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. 2026 Feb 25;21(2):e0341645. doi: 10.1371/journal.pone.0341645

Unequal by the gun: Four decades of the Black-White firearm homicide gap

Alex Knorre 1,*,#, John MacDonald 2,#
Editor: Annesha Sil3
PMCID: PMC12935247  PMID: 41739740

Abstract

Background: Firearm homicide is a leading cause of death in the United States, with substantial racial disparities documented over time. Black Americans experience disproportionately higher rates of firearm homicide compared to White Americans, reflecting long-standing social, economic, and structural inequities. This study contributes to understanding the magnitude and trends of this disparity.

Objective: We investigate the Black-White population-level disparity in firearm homicide rates over 45 years in the United States and estimate the fraction of excess deaths in the Black population attributable to firearm homicides.

Methods: We measure racial disparities in firearm homicides as the ratio of age-adjusted rates between Black and White populations. Using annual national firearm homicide and population data from CDC WONDER (1979–2023), disaggregated by race, age, and sex, we calculate age-adjusted Black–White mortality ratios by year and sex, as well as the number of excess Black firearm homicide deaths attributable to these disparities.

Results: After a steady period of 1990-2010, the Black-White disparity began increasing and peaked in 2020 when the firearm homicide rate in males was 10.38 times higher in Blacks than Whites. There were 31,202 excess firearm homicides of Black people attributed to the Black-White racial disparity in 2021-2023.

Conclusions: Despite significant declines in firearm homicides during the 1990s, the relative racial gap in firearm homicide has persisted and grown, reflecting the unequal burden of violence borne by the Black population during both declines and surges of violence.

Introduction

Serious crime and violence in the United States is spatially concentrated in the most socially and economically disadvantaged urban neighborhoods where many residents are Black or Hispanic [1,2]. The concentration of serious crime and violence patterns is associated with long-standing racial inequalities in housing, education, finance, criminal justice, health care, employment, and other institutions. Scholars identify these key structural forces as the main drivers of racial gaps in mortality and life expectancy in the United States, noting that they reflect evidence of structural racism [38]. Recent research shows that the surge in gun violence during the COVID-19 pandemic was disproportionately concentrated in high-poverty neighborhoods, where the majority of residents are Black or Hispanic, communities that already had a higher share of firearm violence before the pandemic. For example, in cities Philadelphia, New York, and Los Angeles, between 36% and 55% of the increase in shootings between 2020 and 2021 occurred in just 10% of city census block groups — areas where the residents were overwhelmingly Black and Hispanic [9]. The toll of gun violence is especially concentrated in the most affected communities. In the most economically disadvantaged neighborhoods of Chicago and Philadelphia, young males face an annual risk of gun injury or death greater than 5%, comparable to or exceeding combat risks of the US service members deployed to Afghanistan and Iraq [10].

To Since 2015, life expectancy in the U.S. has plateaued and modestly declined, with mortality increasing most notably among individuals ages 15 to 44 — a trend that reflects an enduring and ethnic inequality [11]. Between 2000 and 2010, the Black-White life expectancy gap had been narrowing, largely due to shifts in the age composition of these populations, which led to a reduction in mortality differences from chronic diseases [12]. More recently, however, the Black-White life expectancy gap has increased as a result of emerging causes, including drug overdoses, gun violence, and suicides [13].

Homicide is a major driver of the Black-White mortality gap, disproportionately affecting Black individuals, especially young adults aged 15-44 [14]. In 2016, the homicide mortality for Black males was 20 times higher than for White males in the United States [5]. Eliminating homicide mortality for Black males would result in 0.53 years of life gained, considerably larger than the effect of removing mortality from suicides (0.16), auto accidents (0.21), and drug overdoses (0.10). By contrast, the elimination of homicide mortality for White males would increase life expectancy by 0.13 years, a smaller estimate than suicides (0.24), auto accidents (0.24), and drug overdoses (0.24) [5].

Firearms are the most significant contributor to homicides among youth and young adults in the U.S., accounting for approximately 81% of all cases [15]. Firearm homicides are the major contributor to racially disparate homicide rates [16]. The Black-White inequality in firearm homicides has been documented across decades in the United States [1719]. During 2018-2022, there was a stable Black-White gap in firearm homicide rates [20,21], which exceeded all other types of violent victimization. In 2020 and 2021, homicide was the leading contributor to disparities in life expectancy between Black and White males in the U.S., exceeding that of deaths from COVID-19 [22]. However, less is known about how Black-White inequality in firearm homicides has changed over time, particularly across periods of surges and declines in gun violence.

