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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="1.3" xml:lang="en" article-type="research-article"><?properties manuscript?><processing-meta base-tagset="archiving" mathml-version="3.0" table-model="xhtml" tagset-family="jats"><restricted-by>pmc</restricted-by></processing-meta><front><journal-meta><journal-id journal-id-type="nlm-journal-id">7513587</journal-id><journal-id journal-id-type="pubmed-jr-id">3445</journal-id><journal-id journal-id-type="nlm-ta">Drug Alcohol Depend</journal-id><journal-id journal-id-type="iso-abbrev">Drug Alcohol Depend</journal-id><journal-title-group><journal-title>Drug and alcohol dependence</journal-title></journal-title-group><issn pub-type="ppub">0376-8716</issn><issn pub-type="epub">1879-0046</issn></journal-meta><article-meta><article-id pub-id-type="pmid">35461083</article-id><article-id pub-id-type="pmc">9106898</article-id><article-id pub-id-type="doi">10.1016/j.drugalcdep.2022.109467</article-id><article-id pub-id-type="manuscript">HHSPA1800451</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Naloxone administration among opioid-involved overdose deaths in 38 United States jurisdictions in the State Unintentional Drug Overdose Reporting System, 2019</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Quinn</surname><given-names>Kelly</given-names></name><xref rid="CR1" ref-type="corresp">*</xref></contrib><contrib contrib-type="author"><name><surname>Kumar</surname><given-names>Sagar</given-names></name></contrib><contrib contrib-type="author"><name><surname>Hunter</surname><given-names>Calli T.</given-names></name></contrib><contrib contrib-type="author"><name><surname>O&#x02019;Donnell</surname><given-names>Julie</given-names></name></contrib><contrib contrib-type="author"><name><surname>Davis</surname><given-names>Nicole L.</given-names></name></contrib><aff id="A1">Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, Division of Overdose Prevention, 4770 Buford Hwy, Atlanta, GA 30341, USA</aff></contrib-group><author-notes><fn fn-type="con" id="FN1"><p id="P1">Contributors</p><p id="P2">KQ conceived the study, conducted data analyses, interpreted the data, and wrote the manuscript. SK conceived the study, conducted data analyses, interpreted the data, and revised the manuscript. CH conceived the study, interpreted the data, and revised the manuscript. JO conceived the study, conducted data analyses, interpreted the data, and revised the manuscript. ND interpreted the data and reviewed and revised the manuscript. All authors approved the final article.</p></fn><corresp id="CR1"><label>*</label>Corresponding author. <email>jpe8@cdc.gov</email> (K. Quinn)</corresp></author-notes><pub-date pub-type="nihms-submitted"><day>22</day><month>4</month><year>2022</year></pub-date><pub-date pub-type="ppub"><day>01</day><month>6</month><year>2022</year></pub-date><pub-date pub-type="epub"><day>16</day><month>4</month><year>2022</year></pub-date><pub-date pub-type="pmc-release"><day>01</day><month>6</month><year>2023</year></pub-date><volume>235</volume><fpage>109467</fpage><lpage>109467</lpage><abstract id="ABS1"><sec id="S1"><title>Background:</title><p id="P3">The majority of drug overdose deaths in the United States involve opioids, and synthetic opioid-involved overdose death rates are increasing. Naloxone is a key prevention strategy yet estimates of its administration are limited.</p></sec><sec id="S2"><title>Methods:</title><p id="P4">We analyzed 2019 data from 37 states and the District of Columbia in CDC&#x02019;s State Unintentional Drug Overdose Reporting System to estimate the percentage of decedents, by sociodemographic subgroup, who experienced a fatal opioid-involved overdose and had no evidence of naloxone administration.</p></sec><sec id="S3"><title>Results:</title><p id="P5">A total of 77.3% of 33,084 opioid-involved overdose deaths had no evidence of naloxone administration. Statistically significant subgroup differences were observed for all sociodemographic groups examined except housing status. The highest percentages of decedents lacking evidence of naloxone administration were those with highest educational attainment (doctorate or professional degree, 87.0%), oldest (55&#x02013;64 years, 83.4%; &#x02265;65 years, 87.3%) and youngest ages (&#x0003c;15 years, 87.5%), and single marital status (84.5%). The lowest percentages of no evidence of naloxone administration were observed for non-Hispanic American Indian/Alaskan Native persons (66.2%) and those ages 15&#x02013;24 years (70.8%).