General Strain and Reported Gun Ownership Before and During the COVID-19 Pandemic: Implications for Crime and Public Safety

Abstract

The COVID-19 pandemic has been one of the most globally disruptive social events in recent history, bringing widespread lockdowns, restrictions on movement, remote work, mass vaccination campaigns, and millions of deaths worldwide. These unprecedented circumstances have reshaped many aspects of social life, including perceptions of safety and firearm ownership. This study examines changes in reported gun ownership before and during the COVID-19 pandemic in the United States, using binary logistic regression analyses of General Social Survey (GSS) data from 2018 and 2021. Analysis revealed that reported gun ownership remained stable at approximately 35% in both years. However, the demographic and social profile of gun owners shifted significantly. Demographic factors such as sex, US birth, marital status, and income consistently predicted ownership in both years, while race, middle-class identification, and political party affiliation emerged as significant predictors only during the pandemic, with Democrats becoming significantly less likely to report gun ownership. The results demonstrate how social crises can reshape the composition of firearm owners rather than overall rates, with implications for public policy and safety.

1. Introduction

Disruptive worldwide crises such as the COVID-19 pandemic have significant effects on societies. Biological crises, such as epidemics and pandemics, natural disasters like hurricanes and tornadoes, and sociopolitical events like wars can all disrupt daily life [1]. One important piece of context for these disruptions is the long-documented decline in public trust in government and social institutions. For example, the Pew Research Center [2] reported that public trust in the U.S. government has decreased steadily since its peak in 1958. Similarly, Long and Sitkin [3] argue that declining trust in institutions reduces society’s ability to respond to challenges such as climate change and pandemics.

The COVID-19 pandemic was a unique case of disruption that changed work, education, and social interaction. Stay-at-home restrictions moved classrooms into online environments, relocated work into private homes, and disrupted normal routines by limiting mobility and access to public places. These restrictions reshaped daily behavior and also had effects on crime and public safety. Official statistics show decreases in violent crime and property crime in the United States during the first year of the pandemic, with violent crime declining by 22% and property crime by 7% [4]. In large U.S. cities such as Washington, D.C., Chicago, New York, and Los Angeles, theft, fraud, and robbery also declined between 2020 and 2022 [5].

Although many scholars have studied the effects of COVID-19 on different types of crime, including violent and property offenses [6,7], less attention has been given to gun ownership during this time. Previous studies suggest that disruptive events and perceived threats often coincide with increases in gun purchases. Johnson and Lee [8] and Thompson [9] showed that gun acquisitions rise during riots or social unrest, especially when people believe institutional responses are insufficient. This means that in times when trust in institutions is already weak, owning a firearm may be seen as a rational response to insecurity.

There are, however, differing perspectives within the research field. Some scholars argue that gun ownership is primarily cultural, shaped by long-standing demographic and social patterns rather than by situational threats [10]. An alternative perspective suggests that collective crises, such as pandemics, can reshape the social determinants of gun ownership by amplifying strains related to insecurity, inequality, and declining social trust [11]. These contrasting views highlight the importance of examining whether the underlying factors influencing ownership have shifted.

To address these limitations, this study investigates the relationship between factors related to general strain theory and gun ownership. Using data from the General Social Survey for 2018 and 2021, this study provides additional information on the impact of the COVID-19 pandemic on gun ownership. This study also examines potential shifts in the social determinants of gun ownership during the pandemic. The results provide evidence that during the pandemic, both demographic and social determinants of ownership shifted. This study has practical significance, since a better understanding of changes in factors that affect gun ownership due to tumultuous social events, such as natural or biological disasters, could help in developing more effective policies surrounding the issue. By gaining deeper insight into who was more likely to acquire guns during the pandemic and the potential drivers of gun ownership, policymakers could use this knowledge to create more effective legislation to respond in times of crisis and evaluate levels of preparedness for future events.

2. Literature Review

According to Gresham and Demuth [12], there are 93 guns per 100 U.S. citizens. A survey conducted by the Pew Research Center [2] shows that about four-in-ten adults (42%) report that there is a gun in their household, with three-in-ten saying they personally own a gun and 11% saying they do not own a gun but someone else in their household does. Gun ownership varies across demographic groups: about 39% of men and 22% of women personally own a gun; 36% of whites, 24% of blacks, and 15% of Hispanics report owning a gun. White men are especially likely to own a gun (48%), compared with white women and nonwhite men (24% each) and nonwhite women (16%) [2]. While this represents a substantial number of gun owners, ownership is not evenly distributed: some individuals possess multiple firearms. For example, Gresham and Demuth [12] report that in 2015, 39 percent of all guns were owned by 8 percent of gun owners, illustrating that a relatively small portion of the population accounts for a disproportionate share of firearms.

Summerfield [13] highlights that war impacts mental health beyond trauma by disrupting social, economic, and cultural life, and concludes that effective responses should restore community and social structures rather than over-medicalize normal reactions.

An important factor in understanding gun ownership in the U.S. is exploring the reasons why Americans choose to own guns and which subpopulations own them. According to the Pew Research Center [2], 67 percent of U.S. adults who own guns reported personal safety or protection as their primary reason for ownership, 38 percent reported hunting as their primary reason, and 30 percent reported recreation or sport as their primary reason. This clarifies that these percentages represent distinct groups based on their main motivation for owning a firearm. Furthermore, in terms of demographic characteristics, middle-aged or older men were more likely to own a handgun compared to younger men or women. Individuals with politically conservative views were more likely to be gun owners compared to those with liberal views [2]. Educational attainment also plays a role, as the Pew Research Center [2] found that Americans with higher levels of education are less likely to own guns.

Additionally, Cao et al. [14] point to resources and socialization as significant factors in gun ownership. For example, individuals who were exposed to guns as children, or who had family members who were gun owners, are likely to become gun owners themselves. Additionally, Cao et al.’s [14] research suggests that those with higher levels of educational attainment are less likely to own a gun. Montano and Savitt [15] use COVID-19 as a case study to show how categorizing pandemics as “disasters” shapes policy responses and exposes the limitations of existing disaster frameworks. They conclude that COVID-19 does not fully fit the usual idea of a disaster, and that governments need clearer or new categories to better guide responses to pandemics.