Racial disparities in firearm mortality rates closely correspond to surges in gun violence cycles in the U.S. Over the past three decades, the U.S. has experienced several such cycles. In the late 1980s, there was a major increase in homicide rates associated with the introduction of crack cocaine and its attendant drug markets [23]. More youth engaged in the illegal drug trade started to carry firearms for protection, which naturally led to increased rates of firearm homicides among these age groups [17]. Starting from the mid-1990s, homicide rates began to plummet [24]. The drop in homicide rates was unexpected, and scholars from different fields speculated on the causes [25]. The decline in the homicide rates in the U.S. in the 1990s did not equally impact the same groups that experienced the rise. The racial inequality in homicides caused by the growth of homicide victimization of young Black males remained persistently higher than it was before the epidemic rise [26]. While a variety of theories have been proposed to explain the unexpected decrease in homicides in the 1990s, one of the main outcomes of the drop was the dramatic gain in the life expectancy of Black males that lasted until the 2010s [27,28].

The homicide rate in the U.S. began rising from a low point in 2014. Between 2014 and 2020, the firearm homicide rate across 100 major U.S. cities increased by 76% [29]. The rise in violence was most acute in majority-Black neighborhoods, where firearm homicides rose by 87% during this period [29]. In Chicago, for example, this increase in homicide erased the progress in Black-White inequality that had been achieved during the long decline in violence from the early 1990s to the mid-2010s. The upward trend peaked in 2020, marked by a 25% increase in the national homicide rate—the largest single-year rise ever recorded [30]. The causes of the rise in homicides since 2014 remain largely unexplored, especially given that the trend predates the pandemic-era spike. Given that firearm homicide mortality is the leading cause of death for young Black males aged 15-34 [31], it is important to understand changes in the Black-White inequality in firearm homicide rates over the longer term and during periods of surges.

This study provides new statistical evidence of excess deaths from firearm homicides in the U.S., highlighting their role in the Black–White mortality disparity over the past 45 years. We calculate the mortality ratio over 1979-2023 and estimate the fraction of excess deaths in the Black population due to the Black-White inequality in firearm homicides. Several studies have analyzed racial disparity in firearm homicides at the sub-national level in the U.S. and found robust evidence of the Black-White gap [3235].

We follow an approach used by Preston and Vierboom [36] to estimate the age-adjusted mortality in the U.S. relative to five European countries, which has been used in several other recent applications [3740]. Preston and Vierboom estimate that the U.S. would have had 400,700 fewer deaths between 2000 and 2017 if it had a similar mortality rate as European comparisons. In this paper, we follow the same approach and examine the Black-White ratio of firearm homicide mortality rates between 1979 and 2023 after adjusting for sex, age, and calendar year effects (hereafter, we use “years” to refer to calendar years for brevity). We rely on these comparisons to calculate the attributable fraction of excess firearm homicide deaths for the Black population.

Materials and methods

Data

We obtained data from the Wide-ranging Online Data for Epidemiological Research (WONDER) database maintained by the Centers for Disease Control and Prevention (CDC). We accessed and compiled firearm homicides from three sources that provide details on firearm homicides in the US: Compressed Mortality (1979-1998), Compressed Mortality (1999-2016), and Underlying Cause of Death (2017-2023). From these files, we selected Homicide as the Injury Intent and Firearm as the Injury Mechanism. We obtained firearm homicide counts and populations for every single year, race, age group, and sex at the national level. We did not have access to personally identifiable information and compiled these publicly available datasets in aggregated form on December 1, 2022 and then accessed new years of data on June 15, 2025. The replication package containing data and code is available here: https://github.com/alexeyknorre/racial_gap_gun_homicides

One significant limitation of the data from 1979-1998 is that it only contains records on three racial categories (Blacks, Whites, and “Other”), so we focus our analysis on comparing Black and White populations only. We aggregated age groups into 5-year (10-14, 15-19, 20-24) and 10-year (0-9, 25-34, 35-44,..., 75-84) intervals to ensure comparability across CDC databases. The age group of 85 or older was removed because it is often suppressed due to low counts.