</p></sec><sec id="S4"><title>Conclusions:</title><p id="P6">More than three-quarters of opioid-involved overdose deaths had no evidence of naloxone administration, underscoring the need to ensure sufficient naloxone access and capacity for utilization. While fatal overdose data cannot fully characterize sociodemographic disparities in naloxone administration, naloxone education and access efforts can be informed by apparent inequities. Public health partners can assist persons who use drugs (PWUD) by maintaining naloxone supply and amplifying messages about the high risk of using drugs alone among PWUD and their social networks.</p></sec></abstract><kwd-group><kwd>Naloxone</kwd><kwd>Harm reduction</kwd><kwd>Opioid-involved overdose</kwd><kwd>Overdose mortality</kwd><kwd>Health disparities</kwd></kwd-group></article-meta></front><body><sec id="S5"><label>1.</label><title>Introduction</title><p id="P7">In 2020, 74.8% of 91,799 drug overdose deaths in the United States involved opioids, and 61.6% involved synthetic opioids, which likely consisted largely of illicitly manufactured fentanyls (IMFs) (<xref rid="R6" ref-type="bibr">CDC WONDER</xref>). Preliminary 2021 data suggest that overall drug and synthetic opioid-involved overdose death rates continue to increase (<xref rid="R1" ref-type="bibr">Ahmad et al., 2021</xref>). Naloxone is an opioid antagonist medication that can reverse the effects of an opioid overdose when administered in time and is a key overdose prevention strategy.</p><p id="P8">Evidence suggests that efforts to increase naloxone awareness and access, including through community distribution, can be effective in preventing deaths from opioid overdose (<xref rid="R15" ref-type="bibr">Irvine et al., 2018</xref>; <xref rid="R25" ref-type="bibr">McClellan et al., 2018</xref>; <xref rid="R27" ref-type="bibr">Mueller et al., 2015</xref>; <xref rid="R12" ref-type="bibr">Giglio et al., 2015</xref>; <xref rid="R37" ref-type="bibr">Walley et al., 2013</xref>; <xref rid="R39" ref-type="bibr">Wheeler et al., 2015</xref>). Access to naloxone among laypersons and co-drug use partners and education about overdose recognition and naloxone administration in the general population are critical given the increasing availability of highly potent IMFs in the illicit drug supply. However, stigmatization of persons who use drugs (PWUD), misconceptions that naloxone access increases high-risk drug use, and fear of legal repercussions may hinder naloxone distribution and use, and therefore, its life-saving potential (<xref rid="R21" ref-type="bibr">Lai et al., 2021</xref>; <xref rid="R8" ref-type="bibr">Dayton et al., 2020</xref>; <xref rid="R7" ref-type="bibr">Crabtree and Masuda, 2019</xref>; <xref rid="R5" ref-type="bibr">Carson, 2019</xref>; <xref rid="R34" ref-type="bibr">Sisson et al., 2019</xref>).</p><p id="P9">U.S. population estimates of naloxone administration are elusive because naloxone can be administered by various trained and untrained people, including EMS personnel and other first responders, co-drug use partners, and other bystanders, making utilization difficult to monitor. Studies of naloxone administration, access (including ongoing access), and training in subpopulations (e.g., PWUD, individuals with health care coverage, persons receiving EMS response/treatment for an overdose) suggest sociodemographic inequities (<xref rid="R20" ref-type="bibr">Kinnard et al., 2021</xref>; <xref rid="R11" ref-type="bibr">Geiger et al., 2020</xref>; <xref rid="R8" ref-type="bibr">Dayton et al., 2020</xref>; <xref rid="R19" ref-type="bibr">Kim et al., 2020</xref>; <xref rid="R31" ref-type="bibr">Ong et al., 2020</xref>; <xref rid="R3" ref-type="bibr">Barboza and Angulski, 2020</xref>; <xref rid="R32" ref-type="bibr">Reed et al., 2019</xref>; <xref rid="R16" ref-type="bibr">Jones et al., 2016</xref>; <xref rid="R33" ref-type="bibr">Rowe et al., 2015</xref>).</p><p id="P10">We used data from the Centers for Disease Control and Prevention&#x02019;s (CDC) State Unintentional Drug Overdose Reporting System (SUDORS) to estimate the percentage of decedents who experienced an opioid-involved overdose that potentially could have been reversed with naloxone yet had no evidence of naloxone administration. We also investigated whether sociodemographic subgroup differences in naloxone administration exist in this sample of U.S. overdose decedents.</p></sec><sec id="S6"><label>2.