An emerging body of literature has begun to explore changes in firearm sales during the pandemic. Lang and Lang [16] conducted a preliminary analysis on this topic and found an increase in firearm background check rates between March and June 2020 that differed from earlier instances. Furthermore, trends in gun purchases in 2020 were seemingly bipartisan, with similar effects observed in Republican and Democratic states [16]. Similarly, Crifasi et al. [17] examined gun purchasing behaviors in the initial months of the pandemic, revealing a notable increase in gun purchases from March to mid-July 2020. Miller et al. [10] used data from the 2021 National Firearms Survey, a comprehensive online study encompassing 2020 U.S. adults, to identify trends and motivations behind firearm purchases during the COVID-19 pandemic. Their research showed a noticeable change in firearm purchases during the initial months of the pandemic, estimating that around 4.3 million U.S. adults, approximately 1.7% of the adult population, acquired a firearm between January and May 2020. This revealed a substantial 64% increase compared to the same period in 2019 [10].

Additionally, Miller et al. [10] explored how demographic factors like gender, race, political affiliations, and pandemic-related stressors influenced increases in firearm purchases. For example, they noted that women, non-Hispanic Black adults, strongly conservative individuals, and those experiencing moderate to severe anxiety or depressive symptoms were more inclined to acquire firearms [10]. However, their study lacked historical data preceding the pandemic, limiting insights into whether these trends were pandemic-specific or pre-existing. Similarly, Roess et al. [18] investigated factors influencing firearm purchasing during the pandemic by examining the relationship between socio-demographic variables, anxiety levels, political affiliations, and the decision to purchase firearms. Their findings indicated that these socio-demographic factors were interconnected and underlie the increase in firearm purchases during the pandemic.

Alternatively, Hill et al. [19] approached the issue of increased gun purchases during the pandemic from a social epidemiological standpoint by examining how gun acquisitions could be understood as part of the so-called “pandemic arms race.” Their study focused on the role of social networks and individuals’ perceptions in driving this phenomenon. Their findings indicate that the rise in gun sales may have been influenced by psychosocial factors such as anxiety, apprehension, and a perceived need for self-defense, which may have been exacerbated by the difficulties and uncertainties brought on by the pandemic. Similarly, Caputi et al. [20] investigated firearm purchasing during the COVID-19 pandemic, focusing on how information diffusion influenced individuals’ decisions to buy guns during this period. This was achieved using an “infodemiology” approach, which is analyzing patterns in online information and digital communication to understand how exposure to certain narratives, such as fear or uncertainty, affected public behaviors. Their findings showed that the spread of information online significantly impacted people’s decisions, creating what they called collateral crises of gun preparation [20,21]. Moreover, Caputi et al. [20], who also stressed the significance of infodemiology in understanding the junction between the pandemic and increased weapons preparation, provided further support for this conclusion.

A limitation of these studies is their failure to incorporate pre-pandemic data to better distinguish pandemic-related changes in trends from previously existing patterns. The present study addresses this issue by utilizing GSS data from 2018. Additionally, while some of the research findings discussed above indicate heightened stress levels and concerns about personal safety during the COVID-19 pandemic, additional research is needed to understand how individual perceptions of safety and the perceived need for self-defense may vary across the U.S. population based on demographic factors such as race, age, marital status, and gender. The present study addresses this limitation as well.

Robert Agnew [11] identified three major strain types in his original introduction to General Strain Theory (GST). These include instances where others prevent an individual from achieving positively valued goals, remove (or threaten to remove) positively valued stimuli, or introduce (or threaten to introduce) an individual to negatively valued stimuli [11]. For many individuals, the disruption of the COVID-19 pandemic required putting their daily activities and plans on hold, whether that was because of ‘stay-at-home’ directives, employment layoffs, unexpected economic challenges, declines in mental or physical well-being, or a combination of these factors [22]. While no two experiences are exactly alike, many adults felt the impacts of role strain and role compartmentalization during this period as they struggled to adapt to shifting obligations regarding work, adopting new roles and responsibilities within their family unit, and coping with lost roles, either temporary or permanent [23].

Agnew [11] identified four factors that determine how influential adverse events can be for individuals regarding their strain experience. Adverse events that are greater in magnitude, recent, of long duration, and clustered in time have more influence on individuals and can have a cumulative effect on the resulting amount of strain they experience [11]. The magnitude of the COVID-19 pandemic as an adverse event varies based on individual experiences, but according to GST, ‘magnitude’ can refer to the perceived gap between one’s goals and reality, the amount of loss, or the amount of discomfort inflicted by the adverse event [11]. An additional limitation of previous studies is that they have not explicitly incorporated a detailed consideration of general strain theory concepts. The study addresses this limitation.

In terms of recency and duration, at the initial onset of the COVID-19 pandemic, it was uncertain how fast or far the virus would spread. Once it began to acutely impact Americans, it was unclear how long it would last [24]. While recent events are often considered more impactful than older ones [11], during this time, the adverse event introduced a new temporality that outlasted the expected duration for many. The lack of tolerance for uncertainty has been identified as a psychological process associated with pandemic anxiety [25]. Adverse events that are clustered closely in time tend to have a stronger impact on the experience of strain and lead to more negative outcomes, as they can produce feelings of overwhelm that make coping difficult [11]. While the COVID-19 pandemic was an adverse event in and of itself, it also led to several additional adverse events at the individual level that were clustered within a period of less than two years [20,25].

Gun and ammunition purchases had the highest increase during the first phase of the pandemic (March–July 2020), with 35% of sales going to individuals buying firearms for the first time [17]. A study examining the psychosocial impacts of the COVID-19 pandemic also identified increased rates of anxiety, depression, stress, and suicidal ideation as being highest between March and May 2020; however, these symptoms began to flatten over time [22]. This indicates that the early months of the pandemic were uniquely stressful, which could potentially explain the increase in purchases of gun purchases during this same period.

