Privately Made Firearm in the US: Results from a National Survey

Privately Made Firearm in the US: Results from a National Survey | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Privately Made Firearm in the US: Results from a National Survey Symphony Fletcher, Deborah Azrael, Matthew Miller This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8552600/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Feb, 2026 Read the published version in Injury Epidemiology → Version 1 posted 10 You are reading this latest preprint version Abstract Background Almost nothing is known about the size or composition of the stock of privately made firearms (PMF). Objective Estimate the size and composition of the U.S. PMF stock. Methods A probability-based online survey of US adults conducted in December 2024 were used to generate nationally representative estimates. 12,907/ 20,907 adults (59%) responded to the survey invitation; 4,059 owned a working firearm. Respondents were asked whether they owned PMFs, defined as “firearms that were NOT produced by a manufacturer (sometimes called privately made firearms), such as guns that were assembled from a kit, 3-D printed or otherwise put together” and if so, how many and what types. They were also asked about their most recent PMF acquisition. Results We estimate that 2.9 million [CI: 2.2 million, 3.8 million] US adults own approximately 10.1 million PMFs. Most were constructed from kits (34%) or unfinished parts (32%); 16% were 3D printed, and the remainder were machined from raw materials (18%). Half 49% [CI: 0.43, 0.53] were unserialized. Among US adults who last acquired a PMF within 24 months of the survey, 67.2%, [CI: 48.7, 81.6] had a background check for their most recent acquisition, compared with 45.2% [33.9, 56.9] for PMF owners who last acquired a PMF > 24 months prior (P < 0.05). Comparable statistics for serialization were 68.9% [CI: 51.7, 82.1] and 53.8% [42.2, 64.9] (P = 0.14). Conclusion Approximately half of the 10 million PMFs owned by US adults were not serialized. More recently acquired PMFs are more likely to be serialized. INTRODUCTION A privately manufactured firearm PMF is a firearm, including a frame or receiver, completed, assembled, or otherwise produced by a person other than a licensed manufacturer. PMFs are assembled using unfinished frames or receivers, partially complete parts kits, 3-D printers, or computerized numerical control CNC milling machines. 1 Some PMFs are referred to as “ghost guns” due to the fact that they cannot be traced by law enforcement, most often due to lack of serialization at time of purchase or production. From 2017–2023, the number of PMFs recovered at crime scenes increased more than 16-fold, from 1,629 to 27,490, suggesting that PMFs may have become increasingly available or desirable for use in crime. Little else is known about size and composition of the stock of PMFs from which these seized PMFs are drawn, whether recently acquired PMFs differ from those acquired more remotely (e.g., by type, serialization), or whether background checks have become a more or less common feature of the PMF acquisition process. 2 , 3 To our knowledge, the current study is the first nationally representative survey of US adults to a) estimate the number and types of PMF owned by US adults, b) characterize the US adults who own these firearms. We also sought to assess serialization and background checks before and after ATF Final Rule 2021R-05F. 4 That rule, implemented in late August of 2022, required Federal Firearm Licensees (FFLs) to treat PMFs as firearms (and thus to serialize them) and manufacturers of parts and kits to serialize these components. METHODS Sample Data for this study come from the 2024 National Firearms Survey NFS, a nationally representative web- based survey designed by the authors (DA, MM) and conducted in December 2024 by the research firm Ipsos. Respondents were drawn from Ipsos’ KnowledgePanel KP, an online panel that includes approximately 60,000 U.S. adults. The KP panel is selected on an ongoing basis. Using an equal probability of selection design to provide samples that are representative of the U.S. population. Prior to selection of a specific study sample, Ipsos adjusts panel base weights to account for any discrepancies between panel composition and the distribution of key demographic characteristics of the U.S. population as reflected in the most recent Current Population Survey. 5 For this survey, 21,907 KP members were selected and received an invitation to participate in either English or Spanish, of whom 12,909 (59%) completed the survey. Invitations to participate were sent by email. One reminder email was sent to non-responders three days after initial outreach. Participants were not given any specific incentive to complete this survey, although Ipsos provides raffles and sweepstakes with cash rewards and other prizes for KP participants. The current study sample comprises the 4,059 (28.6%) of these 12,909 respondents who reported that they personally owned a gun. Measures Privately made firearm owners were identified through two questions. First, all respondents were asked “Do you personally own a working gun?” Working guns were defined as “guns that are in working order and capable of being fired”. If participants responded affirmatively, they were asked a series of questions about the number and types of firearms they owned, and then prompted to respond to the question, “Are any of the handguns, long guns or other guns you described above guns that were NOT made by a licensed manufacturer such as Beretta or Bushmaster? Sometimes this type of gun is referred to as a "privately made firearm" or PMF. That is, are any of your guns assembled from a kit, 3-D printed, or otherwise put together from parts?” Respondents were then asked about the number of PMFs they owned, by type (handgun and/or long gun). Respondents who owned PMFs were asked about their most recent PMF acquisition, including when the acquisition occurred, the manufacturing method used, whether or not the PMF was serialized, and the PMF’s cost. Respondents were also asked whether they had undergone a background check at the time they acquired their most recent PMF. Statistical Analysis Study weights provided by Ipsos combined pre- sample weights with two study-specific post-stratification weights accounting for oversampling and for survey nonresponse. We report weighted percentages, confidence intervals, and unadjusted odds ratios (OR) using the svy suite of commands in StataNow 18, following the STROBE Strengthening the Reporting of Observational Studies in Epidemiology guidelines for reporting. 