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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">8508335</journal-id><journal-id journal-id-type="pubmed-jr-id">3436</journal-id><journal-id journal-id-type="nlm-ta">Diabetes Res Clin Pract</journal-id><journal-id journal-id-type="iso-abbrev">Diabetes Res Clin Pract</journal-id><journal-title-group><journal-title>Diabetes research and clinical practice</journal-title></journal-title-group><issn pub-type="ppub">0168-8227</issn><issn pub-type="epub">1872-8227</issn></journal-meta><article-meta><article-id pub-id-type="pmid">38968092</article-id><article-id pub-id-type="pmc">11226753</article-id><article-id pub-id-type="doi">10.1016/j.diabres.2023.110985</article-id><article-id pub-id-type="manuscript">HHSPA1987381</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Change in testing for blood glucose during the COVID-19 pandemic, United States 2019&#x02013;2021</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Miyamoto</surname><given-names>Yoshihisa</given-names></name><xref rid="CR1" ref-type="corresp">*</xref></contrib><contrib contrib-type="author"><name><surname>Saelee</surname><given-names>Ryan</given-names></name></contrib><contrib contrib-type="author"><name><surname>Koyama</surname><given-names>Alain K.</given-names></name></contrib><contrib contrib-type="author"><name><surname>Zaganjor</surname><given-names>Ibrahim</given-names></name></contrib><contrib contrib-type="author"><name><surname>Xu</surname><given-names>Fang</given-names></name></contrib><contrib contrib-type="author"><name><surname>Onufrak</surname><given-names>Stephen</given-names></name></contrib><contrib contrib-type="author"><name><surname>Pavkov</surname><given-names>Meda E.</given-names></name></contrib><aff id="A1">Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention (CDC), Atlanta, GA, USA</aff></contrib-group><author-notes><corresp id="CR1"><label>*</label>Corresponding author at: Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, 4770 Buford Hwy NE, Atlanta, GA, 30341, USA. <email>twh8@cdc.gov</email> (Y. Miyamoto).</corresp></author-notes><pub-date pub-type="nihms-submitted"><day>20</day><month>4</month><year>2024</year></pub-date><pub-date pub-type="ppub"><month>11</month><year>2023</year></pub-date><pub-date pub-type="epub"><day>29</day><month>10</month><year>2023</year></pub-date><pub-date pub-type="pmc-release"><day>06</day><month>7</month><year>2024</year></pub-date><volume>205</volume><fpage>110985</fpage><lpage>110985</lpage><abstract id="ABS1"><sec id="S1"><title>Aim:</title><p id="P1">This study assessed changes in testing for blood glucose in the United States (US) from 2019 to 2021.</p></sec><sec id="S2"><title>Methods:</title><p id="P2">We conducted a serial cross-sectional analysis of the 2019&#x02013;2021 National Health Interview Survey by including adults aged &#x02265; 18 years without reported diagnosed diabetes. We estimated the prevalence of testing for blood glucose within 12 months and the difference in the testing prevalence between 2019 and 2021.</p></sec><sec id="S3"><title>Results:</title><p id="P3">The study sample included 82,594 respondents without diabetes in 2019&#x02013;&#x02013;2021, with a mean age between 46.4 and 46.8 years. Overall, the prevalence of testing for blood glucose decreased significantly from 64.2 % (95 % confidence interval [CI] 63.3 %, 65.1 %) in 2019 to 60.0 % (95 % CI 59.1 %, 60.9 %) in 2021. Among adults who met the United States Preventive Services Task Force&#x02019;s 2015 screening recommendation, the prevalence decreased from 73.4 % (95 % CI 72.2 %, 74.6 %) to 69.5 % (95 % CI 68.3 %, 70.6 %). Although decreases in testing were observed in most groups, the extent of the decline differed by subgroups.</p></sec><sec id="S4"><title>Conclusions:</title><p id="P4">Testing for blood glucose decreased in the US during the COVID-19 pandemic. This may have delayed diagnosis and treatment of prediabetes and diabetes, underscoring the importance of continued access to diabetes screening during pandemics.</p></sec></abstract><kwd-group><kwd>Diabetes</kwd><kwd>Prediabetes</kwd><kwd>Screening</kwd><kwd>Testing</kwd><kwd>COVID-19</kwd></kwd-group></article-meta></front><body><sec id="S5"><label>1.</label><title>Introduction</title><p id="P5">Diabetes and prediabetes affect 13 % and 34.5 % of U.S. adults, respectively [<xref rid="R1" ref-type="bibr">1</xref>]. Testing adults&#x02019; blood glucose levels to screen for prediabetes or diabetes is important for early detection and subsequent management. Regular screening of asymptomatic individuals is vital to achieve the Healthy People 2030 objectives: reduce the number of diabetes cases diagnosed yearly &#x02014; D-01; and reduce the proportion of adults who don&#x02019;t know they have prediabetes &#x02014; D-02 [<xref rid="R2" ref-type="bibr">2</xref>]. The U.S. Preventive Services Task Force (USPSTF) guideline in 2015 recommended screening for prediabetes and type 2 diabetes in adults aged 40&#x02013;70 years who are overweight or obese [<xref rid="R3" ref-type="bibr">3</xref>]. In 2021, the USPSTF updated the recommendation by lowering that age criteria for screening from 40 to 35 years for earlier detection [<xref rid="R4" ref-type="bibr">4</xref>].