Purchasing firearms can also be seen as a coping strategy, both behaviorally and emotionally. The behavior of purchasing guns and ammunition during the global crisis may have afforded individuals a sense of perceived control over their personal safety and allowed them to protect their positively valued stimuli (e.g., loved ones and personal property). Additionally, acquiring firearms can be viewed as an emotional coping strategy, as individuals were acting on negative thoughts, feelings, and emotions that resulted from a loss of safety, increased vulnerability, and reduced personal autonomy. Saha et al. [22] discuss hoarding and stockpiling behaviors associated with pandemic anxiety, and gun/ammunition purchasing during this time period could be seen as an alternative expression of this for some.

To sum up, these studies show that while gun purchasing rose during the pandemic, the mechanisms, demographic patterns, and social determinants remain contested [10,19]. Moreover, most studies lacked pre-pandemic baseline data, making it difficult to assess whether changes were unique to the pandemic or the changes were part of longer-term trends. This study addresses these gaps by comparing nationally representative data from the 2018 and 2021 General Social Surveys to examine shifts in demographic and social determinants of gun ownership, using general strain theory.

3. Hypotheses

This study aims to examine changes in the demographic and social factors that influenced reported gun ownership both before and during the COVID-19 pandemic. Previous research explored these factors as they related to gun purchasing patterns during the pandemic, but was limited by the lack of historical data needed to compare these findings with trends prior to 2020. The following hypotheses were developed based on specific demographic and social factors identified in the prior research discussed above and, guided by Agnew’s GST, are intended to account for the influences of collective and cumulative psychosocial strain experienced by many during the COVID-19 pandemic. Specifically, this study proposes the following hypotheses:

Hypothesis 1:

Demographic determinants of gun ownership changed during the COVID-19 pandemic compared to 2018.

The pandemic might have influenced individuals’ perceptions of safety and their need for self-defense differently based on race, age, marital status, and gender. For example, certain age groups or communities might have experienced increased feelings of vulnerability compared to others, leading to differences in their attitudes toward gun ownership and the potential need to own firearms. This hypothesis assumes that pandemic-induced changes in daily life and security perceptions would alter gun ownership patterns across different demographics [10].

Based on the tenets of GST, it can be inferred that demographic changes in gun ownership may be observed among groups that experienced high levels of strain before the pandemic, leading to cumulative strain with the onset of COVID-19 and the additional stresses it imposed. Although such strain could occur across any demographic group, including race, age, marital status, and gender, at the population level, this study posits that it will likely be most apparent among historically marginalized groups in American society, such as Black and Latino groups, as well as women. Different groups in society may experience varying degrees of change in their willingness to buy and keep guns due to their unique experiences in critical situations. Overall, this hypothesis proposes that the demographic determinants of gun ownership during the COVID-19 pandemic differed from those observed in 2018 and varied across social statuses and backgrounds [26].

Hypothesis 2:

Social determinants of gun ownership changed during the COVID-19 pandemic.

This hypothesis is derived from the understanding that the pandemic’s economic, social, and psychological impacts could influence individuals’ attitudes toward gun ownership. Changes in subjective socioeconomic class, religiosity, education, political affiliation, anxiety levels, and happiness might have led to shifts in perceived needs for personal protection, as these are all associated with push factors related to social strain outlined in GST [11]. For instance, concerns about public safety could affect individuals’ decisions to own firearms, as these circumstances threaten the loss of positively valued stimuli individuals have worked to achieve [11,21]. This hypothesis suggests that the pandemic-related shifts in these social determinants would affect gun ownership. The hypothesis is based on the idea that the spread of COVID-19 may cause various changes in one’s views toward economic stability, social status, and physical safety. These psychosocial shifts can result from changes in subjective measures such as economic status, religiosity, taxation, level of education, political beliefs, fear, and well-being [27]. For example, increased concerns about the condition of the economy and public safety may influence people’s decisions about purchasing firearms, indicating that changes may occur in the impact of these social and economic factors during the pandemic [27].

4. Materials and Methods

4.1. Data

The data utilized for this analysis were drawn from the General Social Survey (GSS) conducted by NORC at the University of Chicago [28,29]. The GSS is a nationally representative, repeated cross-sectional survey that has been conducted in the United States since 1972 to monitor and explain trends in American attitudes, opinions, and behaviors. Data from the 2018 GSS Cross-Section and the 2021 GSS Cross-Section (Release 2A) were used. The 2018 dataset represents reported gun ownership before the pandemic since it is the most recent wave preceding the global disruption, as the GSS is conducted biennially. The 2021 dataset includes responses collected between December 2020 and May 2021, representing the early phase of the pandemic. This dataset was used since it was the most recent data available at the time of this study.

4.2. Variables

4.2.1. Dependent Variable

The dependent variable “OWNGUN2” is dichotomous and measures whether the respondent reports having a gun in their home. It is coded as 0 = no, 1 = yes. This variable captures household gun presence rather than personal ownership, meaning it includes guns owned by any household member.

4.2.2. Independent Variables

The independent variables selected for the analysis include demographic, social class, and social-psychological measures.

Demographic variables include: RACE (race of respondent, coded as 1 = White, 2 = Black, 3 = Other); BORN (was respondent born in the US, coded as: 1 = Yes, 2 = No); AGE (age of respondent, a continuous variable representing the respondent’s age in years); MARITAL (respondent’s marital status, coded as 1 = Never married, 2 = Married, 3 = Widowed, 4 = Divorced, 5 = Separated); and SEX (respondent’s sex, coded as 1 = Male, 2 = Female).

Social class and economic variables include: CLASS (respondent’s subjective class identification, coded as 1 = Lower class, 2 = Working class, 3 = Middle class, 4 = Upper class); CONINC (family income in constant dollars, a continuous variable adjusting for inflation to allow comparison across years); and EDUC (respondent’s highest year of school completed, a continuous variable ranging from 0 to 20 years).

