Firearms are the second leading cause of pediatric death in the United States. There is significant variation in firearm legislation at the state level. Recently, 3 state laws were associated with a reduction in overall deaths from firearms: universal background checks for firearm purchases, universal background checks for ammunition purchases, and identification requirement for firearms. We sought to determine if stricter firearm legislation at the state level is associated with lower pediatric firearm-related mortality.
This was a cross-sectional study in which we used 2011–2015 Web-based Injury Statistics Query and Reporting System and Census data. We measured the association of the (1) strictness of firearm legislation (gun law score) and (2) presence of the 3 aforementioned gun laws with pediatric firearm-related mortality. We performed negative binomial regression accounting for differences in state-level characteristics (population-based race and ethnicity, education, income, and gun ownership) to derive mortality rate ratios associated with a 10-point change in each predictor and predicted mortality rates.
A total of 21 241 children died of firearm-related injuries during the 5-year period. States with stricter gun laws had lower rates of firearm-related pediatric mortality (adjusted incident rate ratio 0.96 [0.93–0.99]). States with laws requiring universal background checks for firearm purchase in effect for ≥5 years had lower pediatric firearm-related mortality rates (adjusted incident rate ratio 0.65 [0.46–0.90]).
In this 5-year analysis, states with stricter gun laws and laws requiring universal background checks for firearm purchase had lower firearm-related pediatric mortality rates. These findings support the need for further investigation to understand the impact of firearm legislation on pediatric mortality.
Firearm-related injuries are the second leading cause of pediatric death in the United States, yet there is significant variation in firearm legislation at the state level.
States with stricter firearm legislation, specifically legislation regarding universal background checks for firearms, had lower firearm-related mortality rates in children.
Firearm injury is the second leading cause of traumatic death and the third leading cause of death overall among children in the United States.1 The United States has the highest rate of firearm-related injuries in children relative to other industrialized countries.1,2 Of note, ∼7 US children die of firearm-related injuries daily.3
When compared with other high-income countries, the United States has the highest rate of gun ownership, the weakest gun laws, and the highest rate of firearm-related deaths in children.4,–6 Firearm legislation varies at the state level and regulations differ with respect to the presence or absence of laws for firearm purchase, ownership, and carriage.7 Each year, the Brady Campaign to Prevent Gun Violence gathers an expert panel to objectively assess and rate state firearm legislation on the basis of a series of 33 different gun policies.8 Additionally, authors of a recent study found 3 state laws in particular to be strongly associated with a reduction in firearm-related deaths among children and adults combined: universal background checks for firearm purchase, universal background checks for ammunition purchase, and identification requirement for firearms.9
Authors of several previous studies have described lower rates of pediatric suicide, homicide, firearm carriage, and firearm-related morbidity in states with strict gun laws.10,–15 We performed this study to test the hypothesis that stricter firearm legislation at the state level is associated with lower pediatric firearm-related mortality rates.
Methods
Study Design and Data Source
This was a repeated cross-sectional study using the 2011–2015 Web-based Injury Statistics Query and Reporting System (WISQARS). WISQARS is a publicly available, interactive, online, de-identified database that provides fatal injury data in the United States from the Centers for Disease Control and Prevention by broad demographic characteristics and cause of injury.3 These data were used to select firearm-related deaths per year for those aged ≤21 years by state, except in states with <10 annual firearm-related deaths where the counts were suppressed. These data were matched to comparable state population data for all children aged ≤21 years. Although the intent of injury may differ across the pediatric age group, we chose to focus this study across the entire pediatric age spectrum because the primary purpose of this analysis was to measure the relationship between a comprehensive score of state-based firearm legislation (which may impact children from infancy through young adulthood) and firearm-related mortality. This study was exempt from institutional review board approval because of the use of publicly available de-identified data.
Outcome Variable
The primary outcome was firearm-related mortality rate in children. Deaths were identified by using International Classification of Diseases, 10th Revision codes W32–W34, X72–X74, X93–X95, Y22–Y24, Y35.0, and *U01.4 to specify firearm-related mortality. State-specific firearm-related mortality rates were calculated by using respective US 2011–2015 census data.
Exposure Variables
The primary exposure variable was gun law score based on the 2011–2015 Gun Law Scorecards from the Brady Campaign to Prevent Gun Violence. States can receive a maximum of 100 points, based on points awarded for having consistently strong laws. The higher the state gun law score, the stricter the firearm legislation. In 2013, states began losing points for laws considered to weaken public safety. Because states could lose points, negative scores were possible.8 To facilitate statistical modeling, scores were inflated by a constant of 40 to prevent negative values while preserving the original scale.
