<!DOCTYPE article
PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD with MathML3 v1.2 20190208//EN" "JATS-archivearticle1-mathml3.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" article-type="research-article"><?properties manuscript?><front><journal-meta><journal-id journal-id-type="nlm-journal-id">101600811</journal-id><journal-id journal-id-type="pubmed-jr-id">40952</journal-id><journal-id journal-id-type="nlm-ta">Ann Am Thorac Soc</journal-id><journal-id journal-id-type="iso-abbrev">Ann Am Thorac Soc</journal-id><journal-title-group><journal-title>Annals of the American Thoracic Society</journal-title></journal-title-group><issn pub-type="ppub">2329-6933</issn><issn pub-type="epub">2325-6621</issn></journal-meta><article-meta><article-id pub-id-type="pmid">30888833</article-id><article-id pub-id-type="pmc">6675641</article-id><article-id pub-id-type="doi">10.1513/AnnalsATS.201901-062RL</article-id><article-id pub-id-type="manuscript">HHSPA1028138</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Influence of county sampling on past estimates of latent tuberculosis infection prevalence</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Haddad</surname><given-names>Maryam B.</given-names></name><contrib-id contrib-id-type="orcid">http://orcid.org/0000-0001-6327-068X1</contrib-id><xref ref-type="aff" rid="A1">1</xref><xref ref-type="aff" rid="A2">2</xref><xref ref-type="aff" rid="A3">3</xref></contrib><contrib contrib-type="author"><name><surname>Raz</surname><given-names>Kala Marks</given-names></name><xref ref-type="aff" rid="A1">1</xref></contrib><contrib contrib-type="author"><name><surname>Hill</surname><given-names>Andrew N.</given-names></name><xref ref-type="aff" rid="A1">1</xref><xref ref-type="aff" rid="A2">2</xref></contrib><contrib contrib-type="author"><name><surname>Navin</surname><given-names>Thomas R.</given-names></name><xref ref-type="aff" rid="A1">1</xref></contrib><contrib contrib-type="author"><name><surname>Castro</surname><given-names>Kenneth G.</given-names></name><xref ref-type="aff" rid="A1">1</xref><xref ref-type="aff" rid="A2">2</xref></contrib><contrib contrib-type="author"><name><surname>Winston</surname><given-names>Carla A.</given-names></name><xref ref-type="aff" rid="A1">1</xref><xref ref-type="aff" rid="A2">2</xref></contrib><contrib contrib-type="author"><name><surname>Gandhi</surname><given-names>Neel R.</given-names></name><xref ref-type="aff" rid="A1">1</xref><xref ref-type="aff" rid="A2">2</xref></contrib><contrib contrib-type="author"><name><surname>Lash</surname><given-names>Timothy L.</given-names></name><xref ref-type="aff" rid="A2">2</xref></contrib></contrib-group><aff id="A1"><label>1</label>Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, Georgia</aff><aff id="A2"><label>2</label>Rollins School of Public Health, Emory University, Atlanta, Georgia</aff><aff id="A3"><label>3</label>Laney Graduate School, Emory University, Atlanta, Georgia</aff><author-notes><fn fn-type="con" id="FN1"><p id="P1"><italic>Author Contributions</italic>: M.B.H. conceptualized the analysis, and all of the authors contributed to its design. M.B.H. and K.M.R. created the non-NHANES county-level dataset. M.B.H. executed the analysis and prepared the first draft of the article within the National Center for Health Statistics Research Data Center. All of the authors provided critical revisions and approved the final version.</p></fn><corresp id="CR1">Corresponding author: Maryam B. Haddad, Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Mailstop US12-4, Atlanta, GA 30329-4027, USA. <email>mhaddad@cdc.gov</email></corresp></author-notes><pub-date pub-type="nihms-submitted"><day>21</day><month>5</month><year>2019</year></pub-date><pub-date pub-type="ppub"><month>8</month><year>2019</year></pub-date><pub-date pub-type="pmc-release"><day>01</day><month>8</month><year>2020</year></pub-date><volume>16</volume><issue>8</issue><fpage>1069</fpage><lpage>1071</lpage><!