</p><p id="P6">The COVID-19 pandemic has negatively impacted preventive health services, and identification and management of chronic diseases [<xref rid="R5" ref-type="bibr">5</xref>]. Previous research showed that people delayed or avoided routine medical care during the pandemic [<xref rid="R6" ref-type="bibr">6</xref>]. Reports from Europe and the United Kingdom (U.K.) showed the COVID-19 pandemic adversely affected testing for glycated hemoglobin in people with or at risk for diabetes, delaying delivery of diabetes care [<xref rid="R7" ref-type="bibr">7</xref>,<xref rid="R8" ref-type="bibr">8</xref>]. One U.S. report showed that preventive health screenings for cardiometabolic diseases&#x02014;including diabetes&#x02014; and cancers declined in 2021 relative to 2019, with variation by educational attainment and race and ethnicity [<xref rid="R9" ref-type="bibr">9</xref>].</p><p id="P7">However, among adults without diagnosed diabetes, no study has assessed how changes in blood glucose testing differed by demographic factors and geographic locations. We hypothesized that disparities in demographic characteristics and geographic locations exist in blood glucose testing among adults without diagnosed diabetes. Capturing changes in preventive screening uptake is important, as its consequences may extend long after the pandemic, and it can inform future pandemic readiness. Therefore, we used the National Health Interview Survey (NHIS), 2019&#x02013;2021, to investigate the prevalence of blood glucose testing among U.S. adults without diagnosed diabetes&#x02014;overall and by selected sociodemographic characteristics.</p></sec><sec id="S6"><label>2.</label><title>Methods</title><sec id="S7"><label>2.1.</label><title>Data source</title><p id="P8">NHIS is a nationally representative survey of the U.S. civilian noninstitutionalized population conducted by the Centers for Disease Control and Prevention&#x02019;s National Center for Health Statistics (NCHS). NHIS collects information on health status, health-related behaviors, and accessibility to health care [<xref rid="R10" ref-type="bibr">10</xref>]. From before the COVID-19 pandemic until March 2020, interviews were conducted in respondents&#x02019; homes (following regular survey interviewing procedures). From April to June 2020, due to the COVID-19 pandemic, all interviews were conducted by telephone. From July 2020 to April 2021, contact with household members was attempted first via telephone, with subsequent home visits. After May 2021, interviewers returned to regular survey interviewing procedures. Households were sampled using a geographically clustered method. From each selected household, a sample adult was randomly selected to complete a more detailed interview about their health. The sample adult response rate was 59.1 %, 49.9 %, and 50.9 % in 2019, 2020, and 2021, respectively. We did not include data from NHIS prior to 2019 due to a major questionnaire redesign including change in some items and the sampling weights for nonresponse [<xref rid="R10" ref-type="bibr">10</xref>&#x02013;<xref rid="R12" ref-type="bibr">12</xref>].</p></sec><sec id="S8"><label>2.2.</label><title>Study population</title><p id="P9">The study population included non-pregnant adults aged &#x02265; 18 years who did not have self-reported diagnosed diabetes. We estimated the prevalence of respondents who received blood glucose testing within the previous 12 months based on the following question: &#x0201c;When was the last time you had a blood test for high blood sugar or diabetes by a doctor, nurse, or other health professional?&#x0201d;. In 2019 and 2020, the question was asked of all adults while in 2021 it was asked only among adults who reported not having diagnosed diabetes. Therefore, we restricted the study sample to those without self-reported diagnosed diabetes across years, to obtain comparable populations. Respondents in 2019 had a 1-year look-back period from January 2018 to December 2019, the period before the COVID-19 pandemic. Respondents interviewed in 2021 had a 1-year look-back from January 2020 to December 2021, corresponding with the initial occurrence of the pandemic, which was declared a Public Health Emergency of International Concern by the World Health Organization on January 30, 2020. We assumed that the difference in the prevalence of testing between 2019 and 2021 reflects the epidemic&#x02019;s possible impact on testing.</p></sec><sec id="S9"><label>2.3.