Secondary exposure variables included individual laws previously associated with lower mortality rates in the total population of adults and children. These included the following 3 laws: (1) universal background checks for firearm purchase, (2) universal background checks for ammunition purchase, and (3) identification requirement for firearms (microstamping, ballistic fingerprinting).9 States were categorized into the following groups on the basis of 2015 laws: states having no law, law in effect for <5 years, or law in effect for ≥5 years.16,17
Confounding Variables
We used the following state-level data from the 2011–2015 US Census to adjust for characteristics previously associated with firearm-related mortality: population-based race and ethnicity proportions, percent of the population with college education, and percent of the population living below the poverty threshold.2,4,18,–20 We adjusted for gun ownership using 2013 data from YouGov, an Internet-based market research company, as reported in a study by Kalesan et al.21 States were dichotomized as having low or high gun ownership on the basis of the median value of the percentage of gun ownership.
Data Analysis
We used standard descriptive statistics to summarize the characteristics of the study population and calculate the overall and state-level firearm-related mortality per 100 000 US children. After determining that the data were too dispersed for Poisson modeling, we used negative binomial multiple regression models to measure the associations of state gun law scores (primary exposure variable) and the presence of the 3 aforementioned laws (secondary exposure variables) with firearm-related mortality rates among children. Four separate models incorporated population-level adjustments for state-level proportions by race and ethnicity, education level, household income, and gun ownership. Variance estimates were adjusted to account for clustering by state across the study years.
Because states with <10 firearm-related deaths among children had suppressed mortality rates, we performed a sensitivity analysis using the mean number of firearm-related deaths over the 5-year study period to estimate an annual mortality rate for states with suppressed data. We compared these results with our primary analysis to assess the robustness of our results. We report incident (mortality) rate ratios (IRRs) and predicted mortality rates with 95% confidence intervals (CIs). We used the “margins” command in Stata version 12.0 (Stata Corp, College Station, TX) to derive predicted mortality rates associated with a 10-point change in the gun law score or in the proportion by race and ethnicity, education level, poverty level, and gun ownership. Similarly, when measuring the impact of the 3 aforementioned laws, we separately calculated predicted mortality rates for states that did not have the law present, states that had the law in effect for <5 years, and states that had the law in effect for ≥5 years.
Results
From 2011 through 2015, there were 21 241 firearm-related deaths among US children reported in WISQARS (∼4250 deaths per year). This translates to an annual firearm-related mortality rate of 4.65 per 100 000 US children. The majority of firearm-related deaths were assault related (61.6%) and occurred among males (87.3%) and 18- to 21-year-old individuals (68.7%) (Table 1).
Characteristics of Study Population, 2011–2015
| Demographic | N (%) (Total N = 21 241) | Rate of Firearm-Related Mortality per 100 000 US Children |
|---|---|---|
| Age group, y | ||
| ≤12 | 1141 (5.4) | 0.4 |
| 13–17 | 5517 (26.0) | 5.3 |
| 18–21 | 14 583 (68.7) | 16.5 |
| Sex | ||
| Male | 18 544 (87.3) | 7.9 |
| Female | 2697 (12.7) | 1.2 |
| Race | ||
| White | 11 133 (52.4) | 3.2 |
| African American | 9471 (44.6) | 12.4 |
| Other | 637 (3.0) | 1.8 |
| Hispanic ethnicity | ||
| Yes | 3407 (16.0) | 3.2 |
| No | 17 786 (83.7) | 5.1 |
| Unknown | 48 (0.2) | — |
| Intent | ||
| Assault | 13 082 (61.6) | 2.9 |
| Suicide | 7217 (40.0) | 1.6 |
| Unintentional | 696 (3.3) | 0.2 |
| Undetermined | 251 (1.2) | 0.1 |
| Demographic | N (%) (Total N = 21 241) | Rate of Firearm-Related Mortality per 100 000 US Children |
|---|---|---|
| Age group, y | ||
| ≤12 | 1141 (5.4) | 0.4 |
| 13–17 | 5517 (26.0) | 5.3 |
| 18–21 | 14 583 (68.7) | 16.5 |
| Sex | ||
| Male | 18 544 (87.3) | 7.9 |
| Female | 2697 (12.7) | 1.2 |
| Race | ||
| White | 11 133 (52.4) | 3.2 |
| African American | 9471 (44.6) | 12.4 |
| Other | 637 (3.0) | 1.8 |
| Hispanic ethnicity | ||
| Yes | 3407 (16.0) | 3.2 |
| No | 17 786 (83.7) | 5.1 |
| Unknown | 48 (0.2) | — |
| Intent | ||
| Assault | 13 082 (61.6) | 2.9 |
| Suicide | 7217 (40.0) | 1.6 |
| Unintentional | 696 (3.3) | 0.2 |
| Undetermined | 251 (1.2) | 0.1 |
—, not applicable.
State-specific mortality rates ranged from 1.1 to 18.1 per 100 000 children. State gun law scores ranged from −39 to +81, and after scaling, 1 to 121, with higher scores indicating stricter gun laws. Gun ownership ranged from 5.2% to 61.7% (median value: 32.2%).