--elocation-id from pubmed: 10.1513/AnnalsATS.201901-062RL--></article-meta></front><body><sec id="S1"><title>To the Editor:</title><p id="P2">The National Health and Nutrition Examination Survey (NHANES) has tested for <italic>Mycobacterium tuberculosis</italic> infection three times: in 1971&#x02013;1972, 1999&#x02013;2000, and 2011&#x02013;2012. Based on tuberculin skin test results, the estimated national prevalence of latent tuberculosis infection (LTBI) among adults was 11%&#x02013;18% in 1971&#x02013;1972 but has remained &#x02264;6% in subsequent NHANES cycles (<xref rid="R1" ref-type="bibr">1</xref>&#x02013;<xref rid="R4" ref-type="bibr">4</xref>). A single 2-year NHANES cycle is designed to produce accurate and stable estimates for conditions of &#x02265;10% prevalence in the noninstitutionalized civilian U.S. population (<xref rid="R5" ref-type="bibr">5</xref>&#x02013;<xref rid="R7" ref-type="bibr">7</xref>), suggesting that NHANES might no longer be as nationally representative for LTBI as it is for more common health conditions. Approximately 30 counties were selected for each 2-year cycle (<xref rid="R5" ref-type="bibr">5</xref>). We wished to examine whether persons in selected counties might have been systematically more or less likely to have a positive tuberculin skin test than their counterparts in the approximately 3,100 counties that were not selected for NHANES participation.</p></sec><sec id="S2"><title>Methods</title><p id="P3">We created a non-NHANES dataset with demographic profiles and tuberculosis data for all 3,143 U.S. county equivalents (<xref rid="T1" ref-type="table">Table 1</xref>). The U.S. Census Bureau and Department of Agriculture websites provided each county&#x02019;s population size and racial/ethnic composition, rural vs. urban classification, and poverty prevalence for 1970 through 2013. The National Tuberculosis Surveillance System provided annual tuberculosis disease incidence, with the U.S. Census Bureau&#x02019;s Current Population Survey providing county population denominators.</p><p id="P4">We also used genotyping results to derive an estimate of longstanding LTBI prevalence for each county. Briefly, this simple back-calculation method assumed that TB cases not attributed to recent transmission (i.e., based on genotyping results) instead arose from preexisting LTBI. Then a 0.1% annual risk of reactivation was used to derive an estimated number of county residents with untreated LTBI (<xref rid="R8" ref-type="bibr">8</xref>). This county-level LTBI estimation method has not been validated; the only potential comparison in the literature is based on 1958&#x02012;1965 data (<xref rid="R9" ref-type="bibr">9</xref>). However, median estimated LTBI prevalence among the U.S.-born was 0.7% (lower and upper quartiles: 0.4%, 1.3%) and among the non-U.S.-born was 13.1% (lower and upper quartiles: 8.8%, 18.5%), both of which were similar to previous national NHANES-based estimates (<xref rid="R1" ref-type="bibr">1</xref>, <xref rid="R3" ref-type="bibr">3</xref>, <xref rid="R4" ref-type="bibr">4</xref>).</p><p id="P5">Because of disclosure risk, county of residence is not included in the NHANES public-use datasets and cannot be released (<xref rid="R10" ref-type="bibr">10</xref>). Following Research Data Center procedures (<ext-link ext-link-type="uri" xlink:href="https://www.cdc.gov/rdc/">https://www.cdc.gov/rdc/</ext-link>), the National Center for Health Statistics merged masked NHANES 1971&#x02013;1972, 1999&#x02013;2000, and 2011&#x02013;2012 data with our non-NHANES county dataset and allowed us to conduct this geographic analysis without access to county identifiers.</p></sec><sec id="S3"><title>Results</title><p id="P6">The demographics of the counties selected for NHANES participation in 1971&#x02013;1972, 1999&#x02013;2000, and 2011&#x02013;2012 were similar across time, except that the counties selected for NHANES 2011&#x02013;2012 had higher proportions of residents living in poverty, consistent with the recent national trend (<xref rid="T1" ref-type="table">Table 1</xref>). We compared the selected to nonselected counties within strata of counties of similar population size, racial/ethnic composition, rural vs. urban classification, and poverty prevalence. Within those strata, mean tuberculosis disease incidence and estimated LTBI prevalence were similar (<italic>P</italic>&#x02009;&#x0003e;&#x02009;0.05 for each test of equivalence) when comparing the selected to the nonselected counties in NHANES 1971&#x02013;1972, 1999&#x02013;2000, and 2011&#x02013;2012. In 90% of the counties selected for NHANES 2011&#x02013;2012, the unweighted prevalence of a tuberculin skin test result of &#x02265;10 mm of induration was within 1% of the genotyping-derived LTBI prevalence estimate for that county (<xref rid="R8" ref-type="bibr">8</xref>).