</label><title>Methods</title><p id="P11">Data on unintentional and undetermined intent drug overdose deaths that occurred in 37 states and the District of Columbia in 2019 were included. Four jurisdictions reported data for January-June; six reported data for July-December, and 28 reported data for the full year. Twenty-eight jurisdictions reported data on all overdose deaths, and ten reported data for a subset of counties accounting for an estimated &#x02265; 75% of drug overdose deaths in the jurisdiction. Jurisdictions abstracted data from death certificates and medical examiner/coroner reports, including death scene investigation findings and all drugs detected by postmortem toxicology testing; only cases with medical examiner/coroner reports were included.<sup><xref rid="FN2" ref-type="fn">1</xref></sup> Data for 2020 were not included to avoid potential emerging trends associated with the COVID-19 pandemic, such as possible changes in naloxone access and drug-use behaviors (e.g., possible changes in PWUD using drugs alone) (<xref rid="R2" ref-type="bibr">Ali et al., 2021</xref>).</p><p id="P12">We classified deaths as having no evidence of naloxone administration (hereafter &#x0201c;no naloxone&#x0201d;) if there was no scene and no witness evidence to suggest naloxone was administered by a layperson, EMS responder, law enforcement officer, firefighter, or health care worker in an emergency room, hospital, or critical care center; or if toxicology testing did not detect naloxone. If buprenorphine and naloxone were detected by toxicology testing, deaths were classified as no naloxone (absent scene evidence) to avoid misclassifying decedents with the combination buprenorphine-naloxone in their system, which is used to treat opioid use disorder.</p><p id="P13">We examined percentages of no naloxone among deaths with at least one opioid (with or without co-involvement of other drugs) as a cause of death (COD), for seven sociodemographic characteristics: age, sex, race/ethnicity, educational attainment, marital status, housing status, and military service. Cases with missing or unknown values were excluded from subgroup analyses. Frequencies and percentages of no naloxone were estimated in SAS 9.4, SAS Institute. Chi square tests were used to assess subgroup differences; p &#x0003c; 0.05 was considered statistically significant.</p></sec><sec id="S7"><label>3.</label><title>Results</title><p id="P14">Thirty-eight jurisdictions reported 40,288 overdose deaths during 2019. Of these deaths, 82.1% (33,804) involved at least one opioid as a COD. Among opioid-involved overdose deaths, 77.3% were classified as no naloxone. Among the 6484 decedents without an opioid as a COD, 85.8% were classified as no naloxone (not shown and excluded from further analyses). We observed statistically significant subgroup differences in no naloxone opioid-involved overdose deaths for all sociodemographic characteristics other than housing status (<xref rid="T1" ref-type="table">Table 1</xref>).</p><p id="P15">We highlight subgroups with percentages of no naloxone that were &#x02265; 5% higher or lower than the overall percentage among opioid-involved deaths (77.3%). The oldest age groups were among the highest percentages of no naloxone (83.4% for 55&#x02013;64 years and 87.2% for &#x02265;65 years); the percentage for those &#x0003c; 15 years was 87.5% but represented only 35 decedents. Those with the highest educational attainment (doctorate or professional degree), single, not otherwise specified decedents, and current or former military personnel were also among subgroups with the highest percentages of no naloxone (87.0%, 84.5%, and 82.3%, respectively). In contrast, the subgroups with the lowest percentages of no naloxone were non-Hispanic American Indian/Alaskan Native persons (66.2%) and those ages 15&#x02013;24 years (70.8%).</p></sec><sec id="S8"><label>4.</label><title>Discussion</title><p id="P16">SUDORS data allow us to investigate patterns in reported naloxone administration among overdose decedents that may inform public health strategies and overdose prevention policies. The vast majority had no evidence of naloxone administration. These findings are concerning because of the large proportion of overdose deaths that involve opioids, and, in particular, highly-potent IMFs, for which early and sufficient naloxone administration is critical for survival (<xref rid="R30" ref-type="bibr">O&#x02019;Donnell et al., 2021</xref>). The low percentages of naloxone administration, however, may also reflect naloxone&#x02019;s success, when administered, because the current analysis included only overdose deaths.