual's possession of a gun at the time. We included both fatal and nonfatal outcomes and accounted for a variety of individual and situational confounders also measured at the time of assault.

METHODS Section: Choose Top of page Abstract METHODS << RESULTS DISCUSSION References CITING ARTICLES

We applied a case–control study design to determine the association between being injured with a gun in an assault and an individual's possession of a gun at the time. To determine this in the most generalizable way, we chose our target population to be residents of Philadelphia prompting the use of population-based control participants. We considered trial, cohort, and matched cohort designs but for various reasons (ethical considerations, prohibitively long implementation time, limited generalizability, and so on.) these were not pursued.

We assumed that the resident population of Philadelphia risked being shot in an assault at any location and at any time of day or night. This is an acceptable assumption because guns are mobile, potentially concealable items and the bullets they fire can pass through obstacles and travel long distances.11–14 Any member of the general population has the potential to be exposed to guns and the bullets they discharge regardless of where they are or what they are doing. As such, we reasonably chose not to exclude participants as immune from hypothetically becoming cases because they were, for instance, asleep at home during the night or at work in an office building during the day. Instead we measured and controlled for time-based situational characteristics that might have changed, but did not eliminate, the possibility of being shot in an assault.

Participant Identification and Matching Gunshot assault cases caused by powder charge firearms were identified as they occurred, from October 15, 2003, to April 16, 2006. The final 6 months of this period were limited to only fatal cases. We excluded self-inflicted, unintentional, and police-related shootings (an officer shooting someone or being shot), and gun injuries of undetermined intent. We excluded individuals younger than 21 years because it was not legal for them to possess a firearm in Philadelphia and, as such, the relationship we sought to investigate was functionally different enough to prompt separate study of this age group. We excluded individuals who were not residents of Philadelphia as they were outside our target population and individuals not described as Black or White as they were involved in a very small percentage of shootings (< 2%). Even after these exclusions, the study only needed a subset of the remaining shootings to test its hypotheses. A random number was thus assigned to these remaining shootings, as they presented, to enroll a representative one third of them. Data coordinators at the Philadelphia Police Department identified and enrolled new shooting case participants as they occurred by reviewing an electronic incident tracking system and interviewing police officers, detectives, and medical examiners. Basic data for eligible case participants were wirelessly sent to the University of Pennsylvania where study leaders forwarded them to a survey research firm for recruitment of a matched control participant. More detailed information for each enrolled case was later filled in with additional data from state and local police, medical examiner, emergency medical services, and hospital data sources.15 We pair-matched case participants to control participants on the date and time (within 30-minute intervals; i.e., 10:30 pm, 11:00 pm) of each shooting. This was done because the factors we planned to analyze, including gun possession, were often short-lived making the time of the shooting most etiologically relevant.16 This also helped to control for a great many unmeasurable confounders related to time. We also matched our control participants to case participants on the basis of age group (aged 21–24 years, 25–39 years, 40–64 years, and 65 years and older), gender, and race (Black or White). We pair-matched on these variables to avoid extremely sparse data in certain subgroups given a priori knowledge that exceedingly different age, race, and gender distributions existed among assaultive shootings relative to the general population of Philadelphia.17 We did not pair-match case participants and control participants on location. On the basis of early power calculations, we matched 1 control participant to each shooting case. Control participants were in Philadelphia at the time their matched case was shot. The median number of days between the time a shooting occurred and the time a control participant interview was completed was 2 days. More than three quarters of all control participant interviews were completed within 4 days of their matched shooting. Control participants were interviewed as rapidly as possible to minimize recall bias. Control participants were sampled from all of Philadelphia via random-digit dialing.10,18 In the interest of time, multiple interviewers may have simultaneously begun and then completed control participant interviews. This resulted in 7 case participants that had more than 1 control participant. These few additional control participants were retained in final analyses. We also tested for the possibility of unequal sampling by using an inverse probability of selection weight defined as the number of eligible control participants divided by the number of phone lines in a household. These weighted models generated only very small differences (< 5%) in our results. We took several steps to maximize participation and avoid selection biases caused by nonresponse.15,10,19–21 According to standard formulae, the cooperation rate for our control participant survey was calculated to be 74.4% and the response rate 56.0%.22 These rates exceeded those of other surveys conducted at about the same time23 and were high enough to produce a reasonably representative sample of our target population.24,25 Our control participants were statistically similar to the general population of Philadelphia in terms of marital status, retirement, education, general health status, and smoking status within the age, gender, and race categories specified earlier.26 Our control participants were, however, significantly more unemployed than the general population.

Conceptual Framework and Variables We conceptually separated confounding variables in the association between victim gun possession and gun assault into individual and situational characteristics, both of which feed the eventual victim–offender interaction that results in gun assault (Figure 1).27–29 Case subsets included fatal gun assaults and gun assaults in which the victim had at least some chance to resist the threat posed by an offender, based on circumstance data and written accounts from police, paramedics, and medical examiners. Case participants with at least some chance to resist were typically either 2-sided, mutual combat situations precipitated by a prior argument or 1-sided attacks where a victim was face-to-face with an offender who had targeted him or her for money, drugs, or property. Case participants with at least some chance to resist were in contrast to those that happened very suddenly, involved substantial distances, had no face-to-face contact, and had physical barriers between victim and shooter (e.g., an otherwise uninvolved victim shot in his living room from a gun fired during a fight down the street).30–33 Each case's chance-to-resist status was assigned after being independently rated by 2 individuals (initial κ = 0.64 indicating substantial agreement34) who then reconciled differential ratings. For case participants, gun possession at the time of the shooting was determined by police observations at crime scenes and police interviews with victims and witnesses, as well as confiscation and recovery of guns by police investigators. We coded case participants as in possession if 1 or more guns were determined to have been with them and readily available at the time of the shooting. We coded control participants as in possession if they reported any guns in a holster they were wearing, in a pocket or waistband, in a nearby vehicle, or in another place, quickly available and ready to fire at the time of their matched case's shooting. We determined gun possession status for 96.8% of case participants and 99.6% of control participants. We imputed missing data by using multiple imputation by chained equations.35,36 We collected participants' locations as street intersection or blockface points. We collected environmental factors as centroid and population-weighted centroid points of blocks, block groups, and tracts.37 We assigned study participants cumulative, inverse distance-weighted measures of each environmental factor on the basis of the points where they were located and the point locations and magnitudes of the factors surrounding them. The higher the measure, the greater the clustering and magnitude of factors around a participant's location.15,38