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  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">Arq Bras Cardiol</journal-id>
      <journal-id journal-id-type="publisher-id">abc</journal-id>
      <journal-title-group>
        <journal-title>Arquivos Brasileiros de Cardiologia</journal-title>
        <abbrev-journal-title abbrev-type="publisher">Arq. Bras. Cardiol.</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">0066-782X</issn>
      <issn pub-type="epub">1678-4170</issn>
      <publisher>
        <publisher-name>Sociedade Brasileira de Cardiologia - SBC</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id specific-use="scielo-v3" pub-id-type="publisher-id">7k3zrFh4x78yWB4NC57xFDh</article-id>
      <article-id specific-use="scielo-v2" pub-id-type="publisher-id">S0066-782X2025000900307</article-id>
      <article-id pub-id-type="other">00307</article-id>
      <article-id pub-id-type="doi">10.36660/abc.20240425</article-id>
      <article-id pub-id-type="publisher-id">abc.20240425</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Artigo Original</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Estudo dos N&#237;veis Urin&#225;rios de Cafe&#237;na e Metab&#243;litos da Cafe&#237;na em Adultos Americanos com Doen&#231;a Arterial Coronariana: Um Estudo Transversal com Dados do NHANES (2009-2014)</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0009-0005-0840-4821</contrib-id>
          <name>
            <surname>Li</surname>
            <given-names>Qianqian</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>Obten&#231;&#227;o de dados</role>
          <role>An&#225;lise e interpreta&#231;&#227;o dos dados e An&#225;lise estat&#237;stica</role>
          <role>Reda&#231;&#227;o do manuscrito</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0009-0006-0616-4542</contrib-id>
          <name>
            <surname>Ke</surname>
            <given-names>Gan</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>Obten&#231;&#227;o de dados</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0009-0005-9057-8870</contrib-id>
          <name>
            <surname>Liu</surname>
            <given-names>Mengdie</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa</role>
          <role>Reda&#231;&#227;o do manuscrito</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0001-9030-5673</contrib-id>
          <name>
            <surname>Chen</surname>
            <given-names>Yanjun</given-names>
          </name>
          <role>Obten&#231;&#227;o de financiamento e Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do</role>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
          <xref ref-type="corresp" rid="c1"/>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0009-0005-7727-299X</contrib-id>
          <name>
            <surname>Luo</surname>
            <given-names>Ye</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0009-0007-7485-8631</contrib-id>
          <name>
            <surname>Qiu</surname>
            <given-names>Liangxian</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
        </contrib>
        <aff id="aff1">
          <label>1</label>
          <institution content-type="orgname">Shenzhen University</institution>
          <addr-line>
            <named-content content-type="city">Shenzhen</named-content>
          </addr-line>
          <country country="CN">China</country>
          <institution content-type="original">Shenzhen University, Shenzhen &#8211; China</institution>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution content-type="orgname">Peking University Shenzhen Hospital</institution>
          <institution content-type="orgdiv1">Department of Cardiovascular Medicine</institution>
          <addr-line>
            <named-content content-type="city">Shenzhen</named-content>
          </addr-line>
          <country country="CN">China</country>
          <institution content-type="original">Peking University Shenzhen Hospital &#8211; Department of Cardiovascular Medicine, Shenzhen &#8211; China</institution>
        </aff>
      </contrib-group>
      <author-notes>
        <corresp id="c1"><label>Correspond&#234;ncia:</label><bold>Yanjun Chen &#8226;</bold> Shenzhen University &#8211; BeiJing University Shenzhen Hospital, Futian District, Shenzhen, Guangdong Province, China Shenzhen <postal-code>518060</postal-code> &#8211; China E-mail: <email>chenyanjunhyd@163.com</email> </corresp>
        <fn fn-type="conflict">
          <label>Potencial conflito de interesse</label>
          <p>N&#227;o h&#225; conflito com o presente artigo.</p>
        </fn>
        <fn fn-type="edited-by">
          <label>Editor respons&#225;vel pela revis&#227;o:</label>
          <p>Gl&#225;ucia Maria Moraes de Oliveira</p>
        </fn>
      </author-notes>
      <pub-date date-type="pub" publication-format="electronic">
        <day>01</day>
        <month>12</month>
        <year>2025</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2025</year>
      </pub-date>
      <volume>122</volume>
      <issue>09</issue>
      <elocation-id>e20240425</elocation-id>
      <history>
        <date date-type="received">
          <day>07</day>
          <month>08</month>
          <year>2024</year>
        </date>
        <date date-type="rev-recd">
          <day>10</day>
          <month>02</month>
          <year>2025</year>
        </date>
        <date date-type="accepted">
          <day>19</day>
          <month>03</month>
          <year>2025</year>
        </date>
      </history>
      <permissions>
        <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/" xml:lang="en">
          <license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License</license-p>
        </license>
      </permissions>
      <abstract>
        <title>Resumo</title>
        <sec>
          <title>Fundamento:</title>
          <p>Nos &#250;ltimos anos, a influ&#234;ncia da alimenta&#231;&#227;o e do estilo de vida sobre a doen&#231;a arterial coronariana (DAC) tem despertado crescente interesse. A cafe&#237;na, um componente alimentar amplamente consumido, e seus metab&#243;litos podem exercer efeitos sobre a sa&#250;de cardiovascular.</p>
        </sec>
        <sec>
          <title>Objetivo:</title>
          <p>Investigar a associa&#231;&#227;o entre os n&#237;veis urin&#225;rios de cafe&#237;na e de seus metab&#243;litos com a ocorr&#234;ncia de DAC, bem como avaliar se essas associa&#231;&#245;es variam entre diferentes subgrupos populacionais.</p>
        </sec>
        <sec>
          <title>M&#233;todos:</title>
          <p>Foram analisados dados do banco NHANES (2009-2014) por meio de modelos de regress&#227;o log&#237;stica multivariada e t&#233;cnicas de suaviza&#231;&#227;o por curvas. Os participantes foram categorizados em grupo controle (n = 5.005) e grupo com DAC (n = 222), conforme a presen&#231;a ou aus&#234;ncia da doen&#231;a. Os n&#237;veis urin&#225;rios de cafe&#237;na e de seus metab&#243;litos foram quantificados. A regress&#227;o log&#237;stica multivariada foi empregada para avaliar a associa&#231;&#227;o entre os n&#237;veis urin&#225;rios dessas subst&#226;ncias e a incid&#234;ncia de DAC, e a an&#225;lise de curvas suavizadas permitiu explorar poss&#237;veis rela&#231;&#245;es n&#227;o lineares. O n&#237;vel de signific&#226;ncia adotado foi de 5%.</p>
        </sec>
        <sec>
          <title>Resultados:</title>
          <p>N&#237;veis mais elevados de paraxantina urin&#225;ria estiveram associados a menor risco de DAC. Por outro lado, concentra&#231;&#245;es mais altas de cafe&#237;na urin&#225;ria apresentaram associa&#231;&#227;o positiva com a incid&#234;ncia de DAC entre indiv&#237;duos mexicano-americanos, associa&#231;&#227;o esta n&#227;o observada em outros grupos raciais/&#233;tnicos.</p>
        </sec>
        <sec>
          <title>Conclus&#227;o:</title>
          <p>Concentra&#231;&#245;es urin&#225;rias reduzidas de paraxantina podem indicar menor risco de DAC, enquanto n&#237;veis elevados de cafe&#237;na urin&#225;ria podem refletir risco aumentado em popula&#231;&#245;es espec&#237;ficas.</p>
        </sec>
      </abstract>
      <abstract abstract-type="graphical">
        <p>
          <fig id="f03">
            <label>Figura Central:</label>
            <caption>
              <title>Estudo dos N&#237;veis Urin&#225;rios de Cafe&#237;na e Metab&#243;litos da Cafe&#237;na em Adultos Americanos com Doen&#231;a Arterial Coronariana: Um Estudo Transversal com Dados do NHANES (2009-2014)</title>
            </caption>
            <graphic xlink:href=""/>
            <attrib>AVC: acidente vascular cerebral; DAC: doen&#231;a arterial coronariana; DM2: diabetes melito tipo 2.</attrib>
          </fig>
        </p>
      </abstract>
      <kwd-group xml:lang="pt">
        <title>Palavras-chave:</title>
        <kwd>Cafe&#237;na</kwd>
        <kwd>Doen&#231;a Cardiovascular</kwd>
        <kwd>Metab&#243;litos do Caf&#233;</kwd>
        <kwd>Ra&#231;a</kwd>
      </kwd-group>
      <funding-group>
        <award-group>
          <funding-source>The Shenzhen Science and Technology Innovation Foundation</funding-source>
          <award-id>JCYJ20180228162359914</award-id>
        </award-group>
        <award-group>
          <funding-source>Guangdong-Shenzhen Joint Fund Youth</funding-source>
          <award-id>2021A1515111110</award-id>
        </award-group>
        <funding-statement>O presente estudo foi financiado por The Shenzhen Science and Technology Innovation Foundation (No. JCYJ20180228162359914) e Guangdong-Shenzhen Joint Fund Youth Project (No. 2021A1515111110).</funding-statement>
      </funding-group>
      <counts>
        <fig-count count="6"/>
        <table-count count="10"/>
        <equation-count count="0"/>
        <ref-count count="28"/>
      </counts>
    </article-meta>
  </front>
  <body>
    <sec sec-type="intro">
      <title>Introdu&#231;&#227;o</title>
      <p>Nas &#250;ltimas d&#233;cadas, a doen&#231;a arterial coronariana (DAC) consolidou-se como uma das principais causas de mortalidade, sendo respons&#225;vel por mais de 370.000 &#243;bitos anuais.<sup><xref ref-type="bibr" rid="B1">1</xref></sup> Al&#233;m dos fatores de risco tradicionais, como tabagismo, hiperlipidemia, hipertens&#227;o arterial, diabetes melito tipo 2 (DM2) e obesidade, fatores emergentes tamb&#233;m t&#234;m sido identificados, incluindo inflama&#231;&#227;o sist&#234;mica, diabetes gestacional, pr&#233;-ecl&#226;mpsia e menopausa precoce ou cir&#250;rgica.</p>
      <p>Modifica&#231;&#245;es na alimenta&#231;&#227;o demonstraram reduzir a incid&#234;ncia de DAC.<sup><xref ref-type="bibr" rid="B2">2</xref></sup> Compostos naturais com a&#231;&#227;o farmacol&#243;gica &#8212; em especial a cafe&#237;na &#8212; s&#227;o frequentemente utilizados como terapias complementares nas doen&#231;as cardiovasculares.<sup><xref ref-type="bibr" rid="B3">3</xref></sup> O caf&#233;, bebida mais consumida no mundo, cont&#233;m cafe&#237;na (1,3,7-trimetilxantina), que &#233; majoritariamente ingerida por meio de alimentos e bebidas.<sup><xref ref-type="bibr" rid="B4">4</xref> , <xref ref-type="bibr" rid="B5">5</xref> </sup> Embora a cafe&#237;na possa provocar aumento transit&#243;rio da press&#227;o arterial em indiv&#237;duos n&#227;o habituados ao seu consumo, a ingest&#227;o regular de caf&#233; tem sido associada &#224; redu&#231;&#227;o do risco de arritmias e insufici&#234;ncia card&#237;aca, melhora da sensibilidade &#224; insulina e menor risco de desenvolvimento de DM2.</p>
      <p>Diversos estudos descreveram uma rela&#231;&#227;o inversa entre o consumo de caf&#233; e a mortalidade por todas as causas. O h&#225;bito de consumir caf&#233; regularmente est&#225; associado a menor risco de doen&#231;as cardiovasculares e desfechos adversos, incluindo DAC, insufici&#234;ncia card&#237;aca congestiva e acidente vascular cerebral. O consumo prolongado tamb&#233;m tem sido relacionado &#224; redu&#231;&#227;o do risco de DM2, depress&#227;o, obesidade e certos tipos de c&#226;ncer.<sup><xref ref-type="bibr" rid="B6">6</xref> , <xref ref-type="bibr" rid="B7">7</xref> </sup></p>
      <p>Notavelmente, concentra&#231;&#245;es elevadas de cafe&#237;na e teofilina na urina t&#234;m demonstrado correla&#231;&#227;o negativa com doen&#231;as cardiovasculares,<sup><xref ref-type="bibr" rid="B8">8</xref></sup> sendo essa associa&#231;&#227;o mais evidente em mulheres.<sup><xref ref-type="bibr" rid="B9">9</xref></sup> No entanto, a maior parte das evid&#234;ncias atuais baseia-se em relatos autorreferidos de consumo de caf&#233;, os quais podem apresentar varia&#231;&#245;es substanciais devido &#224; marca, origem e tipo da bebida &#8212; fatores que influenciam diretamente o teor de cafe&#237;na. Poucos estudos exploraram a rela&#231;&#227;o entre metab&#243;litos da cafe&#237;na e doen&#231;as cardiovasculares, e muitos n&#227;o consideram a variabilidade introduzida pelas diferentes formas de preparo, origem e processamento do caf&#233;. Al&#233;m disso, poss&#237;veis imprecis&#245;es nos dados autorreferidos comprometem a confiabilidade dos resultados.</p>
      <p>A concentra&#231;&#227;o de cafe&#237;na e seus metab&#243;litos excretados na urina representa um marcador mais objetivo e confi&#225;vel da ingest&#227;o de caf&#233;. Contudo, diferen&#231;as individuais no metabolismo da cafe&#237;na podem resultar em variabilidade nos n&#237;veis circulantes desses compostos. Para compreender melhor a associa&#231;&#227;o entre as concentra&#231;&#245;es urin&#225;rias de cafe&#237;na e seus metab&#243;litos e a presen&#231;a de DAC, realizamos uma an&#225;lise transversal utilizando dados do <italic>National Health and Nutrition Examination Survey</italic> (NHANES) referentes ao per&#237;odo de 2009 a 2014. Este estudo teve como objetivo investigar poss&#237;veis rela&#231;&#245;es entre biomarcadores urin&#225;rios de exposi&#231;&#227;o &#224; cafe&#237;na e a incid&#234;ncia de DAC.</p>
    </sec>
    <sec sec-type="methods">
      <title>M&#233;todos</title>
      <sec>
        <title>Popula&#231;&#227;o do estudo</title>
        <p>O NHANES &#233; uma pesquisa nutricional transversal realizada nos Estados Unidos por meio de amostragem probabil&#237;stica estratificada em m&#250;ltiplos est&#225;gios. A coleta e a dissemina&#231;&#227;o dos dados foram aprovadas pelo <italic>National Center for Health Statistics</italic> .<sup><xref ref-type="bibr" rid="B10">10</xref></sup> Inclu&#237;mos dados de adultos com 20 anos de idade ou mais que participaram do NHANES entre 2009 e 2014.<sup><xref ref-type="bibr" rid="B11">11</xref></sup> Durante e ap&#243;s a coleta dos dados, n&#227;o tivemos acesso a nenhuma informa&#231;&#227;o pessoalmente identific&#225;vel.</p>
        <p>Inicialmente, foram considerados 30.468 participantes. Ap&#243;s a aplica&#231;&#227;o dos crit&#233;rios de exclus&#227;o, a an&#225;lise final incluiu 5.227 indiv&#237;duos. Foram exclu&#237;dos: participantes com menos de 20 anos de idade (n = 13.261), indiv&#237;duos com dados incompletos sobre doen&#231;a arterial coronariana (n = 67) e participantes com dados ausentes sobre cafe&#237;na e seus metab&#243;litos (n = 11.913). Ap&#243;s a aplica&#231;&#227;o desses crit&#233;rios de exclus&#227;o, restaram 5.227 participantes para a an&#225;lise final ( <xref ref-type="fig" rid="f1">Figura 1</xref> ).</p>
        <fig id="f1">
          <label>Figura 1</label>
          <caption>
            <title>Fluxograma do processo de sele&#231;&#227;o dos participantes. DAC: doen&#231;a arterial coronariana; NHANES: National Health and Nutrition Examination Survey.</title>
          </caption>
          <graphic xlink:href=""/>
        </fig>
      </sec>
      <sec>
        <title>Fatores de exposi&#231;&#227;o</title>
        <p>A teobromina (3,7-dimetilxantina), a teofilina (1,3-dimetilxantina) e a paraxantina (1,7-dimetilxantina) s&#227;o os principais metab&#243;litos da cafe&#237;na no organismo humano.<sup><xref ref-type="bibr" rid="B12">12</xref></sup> Neste estudo, as concentra&#231;&#245;es urin&#225;rias de cafe&#237;na e seus metab&#243;litos foram utilizadas como vari&#225;veis de exposi&#231;&#227;o. As amostras de urina foram coletadas entre 10h e 12h, ap&#243;s jejum noturno de 9 horas. Ap&#243;s o recebimento, as amostras foram processadas e armazenadas, sendo posteriormente enviadas &#224; Divis&#227;o de Ci&#234;ncias Laboratoriais do <italic>National Center for Environmental Health</italic> , dos <italic>Centers for Disease Control and Prevention</italic> (CDC), em Atlanta, Ge&#243;rgia, para an&#225;lise.</p>
        <p>Cromatografia l&#237;quida de alta efici&#234;ncia com ioniza&#231;&#227;o por <italic>eletrospray</italic> acoplada &#224; espectrometria de massas em tandem com analisador de quadrupolo foi utilizada, em combina&#231;&#227;o com padr&#245;es internos marcados com is&#243;topos est&#225;veis, para quantificar a cafe&#237;na e seus metab&#243;litos na urina.<sup><xref ref-type="bibr" rid="B13">13</xref></sup> Em seguida, os dados foram revisados quanto &#224; qualidade; valores incertos ou incompletos foram devolvidos ao laborat&#243;rio para verifica&#231;&#227;o.</p>
      </sec>
      <sec>
        <title>Vari&#225;vel desfecho</title>
        <p>O diagn&#243;stico de DAC foi baseado em registros cl&#237;nicos e exames de imagem, como a angiografia coronariana. Os dados foram obtidos por entrevistas pessoais assistidas por computador (CAPI), conduzidas por entrevistadores treinados. O question&#225;rio e a metodologia est&#227;o dispon&#237;veis no site do NHANES.</p>
      </sec>
      <sec>
        <title>Covari&#225;veis</title>
        <p>As seguintes covari&#225;veis foram inclu&#237;das para ajuste de potenciais fatores de confus&#227;o na rela&#231;&#227;o entre os n&#237;veis de cafe&#237;na/metab&#243;litos e a doen&#231;a arterial coronariana: sexo, idade, ra&#231;a/etnia, hist&#243;rico de hipertens&#227;o, hipercolesterolemia, DM2, acidente vascular cerebral e tabagismo (definido como o consumo de pelo menos 100 cigarros ao longo da vida). Vari&#225;veis adicionais inclu&#237;ram consumo de &#225;lcool (definido como o consumo de pelo menos 12 bebidas alco&#243;licas por ano), atividade f&#237;sica (avaliada em equivalentes metab&#243;licos de tarefa [ <italic>metabolic equivalents of task</italic> , METs]) e &#237;ndice de massa corporal (IMC, kg/m<sup><xref ref-type="bibr" rid="B2">2</xref></sup>).<sup><xref ref-type="bibr" rid="B11">11</xref></sup> O IMC foi calculado pela raz&#227;o entre o peso (kg) e o quadrado da altura (m<sup><xref ref-type="bibr" rid="B2">2</xref></sup>). As medidas antropom&#233;tricas foram obtidas por t&#233;cnicos de sa&#250;de treinados em unidades m&#243;veis de exame, enquanto as demais covari&#225;veis foram coletadas por meio do sistema CAPI.</p>
      </sec>
      <sec>
        <title>An&#225;lise estat&#237;stica</title>
        <p>As an&#225;lises estat&#237;sticas foram realizadas utilizando o software R e o EmpowerStats.<sup><xref ref-type="bibr" rid="B14">14</xref></sup> Considerou-se signific&#226;ncia estat&#237;stica para valores de p bilaterais &lt; 0,05. Vari&#225;veis cont&#237;nuas com dados ausentes foram exclu&#237;das da an&#225;lise, enquanto vari&#225;veis categ&#243;ricas ausentes foram tratadas como uma categoria separada.</p>
        <p>A normalidade das vari&#225;veis cont&#237;nuas foi avaliada por meio do teste de Kolmogorov-Smirnov, com apoio de visualiza&#231;&#227;o gr&#225;fica por histogramas. Quando a distribui&#231;&#227;o foi normal, os resultados foram expressos como m&#233;dia &#177; desvio padr&#227;o (DP), e as compara&#231;&#245;es entre grupos foram realizadas utilizando o teste t para amostras independentes. Para dados n&#227;o normalmente distribu&#237;dos, os resultados foram apresentados como mediana e intervalo interquartil (Q1-Q3), e as compara&#231;&#245;es entre grupos foram conduzidas pelo teste de Mann-Whitney. Conforme detalhado no Ap&#234;ndice 1, as vari&#225;veis cont&#237;nuas deste estudo n&#227;o apresentaram distribui&#231;&#227;o normal.</p>
        <p>Vari&#225;veis categ&#243;ricas foram apresentadas como n&#250;meros absolutos (n) e percentuais (%), e as diferen&#231;as entre grupos foram avaliadas por meio do teste do qui-quadrado. Quando as frequ&#234;ncias esperadas foram &lt;10, aplicou-se o teste exato de Fisher.</p>
        <p>A an&#225;lise de regress&#227;o log&#237;stica multivariada foi empregada para investigar a associa&#231;&#227;o entre os n&#237;veis urin&#225;rios de cafe&#237;na e seus metab&#243;litos e a presen&#231;a de doen&#231;a arterial coronariana. Para vari&#225;veis cont&#237;nuas com distribui&#231;&#227;o n&#227;o normal, os dados foram estratificados em quartis (Q1-Q4). O quartil Q1, representando os 25% mais baixos dos valores, foi utilizado como grupo de refer&#234;ncia. Os quartis Q2, Q3 e Q4 representaram n&#237;veis progressivamente mais elevados, permitindo interpreta&#231;&#227;o mais clara das tend&#234;ncias ao longo da distribui&#231;&#227;o. Ressalta-se que Q4 corresponde aos 25% mais altos dos dados e n&#227;o faz parte de uma divis&#227;o em quintis.</p>
        <p>Ao agrupar os dados em quartis (Q1-Q4), foi poss&#237;vel avaliar de forma mais clara as tend&#234;ncias ao longo da distribui&#231;&#227;o da vari&#225;vel de interesse. O Q1, como menor n&#237;vel de exposi&#231;&#227;o, serviu como grupo de refer&#234;ncia, fornecendo uma base para compara&#231;&#227;o com os quartis superiores (Q2, Q3 e Q4). Essa abordagem permitiu avaliar em maior detalhe o comportamento da vari&#225;vel &#224; medida que os n&#237;veis de exposi&#231;&#227;o aumentavam. O Q4 destacou as caracter&#237;sticas do grupo com maior exposi&#231;&#227;o, evidenciando diferen&#231;as em rela&#231;&#227;o aos demais quartis. Tal m&#233;todo favorece a clareza na observa&#231;&#227;o de tend&#234;ncias e padr&#245;es no conjunto de dados.</p>
        <p>Selecionou-se o Q1 como grupo de refer&#234;ncia por representar o menor n&#237;vel de exposi&#231;&#227;o, geralmente associado ao menor risco, o que o torna adequado como grupo controle. Os demais quartis (Q2-Q4) refletem n&#237;veis crescentes de exposi&#231;&#227;o, permitindo uma compara&#231;&#227;o estruturada entre gradientes de exposi&#231;&#227;o e favorecendo a interpreta&#231;&#227;o das diferen&#231;as entre os grupos.</p>
        <p>Neste estudo, foram constru&#237;dos tr&#234;s modelos: o modelo 1 n&#227;o foi ajustado; o modelo 2 foi ajustado por sexo, idade e ra&#231;a/etnia; e o modelo 3 foi adicionalmente ajustado por sexo, idade, ra&#231;a/etnia, estatura, hist&#243;rico de hipertens&#227;o, hipercolesterolemia, DM2 e acidente vascular cerebral, bem como hist&#243;rico de tabagismo (definido como o consumo de pelo menos 100 cigarros ao longo da vida), consumo de &#225;lcool (&#8805;12 bebidas alco&#243;licas/ano) e IMC (kg/m<sup><xref ref-type="bibr" rid="B2">2</xref></sup>).</p>
        <p>Esses modelos foram utilizados para explorar a associa&#231;&#227;o entre os n&#237;veis urin&#225;rios de cafe&#237;na e seus metab&#243;litos e a DAC, considerando poss&#237;veis fatores de confus&#227;o. Al&#233;m disso, empregou-se ajuste por curvas suaves para examinar poss&#237;veis rela&#231;&#245;es n&#227;o lineares entre os n&#237;veis de cafe&#237;na/metab&#243;litos e a DAC. Tamb&#233;m foram realizadas an&#225;lises de subgrupos para explorar essas associa&#231;&#245;es dentro de estratos populacionais espec&#237;ficos e identificar poss&#237;veis modificadores de efeito.</p>
      </sec>
      <sec>
        <title>Aprova&#231;&#227;o &#233;tica</title>
        <p>Este estudo baseou-se em dados p&#250;blicos do NHANES, anonimizados e dispon&#237;veis no site oficial do programa. Portanto, n&#227;o foi necess&#225;ria aprova&#231;&#227;o &#233;tica.</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Resultados</title>
      <sec>
        <title>Caracter&#237;sticas b&#225;sicas da popula&#231;&#227;o do estudo.</title>
        <p>O teste de normalidade confirmou que as vari&#225;veis cont&#237;nuas n&#227;o seguiam uma distribui&#231;&#227;o normal (ver Ap&#234;ndice 1). Portanto, as vari&#225;veis cont&#237;nuas sem distribui&#231;&#227;o normal foram apresentadas como medianas e intervalos interquartis (IIQ), e as compara&#231;&#245;es entre os grupos foram realizadas por meio do teste de Mann-Whitney U. As vari&#225;veis categ&#243;ricas foram expressas como frequ&#234;ncias e porcentagens (n, %) e comparadas entre os grupos utilizando o teste do qui-quadrado ou o teste exato de Fisher quando as frequ&#234;ncias esperadas eram inferiores a 10. Um valor de p &lt; 0,05 foi considerado estatisticamente significativo.</p>