</p><p id="P17">Approximately one in five decedents had evidence of naloxone administration that did not prevent the fatal overdose. Information on timing of naloxone administration and whether naloxone was administered appropriately was not available. Fentanyl&#x02019;s short duration of effect may increase frequency of its use, potentially leading to the need for more frequent naloxone administration in addition to the potential need for multiple doses (<xref rid="R18" ref-type="bibr">Kim et al., 2019</xref>; <xref rid="R26" ref-type="bibr">Moss and Carlo, 2019</xref>). In April 2021, the U.S. Food and Drug Administration approved a higher dose naloxone hydrochloride nasal spray (8 milligrams (mg) versus 2 mg and 4 mg products previously) (<xref rid="R36" ref-type="bibr">USFDA, 2021</xref>). SUDORS 2019 data reflect the period before this dosage increase but during which time fatal overdoses involving IMFs and co-use of stimulants and opioids increased (<xref rid="R24" ref-type="bibr">Mattson et al., 2021</xref>; <xref rid="R28" ref-type="bibr">O&#x02019;Donnell et al., 2020a</xref>, <xref rid="R29" ref-type="bibr">2020b</xref>). Further, naloxone&#x02019;s duration of effect depends on dose, route of administration, and overdose symptoms (<xref rid="R4" ref-type="bibr">Boyer, 2012</xref>). Resuscitation efforts to support breathing and prolonged monitoring for possible return of overdose symptoms are important aspects of post-naloxone care (<xref rid="R4" ref-type="bibr">Boyer, 2012</xref>; <xref rid="R40" ref-type="bibr">WHO, 2014</xref>). Both the failure to administer naloxone and the administration of naloxone without achieving overdose reversal are adverse outcomes. In addition to increasing naloxone use, mortality prevention strategies can focus on ensuring sufficient doses are administered appropriately in a timely fashion and follow-up care is provided. Both strategies require another person to be present, highlighting the importance of not using drugs alone.</p><p id="P18">We observed statistically significant differences in the percentages of decedents with no naloxone evidence in all but one of the sociodemographic groups examined, though not all were of substantial magnitude (e.g., only a 2.1% difference between males and females). It is important to interpret findings in the context of the population represented by SUDORS data, i.e., people who died from a drug overdose. Without the complement of those who overdosed and survived, we cannot fully characterize disparities. Stigma towards PWUD varies by the sociodemographic characteristics of both the persons with potentially stigmatizing attitudes and the PWUD (<xref rid="R13" ref-type="bibr">Goodyear and Chavanne, 2020</xref>). It is possible that an especially high percentage of no naloxone among some subgroups is influenced by stigma that impacts naloxone use and/or bias in acknowledging risk of drug overdose among certain populations. For example, 87% no naloxone was observed among those with a PhD or professional degree; however, higher SES individuals may not be well-represented in this sample if they were more likely to survive a drug overdose. Similarly, the high no naloxone among the 65 + age group (87%) might be influenced by misconceptions about low illicit and prescription drug misuse among elderly populations.</p><p id="P19">Individual, societal, and policy-level factors may play a role in naloxone&#x02019;s administration, which may in turn contribute to sociodemographic differences. Overdose circumstances, such as place (e.g., at home vs. in public, rural vs. urban setting) and presence and type of bystanders to administer naloxone appropriately, are important. Community access to and use of naloxone may be related to funding, training for EMS personnel and other first responders and laypersons, and Good Samaritan laws. Such multi-level influences are suggested by studies of unhoused PWUD for whom inadequate naloxone availability may be associated with this population&#x02019;s greater exposure to public drug use and overdose, more frequent need for naloxone administration, and thus greater need for refills; (<xref rid="R20" ref-type="bibr">Kinnard et al., 2021</xref>; <xref rid="R35" ref-type="bibr">Trayner et al., 2020</xref>; <xref rid="R9" ref-type="bibr">Deonarine et al., 2016</xref>).