In unadjusted analysis, the association between the gun law score and pediatric firearm-related mortality demonstrated that for every 10-point increase in the gun law score (eg, stricter firearm legislation), the firearm-related mortality rate among children decreased by 8% (IRR 0.92 [95% CI 0.89–0.96]). Sensitivity analysis, in which we used the mean mortality rate over the 5-year period as the annual mortality rate for states that had suppressed mortality data (DE, HI, ME, NH, RI, SD, VT, and WY), revealed similar results (IRR 0.92 [95% CI 0.88–0.96]). Table 2 reveals the results of the fully adjusted model. In this fully adjusted model, every 10-point increase in gun law score decreases the firearm-related mortality rate in children by 4% (adjusted incident rate ratio [aIRR] 0.96 [95% CI 0.93–0.99]). Figure 1 illustrates the relationship between the gun law score and firearm-related mortality in children after population-level adjustments by race and ethnicity, education level, household income, and gun ownership. As illustrated in Fig 1, predicted firearm-related mortality decreases as firearm laws get stronger.
Association of State Gun Law Scores With Firearm-Related Mortality Rates, 2011–2015
| aIRR (95% CI)a | |
|---|---|
| Gun law score | 0.96 (0.93–0.99)b |
| High gun ownership (referent = low gun ownership) | 0.96 (0.83–1.12) |
| Percent of population with African American race | 1.16 (1.07–1.25)b |
| Percent of population with Hispanic ethnicity | 0.98 (0.91–1.05) |
| Percent of population with a college education | 0.72 (0.57–0.90)b |
| Percent of population living below the poverty level | 0.79 (0.51–1.22) |
| aIRR (95% CI)a | |
|---|---|
| Gun law score | 0.96 (0.93–0.99)b |
| High gun ownership (referent = low gun ownership) | 0.96 (0.83–1.12) |
| Percent of population with African American race | 1.16 (1.07–1.25)b |
| Percent of population with Hispanic ethnicity | 0.98 (0.91–1.05) |
| Percent of population with a college education | 0.72 (0.57–0.90)b |
| Percent of population living below the poverty level | 0.79 (0.51–1.22) |
For every 10-point increase in the gun law score (eg, stricter firearm legislation), the firearm-related mortality rate among children decreases by 4%.
Statistical significance at P value <.05; adjusted for year and clustered by state.
Gun law score and predicted pediatric firearm-related mortality rates, 2011–2015.
Gun law score and predicted pediatric firearm-related mortality rates, 2011–2015.
Table 3 reveals the relationship between specific laws and firearm-related mortality in children. A summary of the presence of these laws by state can be found in the Supplemental Information. In 2015, 7 states had laws requiring universal background checks for firearm purchases that had been in effect for ≥5 years, 5 states had these laws for <5 years, and 38 states did not have such laws. After population-level adjustments, states that had these laws in effect for ≥5 years had a predicted mortality rate of 3.80 (2.67–4.94) per 100 000 children compared with 5.88 (5.25–6.52) per 100 000 children in states that did not have such laws (aIRR 0.65 [95% CI 0.46–0.90]). The majority of states (n = 47) did not have laws requiring universal background checks for ammunition purchases in 2015. After population-level adjustment, the 1 state that had laws regarding universal background checks for ammunition purchase in effect for <5 years had a lower firearm-related mortality rate than states that did not have such laws (aIRR 2.18 [CI 0.52–3.84] per 100 000 children compared with aIRR 5.69 [CI 5.17–6.22] per 100 000 children; aIRR 0.38 [CI 0.19–0.82]); however, this association was not significant when compared with the 2 states that had such laws for ≥5 years. Only 2 states had laws requiring firearm identification in 2015, and there was no statistically significant difference in mortality rates between the 2 states that had these laws versus the states that did not.
Specific Firearm Legislation in 2015 and Pediatric Firearm-Related Mortality Rates
| Law | No. States | Predicted Mortality Ratea (95% CI) | Adjusted IRRb (95% CI) |
|---|---|---|---|
| Universal background checks for firearm purchase | |||
| Not present | 38 | 5.88 (5.25–6.52) | Referent |
| Present <5 y | 5 | 5.25 (3.53–6.96) | 0.89 (0.63–1.27) |
| Present ≥5 y | 7 | 3.80 (2.67–4.94) | 0.65 (0.46–0.90) |
| Universal background checks for ammunition purchase | |||
| Not present | 47 | 5.69 (5.17–6.22) | Referent |
| Present <5 y | 1 | 2.18 (0.52–3.84) | 0.38 (0.19–0.82) |
| Present ≥5 y | 2 | 3.65 (1.94–5.36) | 0.64 (0.39–1.03) |
| Identification requirement for firearms | |||
| Not present | 48 | 5.59 (5.03–6.15) | Referent |
| Present <5 y | 0 | — | — |
| Present ≥5 y | 2 | 5.89 (2.86–8.91) | 1.05 (0.63–1.77) |
| Law | No. States | Predicted Mortality Ratea (95% CI) | Adjusted IRRb (95% CI) |
|---|---|---|---|
| Universal background checks for firearm purchase | |||
| Not present | 38 | 5.88 (5.25–6.52) | Referent |
| Present <5 y | 5 | 5.25 (3.53–6.96) | 0.89 (0.63–1.27) |
| Present ≥5 y | 7 | 3.80 (2.67–4.94) | 0.65 (0.46–0.90) |
| Universal background checks for ammunition purchase | |||
| Not present | 47 | 5.69 (5.17–6.22) | Referent |
| Present <5 y | 1 | 2.18 (0.52–3.84) | 0.38 (0.19–0.82) |
| Present ≥5 y | 2 | 3.65 (1.94–5.36) | 0.64 (0.39–1.03) |
| Identification requirement for firearms | |||
| Not present | 48 | 5.59 (5.03–6.15) | Referent |
| Present <5 y | 0 | — | — |
| Present ≥5 y | 2 | 5.89 (2.86–8.91) | 1.05 (0.63–1.77) |
—, not applicable.