Another limitation of the data is the transition from bridged-race categories to single-race categories for Underlying Cause of Death (UCD) data spanning 1999-2023. In 2021, the CDC stopped providing data with the four mutually exclusive bridged race-ethnicity categories: White, Black, Asian, and American Indian. Instead, starting in 2018, CDC WONDER rolled out a more granular measure of race and ethnicity (single race categories), with either 6, 15, or 31 racial categories. Specifically, UCD data with 6 race categories contain Black, White, Asian, American Indian, Pacific Islander, and “More than one race”. This breaks compatibility with the pre-2021 UCD data because now some people can be categorized as “More than one race”, thus deflating death and population counts, particularly for Black individuals. Thus, UCD-6 cannot be used to recreate race-specific mortality rates for years after 2020 that are fully consistent with previous years. UCD is also available with more granular racial and ethnic categories in two forms, containing 15 and 31 mutually exclusive options. However, UCD with more than 6 race and ethnicity categories does not provide total population numbers.

To address the change in data categorizations, we proceed with our analysis by combining UCD’s four bridged-race categories data in 2018-2020 and six single-race categories data in 2018-2023. Single-race categories are created in two possible variations: with and without adding “More than one race” records to Black and White population and death counts. While this does not allow us to perfectly align post-2020 estimates with previous years, it creates upper and lower bounds for the change in 2021-2023, allowing us to see the direction of change in the racial gap in homicide mortality from firearms. Importantly, the change in CDC’s race and ethnicity categories does not affect the estimates of excess deaths, as can be seen from Fig 4.

Fig 4. Excess Black firearm deaths relative to White over time.

Fig 4

Our final analytic sample contains a total of 607,315 firearm homicides of Black and White victims that occurred in the U.S. from 1979 to 2023. This number excludes 15,812 firearm homicides with the race coded as “Other” before 1999. The final analytic dataset includes deaths for combined Single and Multiple race categories recorded in 2018-2023 but excludes deaths for Single-race categories.

Methods

Rate and ratio calculation.

We calculated the firearm homicide mortality rate (DR) by dividing the total number of firearm homicides by the population for each age group a, year y, sex s, and race r:

DRa,y,s,r=Firearm homicide deathsa,y,s,rPopulationa,y,s,r×100,000 (1)

We then calculated the mortality ratio (MR) by dividing the rates for the Black population by the rates for the White population at each subgroup of age, year, and sex:

MRa,y,s=DRa,y,s|r=BlackDRa,y,s|r=White (2)

For each year and sex, we then calculated the age-adjusted mortality ratio. To do this, we calculated the age-adjusted mortality rates using the direct method [41] which accounts for the differences in the underlying age structure of the Black and White populations. We used the age population structure separately for males and females as the standard at each given year according to the following calculation:

AADRy,s|r=White=awa,y,s×DRa=i,y,s|r=White (3)

where wa,y,s is the weight given by the referential age population structure of Blacks for a given year and sex as in the following calculation:

wa,y,s=Populationa,y,s|r=BlackPopulationa,y,s|r=Black (4)

The age-adjusted firearm homicide mortality ratio (AAMR) for each year and sex is given by the final calculation shown in Eq 5:

AAMRy,s=DRy,s|r=BlackAADRy,s|r=White (5)

The resulting age-adjusted mortality ratio estimates the relative Black-White racial gap in firearm homicide mortality. The resulting number shows how much more likely a Black person is to die from a firearm homicide than a White person of the same age group, sex, and in the same year.

Excess deaths.

We estimated the number of excess deaths resulting from this gap. Following the approach of [36], the number of excess Black firearm homicide victims (ED) for a given age group a, year y and sex s is calculated as the difference between the actual number of firearm deaths within the subgroup and the counterfactual number of deaths that would have occurred if the Black population had the same age, sex, and year-specific firearm homicide rate as the White population:

EDa,y,s=Deathsa,y,s|r=BlackActual deaths (6)
DRa,y,s|r=White×100,0001×Populationa,y,s|r=BlackCounterfactual deaths 

We plot the total number of excess deaths attributable to firearm homicides in the Black population over time. For clarity and parsimony, we present combined estimates of excess deaths by age and sex in three-year increments. Using three-year periods helps smooth out year-to-year fluctuations and allows for more stable and interpretable trend estimates, especially given the year-to-year variability in firearm homicides. We focus on the three-year periods with the highest number of Black excess deaths between 1979 and 2023, highlighting peaks in the early 1990s (1991–1993), during the post-2014 rise (2018–2020), and in the most recent years of available data (2021–2023).

Results

Racial gap in firearm homicide mortality

Fig 1 shows the crude firearm homicide mortality rates since 1979 for Black and White males and females. Since 1978, there have been three major spikes in firearm homicides in the U.S. that occurred in 1980, 1993, and 2020. The highest rate of 7.20 firearm homicides per 100,000 people occurred in 1993, while there were a total of 6.36 firearm homicides per 100,000 in 2020. The burden of firearm homicides is disproportionately concentrated among Black males, with Black females having a rate of firearm homicides similar to that of White males.