</p></sec><sec id="S4"><title>Discussion</title><p id="P7">Because of strict confidentially protections that include the geographic locations of NHANES participants, the results of this masked analysis cannot be shown in more detail (<xref rid="R10" ref-type="bibr">10</xref>). However, our findings reinforce confidence in national LTBI prevalence estimates based on past NHANES cycles (<xref rid="R1" ref-type="bibr">1</xref>&#x02013;<xref rid="R4" ref-type="bibr">4</xref>). We found no evidence that the selected counties had different tuberculosis disease incidence or different LTBI prevalence from the counties not selected for NHANES participation in 1971&#x02013;1972, 1999&#x02013;2000, and 2011&#x02013;2012.</p><p id="P8">Despite these reassuring findings, both the low prevalence and geographic heterogeneity of this condition in the United States suggest that incorporating tuberculosis components (e.g., interferon-gamma release assays) into future NHANES cycles for &#x0003e;2 consecutive years would help achieve more stable population estimates (<xref rid="R4" ref-type="bibr">4</xref>&#x02013;<xref rid="R7" ref-type="bibr">7</xref>). Our findings also imply that genotyping-derived estimates of county-level LTBI prevalence that do not rely on NHANES data could continue to prove useful in the future (<xref rid="R8" ref-type="bibr">8</xref>).</p></sec></body><back><ack id="S5"><title>Acknowledgments:</title><p id="P9">We thank Wanjun (June) Cui, Frances McCarty, and other National Center for Health Statistics staff for their gracious assistance in facilitating access to restricted NHANES variables in the Research Data Center in Atlanta. We thank NHANES participants and staff for making this survey possible.</p><p id="P10">M.B.H. and several coauthors are employees of the Centers for Disease Control and Prevention. K.G.C. is supported by an existing US Agency for International Development Intergovernmental Personnel Act agreement with Emory University. N.R.G. is supported by a K24 grant (1K24AI114444) funded by National Institute of Allergy and Infectious Disease, National Institutes of Health, US Department of Health and Human Services.</p><p id="P11">Note</p><p id="P12">The findings and conclusions in this research letter are those of the authors and do not necessarily represent the official position or views of the Research Data Center, the National Center for Health Statistics, or the Centers for Disease Control and Prevention.</p></ack><ref-list><title>References</title><ref id="R1"><label>1.</label><mixed-citation publication-type="journal"><name><surname>Khan</surname><given-names>K</given-names></name>, <name><surname>Wang</surname><given-names>J</given-names></name>, <name><surname>Hu</surname><given-names>W</given-names></name>, <name><surname>Bierman</surname><given-names>A</given-names></name>, <name><surname>Li</surname><given-names>Y</given-names></name>, <name><surname>Gardam</surname><given-names>M</given-names></name>. <article-title>Tuberculosis infection in the United States: national trends over three decades.</article-title>
<source>Am J Respir Crit Care Med</source>
<year>2008</year>;<volume>177</volume>:<fpage>455</fpage>&#x02013;<lpage>460</lpage>.<pub-id pub-id-type="pmid">18029790</pub-id></mixed-citation></ref><ref id="R2"><label>2.</label><mixed-citation publication-type="web"><name><surname>Engel</surname><given-names>A</given-names></name>, <name><surname>Roberts</surname><given-names>J</given-names></name>, <collab>National Center for Health Statistics</collab>. <source>Tuberculin skin test reaction among adults 25&#x02013;74 years, United States, 1971&#x02013;72</source> [Accessed 2019 Mar 3]. Available from: <comment><ext-link ext-link-type="uri" xlink:href="https://www.cdc.gov/nchs/data/series/sr_11/sr11_204.pdf">https://www.cdc.gov/nchs/data/series/sr_11/sr11_204.pdf</ext-link></comment></mixed-citation></ref><ref id="R3"><label>3.</label><mixed-citation publication-type="journal"><name><surname>Bennett</surname><given-names>DE</given-names></name>, <name><surname>Courval</surname><given-names>JM</given-names></name>, <name><surname>Onorato</surname><given-names>I</given-names></name>, <name><surname>Agerton</surname><given-names>T</given-names></name>, <name><surname>Gibson</surname><given-names>JD</given-names></name>, <name><surname>Lambert</surname><given-names>L</given-names></name>, <name><surname>McQuillan</surname><given-names>GM</given-names></name>, <name><surname>Lewis</surname><given-names>B</given-names></name>, <name><surname>Navin</surname><given-names>TR</given-names></name>, <name><surname>Castro</surname><given-names>KG</given-names></name>. <article-title>Prevalence of tuberculosis infection in the United States population: the National Health and Nutrition Examination Survey, 1999&#x02013;2000.</article-title>