</label><title>Statistical analysis</title><p id="P10">Between 2019 and 2021, descriptive statistics of the study population and the distribution of sociodemographic and clinical characteristics were compared using chi-squared test [<xref rid="R13" ref-type="bibr">13</xref>]. Prevalence of blood glucose testing with 95 % confidence intervals (CI) by year for sociodemographic and clinical characteristics were estimated using the Korn and Graubard method for complex survey design [<xref rid="R14" ref-type="bibr">14</xref>]. The 2013 NCHS urban&#x02013;rural classification scheme was used for counties: large central metro, large fringe metro, medium and small metro, and non-metropolitan [<xref rid="R15" ref-type="bibr">15</xref>]. Missing of income was imputed by NCHS for each year. Family income was assessed as the ratio of imputed household income to the federal poverty level (FPL), and categorized as &#x0003c; 100 %, 100&#x02013;300 %, or &#x02265; 300 % based on the distribution of the data. FPL published by the US Census Bureau depends on family size and the number of related children under 18 years [<xref rid="R16" ref-type="bibr">16</xref>,<xref rid="R17" ref-type="bibr">17</xref>]. A ratio of 100 % of FPL represents a family&#x02019;s income equal to the FPL and higher values correspond to higher income. Age-adjusted absolute and relative changes of testing prevalence were estimated using logistic regression and predictive marginal prevalence for each subgroup. In addition, we estimated the absolute and relative changes in prevalence after adjusting for all variables using a multivariable logistic regression model. We also repeated the analysis among adults who fulfilled the USPSTF 2015 screening recommendation for prediabetes or type 2 diabetes: adults aged 40&#x02013;70 years who have overweight or obesity based on self-reported weight and height [<xref rid="R3" ref-type="bibr">3</xref>]. All results were weighted to account for the complex survey design and to produce nationally representative estimates. For statistical analyses we used SAS callable SUDAAN version 11 (SAS Institute Inc, Cary, NC; RTI International, Research Triangle Park, NC).</p></sec></sec><sec id="S10"><label>3.</label><title>Results</title><p id="P11">The study sample included 82,594 respondents without diabetes in 2019&#x02013;2021, with a mean age of 46.4&#x02013;46.8 years (48.4 %&#x02013;48.7 % were men). Population characteristics by survey year are shown in <xref rid="T1" ref-type="table">Table 1</xref>. Most demographic features showed similar distributions over the 3 years. However, compared with adults in 2019, those in 2021 were on average older, more likely to report diagnosed prediabetes, living in large central metro areas, having health insurance, reporting higher income, and having a college degree or greater.</p><p id="P12">Overall, the prevalence of adults without diagnosed diabetes who received blood glucose testing within 12 months was 64.2 % (95 % CI 63.3 %, 65.1 %) in 2019 and 60.0 % (95 % CI 59.1 %, 60.9 %) in 2021. These findings are equivalent to an absolute change in percentage points of &#x02212;4.2 (95 % CI &#x02212;5.3, &#x02212;3.1) and a relative change of &#x02212;6.6 % (95 % CI, &#x02212;8.2 %,&#x02212;4.9 %). Among the adults who fulfilled the USPSTF 2015 recommendation for screening of prediabetes and type 2 diabetes, the absolute and relative change in prevalence from 2019 to 2021 was &#x02212;3.9 (95 % CI, &#x02212;5.6, &#x02212;2.3) and &#x02013;5.4 % (95 % CI, &#x02212;7.5 %, &#x02212;3.2 %), respectively. <xref rid="F1" ref-type="fig">Fig. 1</xref> shows the age-adjusted prevalence of adults who received testing for blood glucose within 12 months by year, overall and for those meeting USPSTF 2015 recommendation.</p><p id="P13"><xref rid="F2" ref-type="fig">Fig. 2</xref> shows age-adjusted absolute and relative change in testing prevalence from 2019 to 2021, and <xref rid="SD1" ref-type="supplementary-material">Supplemental Table 1</xref> also shows crude prevalence of adults who received blood glucose testing for the 3 years by selected characteristics. Significantly lower testing was observed for almost every demographic and geographic subgroup except non-Hispanic (NH) American Indian and Alaska Native adults, other single or multiple race adults, those with underweight, and those with family income &#x0003c; 100 % of FPL.</p><p id="P14">In 2019, prevalence of blood glucose testing within 12 months was lowest among adults without health insurance and in the youngest age group. The highest testing prevalence both in 2019 and 2021 was observed among adults aged 40&#x02013;64 years and &#x02265; 65 years, NH Black adults, and those with self-reported prediabetes.</p><p id="P15">The largest age-adjusted decline in testing prevalence, in both absolute and relative terms, was observed in NH Asian adults (&#x02212;10.0 and &#x02212; 14.8 %, respectively), the West region (&#x02212;7.2 and &#x02212; 12.0 %, respectively), large central metro areas (&#x02212;6.9 and &#x02212; 10.5 %, respectively), those without health insurance (&#x02212;6.3 and &#x02212; 17.3 %, respectively), and the youngest age group (&#x02212;5.0, &#x02212; 10.3 %, respectively). Notably, among racial and ethnic groups, Hispanic adults experienced the second-largest decline in testing, from 60.7 % in 2019 to 54.7 % in 2021 (&#x02212;6.1 % absolute and &#x02212; 10.0 % relative change).</p><p id="P16">More frequent testing in 2021 than 2019 was observed among NH American Indian and Alaska Native adults, other single or multiple race adults, and those with BMI &#x0003c; 18.5 kg/m<sup>2</sup>. However, these changes were not statistically significant, and the 51.9 %&#x02013;61.4 % testing prevalence attained in 2021 remained at the lower end of the overall prevalence distribution.