</p><p id="P20">Challenges to obtaining high quality overdose data include stigma, legal ramifications, and resources. Data abstraction relies on source data (e.g., death certificates, medical examiner/coroner reports, and toxicology results) that vary in availability and quality across jurisdictions. Misclassification bias may stem from the inclusion of 13,267 decedents (40% of opioid-involved overdose deaths) with unknown naloxone status in the no evidence of naloxone group, and naloxone administration may be higher than 22.7%. Despite limitations to estimating naloxone administration and sociodemographic disparities, this analysis suggests that a high proportion of people who died from opioid-involved overdose in the U.S. in 2019 did not receive naloxone, which might have reversed overdoses and saved lives.</p><p id="P21">A range of approaches is needed to make naloxone ubiquitous and easily accessible to laypersons as well as EMS personnel and other first responders. The Office of National Drug Control Policy announced the release of a model law that provides states with a potential roadmap for expanding naloxone access and availability (<xref rid="R22" ref-type="bibr">LAPPA, 2021</xref>). Expanding access is important as studies have found low rates of the following: co-prescribing naloxone to people with both opioid and benzodiazepine prescriptions; dispensing naloxone prescriptions to those presenting in emergency departments for drug overdose, opioid use disorder, or withdrawal; using insurance to obtain naloxone; and accessing naloxone from retail pharmacies (<xref rid="R14" ref-type="bibr">Guy et al., 2021</xref>; <xref rid="R17" ref-type="bibr">Kilaru et al., 2021</xref>; <xref rid="R23" ref-type="bibr">Lin et al., 2020</xref>; <xref rid="R10" ref-type="bibr">Follman et al., 2019</xref>). Further, focusing on such avenues may exacerbate disparities in naloxone access given unequal access to care. Evidence suggests that community-based efforts (e.g., distribution in public place and through syringe service programs, training laypersons) have the potential to be an effective route for reducing fatal overdoses (<xref rid="R15" ref-type="bibr">Irvine et al., 2018</xref>; <xref rid="R25" ref-type="bibr">McClellan et al., 2018</xref>; <xref rid="R27" ref-type="bibr">Mueller et al., 2015</xref>; <xref rid="R12" ref-type="bibr">Giglio et al., 2015</xref>; <xref rid="R37" ref-type="bibr">Walley et al., 2013</xref>; <xref rid="R39" ref-type="bibr">Wheeler et al., 2015</xref>). Innovative approaches used during the COVID-19 pandemic, such as mail-based naloxone, may reduce gaps in naloxone access and use (<xref rid="R38" ref-type="bibr">Wenger et al., 2021</xref>). Cultural competence in overdose prevention strategies, such as engaging social networks and peer educators, will likely be crucial to engaging subpopulations in the use of naloxone. (<xref rid="R8" ref-type="bibr">Dayton et al., 2020</xref>).</p></sec><sec id="S9"><label>5.</label><title>Conclusions</title><p id="P22">Ongoing efforts by CDC and participating SUDORS jurisdictions to improve the quality of drug overdose data through partnerships and resources for medicolegal death investigators, medical examiners and coroners, and forensic toxicologists are critical to identify gaps in overdose mortality prevention, such as naloxone administration. Future research could aim to link fatal and nonfatal overdose data to better characterize disparities in naloxone administration and successful or unsuccessful use. Analyses of geographic and temporal trends, which may be influenced by variation in programs and policies, the COVID-19 pandemic, and other factors, may inform our understanding of naloxone outcomes. Because inter-related individual and societal factors likely influence naloxone outcomes through various pathways, multivariable models could attempt to examine the influences of overdose circumstances (e.g., rapid onset overdose, EMS response time, presence of bystanders) and whether they differ by sociodemographic characteristics. While surveillance and research are being advanced, public health partners can assist PWUD to maintain adequate naloxone supply and amplify messages about the high risk of using drugs alone among PWUD and their social networks.</p></sec></body><back><ack id="S10"><title>Role of funding source</title><p id="P24">Nothing declared.</p></ack><fn-group><fn id="FN2"><label>1</label><p id="P29">For additional SUDORS description see O&#x02019;Donnell, J., Gladden, R.M., Kariisa, M., Mattson, C.L.,2021. Using death scene and toxicology evidence to define involvement of heroin, pharmaceutical morphine, illicitly manufactured fentanyl and pharmaceutical fentanyl in opioid overdose deaths, 38 states and the District of Columbia, January 2018&#x02013;December 2019. Addiction. 1&#x02013;8. 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<hr/>