Per 100 000 children.
Population-level adjustments by race and ethnicity, education level, household income, and gun ownership.
Discussion
This study supports the hypothesis that states with stricter firearm-related legislation have lower rates of pediatric firearm-related deaths compared with states with less strict firearm legislation. This association persists after adjustment for gun ownership and other sociodemographic variables. We found that of the 21 241 children who died of firearm-related injuries from 2011 through 2015, rates of firearm-related death were lower in states that had higher (more strict) gun law scores and in states that had laws requiring universal background checks for firearm purchases.
Our findings reveal an important association between firearm legislation and pediatric firearm-related mortality. This association was strong even after adjustment for rates of gun ownership. These data suggest that strict firearm legislation may be protective of children even in areas of high gun ownership.
Our results are consistent with previous studies that revealed lower rates of firearm-related injury in states with stricter firearm laws in a hospitalized population.13,18 Safavi et al13 found lower pediatric hospitalization rates in states with stricter firearm legislation. Simonetti et al18 demonstrated that stricter firearm legislation is associated with lower hospital discharge rates for firearm-related injuries in a combined adult and pediatric population in 18 states. Similarly, authors of other studies have observed an association between firearm-related mortality and strictness of firearm legislation or specific firearms laws across 50 states.9,19,22 For instance, Fleegler et al22 demonstrated that states with more firearm laws had lower rates of firearm fatalities in a population of adults and children. In an exhaustive review of the literature, Lee et al19 found that stronger gun policies were associated with lower rates of firearm homicide in the United States. Furthermore, authors of a 2015 international review of 130 studies concluded that the implementation of firearm restrictions is associated with reductions in firearm deaths in the combined population of adults and children.23
In general, firearm legislation impacts overall mortality in adults; states with higher numbers of laws regulating firearms have lower rates of overall firearm mortality as well as fewer suicides and homicides than states with fewer total laws.22 Additionally, laws enforcing strict waiting periods before firearm purchases, universal background checks, restrictions to carrying guns in public, and mandated gun locks were associated with lower adult suicides.24 Studies such as these suggest that specific laws may have particular efficacy in preventing firearm mortality. Kalesan et al9 studied 25 different regulations related to firearms and found that 3 laws were associated with a decrease in overall firearm mortality: universal background checks for firearm purchases, background checks for ammunition purchases, and a requirement of identification on the firearm (microstamping or ballistic fingerprinting). In our study, which was specific to children, we found that states with laws requiring universal background checks for firearm purchases had lower firearm-related mortality. The presence of these laws was associated with a >35% lower rate of firearm-related mortality, even after adjustment for socioeconomic factors and gun ownership. Few states had laws regarding background checks for ammunition purchases or identification requirements for firearms; therefore, the sample was too small to draw conclusions on the impact. Furthermore, laws regarding firearm identification faced challenges at the state level in both California and Maryland. In 2013, California expanded its firearm identification laws and was the first state to pass a microstamping requirement for all new handguns. However, the law faced multiple legal challenges, and gun manufacturers refused to sell new handguns in the state to avoid this requirement. Additionally, in Maryland, a ballistics fingerprinting program that had been in place for almost 15 years was repealed in 2015.17 Therefore, it may be too early to study the impact of microstamping or ballistics identification on preventing firearm-related injury.
Although many state and federal laws are passed with the intent to reduce firearm-related morbidity and mortality, the nuances of differential implementation can make it difficult to elucidate the effectiveness of these laws individually or as a whole. In previous studies, mostly focused on the general population rather than specifically on children, authors have suggested that there are lower firearm-related deaths in states with lower gun ownership25,26 in states with specific laws on safer firearm storage practices,20,27,–29 and in states with background check requirements for firearm or ammunition purchase.9,19 Alternatively, authors of other studies have used composite scores, such as the gun law score, to measure differences in firearm-related injury and mortality. In these studies, authors found lower rates of firearm-related injury and death in states with more restrictive firearm legislation.13,18,22 However, these studies were limited to either a hospitalized population or a population consisting of both adults and children. We used a combined approach in our study in which we evaluated the association of firearm-related mortality among children with strictness of firearm legislation using the gun law score as well as the presence of the 3 laws previously noted by Kalesan et al9 to be associated with lower rates of firearm mortality across all ages. We also studied these trends over a 5-year study period rather than limiting our analysis to just 1 year. In addition, we were able to assess the impact of firearm legislation after adjustment for gun ownership.