6 A single respondent reported owning a total of 100 PMFs and was considered an outlier and thus excluded from estimates of the average number of PMFs owned, but was retained for all other analyses (e.g., number of PMF owners, whether the respondents most recently acquired PMF was serialized). This work was supported by the Robert Wood Johnson Foundation, the Joyce Foundation and the New Venture Fund. Funders did not play a role in the design, conduct, or reporting of the research, or in the decision to submit the manuscript for publication. The Harvard School of Public Health and Northeastern University Institutional Review Boards each determined that studies using the NFS meet the criteria for exemption per regulations governing research involving human subjects. The public was not involved in the design or analysis of this research. RESULTS We estimate that 28.6% (n = 4059) of US adults owned a firearm in December 2024, of whom, 3.8% [CI: 2.9, 4.0] (n = 138) owned at least one PMF (Table 1 ). Scaling our findings to the U.S. population of adults 18 years and older (266.3 million), 7 we estimate that there are approximately 76.2 million gun owners of whom roughly 2.9 million own at least one PMF (CI: 2.2 million, 3.8 million). Given that the average number of PMFs owned is 3.5 [CI: 1.8, 5.2], we estimate that there are approximately 10.1 million PMFs currently owned by US adults. Estimates including the single outlier who reported owning 100 PMFs yield an estimate of the PMF stock of 12.8 million (not shown). Table 1 Characteristics of Owners of Privately Made Firearms and of Firearm Owners Who Do Not Own Privately Made Firearms PMF owners (n = 138)* Firearm owners who do not own PMFs (n = 3921) weighted column %, 95% CI Race White 64.9 [54.9, 73.8] 73.3 [71.7, 74.9] Black 9.2 [4.9, 16.6] 10.7 [9.6,11.9] Hispanic 19.5 [12.1, 29.9] 10.5 [9.3,11.8] Mixed Race 2.4 [1.1, 5.3] 2.0 [1.7, 2.3] Other 4.0 [1.5, 10.1] 3.5 [2.8, 4.4] Age 18–20 2.9 [0.7, 10.9] 2.3 [1.7, 3.2] 21–29 12.4 [6.5, 22.5] 9.4 [8.2, 10.8] 30–44 35.7 [27.4, 45.1] 25.5 [23.9, 27.1] 45–59 26.9 [19.6, 35.7] 26.4 [24.9, 27.9] 60+ 22.0 [16.0, 29.5] 36.4 [34.8, 37.9] Income 150,000 35.6 [27.2, 45.0] 30.6 [29.0, 32.3] Education Less than high school 11.1 [5.8, 20.4] 5.7 [4.7, 6.8] High school 27.1 [19.2, 36.7] 27.0 [25.4, 28.7] Some college 25.1 [18.1, 33.6] 32.1 [30.6, 33.8] Bachelor’s degree or higher 36.7 [28.6, 45.7] 35.2 [33.6, 36.8] Gender Male 64.6 [54.9, 73.3] 65.6 [63.9, 67.2] Female 35.4 [26.7, 45.1] 34.4 [32.8, 36.1] Urbanization Urban 35.5 [27.0,45.0] 30.7 [29.1, 32.4] Rural 26.7 [1.9, 35.4] 29.5 [27.9, 31.1] Suburban 37.8 [29.2, 47.2] 39.8 [38.1, 41.5] Region Northeast 11.2 [6.4, 18.9] 11.7 [10.6, 12.8] Midwest 21.5 [14.7, 30.4] 23.0 [21.6, 24.5] South 41.9 [33.1, 51.2] 44.6 [42.9, 46.3] West 25.4 [18.1, 34.4] 20.7 [19.3, 22.2] Employment Status Full time 67.4 [58.2, 75.3] 56.7 [54.9, 58.4] Part time 7.2 [3.6, 14.0] 9.8 [8.8, 10.9] Unemployed 25.4 [18.4, 34.1] 33.5 [31.9, 35.1] Veteran Status Yes 30.1 [22.0, 39.7] 16.1 [14.9, 17.3] No 69.9 [60.3, 78.0] 83.9 [82.7, 85.0] Has carried a loaded gun within the past 30 days Yes 57.4 [48.1, 66.1] 25.7 [24.2, 27.3] No 42.6 [33.9, 51.9] 74.3 [72.7, 75.8] Types of firearms owned* Handgun Only 27.9 [18.4, 39.9] 36.9 [35.0, 38.7] Long Gun Only 6.4 [2.7, 14.4] 14.3 [13.1, 15.7] Handgun and Long Gun 65.7 [53.7, 75.9] 48.8 [46.9, 50.7] Number of firearms owned 1 10.9 [6.3, 18.2] 30.5 [28.9, 32.1] 2 9.4 [5.2, 16.6] 19.3 [17.9, 20.8] 3–5 25.0 [17.5, 34.4] 26.2 [24.7, 27.8] >=6 54.7 [45.1, 63.9] 24.0 [22.6, 25.5] *The 138 PMF owners represent 3.8% of all firearm owners [CI: 2.9, 4.0], equivalent to 2.9 million US adults (CI: 2.2 million, 3.8 million). Owners Of PMFs Compared with Gun Owners without PMFs Compared with gun owners who did not own PMFs, PMF owners were more likely to be Hispanic 20% [CI: 12.1, 29.9] vs. 11% [CI: 9.3,11.8], to have served in the armed forces 30% [CI: 22.0, 39.7] vs. 16% [CI: 14.9, 17.3 and less likely to be over the age of 60 (22% [CI: 16.0, 29.5] vs. 36% [CI: 34.8, 37.9]). In terms of firearm-related behaviors, PMF owners were more likely than gun owners who did not own PMFs to report having carried a loaded firearm in the last 30 days 57% [CI: 48.1, 66.1] vs 26% [CI: 24.2, 27.3]. Owners of PMFs also owned more guns than did gun owners who did not own PMFs, for example, 55% [CI: 45.1, 63.9] of PMF owners owned more than 6 total firearms, compared with 24% [CI: 22.6, 25.5] of gun owners who did not own PMFs. Characteristics of the stock of PMFs Most PMFs were assembled from kits 3.4 million (CI: 2.9, 3.9) or unfinished parts (i.e. receivers or frames) 3.2 million [CI: 2.7, 3.6] (Table 2 ). Approximately half of the PMF stock were handguns (4.7 million) [CI: 4.1, 5.1], and approximately half were unserialized (4.9 million), [CI: 4.3, 5.4]. Table 2 Characteristics of the stock of Privately Made Firearms owned by US Adults, December 2024 Estimated Number of PMFs (95% CI), Millions PMF Type Handgun (n = 171) 4.7 (4.1, 5.1) Long gun (197) 5.4 (4.8, 5.9) Total (368) Serialization Unserialized (n = 178) 4.9 (4.3, 5.4) Serialized (n = 189) 5.2 (4.6, 5.7) PMF Construction Method Assembled from kit (n = 123) 3.4 (2.9, 3.9) Printed on 3D printer (n = 60) 1.6 (1.3, 2.1) Machined from raw materials (n = 41) 1.1 (0.8, 1.5) Purchased as an unfinished receiver/frame (n = 115) 3.2 (2.7, 3.6) Other (n = 26) 0.7 (0.4, 1.0) Region Northeast (n = 37) 1.0 (0.7, 1.4) Midwest (n = 106) 2.9 (2.4, 3.4) South (n = 163) 4.5 (3.9, 4.9) West (n = 62) 1.7 (1.3, 2.1) +These calculations omit the single respondent who reported owning 100 PMFs. This respondent reported that 50 of his PMFs were handguns and another 50 were long guns, and that all of his PMFs were serialized. Characteristics of most recently acquired PMFs by PMF Acquisition Period Approximately 29% of PMF owners reported having acquired their most recent PMF within the 2 years prior to the survey (Table 3 ). Among US adults who last acquired a PMF within 24 months of the survey, 67.2%, [CI: 48.7, 81.6] underwent a background check for that acquisition, compared with 45.2% [33.9, 56.9] for PMF owners whose most recent PMF was acquired more than 24 months prior. Comparable statistics for serialization were 68.9% [CI: 51.7, 82.1] and 53.8% [CI: 42.2, 64.9]. The cost, by contrast did not appear to appreciably change. Table 3 Characteristics most recently acquired Privately Made Firearm by recency of last PMF Acquisition (within the past 24 months vs. 25 or more months ago) Last acquisition within the Past 24 months (n = 40) Weighted Percentage [95% ci] Last acquisition 25 or more months ago (n = 91) Weighted Percentage [95% ci] P-Value Serialization 0.139 Yes 25 68.9 [51.7, 82.1] 44 53.8 [42.2, 64.9] Background Check 0.046 Yes 25 67.2 [48.7, 81.6] 36 45.2 [33.9, 56.9] Cost 0.635 $ 200 or less 13 29.3 [16.1, 47.3] 28 29.7 [20.3, 41.2] $ 201- $ 400 11 35.9 [20.3, 55.2] 23 24.5 [16.2, 35.3] $ 401 or more 11 23.6 [12.1, 40.8] 28 32.8 [22.6, 44.9] No cost 5 11.2 [4.3, 26.4] 10 13.0 [6.7, 23.7] DISCUSSION We estimate that approximately 2.9 million PMF owners owned 10.1 million PMFs at the end of 2024, roughly one half of which (4.9 million) were unserialized. Most PMFs were constructed using assembly kits or precursor parts (one fourth were 3D-printed or machined from raw materials). We asked PMF owners to tell us about their most recently acquired PMF. Among these, we found that those acquired within the past 24 months were more likely to have been serialized than those acquired more distally. Although we do not know where owners acquired their most recent PMF (e.g., from an FFL, private party, etc.), this trend is broadly consistent the intended effect of ATF Final Rule 2021R-05F. Our finding of increased serialization represents a weighted average of the effect of Final Rule 2021R-05F on the PMFs it targets and the serialization of those PMFs not subject to the rule (i.e., 3D printed and milled firearms that are not transferred by a federally licensed dealer). As 3D printing technology becomes easier to access and more affordable, this trend could be reversed. As such, extending the Final Rule 2021R-05F to include these currently unregulated PMFs would increase the fraction of PMFs serialized still further. Limitations Our findings should be considered in light of several limitations. First, we chose to ask respondents first about the total number of firearms they owned, and then how many of the firearms they owned were PMFs. To the extent that any respondents did not consider their PMFs firearms we may underestimate the total number of PMFs. Additionally, although we aimed to assess the impact of 2022 ATF rule on serialization and background check at time of most recent PMF purchase, our sample size of PMF owners was not large enough to directly analyze the effect of this regulatory policy. Furthermore, we did not ask respondents to classify their most recently acquired PMF in a sufficiently granular way to allow us to examine how our aggregate statistics about serialization and background checks may have been affected by changes in types of PMFs acquired or whether they were obtained through a licensed firearms dealer. Future work on trends in serialization and background checking should better specify these aspects of the acquisitions than we did in the current study. CONCLUSION Approximately half of the 10 million PMFs owned by US adults were not serialized, including one-third of those acquired by adults who acquired a PMF since 2022. Recent changes in how PMFs are regulated appear to be associated with an increased likelihood that when someone purchases a PMF, or constructs one themselves, their PMF will be serialized and that they will undergo a background check as part of any transaction. Declarations Ethical Approval Human Ethics declarations were not applicable. Consent to participate Consent to participate declarations were not applicable. Consent for publication Consent for publication was not applicable. Author Contribution All authors (S. Fletcher, D. Azrael, M. Miller) have contributed meaningfully to the authoring of the manuscript, which is original work and is not being considered for publication elsewhere. Author S. Fletcher created all tables throughout the manuscript. Data Availability The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. References California DOJ Office of Gun Violence Prevention Report, Oct 2024 https://oag.ca.gov/system/files/media/ogvp-report-ghost-guns.pdf Privately Made Firearms | Bureau of Alcohol, Tobacco, Firearms and Explosives. https://www.atf.gov/firearms/privately-made-firearms Privately Made Firearms Updates and New Analysis. National Firearms Commerce and Trafficking Assessment. Vol. Four. https://www.atf.gov/firearms/docs/report/nfcta-volume-iv-part-v-%E2%80%93-pmf-updates-and-new-analysis/download Summary of Final Rule 2021R-05F | Bureau of Alcohol, Tobacco, Firearms and Explosives. Accessed April 9, 2025. https://www.atf.gov/rules-and-regulations/definition-frame-or-receiver/summary Ipsos Public Affairs. National Firearms Survey 2024; 2025. von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453-1457. U.S. Census Bureau QuickFacts: United States. https://www.census.gov/quickfacts/fact/table/US/PST0452201 Additional Declarations No competing interests reported. 