        <p>Os participantes do grupo com doen&#231;a arterial coronariana eram significativamente mais velhos (mediana de idade: 72 [IIQ: 63-80] anos) do que aqueles do grupo controle (mediana de idade: 48 [IIQ: 34-62] anos; p &lt; 0,001). O grupo com DAC tamb&#233;m apresentou maiores preval&#234;ncias de hipertens&#227;o, hipercolesterolemia, DM2 e acidente vascular cerebral, al&#233;m de maior hist&#243;rico de tabagismo e consumo de &#225;lcool (todos p &lt; 0,001). Al&#233;m disso, foram observadas diferen&#231;as significativas na distribui&#231;&#227;o &#233;tnica entre os grupos (p = 0,001).</p>
        <p>Dos metab&#243;litos urin&#225;rios analisados, apenas os n&#237;veis de paraxantina diferiram significativamente entre os grupos (p = 0,018) ( <xref ref-type="table" rid="t1">Tabela 1</xref> ).</p>
        <table-wrap id="t1">
          <label>Tabela 1</label>
          <caption>
            <title>Caracter&#237;sticas basais e n&#237;veis urin&#225;rios de cafe&#237;na e seus metab&#243;litos entre os participantes do estudo</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup width="14%">
              <col width="1%"/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
              <tr style="background-color:#76B4CF">
                <th align="left" colspan="2" valign="middle">Vari&#225;vel</th>
                <th align="center" valign="middle">Grupo com DAC <break/> (n = 222)</th>
                <th align="center" valign="middle">Grupo controle <break/> (n = 5.005)</th>
                <th align="center" valign="middle">Diferen&#231;a padronizada</th>
                <th align="center" valign="middle">Valor de p</th>
                <th align="center" valign="middle">Valor de p ajustado <break/> (se aplic&#225;vel)*</th>
              </tr>
            </thead>
            <tbody style="border-bottom: thin solid; border-color: #000000">
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>Idade (anos)</bold>
                </td>
                <td align="center" valign="middle">72 (63 a 80)</td>
                <td align="center" valign="middle">48 (34 a 62)</td>
                <td align="center" valign="middle">1,5 (1,3 a 1,6)</td>
                <td align="center" valign="middle">&lt;0,001</td>
                <td align="center" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>Sexo</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,4 (0,3 a 0,6)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&lt;0,001</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Masculino</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">153 (68,9%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">2.390 (47,8%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Feminino</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">69 (31,1%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">2.615 (52,2%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>Ra&#231;a/Etnia</bold>
                </td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle">0,5 (0,4 a 0,6)</td>
                <td align="center" valign="middle">&lt;0,001</td>
                <td align="center" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Mexicano-americano</td>
                <td align="center" valign="middle">17 (7,7%)</td>
                <td align="center" valign="middle">700 (14,0%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Outro hisp&#226;nico</td>
                <td align="center" valign="middle">18 (8,1%)</td>
                <td align="center" valign="middle">504 (10,1%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Branco n&#227;o hisp&#226;nico</td>
                <td align="center" valign="middle">146 (65,8%)</td>
                <td align="center" valign="middle">2.111 (42,2%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Negro n&#227;o hisp&#226;nico</td>
                <td align="center" valign="middle">26 (11,7%)</td>
                <td align="center" valign="middle">1.074 (21,5%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Outra/multirracial</td>
                <td align="center" valign="middle">15 (6,8%)</td>
                <td align="center" valign="middle">616 (12,3%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>Hipertens&#227;o</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,0 (0,8 a 1,1)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&lt;0,001</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Sim</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">173 (77,9%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1.735 (34,7%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">48 (21,6%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">3.262 (65,2%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o sabe</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1 (0,5%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">8 (0,2%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>Hipercolesterolemia</bold>
                </td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle">1,0 (0,9 a 1,1)</td>
                <td align="center" valign="middle">&lt;0,001</td>
                <td align="center" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Sim</td>
                <td align="center" valign="middle">163 (73,4%)</td>
                <td align="center" valign="middle">1.552 (31,0%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">N&#227;o</td>
                <td align="center" valign="middle">56 (25,2%)</td>
                <td align="center" valign="middle">2.887 (57,7%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">N&#227;o sabe</td>
                <td align="center" valign="middle">3 (1,4%)</td>
                <td align="center" valign="middle">31 (0,6%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Ausente</td>
                <td align="center" valign="middle">0 (0,0%)</td>
                <td align="center" valign="middle">535 (10,7%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>DM2</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,5 (0,4 a 0,6)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&lt;0,001</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Sim</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">65 (29,3%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">550 (11,0%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">147 (66,2%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">4.333 (86,6%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Lim&#237;trofe</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">10 (4,5%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">117 (2,3%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o sabe</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0 (0,0%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">5 (0,1%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>Acidente vascular cerebral</bold>
                </td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle">0,4 (0,3 a 0,5)</td>
                <td align="center" valign="middle">&lt;0,001</td>
                <td align="center" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Sim</td>
                <td align="center" valign="middle">29 (13,1%)</td>
                <td align="center" valign="middle">138 (2,8%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">N&#227;o</td>
                <td align="center" valign="middle">192 (86,5%)</td>
                <td align="center" valign="middle">4.864 (97,2%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">N&#227;o sabe</td>
                <td align="center" valign="middle">1 (0,5%)</td>
                <td align="center" valign="middle">3 (0,1%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>Fumou &#8805;100 cigarros na vida</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,4 (0,2 a 0,5)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&lt;0,001</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Sim</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">136 (61,3%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">2.160 (43,2%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">86 (38,7%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">2.844 (56,8%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o sabe</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0 (0,0%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1 (0,0%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>&#8805;12 doses de bebida alco&#243;lica/ano</bold>
                </td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle">0,2 (0,0 a 0,3)</td>
                <td align="center" valign="middle">0,195</td>
                <td align="center" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Sim</td>
                <td align="center" valign="middle">156 (70,3%)</td>
                <td align="center" valign="middle">3.278 (65,5%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">N&#227;o</td>
                <td align="center" valign="middle">54 (24,3%)</td>
                <td align="center" valign="middle">1.249 (25,0%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">N&#227;o sabe</td>
                <td align="center" valign="middle">0 (0,0%)</td>
                <td align="center" valign="middle">2 (0,0%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Ausente</td>
                <td align="center" valign="middle">12 (5,4%)</td>
                <td align="center" valign="middle">476 (9,5%)</td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>Atividade f&#237;sica (MET)</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,4 (0,3 a 0,6)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&lt;0,001</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">&lt;4</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">91 (41,0%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1.264 (25,3%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">4&#8211;8</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">70 (31,5%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1.392 (27,8%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">&#8805;8</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">61 (27,5%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">2.349 (46,9%)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>IMC (kg/m<sup>2</sup>)</bold>
                </td>
                <td align="center" valign="middle">28,86 <break/> (25,80 a 32,98)</td>
                <td align="center" valign="middle">28,00 <break/> (24,30 a 32,42)</td>
                <td align="center" valign="middle">0,2 <break/> (0,0 a 0,3)</td>
                <td align="center" valign="middle">0,023</td>
                <td align="center" valign="middle">0,007</td>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>Teofilina urin&#225;ria (&#956;mol/L)</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,645 <break/> (0,625 a 3,538)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,88 <break/> (0,639 a 3,84)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,1 <break/> (&#8211;0,1 a 0,2)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,532</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,367</td>
              </tr>
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>Paraxantina urin&#225;ria (&#956;mol/L)</bold>
                </td>
                <td align="center" valign="middle">16,6 <break/> (4,738 a 29,325)</td>
                <td align="center" valign="middle">17,5 <break/> (5,72 a 37,4)</td>
                <td align="center" valign="middle">0,2 <break/> (0,0 a 0,3)</td>
                <td align="center" valign="middle">0,018</td>
                <td align="center" valign="middle">0,098</td>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>Teobromina urin&#225;ria (&#956;mol/L)</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">13,5 <break/> (6,285 a 29,8)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">15,3 <break/> (6,36 a 34,0)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,1 <break/> (&#8211;0,1 a 0,2)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,367</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,289</td>
              </tr>
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>Cafe&#237;na urin&#225;ria (&#956;mol/L)</bold>
                </td>
                <td align="center" valign="middle">5,465 <break/> (1,533 a 12,2)</td>
                <td align="center" valign="middle">4,23 <break/> (1,01 a 10,8)</td>
                <td align="center" valign="middle">0,1 <break/> (&#8211;0,0 a 0,2)</td>
                <td align="center" valign="middle">0,086</td>
                <td align="center" valign="middle">0,045</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN1">
              <p>DAC: doen&#231;a arterial coronariana; DM2: diabetes melito tipo 2; IMC: &#237;ndice de massa corporal; MET: <italic>metabolic equivalent of task</italic> .</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>Os resultados da associa&#231;&#227;o entre os n&#237;veis urin&#225;rios de cafe&#237;na e a DAC est&#227;o apresentados na <xref ref-type="table" rid="t2">Tabela 2</xref> . Na an&#225;lise n&#227;o ajustada, os n&#237;veis de cafe&#237;na urin&#225;ria como vari&#225;vel cont&#237;nua n&#227;o se associaram significativamente &#224; DAC (todos os valores de p &gt; 0,05). Quando os n&#237;veis de cafe&#237;na foram categorizados em quartis, os indiv&#237;duos no quartil mais alto (Q4) apresentaram um aumento estatisticamente significativo no risco de DAC (OR 1,54; IC 95%: 1,04-2,30; p = 0,0318) em compara&#231;&#227;o com aqueles no quartil mais baixo (Q1). Isso indica que os participantes no Q4 tinham 54% mais chances de DAC do que aqueles no Q1.</p>
        <table-wrap id="t2">
          <label>Tabela 2</label>
          <caption>
            <title>Associa&#231;&#227;o entre n&#237;veis urin&#225;rios de cafe&#237;na (&#956;mol/L) e DAC</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup width="20%">
              <col width="1%"/>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
              <tr style="background-color:#76B4CF">
                <th align="left" colspan="2" valign="middle">Vari&#225;vel</th>
                <th align="center" valign="middle">Modelo 1, <break/> OR (IC 95%), valor p</th>
                <th align="center" valign="middle">Modelo 2, <break/> OR (IC 95%), valor p</th>
                <th align="center" valign="middle">Modelo 3, <break/> OR (IC 95%), valor p</th>
              </tr>
            </thead>
            <tbody style="border-bottom: thin solid; border-color: #000000">
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>Cafe&#237;na (&#956;mol/L)</bold>
                </td>
                <td align="center" valign="middle">1,01 (1,00-1,02), 0,0859</td>
                <td align="center" valign="middle">1,00 (0,99-1,01), 0,9476</td>
                <td align="center" valign="middle">0,99 (0,98-1,01), 0,3973</td>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>Quartis de cafe&#237;na</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Q1 (Refer&#234;ncia)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Q2</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,37 (0,91-2,06), 0,1257</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,20 (0,78-1,85), 0,3998</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,13 (0,73-1,77), 0,5799</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Q3</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,42 (0,95-2,13), 0,0874</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,18 (0,77-1,81), 0,4479</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,01 (0,65-1,59), 0,9487</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Q4</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,54 (1,04-2,30), 0,0318</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,10 (0,72-1,68), 0,6571</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,94 (0,61-1,47), 0,8006</td>
              </tr>
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>Sexo</bold>
                </td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Masculino</td>
                <td align="center" valign="middle">1,00 (1,00-1,00), 0,009</td>
                <td align="center" valign="middle">1,00 (1,00-1,00), 0,545</td>
                <td align="center" valign="middle">1,00 (1,00-1,00), 0,804</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Feminino</td>
                <td align="center" valign="middle">1,00 (1,00-1,00), 0,721</td>
                <td align="center" valign="middle">1,00 (1,00-1,00), 0,282</td>
                <td align="center" valign="middle">1,00 (1,00-1,00), 0,155</td>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>Ra&#231;a/etnia</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Mexicano-americano</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,03 (1,01-1,05), 0,0081</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,03 (1,00-1,05), 0,0700</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,02 (0,98-1,06), 0,2327</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Outro hisp&#226;nico</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,03 (0,99-1,07), 0,1409</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,02 (0,97-1,06), 0,4538</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,00 (0,95-1,05), 0,9737</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Branco n&#227;o hisp&#226;nico</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,99 (0,98-1,01), 0,3734</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,99 (0,97-1,01), 0,2670</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,98 (0,97-1,00), 0,0826</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Negro n&#227;o hisp&#226;nico</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,00 (0,95-1,05), 0,9936</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,99 (0,94-1,04), 0,6900</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,99 (0,93-1,04), 0,6351</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>An&#225;lises adicionais foram estratificadas por sexo e ra&#231;a/etnia. Na an&#225;lise estratificada por sexo, os n&#237;veis urin&#225;rios de cafe&#237;na n&#227;o se associaram significativamente &#224; incid&#234;ncia de DAC em homens ou mulheres (OR 1,00; IC 95%: 1,00-1,00; p = 0,009, o que provavelmente reflete artefato do modelo ou colinearidade).</p>
        <p>Na an&#225;lise estratificada por ra&#231;a, uma associa&#231;&#227;o positiva significativa foi observada apenas entre participantes mexicano-americanos, nos quais cada aumento de 1 &#956;mol/L nos n&#237;veis urin&#225;rios de cafe&#237;na se associou a um aumento de 3% no risco de DAC (OR 1,03; IC 95%: 1,03-1,05; p = 0,0081). Nenhuma associa&#231;&#227;o estatisticamente significativa foi encontrada nos demais grupos raciais/&#233;tnicos (todos os p &gt; 0,05).</p>
        <p>Essas associa&#231;&#245;es est&#227;o representadas visualmente na <xref ref-type="fig" rid="f2">Figura 2A</xref> , que mostra uma curva suavizada ilustrando a rela&#231;&#227;o entre a concentra&#231;&#227;o urin&#225;ria de cafe&#237;na e a incid&#234;ncia de DAC.</p>
        <fig id="f2">
          <label>Figura 2</label>
          <caption>
            <title>Gr&#225;ficos de curvas suavizadas exibindo a rela&#231;&#227;o entre os n&#237;veis urin&#225;rios de cafe&#237;na e seus metab&#243;litos (&#956;mol/L) e a incid&#234;ncia de DAC. A linha vermelha representa a curva ajustada que mostra a associa&#231;&#227;o estimada, enquanto a &#225;rea azul sombreada denota o intervalo de confian&#231;a de 95%. Os modelos foram ajustados por sexo, idade, ra&#231;a/etnia, hipertens&#227;o, hipercolesterolemia, diabetes melito tipo 2, AVC, tabagismo, consumo de &#225;lcool e IMC. AVC: acidente vascular cerebral; IMC: &#237;ndice de massa corporal; DAC: doen&#231;a arterial coronariana; DM2: diabetes mellitus tipo 2.</title>
          </caption>
          <graphic xlink:href=""/>
        </fig>
        <p>As associa&#231;&#245;es entre os n&#237;veis urin&#225;rios dos metab&#243;litos da cafe&#237;na e a DAC est&#227;o apresentadas na <xref ref-type="table" rid="t3">Tabela 3</xref> .</p>
        <table-wrap id="t3">
          <label>Tabela 3</label>
          <caption>
            <title>Associa&#231;&#227;o entre n&#237;veis urin&#225;rios dos metab&#243;litos da cafe&#237;na (&#956;mol/L) e DAC</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup width="20%">
              <col width="1%"/>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
              <tr style="background-color:#76B4CF">
                <th align="left" colspan="2" valign="middle">
                  <bold>Vari&#225;vel</bold>
                </th>
                <th align="center" valign="middle">Modelo 1, <break/> OR (IC 95%), p-valor</th>
                <th align="center" valign="middle">Modelo 2, <break/> OR (IC 95%), p-valor</th>
                <th align="center" valign="middle">Modelo 3, <break/> OR (IC 95%), p-valor</th>
              </tr>
            </thead>
            <tbody style="border-bottom: thin solid; border-color: #000000">
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>Teofilina (&#956;mol/L)</bold>
                </td>
                <td align="center" valign="middle">0,98 (0,93 a 1,02), 0,3320</td>
                <td align="center" valign="middle">0,98 (0,94 a 1,02), 0,3084</td>
                <td align="center" valign="middle">0,97 (0,93 a 1,02), 0,2592</td>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>Quartis de teofilina</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Q1 (Refer&#234;ncia)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Q2</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,10 (0,76 a 1,59), 0,6243</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,00 (0,67 a 1,49), 0,9914</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,94 (0,62 a 1,42), 0,7712</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Q3</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,94 (0,64 a 1,38), 0,7660</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,89 (0,59 a 1,34), 0,5788</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,83 (0,54 a 1,27), 0,3800</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Q4</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,92 (0,63 a 1,36), 0,6883</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,90 (0,59 a 1,36), 0,6020</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,85 (0,55 a 1,31), 0,4527</td>
              </tr>
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>Teobromina (&#956;mol/L)</bold>
                </td>
                <td align="center" valign="middle">1,00 (0,99 a 1,00), 0,3674</td>
                <td align="center" valign="middle">1,00 (1,00 a 1,00), 0,6186</td>
                <td align="center" valign="middle">1,00 (1,00 a 1,00), 0,9285</td>
              </tr>
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>Quartis de teobromina</bold>
                </td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Q1 (Refer&#234;ncia)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Q2</td>
                <td align="center" valign="middle">1,12 (0,77 a 1,62), 0,5605</td>
                <td align="center" valign="middle">1,19 (0,80 a 1,76), 0,3965</td>
                <td align="center" valign="middle">1,09 (0,73 a 1,64), 0,6724</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Q3</td>
                <td align="center" valign="middle">1,09 (0,75 a 1,58), 0,6515</td>
                <td align="center" valign="middle">1,14 (0,76 a 1,70), 0,5217</td>
                <td align="center" valign="middle">1,10 (0,73 a 1,68), 0,6430</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Q4</td>
                <td align="center" valign="middle">0,76 (0,51 a 1,14), 0,1816</td>
                <td align="center" valign="middle">0,84 (0,54 a 1,30), 0,4293</td>