<source>Am J Respir Crit Care Med</source>
<year>2008</year>;<volume>177</volume>:<fpage>348</fpage>&#x02013;<lpage>355</lpage>.<pub-id pub-id-type="pmid">17989346</pub-id></mixed-citation></ref><ref id="R4"><label>4.</label><mixed-citation publication-type="journal"><name><surname>Mancuso</surname><given-names>JD</given-names></name>, <name><surname>Diffenderfer</surname><given-names>JM</given-names></name>, <name><surname>Ghassemieh</surname><given-names>BJ</given-names></name>, <name><surname>Horne</surname><given-names>DJ</given-names></name>, <name><surname>Kao</surname><given-names>TC</given-names></name>. <article-title>The prevalence of latent tuberculosis infection in the United States.</article-title>
<source>Am J Respir Crit Care Med</source>
<year>2016</year>;<volume>194</volume>:<fpage>501</fpage>&#x02013;<lpage>509</lpage>.<pub-id pub-id-type="pmid">26866439</pub-id></mixed-citation></ref><ref id="R5"><label>5.</label><mixed-citation publication-type="web"><collab>Centers for Disease Control and Prevention</collab>. <source>The National Health and Nutrition Examination Survey: sample design, 1999&#x02013;2006</source> [Accessed 2019 Mar 3]. Available from: <comment><ext-link ext-link-type="uri" xlink:href="https://www.cdc.gov/nchs/data/series/sr_02/sr02_155.pdf">https://www.cdc.gov/nchs/data/series/sr_02/sr02_155.pdf</ext-link></comment></mixed-citation></ref><ref id="R6"><label>6.</label><mixed-citation publication-type="web"><collab>Centers for Disease Control and Prevention</collab>. <source>National Health and Nutrition Examination Survey: analytic guidelines, 1999&#x02013;2010</source> [Accessed 2019 Mar 3]. Available from: <comment><ext-link ext-link-type="uri" xlink:href="https://www.cdc.gov/nchs/data/series/sr_02/sr02_161.pdf">https://www.cdc.gov/nchs/data/series/sr_02/sr02_161.pdf</ext-link></comment></mixed-citation></ref><ref id="R7"><label>7.</label><mixed-citation publication-type="web"><name><surname>Curtin</surname><given-names>LR</given-names></name>, <name><surname>Kruszon-Moran</surname><given-names>D</given-names></name>, <name><surname>Carroll</surname><given-names>M</given-names></name>, <name><surname>Li</surname><given-names>X</given-names></name>. <source>Estimation and analytic issues for rare events in NHANES</source> [Accessed 2019 Mar 3]. Available from: <comment><ext-link ext-link-type="uri" xlink:href="https://www.researchgate.net/publication/253720335_Estimation_and_Analytic_Issues_for_Rare_Events_in_NHANES">https://www.researchgate.net/publication/253720335_Estimation_and_Analytic_Issues_for_Rare_Events_in_NHANES</ext-link></comment></mixed-citation></ref><ref id="R8"><label>8.</label><mixed-citation publication-type="journal"><name><surname>Haddad</surname><given-names>MB</given-names></name>, <name><surname>Raz</surname><given-names>KM</given-names></name>, <name><surname>Lash</surname><given-names>TL</given-names></name>, <name><surname>Hill</surname><given-names>AN</given-names></name>, <name><surname>Kammerer</surname><given-names>JS</given-names></name>, <name><surname>Winston</surname><given-names>CA</given-names></name>, <name><surname>Castro</surname><given-names>KG</given-names></name>, <name><surname>Gandhi</surname><given-names>NR</given-names></name>, <name><surname>Navin</surname><given-names>TR</given-names></name>. <article-title>Simple county-level estimates for the prevalence of latent tuberculosis infection &#x02014; United States, 2011&#x02013;2015.</article-title>
<source>Emerg Infect Dis</source>