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receiver, completed, assembled, or otherwise produced by a person other than a licensed manufacturer. PMFs are assembled using unfinished frames or receivers, partially complete parts kits, 3-D printers, or computerized numerical control CNC milling machines.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Some PMFs are referred to as \u0026ldquo;ghost guns\u0026rdquo; due to the fact that they cannot be traced by law enforcement, most often due to lack of serialization at time of purchase or production.\u003c/p\u003e \u003cp\u003eFrom 2017\u0026ndash;2023, the number of PMFs recovered at crime scenes increased more than 16-fold, from 1,629 to 27,490, suggesting that PMFs may have become increasingly available or desirable for use in crime. Little else is known about size and composition of the stock of PMFs from which these seized PMFs are drawn, whether recently acquired PMFs differ from those acquired more remotely (e.g., by type, serialization), or whether background checks have become a more or less common feature of the PMF acquisition process.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eTo our knowledge, the current study is the first nationally representative survey of US adults to a) estimate the number and types of PMF owned by US adults, b) characterize the US adults who own these firearms. We also sought to assess serialization and background checks before and after ATF Final Rule 2021R-05F.\u003csup\u003e4\u003c/sup\u003e That rule, implemented in late August of 2022, required Federal Firearm Licensees (FFLs) to treat PMFs as firearms (and thus to serialize them) and manufacturers of parts and kits to serialize these components.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eSample\u003c/p\u003e \u003cp\u003eData for this study come from the 2024 National Firearms Survey NFS, a nationally representative web- based survey designed by the authors (DA, MM) and conducted in December 2024 by the research firm Ipsos. Respondents were drawn from Ipsos\u0026rsquo; KnowledgePanel KP, an online panel that includes approximately 60,000 U.S. adults. The KP panel is selected on an ongoing basis. Using an equal probability of selection design to provide samples that are representative of the U.S. population. Prior to selection of a specific study sample, Ipsos adjusts panel base weights to account for any discrepancies between panel composition and the distribution of key demographic characteristics of the U.S. population as reflected in the most recent Current Population Survey.\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFor this survey, 21,907 KP members were selected and received an invitation to participate in either English or Spanish, of whom 12,909 (59%) completed the survey. Invitations to participate were sent by email. One reminder email was sent to non-responders three days after initial outreach. Participants were not given any specific incentive to complete this survey, although Ipsos provides raffles and sweepstakes with cash rewards and other prizes for KP participants. The current study sample comprises the 4,059 (28.6%) of these 12,909 respondents who reported that they personally owned a gun.\u003c/p\u003e \u003cp\u003eMeasures\u003c/p\u003e \u003cp\u003ePrivately made firearm owners were identified through two questions. First, all respondents were asked \u0026ldquo;Do you personally own a working gun?\u0026rdquo; Working guns were defined as \u0026ldquo;guns that are in working order and capable of being fired\u0026rdquo;. If participants responded affirmatively, they were asked a series of questions about the number and types of firearms they owned, and then prompted to respond to the question, \u0026ldquo;Are any of the handguns, long guns or other guns you described above guns that were NOT made by a licensed manufacturer such as Beretta or Bushmaster? Sometimes this type of gun is referred to as a \"privately made firearm\" or PMF. That is, are any of your guns assembled from a kit, 3-D printed, or otherwise put together from parts?\u0026rdquo; Respondents were then asked about the number of PMFs they owned, by type (handgun and/or long gun). Respondents who owned PMFs were asked about their most recent PMF acquisition, including when the acquisition occurred, the manufacturing method used, whether or not the PMF was serialized, and the PMF\u0026rsquo;s cost. Respondents were also asked whether they had undergone a background check at the time they acquired their most recent PMF.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStudy weights provided by Ipsos combined pre- sample weights with two study-specific post-stratification weights accounting for oversampling and for survey nonresponse. We report weighted percentages, confidence intervals, and unadjusted odds ratios (OR) using the svy suite of commands in StataNow 18, following the STROBE Strengthening the Reporting of Observational Studies in Epidemiology guidelines for reporting.\u003csup\u003e6\u003c/sup\u003e A single respondent reported owning a total of 100 PMFs and was considered an outlier and thus excluded from estimates of the average number of PMFs owned, but was retained for all other analyses (e.g., number of PMF owners, whether the respondents most recently acquired PMF was serialized).\u003c/p\u003e \u003cp\u003eThis work was supported by the Robert Wood Johnson Foundation, the Joyce Foundation and the New Venture Fund. Funders did not play a role in the design, conduct, or reporting of the research, or in the decision to submit the manuscript for publication.\u003c/p\u003e \u003cp\u003eThe Harvard School of Public Health and Northeastern University Institutional Review Boards each determined that studies using the NFS meet the criteria for exemption per regulations governing research involving human subjects. The public was not involved in the design or analysis of this research.