Fig 1. Crude firearm homicide rates in the United States in 1979-2023.

Fig 1

Rates are not adjusted for age and represent counts of firearm homicides per 100,000 population.

As previously explained, the CDC changed the classification of race in 2021, transitioning from bridged-race to single/multiple-race categories. We show three different race trends in our plots to account for the changing racial classification, yet the results differ only slightly.

Fig 2 presents the main results with the age-adjusted firearm mortality ratio between Black and White males and females, along with the 95% confidence interval. There was relative stability in the Black-White male inequality in firearm homicides between 1988 and 2010. Black males were on average eight to nine times more likely than White males to die from a firearm homicide. Starting in 2010, the Black-White inequality started to grow slowly, even though this period of 2010-2015 had the lowest absolute rate of firearm homicides of Black males. In 2020 the Black-White male gap in firearm homicides was at its highest since 1979, with Black males being 10.38 times more likely than White males to die from a firearm homicide. If we use single-race categories instead of bridged-race categories, the racial gap increases to 10.88. In 2021-2023, this racial gap decreased only slightly.

Fig 2. Changing racial gap in the age-adjusted firearm homicide mortality ratio.

Fig 2

The lines show yearly mortality ratios of age-adjusted Black-White firearm homicide rates. The grey area shows 95% confidence intervals.

The historical change in the Black-White gap of firearm mortality for females is significantly smaller than for males. The onset of racial disparity in lethal shootings for females started in 1979, with Black females being 4.96 times more likely than White females to be the victim of firearm homicide. The Black-White gap in firearm homicides for females narrowed between 1979 and 2017. Since 2017, the Black-White inequality in female firearm homicide rates has grown, reached a peak of 4.74 in 2020, continued to grow in 2021, and has since decreased similarly to the male racial gap between 2021 and 2023.

Fig 3 further subsets the analysis by age groups. Over the last two decades, the Black-White gap has been increasing among young males. Compared to the era of the high violence of 1985-1994, Black males aged 25-34 now have much higher rates of mortality from firearm homicides than in the early 1990s when homicide rates were at peak levels.

Fig 3. Black-White firearm homicide mortality gap by age groups.

Fig 3

Excess deaths

Fig 4 shows how the Black-White gap in firearm homicide mortality translates into the number of deaths that would not have occurred if this gap disappeared each year. Table 1 shows these calculations by sex, age, and race for three-year increments of 1991-1993, 2018-2020, and 2021-2023. In 1991-1993, 28,254 of the victims of firearm homicides were Black. If the Black population experienced age and sex-specific mortality rates similar to the White population, we project that there would be 3,540 Black victims of firearm homicides during this period. After taking the difference between the two, there is an estimated 24,714 excess deaths solely attributable to the relative Black-White inequality in firearm homicide mortality.

Table 1. Excess Firearm Homicide of Black Population.

Age Firearm homicide deaths
1991-93 2018-20 2021-23
Actual Counterfactual Excess Actual Counterfactual Excess Actual Counterfactual Excess
0-9 187 49 138 226 41 185 265 47 218
10-14 502 87 415 251 50 201 500 81 419
15-19 5,459 585 4,874 3,789 390 3,399 5,303 621 4,682
20-24 7,316 696 6,620 5,960 552 5,408 6,824 688 6,136
25-34 8,626 1,047 7,579 10,029 965 9,064 11,736 1,375 10,361
35-44 3,956 614 3,342 4,924 652 4,272 6,484 952 5,532
45-54 1,310 267 1,043 2,101 376 1,725 2,874 516 2,358
55-64 518 117 401 1,083 216 867 1,440 276 1,164
65-74 293 56 237 309 81 228 437 109 328
75-84 87 22 65 60 34 26 42 38 4
Total 28,254 3,540 24,714 28,732 3,357 25,375 35,905 4,703 31,202

Columns “Actual” show counts of Black firearm homicides by age groups and year periods. Columns “Counterfactual” show estimated counts of Black firearm homicides if they had experienced White firearm homicide rates for the respective age group and year period. Columns “Excess” show the difference between actual and counterfactual counts.