<year>2018</year>;<volume>24</volume>;<fpage>1930</fpage>&#x02013;<lpage>1933</lpage>. [<comment>Accessed 2019 Mar 3</comment>]. Available from: <comment><ext-link ext-link-type="uri" xlink:href="https://wwwnc.cdc.gov/eid/article/24/10/18-0716_article">https://wwwnc.cdc.gov/eid/article/24/10/18-0716_article</ext-link></comment><pub-id pub-id-type="pmid">30226174</pub-id></mixed-citation></ref><ref id="R9"><label>9.</label><mixed-citation publication-type="journal"><name><surname>Edwards</surname><given-names>LB</given-names></name>, <name><surname>Acquaviva</surname><given-names>FA</given-names></name>, <name><surname>Livesay</surname><given-names>VT</given-names></name>, <name><surname>Cross</surname><given-names>FW</given-names></name>, <name><surname>Palmer</surname><given-names>CE</given-names></name>. <article-title>An atlas of sensitivity to tuberculin, PPD-B, and histoplasmin in the United States.</article-title>
<source>Am Rev Respir Dis</source>
<year>1969</year>;<volume>99</volume>(<issue>Suppl</issue>):<fpage>1</fpage>&#x02013;<lpage>132</lpage>.<pub-id pub-id-type="pmid">4973586</pub-id></mixed-citation></ref><ref id="R10"><label>10.</label><mixed-citation publication-type="web"><collab>Centers for Disease Control and Prevention</collab>. <source>How the National Health and Nutrition Examination Survey keeps your information confidential</source> [Accessed 2019 Mar 3]. Available from: <comment><ext-link ext-link-type="uri" xlink:href="https://www.cdc.gov/nchs/nhanes/participant/participant-confidentiality.htm">https://www.cdc.gov/nchs/nhanes/participant/participant-confidentiality.htm</ext-link></comment></mixed-citation></ref></ref-list></back><floats-group><table-wrap id="T1" position="float" orientation="portrait"><label>Table 1.</label><caption><p id="P13">Demographic characteristics pertinent to tuberculosis burden, and active tuberculosis disease incidence, by county or county equivalent<xref rid="TFN1" ref-type="table-fn">*</xref>, during the 1971&#x02013;1972, 1999&#x02013;2000, and 2011&#x02013;2012 National Health and Nutrition Examination Survey (NHANES) cycles (N=3,143 counties)</p></caption><table frame="hsides" rules="groups"><colgroup span="1"><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/><col align="left" valign="middle" span="1"/></colgroup><thead><tr><th align="left" valign="top" rowspan="1" colspan="1"/><th colspan="3" align="center" valign="top" rowspan="1">No. counties (percent)<hr/></th></tr><tr><th align="left" valign="top" rowspan="1" colspan="1"/><th align="center" valign="top" rowspan="1" colspan="1">1971&#x02013;1972</th><th align="center" valign="top" rowspan="1" colspan="1">1999&#x02013;2000</th><th align="center" valign="top" rowspan="1" colspan="1">2011&#x02013;2012</th></tr></thead><tbody><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>County size</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"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02264;10,000 population at time of NHANES cycle</td><td align="right" valign="top" rowspan="1" colspan="1">876 (28)</td><td align="right" valign="top" rowspan="1" colspan="1">697 (22)</td><td align="right" valign="top" rowspan="1" colspan="1">698 (22)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;10,001&#x02013;24,999</td><td align="right" valign="top" rowspan="1" colspan="1">1,016 (32)</td><td align="right" valign="top" rowspan="1" colspan="1">886 (28)</td><td align="right" valign="top" rowspan="1" colspan="1">845 (27)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;25,000&#x02013;99,999</td><td align="right" valign="top" rowspan="1" colspan="1">902 (29)</td><td align="right" valign="top" rowspan="1" colspan="1">1,036 (33)</td><td align="right" valign="top" rowspan="1" colspan="1">1,022 (33)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02265;100,000</td><td align="right" valign="top" rowspan="1" colspan="1">349 (11)</td><td align="right" valign="top" rowspan="1" colspan="1">524 (17)</td><td align="right" valign="top" rowspan="1" colspan="1">578 (18)</td></tr><tr><td colspan="4" align="left" valign="top" rowspan="1"><hr/></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>Non-U.S.