Evidence-based policy to drive legislative change suggests that a combination of laws may be the most effective to reduce firearm-related injury and death. Moreover, the American Academy of Pediatrics affirms that the most effective method for preventing pediatric firearm-related injuries is a multilateral approach, advocating for legislation that reduces firearm availability and imposes stricter requirements regarding child access, safety, and design.2 This approach requires more detailed data sources with information on the acquisition of firearms, types of firearms, and enforcement of firearm laws.
The findings of this study build on previous literature and help provide compelling data that an evidence-based, data-driven, public health approach to firearm legislation may be successful in reducing firearm-related injury in children. Legislation to decrease injury from other obvious public health hazards, such as motor vehicle collisions and secondhand smoke exposure, has shown that the adoption of restrictive laws (eg, seat belts, use of car seats, limits on where an individual can smoke, etc) results in lower injury rates.30,31 For instance, as a result of the evidence-based approach taken to reduce mortality from motor vehicle collisions, motor vehicle–related mortality rates have decreased from 9.8 per 100 000 children in 2007 to 6.1 in 2015.32 In contrast, firearm-related crude mortality has not changed, with 5.4 per 100 000 children in 2007 to 5.2 in 2015.32 Thus, an evidence-driven approach, based on more comprehensive data sources, is needed to inform decision-making to reduce childhood injury and death from firearms.
There are several potential limitations to this study. First, because this is a repeated cross-sectional study, we are unable to establish causality between the strictness of firearm legislation and state-based mortality. However, given that the study was conducted over a 5-year period, we believe this adds to the robustness of our findings. Second, the Gun Law Scorecard is not a validated measure of strictness of firearm legislation. However, many studies have used the Gun Law Scorecard to assess “strictness” of firearm legislation at the state level.10,13,18,33 We are unaware of any validated scoring system for firearm legislation, but given the comprehensiveness of the Gun Law Scorecard and its use in published literature, it is a reasonable means to compare levels of firearm strictness. Third, we used the 2013 YouGov survey to estimate gun ownership in our models. Although this survey provides the most recent estimate of gun ownership in the United States, it is possible that this estimate is inaccurate. Nevertheless, it likely reflects relative patterns in gun ownership because its estimates approximate those derived from the Centers for Disease Control and Prevention 2002 Behavioral Risk Factor Surveillance System and has been used in previously published studies.9,34 Furthermore, although we assessed the presence or absence of certain firearm legislation, we were unable to assess the effectiveness of the enforcement of these laws. In addition, when the presence of specific gun laws was evaluated, the effect of other coexistent laws was not adjusted for in the multivariable model. Lastly, these analyses were limited strictly to firearm-related deaths rather than firearm-related injuries, which underestimates the burden of firearm-related morbidity among children.
Conclusions
We found that states with stricter firearm legislation had lower rates of firearm-related death in children. This association remained after population-based adjustment for sociodemographic factors and gun ownership. Furthermore, states with laws requiring universal background checks for firearm purchase also had lower rates of pediatric firearm-related deaths. These results support the need for more robust research related to the impact of firearm legislation on firearm-related injury and death in children. Implementation of evidence-based policies and legislation is required to reduce firearm-related injury in children.
Dr Goyal conceptualized and designed the study, drafted the initial manuscript, and assisted with data analysis and interpretation; Ms Badolato performed data analysis and critically revised the manuscript for important intellectual content; Dr McCarter supervised and performed data analysis and critically revised the manuscript for important intellectual content; Drs Iqbal, Patel, and Parikh helped design the study, assisted with data interpretation, and critically revised the manuscript for important intellectual content; and all authors approved the final manuscript as submitted.
FUNDING: No external funding.
COMPANION PAPER: A companion to this article can be found online at www.pediatrics.org/cgi/doi/10.1542/peds.2019-1300.
Comments
RE: Goyal MK, Badolato GM, Patel SJ, et al. State Gun Laws and Pediatric Firearm-Related Mortality. Pediatrics. 2019;144(2):e20183283
Goyal et al [1] use cross-sectional data to assess whether firearm mortality among US children and young adults is related to state-level firearm-related characteristics, including a summary score of overall firearm legislation strength, select firearm laws, and a survey-based measure of household firearm ownership. They conclude that their findings “suggest that strict firearm legislation may be protective of children even in areas of high gun ownership.”
For several reasons, their approach cannot provide insight into the effect of legislation on mortality. The reported association does, however, raise the question: what likely causal factor makes states that have passed stricter gun laws more likely to have lower firearm-related deaths? To Goyal et al’s credit, they include a variable in their models for the strongest correlate of state-level firearm mortality that has been identified: household firearm ownership. Unfortunately, the data they use, and the way they operationalize their adjustment for firearm prevalence, is flawed. First, the data come from a survey of only a few thousand people (while nationally representative it is not representative at the state-level). Second, their decision to dichotomize gun ownership, rather than use it as a continuous measure, severely undercuts the very adjustment inclusion of this variable was intended to accomplish.