A similar calculation for 2018-2020 period, where 2020 was the year with the highest absolute rate of 7 firearm homicide deaths per 100,000 in the United States, yields 25,375 excess Black firearm homicides. In 2021-2023, there were an estimated 31,202 excess Black firearm homicides. Together, these estimates indicate that the relative inequality in firearm homicide deaths affecting the Black population in the United States has grown substantially since 2014, surpassing levels seen even in the early 1990s, with the period from 2016 to 2023 standing out as the most severe on record when age-adjusted comparisons to the White population are taken into account. As can be seen from Table 1, excess firearm homicides of Black youth (age 10-24) are roughly similar across cohorts of 1991-1993 and 2021-2023. The increase in excess Black firearm homicides in 2021-2023 compared to 1991-1993 can be attributed to the age groups of 25 years and older.

Discussion

The great homicide decline in the United States in the 1990s has been celebrated as a public health achievement [27]. Although the absolute rates of firearm homicides decreased between the mid-1990s and mid-2010s for the Black population, the Black-White inequality in firearm homicide rates did not [14]. The ratio of Black-to-White male firearm homicide rates held steady at about 8 or 9 between 1990 and 2010. However, it began to climb after 2010, peaking at 10.38 in 2020. This growth in homicide since 2014 caused by firearms has erased the benefits of the great homicide decline of the 1990 to 2010 period for the Black population in the United States. This disparity results in thousands of excess lives lost among the Black population in the U.S. In 2021 alone, we estimate there were 11,548 excess Black victims of firearm homicides, a number that is even higher than that estimated for 1993 when the U.S. had the highest recorded firearm homicide rate. The period from 2018 to 2023 saw the highest number of excess firearm homicides among Black Americans compared to any other six-year span since 1979.

While the 2020 spike in firearm homicides is a topic that has received national attention, this surge masks a longer trend of increasing Black-White inequality in firearm homicides [42]. Many studies in the social sciences and public health have focused on the concentrated poverty and other social disadvantages in predominantly Black neighborhoods and its association with violence and health outcomes [27,43,44]. The long-standing racial disparities in violent and firearm victimization in the U.S. are tied to other dimensions of structural inequality, and suggest action is needed to address these enduring differences by race [37]. At the same time, there is no clear evidence for causal pathways between the rise in homicide and the growth in the Black-White inequality in firearm homicides that started in 2015 and accelerated during the COVID-19 pandemic. Rosenfeld argues that the recent upturn in homicide and violent crime started in 2015 and can be explained by two mechanisms [45]. The first is an overall reduction in policing effectiveness stemming from the reduced proactive enforcement activity and compromised police legitimacy, with racial minority communities being affected the most. The second explanation for the increase in homicide and violent crime is the opioid epidemic and its impact on illegal drug markets. While the opioid epidemic has affected large swaths of the rural White population [46], its connection to the dramatic racial gap in firearm homicides is unclear.

The analysis presented here has several limitations. First, we only look at Black and White firearm homicide rates due to the unavailability of a more granular indication of race and ethnicity. A more advanced study would specifically look at firearm homicide mortality among other racial and ethnic groups, particularly Hispanics. Second, given that the Black population in the U.S. is experiencing disproportionately more concentrated disadvantage, further studies might look at the long-term trends of firearm homicides while simultaneously controlling for socioeconomic characteristics of neighborhoods. An extensive literature already documents these trends at the level of states, counties, and selected cities [3235]. More research is needed to understand how local contexts and policies are associated with the racial gap in firearms homicide. Policy evaluations and quasi-experimental studies are required to identify which interventions are effective at reducing these disparities over time.

High levels of firearm homicide victimization in the Black population in the United States appear to be strongly implicated in population-level life expectancy [22]. This study demonstrates that during surges in gun violence in the United States, the Black population experiences thousands of excess deaths that could be avoided if public health and policy efforts were effective at reducing the racial gap in homicide victimization for people living in the U.S.

Data Availability

The replication package containing data and code is available here: https://github.com/alexeyknorre/racial_gap_gun_homicides.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Claudio Dávila-Cervantes

14 Aug 2025

PONE-D-25-38735Unequal by the gun: Four decades of the Black-White firearm homicide gapPLOS ONE

Dear Dr. Knorre,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

ACADEMIC EDITOR:

The peer-review process has been completed. The reviewers have requested some major issues that need to be addressed before the manuscript can be considered for publication. The detailed feedback from reviewers is included below/attached for your reference.

We kindly request that you address these points in your revised manuscript and provide a response letter detailing the changes made. Please submit the revised version of your manuscript along with the response letter through our submission system.

We look forward to receiving your revised manuscript.