Social-psychological variables include: ATTEND (frequency of attendance at religious services), which is a continuous variable with higher values indicating more frequent attendance; FEAR (is the respondent afraid of walking at night in their neighborhood), coded as a continuous measure where higher values indicate greater fear.; HAPPY (respondent’s general happiness, a continuous variable where higher values indicate greater happiness); and PARTYID (respondent’s political party affiliation, coded as 1 = Strong Democrat, 2 = Not strong Democrat, 3 = Independent close to Democrat, 4 = Independent, 5 = Independent close to Republican, 6 = Not strong Republican, 7 = Strong Republican, or 8 = Other party).

Categorical variables (RACE, BORN, MARITAL, SEX, CLASS, PARTYID) were entered as factors in the logistic regression models, with SPSS 28.0.1.0 (142) creating indicator variables automatically. Reference categories were: Black (for RACE), Not born in US (for BORN), Never married (for MARITAL), Female (for SEX), Upper class (for CLASS), and Other party (for PARTYID).

In the context of this study, General Strain Theory (GST) provides a useful framework for understanding reported gun ownership as a coping response to stress and insecurity. According to Agnew [11], individuals experiencing strain, such as fear, uncertainty, or perceived threats, may adopt behaviors intended to restore control or reduce negative emotions. The COVID-19 pandemic created widespread disruptions in daily life, economic instability, and threats to personal safety, all of which can be viewed as sources of strain [22]. Within this framework, acquiring or owning a firearm can be viewed as an adaptive coping strategy aimed at reducing perceived vulnerability and maintaining a sense of security during times of crisis.

4.3. Sample

In both the 2018 and 2021 GSS datasets, cases with missing or invalid responses were handled using pairwise deletion. This approach retains all cases with valid responses on the dependent variable (reported gun ownership) and uses whatever valid data are available for each independent variable, thereby maximizing sample size and statistical power.

For the descriptive analysis of reported gun ownership rates, the 2018 sample included 1530 respondents who provided valid responses to the gun ownership question (out of 2348 total cases in the dataset), representing a 65.2% valid response rate. The 2021 sample included 3912 respondents with valid gun ownership responses (out of 4032 total cases), representing a 97.0% valid response rate. The higher response rate in 2021 reflects changes in survey administration and question format.

For the logistic regression analyses, pairwise deletion was employed, meaning that the effective sample size varied slightly across predictors depending on the pattern of missing data. The regression models included all cases with valid responses on the dependent variable (n = 1530 in 2018; n = 3912 in 2021), with each predictor utilizing whatever valid data were available for that specific variable.

Missing values on the gun ownership variable were primarily due to respondents selecting “don’t know,” or “refused,” or being classified as “not applicable” based on survey skip patterns. While pairwise deletion maximizes statistical power by retaining cases with partial data, it assumes that data are missing at random (MAR) conditional on observed variables. If missingness is related to unmeasured factors such as reluctance to disclose gun ownership due to stigma or privacy concerns, estimates may be biased [29]. Additionally, gun ownership is a sensitive topic that may be subject to social desirability bias, with some respondents potentially underreporting ownership. Therefore, results should be interpreted with these potential limitations in mind.

4.4. Analytic Strategy

Binary logistic regression was conducted separately for the 2018 and 2021 GSS datasets to identify predictors of reported gun ownership and to assess whether these predictors changed across the two periods. The dependent variable was reported gun ownership (1 = reports owning a gun, 0 = does not report owning a gun). Independent variables included age, sex, race, marital status, US birth, education, family income, subjective class identification, religiosity (frequency of religious attendance), fear of neighborhood crime, general happiness, and political party affiliation.

Logistic regression is appropriate when the dependent variable is dichotomous, as it models the log-odds of the outcome and produces odds ratios that indicate the multiplicative change in odds associated with a one-unit change in each predictor [30]. Categorical predictors were entered as indicator variables with designated reference categories. The two models (2018 and 2021) allowed us to determine which demographic and social factors predicted reported gun ownership and to compare these predictors across the two time periods to assess pandemic-related changes.

Model fit was assessed using the −2 Log Likelihood, model chi-square, and Nagelkerke pseudo-R², which indicates the proportion of variance in the dependent variable explained by the predictors. Statistical significance was set at α = 0.05 for all tests, with p < 0.10 noted as marginally significant where relevant.

5. Results

5.1. Descriptive Statistics: Reported Gun Ownership Rates

Before examining predictors of reported gun ownership, we first assessed whether overall rates changed between 2018 and 2021.

Table 1. Comparison of Reported Gun Ownership Between 2018 and 2021.

Year	Reported Gun Ownership (%)	n	Total N	p-Value
2018	35.1	537	1530	0.86
2021	35.4	1383	3912

presents the comparison of reported gun ownership across the two time periods. The analysis revealed that reported gun ownership remained remarkably stable, with 35.1% of respondents in 2018 (n = 537 out of 1530) and 35.4% in 2021 (n = 1383 out of 3912) reporting gun ownership. A two-proportion z-test indicated this difference was not statistically significant (z = −0.18, p = 0.86), suggesting that aggregate reported gun ownership rates did not change meaningfully during the pandemic period.

This finding was unexpected given the widespread reports of increased firearm sales during the COVID-19 pandemic and the theoretical prediction that pandemic-related strain would drive increased reported gun ownership. The stability in reported ownership rates suggests that while the pandemic may have prompted some first-time purchases, overall prevalence remained constant, possibly due to existing gun owners maintaining their firearms while non-owners largely remained non-owners. This pattern indicates that the pandemic’s impact may have been more evident in who reports owning guns rather than how many people report owning guns. Therefore, the following analyses examine whether the demographic and social characteristics of gun owners shifted during the pandemic period.

