Household Firearm Ownership and Firearm Mortality

Abstract

Importance: Causal associations between household firearm ownership rates (HFRs) and firearm mortality rates are not well understood.

Objective: To assess the population-level temporal sequencing of firearm death rates and HFRs.

Design, setting, and participants: This cohort study used autoregressive cross-lagged models to analyze HFRs, firearm suicide rates, and firearm homicide rates in the US from 1990 to 2018. The suicide analyses included 16 demographic subgroups of adults, defined by study year, state, sex, race and ethnicity, marital status, and urbanicity. The homicide analyses consisted of adult subgroups living in urban or rural areas. Data analysis was conducted from March to December 2023.

Exposures: Firearm mortality rates and HFRs.

Main outcomes and measures: Firearm homicide and suicide rates with HFRs as the exposure, and HFR with mortality as the exposure.

Results: A total of 10 416 observations of 16 demographic subgroups by state and 2-year periods were included in the suicide analyses, while 1302 observations from 2 demographic subgroups by state and 2-year period were included in the homicide analysis. At baseline, the mean (SD) rate per 100 000 population across strata was 7.46 (7.21) for firearm suicides and 3.32 (2.13) for firearm homicides. The mean (SD) baseline HFR was 36.9% (20.2%) for firearm suicides and 36.9% (14.8%) for firearm homicides. Higher HFR preceded increases in suicide rates: demographic strata with equal firearm suicide rates but which differ by 18.6 percentage points on HFR (1 SD) would be expected to have firearm suicide rates that diverged by 0.19 (95% CI, 0.15-0.23) deaths per 100 000 population per period. With these differences accumulated over 8 years, firearm suicide rates in subgroups with the highest decile HFR would be expected to have 1.93 (95% CI, 1.64-2.36) more suicides per 100 000 population than strata with lowest decile HFR, a difference of 25.7% of the overall firearm suicide rate in 2018 and 2019. Firearm suicide rates had a smaller magnitude of association with subsequent changes in HFR: strata with equal HFRs but which differ by 1 SD in firearm suicide rates had minimal subsequent change in HFRs (-0.02 [95% CI, -0.04 to 0.01] percentage points). A 1-SD difference in HFRs was associated with little difference in next-period overall firearm homicides rates (0.03 [95% CI, -0.02 to 0.08] per 100 000 population), but a 1-SD difference in homicide rates was associated with a decrease in HFR (-0.09 [95% CI, -0.16 to -0.04] percentage points).

Conclusions and relevance: This cohort study found an association between high HFRs and subsequent increases in rates of firearm suicide. In contrast, higher firearm homicide rates preceded decreases in HFRs. By demonstrating the temporal sequencing of firearm ownership and mortality, this study may help to rule out some theories of why gun ownership and firearm mortality are associated at the population level.

Figure 1.. Standardized Coefficients for Cross-Lagged Models of Household Firearm Ownership Rate (HFR) and Firearm Mortality

FHR indicates firearm homicide rate; FSR, firearm suicide rate. The e_hfr, e_fsr, e_fhr are model residual terms. The full model includes period fixed effects.

Figure 2.. Extrapolations of Cross-Lagged Household Firearm Ownership Rate (HFR) and Firearm Suicide Rate (FSR) Outcomes Over 8 Years Ending in 2019

Differences in expected FSR and HFR are expressed relative to the expected rate for the 25th percentile FSR or HFR. The ordinate scale (y-axis) spans 0.34 of an SD in FSR (A) and .02 of an SD in HFR (B).

Figure 3.. Extrapolations of Cross-Lagged Household Firearm Ownership Rate (HFR) and Firearm Homicide Rate (FHR) Outcomes Over 8 Years Ending in 2019

Differences in expected FHR and HFR are expressed relative to the expected rate for the 25th percentile FHR or HFR. The ordinate scale (y-axis) spans 0.45 of an SD in FHR (A) and .06 of an SD in HFR (B).