The problems that these data analytic decisions entail are illustrated by considering Hawaii, a state that validated surveys have consistently found to have one of the lowest firearm ownership rates in the US and that Goyal et al’s underlying data indicates has the lowest firearm mortality rate in the entire dataset and the third highest Brady Score (see Table). YouGov estimates a firearm prevalence rate of 45%--well over the national average. This discrepancy is consequential: using YouGov as a continuous variable and excluding Hawaii from analyses attenuates Goyal et al’s findings to statistical non-significance, and, substantively, from an inverse association with a correlation coefficient of -0.5 to a correlation coefficient of -0.2. Using a validated cross-sectional proxy for firearm prevalence, the percentage of suicides involving firearms [2], likewise attenuates the legislation-mortality association to non-significance with a coefficient of approximately 0.2. Further, had they stratified their main finding by their (flawed) classification of high and low gun states, they would see that the legislative effect they report is apparent only in the high gun states --only one of which, Colorado, passed any of the laws that they point to as of particular importance.
In short, Goyal et al's study does not show, one way or the other, whether legislation affects firearm mortality. Instead, because it is easier to pass firearm laws in states with fewer guns (see Table), what their study points to is the well-established relationship between firearm prevalence and firearm mortality [3,4,5]. The danger in publishing findings like these, when misinterpreted as suggesting causality (in either direction), is that it diverts attention away from the availability of the firearm itself, which, in many instances (eg, suicide prevention), is more likely to be affected by non-legislative pathways, such as counselling at risk families to remove guns from their homes.
Matthew Miller, MD,MPH,ScD, Northeastern University
Deborah Azrael, PhD, Harvard University
REFERENCES
[1] Goyal MK, Badolato GM, Patel SJ, et al. State Gun Laws and Pediatric Firearm-Related Mortality. Pediatrics. 2019;144(2):e20183283
[2] Azrael D, Cook P, Miller M. State and local prevalence of firearm ownership measurement, structure and trends. J Quantitative Criminology 2004; 20(1):43-62
[3] Miller M, Azrael D, Hemenway D. Firearm availability and unintentional firearm deaths, suicide and homicide among 5-14 year olds. J of Trauma 2002; 52:267-275.
[4] Miller M, Barber C, Azrael D, White R. Firearms and suicide in the United States: is risk independent of underlying suicidal behavior? Am J Epidemiol 2013 Sep 15;178(6):946-55. doi: 10.1093/aje/kwt197. Epub 2013 Aug 23.
[5] Anglemyer A, Horvath T, Rutherford G. The accessibility of firearms and risk for suicide and homicide victimization among household members: a systematic review and meta-analysis. Ann Intern Med. 2014;160(2):101–110pmid:24592495
TABLE
STATE
BRFSS 2001 household firearm ownership
BRFSS 2002 household firearm ownership
BRFSS 2004 household firearm ownership
Brady Score
YouGov 2013 Household firearm ownership
Firearm mortality Rate 2011-2015 0-21 year olds
Percent of suicides involving firearms (FSS), 2000-2004
Percent of suicides involving firearms (FSS), 2011-2015
Alabama
0.52
0.58
0.52
-18
0.49
7.08
0.74
0.69
Alaska
0.58
0.61
0.6
-30
0.62
10.59
0.66
0.65
Arizona
0.31
0.37
0.32
-39
0.32
4.53
0.6
0.56
Arkansas
0.55
0.59
0.59
-24
0.58
6.42
0.69
0.62
California
0.21
0.21
0.2
76
0.2
3.77
0.46
0.39
Colorado
0.35
0.35
0.35
22
0.34
4.21
0.53
0.49
Connecticut
0.17
0.16
0.18
73
0.17
2.63
0.36
0.3
Delaware
0.26
0.27
0.26
41
0.05
5.09
0.48
0.44
Florida
0.25
0.27
0.25
-20.5
0.33
5.02
0.53
0.52
Georgia
0.4
0.41
0.4
-18
0.32
5.48
0.67
0.63
Hawaii
0.09
0.1
0.12
62
0.45
0.85
0.23
0.2
Idaho
0.55
0.57
0.56
-19
0.57
4.95
0.65
0.6
Illinois
0.2
0.21
0.21
40.5
0.26
6.65
0.41
0.38
Indiana
0.39
0.4
0.38
-14.5
0.34
5.61
0.58
0.53
Iowa
0.43
0.44
0.46
8
0.34
2.9
0.5
0.46
Kansas
0.42
0.44
0.43
-12
0.32
4.69
0.56
0.55
Kentucky
0.48
0.49
0.48
-22
0.42
4.89
0.69
0.65
Louisiana
0.44
0.46
0.45
-27
0.45
10.41
0.7
0.66
Maine
0.41
0.42
0.4
-20
0.23
3.15
0.55
0.53
Maryland
0.21
0.22
0.22
56
0.21
5.33
0.5
0.45
Massachusetts
0.13
0.13
0.11
70
0.23
1.69
0.25
0.21
Michigan
0.38
0.41
0.42
3
0.29
5.8
0.51
0.5
Minnesota
0.42
0.45
0.41
12.5
0.37
2.97
0.5
0.46
Mississippi
0.55
0.55
0.55
-19.5
0.43
7.06
0.73
0.69
Missouri
0.42
0.46
0.44
-9
0.27
6.72