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eWe estimate that 28.6% (n\u0026thinsp;=\u0026thinsp;4059) of US adults owned a firearm in December 2024, of whom, 3.8% [CI: 2.9, 4.0] (n\u0026thinsp;=\u0026thinsp;138) owned at least one PMF (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Scaling our findings to the U.S. population of adults 18 years and older (266.3\u0026nbsp;million),\u003csup\u003e7\u003c/sup\u003e we estimate that there are approximately 76.2\u0026nbsp;million gun owners of whom roughly 2.9\u0026nbsp;million own at least one PMF (CI: 2.2\u0026nbsp;million, 3.8\u0026nbsp;million). Given that the average number of PMFs owned is 3.5 [CI: 1.8, 5.2], we estimate that there are approximately 10.1\u0026nbsp;million PMFs currently owned by US adults. Estimates including the single outlier who reported owning 100 PMFs yield an estimate of the PMF stock of 12.8\u0026nbsp;million (not shown).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of Owners of Privately Made Firearms and of Firearm Owners Who Do Not Own Privately Made Firearms\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePMF owners (n\u0026thinsp;=\u0026thinsp;138)*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirearm owners who do not own PMFs (n\u0026thinsp;=\u0026thinsp;3921)\u003c/p\u003e \u003cp\u003eweighted column %, 95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.9 [54.9, 73.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e73.3 [71.7, 74.9]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.2 [4.9, 16.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.7 [9.6,11.9]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.5 [12.1, 29.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.5 [9.3,11.8]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.4 [1.1, 5.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.0 [1.7, 2.3]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.0 [1.5, 10.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.5 [2.8, 4.4]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.9 [0.7, 10.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.3 [1.7, 3.2]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.4 [6.5, 22.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.4 [8.2, 10.8]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35.7 [27.4, 45.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.5 [23.9, 27.1]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26.9 [19.6, 35.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.4 [24.9, 27.9]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.0 [16.0, 29.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.4 [34.8, 37.9]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIncome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;25,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.8 [10.8, 25.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.7 [5.9, 7.7]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25,000\u0026ndash;74999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.8 [9.4, 22.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.0 [23.6, 26.6]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e75,000\u0026ndash;149,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32.8 [24.7, 42.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.7 [35.9, 39.3]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;150,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35.6 [27.2, 45.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.6 [29.0, 32.3]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.1 [5.8, 20.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.7 [4.7, 6.8]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27.1 [19.2, 36.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.0 [25.4, 28.7]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.1 [18.1, 33.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.1 [30.6, 33.8]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor\u0026rsquo;s degree or higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36.7 [28.6, 45.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.2 [33.6, 36.8]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.6 [54.9, 73.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e65.6 [63.9, 67.2]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35.4 [26.7, 45.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34.4 [32.8, 36.1]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrbanization\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35.5 [27.0,45.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.7 [29.1, 32.4]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26.7 [1.9, 35.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.5 [27.9, 31.1]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuburban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37.8 [29.2, 47.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39.8 [38.1, 41.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.2 [6.4, 18.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.7 [10.6, 12.8]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMidwest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21.5 [14.7, 30.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.0 [21.6, 24.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.9 [33.1, 51.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.6 [42.9, 46.3]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.4 [18.1, 34.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.7 [19.3, 22.2]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFull time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e67.4 [58.2, 75.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.7 [54.9, 58.4]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePart time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.2 [3.6, 14.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.8 [8.8, 10.9]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.4 [18.4, 34.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.5 [31.9, 35.1]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVeteran Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30.1 [22.0, 39.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.1 [14.9, 17.3]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69.9 [60.3, 78.