-born population</bold><xref rid="TFN2" ref-type="table-fn">&#x02020;</xref></td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x0003c;2% of county&#x02019;s total population</td><td align="center" valign="top" rowspan="1" colspan="1"><xref rid="TFN2" ref-type="table-fn">&#x02020;</xref></td><td align="right" valign="top" rowspan="1" colspan="1">1,702 (54)</td><td align="right" valign="top" rowspan="1" colspan="1">1,683 (54)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;2.0%&#x02013;4.9% of county&#x02019;s total population</td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1">832 (26)</td><td align="right" valign="top" rowspan="1" colspan="1">788 (25)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;5.0%&#x02013;9.9% of county&#x02019;s total population</td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1">376 (12)</td><td align="right" valign="top" rowspan="1" colspan="1">410 (13)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02265;10% of county&#x02019;s total population</td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1">233 (7)</td><td align="right" valign="top" rowspan="1" colspan="1">262 (8)</td></tr><tr><td colspan="4" align="left" valign="top" rowspan="1"><hr/></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>Metropolitan/urban</bold><xref rid="TFN3" ref-type="table-fn">&#x02021;</xref></td><td align="right" valign="top" rowspan="1" colspan="1">2,495 (79)<xref rid="TFN3" ref-type="table-fn">&#x02021;</xref></td><td align="right" valign="top" rowspan="1" colspan="1">2,053 (65)</td><td align="right" valign="top" rowspan="1" colspan="1">1,976 (63)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>Nonmetropolitan/rural</bold><xref rid="TFN3" ref-type="table-fn">&#x02021;</xref></td><td align="right" valign="top" rowspan="1" colspan="1">648 (21)<xref rid="TFN3" ref-type="table-fn">&#x02021;</xref></td><td align="right" valign="top" rowspan="1" colspan="1">1,090 (35)</td><td align="right" valign="top" rowspan="1" colspan="1">1,167 (37)</td></tr><tr><td colspan="4" align="left" valign="top" rowspan="1"><hr/></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>Poverty level</bold></td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x0003c;10% of population in poverty</td><td align="right" valign="top" rowspan="1" colspan="1">322 (10)<xref rid="TFN4" ref-type="table-fn">&#x000a7;</xref></td><td align="right" valign="top" rowspan="1" colspan="1">851 (27)</td><td align="right" valign="top" rowspan="1" colspan="1">310 (9)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;10%&#x02013;15.5% in poverty</td><td align="right" valign="top" rowspan="1" colspan="1">1,407 (45)<xref rid="TFN4" ref-type="table-fn">&#x000a7;</xref></td><td align="right" valign="top" rowspan="1" colspan="1">1,362 (43)</td><td align="right" valign="top" rowspan="1" colspan="1">1,092 (35)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;15.6%&#x02013;19.9% in poverty</td><td align="right" valign="top" rowspan="1" colspan="1">518 (16)<xref rid="TFN4" ref-type="table-fn">&#x000a7;</xref></td><td align="right" valign="top" rowspan="1" colspan="1">558 (17)</td><td align="right" valign="top" rowspan="1" colspan="1">825 (26)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;&#x02265;20% in poverty</td><td align="right" valign="top" rowspan="1" colspan="1">896 (29)<xref rid="TFN4" ref-type="table-fn">&#x000a7;</xref></td><td align="right" valign="top" rowspan="1" colspan="1">372 (12)</td><td align="right" valign="top" rowspan="1" colspan="1">916 (29)</td></tr><tr><td colspan="4" align="left" valign="top" rowspan="1"><hr/></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>Historic tuberculosis disease incidence</bold> (1963&#x02013;1972)</td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">based on state&#x02019;s total population<xref rid="TFN4" ref-type="table-fn">&#x000a7;</xref></td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Low (in state averaging &#x0003c;15 annual cases per 100,000)</td><td align="right" valign="top" rowspan="1" colspan="1">631 (20)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Medium (15&#x02013;20 cases per 100,000)</td><td align="right" valign="top" rowspan="1" colspan="1">488 (16)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;High (&#x02265;20 cases per 100,000)</td><td align="right" valign="top" rowspan="1" colspan="1">2,024 (64)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td></tr><tr><td colspan="4" align="left" valign="top" rowspan="1"><hr/></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>Recent tuberculosis disease incidence</bold> (1996&#x02013;2003)</td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>among county&#x02019;s U.S.-born population</bold></td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;None (county with 0 cases among U.S.