0.59
0.58
Montana
0.58
0.62
0.63
-25
0.52
6.94
0.67
0.63
Nebraska
0.39
0.42
0.45
3
0.2
4.03
0.55
0.52
Nevada
0.34
0.33
0.34
-20.5
0.38
4.58
0.58
0.53
New Hampshire
0.3
0.31
0.31
-7
0.14
2.69
0.48
0.44
New Jersey
0.12
0.11
0.11
69
0.11
3.12
0.3
0.25
New Mexico
0.35
0.4
0.4
-19
0.5
6.01
0.56
0.53
New York
0.18
0.18
0.19
65.5
0.1
2.41
0.36
0.28
North Carolina
0.41
0.42
0.39
-2.5
0.29
4.84
0.63
0.57
North Dakota
0.51
0.55
0.56
-3
0.48
4.25
0.54
0.59
Ohio
0.32
0.32
0.34
-5
0.2
5.14
0.53
0.51
Oklahoma
0.43
0.45
0.46
-17
0.31
6.36
0.62
0.62
Oregon
0.4
0.4
0.4
0
0.27
3.69
0.56
0.52
Pennsylvania
0.35
0.37
0.38
23
0.27
5.41
0.54
0.5
Rhode Island
0.13
0.14
0.12
55
0.06
1.75
0.28
0.24
South Carolina
0.42
0.46
0.43
-16
0.44
6.48
0.68
0.65
South Dakota
0.57
0.6
0.6
-9
0.35
3.74
0.52
0.49
Tennessee
0.44
0.47
0.47
-11
0.39
6.49
0.67
0.63
Texas
0.36
0.36
0.37
-3
0.36
3.97
0.59
0.57
Utah
0.44
0.46
0.45
-8.5
0.32
3.91
0.53
0.51
Vermont
0.42
0.46
0.44
-17
0.29
3.49
0.57
0.54
Virginia
0.35
0.37
0.37
-22.5
0.29
4.35
0.6
0.56
Washington
0.33
0.37
0.34
33
0.28
3.43
0.53
0.49
West Virginia
0.55
0.58
0.58
-15
0.54
4.51
0.69
0.64
Wisconsin
0.44
0.45
0.43
6
0.35
3.95
0.49
0.48
Wyoming
0.6
0.63
0.66
-28
0.54
7.8
0.68
0.63
RE: Goyal MK, Badolato GM, Patel SJ, et al. State Gun Laws and Pediatric Firearm-Related Mortality. Pediatrics. 2019;144(2):e20183283
Goyal et al. use cross-sectional data (2011-2015) to assess whether firearm mortality among US children and young adults is related to several state-level firearm-related characteristics, including a summary score of overall firearm legislation strength, select firearm laws, and a survey-based measure of household firearm ownership. They conclude that the data they present “suggest that strict firearm legislation may be protective of children even in areas of high gun ownership.”
For several reasons, Goyal et al.’s cross-sectional approach, as they acknowledge but then fail to reckon with, cannot in fact provide insight into the effect of legislation on their outcome. Their observation of an association between the strength of firearm legislation and firearm mortality does, however, raise the question: what is it about states that have passed stricter gun laws, compared with those that have passed less stringent laws, that is likely to be causally related to lower rates of gun deaths? To Goyal et al.’s credit, they include a variable in their models for the strongest correlate of state-level firearm mortality that has been identified: state-level household firearm ownership. Unfortunately, the data they use, and the way they operationalize their measure of firearm prevalence, is flawed. First, the data come from a survey of only a few thousand people that the firm conducting the survey warns should not be used to estimate state-level firearm prevalence. Second, even were the data appropriate to use (or had they used state level firearm ownership or proxy data that are available and validated), Goyal et al.’s decision to dichotomize gun ownership, rather than use it as a continuous measure at the state level, severely undercuts the very adjustment that inclusion of this variable is intended to accomplish.
One discrepancy that should have given the authors pause is that Hawaii, a state that validated state-level surveys have consistently found to have a low firearm ownership rate (in the 10-15% range, see Table 1), has, in YouGov, a firearm prevalence rate of 45%, well over the national average. It turns out that this discrepancy is also consequential: if one uses YouGov as a continuous variable (note that Goyal et al. provide no rationale for dichotomizing) and excludes Hawaii from analyses, the association they report between the strictness of firearm legislation and firearm mortality attenuates not only to statistical non-significance, but from an inverse association with a correlation coefficient of -0.5 to a correlation coefficient of -0.2 (using a validated cross-sectional proxy for firearm prevalence, the percentage of suicides involving firearms , instead of the YouGov data, the correlation coefficient likewise attenuates to non-significance with a coefficient of approximately 0.2). Further, if Goyal et al. looked at their findings stratified by their classification of high and low gun states, they would see that the legislative effect they report overall can be seen only in the high gun states --only one of which, Colorado, passed any of the laws that they point to as of particular importance.