</p><p id="P17"><xref rid="SD1" ref-type="supplementary-material">Supplemental Table 2</xref> showed multivariable-adjusted change in prevalence between 2019 and 2021 where similar trends to age-adjusted change were observed.</p></sec><sec id="S11"><label>4.</label><title>Discussion</title><p id="P18">In a nationally representative sample of US adults without diabetes, the prevalence of those who received blood glucose testing within 12 months was significantly lower in 2021 than in 2019, suggesting that screening for prediabetes or type 2 diabetes was negatively impacted during the COVID-19 pandemic. Lower testing prevalence from 2019 to 2021 was observed particularly in young adults, non-Hispanic Asian and Hispanic populations, those without health insurance, adults living in central metropolitan areas and adults living in the West. Although testing was consistently higher among adults meeting the 2015 USPSTF criteria, it declined over time in a manner similar to that of the general population without diagnosed diabetes.</p><p id="P19">Reduced use of preventive health services such as screening during the pandemic was consistently observed in our study and in reports from various countries, including the US [<xref rid="R9" ref-type="bibr">9</xref>,<xref rid="R18" ref-type="bibr">18</xref>], the UK [<xref rid="R7" ref-type="bibr">7</xref>,<xref rid="R19" ref-type="bibr">19</xref>], Canada [<xref rid="R20" ref-type="bibr">20</xref>], and Israel [<xref rid="R21" ref-type="bibr">21</xref>]. Because 31.5 % of US adults refrained from routine care during the pandemic due to reduced accessibility, decreased availability of public transportation or fear of exposure to COVID-19 [<xref rid="R6" ref-type="bibr">6</xref>, <xref rid="R22" ref-type="bibr">22</xref>], it is not surprising that people delayed or avoided blood glucose testing as well.</p><p id="P20">The low prevalence of blood glucose testing in the youngest population (aged 18&#x02013;39 years) before the COVID-19 pandemic and that group&#x02019;s further 10 % reduction during the pandemic reflects the generally low prevalence of preventive care in young adults [<xref rid="R23" ref-type="bibr">23</xref>] and a decreased usage of preventive care services [<xref rid="R24" ref-type="bibr">24</xref>]. This finding is concerning for at least two reasons. First, approximately 32 million people aged 18&#x02013;44 years have prediabetes [<xref rid="R25" ref-type="bibr">25</xref>], and they are less likely to be aware of their prediabetes status than older adults [<xref rid="R26" ref-type="bibr">26</xref>]. The observed delay in blood glucose testing might lead to more undetected prediabetes cases and a rise in type 2 diabetes incidence after 2021, as suggested by other population-based studies [<xref rid="R27" ref-type="bibr">27</xref>]. Secondly, national data indicate a resurgence in the incidence of diabetes complications among young and middle-aged adults after 2015 [<xref rid="R28" ref-type="bibr">28</xref>], suggesting that early detection and treatment of diabetes is critical in this population [<xref rid="R29" ref-type="bibr">29</xref>]. It remains to be seen if lowering the age for prediabetes and diabetes screening from 40 to 35 years, as recommended by the USPSTF [<xref rid="R4" ref-type="bibr">4</xref>], will encourage higher rates of blood glucose testing to screen for prediabetes or type 2 diabetes in this segment of the population.</p><p id="P21">The racial and ethnic heterogeneity in testing for blood glucose persisted during the COVID-19 pandemic, with the highest testing prevalence among NH Black adults and the lowest in Hispanic adults and those of other single or multiple races. The largest attrition in testing frequency occurring among NH Asian adults is consistent with one previous report which included only adults aged 40&#x02013;75 [<xref rid="R9" ref-type="bibr">9</xref>]. NH Asian adults had relatively high testing prevalence in 2019; also they were on average less likely to be in the lower income bracket, or to lack health care access or health insurance than other non-White racial and ethnic groups. A combination of potential factors may have prevailed in this population, including its larger concentration in the West&#x02014;where testing was consistently lower than in other regions&#x02014;experiences of discrimination [<xref rid="R30" ref-type="bibr">30</xref>], language barriers [<xref rid="R31" ref-type="bibr">31</xref>], and possibly stricter adoption of isolation practices for COVID-19 prevention [<xref rid="R32" ref-type="bibr">32</xref>].</p><p id="P22">The increasing trend in testing uptake from 2019 to 2021 was unexpected in some groups such as NH American Indian and Alaska Native adults although the differences were not statistically significant, possibly due to the low sample numbers. Use of remote technology in the Indian Health Service might partly explain this population&#x02019;s increase in health care visits and subsequent testing uptake [<xref rid="R33" ref-type="bibr">33</xref>]. One study from a single integrated academic health system in the Upper Midwest showed that American Indian and Alaska Native adults were more likely to use a video or audio visit vs. in-person visits, compared with other race and ethnicity groups in 2020, during the early months of the COVID-19 pandemic [<xref rid="R34" ref-type="bibr">34</xref>]. It may be worth considering further research about the effects of telemedicine on testing during the pandemic.