</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Sex (n = 0 missing/unknown)</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Male</td><td align="right" valign="middle" rowspan="1" colspan="1">18,062</td><td align="left" valign="middle" rowspan="1" colspan="1">77.9</td><td align="right" valign="middle" rowspan="1" colspan="1">5130</td><td align="left" valign="middle" rowspan="1" colspan="1">22.1</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Female</td><td align="right" valign="bottom" rowspan="1" colspan="1">7502</td><td align="left" valign="bottom" rowspan="1" colspan="1">75.8</td><td align="right" valign="bottom" rowspan="1" colspan="1">2390</td><td align="left" valign="bottom" rowspan="1" colspan="1">24.2</td></tr><tr><td colspan="2" align="left" valign="bottom" rowspan="1">Race/ethnicity (n = 310 missing/unknown)</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;White, non-Hispanic</td><td align="right" valign="top" rowspan="1" colspan="1">18,683</td><td align="left" valign="top" rowspan="1" colspan="1">77.6</td><td align="right" valign="top" rowspan="1" colspan="1">5381</td><td align="left" valign="top" rowspan="1" colspan="1">22.4</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Black, non-Hispanic</td><td align="right" valign="top" rowspan="1" colspan="1">4029</td><td align="left" valign="top" rowspan="1" colspan="1">76.5</td><td align="right" valign="top" rowspan="1" colspan="1">1237</td><td align="left" valign="top" rowspan="1" colspan="1">23.5</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;American Indian/Alaskan native,</td><td align="right" valign="top" rowspan="1" colspan="1">196</td><td align="left" valign="bottom" rowspan="1" colspan="1">66.2</td><td align="right" valign="bottom" rowspan="1" colspan="1">100</td><td align="left" valign="top" rowspan="1" colspan="1">33.8</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;non-Hispanic</td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Asian/Pacific Islander, non-Hispanic</td><td align="right" valign="top" rowspan="1" colspan="1">139</td><td align="left" valign="bottom" rowspan="1" colspan="1">80.8</td><td align="right" valign="top" rowspan="1" colspan="1">33</td><td align="left" valign="top" rowspan="1" colspan="1">19.2</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Multi-race, non-Hispanic</td><td align="right" valign="top" rowspan="1" colspan="1">149</td><td align="left" valign="top" rowspan="1" colspan="1">72.0</td><td align="right" valign="top" rowspan="1" colspan="1">58</td><td align="left" valign="bottom" rowspan="1" colspan="1">28.0</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Hispanic</td><td align="right" valign="bottom" rowspan="1" colspan="1">2118</td><td align="left" valign="top" rowspan="1" colspan="1">76.5</td><td align="right" valign="top" rowspan="1" colspan="1">651</td><td align="left" valign="top" rowspan="1" colspan="1">23.5</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">Age (years) (n = 4 missing/unknown)</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Under 15</td><td align="right" valign="top" rowspan="1" colspan="1">35</td><td align="left" valign="top" rowspan="1" colspan="1">87.5</td><td align="right" valign="top" rowspan="1" colspan="1">5</td><td align="left" valign="top" rowspan="1" colspan="1">12.5</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;15&#x02013;24</td><td align="right" valign="bottom" rowspan="1" colspan="1">1612</td><td align="left" valign="middle" rowspan="1" colspan="1">70.8</td><td align="right" valign="bottom" rowspan="1" colspan="1">666</td><td align="left" valign="middle" rowspan="1" colspan="1">29.2</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;25&#x02013;35</td><td align="right" valign="top" rowspan="1" colspan="1">6557</td><td align="left" valign="top" rowspan="1" colspan="1">73.3</td><td align="right" valign="top" rowspan="1" colspan="1">2391</td><td align="left" valign="top" rowspan="1" colspan="1">26.7</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;35&#x02013;44</td><td align="right" valign="top" rowspan="1" colspan="1">6633</td><td