5.2. Hypothesis 1: Demographic Determinants of Reported Gun Ownership

Hypothesis 1 posited that the demographic determinants of reported gun ownership would differ between the pre-pandemic period (2018) and during the pandemic (2021).

Table 2. Logistic Regression Results: Predictors of Reported Gun Ownership (2018 and 2021).

Variable	2018 (n = 1530)			2021 (n = 3912)
	OR	95% CI	Sig.	OR	95% CI	Sig.
Demographics
Age	1.006	[0.997, 1.014]	0.179	1.001	[0.999, 1.003]	0.237
Sex (Male)	1.813	[1.423, 2.311]	<0.001	1.532	[1.322, 1.776]	<0.001
Race (White)	1.512	[0.928, 2.463]	0.097	1.970	[1.444, 2.689]	<0.001
Race (Other)	1.318	[0.748, 2.322]	0.339	1.854	[1.274, 2.696]	0.001
Born in US	8.216	[4.522, 14.928]	<0.001	3.920	[2.862, 5.368]	<0.001
Education	0.991	[0.967, 1.016]	0.500	1.008	[0.997, 1.019]	0.146
Marital Status
Married	2.990	[2.101, 4.257]	<0.001	2.194	[1.802, 2.670]	<0.001
Widowed	1.658	[0.934, 2.943]	0.084	1.523	[1.116, 2.078]	0.008
Divorced	1.549	[1.011, 2.372]	0.044	1.178	[0.923, 1.502]	0.188
Separated	1.895	[0.961, 3.736]	0.065	1.400	[0.852, 2.300]	0.184
Social Class
Lower class	0.709	[0.301, 1.671]	0.432	1.343	[0.820, 2.200]	0.241
Working class	2.178	[1.107, 4.285]	0.024	2.218	[1.473, 3.340]	<0.001
Middle class	1.834	[0.958, 3.512]	0.067	1.952	[1.326, 2.873]	<0.001
Social/Psychological
Income	1.000	[1.000, 1.000]	0.002	1.000	[1.000, 1.000]	0.008
Religiosity	1.011	[0.993, 1.028]	0.234	0.998	[0.989, 1.007]	0.648
Fear	1.006	[0.983, 1.030]	0.594	1.011	[0.993, 1.029]	0.245
Happiness	1.066	[0.884, 1.285]	0.505	1.006	[0.994, 1.019]	0.310
Political Party
Strong Democrat	0.621	[0.296, 1.302]	0.208	0.382	[0.247, 0.592]	<0.001
Not Strong Democrat	0.652	[0.308, 1.379]	0.263	0.440	[0.280, 0.690]	<0.001
Ind. Close to Democrat	0.801	[0.381, 1.682]	0.558	0.523	[0.333, 0.821]	0.005
Independent	1.302	[0.628, 2.700]	0.478	0.583	[0.377, 0.901]	0.015
Ind. Close to Republican	2.157	[1.022, 4.551]	0.044	0.875	[0.550, 1.391]	0.572
Not Strong Republican	1.627	[0.775, 3.417]	0.198	1.233	[0.781, 1.945]	0.368
Strong Republican	1.878	[0.882, 4.001]	0.102	1.396	[0.894, 2.179]	0.142
Model Fit
Nagelkerke R2	0.273			0.201
Model χ2	338.808		<0.001	618.980		<0.001

Note: OR = Odds Ratio; CI = Confidence Interval. Reference categories: Female, Black, Not born in US, Never married, Upper class, Other party. Pairwise deletion was used (n varies by variable).

presents the logistic regression coefficients, odds ratios, and confidence intervals for both years. The analysis revealed both persistent predictors that remained significant across both time periods and pandemic-emergent predictors that became significant only in 2021.

5.2.1. Persistent Predictors (Significant in Both Years)

Several demographic factors consistently predicted reported gun ownership across both time periods, suggesting stable structural patterns in reported gun ownership that persisted despite the pandemic disruption. Being male remained the strongest demographic predictor in both 2018 (OR = 1.81, 95% CI [1.42, 2.31], p < 0.001) and 2021 (OR = 1.53, 95% CI [1.32, 1.78], p < 0.001), indicating that men were approximately 1.5 to 1.8 times more likely than women to report owning guns. This persistent gender gap in reported gun ownership aligns with previous research documenting higher rates of reported gun ownership among men and reflects enduring cultural associations between masculinity and firearms.

Being born in the United States was also a strong predictor in both years, though notably its effect decreased from 2018 (OR = 8.22, 95% CI [4.52, 14.93], p < 0.001) to 2021 (OR = 3.92, 95% CI [2.86, 5.37], p < 0.001). While native-born individuals remained significantly more likely to report owning guns in both periods, the substantial reduction in the odds ratio suggests that the association between US birth and reported gun ownership weakened during the pandemic. This may indicate that foreign-born residents increasingly reported gun ownership during the pandemic, possibly in response to heightened concerns about personal safety or anti-immigrant sentiment.

Marital status also remained a significant predictor across both years. Married individuals were 2.19 to 2.99 times more likely to report owning guns than never-married individuals in both 2018 (OR = 2.99, 95% CI [2.10, 4.26], p < 0.001) and 2021 (OR = 2.19, 95% CI [1.80, 2.67], p < 0.001). This persistent effect may reflect the stability and economic resources associated with marriage, which facilitate gun ownership, as well as the protective motivations that married individuals may feel toward their families.

Family income (measured by CONINC) was a significant positive predictor in both years (2018: OR = 1.000, 95% CI [1.000, 1.000], p = 0.002; 2021: OR = 1.000, 95% CI [1.000, 1.000], p = 0.008), though the effect size was small. This finding suggests that economic resources consistently facilitate reported gun ownership, as firearms represent a financial investment that higher-income households are better positioned to make.

Working-class identification also predicted reported gun ownership in both years. In 2018, working-class respondents were 2.18 times more likely than upper-class respondents to report owning guns (OR = 2.18, 95% CI [1.11, 4.29], p = 0.024), and this effect strengthened in 2021 (OR = 2.22, 95% CI [1.47, 3.34], p < 0.001). This pattern aligns with cultural research documenting stronger gun culture and higher reported ownership rates among working-class Americans [2,14].