</p><p id="P23">Change in testing is linked to locality. People living in large central metro areas may have been more affected by the pandemic, possibly due to enforcement of quarantine measures. In addition, the higher proportion of younger people in urban areas may partly explain the lower testing rates [<xref rid="R35" ref-type="bibr">35</xref>]. Consistently lower testing rates in rural areas may be explained by disparities in health care access linked to financial constraints [<xref rid="R36" ref-type="bibr">36</xref>,<xref rid="R37" ref-type="bibr">37</xref>], in addition to demographics (e.g., rural residents were more likely to be NH White and older).</p><p id="P24">We acknowledge several limitations. NHIS collected self-reported data, which are subject to recall biases. There was also a change to phone interviews during 2020 due to the pandemic, with a lower response rate that may reflect selection bias. Due to a major questionnaire redesign in 2019, we could not assess trends in blood glucose testing to compare frequency before and after 2019.</p></sec><sec id="S12"><label>5.</label><title>Conclusions</title><p id="P25">Testing for blood glucose decreased in the US during the COVID-19 pandemic, with differences by socio-demographic, clinical, and geographic characteristics. Delayed blood glucose testing could result in a higher burden of diabetes management in the post-pandemic era. The study findings reveal the need to encourage diabetes screenings post-pandemic and subsequently, as well as awareness and management of diabetes&#x02014;especially among people who are at increased risk for diabetes. In addition, our findings may be helpful in preparing for a potential pandemic in the future. Routine blood glucose testing among adults without diagnosed diabetes may be an important first step in the cascade of appropriate care for people with diabetes and developing resilient screening systems is warranted.</p></sec><sec sec-type="supplementary-material" id="SM1"><title>Supplementary Material</title><supplementary-material id="SD1" position="float" content-type="local-data"><label>Supplemental</label><media xlink:href="NIHMS1987381-supplement-Supplemental.docx" id="d67e342" position="anchor"/></supplementary-material></sec></body><back><fn-group><fn id="FN1"><p id="P26">Disclaimer: The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.</p><p id="P27">This project was supported in part by an appointment to the Research Participation Program at the Centers for Disease Control and Prevention (CDC), administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and the CDC.</p></fn><fn fn-type="COI-statement" id="FN2"><p id="P28">The authors declare no conflict of interest.</p></fn><fn fn-type="COI-statement" id="FN3"><p id="P29">Declaration of Competing Interest</p><p id="P30">The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.</p></fn><fn id="FN4"><p id="P31">Appendix A. Supplementary data</p><p id="P32">Supplementary data to this article can be found online at <ext-link xlink:href="10.1016/j.diabres.2023.110985" ext-link-type="doi">https://doi.org/10.1016/j.diabres.2023.110985</ext-link>.</p></fn></fn-group><ref-list><title>References</title><ref id="R1"><label>[1]</label><mixed-citation publication-type="other"><collab>Centers for Disease Control and Prevention US Department of Health and Human Services</collab>
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<bold>Age groups, years</bold>
</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"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1">&#x0003c;0.01</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">18&#x02013;39</td><td align="left" valign="top" rowspan="1" colspan="1">9,259</td><td align="left" valign="top" rowspan="1" colspan="1">40.7 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">8,224</td><td align="left" valign="top" rowspan="1" colspan="1">40.3 (0.5)</td><td align="left" valign="top" rowspan="1" colspan="1">8,253</td><td align="left" valign="top" rowspan="1" colspan="1">40.0 (0.5)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">40&#x02013;64</td><td align="left" valign="top" rowspan="1" colspan="1">11,549</td><td align="left" valign="top" rowspan="1" colspan="1">40.6 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">11,642</td><td align="left" valign="top" rowspan="1" colspan="1">40.7 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">10,571</td><td align="left" valign="top" rowspan="1" colspan="1">40.0 (0.4)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02265;65</td><td align="left" valign="top" rowspan="1" colspan="1">7,524</td><td align="left" valign="top" rowspan="1" colspan="1">18.7 (0.3)</td><td align="left" valign="top" rowspan="1" colspan="1">8,104</td><td align="left" valign="top" rowspan="1" colspan="1">19.1 (0.3)</td><td align="left" valign="top" rowspan="1" colspan="1">7,242</td><td align="left" valign="top" rowspan="1" colspan="1">19.9 (0.3)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">