                <td align="center" valign="middle">0,89 (0,57 a 1,40), 0,6291</td>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>Paraxantina (&#956;mol/L)</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,99 (0,99 a 1,00), 0,0177</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,00 (0,99 a 1,00), 0,1037</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,99 (0,99 a 1,00), 0,1154</td>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>Quartis de paraxantina</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Q1 (Refer&#234;ncia)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Q2</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,90 (0,62 a 1,31), 0,5866</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,76 (0,51 a 1,13), 0,1789</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,74 (0,49 a 1,11), 0,1461</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Q3</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,01 (0,71 a 1,45), 0,9409</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,99 (0,67 a 1,45), 0,9396</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,97 (0,65 a 1,45), 0,8707</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Q4</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,65 (0,43 a 0,97), 0,0360</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,68 (0,44 a 1,04), 0,0779</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,65 (0,42 a 1,03), 0,0655</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN2">
              <p>DAC: doen&#231;a arterial coronariana.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>A rela&#231;&#227;o entre os metab&#243;litos urin&#225;rios da cafe&#237;na e a DAC &#233; explorada mais detalhadamente por meio do ajuste de curvas suavizadas na <xref ref-type="fig" rid="f2">Figura 2</xref> .</p>
      </sec>
      <sec>
        <title>Associa&#231;&#227;o entre n&#237;veis urin&#225;rios de cafe&#237;na e DAC</title>
        <p>Os resultados da associa&#231;&#227;o entre os metab&#243;litos urin&#225;rios da cafe&#237;na e a DAC est&#227;o apresentados na <xref ref-type="table" rid="t3">Tabela 3</xref> . No Modelo 1, os n&#237;veis urin&#225;rios de teofilina e teobromina n&#227;o mostraram associa&#231;&#227;o estatisticamente significativa com DAC (todos os valores de p &gt; 0,05). Quando os n&#237;veis de teofilina e teobromina foram categorizados em quartis, nenhuma associa&#231;&#227;o significativa foi observada em nenhum dos modelos. Ap&#243;s o ajuste para potenciais fatores de confus&#227;o nos Modelos 2 e 3, esses achados permaneceram n&#227;o significativos. O ajuste de curvas suavizadas para teofilina e teobromina ( <xref ref-type="fig" rid="f2">Figuras 2B</xref> e <xref ref-type="fig" rid="f2">2C</xref> , respectivamente) tamb&#233;m n&#227;o demonstrou associa&#231;&#227;o clara com o risco de DAC.</p>
        <p>Em contraste, os n&#237;veis urin&#225;rios de paraxantina mostraram uma associa&#231;&#227;o inversa significativa com DAC no modelo n&#227;o ajustado (Modelo 1: OR 0,99; IC 95% 0,99-1,00; p = 0,0177). No entanto, essa associa&#231;&#227;o deixou de ser estatisticamente significativa ap&#243;s o ajuste para covari&#225;veis nos Modelos 2 e 3.</p>
        <p>Para uma avalia&#231;&#227;o adicional da rela&#231;&#227;o, a paraxantina tamb&#233;m foi analisada como vari&#225;vel categ&#243;rica dividida em quartis. No Modelo 1, indiv&#237;duos no quartil mais alto de paraxantina urin&#225;ria (Q4) apresentaram risco significativamente menor de DAC em compara&#231;&#227;o com aqueles no quartil mais baixo (OR 0,65; IC 95% 0,43-0,97; p = 0,036). Contudo, essa associa&#231;&#227;o inversa perdeu signific&#226;ncia estat&#237;stica ap&#243;s o ajuste nos Modelos 2 e 3 (todos os valores de p &gt; 0,05).</p>
        <p>As concentra&#231;&#245;es urin&#225;rias de teofilina, paraxantina, teobromina e cafe&#237;na foram comparadas entre o grupo com cardiopatia cong&#234;nita e o grupo controle, conforme detalhado na <xref ref-type="table" rid="t4">Tabela 4</xref> .</p>
        <table-wrap id="t4">
          <label>Tabela 4</label>
          <caption>
            <title>Compara&#231;&#227;o dos n&#237;veis urin&#225;rios de cafe&#237;na e de seus metab&#243;litos (&#956;mol/L) entre o grupo com DAC e o grupo controle</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup width="20%">
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
              <tr style="background-color:#76B4CF">
                <th align="left" valign="middle">Metab&#243;lito</th>
                <th align="center" valign="middle">Grupo</th>
                <th align="center" valign="middle">Modelo 1, <break/> OR (IC 95%), valor p</th>
                <th align="center" valign="middle">Modelo 2, <break/> OR (IC 95%), valor p</th>
                <th align="center" valign="middle">Modelo 3, <break/> OR (IC 95%), valor p</th>
              </tr>
            </thead>
            <tbody style="border-bottom: thin solid; border-color: #000000">
              <tr>
                <td align="left" valign="middle">
                  <bold>Teofilina</bold>
                </td>
                <td align="center" valign="middle">Controle (n = 5.005)</td>
                <td align="center" valign="middle">Refer&#234;ncia</td>
                <td align="center" valign="middle">Refer&#234;ncia</td>
                <td align="center" valign="middle">Refer&#234;ncia</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="center" valign="middle">DAC (n = 222)</td>
                <td align="center" valign="middle">&#8722;0,4 (&#8722;0,9 a 0,1), 0,0923</td>
                <td align="center" valign="middle">&#8722;0,8 (&#8722;1,5 a &#8722;0,1), 0,0196</td>
                <td align="center" valign="middle">&#8722;0,7 (&#8722;1,5 a &#8722;0,0), 0,0412</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle">
                  <bold>Paraxantina</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">Controle (n = 5.005)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">Refer&#234;ncia</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">Refer&#234;ncia</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">Refer&#234;ncia</td>
              </tr>
              <tr>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle">DAC (n = 222)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;4,8 (&#8722;8,0 a &#8722;1,7), 0,0028</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;5,1 (&#8722;8,4 a &#8722;1,8), 0,0023</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;4,1 (&#8722;7,3 a &#8722;0,8), 0,0135</td>
              </tr>
              <tr>
                <td align="left" valign="middle">
                  <bold>Teobromina</bold>
                </td>
                <td align="center" valign="middle">Controle (n = 5.005)</td>
                <td align="center" valign="middle">Refer&#234;ncia</td>
                <td align="center" valign="middle">Refer&#234;ncia</td>
                <td align="center" valign="middle">Refer&#234;ncia</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="center" valign="middle">DAC (n = 222)</td>
                <td align="center" valign="middle">&#8722;2,5 (&#8722;8,2 a 3,2), 0,3925</td>
                <td align="center" valign="middle">&#8722;0,1 (&#8722;5,9 a 5,7), 0,9689</td>
                <td align="center" valign="middle">&#8722;0,1 (&#8722;5,9 a 5,7), 0,9770</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle">
                  <bold>Cafe&#237;na</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">Controle (n = 5.005)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">Refer&#234;ncia</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">Refer&#234;ncia</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">Refer&#234;ncia</td>
              </tr>
              <tr>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle">DAC (n = 222)</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,2 (&#8722;0,4 a 2,8), 0,1327</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0,9 (&#8722;2,5 a 0,8), 0,2966</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0,5 (&#8722;2,1 a 1,1), 0,5534</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN3">
              <p>DAC: doen&#231;a arterial coronariana.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>Esta an&#225;lise utilizou tr&#234;s modelos: um modelo n&#227;o ajustado (Modelo 1) e dois modelos ajustados &#8212; Modelo 2 (Ajuste 1) e Modelo 3 (Ajuste 2). A <xref ref-type="table" rid="t4">Tabela 4</xref> compara as concentra&#231;&#245;es urin&#225;rias de quatro compostos (teofilina, paraxantina, teobromina e cafe&#237;na) entre dois grupos: indiv&#237;duos sem doen&#231;a arterial coronariana (grupo controle; n = 5.005) e indiv&#237;duos com doen&#231;a arterial coronariana (grupo com DAC; n = 222). Para cada composto, &#233; apresentada a diferen&#231;a na concentra&#231;&#227;o urin&#225;ria m&#233;dia entre o grupo com DAC e o grupo controle, juntamente com o IC 95% correspondente e o valor de p. A diferen&#231;a reflete a estimativa da diferen&#231;a m&#233;dia de concentra&#231;&#227;o entre os dois grupos. O IC 95% fornece a faixa dentro da qual a verdadeira diferen&#231;a provavelmente se encontra. Um valor de p inferior a 0,05 indica uma diferen&#231;a estatisticamente significativa.</p>
        <p>Os resultados mostraram que, no modelo n&#227;o ajustado, a teofilina apresentou uma diferen&#231;a de &#8722;0,4 (&#8722;0,9 a 0,1; p = 0,0923), sem signific&#226;ncia estat&#237;stica. No Ajuste 1, a diferen&#231;a foi de &#8722;0,8 (&#8722;1,5 a &#8722;0,1; p = 0,0196), com signific&#226;ncia estat&#237;stica. No Ajuste 2, a diferen&#231;a foi de &#8722;0,7 (&#8722;1,5 a &#8722;0,0; p = 0,0412), tamb&#233;m estatisticamente significativa. Ap&#243;s o ajuste, a concentra&#231;&#227;o de teofilina no grupo com doen&#231;a arterial coronariana foi significativamente menor do que no grupo controle. Em rela&#231;&#227;o &#224; paraxantina, o modelo n&#227;o ajustado indicou uma diferen&#231;a de &#8722;4,8 (&#8722;8,0 a &#8722;1,7; p = 0,0028), estatisticamente significativa. No Ajuste 1, a diferen&#231;a foi de &#8722;5,1 (&#8722;8,4 a &#8722;1,8; p = 0,0023), tamb&#233;m significativa. No Ajuste 2, a diferen&#231;a foi de &#8722;4,1 (&#8722;7,3 a &#8722;0,8; p = 0,0135), mantendo a signific&#226;ncia estat&#237;stica. Os n&#237;veis de paraxantina foram consistentemente menores em todos os modelos, quando comparados ao grupo controle.</p>
        <p>A teobromina, no modelo n&#227;o ajustado, apresentou uma diferen&#231;a de &#8722;2,5 (&#8722;8,2 a 3,2; p = 0,3925), sem signific&#226;ncia. No Ajuste 1, a diferen&#231;a foi de &#8722;0,1 (&#8722;5,9 a 5,7; p = 0,9689), tamb&#233;m sem signific&#226;ncia. No Ajuste 2, a diferen&#231;a permaneceu em &#8722;0,1 (&#8722;5,9 a 5,7; p = 0,9770), igualmente sem signific&#226;ncia estat&#237;stica. Portanto, n&#227;o houve diferen&#231;a significativa nas concentra&#231;&#245;es de teobromina entre os grupos. A cafe&#237;na, no modelo n&#227;o ajustado, apresentou uma diferen&#231;a de 1,2 (&#8722;0,4 a 2,8; p = 0,1327), sem signific&#226;ncia. No Ajuste 1, a diferen&#231;a foi de &#8722;0,9 (&#8722;2,5 a 0,8; p = 0,2966), tamb&#233;m sem signific&#226;ncia. No Ajuste 2, a diferen&#231;a foi de &#8722;0,5 (&#8722;2,1 a 1,1; p = 0,5534), igualmente sem signific&#226;ncia. Ap&#243;s o ajuste, n&#227;o houve diferen&#231;a estatisticamente significativa na concentra&#231;&#227;o de cafe&#237;na entre os dois grupos.</p>
        <p>Dessa forma, pode-se concluir que as concentra&#231;&#245;es de teofilina e paraxantina no grupo com doen&#231;a arterial coronariana foram significativamente menores em compara&#231;&#227;o ao grupo controle, especialmente ap&#243;s os ajustes, que mantiveram a signific&#226;ncia estat&#237;stica. Isso sugere que esses compostos podem estar associados &#224; DAC. Por outro lado, n&#227;o houve diferen&#231;a significativa nas concentra&#231;&#245;es de teobromina e cafe&#237;na entre os grupos, o que indica que esses compostos podem n&#227;o estar diretamente relacionados &#224; DAC. O impacto dos diferentes modelos de ajuste sobre os resultados foi limitado, mas os dados ajustados s&#227;o considerados mais confi&#225;veis.</p>
      </sec>
      <sec>
        <title>An&#225;lise por subgrupos</title>
        <p>A <xref ref-type="table" rid="t5">Tabela 5</xref> apresenta os resultados da an&#225;lise estratificada da teofilina, paraxantina, teobromina e cafe&#237;na em diferentes subgrupos, incluindo os valores de efeito, ICs 95% e valores p. Por meio da an&#225;lise estratificada, &#233; poss&#237;vel observar as diferen&#231;as nas concentra&#231;&#245;es dos compostos e sua signific&#226;ncia estat&#237;stica entre diferentes grupos com caracter&#237;sticas distintas.</p>
        <table-wrap id="t5">
          <label>Tabela 5</label>
          <caption>
            <title>An&#225;lise por subgrupos</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup width="14%">
              <col width="1%"/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
              <tr style="background-color:#76B4CF">
                <th align="left" colspan="2" valign="middle">Subgrupo</th>
                <th align="center" valign="middle">N</th>
                <th align="center" valign="middle">Teofilina</th>
                <th align="center" valign="middle">Paraxantina</th>
                <th align="center" valign="middle">Teobromina</th>
                <th align="center" valign="middle">Cafe&#237;na</th>
              </tr>
            </thead>
            <tbody style="border-bottom: thin solid; border-color: #000000">
              <tr>
                <td align="left" valign="middle">
                  <bold>Sexo</bold>
                </td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Masculino</td>
                <td align="center" valign="middle">2.543</td>
                <td align="center" valign="middle">&#8722;0,4 (&#8722;2,7 a 1,8), <break/> p = 0,7161</td>
                <td align="center" valign="middle">&#8722;4,8 (&#8722;9,8 a 0,1), <break/> p = 0,0538</td>
                <td align="center" valign="middle">0,4 (&#8722;6,0 a 6,8), <break/> p = 0,9105</td>
                <td align="center" valign="middle">2,2 (0,6 a 3,8), <break/> p = 0,0081</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Feminino</td>
                <td align="center" valign="middle">2.684</td>
                <td align="center" valign="middle">&#8722;0,7 (&#8722;1,7 a 0,4), <break/> p = 0,2290</td>
                <td align="center" valign="middle">&#8722;7,4 (&#8722;14,5 a &#8722;0,4), <break/> p = 0,0379</td>
                <td align="center" valign="middle">&#8722;6,7 (&#8722;16,5 a 3,1), <break/> p = 0,1791</td>
                <td align="center" valign="middle">&#8722;0,5 (&#8722;3,1 a 2,1), <break/> p = 0,7220</td>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>Faixa et&#225;ria (anos)</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">18-39</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1.685</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0,9 (&#8722;3,6 a 1,9), <break/> p = 0,5380</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;11,0 (&#8722;37,5 a 15,4), <break/> p = 0,4137</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;17,7 (&#8722;53,9 a 18,5), <break/> p = 0,3381</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;3,9 (&#8722;11,3 a 3,6), <break/> p = 0,3106</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">40-57</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1.740</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0,6 (&#8722;1,7 a 0,5), <break/> p = 0,2582</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;2,0 (&#8722;13,3 a 9,3), <break/> p = 0,7259</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;8,8 (&#8722;23,3 a 5,8), <break/> p = 0,2373</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,9 (&#8722;2,6 a 4,4), <break/> p = 0,6177</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">58-80</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1.802</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0,8 (&#8722;3,3 a 1,7), <break/> p = 0,5434</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;3,6 (&#8722;7,7 a 0,5), <break/> p = 0,0882</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">2,0 (&#8722;3,8 a 7,8), <break/> p = 0,5072</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,3 (&#8722;1,5 a 2,1), <break/> p = 0,7589</td>
              </tr>
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>Ra&#231;a</bold>
                </td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Mexicano-americano</td>
                <td align="center" valign="middle">717</td>
                <td align="center" valign="middle">1,7 (&#8722;0,0 a 3,4), <break/> p = 0,0531</td>
                <td align="center" valign="middle">3,1 (&#8722;12,4 a 18,5), <break/> p = 0,6971</td>
                <td align="center" valign="middle">3,7 (&#8722;12,0 a 19,4), <break/> p = 0,6447</td>
                <td align="center" valign="middle">9,0 (3,9 a 14,1), <break/> p = 0,0006</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Outro hisp&#226;nico</td>
                <td align="center" valign="middle">522</td>
                <td align="center" valign="middle">0,0 (&#8722;1,4 a 1,5), <break/> p = 0,9699</td>
                <td align="center" valign="middle">1,2 (&#8722;12,3 a 14,8), <break/> p = 0,8565</td>
                <td align="center" valign="middle">&#8722;5,4 (&#8722;22,1 a 11,3), <break/> p = 0,5295</td>
                <td align="center" valign="middle">3,3 (&#8722;1,0 a 7,6), <break/> p = 0,1348</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Branco n&#227;o hisp&#226;nico</td>
                <td align="center" valign="middle">2.257</td>
                <td align="center" valign="middle">&#8722;1,1 (&#8722;3,6 a 1,4), <break/> p = 0,3858</td>
                <td align="center" valign="middle">&#8722;7,3 (&#8722;12,2 a &#8722;2,4), <break/> p = 0,0034</td>
                <td align="center" valign="middle">&#8722;4,9 (&#8722;12,3 a 2,5), <break/> p = 0,1936</td>
                <td align="center" valign="middle">&#8722;0,9 (&#8722;2,8 a 1,1), <break/> p = 0,3745</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Negro n&#227;o hisp&#226;nico</td>
                <td align="center" valign="middle">1.100</td>
                <td align="center" valign="middle">&#8722;0,7 (&#8722;1,6 a 0,2), <break/> p = 0,1460</td>
                <td align="center" valign="middle">&#8722;7,7 (&#8722;18,3 a 2,9), <break/> p = 0,1538</td>
                <td align="center" valign="middle">&#8722;7,7 (&#8722;22,1 a 6,7), <break/> p = 0,2933</td>
                <td align="center" valign="middle">&#8722;0,0 (&#8722;3,1 a 3,0), <break/> p = 0,9936</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Outro / multirracial</td>
                <td align="center" valign="middle">631</td>
                <td align="center" valign="middle">&#8722;0,3 (&#8722;1,9 a 1,2), <break/> p = 0,6714</td>
                <td align="center" valign="middle">&#8722;2,6 (&#8722;19,8 a 14,6), <break/> p = 0,7695</td>
                <td align="center" valign="middle">&#8722;7,0 (&#8722;27,6 a 13,6), <break/> p = 0,5071</td>
                <td align="center" valign="middle">1,7 (&#8722;2,8 a 6,1), <break/> p = 0,4658</td>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>Hipertens&#227;o</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Sim</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1.908</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,1 (&#8722;0,5 a 0,7), <break/> p = 0,8032</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1,4 (&#8722;5,6 a 2,9), <break/> p = 0,5379</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,5 (&#8722;4,2 a 7,2), <break/> p = 0,6026</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,5 (&#8722;0,2 a 3,3), <break/> p = 0,0869</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">3.310</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1,3 (&#8722;4,8 a 2,2), <break/> p = 0,4758</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;9,7 (&#8722;18,5 a &#8722;1,0), <break/> p = 0,0299</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;7,2 (&#8722;19,2 a 4,7), <break/> p = 0,2365</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1,5 (&#8722;4,3 a 1,3), <break/> p = 0,2977</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o sabe</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">9</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>Colesterol alto</bold>
                </td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Sim</td>
                <td align="center" valign="middle">1.715</td>
                <td align="center" valign="middle">&#8722;0,2 (&#8722;0,7 a 0,3), <break/> p = 0,4859</td>
                <td align="center" valign="middle">&#8722;3,7 (&#8722;8,3 a 1,0), <break/> p = 0,1196</td>
                <td align="center" valign="middle">&#8722;1,6 (&#8722;8,3 a 5,0), <break/> p = 0,6333</td>
                <td align="center" valign="middle">1,0 (&#8722;0,8 a 2,8), <break/> p = 0,2794</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">N&#227;o</td>
                <td align="center" valign="middle">2.943</td>
                <td align="center" valign="middle">&#8722;0,7 (&#8722;3,8 a 2,4), <break/> p = 0,6428</td>
                <td align="center" valign="middle">&#8722;7,0 (&#8722;15,1 a 1,1), <break/> p = 0,0924</td>
                <td align="center" valign="middle">&#8722;3,6 (&#8722;14,0 a 6,7), <break/> p = 0,4927</td>
                <td align="center" valign="middle">&#8722;0,4 (&#8722;3,1 a 2,4), <break/> p = 0,7814</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">N&#227;o sabe</td>
                <td align="center" valign="middle">34</td>
                <td align="center" valign="middle">&#8722;0,5 (&#8722;4,8 a 3,9), <break/> p = 0,8378</td>
                <td align="center" valign="middle">&#8722;13,2 (&#8722;57,1 a 30,7), p = 0,5605</td>
                <td align="center" valign="middle">&#8722;14,6 (&#8722;68,1 a 38,9), <break/> p = 0,5969</td>
                <td align="center" valign="middle">0,0 (&#8722;12,4 a 12,4), <break/> p = 0,9987</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Dados ausentes</td>
                <td align="center" valign="middle">535</td>
                <td align="center" valign="middle">&#8212;</td>
                <td align="center" valign="middle">&#8212;</td>
                <td align="center" valign="middle">&#8212;</td>
                <td align="center" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>DM2</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Sim</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">615</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0,4 (&#8722;1,2 a 0,4), <break/> p = 0,3501</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;6,8 (&#8722;13,6 a 0,0), <break/> p = 0,0513</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,1 (&#8722;8,5 a 8,7), <break/> p = 0,9758</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1,0 (&#8722;3,6 a 1,7), <break/> p = 0,4773</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">4.480</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0,2 (&#8722;1,8 a 1,4), <break/> p = 0,7934</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;2,6 (&#8722;7,6 a 2,3), <break/> p = 0,2998</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0,9 (&#8722;7,5 a 5,7), <break/> p = 0,7801</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">2,1 (0,4 a 3,8), <break/> p = 0,0165</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Lim&#237;trofe</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">127</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;3,2 (&#8722;22,6 a 16,3), <break/> p = 0,7500</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;8,0 (&#8722;28,2 a 12,3), <break/> p = 0,4417</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;11,2 (&#8722;50,9 a 28,6), <break/> p = 0,5830</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0,6 (&#8722;9,3 a 8,0), <break/> p = 0,8841</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o sabe</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">5</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" colspan="2" valign="middle">
                  <bold>IMC</bold>
                </td>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
                <td align="center" valign="middle"/>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Baixo <break/> (13,4 &#8804; IMC &#8804; 25,69)</td>
                <td align="center" valign="middle">1.724</td>
                <td align="center" valign="middle">&#8722;1,0 (&#8722;5,1 a 3,0), <break/> p = 0,6270</td>
                <td align="center" valign="middle">&#8722;5,9 (&#8722;14,0 a 2,2), <break/> p = 0,1543</td>
                <td align="center" valign="middle">&#8722;2,6 (&#8722;13,4 a 8,2), <break/> p = 0,6394</td>