==============================

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Academic Editor

PLOS ONE

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[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: MAJOR

Abstract: The abstract leaves a lot to be desired:

• missing “Background” “Methods” “Results” and “Conclusion” sections.

• the data are national for the U.S.

• that there are two calendar-year inflections in increases in the White:Black comparison (“mid-1980s” and 2014).

• that several years had greatest Black vs. White disparity (2020, 2021 and 2023).

• that 31,202 homicides cited as the disparity without indicating over what years and geography (instead expressing the difference with age-adjusted rates).

• “Black men were 10.38 times more likely than White men to die from firearm homicide” can be interpreted to mean that a homicide attempt was 10x more likely to result in death.

• “The firearm homicide rate in males was 10 times higher in Blacks than Whites” would be more accurate. [a 2 decimal number is not necessary].

• The “number of excess Black firearm homicide deaths” should be “rate of excess …” and “homicide deaths” should be “homicides.”

Methods: Superbly explained.

Results: In general, adequately presented.

Discussion: In general, adequately presented. Not included as potential causes are firearm theft rates differences, varying state regulations in firearm purchasing and ownership, firearm industry policies regarding sales racial pitches, and possibly mass shooting differences in Blacks and Whites.

MINOR

In general, “women” should be “females” and “men” (used 19 times) should be “males.”

“100 thousand” should be “100,000”.

Introduction:

• What is meant by “credit” and “other institutions” among the racial inequalities?

• What does “top 10% of block groups” mean?

• How does the reader compare the “greater than 5%” gun injury or death rate in Chicago and Philadelphia with other cities and rural settings if comparative values are not provided?

• “in the decade prior” dangles without specifying the actual years

• How do “shifts in the age composition” explain the life-expectancy gap between Whites and Blacks?

• “In 2016, homicide mortality for Black males was 20 times higher than for White males.” In the U.S.?

• “`Firearms are the most significant contributor to homicides among youth and young adults in the U.S., with firearms accounting for approximately 80.5% of all homicides.” 80.5% is quite finite and not “approximate”.

• “”… we follow a similar design and examine the Black-White ratio of firearm homicide mortality rates between 1979 and 2023 after adjusting for sex, age, and year effects.” Since age is in years, “year” should probably be “calendar year”. Other uses of “year’ in rest of manuscript should probably specific “calendar year”.

Table 1 title/legend lacks description of “Counterfactual”.

Line 172: “similar’ would be more appropriate than “same”.

Lines 173-174: “Excluding the period of 1989-1993, the decrease in firearm homicide rates for Black males is less pronounced than for other groups” is a qualitive statement that is difficult to understand. If anything, the changes after 2000 suggest that Black and White males had similar trends.

Line 207: delete “there’.

Table 1: From 1991-1993 to 2018-2020, the excess number of firearm homicides in Blacks decreased in 10-23 year-old, with a total decrease in excess deaths of 2,901. That young Blacks were spared the overall increase from 1991-1993 to 2018-2020 should be recognized and potentially discussed, albeit it is <10% of the overall excess (of all ages).

Figure 3: Ideally the White and Black data should be shown on the same graph and given the overlap would only be for 2021-2022 for the single race data of ages 15-19 and 20-24, this option is feasible.

Figure 4: Does not specify age range.

Acknowledgements: Why does only one of the two authors acknowledge the source of financial support?

References: Their formatting and content is inconsistent, with doi in some an not others and some titles capitalized and in others not. Internet citations lack date of access. #13 had two doi citations. #9 and #18 repeats the e number. #23, #24, #37 and #40 appear to be incomplete.

Reviewer #2: This is an excellent paper that documents the racial disparities in firearm victimization over time and shows the three different peak differences where the # of excess deaths among blacks is staggering. In this regard, the paper nicely improves some recent work by Piquero and Roman, also using the CDC Wonder data, but does so by looking at longer time periods, dealing with the racial category changes, and calculating excess deaths. I have four comments for the authors to consider.

1. By my calculation, the total # of excess deaths in the thee key peak periods that the authors look at is 81,291. I think it may be helpful for the authors to contextualize this. One way to do this is the following. The Dallas Cowboys NFL Stadium holds around 80,000 people (can be expanded for standing room only). Taking the # of excess deaths means that all those deceased persons can fit in the stadium. There likely is a better way to say this but hopefully the authors get the point. That kind of visual, however depressing, is powerful.

2. I know the authors did not do anything w/ Hispanic ethnicity (though they could look at it in more recent times). Could they do a subset analysis of Hispanic ethnicity (I am not requiring it), but if not at least comment on it.