<bold>Sex</bold>
</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"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1">0.56</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Men</td><td align="left" valign="top" rowspan="1" colspan="1">13,115</td><td align="left" valign="top" rowspan="1" colspan="1">48.7 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">12,885</td><td align="left" valign="top" rowspan="1" colspan="1">48.4 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">11,855</td><td align="left" valign="top" rowspan="1" colspan="1">48.4 (0.4)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Women</td><td align="left" valign="top" rowspan="1" colspan="1">15,295</td><td align="left" valign="top" rowspan="1" colspan="1">51.3 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">15,150</td><td align="left" valign="top" rowspan="1" colspan="1">51.6 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">14,288</td><td align="left" valign="top" rowspan="1" colspan="1">51.6 (0.4)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">
<bold>Race and ethnicity</bold>
</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"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1">0.88</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Hispanic</td><td align="left" valign="top" rowspan="1" colspan="1">3,674</td><td align="left" valign="top" rowspan="1" colspan="1">16.5 (0.7)</td><td align="left" valign="top" rowspan="1" colspan="1">3,375</td><td align="left" valign="top" rowspan="1" colspan="1">16.6 (0.7)</td><td align="left" valign="top" rowspan="1" colspan="1">3,582</td><td align="left" valign="top" rowspan="1" colspan="1">16.7 (0.7)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">NH White</td><td align="left" valign="top" rowspan="1" colspan="1">19,626</td><td align="left" valign="top" rowspan="1" colspan="1">63.7 (0.8)</td><td align="left" valign="top" rowspan="1" colspan="1">19,813</td><td align="left" valign="top" rowspan="1" colspan="1">63.5 (0.8)</td><td align="left" valign="top" rowspan="1" colspan="1">17,644</td><td align="left" valign="top" rowspan="1" colspan="1">63.5 (0.8)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">NH Black</td><td align="left" valign="top" rowspan="1" colspan="1">2,941</td><td align="left" valign="top" rowspan="1" colspan="1">11.4 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">2,678</td><td align="left" valign="top" rowspan="1" colspan="1">11.2 (0.5)</td><td align="left" valign="top" rowspan="1" colspan="1">2,621</td><td align="left" valign="top" rowspan="1" colspan="1">11.1 (0.5)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">NH Asian</td><td align="left" valign="top" rowspan="1" colspan="1">1,495</td><td align="left" valign="top" rowspan="1" colspan="1">5.9 (0.3)</td><td align="left" valign="top" rowspan="1" colspan="1">1,517</td><td align="left" valign="top" rowspan="1" colspan="1">5.9 (0.3)</td><td align="left" valign="top" rowspan="1" colspan="1">1,627</td><td align="left" valign="top" rowspan="1" colspan="1">6.0 (0.3)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">NH AIAN</td><td align="left" valign="top" rowspan="1" colspan="1">372</td><td align="left" valign="top" rowspan="1" colspan="1">1.3 (0.2)</td><td align="left" valign="top" rowspan="1" colspan="1">362</td><td align="left" valign="top" rowspan="1" colspan="1">1.4 (0.2)</td><td align="left" valign="top" rowspan="1" colspan="1">335</td><td align="left" valign="top" rowspan="1" colspan="1">1.3 (0.2)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Other single or multiple races</td><td align="left" valign="top" rowspan="1" colspan="1">305</td><td align="left" valign="top" rowspan="1" colspan="1">1.2 (0.1)</td><td align="left" valign="top" rowspan="1" colspan="1">291</td><td align="left" valign="top" rowspan="1" colspan="1">1.2 (0.1)</td><td align="left" valign="top" rowspan="1" colspan="1">336</td><td align="left" valign="top" rowspan="1" colspan="1">1.4 (0.1)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>Weight Status</bold>
<xref rid="TFN3" ref-type="table-fn">**</xref></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"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1">0.13</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Underweight</td><td align="left" valign="top" rowspan="1" colspan="1">496</td><td align="left" valign="top" rowspan="1" colspan="1">1.8 (0.1)</td><td align="left" valign="top" rowspan="1" colspan="1">439</td><td align="left" valign="top" rowspan="1" colspan="1">1.7 (0.1)</td><td align="left" valign="top" rowspan="1" colspan="1">446</td><td align="left" valign="top" rowspan="1" colspan="1">1.9 (0.1)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Healthy weight</td><td align="left" valign="top" rowspan="1" colspan="1">9,402</td><td align="left" valign="top" rowspan="1" colspan="1">34.1 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">9,146</td><td align="left" valign="top" rowspan="1" colspan="1">32.9 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">8,600</td><td align="left" valign="top" rowspan="1" colspan="1">33.1 (0.4)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Overweight</td><td