                <td align="center" valign="middle">&#8722;0,6 (&#8722;3,2 a 2,1), <break/> p = 0,6778</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">M&#233;dio <break/> (25,7 &#8804; IMC &#8804; 30,59)</td>
                <td align="center" valign="middle">1.750</td>
                <td align="center" valign="middle">&#8722;0,2 (&#8722;2,1 a 1,7), <break/> p = 0,8438</td>
                <td align="center" valign="middle">&#8722;2,9 (&#8722;9,6 a 3,8), p = 0,3952</td>
                <td align="center" valign="middle">&#8722;0,5 (&#8722;9,6 a 8,5), <break/> p = 0,9080</td>
                <td align="center" valign="middle">1,9 (&#8722;0,6 a 4,3), <break/> p = 0,1384</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Alto <break/> (30,7 &#8804; IMC &#8804; 82,1)</td>
                <td align="center" valign="middle">1.753</td>
                <td align="center" valign="middle">&#8722;0,3 (&#8722;1,0 a 0,4), <break/> p = 0,4031</td>
                <td align="center" valign="middle">&#8722;6,5 (&#8722;12,8 a &#8722;0,1), <break/> p = 0,0457</td>
                <td align="center" valign="middle">&#8722;4,9 (&#8722;13,6 a 3,7), <break/> p = 0,2616</td>
                <td align="center" valign="middle">1,5 (&#8722;0,7 a 3,7), <break/> p = 0,1743</td>
              </tr>
              <tr>
                <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                  <bold>AVC</bold>
                </td>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                <td align="center" style="background-color:#C7DFEC" valign="middle"/>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Sim</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">167</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1,0 (&#8722;3,8 a 1,7), <break/> p = 0,4676</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;4,6 (&#8722;13,8 a 4,6), <break/> p = 0,3249</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;6,3 (&#8722;17,6 a 5,0), <break/> p = 0,2746</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1,1 (&#8722;5,5 a 3,3), <break/> p = 0,6228</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">5.056</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0,3 (&#8722;1,8 a 1,1), <break/> p = 0,6445</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;4,1 (&#8722;8,4 a 0,3), <break/> p = 0,0663</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1,2 (&#8722;7,0 a 4,6), <break/> p = 0,6889</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,3 (&#8722;0,2 a 2,8), <break/> p = 0,0862</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o sabe</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">4</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" colspan="7" valign="middle">
                  <bold>J&#225; fumou pelo menos 100 cigarros na vida</bold>
                </td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">Sim</td>
                <td align="center" valign="middle">2.296</td>
                <td align="center" valign="middle">&#8722;0,1 (&#8722;1,6 a 1,4), <break/> p = 0,8906</td>
                <td align="center" valign="middle">&#8722;4,8 (&#8722;10,1 a 0,6), <break/> p = 0,0805</td>
                <td align="center" valign="middle">1,0 (&#8722;5,4 a 7,5), <break/> p = 0,7546</td>
                <td align="center" valign="middle">1,8 (&#8722;0,1 a 3,7), <break/> p = 0,0675</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">N&#227;o</td>
                <td align="center" valign="middle">2.930</td>
                <td align="center" valign="middle">&#8722;1,1 (&#8722;3,5 a 1,3), <break/> p = 0,3891</td>
                <td align="center" valign="middle">&#8722;7,0 (&#8722;13,1 a &#8722;0,8), <break/> p = 0,0265</td>
                <td align="center" valign="middle">&#8722;6,0 (&#8722;15,1 a 3,1), <break/> p = 0,1957</td>
                <td align="center" valign="middle">&#8722;0,3 (&#8722;2,4 a 1,8), <break/> p = 0,7948</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">N&#227;o sabe</td>
                <td align="center" valign="middle">1</td>
                <td align="center" valign="middle">&#8212;</td>
                <td align="center" valign="middle">&#8212;</td>
                <td align="center" valign="middle">&#8212;</td>
                <td align="center" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" colspan="7" style="background-color:#C7DFEC" valign="middle">
                  <bold>Ingeriu pelo menos 12 doses de bebida alco&#243;lica no &#250;ltimo ano</bold>
                </td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Sim</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">3.434</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0,4 (&#8722;2,2 a 1,3), <break/> p = 0,6268</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;4,7 (&#8722;9,7 a 0,3), <break/> p = 0,0677</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1,4 (&#8722;7,9 a 5,0), <break/> p = 0,6600</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">0,9 (&#8722;0,9 a 2,7), <break/> p = 0,3292</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1.303</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0,5 (&#8722;3,2 a 2,1), <break/> p = 0,6935</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;5,5 (&#8722;12,8 a 1,8), <break/> p = 0,1398</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;4,9 (&#8722;15,9 a 6,1), <break/> p = 0,3797</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,8 (&#8722;0,4 a 4,0), <break/> p = 0,1138</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">N&#227;o sabe</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">2</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
              </tr>
              <tr>
                <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                <td align="left" style="background-color:#C7DFEC" valign="middle">Dados ausentes</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">488</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0,5 (&#8722;2,0 a 1,0), <break/> p = 0,5035</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;7,1 (&#8722;22,3 a 8,1), <break/> p = 0,3581</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;5,8 (&#8722;29,3 a 17,7), <break/> p = 0,6281</td>
                <td align="center" style="background-color:#C7DFEC" valign="middle">1,7 (&#8722;3,3 a 6,6), <break/> p = 0,5120</td>
              </tr>
              <tr>
                <td align="left" colspan="7" valign="middle">
                  <bold>MET (equivalentes metab&#243;licos)</bold>
                </td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">&lt; 4</td>
                <td align="center" valign="middle">1.355</td>
                <td align="center" valign="middle">&#8722;0,6 (&#8722;2,8 a 1,7), <break/> p = 0,6099</td>
                <td align="center" valign="middle">&#8722;6,7 (&#8722;12,9 a &#8722;0,4), p = 0,0362</td>
                <td align="center" valign="middle">&#8722;4,8 (&#8722;12,8 a 3,2), <break/> p = 0,2381</td>
                <td align="center" valign="middle">1,6 (&#8722;0,8 a 4,0), <break/> p = 0,1847</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">4-8</td>
                <td align="center" valign="middle">1.462</td>
                <td align="center" valign="middle">&#8722;0,5 (&#8722;1,5 a 0,4), <break/> p = 0,2511</td>
                <td align="center" valign="middle">&#8722;3,6 (&#8722;10,3 a 3,0), <break/> p = 0,2818</td>
                <td align="center" valign="middle">2,0 (&#8722;6,4 a 10,5), <break/> p = 0,6361</td>
                <td align="center" valign="middle">&#8722;0,1 (&#8722;2,4 a 2,2), <break/> p = 0,9365</td>
              </tr>
              <tr>
                <td align="left" valign="middle"/>
                <td align="left" valign="middle">&#8805;8</td>
                <td align="center" valign="middle">2.410</td>
                <td align="center" valign="middle">&#8722;0,0 (&#8722;3,1 a 3,1), <break/> p = 0,9958</td>
                <td align="center" valign="middle">&#8722;1,3 (&#8722;9,3 a 6,6), <break/> p = 0,7388</td>
                <td align="center" valign="middle">&#8722;0,7 (&#8722;11,9 a 10,5), <break/> p = 0,8991</td>
                <td align="center" valign="middle">1,8 (&#8722;0,8 a 4,4), <break/> p = 0,1730</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN4">
              <p>AVC: acidente vascular cerebral; DM2: diabetes melito tipo 2; IMC: &#237;ndice de massa corporal; MET: <italic>metabolic equivalent of task</italic> .</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>As vari&#225;veis de subgrupos analisadas inclu&#237;ram sexo, idade, ra&#231;a, presen&#231;a de hipertens&#227;o arterial, n&#237;veis elevados de colesterol, DM2, tercis de IMC, hist&#243;rico de AVC, tabagismo, consumo de &#225;lcool no &#250;ltimo ano e escore MET. O escore MET foi utilizado para avaliar a capacidade funcional: um escore &lt;4 reflete limita&#231;&#227;o funcional grave e est&#225; fortemente associado a maior risco cardiovascular; um escore entre 4-6 indica limita&#231;&#227;o moderada, geralmente manifestada como dispneia ou fadiga durante atividade f&#237;sica moderada (por exemplo, caminhar pequenas dist&#226;ncias ou realizar tarefas leves); um escore &gt;8 geralmente reflete baixo risco cardiovascular. O tamanho amostral (N) refere-se ao n&#250;mero de indiv&#237;duos em cada subgrupo. Para cada subgrupo, s&#227;o apresentados a diferen&#231;a na concentra&#231;&#227;o de quatro compostos qu&#237;micos entre indiv&#237;duos com DAC e o grupo controle, juntamente com o IC 95% e o valor p correspondente, indicando signific&#226;ncia estat&#237;stica.</p>
        <p>A an&#225;lise estratificada revelou que, na maioria dos subgrupos, a diferen&#231;a na concentra&#231;&#227;o de teofilina entre indiv&#237;duos com DAC e os controles n&#227;o foi estatisticamente significativa (p &gt; 0,05). Por exemplo, entre indiv&#237;duos sem hipertens&#227;o, a diferen&#231;a observada foi de &#8722;1,3 (IC 95%: &#8722;4,8 a 2,2), com valor de p = 0,4758, indicando aus&#234;ncia de associa&#231;&#227;o significativa. No geral, os n&#237;veis de teofilina n&#227;o diferiram de forma relevante entre os subgrupos. Em contraste, a paraxantina apresentou uma diferen&#231;a significativa e relativamente consistente em v&#225;rios subgrupos. Entre as mulheres, a diferen&#231;a foi de &#8722;7,4 (p = 0,0379), e entre os homens, &#8722;4,8 (p = 0,0538). Uma diferen&#231;a acentuada tamb&#233;m foi observada entre indiv&#237;duos brancos n&#227;o hisp&#226;nicos (&#8722;7,3; p = 0,0034), enquanto n&#227;o foram detectadas altera&#231;&#245;es significativas em outros grupos raciais. Entre indiv&#237;duos com hipertens&#227;o, a diferen&#231;a atingiu &#8722;9,7 (p = 0,0299) e, no grupo com IMC elevado, foi de &#8722;6,5 (p = 0,0457). Participantes sem hist&#243;rico de tabagismo apresentaram diferen&#231;a de &#8722;7,0 (p = 0,0265).</p>
        <p>Para participantes com escores MET &lt;4, a diferen&#231;a na concentra&#231;&#227;o de paraxantina foi de &#8722;6,7 (p = 0,0362). Isso indica que os n&#237;veis de paraxantina foram significativamente mais baixos na maioria dos subgrupos em compara&#231;&#227;o ao grupo controle, com diferen&#231;as mais marcantes observadas entre mulheres, brancos n&#227;o hisp&#226;nicos e indiv&#237;duos com condi&#231;&#245;es espec&#237;ficas de sa&#250;de, como hipertens&#227;o, aus&#234;ncia de hist&#243;rico de tabagismo, IMC elevado e baixa capacidade funcional (escore MET reduzido). Em contraste, as concentra&#231;&#245;es de teobromina n&#227;o apresentaram diferen&#231;as estatisticamente significativas em nenhum subgrupo (p &gt; 0,05), sugerindo apenas uma rela&#231;&#227;o fraca ou inconsistente com a DAC. A cafe&#237;na, no entanto, apresentou varia&#231;&#227;o significativa em alguns subgrupos: entre os homens, a diferen&#231;a foi de 2,2 (p = 0,0081), enquanto nenhuma diferen&#231;a significativa foi observada entre as mulheres (p = 0,7220); entre mexicanos-americanos, a diferen&#231;a atingiu 9,0 (p = 0,0006), sem achados significativos em outras categorias raciais. Al&#233;m disso, indiv&#237;duos sem DM2 apresentaram diferen&#231;a de 2,1 (p = 0,0165). Esses achados sugerem que concentra&#231;&#245;es elevadas de cafe&#237;na podem ter maior relev&#226;ncia em homens, mexicanos-americanos e pessoas sem DM2, embora esse padr&#227;o n&#227;o tenha sido consistente em todos os subgrupos.</p>
      </sec>
    </sec>
    <sec sec-type="discussion">
      <title>Discuss&#227;o</title>
      <p>Este estudo transversal de grande escala, com dura&#231;&#227;o de 6 anos, forneceu insights resumidos na Figura Central, que destaca os principais achados da an&#225;lise. Ela ilustra diferen&#231;as basais significativas entre os indiv&#237;duos do grupo com DAC e o grupo controle. Especificamente, os indiv&#237;duos com DAC eram geralmente mais velhos e apresentavam maior preval&#234;ncia de hipertens&#227;o, hipercolesterolemia, DM2, AVC, tabagismo e consumo de &#225;lcool.</p>
      <p>A an&#225;lise dos n&#237;veis urin&#225;rios de cafe&#237;na revelou uma associa&#231;&#227;o positiva com a incid&#234;ncia de DAC, particularmente entre a popula&#231;&#227;o mexicano-americana, onde a associa&#231;&#227;o foi mais pronunciada (OR 1,03; IC 95%: 1,03&#8211;1,05; p = 0,0081). Para cada aumento de 1 &#956;mol/L na concentra&#231;&#227;o urin&#225;ria de cafe&#237;na, o risco de DAC aumentava em 3%, com signific&#226;ncia estat&#237;stica (p &lt; 0,01). Em contraste, n&#227;o foram identificadas associa&#231;&#245;es significativas entre a DAC e os n&#237;veis urin&#225;rios de metab&#243;litos da cafe&#237;na, como teobromina e teofilina. As concentra&#231;&#245;es de teofilina e hipoxantina foram significativamente menores no grupo com DAC em compara&#231;&#227;o aos controles.</p>
      <p>As an&#225;lises por subgrupos revelaram diferen&#231;as significativas nas concentra&#231;&#245;es de hipoxantina em diversos subgrupos definidos por sexo, idade, ra&#231;a, status hipertensivo e tabagismo &#8212; particularmente entre mulheres, indiv&#237;duos com hipertens&#227;o e fumantes. No entanto, n&#227;o foram observadas diferen&#231;as significativas entre subgrupos nas concentra&#231;&#245;es de teobromina ou cafe&#237;na. Esses achados sugerem que a rela&#231;&#227;o entre cafe&#237;na urin&#225;ria e DAC pode ser modulada por ra&#231;a e outros fatores fisiol&#243;gicos, e que a hipoxantina, um metab&#243;lito da cafe&#237;na, pode estar associada &#224; sa&#250;de cardiovascular. Este estudo oferece insights valiosos para a pesquisa cl&#237;nica e b&#225;sica, apoiando a identifica&#231;&#227;o e preven&#231;&#227;o de fatores de risco para a DAC.</p>
      <p>Estudos anteriores relataram uma associa&#231;&#227;o positiva entre o consumo de caf&#233; e o risco de DAC (OR 1,35; IC 95% 1,05-1,73; p = 0,017), bem como um aumento na probabilidade de desenvolver hipertens&#227;o.<sup><xref ref-type="bibr" rid="B9">9</xref> , <xref ref-type="bibr" rid="B15">15</xref> </sup> O consumo moderado a excessivo de caf&#233; tem sido associado ao aumento da atividade inflamat&#243;ria, a qual desempenha um papel fundamental na patog&#234;nese da DAC.<sup><xref ref-type="bibr" rid="B16">16</xref></sup> O consumo excessivo de caf&#233;, ch&#225; e cafe&#237;na tamb&#233;m foi associado ao aumento da mortalidade por todas as causas e mortalidade cardiovascular entre indiv&#237;duos com doen&#231;as cardiovasculares pr&#233;-existentes.<sup><xref ref-type="bibr" rid="B17">17</xref></sup> Al&#233;m disso, o caf&#233; n&#227;o filtrado pode elevar os n&#237;veis s&#233;ricos de triglicer&#237;deos, colesterol e lipoprote&#237;na de baixa densidade (LDL).<sup><xref ref-type="bibr" rid="B18">18</xref> , <xref ref-type="bibr" rid="B19">19</xref> </sup></p>
      <p>Por outro lado, alguns estudos sugerem que o consumo de caf&#233; &#233; seguro e n&#227;o aumenta o risco de mortalidade. Os efeitos de diferentes m&#233;todos de preparo do caf&#233; sobre os desfechos cardiovasculares e a sobrevida parecem variar. Por exemplo, caf&#233; descafeinado, caf&#233; mo&#237;do e caf&#233; instant&#226;neo t&#234;m sido associados a uma redu&#231;&#227;o significativa na incid&#234;ncia e mortalidade por doen&#231;as cardiovasculares.<sup><xref ref-type="bibr" rid="B20">20</xref></sup> O caf&#233; mo&#237;do e o instant&#226;neo sem descafeina&#231;&#227;o tamb&#233;m foram associados a menor risco de arritmias card&#237;acas. Esses achados sugerem que a origem e o m&#233;todo de ingest&#227;o da cafe&#237;na podem influenciar os resultados da pesquisa.<sup><xref ref-type="bibr" rid="B21">21</xref></sup></p>
      <p>Nosso estudo utilizou os n&#237;veis urin&#225;rios de cafe&#237;na e seus metab&#243;litos como indicadores objetivos da ingest&#227;o real de caf&#233; e encontrou uma associa&#231;&#227;o positiva entre os n&#237;veis urin&#225;rios de cafe&#237;na e a incid&#234;ncia de DAC (doen&#231;a arterial coronariana) (OR 1,54; IC 95% 1,04-2,3; p = 0,0318), o que refor&#231;a a validade dessa abordagem. Al&#233;m disso, observamos uma associa&#231;&#227;o negativa entre os n&#237;veis urin&#225;rios de paraxantina e a incid&#234;ncia de DAC. Indiv&#237;duos que consumiam quantidades baixas (1-2 x&#237;caras/dia) ou altas (&gt;2 x&#237;caras/dia) de caf&#233; apresentaram risco reduzido de morte em compara&#231;&#227;o aos que n&#227;o bebiam caf&#233;, com o maior benef&#237;cio observado entre os grandes consumidores.</p>
      <p>V&#225;rios mecanismos podem ajudar a explicar esses achados. Em primeiro lugar, o caf&#233; &#233; uma bebida complexa que cont&#233;m mais de 100 compostos bioativos, sendo a cafe&#237;na o mais proeminente.<sup><xref ref-type="bibr" rid="B22">22</xref> , <xref ref-type="bibr" rid="B23">23</xref> </sup> A cafe&#237;na estimula agudamente o sistema nervoso simp&#225;tico ao inibir a fosfodiesterase, aumentar os n&#237;veis intracelulares de c&#225;lcio e promover a libera&#231;&#227;o de noradrenalina e adrenalina. Esses efeitos podem melhorar a reserva cardiovascular e manter o fluxo sangu&#237;neo coronariano, potencialmente reduzindo o risco de DAC. Em segundo lugar, a a&#231;&#227;o antagonista da cafe&#237;na sobre os receptores de adenosina pode prejudicar o aumento esperado da perfus&#227;o mioc&#225;rdica durante a atividade f&#237;sica.<sup><xref ref-type="bibr" rid="B24">24</xref></sup> Em terceiro lugar, a ingest&#227;o de cafe&#237;na pode ajudar a regular fatores de risco cardiovascular, particularmente entre n&#227;o fumantes. Al&#233;m disso, o consumo de caf&#233; tem sido associado a um poss&#237;vel efeito protetor contra a calcifica&#231;&#227;o das art&#233;rias coron&#225;rias.<sup><xref ref-type="bibr" rid="B25">25</xref></sup> Em quarto lugar, as propriedades antioxidantes da cafe&#237;na podem proteger as c&#233;lulas endoteliais contra danos, reduzindo assim o risco de DAC. Por fim, compostos fen&#243;licos presentes no caf&#233; &#8212; especialmente os &#225;cidos hidroxicin&#226;micos &#8212; podem exercer efeitos cardiovasculares ben&#233;ficos por meio de a&#231;&#245;es anti-inflamat&#243;rias e antioxidantes. Em contraste, o consumo de caf&#233; n&#227;o filtrado a curto prazo pode aumentar os n&#237;veis s&#233;ricos de triglicer&#237;deos, colesterol e LDL.<sup><xref ref-type="bibr" rid="B18">18</xref></sup></p>
      <p>Neste estudo transversal de grande escala, identificamos uma associa&#231;&#227;o negativa entre os n&#237;veis urin&#225;rios de cafe&#237;na e a incid&#234;ncia de DAC entre mexicano-americanos, um padr&#227;o n&#227;o observado em outros grupos &#233;tnicos. Essa disparidade pode refletir diferen&#231;as na preval&#234;ncia de DAC entre diferentes grupos raciais.<sup><xref ref-type="bibr" rid="B26">26</xref></sup> Al&#233;m disso, a variabilidade gen&#233;tica pode influenciar as respostas individuais &#224; cafe&#237;na. Por exemplo, um estudo de Happonen et al.<sup><xref ref-type="bibr" rid="B27">27</xref></sup> sugeriu que polimorfismos gen&#233;ticos espec&#237;ficos &#8212; como variantes no gene <italic>COMT</italic> &#8212; podem modular os efeitos da cafe&#237;na nos desfechos cardiovasculares. Pesquisas anteriores<sup><xref ref-type="bibr" rid="B28">28</xref></sup> tamb&#233;m indicam que n&#237;veis elevados de cafe&#237;na plasm&#225;tica em homens est&#227;o associados &#224; redu&#231;&#227;o do fluxo sangu&#237;neo mioc&#225;rdico induzido por estresse e da reserva de fluxo, enquanto altera&#231;&#245;es hemodin&#226;micas semelhantes n&#227;o foram observadas em mulheres. No entanto, nossos achados n&#227;o revelaram diferen&#231;as relacionadas ao sexo. Essas observa&#231;&#245;es ressaltam a necessidade de novos ensaios cl&#237;nicos randomizados, de alta qualidade e grande escala, que incorporem dados gen&#233;ticos para entender melhor como os polimorfismos g&#234;nicos podem influenciar a rela&#231;&#227;o entre cafe&#237;na e sa&#250;de cardiovascular.</p>
      <p>A an&#225;lise de regress&#227;o mostrou que as concentra&#231;&#245;es de teofilina e hipoxantina foram significativamente menores no grupo com DAC em compara&#231;&#227;o ao grupo controle. Essa diferen&#231;a permaneceu estatisticamente significativa ap&#243;s o ajuste, sugerindo uma poss&#237;vel associa&#231;&#227;o entre esses compostos e a DAC. N&#227;o foram observadas diferen&#231;as significativas nas concentra&#231;&#245;es de teobromina e cafe&#237;na entre os grupos, indicando que esses compostos podem n&#227;o estar diretamente relacionados &#224; DAC.</p>
      <p>A teofilina &#233; um metab&#243;lito secund&#225;rio da cafe&#237;na, e seus n&#237;veis reduzidos podem refletir disfun&#231;&#227;o metab&#243;lica. Por exemplo, indiv&#237;duos com DAC podem apresentar fun&#231;&#227;o hep&#225;tica reduzida ou menor capacidade metab&#243;lica geral, resultando em menor produ&#231;&#227;o de teofilina. Al&#233;m disso, inflama&#231;&#227;o sist&#234;mica ou estresse oxidativo &#8212; comuns em condi&#231;&#245;es cardiovasculares &#8212; podem interferir nas vias metab&#243;licas da teofilina. O aumento nos n&#237;veis de teofilina ap&#243;s o ajuste sugere que fatores de confus&#227;o, como idade, sexo e IMC, podem ter mascarado uma associa&#231;&#227;o real nos modelos n&#227;o ajustados. A redu&#231;&#227;o acentuada da concentra&#231;&#227;o de teofilina destaca seu potencial valor diagn&#243;stico. Estudos futuros poderiam incorporar dados gen&#244;micos, como variantes do gene <italic>CYP1A2</italic> , para avaliar se altera&#231;&#245;es nos n&#237;veis de teofilina podem prever o risco de DAC ou servir como marcadores para monitoramento terap&#234;utico.</p>
      <p>Em todos os modelos, os n&#237;veis de xantina foram consistentemente e significativamente mais baixos no grupo com DAC (varia&#231;&#227;o da diferen&#231;a: &#8722;4,1 a &#8722;5,1; p &lt; 0,05), tanto antes quanto depois do ajuste, indicando uma associa&#231;&#227;o forte e possivelmente independente com a DAC, com influ&#234;ncia limitada de fatores de confus&#227;o. Esse achado apoia seu uso potencial como marcador metab&#243;lico isolado para a DAC. As concentra&#231;&#245;es de teobromina e cafe&#237;na n&#227;o diferiram significativamente entre os grupos, sugerindo que esses compostos podem n&#227;o estar diretamente envolvidos nos processos metab&#243;licos cardiovasculares ou que seus efeitos possam estar mascarados por fatores diet&#233;ticos e de estilo de vida.</p>
      <p>Em pesquisas futuras, a paraxantina poderia ser inclu&#237;da em pain&#233;is de biomarcadores para rastreamento precoce de doen&#231;as card&#237;acas. Abordagens diagn&#243;sticas personalizadas podem ser desenvolvidas com a integra&#231;&#227;o de dados gen&#244;micos, criando estrat&#233;gias de preven&#231;&#227;o e manejo direcionadas, que considerem sexo, ra&#231;a e perfis metab&#243;licos, com base nos pap&#233;is regulat&#243;rios da teofilina e da hipoxantina.</p>
      <p>A an&#225;lise de subgrupos revelou que a paraxantina foi o &#250;nico composto significativamente reduzido na maioria dos grupos, especialmente entre mulheres, indiv&#237;duos com hipertens&#227;o, aqueles com IMC elevado e com escores de MET baixos. Esses achados sugerem que a paraxantina pode atuar como um biomarcador-chave potencial para doen&#231;as card&#237;acas. Como principal metab&#243;lito da cafe&#237;na, a paraxantina &#233; conhecida por exercer efeitos anti-inflamat&#243;rios e regular o metabolismo lip&#237;dico. Sua redu&#231;&#227;o acentuada em indiv&#237;duos com DAC pode refletir n&#237;veis elevados de marcadores inflamat&#243;rios ou vias metab&#243;licas comprometidas, frequentemente associadas a condi&#231;&#245;es cardiovasculares.</p>