align="left" valign="top" rowspan="1" colspan="1">76.2</td><td align="right" valign="top" rowspan="1" colspan="1">2072</td><td align="left" valign="top" rowspan="1" colspan="1">23.8</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;45&#x02013;54</td><td align="right" valign="top" rowspan="1" colspan="1">5467</td><td align="left" valign="top" rowspan="1" colspan="1">79.7</td><td align="right" valign="top" rowspan="1" colspan="1">1389</td><td align="left" valign="top" rowspan="1" colspan="1">20.3</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;55&#x02013;64</td><td align="right" valign="top" rowspan="1" colspan="1">4278</td><td align="left" valign="top" rowspan="1" colspan="1">83.4</td><td align="right" valign="top" rowspan="1" colspan="1">853</td><td align="left" valign="bottom" rowspan="1" colspan="1">16.6</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;65 +</td><td align="right" valign="top" rowspan="1" colspan="1">978</td><td align="left" valign="top" rowspan="1" colspan="1">87.2</td><td align="right" valign="top" rowspan="1" colspan="1">144</td><td align="left" valign="bottom" rowspan="1" colspan="1">12.8</td></tr><tr><td colspan="3" align="left" valign="bottom" rowspan="1">Educational attainment (n = 1085 missing/unknown)</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;8th grade or less</td><td align="right" valign="top" rowspan="1" colspan="1">736</td><td align="left" valign="top" rowspan="1" colspan="1">78.6</td><td align="right" valign="bottom" rowspan="1" colspan="1">200</td><td align="left" valign="top" rowspan="1" colspan="1">21.4</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;9&#x02013;12th grade, no diploma</td><td align="right" valign="bottom" rowspan="1" colspan="1">4077</td><td align="left" valign="bottom" rowspan="1" colspan="1">74.9</td><td align="right" valign="bottom" rowspan="1" colspan="1">1365</td><td align="left" valign="bottom" rowspan="1" colspan="1">25.1</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;High school graduate or GED</td><td align="right" valign="top" rowspan="1" colspan="1">13,096</td><td align="left" valign="top" rowspan="1" colspan="1">77.4</td><td align="right" valign="top" rowspan="1" colspan="1">3825</td><td align="left" valign="bottom" rowspan="1" colspan="1">22.6</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;College credit, no degree</td><td align="right" valign="top" rowspan="1" colspan="1">3648</td><td align="left" valign="top" rowspan="1" colspan="1">76.1</td><td align="right" valign="top" rowspan="1" colspan="1">1149</td><td align="left" valign="top" rowspan="1" colspan="1">23.9</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Associate&#x02019;s degree</td><td align="right" valign="bottom" rowspan="1" colspan="1">1430</td><td align="left" valign="bottom" rowspan="1" colspan="1">78.5</td><td align="right" valign="bottom" rowspan="1" colspan="1">391</td><td align="left" valign="bottom" rowspan="1" colspan="1">29.5</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Bachelor&#x02019;s degree</td><td align="right" valign="bottom" rowspan="1" colspan="1">1365</td><td align="left" valign="bottom" rowspan="1" colspan="1">81.1</td><td align="right" valign="bottom" rowspan="1" colspan="1">318</td><td align="left" valign="bottom" rowspan="1" colspan="1">18.9</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Master&#x02019;s degree</td><td align="right" valign="bottom" rowspan="1" colspan="1">248</td><td align="left" valign="bottom" rowspan="1" colspan="1">80.8</td><td align="right" valign="bottom" rowspan="1" colspan="1">59</td><td align="left" valign="bottom" rowspan="1" colspan="1">19.2</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Doctorate or professional degree</td><td align="right" valign="bottom" rowspan="1" colspan="1">80</td><td align="left" valign="middle" rowspan="1" colspan="1">87.0</td><td align="right" valign="bottom" rowspan="1" colspan="1">12</td><td align="left" valign="middle" rowspan="1" colspan="1">13.0</td></tr><tr><td colspan="2" align="left" valign="bottom" rowspan="1">Military service (n = 1864 missing/unknown)</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;No military service</td><td align="right" valign="top" rowspan="1" colspan="1">22,757</td><td align="left" valign="top" rowspan="1" colspan="1">77.3</td><td align="right" valign="top" rowspan="1" colspan="1">6670</td><td align="left" valign="top" rowspan="1" colspan="1">22.7</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Current or former military</td><td