In the end, Goyal's study does not show, one way or the other, whether legislation affects firearm mortality. Instead, because it is easier to pass firearm laws in states with fewer guns (the Brady Law Scorecard turns out to be a modestly good proxy for household firearm ownership, rho >-0.8 –Table 1), what Goyal's study points to is the well-established relationship between firearm prevalence and firearm mortality. , , The danger in looking to unsubstantiated legislative effect and not to the availability of the firearm itself, which can be affected by non-legislative as well as legislative pathways, is that we will congratulate ourselves on having saved lives by passing legislation when, in fact, other approaches, such as counselling at risk families to remove guns from their homes, are more likely in many instances (e.g., suicide prevention) to prove effective.
Matthew Miller, MD, MPH, ScD,
Northeastern University
Deborah Azrael, PhD
Harvard University
Table 1:
Please note I was unable to upload the table of data that I want to and that adds an important empirical data set for readers. Please help. Thanks.
RE: UBCs have no effect on firearm homicide and suicide rates
This is stated in the background section but it disagrees with the two most recent studies on CBCs from JHU/Bloomberg and UC Davis/VPRP:
"Recently, 3 state laws were associated with a reduction in overall deaths from firearms: universal background checks for firearm purchases, universal background checks for ammunition purchases, and identification requirement for firearms."
The two most-recent studies on CBCs state:
1. The simultaneous implementation of CBC and MVP policies was not associated with a net change in the firearm homicide rate over the ensuing 10 years in California. The decrease in firearm suicides in California was similar to the decrease in nonfirearm suicides in that state.
https://www.sciencedirect.com/science/article/abs/pii/S1047279718306161
2. The average rates of firearm homicide and suicide in Indiana and Tennessee following repeal were within the range of what could be expected, given natural variation
https://www.ncbi.nlm.nih.gov/pubmed/29613872
What data are you using that shows universal background checks are associated with a reduction in firearm deaths?
RE: State Gun Laws and Pediatric Firearm-Related Mortality
Goyal et al use cross-sectional data (2011-2016) to assess the association between firearm mortality and several state-level firearm-related characteristics, including a measure of the strength of firearm legislation, presence of select firearm laws, and an unvalidated survey based measure of state-level household firearm ownership. In the authors’ words, their objective was “to determine if stricter firearm legislation at the state level is associated with lower pediatric firearm-related mortality.” Unfortunately, the study is unable to meet even this limited objective because, fundamentally, one cannot assess the effect of legislation, firearm or other, using cross sectional data.
The authors, relative new-comers to the firearm research field, also appear to be unacquainted with the limitations of the data upon which they rely, such as using a 2013 YouGov survey of a few thousand people to assess state-level firearm prevalence. As stated by the market research company that conducted the survey, while nationally representative, survey estimates are not representative of gun ownership at the state level. That the data are similarly misused in the widely challenged paper they cite as the source of these data (and of the particular laws Goyal et al focus on as a secondary outcome), is one reason we felt compelled to call out this common misappropriation. Further, even if the You.gov survey were, by chance, representative at the state level, Goyal et al’s decision to dichotomize states into high vs. low gun ownership as a way to adjust for firearm prevalence, when many states have prevalence estimates that cluster in the mid-range, necessarily compromises all but rhetorically the very adjustment that inclusion of this variable is intended to accomplish. Likewise, the author’s decision to pool all firearm deaths (suicide, homicide, unintentional firearm deaths) rather than look at outcomes separately betrays an uninformed perspective of the ways and extent to which these deaths might reasonably be affected by legislation. Take for example their decision to examine ballistic fingerprinting laws (along with background check laws for ammunition and firearms), that, on their face, are unlikely to produce changes in youth firearm mortality. Whatever value one might postulate ballistic fingerprinting might provide with regard to preventing homicide among adults, what possible, let alone measurable value could it have in preventing suicide when the gun used in the suicide is itself ends up lying next to the decedent (and is usually a gun that belongs not to the child but to the child’s parent)? Lastly, including 21-year-old adults along with younger adolescents and children strongly skews the death data towards older youth (and 21-year-old adults), undercutting the putative motivation for the study itself – to better understand understudied pediatric deaths.
In the end, what the Goyal et al's published data show is that in states where more and stricter laws are passed, more youth die by gunfire. Because it is easier to pass laws in states with fewer guns (an empirical observation borne out by the high correlation between firearm prevalence and measures of gun law strictness), what Goyal's study points to is the well-established relationship between firearm prevalence and firearm mortality among children.
Sincerely,
Matthew Miller, MD, MPH, ScD
Northeastern University
Deborah Azrael, PhD
Harvard University