      <p>Em indiv&#237;duos hipertensos e com IMC elevado, n&#237;veis mais altos de estresse metab&#243;lico podem contribuir para a redu&#231;&#227;o da paraxantina, provavelmente associada a dist&#250;rbios no metabolismo lip&#237;dico, disfun&#231;&#227;o hep&#225;tica e inflama&#231;&#227;o sist&#234;mica. A redu&#231;&#227;o significativa da paraxantina em mulheres, pacientes hipertensos e em indiv&#237;duos com limita&#231;&#245;es funcionais graves pode indicar respostas metab&#243;licas espec&#237;ficas por sexo e o efeito cumulativo da hipertens&#227;o sobre o perfil metab&#243;lico na DAC. A signific&#226;ncia estat&#237;stica observada entre brancos n&#227;o hisp&#226;nicos pode refletir diferen&#231;as inter&#233;tnicas na atividade de enzimas metab&#243;licas, padr&#245;es de estilo de vida e suscetibilidade &#224; doen&#231;a.</p>
      <p>Pesquisas futuras dever&#227;o focar em estudos de coorte em larga escala para validar ainda mais a xantina como biomarcador confi&#225;vel para DAC. N&#227;o foram observadas diferen&#231;as estatisticamente significativas nas concentra&#231;&#245;es de teofilina e teobromina, indicando associa&#231;&#227;o mais fraca com DAC. A teofilina, um metab&#243;lito intermedi&#225;rio da cafe&#237;na, &#233; fortemente influenciada por atividade enzim&#225;tica hep&#225;tica e gen&#233;tica (especialmente polimorfismos no gene <italic>CYP1A2</italic> ). Como essas vias metab&#243;licas n&#227;o est&#227;o diretamente envolvidas na fisiopatologia cardiovascular, altera&#231;&#245;es em suas concentra&#231;&#245;es podem n&#227;o ser indicadoras sens&#237;veis de DAC. Al&#233;m disso, a meia-vida mais longa da teofilina pode atenuar os efeitos de flutua&#231;&#245;es metab&#243;licas transit&#243;rias.</p>
      <p>A teobromina, um alcaloide derivado do cacau e metab&#243;lito secund&#225;rio da cafe&#237;na, possui baixa efici&#234;ncia metab&#243;lica e n&#237;veis relativamente est&#225;veis no organismo, o que a torna menos propensa a refletir altera&#231;&#245;es metab&#243;licas cardiovasculares. As diferen&#231;as nas concentra&#231;&#245;es de cafe&#237;na foram significativas apenas em subgrupos espec&#237;ficos, sem tend&#234;ncia consistente, sugerindo associa&#231;&#227;o fraca ou indireta com a DAC ou influ&#234;ncia de fatores externos. Os n&#237;veis elevados de cafe&#237;na em homens podem ser explicados por maior consumo (p.ex., mais ingest&#227;o de caf&#233;) e taxas metab&#243;licas mais r&#225;pidas, enquanto em mulheres o estrog&#234;nio pode modular o metabolismo da cafe&#237;na, reduzindo as diferen&#231;as observadas.</p>
      <p>Os n&#237;veis significativamente mais altos em mexicanos americanos podem ser atribu&#237;dos a polimorfismos populacionais espec&#237;ficos nos genes que metabolizam a cafe&#237;na, bem como a h&#225;bitos culturais e alimentares. Al&#233;m disso, os n&#237;veis elevados de cafe&#237;na em indiv&#237;duos n&#227;o diab&#233;ticos sugerem que o DM2 pode prejudicar a depura&#231;&#227;o da cafe&#237;na por meio de altera&#231;&#245;es no metabolismo. Em conjunto, a redu&#231;&#227;o observada nos n&#237;veis de xantina pode representar um valioso marcador metab&#243;lico para DAC, apoiando seu uso em triagem precoce e interven&#231;&#245;es cl&#237;nicas. A identifica&#231;&#227;o de padr&#245;es espec&#237;ficos por subgrupo tamb&#233;m pode facilitar o desenvolvimento de estrat&#233;gias personalizadas de preven&#231;&#227;o e manejo da doen&#231;a.</p>
      <p>Nosso estudo apresenta diversos pontos fortes. Primeiramente, utiliza dados do NHANES para realizar uma an&#225;lise com grande amostra, minimizando de forma eficaz os vieses associados a tamanhos amostrais pequenos. Em segundo lugar, os dados foram estratificados por sexo, idade e ra&#231;a, e confundidores multivari&#225;veis como hipertens&#227;o e IMC foram considerados na an&#225;lise de regress&#227;o. Essa abordagem permitiu uma investiga&#231;&#227;o mais precisa da rela&#231;&#227;o entre a cafe&#237;na urin&#225;ria e seus metab&#243;litos com a incid&#234;ncia de DAC. Em terceiro lugar, em vez de depender de question&#225;rios autorrelatados sobre o consumo de cafe&#237;na, utilizamos as concentra&#231;&#245;es urin&#225;rias de cafe&#237;na e seus metab&#243;litos como vari&#225;veis de exposi&#231;&#227;o, evitando assim vieses de mem&#243;ria, erros de classifica&#231;&#227;o e variabilidade na origem alimentar. Em quarto lugar, ao construir m&#250;ltiplos modelos e incorporar uma gama de covari&#225;veis, conseguimos gerar resultados mais robustos e confi&#225;veis sobre a associa&#231;&#227;o entre a cafe&#237;na, seus metab&#243;litos e a DAC.</p>
      <p>No entanto, este estudo possui algumas limita&#231;&#245;es. Primeiramente, por ser um estudo transversal, n&#227;o &#233; poss&#237;vel estabelecer uma rela&#231;&#227;o causal entre os metab&#243;litos da cafe&#237;na e a DAC. Em segundo lugar, os participantes eram majoritariamente dos Estados Unidos, o que pode limitar a generaliza&#231;&#227;o dos achados para outras popula&#231;&#245;es. Terceiro, devido &#224; estrat&#233;gia de estratifica&#231;&#227;o do NHANES e &#224; preval&#234;ncia relativamente baixa de DAC, o n&#250;mero de casos no grupo com DAC foi limitado, podendo introduzir vi&#233;s nos resultados. Portanto, estudos longitudinais futuros e investiga&#231;&#245;es multic&#234;ntricas e multirregionais s&#227;o necess&#225;rios para confirmar esses achados e elucidar melhor a rela&#231;&#227;o entre a cafe&#237;na, seus metab&#243;litos e a DAC.</p>
    </sec>
    <sec sec-type="conclusions">
      <title>Conclus&#227;o</title>
      <p>Este estudo encontrou uma associa&#231;&#227;o inversa entre os n&#237;veis urin&#225;rios de paraxantina e o risco de DAC. Em contraste, os n&#237;veis urin&#225;rios de cafe&#237;na mostraram associa&#231;&#227;o positiva com DAC entre mexicanos americanos, enquanto nenhuma associa&#231;&#227;o significativa foi observada em outros grupos &#233;tnicos. De modo geral, concentra&#231;&#245;es urin&#225;rias mais elevadas de cafe&#237;na estiveram associadas a maior incid&#234;ncia de DAC, embora essa tend&#234;ncia n&#227;o tenha sido evidente nas an&#225;lises estratificadas por sexo. Esses achados podem contribuir para a predi&#231;&#227;o cl&#237;nica e o diagn&#243;stico, mas s&#227;o necess&#225;rios mais estudos prospectivos em larga escala para confirmar esses resultados.</p>
    </sec>
    <sec sec-type="data-availability" specific-use="data-in-article">
      <label>Disponibilidade de Dados</label>
      <p>Os conte&#250;dos subjacentes ao texto da pesquisa est&#227;o contidos no manuscrito.</p>
    </sec>
    <sec sec-type="supplementary-material">
      <title>Material Suplementar</title>
      <supplementary-material id="suppl1">
        <label>*Material suplementar</label>
        <p>Para informa&#231;&#227;o adicional, por favor, <media mimetype="application" mime-subtype="pdf" xlink:href="https://minio.scielo.br/documentstore/1678-4170/7k3zrFh4x78yWB4NC57xFDh/1cf3184cd55244a29b59a49c9745a7dcb31108f5.pdf">clique aqui</media> .</p>
      </supplementary-material>
    </sec>
  </body>
  <back>
    <fn-group>
      <fn fn-type="financial-disclosure" id="fn5">
        <label>Fontes de financiamento</label>
        <p>O presente estudo foi financiado por The Shenzhen Science and Technology Innovation Foundation (No. JCYJ20180228162359914) e Guangdong-Shenzhen Joint Fund Youth Project (No. 2021A1515111110).</p>
      </fn>
      <fn fn-type="other" id="fn6">
        <label>Vincula&#231;&#227;o acad&#234;mica</label>
        <p>N&#227;o h&#225; vincula&#231;&#227;o deste estudo a programas de p&#243;s-gradua&#231;&#227;o</p>
      </fn>
      <fn fn-type="other" id="fn7">
        <label>Aprova&#231;&#227;o &#201;tica e Consentimento Informado</label>
        <p>Este artigo n&#227;o cont&#233;m estudos com humanos ou animais realizados por nenhum dos autores.</p>
      </fn>
      <fn fn-type="other" id="fn8">
        <label>Uso de Intelig&#234;ncia Artificial</label>
        <p>Os autores n&#227;o utilizaram ferramentas de intelig&#234;ncia artificial no desenvolvimento deste trabalho.</p>
      </fn>
    </fn-group>
    <ack>
      <title>Agradecimentos</title>
      <p>Agradecemos ao programa NHANES por fornecer os dados publicamente dispon&#237;veis.</p>
    </ack>
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          <pub-id pub-id-type="doi">10.2967/jnumed.121.261970</pub-id>
        </element-citation>
        <mixed-citation>28 Lassen ML, Byrne C, Sheykhzade M, Wissenberg M, Hurry PK, Schmedes AV, et al. Sex Differences and Caffeine Impact in Adenosine-Induced Hyperemia. J Nucl Med. 2022;63(3):431-7. doi: 10.2967/jnumed.121.261970.</mixed-citation>
      </ref>
    </ref-list>
  </back>
  <sub-article article-type="translation" id="S1" xml:lang="en">
    <front-stub>
      <article-id pub-id-type="doi">10.36660/abc.20240425i</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Original Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Study on Urinary Caffeine and Caffeine Metabolite Levels in American Adults with Coronary Heart Disease: A Cross-Sectional NHANES Study (2009-2014)</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0009-0005-0840-4821</contrib-id>
          <name>
            <surname>Li</surname>
            <given-names>Qianqian</given-names>
          </name>
          <role>Conception and design of the research</role>
          <role>Acquisition of data</role>
          <role>Analysis and interpretation of the data and Statistical analysis</role>
          <role>Writing of the manuscript</role>
          <xref ref-type="aff" rid="aff3">
            <sup>1</sup>
          </xref>
          <xref ref-type="aff" rid="aff4">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0009-0006-0616-4542</contrib-id>
          <name>
            <surname>Ke</surname>
            <given-names>Gan</given-names>
          </name>
          <role>Conception and design of the research</role>
          <role>Acquisition of data</role>
          <xref ref-type="aff" rid="aff3">
            <sup>1</sup>
          </xref>
          <xref ref-type="aff" rid="aff4">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0009-0005-9057-8870</contrib-id>
          <name>
            <surname>Liu</surname>
            <given-names>Mengdie</given-names>
          </name>
          <role>Conception and design of the research</role>
          <role>Writing of the manuscript</role>
          <xref ref-type="aff" rid="aff3">
            <sup>1</sup>
          </xref>
          <xref ref-type="aff" rid="aff4">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0001-9030-5673</contrib-id>
          <name>
            <surname>Chen</surname>
            <given-names>Yanjun</given-names>
          </name>
          <role>Obtaining financing and Critical revision of the manuscript for content</role>
          <xref ref-type="aff" rid="aff4">
            <sup>2</sup>
          </xref>
          <xref ref-type="corresp" rid="c2"/>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0009-0005-7727-299X</contrib-id>
          <name>
            <surname>Luo</surname>
            <given-names>Ye</given-names>
          </name>
          <xref ref-type="aff" rid="aff4">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0009-0007-7485-8631</contrib-id>
          <name>
            <surname>Qiu</surname>
            <given-names>Liangxian</given-names>
          </name>
          <xref ref-type="aff" rid="aff4">
            <sup>2</sup>
          </xref>
        </contrib>
        <aff id="aff3">
          <label>1</label>
          <addr-line>
            <named-content content-type="city">Shenzhen</named-content>
          </addr-line>
          <country country="CN">China</country>
          <institution content-type="original">Shenzhen University, Shenzhen &#8211; China</institution>
        </aff>
        <aff id="aff4">
          <label>2</label>
          <addr-line>
            <named-content content-type="city">Shenzhen</named-content>
          </addr-line>
          <country country="CN">China</country>
          <institution content-type="original">Peking University Shenzhen Hospital &#8211; Department of Cardiovascular Medicine, Shenzhen &#8211; China</institution>
        </aff>
      </contrib-group>
      <author-notes>
        <corresp id="c2"><label>Mailing Address:</label><bold>Yanjun Chen &#8226;</bold> Shenzhen University &#8211; BeiJing University Shenzhen Hospital, Futian District, Shenzhen, Guangdong Province, China Shenzhen <postal-code>518060</postal-code> &#8211; China E-mail: <email>chenyanjunhyd@163.com</email> </corresp>
        <fn fn-type="conflict">
          <label>Potential conflict of interest</label>
          <p>No potential conflict of interest relevant to this article was reported.</p>
        </fn>
        <fn fn-type="edited-by">
          <label>Editor responsible for the review:</label>
          <p>Gl&#225;ucia Maria Moraes de Oliveira</p>
        </fn>
      </author-notes>
      <abstract>
        <title>Abstract</title>
        <sec>
          <title>Background:</title>
          <p>In recent years, the impact of diet and lifestyle on coronary heart disease (CHD) has garnered significant attention. Caffeine, a common dietary component, and its metabolites may influence cardiovascular health.</p>
        </sec>
        <sec>
          <title>Objective:</title>
          <p>This study aimed to investigate the association between urinary levels of caffeine and its metabolites and the incidence of CHD as well as to assess how these associations vary across different population groups.</p>
        </sec>
        <sec>
          <title>Methods:</title>
          <p>Data from the NHANES database (2009-2014) were analyzed using multivariable logistic regression models and smooth curve fitting techniques. Participants were categorized into a control group (n = 5,005) and a CHD group (n = 222) based on CHD status. Urinary levels of caffeine and its metabolites were measured and recorded. Multivariable logistic regression was used to evaluate the association between urinary caffeine/metabolite levels and CHD incidence, while smooth curve fitting was employed to explore potential nonlinear relationships. A significance level of 5% was used to determine statistical significance.</p>
        </sec>
        <sec>
          <title>Results:</title>
          <p>Higher urinary paraxanthine levels were associated with a lower risk of CHD. In contrast, elevated urinary caffeine levels were positively associated with CHD incidence among Mexican Americans, an association not observed in other racial/ethnic groups.</p>
        </sec>
        <sec>
          <title>Conclusion:</title>
          <p>Lower urinary paraxanthine levels may reflect a reduced risk of CHD, while higher urinary caffeine levels could indicate an increased CHD risk in specific populations.</p>
        </sec>
      </abstract>
      <abstract abstract-type="graphical">
        <p>
          <fig id="f6">
            <label>Central Illustration:</label>
            <caption>
              <title>Study on Urinary Caffeine and Caffeine Metabolite Levels in American Adults with Coronary Heart Disease: A Cross-Sectional NHANES Study (2009-2014)</title>
            </caption>
            <graphic xlink:href=""/>
            <attrib>CHD: coronary heart disease; T2DM: type 2 diabetes mellitus.</attrib>
          </fig>
        </p>
      </abstract>
      <kwd-group xml:lang="en">
        <title>Keywords:</title>
        <kwd>Caffeine</kwd>
        <kwd>Cardiovascular Disease</kwd>
        <kwd>Coffee Metabolites</kwd>
        <kwd>Race</kwd>
      </kwd-group>
      <funding-group>
        <award-group>
          <funding-source>Shenzhen Science and Technology Innovation Foundation</funding-source>
          <award-id>JCYJ20180228162359914</award-id>
        </award-group>
        <award-group>
          <funding-source>Guangdong-Shenzhen Joint Fund Youth</funding-source>
          <award-id>2021A1515111110</award-id>
        </award-group>
        <funding-statement>This study was partially funded by Shenzhen Science and Technology Innovation Foundation (No. JCYJ20180228162359914) and the Guangdong-Shenzhen Joint Fund Youth Project (No. 2021A1515111110).</funding-statement>
      </funding-group>
    </front-stub>
    <body>
      <sec sec-type="intro">
        <title>Introduction</title>
        <p>In recent years, coronary heart disease (CHD) has become one of the leading causes of mortality, accounting for over 370,000 deaths annually.<sup><xref ref-type="bibr" rid="B1">1</xref></sup>In addition to traditional risk factors such as smoking, hyperlipidemia, hypertension, type 2 diabetes mellitus (T2DM), and obesity, emerging factors have also been identified, including systemic inflammation, gestational diabetes, preeclampsia, and early or surgical menopause.</p>
        <p>Dietary modifications have been shown to reduce the incidence of CHD.<sup><xref ref-type="bibr" rid="B2">2</xref></sup>Natural pharmacological compounds &#8212; particularly caffeine &#8212; are often employed as complementary therapies for cardiovascular diseases.<sup><xref ref-type="bibr" rid="B3">3</xref></sup>Coffee, the most widely consumed beverage worldwide, contains caffeine (1,3,7-trimethylxanthine), which is primarily ingested through foods and beverages.<sup><xref ref-type="bibr" rid="B4">4</xref> , <xref ref-type="bibr" rid="B5">5</xref> </sup>Although caffeine may cause a transient increase in blood pressure among nonhabitual consumers, long-term coffee intake has been associated with a reduced risk of arrhythmias and heart failure, improved insulin sensitivity, and a lower risk of T2DM.</p>
        <p>Several studies have reported an inverse relationship between coffee consumption and all-cause mortality. Habitual coffee drinking is associated with reduced risks of cardiovascular diseases and adverse cardiovascular outcomes, including CHD, congestive heart failure, and stroke. Long-term consumption has also been linked to lower risks of T2DM, depression, obesity, and certain cancers.<sup><xref ref-type="bibr" rid="B6">6</xref> , <xref ref-type="bibr" rid="B7">7</xref> </sup></p>
        <p>In particular, elevated urinary levels of caffeine and theophylline have been found to be negatively correlated with cardiovascular diseases,<sup><xref ref-type="bibr" rid="B8">8</xref></sup>with the association being more pronounced in women.<sup><xref ref-type="bibr" rid="B9">9</xref></sup>However, most current evidence is based on self-reported coffee consumption, which is subject to variation due to differences in brand, origin, and coffee type &#8212; all of which influence caffeine content. Few studies have examined the relationship between caffeine metabolites and cardiovascular disease, and many of those fail to account for variability introduced by coffee type, origin, and production processes. Additionally, potential inaccuracies in self-reported data may affect the reliability of findings.</p>
        <p>A reliable indicator of coffee intake is the concentration of caffeine and its metabolites excreted in urine. However, individual differences in caffeine metabolism can result in variability in circulating levels of caffeine and its metabolites. To better understand the association between urinary concentrations of caffeine and its metabolites and the presence of CHD, we conducted a cross-sectional analysis using data from the 2009-2014 National Health and Nutrition Examination Survey (NHANES). This study aimed to explore potential relationships between urinary biomarkers of caffeine exposure and CHD incidence.</p>
      </sec>
      <sec sec-type="methods">
        <title>Methods</title>
        <sec>
          <title>Study population</title>
          <p>NHANES is a cross-sectional nutritional survey conducted in the United States using a multistage, stratified probability sampling method. Approval for data collection and dissemination was granted by the National Center for Health Statistics.<sup><xref ref-type="bibr" rid="B10">10</xref></sup>We included data from adults aged 20 years and over who participated in NHANES between 2009 and 2014.<sup><xref ref-type="bibr" rid="B11">11</xref></sup>During and after data collection, we did not have access to any personally identifiable information.</p>
          <p>A total of 30,468 participants were initially considered. After applying exclusion criteria, the final analysis included 5,227 participants. These criteria excluded individuals under the age of 20 (n = 13,261), individuals with incomplete data on CHD (n = 67) and individuals with missing data on caffeine and its metabolites (n = 11,913). After applying these exclusion criteria, 5,227 participants were included in the final analysis ( <xref ref-type="fig" rid="f4">Figure 1</xref> ).</p>
          <fig id="f4">
            <label>Figure 1</label>
            <caption>
              <title>Flowchart of participant selection process. CHD: coronary heart disease; NHANES: National Health and Nutrition Examination Survey.</title>
            </caption>
            <graphic xlink:href=""/>
          </fig>
        </sec>
        <sec>
          <title>Exposure factors</title>
          <p>Theobromine (3,7-dimethylxanthine), theophylline (1,3-dimethylxanthine), and paraxanthine (1,7-dimethylxanthine) are the main human caffeine metabolites.<sup><xref ref-type="bibr" rid="B12">12</xref></sup>In this study, urinary concentrations of caffeine and its metabolites were used as exposure variables. Urine samples were collected between 10:00 a.m. and 12:00 p.m. after a 9-hour overnight fast. Samples were received, processed, and stored before being shipped to the Division of Laboratory Sciences at the National Center for Environmental Health, Centers for Disease Control and Prevention, in Atlanta, Georgia, for analysis.</p>
          <p>High-performance liquid chromatography-electrospray ionization-tandem quadrupole mass spectrometry was used in combination with stable isotope-labeled internal standards to quantify caffeine and its metabolites in urine.<sup><xref ref-type="bibr" rid="B13">13</xref></sup>Data were then reviewed for quality; uncertain or incomplete values were returned to the laboratory for verification.</p>
        </sec>
        <sec>
          <title>Outcome variable</title>
          <p>The diagnosis of CAD was based on clinical records and imaging results, such as coronary angiography. Data were collected through computer-assisted personal interviews (CAPI) conducted by trained interviewers. The questionnaire and methodology are available on the NHANES website.</p>
        </sec>
        <sec>
          <title>Covariates</title>
          <p>The following covariates were included to adjust for potential confounders in the relationship between caffeine/metabolite levels and CHD: sex, age, race/ethnicity, history of hypertension, hypercholesterolemia, T2DM, stroke, and smoking (defined as having smoked at least 100 cigarettes in a lifetime). Additional variables included alcohol consumption (defined as at least 12 alcoholic drinks per year), physical activity (measured in metabolic equivalents of task [METs]), and body mass index (BMI, kg/m<sup><xref ref-type="bibr" rid="B2">2</xref></sup>).<sup><xref ref-type="bibr" rid="B11">11</xref></sup>BMI was calculated as weight (kg) divided by height squared (m<sup><xref ref-type="bibr" rid="B2">2</xref></sup>). Anthropometric measurements were obtained by trained health technicians at mobile examination centers, while other covariates were collected via the CAPI system.</p>
        </sec>
        <sec>
          <title>Statistical analysis</title>
          <p>Statistical analyses were performed using R software and EmpowerStats.<sup><xref ref-type="bibr" rid="B14">14</xref></sup>A two-sided p-value &lt; 0.05 was considered statistically significant. Continuous variables with missing data were excluded from the analysis, while missing categorical variables were treated as a separate category.</p>