5.2.2. Pandemic-Emergent Predictors (Significant Only in 2021)

Several demographic variables became significant predictors only during the pandemic, suggesting that the crisis altered the demographic profile of those who report gun ownership. Race emerged as a significant factor in 2021, with White respondents (OR = 1.97, 95% CI [1.44, 2.69], p < 0.001) and respondents of other races (OR = 1.85, 95% CI [1.27, 2.70], p = 0.001) significantly more likely to report owning guns than Black respondents. In 2018, race showed no significant association with reported gun ownership (White: OR = 1.51, p = 0.097; Other: OR = 1.32, p = 0.339). Tis emergent racial disparity during the pandemic may reflect differential responses to pandemic-related threats and civil unrest, with White Americans potentially more likely to view gun ownership as a protective response to perceived social instability.

Middle-class identification became a strong predictor in 2021 (OR = 1.95, 95% CI [1.33, 2.87], p < 0.001), whereas it showed only marginal significance in 2018 (OR = 1.83, 95% CI [0.96, 3.51], p = 0.067). This suggests that middle-class Americans increasingly turned to gun ownership during the pandemic, possibly reflecting heightened concerns about protecting economic security and property during a period of widespread economic disruption.

5.2.3. Changed Effects Between Years

Some demographic predictors showed significant changes in their effects between 2018 and 2021. The effect of being widowed strengthened during the pandemic, moving from marginal significance in 2018 (OR = 1.66, 95% CI [0.93, 2.94], p = 0.084) to statistical significance in 2021 (OR = 1.52, 95% CI [1.12, 2.08], p = 0.008). This may reflect heightened vulnerability and isolation experienced by widowed individuals during the pandemic.

Conversely, being divorced was a significant predictor in 2018 (OR = 1.55, 95% CI [1.01, 2.37], p = 0.044) but not in 2021 (OR = 1.18, 95% CI [0.92, 1.50], p = 0.188). This suggests that the unique stressors faced by divorced individuals, which previously predicted reported gun ownership, may have been overshadowed by pandemic-related stressors that affected the broader population more uniformly.

Age and education remained non-significant predictors in both years, indicating that these factors did not independently influence reported gun ownership when controlling for other demographic and social variables.

5.2.4. Summary of Hypothesis 1

Overall, Hypothesis 1 was partially supported. While certain demographic predictors (male sex, US birth, married status, income, working-class identification) remained consistent across both periods, several new demographic factors emerged as significant during the pandemic. Most notably, race and middle-class identification became significant predictors only in 2021, suggesting that the pandemic crisis altered the demographic profile of those who report gun ownership. These findings indicate that while a core set of demographic characteristics consistently predicted reported gun ownership, the pandemic introduced new patterns that reflected the specific anxieties and vulnerabilities created by the COVID-19 crisis.

5.3. Hypothesis 2: Social Determinants of Reported Gun Ownership

Hypothesis 2 posited that the social determinants of reported gun ownership would change during the pandemic compared to the pre-pandemic period. This hypothesis received partial support, with political party affiliation showing dramatic changes while other social variables remained largely non-significant.

5.3.1. Political Party Affiliation: Pandemic Polarization

The most striking change involved political party identification, which showed minimal effects in 2018 but emerged as a powerful predictor in 2021. In 2018, most political affiliations showed no significant relationship with reported gun ownership compared to the reference category of other parties. Only respondents who identified as independent but leaning Republican showed higher reported gun ownership (OR = 2.16, 95% CI [1.02, 4.55], p = 0.044). Strong Republicans (OR = 1.88, p = 0.102), not-strong Republicans (OR = 1.63, p = 0.198), strong Democrats (OR = 0.62, p = 0.208), not-strong Democrats (OR = 0.65, p = 0.263), independents leaning Democrat (OR = 0.80, p = 0.558), and true independents (OR = 1.30, p = 0.478) all showed non-significant relationships with reported gun ownership in 2018.

By 2021, however, a partisan divide emerged, characterized primarily by significant declines in reported gun ownership among Democratic identifiers. Multiple Democratic-leaning categories became significantly less likely to report owning guns compared to members of other parties: strong Democrats (OR = 0.38, 95% CI [0.25, 0.59], p < 0.001), not-strong Democrats (OR = 0.44, 95% CI [0.28, 0.69], p < 0.001), independents leaning Democrat (OR = 0.52, 95% CI [0.33, 0.82], p = 0.005), and true independents (OR = 0.58, 95% CI [0.38, 0.90], p = 0.015). Meanwhile, Republican affiliations, which showed some elevation in 2018, no longer differed significantly from the reference group of other party members in 2021: independents leaning Republican (OR = 0.88, p = 0.572), not-strong Republicans (OR = 1.23, p = 0.368), and strong Republicans (OR = 1.40, p = 0.142).

This pattern suggests that the partisan gap in reported gun ownership transformed substantially during the pandemic. Rather than Republicans increasing their gun ownership, the primary shift was Democratic identifiers becoming distinctly less likely to report gun ownership in 2021 compared to 2018, while Republican affiliations moved from showing some elevation in 2018 to being statistically indistinguishable from other party members in 2021. This asymmetric polarization, driven primarily by Democratic decline rather than Republican increase, may reflect the politicization of pandemic responses, heightened gun rights rhetoric during the 2020 presidential campaign, and partisan differences in threat perception during the civil unrest of 2020. The Democratic Party’s gun control platform may have become more salient during this period, further distinguishing those who report gun ownership by political identity.

5.3.2. Other Social Variables

Contrary to expectations, several social variables showed no significant relationship with reported gun ownership in either year. Religiosity (measured by frequency of religious service attendance) was non-significant in both 2018 (OR = 1.01, p = 0.234) and 2021 (OR = 1.00, p = 0.648), suggesting that religious involvement did not independently predict reported gun ownership when controlling for demographic factors.