align="left" valign="top" rowspan="1" colspan="1">9,553</td><td align="left" valign="top" rowspan="1" colspan="1">34.2 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">9,705</td><td align="left" valign="top" rowspan="1" colspan="1">34.5 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">8,872</td><td align="left" valign="top" rowspan="1" colspan="1">34.2 (0.4)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Obese</td><td align="left" valign="top" rowspan="1" colspan="1">8,193</td><td align="left" valign="top" rowspan="1" colspan="1">29.9 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">8,102</td><td align="left" valign="top" rowspan="1" colspan="1">30.9 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">7,586</td><td align="left" valign="top" rowspan="1" colspan="1">30.8 (0.4)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">
<bold>Diagnosed Prediabetes</bold>
</td><td align="left" valign="top" rowspan="1" colspan="1">2,355</td><td align="left" valign="top" rowspan="1" colspan="1">7.5 (0.2)</td><td align="left" valign="top" rowspan="1" colspan="1">2,636</td><td align="left" valign="top" rowspan="1" colspan="1">8.5 (0.2)</td><td align="left" valign="top" rowspan="1" colspan="1">2,558</td><td align="left" valign="top" rowspan="1" colspan="1">8.9 (0.2)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x0003c;0.01</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">
<bold>Rural-urban classification</bold>
</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"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1">0.04</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Large central metro</td><td align="left" valign="top" rowspan="1" colspan="1">8,382</td><td align="left" valign="top" rowspan="1" colspan="1">30.9 (1.2)</td><td align="left" valign="top" rowspan="1" colspan="1">8,370</td><td align="left" valign="top" rowspan="1" colspan="1">31.1 (1.2)</td><td align="left" valign="top" rowspan="1" colspan="1">8,032</td><td align="left" valign="top" rowspan="1" colspan="1">32.2 (1.1)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Large fringe metro</td><td align="left" valign="top" rowspan="1" colspan="1">6,651</td><td align="left" valign="top" rowspan="1" colspan="1">25.0 (1.2)</td><td align="left" valign="top" rowspan="1" colspan="1">6,709</td><td align="left" valign="top" rowspan="1" colspan="1">25.1 (1.2)</td><td align="left" valign="top" rowspan="1" colspan="1">6,221</td><td align="left" valign="top" rowspan="1" colspan="1">24.2 (1.1)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Medium and small metro</td><td align="left" valign="top" rowspan="1" colspan="1">9,035</td><td align="left" valign="top" rowspan="1" colspan="1">30.2 (1.5)</td><td align="left" valign="top" rowspan="1" colspan="1">8,879</td><td align="left" valign="top" rowspan="1" colspan="1">30.1 (1.5)</td><td align="left" valign="top" rowspan="1" colspan="1">8,210</td><td align="left" valign="top" rowspan="1" colspan="1">30.6 (1.4)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Non-metropolitan</td><td align="left" valign="top" rowspan="1" colspan="1">4,345</td><td align="left" valign="top" rowspan="1" colspan="1">13.8 (0.6)</td><td align="left" valign="top" rowspan="1" colspan="1">4,078</td><td align="left" valign="top" rowspan="1" colspan="1">13.7 (0.6)</td><td align="left" valign="top" rowspan="1" colspan="1">3,682</td><td align="left" valign="top" rowspan="1" colspan="1">13.1 (0.6)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">
<bold>U.S. Census Bureau region</bold>
</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"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1">0.72</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Northeast</td><td align="left" valign="top" rowspan="1" colspan="1">4,876</td><td align="left" valign="top" rowspan="1" colspan="1">18.0 (0.6)</td><td align="left" valign="top" rowspan="1" colspan="1">5,014</td><td align="left" valign="top" rowspan="1" colspan="1">17.7 (0.6)</td><td align="left" valign="top" rowspan="1" colspan="1">4,302</td><td align="left" valign="top" rowspan="1" colspan="1">17.7 (0.6)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Midwest</td><td align="left" valign="top" rowspan="1" colspan="1">6,315</td><td align="left" valign="top" rowspan="1" colspan="1">21.1 (0.7)</td><td align="left" valign="top" rowspan="1" colspan="1">6,402</td><td align="left" valign="top" rowspan="1" colspan="1">21.1 (0.7)</td><td align="left" valign="top" rowspan="1" colspan="1">5,567</td><td align="left" valign="top" rowspan="1" colspan="1">20.7 (0.7)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">South</td><td align="left" valign="top" rowspan="1" colspan="1">10,162</td><td align="left" valign="top" rowspan="1" colspan="1">37.1 (0.9)</td><td align="left" valign="top" rowspan="1" colspan="1">9,491</td><td align="left" valign="top" rowspan="1" colspan="1">37.3 (0.9)</td><td align="left" valign="top" rowspan="1" colspan="1">9,378</td><td align="left" valign="top" rowspan="1" colspan="1">37.5 (0.8)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">West</td><td align="left" valign="top" rowspan="1" colspan="1">7,060</td><td align="left" valign="top" rowspan="1" colspan="1">23.8 (0.9)</td><td align="left" valign="top" rowspan="1" colspan="1">7,129</td><td align="left" valign="top" rowspan="1" colspan="1">24.0 (1.0)</td><td align="left" valign="top" rowspan="1" colspan="1">6,898</td><td align="left" valign="top" rowspan="1" colspan="1">24.1 (0.8)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">