          <p>The normality of continuous variables was assessed using the Kolmogorov-Smirnov test, supported by histogram visualization. If data followed a normal distribution, results were reported as mean &#177; SD, and independent-samples <italic>t</italic> -tests were used for group comparisons. For data not normally distributed, results were expressed as median and interquartile range (Q1-Q3), and group comparisons were performed using the Mann-Whitney <italic>U</italic> test. As detailed in Appendix 1, continuous variables in this study did not conform to a normal distribution.</p>
          <p>Categorical variables were reported as absolute numbers (n) and percentages (%), and group differences were assessed using the chi-square test. When expected frequencies were &lt;10, Fisher's exact test was applied.</p>
          <p>Multivariable logistic regression analysis was used to examine the association between urinary levels of caffeine and its metabolites and the presence of CHD. For non-normally distributed continuous variables, data were divided into quartiles (Q1-Q4). Q1 represented the lowest 25% of values and was designated as the reference group. Q2, Q3, and Q4 represented progressively higher levels, enabling a clearer interpretation of trends across the distribution spectrum. Notably, Q4 referred to the highest 25% of data and was not part of a quintile division.</p>
          <p>By grouping data into quartiles (Q1-Q4), we were able to clearly assess trends across the distribution of the variable of interest. Q1, representing the lowest 25% of values, served as the reference group and provided a baseline for comparison with the higher quartiles (Q2, Q3, and Q4). This approach allowed for a more detailed evaluation of how the variable behaves across progressively increasing levels. Q4, which represents the top 25% of data, highlighted the characteristics of the highest exposure group and its distinctions from the others. This method enhances the clarity of observed trends and patterns in the dataset.</p>
          <p>We selected Q1 as the reference group because it represents the lowest exposure level, often associated with the lowest risk, making it suitable as a control group. The other quartiles (Q2-Q4) reflect increasing levels of exposure, which allows for a structured comparison across exposure gradients and improves the interpretability of differences between groups.</p>
          <p>In this study, we constructed three models: model 1 was unadjusted; model 2 was adjusted for sex, age, and race/ethnicity; model 3 was further adjusted for sex, age, race/ethnicity, height, history of hypertension, hypercholesterolemia, T2DM, and stroke, as well as smoking history (defined as smoking at least 100 cigarettes in a lifetime), alcohol consumption (&#8805;12 alcoholic drinks/year), and BMI (kg/m<sup><xref ref-type="bibr" rid="B2">2</xref></sup>).</p>
          <p>These models were used to explore the association between urinary levels of caffeine and its metabolites and CHD while accounting for potential confounders. In addition, smooth curve fitting was applied to examine potential nonlinear relationships between caffeine/metabolite levels and CHD after adjustment. Subgroup analyses were also conducted to further explore these associations within specific population strata and to identify potential effect modifiers.</p>
        </sec>
        <sec>
          <title>Ethical approval</title>
          <p>This study was based on publicly available data from the NHANES, which is de-identified and accessible through the official NHANES website. Therefore, ethical approval was not required.</p>
        </sec>
      </sec>
      <sec sec-type="results">
        <title>Results</title>
        <sec>
          <title>Basic characteristics of the study population.</title>
          <p>The normality test confirmed that the continuous variables did not follow a normal distribution (see Appendix 1). Therefore, non-normally distributed continuous variables are presented as medians and interquartile ranges (IQRs), and group comparisons were conducted using the Mann-Whitney U test. Categorical variables are expressed as frequencies and percentages (n, %) and were compared between groups using the chi-square test or Fisher's exact test when expected frequencies were &lt;10. A p-value &lt; 0.05 was considered statistically significant.</p>
          <p>Participants in the CHD group were significantly older (median age: 72 [IQR: 63-80] years) than those in the control group (median age: 48 [IQR: 34-62] years; p &lt; 0.001). The CHD group also had higher prevalences of hypertension, hypercholesterolemia, T2DM, and stroke as well as a greater history of smoking and alcohol consumption (all p &lt; 0.001). Additionally, significant differences in ethnic distribution were observed between groups (p = 0.001).</p>
          <p>Of the urinary metabolites analyzed, only paraxanthine levels differed significantly between groups (p = 0.018) ( <xref ref-type="table" rid="t6">Table 1</xref> ).</p>
          <table-wrap id="t6">
            <label>Table 1</label>
            <caption>
              <title>Baseline characteristics and urinary levels of caffeine and its metabolites among study participants</title>
            </caption>
            <table frame="hsides" rules="groups">
              <colgroup width="14%">
                <col width="1%"/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
              </colgroup>
              <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
                <tr style="background-color:#76B4CF">
                  <th align="left" colspan="2" valign="middle">Variable</th>
                  <th align="center" valign="middle">CHD group <break/> (n = 222)</th>
                  <th align="center" valign="middle">Control <break/> group <break/> (n = 5,005)</th>
                  <th align="center" valign="middle">Standardized difference</th>
                  <th align="center" valign="middle">p-value</th>
                  <th align="center" valign="middle">Adjusted <break/> p-value <break/> (if applicable)*</th>
                </tr>
              </thead>
              <tbody style="border-bottom: thin solid; border-color: #000000">
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>Age (years)</bold>
                  </td>
                  <td align="center" valign="middle">72 (63 a 80)</td>
                  <td align="center" valign="middle">48 (34 a 62)</td>
                  <td align="center" valign="middle">1.5 (1.3 a 1.6)</td>
                  <td align="center" valign="middle">&lt;0.001</td>
                  <td align="center" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Sex</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.4 (0.3 a 0.6)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&lt;0.001</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Male</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">153 (68.9%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">2.390 (47.8%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Female</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">69 (31.1%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">2.615 (52.2%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>Race/Ethnicity</bold>
                  </td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle">0.5 (0.4 a 0.6)</td>
                  <td align="center" valign="middle">&lt;0.001</td>
                  <td align="center" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Mexican American</td>
                  <td align="center" valign="middle">17 (7.7%)</td>
                  <td align="center" valign="middle">700 (14.0%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Other Hispanic</td>
                  <td align="center" valign="middle">18 (8.1%)</td>
                  <td align="center" valign="middle">504 (10.1%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Non-Hispanic White</td>
                  <td align="center" valign="middle">146 (65.8%)</td>
                  <td align="center" valign="middle">2.111 (42.2%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Non-Hispanic Black</td>
                  <td align="center" valign="middle">26 (11.7%)</td>
                  <td align="center" valign="middle">1.074 (21.5%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Other/multi-racial</td>
                  <td align="center" valign="middle">15 (6.8%)</td>
                  <td align="center" valign="middle">616 (12.3%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Hypertension</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.0 (0.8 a 1.1)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&lt;0.001</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Yes</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">173 (77.9%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.735 (34.7%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">No</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">48 (21.6%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">3.262 (65.2%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Do not know</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1 (0.5%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">8 (0.2%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>High cholesterol</bold>
                  </td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle">1.0 (0.9 a 1.1)</td>
                  <td align="center" valign="middle">&lt;0.001</td>
                  <td align="center" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Yes</td>
                  <td align="center" valign="middle">163 (73.4%)</td>
                  <td align="center" valign="middle">1.552 (31.0%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">No</td>
                  <td align="center" valign="middle">56 (25.2%)</td>
                  <td align="center" valign="middle">2.887 (57.7%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Do not know</td>
                  <td align="center" valign="middle">3 (1.4%)</td>
                  <td align="center" valign="middle">31 (0.6%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Missing</td>
                  <td align="center" valign="middle">0 (0.0%)</td>
                  <td align="center" valign="middle">535 (10.7%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>T2DM</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.5 (0.4 a 0.6)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&lt;0.001</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Yes</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">65 (29.3%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">550 (11.0%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">No</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">147 (66.2%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">4.333 (86.6%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Borderline</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">10 (4.5%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">117 (2.3%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Do not know</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0 (0.0%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">5 (0.1%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>Stroke</bold>
                  </td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle">0.4 (0.3 a 0.5)</td>
                  <td align="center" valign="middle">&lt;0.001</td>
                  <td align="center" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Yes</td>
                  <td align="center" valign="middle">29 (13.1%)</td>
                  <td align="center" valign="middle">138 (2.8%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">No</td>
                  <td align="center" valign="middle">192 (86.5%)</td>
                  <td align="center" valign="middle">4.864 (97.2%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Do not know</td>
                  <td align="center" valign="middle">1 (0.5%)</td>
                  <td align="center" valign="middle">3 (0.1%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Smoked &#8805;100 cigarettes (lifetime)</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.4 (0.2 a 0.5)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&lt;0.001</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Yes</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">136 (61.3%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">2.160 (43.2%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">No</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">86 (38.7%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">2.844 (56.8%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Do not know</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0 (0.0%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1 (0.0%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>&#8805;12 alcoholic drinks/year</bold>
                  </td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle">0.2 (0.0 a 0.3)</td>
                  <td align="center" valign="middle">0.195</td>
                  <td align="center" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Yes</td>
                  <td align="center" valign="middle">156 (70.3%)</td>
                  <td align="center" valign="middle">3.278 (65.5%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">No</td>
                  <td align="center" valign="middle">54 (24.3%)</td>
                  <td align="center" valign="middle">1.249 (25.0%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Do not know</td>
                  <td align="center" valign="middle">0 (0.0%)</td>
                  <td align="center" valign="middle">2 (0.0%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Missing</td>
                  <td align="center" valign="middle">12 (5.4%)</td>
                  <td align="center" valign="middle">476 (9.5%)</td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Physical activity (MET)</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.4 (0.3 a 0.6)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&lt;0.001</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">&lt;4</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">91 (41.0%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.264 (25.3%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">4-8</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">70 (31.5%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.392 (27.8%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">&#8805;8</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">61 (27.5%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">2.349 (46.9%)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>BMI (kg/m<sup>2</sup>)</bold>
                  </td>
                  <td align="center" valign="middle">28.86 <break/> (25.80 a 32.98)</td>
                  <td align="center" valign="middle">28.00 <break/> (24.30 a 32.42)</td>
                  <td align="center" valign="middle">0.2 <break/> (0.0 a 0.3)</td>
                  <td align="center" valign="middle">0.023</td>
                  <td align="center" valign="middle">0.007</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Urinary theophylline (&#956;mol/L)</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.645 <break/> (0.625 a 3.538)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.88 <break/> (0.639 a 3.84)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.1 <break/> (&#8211;0.1 a 0.2)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.532</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.367</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>Urinary paraxanthine (&#956;mol/L)</bold>
                  </td>
                  <td align="center" valign="middle">16.6 <break/> (4.738 a 29.325)</td>
                  <td align="center" valign="middle">17.5 <break/> (5.72 a 37.4)</td>
                  <td align="center" valign="middle">0.2 <break/> (0.0 a 0.3)</td>
                  <td align="center" valign="middle">0.018</td>
                  <td align="center" valign="middle">0.098</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Urinary theobromine (&#956;mol/L)</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">13.5 <break/> (6.285 a 29.8)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">15.3 <break/> (6.36 a 34.0)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.1 <break/> (&#8211;0.1 a 0.2)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.367</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.289</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>Urinary caffeine (&#956;mol/L)</bold>
                  </td>
                  <td align="center" valign="middle">5.465 <break/> (1.533 a 12.2)</td>
                  <td align="center" valign="middle">4.23 <break/> (1.01 a 10.8)</td>
                  <td align="center" valign="middle">0.1 <break/> (&#8211;0.0 a 0.2)</td>
                  <td align="center" valign="middle">0.086</td>
                  <td align="center" valign="middle">0.045</td>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <fn id="TFN5">
                <p>CHD: coronary heart disease; BMI: body mass index; MET: metabolic equivalent of task; T2DM: type 2 diabetes mellitus.</p>
              </fn>
            </table-wrap-foot>
          </table-wrap>
        </sec>
        <sec>
          <title>Association between urinary caffeine levels and CHD</title>
          <p>The results of the association between urinary caffeine levels and CHD are presented in <xref ref-type="table" rid="t7">Table 2</xref> . In the unadjusted analysis, urinary caffeine levels as a continuous variable were not significantly associated with CHD (all p &gt; 0.05). When caffeine levels were categorized into quartiles, individuals in the highest quartile (Q4) exhibited a statistically significant increase in CHD risk (OR 1.54; 95% CI 1.04-2.30; p = 0.0318) compared to those in the lowest quartile (Q1). This indicates that participants in Q4 had 54% higher odds of CHD than those in Q1.</p>
          <table-wrap id="t7">
            <label>Table 2</label>
            <caption>
              <title>Association between urinary caffeine levels (&#956;mol/L) and CHD</title>
            </caption>
            <table frame="hsides" rules="groups">
              <colgroup width="20%">
                <col width="1%"/>
                <col/>
                <col/>
                <col/>
                <col/>
              </colgroup>
              <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
                <tr style="background-color:#76B4CF">
                  <th align="left" colspan="2" valign="middle">Variable</th>
                  <th align="center" valign="middle">Model 1, <break/> OR (95% CI), p-value</th>
                  <th align="center" valign="middle">Model 2, <break/> OR (95% CI), p-value</th>
                  <th align="center" valign="middle">Model 3, <break/> OR (95% CI), p-value</th>
                </tr>
              </thead>
              <tbody style="border-bottom: thin solid; border-color: #000000">
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>Caffeine (&#956;mol/L)</bold>
                  </td>
                  <td align="center" valign="middle">1.01 (1.00-1.02). 0.0859</td>
                  <td align="center" valign="middle">1.00 (0.99-1.01). 0.9476</td>
                  <td align="center" valign="middle">0.99 (0.98-1.01). 0.3973</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Caffeine quartiles</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Q1 (Reference)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Q2</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.37 (0.91-2.06). 0.1257</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.20 (0.78-1.85). 0.3998</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.13 (0.73-1.77). 0.5799</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Q3</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.42 (0.95-2.13). 0.0874</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.18 (0.77-1.81). 0.4479</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.01 (0.65-1.59). 0.9487</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Q4</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.54 (1.04-2.30). 0.0318</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.10 (0.72-1.68). 0.6571</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.94 (0.61-1.47). 0.8006</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>Sex</bold>
                  </td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Male</td>
                  <td align="center" valign="middle">1.00 (1.00-1.00). 0.009</td>
                  <td align="center" valign="middle">1.00 (1.00-1.00). 0.545</td>
                  <td align="center" valign="middle">1.00 (1.00-1.00). 0.804</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Female</td>
                  <td align="center" valign="middle">1.00 (1.00-1.00). 0.721</td>
                  <td align="center" valign="middle">1.00 (1.00-1.00). 0.282</td>
                  <td align="center" valign="middle">1.00 (1.00-1.00). 0.155</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Race/ethnicity</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Mexican American</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.03 (1.01-1.05). 0.0081</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.03 (1.00-1.05). 0.0700</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.02 (0.98-1.06). 0.2327</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Other Hispanic</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.03 (0.99-1.07). 0.1409</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.02 (0.97-1.06). 0.4538</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.00 (0.95-1.05). 0.9737</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Non-Hispanic White</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.99 (0.98-1.01). 0.3734</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.99 (0.97-1.01). 0.2670</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.98 (0.97-1.00). 0.0826</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Non-Hispanic Black</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.00 (0.95-1.05). 0.9936</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.99 (0.94-1.04). 0.6900</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.99 (0.93-1.04). 0.6351</td>
                </tr>
              </tbody>
            </table>
          </table-wrap>
          <p>Further analyses were stratified by sex and race/ethnicity. In the sex-stratified analysis, urinary caffeine levels were not significantly associated with CHD incidence in either men or women (OR 1.00; 95% CI 1.00-1.00; p = 0.009, which likely reflects model artifact or collinearity).</p>
          <p>In the race-stratified analysis, a significant positive association was observed only among Mexican American participants, where each 1 &#956;mol/L increase in urinary caffeine was associated with a 3% higher risk of CHD (OR 1.03; 95% CI 1.03-1.05; p = 0.0081). No statistically significant associations were found in other racial/ethnic groups (all p &gt; 0.05).</p>
          <p>These associations are visually represented in <xref ref-type="fig" rid="f5">Figure 2A</xref> , which depicts a smoothed curve illustrating the relationship between urinary caffeine concentration and CHD incidence.</p>
          <fig id="f5">
            <label>Figure 2</label>
            <caption>
              <title>Smoothed curve plots displaying the relationship between urinary levels of caffeine and its metabolites (&#956;mol/L) and the incidence of CHD. The red line represents the fitted curve showing the estimated association, while the blue shaded area denotes the 95% CI. Models were adjusted for sex, age, race/ethnicity, hypertension, hypercholesterolemia, T2DM, stroke, smoking, alcohol consumption, and BMI. BMI: body mass index; CHD: coronary heart disease; T2DM: type 2 diabetes mellitus.</title>
            </caption>
            <graphic xlink:href=""/>
          </fig>
          <p>The associations between urinary caffeine metabolite levels and CHD are presented in <xref ref-type="table" rid="t8">Table 3</xref> .</p>
          <table-wrap id="t8">
            <label>Table 3</label>
            <caption>
              <title>Association between urinary caffeine metabolite levels (&#956;mol/L) and CHD</title>
            </caption>
            <table frame="hsides" rules="groups">
              <colgroup width="20%">
                <col width="1%"/>
                <col/>
                <col/>
                <col/>
                <col/>