3. The paper lends heavily on structural explanations of the differential risk of firearm victimization. I do not discount that this matters, however, people still have to pick up guns AND use them. There still remains some sort of individual-level decision making here, whether its code of the street, self-control, etc. I think the authors need to point that out.

4. I like descriptive papers. A lot. Yet, not much policy commentary is here. I think a sentence or two would be useful.

Reviewer #3: Overall Comments:

The authors of this manuscript examine trends in Black–White disparities in firearm homicide over four decades. While such disparities are well-documented in the literature, this study contributes by providing more precise estimates—specifically, ratios quantifying the disparity—and by calculating measures of excess mortality.

However, I am concerned by the absence of a substantive investigation into racism as a driver of these trends. The framing largely gives a cursory mention of socioeconomic and neighborhood-level characteristics without adequately addressing the structural and systemic racism that underlies and shapes these factors. Without explicitly engaging with racism as a root cause, the analysis risks reinforcing race as a proxy for other factors rather than interrogating the historical and ongoing policies, practices, and power structures that produce and maintain these disparities.

Integrating a discussion of racism—at minimum through a theoretical lens, but ideally via an empirical consideration—would strengthen the manuscript, situating the observed trends within the broader social and political context that creates disparities in firearm homicide.

Introduction:

1. This section is a bit lengthy and redundant in places. For example, the authors include a lengthy discussion the place-boundedness of these racial disparities, but since this is not the focus of the paper, this section could be reduced or moved to the discussion.

2. The introduction is missing several references to existing literature on firearm homicide disparities. These may also fit in the discussion.

a. Wong B, Bernstein S, Jay J, Siegel M. Differences in racial disparities in firearm homicide across cities: the role of racial residential segregation and gaps in structural disadvantage. Journal of the National Medical Association. 2020 Oct 1;112(5):518-30.

b. Conrick KM, Adhia A, Ellyson A, Haviland MJ, Lyons VH, Mills B, Rowhani-Rahbar A. Race, structural racism and racial disparities in firearm homicide victimisation. Injury prevention. 2023 Aug 1;29(4):290-5.

c. Siegel M, Rieders M, Rieders H, Moumneh J, Asfour J, Oh J, Oh S. Measuring structural racism and its association with racial disparities in firearm homicide. Journal of racial and ethnic health disparities. 2023 Dec;10(6):3115-30.

d. Knopov A, Rothman EF, Cronin SW, Franklin L, Cansever A, Potter F, Mesic A, Sharma A, Xuan Z, Siegel M, Hemenway D. The role of racial residential segregation in Black-White disparities in firearm homicide at the state level in the United States, 1991-2015. Journal of the National Medical Association. 2019 Feb 1;111(1):62-75.

e. Bottiani JH, Camacho DA, Lindstrom Johnson S, Bradshaw CP. Annual research review: youth firearm violence disparities in the United States and implications for prevention. Journal of child psychology and psychiatry. 2021 May;62(5):563-79.

Methods:

3. Why did the authors not conduct formal trend analyses, such as via Joinpoint? This would allow the conclusions regarding spikes to be more sound.

Results:

4. The terminology of “fatal shootings” is new in this section and could be misleading. Please specify the unit is firearm homicides per 100 thousand people. Additionally, were these truly whole numbers? That is “7.0 per 100 thousand;” if not, please include the precise numbers.

5. Please be consistent in using terms related to sex (male, female) compared to gender (men, women).

6. It would be helpful to discuss in what ways trends changed with the change in race definitions.

7. In Figure 1, the difference in the dashed line between single race and single + multi race is difficult to distinguish. Consider making one a dotted line. Additionally, the major differences in y-axes make it difficult to make visual comparisons.

8. In Figures 1-2, what is the unit for the y-axis? Per 100 thousand?

Discussion

9. The discussion needs expanded explanations for these trends. Remarkably, the word “racism” does not appear at all in the manuscript. Please see: https://www.healthaffairs.org/content/forefront/racism-new-standard-publishing-racial-health-inequities. There is an extremely large body of literature examining the association of structural racism with disparities in firearm homicide that provides several causal explanations.

10. “At the same time, there is no clear causal evidence for the rise in homicide and the growth in the Black-White inequality in firearm homicides that started in 2015 and accelerated during the COVID-19 pandemic.” This sentence is a bit misleading; I believe the authors mean to say that this literature is nascent, and we are still identifying the causal pathway. However, it may be misinterpreted to mean that there is no causal relationship at all, rather than that the current evidence base is limited and evolving. Clarifying that the body of research is emerging, and that causal mechanisms are still being explored, would help avoid confusion.