<bold>Health insurance (yes)</bold>
</td><td align="left" valign="top" rowspan="1" colspan="1">26,211</td><td align="left" valign="top" rowspan="1" colspan="1">90.2 (0.3)</td><td align="left" valign="top" rowspan="1" colspan="1">26,136</td><td align="left" valign="top" rowspan="1" colspan="1">90.6 (0.3)</td><td align="left" valign="top" rowspan="1" colspan="1">24,270</td><td align="left" valign="top" rowspan="1" colspan="1">91.1 (0.3)</td><td align="right" valign="top" rowspan="1" colspan="1">0.01</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">
<bold>Educational attainment</bold>
</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"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1">&#x0003c;0.01</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Below high school</td><td align="left" valign="top" rowspan="1" colspan="1">2,378</td><td align="left" valign="top" rowspan="1" colspan="1">11.5 (0.3)</td><td align="left" valign="top" rowspan="1" colspan="1">2,004</td><td align="left" valign="top" rowspan="1" colspan="1">11.1 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">2,052</td><td align="left" valign="top" rowspan="1" colspan="1">8.7 (0.3)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">High school graduate or GED</td><td align="left" valign="top" rowspan="1" colspan="1">7,177</td><td align="left" valign="top" rowspan="1" colspan="1">27.3 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">6,516</td><td align="left" valign="top" rowspan="1" colspan="1">28.3 (0.4)</td><td align="left" valign="top" rowspan="1" colspan="1">6,261</td><td align="left" valign="top" rowspan="1" colspan="1">27.8 (0.5)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Some college</td><td align="left" valign="top" rowspan="1" colspan="1">4,605</td><td align="left" valign="top" rowspan="1" colspan="1">17.9 (0.3)</td><td align="left" valign="top" rowspan="1" colspan="1">4,372</td><td align="left" valign="top" rowspan="1" colspan="1">17.5 (0.3)</td><td align="left" valign="top" rowspan="1" colspan="1">3,913</td><td align="left" valign="top" rowspan="1" colspan="1">15.2 (0.3)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02265; College graduate</td><td align="left" valign="top" rowspan="1" colspan="1">14,100</td><td align="left" valign="top" rowspan="1" colspan="1">43.3 (0.5)</td><td align="left" valign="top" rowspan="1" colspan="1">15,020</td><td align="left" valign="top" rowspan="1" colspan="1">43.2 (0.5)</td><td align="left" valign="top" rowspan="1" colspan="1">13,787</td><td align="left" valign="top" rowspan="1" colspan="1">48.3 (0.5)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">
<bold>Family income, %</bold>
</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"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1">&#x0003c;0.01</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x0003c;100 FPL</td><td align="left" valign="top" rowspan="1" colspan="1">2,943</td><td align="left" valign="top" rowspan="1" colspan="1">10.7 (0.3)</td><td align="left" valign="top" rowspan="1" colspan="1">2,339</td><td align="left" valign="top" rowspan="1" colspan="1">9.5 (0.3)</td><td align="left" valign="top" rowspan="1" colspan="1">2,438</td><td align="left" valign="top" rowspan="1" colspan="1">9.5 (0.3)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">100&#x02013;300 FPL</td><td align="left" valign="top" rowspan="1" colspan="1">9,534</td><td align="left" valign="top" rowspan="1" colspan="1">34.9 (0.5)</td><td align="left" valign="top" rowspan="1" colspan="1">8,729</td><td align="left" valign="top" rowspan="1" colspan="1">34.1 (0.5)</td><td align="left" valign="top" rowspan="1" colspan="1">8,496</td><td align="left" valign="top" rowspan="1" colspan="1">32.8 (0.4)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02265;300 FPL</td><td align="left" valign="top" rowspan="1" colspan="1">15,936</td><td align="left" valign="top" rowspan="1" colspan="1">54.5 (0.6)</td><td align="left" valign="top" rowspan="1" colspan="1">16,968</td><td align="left" valign="top" rowspan="1" colspan="1">56.4 (0.6)</td><td align="left" valign="top" rowspan="1" colspan="1">15,211</td><td align="left" valign="top" rowspan="1" colspan="1">57.7 (0.6)</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr></tbody></table><table-wrap-foot><fn id="TFN1"><p id="P36">Abbreviations: AIAN, American Indian and Alaska Native; BMI, body mass index; FPL, Federal Poverty Level; GED, General Educational Development; NH, non-Hispanic; SE, standard error.</p></fn><fn id="TFN2"><label>*</label><p id="P37">Reflects comparisons between 2019 and 2021.</p></fn><fn id="TFN3"><label>**</label><p id="P38">Categories are defined by BMI (kg/m<sup>2</sup>): underweight &#x0003c; 18.5, healthy weight 18.5 to 25, overweight 25 to 30, and obese &#x02265; 30.</p></fn></table-wrap-foot></table-wrap></floats-group></article>