              </colgroup>
              <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
                <tr style="background-color:#76B4CF">
                  <th align="left" colspan="2" valign="middle">Variable</th>
                  <th align="center" valign="middle">Model 1 <break/> OR (95% CI), p-value</th>
                  <th align="center" valign="middle">Model 2 <break/> OR (95% CI), p-value</th>
                  <th align="center" valign="middle">Model 3 <break/> OR (95% CI), p-value</th>
                </tr>
              </thead>
              <tbody style="border-bottom: thin solid; border-color: #000000">
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>Theophylline (&#956;mol/L)</bold>
                  </td>
                  <td align="center" valign="middle">0.98 (0.93 to 1.02), 0.3320</td>
                  <td align="center" valign="middle">0.98 (0.94 to 1.02), 0.3084</td>
                  <td align="center" valign="middle">0.97 (0.93 to 1.02), 0.2592</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Theophylline quartiles</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Q1 (Reference)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Q2</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.10 (0.76 to 1.59), 0.6243</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.00 (0.67 to 1.49), 0.9914</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.94 (0.62 to 1.42), 0.7712</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Q3</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.94 (0.64 to 1.38), 0.7660</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.89 (0.59 to 1.34), 0.5788</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.83 (0.54 to 1.27), 0.3800</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Q4</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.92 (0.63 to 1.36), 0.6883</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.90 (0.59 to 1.36), 0.6020</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.85 (0.55 to 1.31), 0.4527</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>Theobromine (&#956;mol/L)</bold>
                  </td>
                  <td align="center" valign="middle">1.00 (0.99 to 1.00), 0.3674</td>
                  <td align="center" valign="middle">1.00 (1.00 to 1.00), 0.6186</td>
                  <td align="center" valign="middle">1.00 (1.00 to 1.00), 0.9285</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>Theobromine quartiles</bold>
                  </td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Q1 (Reference)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Q2</td>
                  <td align="center" valign="middle">1.12 (0.77 to 1.62), 0.5605</td>
                  <td align="center" valign="middle">1.19 (0.80 to 1.76), 0.3965</td>
                  <td align="center" valign="middle">1.09 (0.73 to 1.64), 0.6724</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Q3</td>
                  <td align="center" valign="middle">1.09 (0.75 to 1.58), 0.6515</td>
                  <td align="center" valign="middle">1.14 (0.76 to 1.70), 0.5217</td>
                  <td align="center" valign="middle">1.10 (0.73 to 1.68), 0.6430</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Q4</td>
                  <td align="center" valign="middle">0.76 (0.51 to 1.14), 0.1816</td>
                  <td align="center" valign="middle">0.84 (0.54 to 1.30), 0.4293</td>
                  <td align="center" valign="middle">0.89 (0.57 to 1.40), 0.6291</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Paraxanthine (&#956;mol/L)</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.99 (0.99 to 1.00), 0.0177</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.00 (0.99 to 1.00), 0.1037</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.99 (0.99 to 1.00), 0.1154</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Paraxanthine quartiles</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Q1 (Reference)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Q2</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.90 (0.62 to 1.31), 0.5866</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.76 (0.51 to 1.13), 0.1789</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.74 (0.49 to 1.11), 0.1461</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Q3</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.01 (0.71 to 1.45), 0.9409</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.99 (0.67 to 1.45), 0.9396</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.97 (0.65 to 1.45), 0.8707</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Q4</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.65 (0.43 to 0.97), 0.0360</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.68 (0.44 to 1.04), 0.0779</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.65 (0.42 to 1.03), 0.0655</td>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <fn id="TFN6">
                <p>CHD: coronary heart disease.</p>
              </fn>
            </table-wrap-foot>
          </table-wrap>
          <p>The relationship between urinary caffeine metabolites and CHD is further explored using smooth curve fitting in <xref ref-type="fig" rid="f5">Figure 2</xref> .</p>
          <p>The results of the association between urinary caffeine metabolites and CHD are presented in <xref ref-type="table" rid="t8">Table 3</xref> . In Model 1, urinary levels of theophylline and theobromine showed no statistically significant association with CHD (all p &gt; 0.05). When theophylline and theobromine levels were categorized into quartiles, no significant associations were observed across any model. After adjusting for potential confounders in Models 2 and 3, these findings remained nonsignificant. The smoothed curve fitting for theophylline and theobromine ( <xref ref-type="fig" rid="f5">Figures 2B</xref> and <xref ref-type="fig" rid="f5">2C</xref> , respectively) also demonstrated no clear association with CHD risk.</p>
          <p>In contrast, urinary paraxanthine levels showed a significant inverse association with CHD in the unadjusted model (Model 1: OR 0.99; 95% CI 0.99-1.00; p = 0.0177). However, this association was no longer statistically significant after adjusting for covariates in Models 2 and 3.</p>
          <p>To further assess the relationship, paraxanthine was also analyzed as a categorical variable divided into quartiles. In Model 1, individuals in the highest quartile of urinary paraxanthine (Q4) had a significantly lower risk of CHD compared to those in the lowest quartile (OR 0.65; 95% CI 0.43-0.97; p = 0.036). Nonetheless, this inverse association lost statistical significance after adjustment in Models 2 and 3 (all p &gt; 0.05).</p>
          <p>The urinary concentrations of theophylline, paraxanthine, theobromine, and caffeine were compared between the CHD group and the control group, as detailed in <xref ref-type="table" rid="t9">Table 4</xref> .</p>
          <table-wrap id="t9">
            <label>Table 4</label>
            <caption>
              <title>Comparison of urinary caffeine and caffeine metabolite levels (&#956;mol/L) between the CHD group and the control group</title>
            </caption>
            <table frame="hsides" rules="groups">
              <colgroup width="20%">
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
              </colgroup>
              <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
                <tr style="background-color:#76B4CF">
                  <th align="left" valign="middle">Metabolite</th>
                  <th align="center" valign="middle">Group</th>
                  <th align="center" valign="middle">Model 1, <break/> OR (95% CI), p-value</th>
                  <th align="center" valign="middle">Model 2, <break/> OR (95% CI), p-value</th>
                  <th align="center" valign="middle">Model 3, <break/> OR (95% CI), p-value</th>
                </tr>
              </thead>
              <tbody style="border-bottom: thin solid; border-color: #000000">
                <tr>
                  <td align="left" valign="middle">
                    <bold>Theophylline</bold>
                  </td>
                  <td align="center" valign="middle">Control (n = 5,005)</td>
                  <td align="center" valign="middle">Reference</td>
                  <td align="center" valign="middle">Reference</td>
                  <td align="center" valign="middle">Reference</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="center" valign="middle">CHD (n = 222)</td>
                  <td align="center" valign="middle">&#8722;0.4 (&#8722;0.9 to 0.1), 0.0923</td>
                  <td align="center" valign="middle">&#8722;0.8 (&#8722;1.5 to &#8722;0.1), 0.0196</td>
                  <td align="center" valign="middle">&#8722;0.7 (&#8722;1.5 to &#8722;0.0), 0.0412</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">
                    <bold>Paraxanthine</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">Control (n = 5,005)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">Reference</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">Reference</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">Reference</td>
                </tr>
                <tr>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">CHD (n = 222)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;4.8 (&#8722;8.0 to &#8722;1.7), 0.0028</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;5.1 (&#8722;8.4 to &#8722;1.8), 0.0023</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;4.1 (&#8722;7.3 to &#8722;0.8), 0.0135</td>
                </tr>
                <tr>
                  <td align="left" valign="middle">
                    <bold>Theobromine</bold>
                  </td>
                  <td align="center" valign="middle">Control (n = 5,005)</td>
                  <td align="center" valign="middle">Reference</td>
                  <td align="center" valign="middle">Reference</td>
                  <td align="center" valign="middle">Reference</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="center" valign="middle">CHD (n = 222)</td>
                  <td align="center" valign="middle">&#8722;2.5 (&#8722;8.2 to 3.2), 0.3925</td>
                  <td align="center" valign="middle">&#8722;0.1 (&#8722;5.9 to 5.7), 0.9689</td>
                  <td align="center" valign="middle">&#8722;0.1 (&#8722;5.9 to 5.7), 0.9770</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">
                    <bold>Caffeine</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">Control (n = 5,005)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">Reference</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">Reference</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">Reference</td>
                </tr>
                <tr>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">CHD (n = 222)</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.2 (&#8722;0.4 to 2.8), 0.1327</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0.9 (&#8722;2.5 to 0.8), 0.2966</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0.5 (&#8722;2.1 to 1.1), 0.5534</td>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <fn id="TFN7">
                <p>CHD: coronary heart disease.</p>
              </fn>
            </table-wrap-foot>
          </table-wrap>
          <p>This analysis employed three models: an unadjusted model (Model 1), and two adjusted models &#8212; Model 2 (Adjust 1) and Model 3 (Adjust 2). <xref ref-type="table" rid="t9">Table 4</xref> compares the urinary concentrations of four compounds (i.e., theophylline, paraxanthine, theobromine, and caffeine) between two groups: individuals without CHD (control group; n = 5,005) and those with CHD (CHD group; n = 222). For each compound, the difference in mean urinary concentration between the CHD group and the control group is presented, along with the corresponding 95% CI and p-value. The difference reflects the estimated average concentration difference between the two groups. The 95% CI provides the range within which the true difference is likely to fall. A p-value &lt; 0.05 indicates a statistically significant difference.</p>
          <p>The results showed that theophylline in the non-adjusted model had a difference of &#8722;0.4 (&#8722;0.9 to 0.1; p = 0.0923), which did not reach statistical significance. In Adjust I, the difference was &#8722;0.8 (&#8722;1.5 to &#8722;0.1; p = 0.0196), which was significant. In Adjust II, the difference was &#8722;0.7 (&#8722;1.5 to &#8722;0.0; p = 0.0412), also significant. After adjustment, the concentration of theophylline in the CHD group was significantly lower than in the control group. For paraxanthine, the non-adjusted model showed a difference of &#8722;4.8 (&#8722;8.0 to &#8722;1.7; p = 0.0028), which was significant. In Adjust I, the difference was &#8722;5.1 (&#8722;8.4 to &#8722;1.8; p = 0.0023), also significant. In Adjust II, the difference was &#8722;4.1 (&#8722;7.3 to &#8722;0.8; p = 0.0135), remaining significant. Paraxanthine levels were consistently lower in all models compared to the control group.</p>
          <p>Theobromine in the non-adjusted model showed a difference of &#8722;2.5 (&#8722;8.2 to 3.2; p = 0.3925), which was not significant. In Adjust I, the difference was &#8722;0.1 (&#8722;5.9 to 5.7; p = 0.9689), not significant. In Adjust II, the difference remained &#8722;0.1 (&#8722;5.9 to 5.7; p = 0.9770), also not significant. There was no significant difference in the concentration of theobromine between the CHD group and the control group. Caffeine in the non-adjusted model showed a difference of 1.2 (&#8722;0.4 to 2.8; p = 0.1327), not significant. In Adjust I, the difference was &#8722;0.9 (&#8722;2.5 to 0.8; p = 0.2966), not significant. In Adjust II, the difference was &#8722;0.5 (&#8722;2.1 to 1.1; p = 0.5534), also not significant. After adjustment, there was no significant difference in caffeine concentration between the two groups.</p>
          <p>Therefore, we can conclude that the concentrations of theophylline and paraxanthine in the CHD group were significantly lower than those in the control group, especially after adjustment, which still showed statistical significance. This suggests that these compounds may be associated with CHD. There was no significant difference in the concentrations of theobromine and caffeine between the two groups, indicating that these compounds may not be directly related to CHD. The impact of the different adjustment models on the results was limited, but the adjusted results are more reliable.</p>
        </sec>
        <sec>
          <title>Subgroup analysis</title>
          <p><xref ref-type="table" rid="t10">Table 5</xref> presents the stratified analysis results of theophylline, paraxanthine, theobromine, and caffeine in different subgroups, including effect values, 95% CIs, and p-values. Through stratified analysis, differences in compound concentrations and their significance can be observed among different characteristic groups.</p>
          <table-wrap id="t10">
            <label>Table 5</label>
            <caption>
              <title>Subgroup analysis</title>
            </caption>
            <table frame="hsides" rules="groups">
              <colgroup width="14%">
                <col width="1%"/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
              </colgroup>
              <thead style="border-top: thin solid; border-bottom: thin solid; border-color: #000000">
                <tr style="background-color:#76B4CF">
                  <th align="left" colspan="2" valign="middle">Subgroup</th>
                  <th align="center" valign="middle">N</th>
                  <th align="center" valign="middle">Theophylline</th>
                  <th align="center" valign="middle">Paraxanthine</th>
                  <th align="center" valign="middle">Theobromine</th>
                  <th align="center" valign="middle">Caffeine</th>
                </tr>
              </thead>
              <tbody style="border-bottom: thin solid; border-color: #000000">
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>Sex</bold>
                  </td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Male</td>
                  <td align="center" valign="middle">2,543</td>
                  <td align="center" valign="middle">&#8722;0.4 (&#8722;2.7 to 1.8) 0.7161</td>
                  <td align="center" valign="middle">&#8722;4.8 (&#8722;9.8 to 0.1) 0.0538</td>
                  <td align="center" valign="middle">0.4 (&#8722;6.0 to 6.8) 0.9105</td>
                  <td align="center" valign="middle">2.2 (0.6 to 3.8) 0.0081</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Female</td>
                  <td align="center" valign="middle">2,684</td>
                  <td align="center" valign="middle">&#8722;0.7 (&#8722;1.7 to 0.4) 0.2290</td>
                  <td align="center" valign="middle">&#8722;7.4 (&#8722;14.5 to &#8722;0.4) 0.0379</td>
                  <td align="center" valign="middle">&#8722;6.7 (&#8722;16.5 to 3.1) 0.1791</td>
                  <td align="center" valign="middle">&#8722;0.5 (&#8722;3.1 to 2.1) 0.7220</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Age group (years)</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">18-39</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1,685</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0.9 (&#8722;3.6 to 1.9) 0.5380</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;11.0 (&#8722;37.5 to 15.4) 0.4137</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;17.7 (&#8722;53.9 to 18.5) 0.3381</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;3.9 (&#8722;11.3 to 3.6) 0.3106</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">40-57</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1,740</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0.6 (&#8722;1.7 to 0.5) 0.2582</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;2.0 (&#8722;13.3 to 9.3) 0.7259</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;8.8 (&#8722;23.3 to 5.8) 0.2373</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.9 (&#8722;2.6 to 4.4) 0.6177</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">58-80</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1,802</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0.8 (&#8722;3.3 to 1.7) 0.5434</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;3.6 (&#8722;7.7 to 0.5) 0.0882</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">2.0 (&#8722;3.8 to 7.8) 0.5072</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.3 (&#8722;1.5 to 2.1) 0.7589</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>Race</bold>
                  </td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Mexican American</td>
                  <td align="center" valign="middle">717</td>
                  <td align="center" valign="middle">1.7 (&#8722;0.0 to 3.4) 0.0531</td>
                  <td align="center" valign="middle">3.1 (&#8722;12.4 to 18.5) 0.6971</td>
                  <td align="center" valign="middle">3.7 (&#8722;12.0 to 19.4) 0.6447</td>
                  <td align="center" valign="middle">9.0 (3.9 to 14.1) 0.0006</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Other Hispanic</td>
                  <td align="center" valign="middle">522</td>
                  <td align="center" valign="middle">0.0 (&#8722;1.4 to 1.5) 0.9699</td>
                  <td align="center" valign="middle">1.2 (&#8722;12.3 to 14.8) 0.8565</td>
                  <td align="center" valign="middle">&#8722;5.4 (&#8722;22.1 to 11.3) 0.5295</td>
                  <td align="center" valign="middle">3.3 (&#8722;1.0 to 7.6) 0.1348</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Non-Hispanic White</td>
                  <td align="center" valign="middle">2,257</td>
                  <td align="center" valign="middle">&#8722;1.1 (&#8722;3.6 to 1.4) 0.3858</td>
                  <td align="center" valign="middle">&#8722;7.3 (&#8722;12.2 to &#8722;2.4) 0.0034</td>
                  <td align="center" valign="middle">&#8722;4.9 (&#8722;12.3 to 2.5) 0.1936</td>
                  <td align="center" valign="middle">&#8722;0.9 (&#8722;2.8 to 1.1) 0.3745</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Non-Hispanic Black</td>
                  <td align="center" valign="middle">1,100</td>
                  <td align="center" valign="middle">&#8722;0.7 (&#8722;1.6 to 0.2) 0.1460</td>
                  <td align="center" valign="middle">&#8722;7.7 (&#8722;18.3 to 2.9) 0.1538</td>
                  <td align="center" valign="middle">&#8722;7.7 (&#8722;22.1 to 6.7) 0.2933</td>
                  <td align="center" valign="middle">&#8722;0.0 (&#8722;3.1 to 3.0) 0.9936</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Other / Multiracial</td>
                  <td align="center" valign="middle">631</td>
                  <td align="center" valign="middle">&#8722;0.3 (&#8722;1.9 to 1.2) 0.6714</td>
                  <td align="center" valign="middle">&#8722;2.6 (&#8722;19.8 to 14.6) 0.7695</td>
                  <td align="center" valign="middle">&#8722;7.0 (&#8722;27.6 to 13.6) 0.5071</td>
                  <td align="center" valign="middle">1.7 (&#8722;2.8 to 6.1) 0.4658</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Hypertension</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Yes</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1,908</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.1 (&#8722;0.5 to 0.7) 0.8032</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1.4 (&#8722;5.6 to 2.9) 0.5379</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.5 (&#8722;4.2 to 7.2) 0.6026</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.5 (&#8722;0.2 to 3.3) 0.0869</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">No</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">3,310</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1.3 (&#8722;4.8 to 2.2) 0.4758</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;9.7 (&#8722;18.5 to &#8722;1.0) 0.0299</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;7.2 (&#8722;19.2 to 4.7) 0.2365</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1.5 (&#8722;4.3 to 1.3) 0.2977</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Do not know</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">9</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>High Cholesterol Level</bold>
                  </td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Yes</td>
                  <td align="center" valign="middle">1,715</td>
                  <td align="center" valign="middle">&#8722;0.2 (&#8722;0.7 to 0.3) 0.4859</td>
                  <td align="center" valign="middle">&#8722;3.7 (&#8722;8.3 to 1.0) 0.1196</td>
                  <td align="center" valign="middle">&#8722;1.6 (&#8722;8.3 to 5.0) 0.6333</td>
                  <td align="center" valign="middle">1.0 (&#8722;0.8 to 2.8) 0.2794</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">No</td>
                  <td align="center" valign="middle">2,943</td>
                  <td align="center" valign="middle">&#8722;0.7 (&#8722;3.8 to 2.4) 0.6428</td>
                  <td align="center" valign="middle">&#8722;7.0 (&#8722;15.1 to 1.1) 0.0924</td>
                  <td align="center" valign="middle">&#8722;3.6 (&#8722;14.0 to 6.7) 0.4927</td>
                  <td align="center" valign="middle">&#8722;0.4 (&#8722;3.1 to 2.4) 0.7814</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Do not know</td>
                  <td align="center" valign="middle">34</td>
                  <td align="center" valign="middle">&#8722;0.5 (&#8722;4.8 to 3.9) 0.8378</td>
                  <td align="center" valign="middle">&#8722;13.2 (&#8722;57.1 to 30.7) 0.5605</td>
                  <td align="center" valign="middle">&#8722;14.6 (&#8722;68.1 to 38.9) 0.5969</td>
                  <td align="center" valign="middle">0.0 (&#8722;12.4 to 12.4) 0.9987</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Missing</td>
                  <td align="center" valign="middle">535</td>
                  <td align="center" valign="middle">&#8212;</td>
                  <td align="center" valign="middle">&#8212;</td>
                  <td align="center" valign="middle">&#8212;</td>