Fear of walking in one’s neighborhood at night showed no significant effect in either 2018 (OR = 1.01, p = 0.594) or 2021 (OR = 1.01, p = 0.245). This unexpected null finding suggests that localized fear of crime may not be a primary driver of reported gun ownership at the national level, or that the measure used may not adequately capture the types of fear that motivate gun ownership.

General happiness also showed no significant relationship with reported gun ownership in either year (2018: OR = 1.07, p = 0.505; 2021: OR = 1.01, p = 0.310), indicating that self-reported well-being did not independently predict reported gun ownership patterns.

Education showed no significant effect in either 2018 (OR = 0.99, p = 0.500) or 2021 (OR = 1.01, p = 0.146), contradicting previous literature suggesting that education level influences reported gun ownership [2,14]. This null finding may reflect the complexity of education’s relationship with reported gun ownership, with higher education associated with both liberal political values (which decrease reported gun ownership) and higher income (which facilitates gun ownership), resulting in no net effect when these factors are controlled.

5.3.3. Summary of Hypothesis 2

Hypothesis 2 was partially supported. Political party affiliation showed dramatic changes during the pandemic, with Democratic identifiers becoming significantly less likely to report owning guns in 2021, a pattern not observed in 2018, while Republican affiliations shifted from showing some elevation in 2018 to being statistically similar to other party members in 2021. This asymmetric transformation indicates that political polarization around reported gun ownership intensified during the pandemic through declining ownership among Democrats rather than increasing ownership among Republicans, possibly reflecting broader partisan divisions regarding threat perception, government response to crisis, and the cultural significance of firearms. However, other social variables (religiosity, education, fear, happiness) remained non-significant predictors in both years, suggesting that these factors do not independently drive reported gun ownership patterns when demographic and political factors are controlled. The emergence of partisan polarization as a defining feature of reported gun ownership during the pandemic represents a significant shift in the social landscape of American gun culture.

5.4. Model Fit and Overall Assessment

Model fit statistics are presented at the bottom of Table 2. Both the 2018 and 2021 models were statistically significant, indicating that the included predictors collectively explained significant variance in reported gun ownership. The 2018 model demonstrated a Nagelkerke R² of 0.273, while the 2021 model showed a Nagelkerke R² of 0.201. Both models showed significant improvement over the null model (2018: χ² = 338.81, df = 28, p < 0.001; 2021: χ² = 618.98, df = 37, p < 0.001).

The lower pseudo-R² in the 2021 model compared to 2018 suggests that reported gun ownership during the pandemic may have been influenced by unmeasured factors beyond the demographic and social variables included in the model. Pandemic-specific stressors such as health anxiety about COVID-19, acute economic disruption and unemployment, concerns about civil unrest following the George Floyd protests, and disruptions to daily routines and social support systems may have influenced gun ownership decisions in ways not captured by traditional demographic and social predictors. This interpretation is consistent with General Strain Theory, which emphasizes that acute, clustered stressors may produce behavioral responses that differ from those driven by chronic background conditions [11].

Despite the lower variance explained in 2021, the model successfully identified key shifts in the demographic and social profile of those who report gun ownership during the pandemic, particularly the emergence of race and political party as significant predictors. These findings suggest that while the pandemic did not increase overall reported gun ownership rates, it did reshape the social and demographic composition of those who report gun ownership in meaningful ways.

6. Discussion

According to national surveys, about 30–35% of adults reported owning a gun before the pandemic [2,29]. Although this proportion may seem modest, many gun owners possess multiple firearms, which contributes to the high total number of guns in the country. Although this proportion may seem modest, many gun owners possess multiple firearms [2,12], which contributes to the high total number of guns in the country.

The demographic findings also provide important insights, supporting Hypothesis 1 Before the pandemic, significant predictors of reported gun ownership included being widowed, divorced, male, and having a minor political affiliation (“Other”). These patterns are consistent with previous research showing that men and people with disrupted family roles were more likely to own guns [2,12]. During the pandemic, new predictors appeared, including race and middle-class identification. Additionally, political party affiliation became a strong predictor, with Democrats becoming significantly less likely to report gun ownership. These results suggest that the pandemic changed the social factors influencing gun ownership.

Race became a significant predictor in 2021. White Americans and people of other races were about twice as likely as Black Americans to report gun ownership during the pandemic, a pattern not observed in 2018. This fits with GST, which suggests that people are more likely to respond to threats by protecting their valued things when they feel institutional support is insufficient. Middle-class identification also became significant, with middle-class people being almost twice as likely as upper-class people to own guns. This may reflect that middle-class individuals worried more about protecting their economic security during widespread economic disruption.

Some variables that we expected to matter did not predict gun ownership in either year. Religiosity (measured by frequency of religious service attendance) showed no significant relationship with gun ownership in 2018 or 2021, suggesting that religious involvement does not independently influence gun ownership when other factors are controlled. Similarly, education level, fear of neighborhood crime, and general happiness were not significant predictors in either year.

Political party affiliation, however, showed dramatic changes. In 2018, political party had minimal effects on gun ownership. By 2021, a clear partisan divide emerged. Democrats became much less likely to report gun ownership compared to members of other political parties, possibly reflecting differences in how groups perceive threats, trust in government protection, and the cultural meaning of firearms.

Sex and marital status remained important predictors. Men continued to own more guns than women, and people who were widowed or divorced had higher rates of ownership. These findings support GST, as these groups may feel more strain due to social or role disruptions, leading them to use firearms as a coping strategy. The results suggest that strain is not experienced equally across all groups; those facing more social or personal stress may have been more likely to respond with protective behaviors, such as gun acquisition.

These findings can be better understood through GST’s focus on cumulative strain. The COVID-19 pandemic was not just one stressful event; it included health risks, job losses, social isolation, and uncertainty, all happening at the same time. GST emphasizes that the severity, timing, and clustering of stressful events influence how people respond. The purchase of guns during this period can be seen as both a behavioral and emotional way to cope with these overlapping strains.