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83.9 [82.7, 85.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHas carried a loaded gun within the past 30 days\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57.4 [48.1, 66.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.7 [24.2, 27.3]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42.6 [33.9, 51.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74.3 [72.7, 75.8]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTypes of firearms owned*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHandgun Only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27.9 [18.4, 39.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.9 [35.0, 38.7]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLong Gun Only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.4 [2.7, 14.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.3 [13.1, 15.7]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHandgun and Long Gun\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65.7 [53.7, 75.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.8 [46.9, 50.7]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of firearms owned\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.9 [6.3, 18.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.5 [28.9, 32.1]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.4 [5.2, 16.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.3 [17.9, 20.8]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.0 [17.5, 34.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.2 [24.7, 27.8]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;=6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.7 [45.1, 63.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.0 [22.6, 25.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e*The 138 PMF owners represent 3.8% of all firearm owners [CI: 2.9, 4.0], equivalent to 2.9\u0026nbsp;million US adults (CI: 2.2\u0026nbsp;million, 3.8\u0026nbsp;million).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eOwners Of PMFs Compared with Gun Owners without PMFs\u003c/h3\u003e\n\u003cp\u003eCompared with gun owners who did not own PMFs, PMF owners were more likely to be Hispanic 20% [CI: 12.1, 29.9] vs. 11% [CI: 9.3,11.8], to have served in the armed forces 30% [CI: 22.0, 39.7] vs. 16% [CI: 14.9, 17.3 and less likely to be over the age of 60 (22% [CI: 16.0, 29.5] vs. 36% [CI: 34.8, 37.9]). In terms of firearm-related behaviors, PMF owners were more likely than gun owners who did not own PMFs to report having carried a loaded firearm in the last 30 days 57% [CI: 48.1, 66.1] vs 26% [CI: 24.2, 27.3]. Owners of PMFs also owned more guns than did gun owners who did not own PMFs, for example, 55% [CI: 45.1, 63.9] of PMF owners owned more than 6 total firearms, compared with 24% [CI: 22.6, 25.5] of gun owners who did not own PMFs.\u003c/p\u003e\n\u003ch3\u003eCharacteristics of the stock of PMFs\u003c/h3\u003e\n\u003cp\u003eMost PMFs were assembled from kits 3.4\u0026nbsp;million (CI: 2.9, 3.9) or unfinished parts (i.e. receivers or frames) 3.2\u0026nbsp;million [CI: 2.7, 3.6] (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Approximately half of the PMF stock were handguns (4.7\u0026nbsp;million) [CI: 4.1, 5.1], and approximately half were unserialized (4.9\u0026nbsp;million), [CI: 4.3, 5.4].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the stock of Privately Made Firearms owned by US Adults, December 2024\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimated Number of PMFs (95% CI), Millions\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePMF Type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHandgun (n\u0026thinsp;=\u0026thinsp;171)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.7 (4.1, 5.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLong gun (197)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.4 (4.8, 5.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal (368)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerialization\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnserialized (n\u0026thinsp;=\u0026thinsp;178)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.9 (4.3, 5.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerialized (n\u0026thinsp;=\u0026thinsp;189)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.2 (4.6, 5.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePMF Construction Method\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssembled from kit (n\u0026thinsp;=\u0026thinsp;123)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.4 (2.9, 3.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrinted on 3D printer (n\u0026thinsp;=\u0026thinsp;60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.6 (1.3, 2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMachined from raw materials (n\u0026thinsp;=\u0026thinsp;41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.1 (0.8, 1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePurchased as an unfinished receiver/frame (n\u0026thinsp;=\u0026thinsp;115)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.2 (2.7, 3.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther (n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.7 (0.4, 1.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNortheast (n\u0026thinsp;=\u0026thinsp;37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0 (0.7, 1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMidwest (n\u0026thinsp;=\u0026thinsp;106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.9 (2.4, 3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth (n\u0026thinsp;=\u0026thinsp;163)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.5 (3.9, 4.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWest (n\u0026thinsp;=\u0026thinsp;62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.7 (1.3, 2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e+These calculations omit the single respondent who reported owning 100 PMFs. This respondent reported that 50 of his PMFs were handguns and another 50 were long guns, and that all of his PMFs were serialized.