11. Regarding the section on poverty, please also see:

a. Ellyson AM, Rivara FP, Rowhani-Rahbar A. Poverty and firearm-related deaths among US youth. JAMA pediatrics. 2022 Feb 1;176(2):e214819-.

b. Barrett JT, Lee LK, Monuteaux MC, Farrell CA, Hoffmann JA, Fleegler EW. Association of county-level poverty and inequities with firearm-related mortality in US youth. JAMA pediatrics. 2022 Feb 1;176(2):e214822-.

12. Please remove the recommendation that future studies control for neighborhood socioeconomic characteristics for two reasons. First, an extensive body of literature already examines neighborhood characteristics and disparities in firearm homicide. Second, rather than controlling for these characteristics, it would be more useful for future research to identify which specific characteristics are associated with higher or lower disparities.

**********

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Reviewer #1: Yes:Archie Bleyer

Reviewer #2: No

Reviewer #3: No

**********

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Decision Letter 1

Claudio Dávila-Cervantes

5 Dec 2025

PONE-D-25-38735R1Unequal by the gun: Four decades of the Black-White firearm homicide gapPLOS ONE

Dear Dr. Knorre,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jan 19 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Claudio Alberto Dávila-Cervantes, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

Reviewer #4: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Partly

Reviewer #4: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2:

Reviewer #3: The authors’ response—adding a sentence citing literature that "invokes" structural racism but declining to use the term “racism” explicitly because of concerns about causal certainty—does not address the core issue. The manuscript frames socioeconomic and neighborhood-level characteristics in cursory terms without situating them within the power structures, policies, and historical practices that produce these factors. In the fields of public health, medicine, criminology, and social work, among others, structural racism is widely understood as the organizing framework through which disparities in housing, policing, economic opportunity, and access to safety are generated, even when a single dataset cannot trace every mechanism in detail. Without naming racism, the introduction and discussion risk reducing racial disparities to proxy variables rather than recognizing the root causes documented across multiple disciplines. This omission undermines the manuscript’s scientific clarity and leaves it out of step with current scientific expectations for accurately naming and addressing the structural drivers of racial health inequities, namely structural racism.

Reviewer #4: I did not review the first draft of this paper, but I believe the revised manuscript has adequately addressed the reviewers’ comments. The paper identifies important emerging patterns in U.S. firearm homicide mortality and employs methodologically sound and sophisticated analytical approaches. The racial disparities documented here have significant policy and theoretical implications, and future research will be needed to unpack the mechanisms driving these widening disparities.

It would also be helpful for the author to specify where the data and replication files will be made publicly available once the paper is published.

**********

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Reviewer #2: No

Reviewer #3: No

Reviewer #4: No

**********

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Decision Letter 2

Annesha Sil

11 Jan 2026

Unequal by the gun: Four decades of the Black-White firearm homicide gap

PONE-D-25-38735R2

Dear Dr. Knorre,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Annesha Sil, Ph.D.

Staff Editor

PLOS One

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #3: All comments have been addressed

Reviewer #4: All comments have been addressed

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Reviewer #3: Yes

Reviewer #4: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

Reviewer #4: Yes

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Reviewer #3: Yes

Reviewer #4: Yes

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Reviewer #3: Yes

Reviewer #4: Yes

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Reviewer #3: Thank you for the revisions and for engaging with this comment. I appreciate that the manuscript now explicitly uses the term “structural racism” at least once. While the framing remains cautious and somewhat indirect, the added language provides clearer conceptual grounding than the prior version. I have no further comments on this point.

Reviewer #4: No additional comments, the authors have properly addressed all the reviewers' comments in this submission.

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Reviewer #3: No

Reviewer #4: No

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Acceptance letter

Annesha Sil

PONE-D-25-38735R2

PLOS One

Dear Dr. Knorre,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS One. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

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* There are no issues that prevent the paper from being properly typeset

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Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr Annesha Sil

Staff Editor

PLOS One

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: racial_gap_in_shootings_rev1_response.pdf

    pone.0341645.s001.pdf (147.4KB, pdf)
    Attachment

    Submitted filename: racial_gap_response_v2.pdf

    pone.0341645.s002.pdf (88.6KB, pdf)

    Data Availability Statement

    The replication package containing data and code is available here: https://github.com/alexeyknorre/racial_gap_gun_homicides.


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