Comparing these results with previous studies shows that people tend to buy guns when they feel unsafe or when institutions seem unable to protect them [8,9,20]. The pandemic created a unique situation in which many stressors occurred simultaneously, and this study shows that demographic and social predictors of gun ownership can change under such conditions.

The results also have practical implications. Understanding how stress and strain influence gun ownership can help policymakers design programs and strategies to reduce perceived risks and protect communities during crises. For example, community support programs, communication about public safety, and targeted interventions for vulnerable groups could help reduce fear and prevent unnecessary gun purchases.

This study also suggests directions for future research. Examining regional differences in gun ownership or looking at trends over longer periods could provide more insight into how strain affects behavior. Comparing the U.S. with other countries could show how culture and laws shape responses to crises. From a theoretical perspective, further work could explore how different forms of strain interact to influence protective behaviors, such as gun ownership. The COVID-19 pandemic led to significant changes in gun ownership in the United States. Using GST, this study shows that people respond to cumulative stress by taking protective actions, such as purchasing firearms. The pandemic changed both who owns guns and why they own them. Understanding these changes can help researchers, policymakers, and community leaders respond to future crises in ways that support public safety and reduce fear.

7. Conclusions

The findings of this study suggest that the COVID-19 pandemic affected reported gun ownership in the United States, consistent with the predictions of General Strain Theory (GST).

Regarding Hypothesis 1, several demographic predictors of reported gun ownership persisted across both pre-pandemic and pandemic periods. Being married, being widowed, being divorced, and being male remained significant predictors, suggesting that established social patterns continued to influence firearm ownership despite the extraordinary circumstances of 2021. For instance, older adults were more likely to report owning firearms, confirming previous findings that 33% of adults aged 65 and older own a gun [31]. These persistent patterns highlight the role of long-standing demographic factors in shaping protective behaviors, even when society faces new and widespread disruptions.

The pandemic also introduced new demographic and social influences, reflecting the unique cumulative strain experienced during this period. Native-born Americans were significantly more likely than foreign-born individuals to report gun ownership in 2021, though this effect decreased from pre-pandemic levels (2018: OR = 8.22; 2021: OR = 3.92). This finding aligns with GST [11], as individuals respond to threats or the loss of positively valued stimuli, such as personal safety, social stability, and access to resources, by engaging in behaviors aimed at regaining control. The strengthening of gun ownership among U.S.-born individuals relative to foreign-born residents is particularly notable given the concurrent increase in hate crimes and discrimination against Asian Americans and other minority groups during the pandemic [32]. The weakening (though still significant) association between native-born status and gun ownership suggests that foreign-born residents may have increasingly turned to gun ownership as a protective response during this period.

Hypothesis 2, which focused on changes in social determinants of gun ownership, is also partially supported by the findings. Political affiliation emerged as the most significant social determinant, with Democrats becoming much less likely to report gun ownership during the pandemic compared to pre-pandemic patterns. This may reflect partisan differences in how groups perceive threats and appropriate coping strategies. Other social variables, such as religiosity, education, fear, and happiness, did not predict gun ownership in either year, suggesting these factors are less important than political identity when other factors are controlled. These changes suggest that the pandemic altered social perceptions of risk and protection, illustrating the cumulative and interactive nature of strain. Individuals faced simultaneous stressors, including economic uncertainty, social isolation, health threats, and decreased trust in institutions, prompting shifts in behaviors and decision-making consistent with GST’s framework.

By integrating both hypotheses, the study shows that both enduring demographic characteristics and pandemic-specific social factors impacted reported gun ownership. While sex, marital status, US birth, and income remained significant, pandemic-related stressors created new pressures that influenced ownership decisions. The study provides evidence that gun ownership during the COVID-19 pandemic was not solely a matter of cultural preference or routine behavior; it can also be seen as affected by a response to multiple forms of strain, including threats to personal safety, social stability, and perceived control over one’s environment [11,29]. These findings emphasize GST’s central idea that cumulative strain, particularly when multiple adverse events cluster in time, can significantly shape coping behaviors [11].

Future research could expand the scope of analysis. Comparative international studies could examine how patterns of gun ownership during the COVID-19 pandemic differ in the United States compared with countries that have distinct firearm laws and social contexts. Such comparisons may enhance understanding of the unique characteristics of American gun culture and help identify potential solutions to this ongoing public health and social issue.

Future research should also consider health-related variables, such as COVID-19 exposure, pre-existing health conditions, and pandemic-related health anxiety, which may influence gun ownership decisions during health crises.

It would also be valuable to investigate geographic variations in gun ownership during the pandemic by analyzing state- or county-level patterns. Regional differences may reflect variations in state gun laws, urban–rural divides, or local events influencing firearm purchasing decisions. Detailed regional analyses could inform state and local policymakers about the potential impacts of gun ownership during times of crisis, such as natural disasters, social unrest, or economic instability. Moreover, understanding how local factors interact with national-level policies can guide the development of targeted interventions and public safety strategies, particularly given that firearm policies often enacted during stable periods may have unforeseen consequences during times of uncertainty and crisis.

One of the limitations of this study is that not all cases in the original datasets provided valid responses to all variables. The 2018 sample included 1530 respondents who provided valid responses to the gun ownership question (out of 2348 total cases), while the 2021 sample included 3912 respondents with valid gun ownership responses (out of 4032 total cases). Pairwise deletion was used to maximize sample size. This represents a 65.2% response rate for 2018 and a 97.0% response rate for 2021, indicating that the majority of cases were retained rather than excluded, meaning cases were retained if they had valid responses on the dependent variable, even if some independent variables had missing data. Missing values were primarily due to respondents selecting ‘don’t know,’ or ‘refused,’ or being classified as ‘not applicable’ based on survey skip patterns. As noted by Davern et al. [29], the exclusion of cases with missing data can introduce nonresponse bias and limit the generalizability of findings; therefore, the results of this study should be interpreted with caution.