align="right" valign="bottom" rowspan="1" colspan="1">1475</td><td align="left" valign="bottom" rowspan="1" colspan="1">82.3</td><td align="right" valign="bottom" rowspan="1" colspan="1">318</td><td align="left" valign="bottom" rowspan="1" colspan="1">17.7</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;personnel</td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td colspan="2" align="left" valign="top" rowspan="1">Housing status (n = 2171 missing/unknown)</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Not experiencing homelessness</td><td align="right" valign="bottom" rowspan="1" colspan="1">22,828</td><td align="left" valign="top" rowspan="1" colspan="1">77.1</td><td align="right" valign="top" rowspan="1" colspan="1">6766</td><td align="left" valign="top" rowspan="1" colspan="1">22.9</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Experiencing homelessness</td><td align="right" valign="middle" rowspan="1" colspan="1">1021</td><td align="left" valign="top" rowspan="1" colspan="1">77.4</td><td align="right" valign="top" rowspan="1" colspan="1">298</td><td align="left" valign="middle" rowspan="1" colspan="1">22.6</td></tr><tr><td colspan="2" align="left" valign="bottom" rowspan="1">Marital status (n = 617 missing/unknown)</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Married, civil union, domestic</td><td align="right" valign="bottom" rowspan="1" colspan="1">3886</td><td align="left" valign="bottom" rowspan="1" colspan="1">74.8</td><td align="right" valign="bottom" rowspan="1" colspan="1">1313</td><td align="left" valign="bottom" rowspan="1" colspan="1">25.2</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;partnership</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Never married</td><td align="right" valign="top" rowspan="1" colspan="1">14,102</td><td align="left" valign="top" rowspan="1" colspan="1">76.2</td><td align="right" valign="top" rowspan="1" colspan="1">4415</td><td align="left" valign="top" rowspan="1" colspan="1">23.8</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Widowed</td><td align="right" valign="middle" rowspan="1" colspan="1">902</td><td align="left" valign="bottom" rowspan="1" colspan="1">81.8</td><td align="right" valign="bottom" rowspan="1" colspan="1">201</td><td align="left" valign="bottom" rowspan="1" colspan="1">18.2</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Divorced</td><td align="right" valign="top" rowspan="1" colspan="1">5485</td><td align="left" valign="top" rowspan="1" colspan="1">80.7</td><td align="right" valign="top" rowspan="1" colspan="1">1312</td><td align="left" valign="top" rowspan="1" colspan="1">19.3</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Married, civil union, domestic</td><td align="right" valign="bottom" rowspan="1" colspan="1">496</td><td align="left" valign="bottom" rowspan="1" colspan="1">77.7</td><td align="right" valign="bottom" rowspan="1" colspan="1">142</td><td align="left" valign="bottom" rowspan="1" colspan="1">22.3</td></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;partnership, separated</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="middle" rowspan="1" colspan="1">&#x02003;Single, not otherwise specified</td><td align="right" valign="middle" rowspan="1" colspan="1">180</td><td align="left" valign="top" rowspan="1" colspan="1">84.5</td><td align="right" valign="top" rowspan="1" colspan="1">33</td><td align="left" valign="top" rowspan="1" colspan="1">15.5</td></tr></tbody></table><table-wrap-foot><fn id="TFN1"><p id="P31">Chi-squared tests compared categories within each sociodemographic characteristic and were statistically significant for all at p &#x0003c; 0.0001, except for housing status (p = 0.8).</p></fn><fn id="TFN2"><label>a</label><p id="P32">38 jurisdictions include the following states and District of Columbia: Alaska, Arizona, Colorado, Connecticut, Delaware, Florida, Georgia, Illinois, Indiana, Kansas, Kentucky, Louisiana Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Montana, Nevada, New Hampshire, New Jersey, New Mexico, North Carolina, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Dakota, Tennessee, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin.</p></fn><fn id="TFN3"><label>b</label><p id="P33">Florida, Louisiana, Maryland, and Michigan reported data for only January- June 2019. Arizona, Colorado, Kansas, Montana, Oregon, and South Dakota reported data for only July-December 2019.</p></fn></table-wrap-foot></table-wrap></floats-group></article>