-born)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">622 (20)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Low/Medium (averaging &#x0003c;10 annual cases per 100,000)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">2,339 (74)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;High (county with &#x02265;10 annual cases per 100,000)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">182 (6)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td></tr><tr><td colspan="4" align="left" valign="top" rowspan="1"><hr/></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>among county&#x02019;s non-U.S.-born population</bold><xref rid="TFN2" ref-type="table-fn">&#x02020;</xref></td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;None (county with 0 cases among non-U.S.-born)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">1,641 (52)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Low/Medium (averaging &#x0003c;10 annual cases per 100,000)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">173 (6)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;High (county with &#x02265;10 annual cases per 100,000)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">1,329 (42)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>Modern tuberculosis disease incidence</bold> (2008&#x02013;2015)</td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>among county&#x02019;s U.S.-born population</bold></td><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;None (county with 0 cases among U.S.-born)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">1,041 (33)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Low/Medium (averaging &#x0003c;10 annual cases per 100,000)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">2,076 (66)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;High (county with &#x02265;10 annual cases per 100,000)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">26 (1)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><bold>among county&#x02019;s non-U.S.-born population</bold><xref rid="TFN2" ref-type="table-fn">&#x02020;</xref></td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;None (county with 0 cases among non-U.S.-born)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">1,607 (51)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Low/Medium (averaging &#x0003c;10 annual cases per 100,000)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">275 (9)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;High (county with &#x02265;10 annual cases per 100,000)</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">&#x02014;</td><td align="right" valign="top" rowspan="1" colspan="1">1,261 (40)</td></tr></tbody></table><table-wrap-foot><fn id="TFN1"><label>*</label><p id="P14">Included as county equivalents are the Alaska boroughs, the District of Columbia, Louisiana parishes, and Virginia independent cities</p></fn><fn id="TFN2"><label>&#x02020;</label><p id="P15">Where the county&#x02019;s non-U.S.-born proportion was provided by the U.S. Census Bureau&#x02019;s Current Population Survey, that proportion was applied to the total county population size to derive a non-U.S.-born count. In 2000, the Current Population Survey provided an estimate of the proportion of the county&#x02019;s population that was non-U.S.-born; in later years, that proportion is only consistently available at the state level. In 2010, it was provided for 801 counties only; for the other 2,342 counties, the non-U.S.-born population size was imputed based on the county&#x02019;s non-U.S.-born proportion in 2000 and the state&#x02019;s total non-U.S.-born population size in 2010.</p></fn><fn id="TFN3"><label>&#x02021;</label><p id="P16">Rural-Urban Continuum Codes from the U.S. Department of Agriculture for 1974, 2003, and 2013 were dichotomized into these two categories (i.e., codes 4&#x02013;9 considered rural and codes 0&#x02013;3 considered metropolitan). Note that due to changes to the criteria that were implemented after the 2000 Census, the 1974 Rural-Urban Continuum Codes are not directly comparable with those in 2003 and 2013.</p></fn><fn id="TFN4"><label>&#x000a7;</label><p id="P17">Measures of poverty in 1970 and TB disease incidence in 1963&#x02013;1972 only available at the state level; later measures from the National Tuberculosis Surveillance System are at the county level.</p></fn></table-wrap-foot></table-wrap></floats-group></article>