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eCharacteristics of most recently acquired PMFs by PMF Acquisition Period\u003c/h3\u003e\n\u003cp\u003eApproximately 29% of PMF owners reported having acquired their most recent PMF within the 2 years prior to the survey (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among US adults who last acquired a PMF within 24 months of the survey, 67.2%, [CI: 48.7, 81.6] underwent a background check for that acquisition, compared with 45.2% [33.9, 56.9] for PMF owners whose most recent PMF was acquired more than 24 months prior. Comparable statistics for serialization were 68.9% [CI: 51.7, 82.1] and 53.8% [CI: 42.2, 64.9]. The cost, by contrast did not appear to appreciably change.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics most recently acquired Privately Made Firearm by recency of last PMF Acquisition (within the past 24 months vs. 25 or more months ago)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLast acquisition within the Past 24 months (n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted Percentage [95% ci]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLast acquisition 25 or more months ago (n\u0026thinsp;=\u0026thinsp;91)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWeighted Percentage [95% ci]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerialization\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.9 [51.7, 82.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53.8 [42.2, 64.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBackground Check\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.2 [48.7, 81.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45.2 [33.9, 56.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCost\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e200 or less\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.3 [16.1, 47.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29.7 [20.3, 41.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e201-\u003cspan\u003e$\u003c/span\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.9 [20.3, 55.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.5 [16.2, 35.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e401 or more\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.6 [12.1, 40.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32.8 [22.6, 44.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo cost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.2 [4.3, 26.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.0 [6.7, 23.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eWe estimate that approximately 2.9\u0026nbsp;million PMF owners owned 10.1\u0026nbsp;million PMFs at the end of 2024, roughly one half of which (4.9\u0026nbsp;million) were unserialized. Most PMFs were constructed using assembly kits or precursor parts (one fourth were 3D-printed or machined from raw materials).\u003c/p\u003e \u003cp\u003eWe asked PMF owners to tell us about their most recently acquired PMF. Among these, we found that those acquired within the past 24 months were more likely to have been serialized than those acquired more distally. Although we do not know where owners acquired their most recent PMF (e.g., from an FFL, private party, etc.), this trend is broadly consistent the intended effect of ATF Final Rule 2021R-05F. Our finding of increased serialization represents a weighted average of the effect of Final Rule 2021R-05F on the PMFs it targets and the serialization of those PMFs not subject to the rule (i.e., 3D printed and milled firearms that are not transferred by a federally licensed dealer). As 3D printing technology becomes easier to access and more affordable, this trend could be reversed. As such, extending the Final Rule 2021R-05F to include these currently unregulated PMFs would increase the fraction of PMFs serialized still further.\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eOur findings should be considered in light of several limitations. First, we chose to ask respondents first about the total number of firearms they owned, and then how many of the firearms they owned were PMFs. To the extent that any respondents did not consider their PMFs firearms we may underestimate the total number of PMFs.\u003c/p\u003e \u003cp\u003eAdditionally, although we aimed to assess the impact of 2022 ATF rule on serialization and background check at time of most recent PMF purchase, our sample size of PMF owners was not large enough to directly analyze the effect of this regulatory policy. Furthermore, we did not ask respondents to classify their most recently acquired PMF in a sufficiently granular way to allow us to examine how our aggregate statistics about serialization and background checks may have been affected by changes in types of PMFs acquired or whether they were obtained through a licensed firearms dealer. Future work on trends in serialization and background checking should better specify these aspects of the acquisitions than we did in the current study.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eApproximately half of the 10\u0026nbsp;million PMFs owned by US adults were not serialized, including one-third of those acquired by adults who acquired a PMF since 2022. Recent changes in how PMFs are regulated appear to be associated with an increased likelihood that when someone purchases a PMF, or constructs one themselves, their PMF will be serialized and that they will undergo a background check as part of any transaction.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthical Approval\u003c/strong\u003e \u003cp\u003eHuman Ethics declarations were not applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to participate\u003c/strong\u003e \u003cp\u003eConsent to participate declarations were not applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eConsent for publication was not applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors (S. Fletcher, D. Azrael, M. Miller) have contributed meaningfully to the authoring of the manuscript, which is original work and is not being considered for publication elsewhere. Author S. Fletcher created all tables throughout the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eCalifornia DOJ Office of Gun Violence Prevention Report, Oct 2024 https://oag.ca.gov/system/files/media/ogvp-report-ghost-guns.pdf\u003c/li\u003e\n \u003cli\u003ePrivately Made Firearms | Bureau of Alcohol, Tobacco, Firearms and Explosives. https://www.atf.gov/firearms/privately-made-firearms \u0026nbsp;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePrivately Made Firearms Updates and New Analysis. National Firearms Commerce and Trafficking Assessment. Vol. Four. https://www.atf.gov/firearms/docs/report/nfcta-volume-iv-part-v-%E2%80%93-pmf-updates-and-new-analysis/download\u003c/li\u003e\n \u003cli\u003eSummary of Final Rule 2021R-05F | Bureau of Alcohol, Tobacco, Firearms and Explosives. Accessed April 9, 2025. https://www.atf.gov/rules-and-regulations/definition-frame-or-receiver/summary\u003c/li\u003e\n \u003cli\u003eIpsos Public Affairs. National Firearms Survey 2024; 2025.\u003c/li\u003e\n \u003cli\u003evon Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453-1457.\u003c/li\u003e\n \u003cli\u003eU.S. Census Bureau QuickFacts: United States. https://www.census.gov/quickfacts/fact/table/US/PST0452201\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"injury-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"inep","sideBox":"Learn more about [Injury Epidemiology](https://injepijournal.biomedcentral.com)","snPcode":"40621","submissionUrl":"https://submission.nature.com/new-submission/40621/3","title":"Injury Epidemiology","twitterHandle":"@InjuryEpi","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8552600/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8552600/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAlmost nothing is known about the size or composition of the stock of privately made firearms (PMF).\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eEstimate the size and composition of the U.S. PMF stock.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA probability-based online survey of US adults conducted in December 2024 were used to generate nationally representative estimates. 12,907/ 20,907 adults (59%) responded to the survey invitation; 4,059 owned a working firearm. Respondents were asked whether they owned PMFs, defined as \u0026ldquo;firearms that were NOT produced by a manufacturer (sometimes called privately made firearms), such as guns that were assembled from a kit, 3-D printed or otherwise put together\u0026rdquo; and if so, how many and what types. They were also asked about their most recent PMF acquisition.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe estimate that 2.9\u0026nbsp;million [CI: 2.2\u0026nbsp;million, 3.8 million] US adults own approximately 10.1\u0026nbsp;million PMFs. Most were constructed from kits (34%) or unfinished parts (32%); 16% were 3D printed, and the remainder were machined from raw materials (18%). Half 49% [CI: 0.43, 0.53] were unserialized. Among US adults who last acquired a PMF within 24 months of the survey, 67.2%, [CI: 48.7, 81.6] had a background check for their most recent acquisition, compared with 45.2% [33.9, 56.9] for PMF owners who last acquired a PMF\u0026thinsp;\u0026gt;\u0026thinsp;24 months prior (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Comparable statistics for serialization were 68.9% [CI: 51.7, 82.1] and 53.8% [42.2, 64.9] (P\u0026thinsp;=\u0026thinsp;0.14).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eApproximately half of the 10\u0026nbsp;million PMFs owned by US adults were not serialized. More recently acquired PMFs are more likely to be serialized.\u003c/p\u003e","manuscriptTitle":"Privately Made Firearm in the US: Results from a National Survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 17:21:21","doi":"10.21203/rs.3.rs-8552600/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-26T19:28:32+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-26T17:37:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"228176401696607012001934679253277130649","date":"2026-01-16T13:49:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214691557620088133612360973578829892909","date":"2026-01-15T15:42:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-15T15:40:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"339702485938888712451587152012376514346","date":"2026-01-15T15:16:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-14T13:38:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-14T06:16:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-14T06:15:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"Injury Epidemiology","date":"2026-01-08T14:22:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"injury-epidemiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"inep","sideBox":"Learn more about [Injury Epidemiology](https://injepijournal.biomedcentral.com)","snPcode":"40621","submissionUrl":"https://submission.nature.com/new-submission/40621/3","title":"Injury Epidemiology","twitterHandle":"@InjuryEpi","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"21502519-df4d-4ace-ac6d-a4a3faecbb51","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-23T16:06:28+00:00","versionOfRecord":{"articleIdentity":"rs-8552600","link":"https://doi.org/10.1186/s40621-026-00661-w","journal":{"identity":"injury-epidemiology","isVorOnly":false,"title":"Injury Epidemiology"},"publishedOn":"2026-02-22 15:58:07","publishedOnDateReadable":"February 22nd, 2026"},"versionCreatedAt":"2026-01-16 17:21:21","video":"","vorDoi":"10.1186/s40621-026-00661-w","vorDoiUrl":"https://doi.org/10.1186/s40621-026-00661-w","workflowStages":[]},"version":"v1","identity":"rs-8552600","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8552600","identity":"rs-8552600","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}