                  <td align="center" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>T2DM</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Yes</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">615</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0.4 (&#8722;1.2 to 0.4) 0.3501</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;6.8 (&#8722;13.6 to 0.0) 0.0513</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.1 (&#8722;8.5 to 8.7) 0.9758</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1.0 (&#8722;3.6 to 1.7) 0.4773</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">No</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">4,480</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0.2 (&#8722;1.8 to 1.4) 0.7934</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;2.6 (&#8722;7.6 to 2.3) 0.2998</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0.9 (&#8722;7.5 to 5.7) 0.7801</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">2.1 (0.4 to 3.8) 0.0165</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Borderline</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">127</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;3.2 (&#8722;22.6 to 16.3) 0.7500</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;8.0 (&#8722;28.2 to 12.3) 0.4417</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;11.2 (&#8722;50.9 to 28.6) 0.5830</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0.6 (&#8722;9.3 to 8.0) 0.8841</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Do not know</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">5</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" valign="middle">
                    <bold>BMI</bold>
                  </td>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                  <td align="center" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Low <break/> (13.4 &#8804; BMI &#8804; 25.69)</td>
                  <td align="center" valign="middle">1,724</td>
                  <td align="center" valign="middle">&#8722;1.0 (&#8722;5.1 to 3.0) 0.6270</td>
                  <td align="center" valign="middle">&#8722;5.9 (&#8722;14.0 to 2.2) 0.1543</td>
                  <td align="center" valign="middle">&#8722;2.6 (&#8722;13.4 to 8.2) 0.6394</td>
                  <td align="center" valign="middle">&#8722;0.6 (&#8722;3.2 to 2.1) 0.6778</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Middle <break/> (25.7 &#8804; BMI &#8804; 30.59)</td>
                  <td align="center" valign="middle">1,750</td>
                  <td align="center" valign="middle">&#8722;0.2 (&#8722;2.1 to 1.7) 0.8438</td>
                  <td align="center" valign="middle">&#8722;2.9 (&#8722;9.6 to 3.8) 0.3952</td>
                  <td align="center" valign="middle">&#8722;0.5 (&#8722;9.6 to 8.5) 0.9080</td>
                  <td align="center" valign="middle">1.9 (&#8722;0.6 to 4.3) 0.1384</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">High <break/> (30.7 &#8804; BMI &#8804; 82.1)</td>
                  <td align="center" valign="middle">1,753</td>
                  <td align="center" valign="middle">&#8722;0.3 (&#8722;1.0 to 0.4) 0.4031</td>
                  <td align="center" valign="middle">&#8722;6.5 (&#8722;12.8 to &#8722;0.1) 0.0457</td>
                  <td align="center" valign="middle">&#8722;4.9 (&#8722;13.6 to 3.7) 0.2616</td>
                  <td align="center" valign="middle">1.5 (&#8722;0.7 to 3.7) 0.1743</td>
                </tr>
                <tr>
                  <td align="left" colspan="2" style="background-color:#C7DFEC" valign="middle">
                    <bold>Stroke</bold>
                  </td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="center" style="background-color:#C7DFEC" valign="middle"/>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Yes</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">167</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1.0 (&#8722;3.8 to 1.7) 0.4676</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;4.6 (&#8722;13.8 to 4.6) 0.3249</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;6.3 (&#8722;17.6 to 5.0) 0.2746</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1.1 (&#8722;5.5 to 3.3) 0.6228</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">No</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">5,056</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0.3 (&#8722;1.8 to 1.1) 0.6445</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;4.1 (&#8722;8.4 to 0.3) 0.0663</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1.2 (&#8722;7.0 to 4.6) 0.6889</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.3 (&#8722;0.2 to 2.8) 0.0862</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Do not know</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">4</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" colspan="7" valign="middle">
                    <bold>Smoked at least 100 cigarettes in life</bold>
                  </td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Yes</td>
                  <td align="center" valign="middle">2,296</td>
                  <td align="center" valign="middle">&#8722;0.1 (&#8722;1.6 to 1.4) 0.8906</td>
                  <td align="center" valign="middle">&#8722;4.8 (&#8722;10.1 to 0.6) 0.0805</td>
                  <td align="center" valign="middle">1.0 (&#8722;5.4 to 7.5) 0.7546</td>
                  <td align="center" valign="middle">1.8 (&#8722;0.1 to 3.7) 0.0675</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">No</td>
                  <td align="center" valign="middle">2,930</td>
                  <td align="center" valign="middle">&#8722;1.1 (&#8722;3.5 to 1.3) 0.3891</td>
                  <td align="center" valign="middle">&#8722;7.0 (&#8722;13.1 to &#8722;0.8) 0.0265</td>
                  <td align="center" valign="middle">&#8722;6.0 (&#8722;15.1 to 3.1) 0.1957</td>
                  <td align="center" valign="middle">&#8722;0.3 (&#8722;2.4 to 1.8) 0.7948</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">Do not know</td>
                  <td align="center" valign="middle">1</td>
                  <td align="center" valign="middle">&#8212;</td>
                  <td align="center" valign="middle">&#8212;</td>
                  <td align="center" valign="middle">&#8212;</td>
                  <td align="center" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" colspan="7" style="background-color:#C7DFEC" valign="middle">
                    <bold>At least 12 alcoholic drinks in the past year</bold>
                  </td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Yes</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">3,434</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0.4 (&#8722;2.2 to 1.3) 0.6268</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;4.7 (&#8722;9.7 to 0.3) 0.0677</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;1.4 (&#8722;7.9 to 5.0) 0.6600</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">0.9 (&#8722;0.9 to 2.7) 0.3292</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">No</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1,303</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0.5 (&#8722;3.2 to 2.1) 0.6935</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;5.5 (&#8722;12.8 to 1.8) 0.1398</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;4.9 (&#8722;15.9 to 6.1) 0.3797</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.8 (&#8722;0.4 to 4.0) 0.1138</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Do not know</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">2</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8212;</td>
                </tr>
                <tr>
                  <td align="left" style="background-color:#C7DFEC" valign="middle"/>
                  <td align="left" style="background-color:#C7DFEC" valign="middle">Missing</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">488</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;0.5 (&#8722;2.0 to 1.0) 0.5035</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;7.1 (&#8722;22.3 to 8.1) 0.3581</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">&#8722;5.8 (&#8722;29.3 to 17.7) 0.6281</td>
                  <td align="center" style="background-color:#C7DFEC" valign="middle">1.7 (&#8722;3.3 to 6.6) 0.5120</td>
                </tr>
                <tr>
                  <td align="left" colspan="7" valign="middle">
                    <bold>MET</bold>
                  </td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">&lt;4</td>
                  <td align="center" valign="middle">1,355</td>
                  <td align="center" valign="middle">&#8722;0.6 (&#8722;2.8 to 1.7) <break/> 0.6099</td>
                  <td align="center" valign="middle">&#8722;6.7 (&#8722;12.9 to &#8722;0.4) <break/> 0.0362</td>
                  <td align="center" valign="middle">&#8722;4.8 (&#8722;12.8 to 3.2) <break/> 0.2381</td>
                  <td align="center" valign="middle">1.6 (&#8722;0.8 to 4.0) <break/> 0.1847</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">4-8</td>
                  <td align="center" valign="middle">1,462</td>
                  <td align="center" valign="middle">&#8722;0.5 (&#8722;1.5 to 0.4) <break/> 0.2511</td>
                  <td align="center" valign="middle">&#8722;3.6 (&#8722;10.3 to 3.0) <break/> 0.2818</td>
                  <td align="center" valign="middle">2.0 (&#8722;6.4 to 10.5) <break/> 0.6361</td>
                  <td align="center" valign="middle">&#8722;0.1 (&#8722;2.4 to 2.2) <break/> 0.9365</td>
                </tr>
                <tr>
                  <td align="left" valign="middle"/>
                  <td align="left" valign="middle">&#8805;8</td>
                  <td align="center" valign="middle">2,410</td>
                  <td align="center" valign="middle">&#8722;0.0 (&#8722;3.1 to 3.1) <break/> 0.9958</td>
                  <td align="center" valign="middle">&#8722;1.3 (&#8722;9.3 to 6.6) <break/> 0.7388</td>
                  <td align="center" valign="middle">&#8722;0.7 (&#8722;11.9 to 10.5) <break/> 0.8991</td>
                  <td align="center" valign="middle">1.8 (&#8722;0.8 to 4.4) <break/> 0.1730</td>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <fn id="TFN8">
                <p>BMI: body mass index; MET: metabolic equivalent of task.</p>
              </fn>
            </table-wrap-foot>
          </table-wrap>
          <p>The subgroup variables analyzed included sex, age, race, presence of high blood pressure, high cholesterol levels, T2DM, BMI tertiles, history of stroke, smoking status, alcohol consumption in the past year, and MET score. The MET score was used to assess functional capacity: a score &lt;4 reflects severe functional limitation and is strongly associated with increased cardiovascular risk; a score 4-6 indicates moderate limitation, often presenting as dyspnea or fatigue during moderate physical activity (e.g., walking short distances or performing light work); a score &gt;8 typically reflects low cardiovascular risk. Sample size (N) refers to the number of individuals in each subgroup. For each subgroup, the difference in concentration of four chemical compounds between individuals with CHD and the control group is shown, along with the 95% CI and the corresponding p-value to indicate statistical significance.</p>
          <p>Stratified analysis revealed that in most subgroups the difference in theophylline concentration between individuals with CHD and controls was not statistically significant (p &gt; 0.05). For instance, among individuals without hypertension, the observed difference was &#8722;1.3 (95% CI &#8722;4.8 to 2.2), with a p-value of 0.4758, indicating no significant association. Overall, theophylline levels did not differ meaningfully across subgroups. In contrast, paraxanthine showed a significant and relatively consistent difference across several subgroups. Among females, the difference was &#8722;7.4 (p = 0.0379), and among males, &#8722;4.8 (p = 0.0538). A pronounced difference was also observed in Non-Hispanic White individuals (&#8722;7.3, p = 0.0034), while no significant changes were detected in other racial groups. Among individuals with hypertension, the difference reached &#8722;9.7 (p = 0.0299), and in the high BMI group, it was &#8722;6.5 (p = 0.0457). Participants without a history of smoking showed a difference of &#8722;7.0 (p = 0.0265).</p>
          <p>For participants with MET scores &lt;4, the difference in paraxanthine concentration was &#8722;6.7 (p = 0.0362). This indicates that paraxanthine levels were significantly lower in most subgroups compared to the control group, with more notable differences observed among women, Non-Hispanic Whites, and individuals with specific health conditions such as hypertension, absence of smoking history, elevated BMI, and reduced functional capacity (low MET scores). In contrast, theobromine concentrations did not show statistically significant differences in any subgroup (p &gt; 0.05), suggesting only a weak or inconsistent relationship with CHD. Caffeine, however, showed significant variation in a few subgroups: among males, the difference was 2.2 (p = 0.0081), while no significant difference was seen in females (p = 0.7220); among Mexican Americans, the difference reached 9.0 (p = 0.0006), with no significant findings in other racial categories. Additionally, individuals without T2DM showed a difference of 2.1 (p = 0.0165). These findings suggest that elevated caffeine concentrations may be more relevant in men, Mexican Americans, and those without T2DM, although this pattern was not consistent across all subgroups.</p>
        </sec>
      </sec>
      <sec sec-type="discussion">
        <title>Discussion</title>
        <p>This 6-year, large-scale cross-sectional study provided insights summarized in Central Illustration, which highlights the key findings of the analysis. It illustrates significant baseline differences between individuals in the CHD group and those in the control group. Specifically, individuals with CHD were generally older and exhibited a higher prevalence of hypertension, hypercholesterolemia, T2DM, stroke, smoking, and alcohol consumption.</p>
        <p>Analysis of urinary caffeine levels revealed a positive association with CHD incidence, particularly among the Mexican American population, where the association was more pronounced (OR 1.03; 95% CI 1.03-1.05; p = 0.0081). For each 1 &#956;mol/L increase in urinary caffeine concentration, the risk of CHD increased by 3%, with statistical significance (p &lt; 0.01). In contrast, no significant associations were identified between CHD and urinary levels of caffeine metabolites such as theobromine and theophylline. Both theophylline and hypoxanthine concentrations were significantly lower in the CHD group compared to controls.</p>
        <p>Subgroup analyses revealed significant differences in hypoxanthine concentrations across various subgroups defined by sex, age, race, hypertension status, and smoking status &#8212; particularly among women, individuals with hypertension, and smokers. However, no significant subgroup differences were observed for theobromine or caffeine concentrations. These findings suggest that the relationship between urinary caffeine and CHD may be modulated by race and other physiological factors, and that hypoxanthine, a caffeine metabolite, may be linked to cardiovascular health. This study offers valuable insights for both clinical and basic research, supporting the identification and prevention of risk factors for CHD.</p>
        <p>Previous studies have reported a positive association between coffee consumption and the risk of CHD (OR 1.35; 95% CI 1.05-1.73; p = 0.017) as well as an increased likelihood of developing hypertension.<sup><xref ref-type="bibr" rid="B9">9</xref> , <xref ref-type="bibr" rid="B15">15</xref> </sup>Moderate to excessive coffee intake has been linked to heightened inflammatory activity, which plays a key role in the pathogenesis of CHD.<sup><xref ref-type="bibr" rid="B16">16</xref></sup>Excessive consumption of coffee, tea, and caffeine has also been associated with increased all-cause and cardiovascular mortality among individuals with existing cardiovascular conditions.<sup><xref ref-type="bibr" rid="B17">17</xref></sup>Additionally, unfiltered coffee may elevate serum triglyceride, cholesterol, and low-density lipoprotein (LDL) levels.<sup><xref ref-type="bibr" rid="B18">18</xref> , <xref ref-type="bibr" rid="B19">19</xref> </sup></p>
        <p>On the other hand, some studies suggest that coffee consumption is safe and does not increase mortality risk. The effects of various coffee preparation methods on cardiovascular outcomes and survival appear to differ. For example, decaffeinated coffee, ground coffee, and instant coffee have been associated with a significant reduction in cardiovascular disease incidence and mortality.<sup><xref ref-type="bibr" rid="B20">20</xref></sup>Ground and instant coffee without decaffeination have also been linked to a lower risk of cardiac arrhythmias. These findings suggest that the source and method of caffeine intake may influence research outcomes.<sup><xref ref-type="bibr" rid="B21">21</xref></sup></p>
        <p>In conclusion, our study used urinary levels of caffeine and its metabolites as objective indicators of actual coffee intake and found a positive association between urinary caffeine levels and the incidence of CHD (OR 1.54; 95% CI 1.04-2.3; p = 0.0318), supporting the validity of this approach. Moreover, we observed a negative association between urinary paraxanthine levels and CHD incidence. Individuals who consumed low (1-2 cups/day) or high (&gt;2 cups/day) amounts of coffee had a reduced risk of death compared to non-coffee drinkers, with the greatest benefit observed among heavy coffee consumers.</p>
        <p>Several mechanisms may help explain these findings. First, coffee is a complex beverage containing more than 100 bioactive compounds, with caffeine being the most prominent.<sup><xref ref-type="bibr" rid="B22">22</xref> , <xref ref-type="bibr" rid="B23">23</xref> </sup>Caffeine acutely stimulates the sympathetic nervous system by inhibiting phosphodiesterase, increasing intracellular calcium levels, and promoting the release of norepinephrine and adrenaline. These effects may enhance cardiovascular reserve and sustain coronary blood flow, potentially reducing the risk of CHD. Second, caffeine's antagonism of adenosine receptors may impair the expected increase in myocardial perfusion during physical activity.<sup><xref ref-type="bibr" rid="B24">24</xref></sup>Third, caffeine intake may help to regulate cardiovascular risk factors, particularly among non-smokers. Furthermore, coffee consumption has been linked to a potential protective effect against coronary artery calcification.<sup><xref ref-type="bibr" rid="B25">25</xref></sup>Fourth, the antioxidant properties of caffeine may protect endothelial cells from damage, thereby reducing the risk of CHD. Finally, phenolic compounds in coffee &#8212; especially hydroxycinnamic acids &#8212; may exert cardiovascular benefits through anti-inflammatory and antioxidant effects. In contrast, short-term consumption of unfiltered coffee may raise serum levels of triglycerides, cholesterol, and LDL.<sup><xref ref-type="bibr" rid="B18">18</xref></sup></p>
        <p>In this large-scale cross-sectional study, we identified a negative association between urinary caffeine levels and the incidence of CHD among Mexican Americans, a pattern not observed in other ethnic groups. This disparity may reflect differences in CHD prevalence across racial groups.<sup><xref ref-type="bibr" rid="B26">26</xref></sup>Additionally, genetic variability may influence individual responses to caffeine. For instance, a study by Happonen et al.<sup><xref ref-type="bibr" rid="B27">27</xref></sup>suggested that specific genetic polymorphisms &#8212; such as variants in the <italic>COMT</italic> gene &#8212; may modulate caffeine's effects on cardiovascular outcomes. Prior research<sup><xref ref-type="bibr" rid="B28">28</xref></sup>also indicates that elevated plasma caffeine levels in men are linked to reduced stress-induced myocardial blood flow and flow reserve, whereas similar hemodynamic changes were not observed in women. However, our findings did not reveal any sex-related differences. These observations highlight the need for further high-quality, large-scale randomized controlled trials that incorporate genetic data to better understand how gene polymorphisms may influence the relationship between caffeine and cardiovascular health.</p>
        <p>Regression analysis showed that the concentrations of theophylline and hypoxanthine were significantly lower in the CHD group compared to the control group. This difference remained statistically significant after adjustment, suggesting a potential association between these compounds and CHD. No significant differences were observed in the concentrations of theobromine and caffeine between groups, indicating that these compounds may not be directly related to CHD.</p>
        <p>Theophylline is a secondary metabolite of caffeine, and its reduced levels may reflect impaired metabolic function. For example, individuals with CHD may experience decreased liver function or overall metabolic capacity, resulting in lower theophylline production. Additionally, systemic inflammation or oxidative stress &#8212; common in cardiovascular conditions &#8212; may disrupt the metabolic pathways of theophylline. The increase in theophylline levels after adjustment suggests that confounders such as age, sex, and BMI may have masked a true association in unadjusted models. The marked reduction in theophylline concentration highlights its potential diagnostic value. Future studies could incorporate genomic data, such as <italic>CYP1A2</italic> gene variants, to assess whether changes in theophylline levels can predict CHD risk or serve as markers for therapeutic monitoring.</p>
        <p>Across all models, xanthine levels were consistently and significantly lower in the CHD group (difference range: &#8722;4.1 to &#8722;5.1, p &lt; 0.05), both before and after adjustment, indicating a strong and potentially independent link to CHD with limited influence from confounders. This finding supports its potential use as a standalone metabolic marker for CHD. Theobromine and caffeine concentrations did not differ significantly between groups, suggesting they may not be directly involved in cardiovascular metabolic processes or that their effects may be obscured by diet and lifestyle factors.</p>
        <p>In future research, paraxanthine could be included in early screening biomarker panels for CHD. Personalized diagnostic approaches may be developed by integrating genomic data and creating targeted prevention and management strategies that account for sex, race, and metabolic profiles, based on the regulatory roles of theophylline and hypoxanthine.</p>
        <p>Subgroup analysis revealed that paraxanthine was the only compound significantly reduced across most groups, particularly among women, individuals with hypertension, those with high BMI, and those with low MET scores. These findings suggest that paraxanthine may serve as a key potential biomarker for CHD. As the primary metabolite of caffeine, paraxanthine is known to exert anti-inflammatory effects and regulate lipid metabolism. Its marked decrease in individuals with CHD may reflect elevated inflammatory markers or impaired metabolic pathways commonly associated with cardiovascular conditions.</p>
        <p>In hypertensive individuals and those with elevated BMI, higher levels of metabolic stress may contribute to reduced paraxanthine levels, likely linked to lipid metabolism disturbances, impaired liver function, and systemic inflammation. The significant reduction of paraxanthine in women, hypertensive patients, and those with severe functional limitations may indicate gender-specific metabolic responses and the compounding effect of hypertension on the metabolic profile of CHD. The statistical significance observed among Non-Hispanic Whites may reflect interethnic differences in metabolic enzyme activity, lifestyle patterns, and disease susceptibility.</p>
        <p>Future research will focus on large-scale cohort studies to further validate xanthine as a reliable biomarker for CHD. No statistically significant differences were observed in the concentrations of theophylline and theobromine, indicating a weaker association with CHD. Theophylline, an intermediate metabolite of caffeine, is heavily influenced by genetic and hepatic enzyme activity (notably polymorphisms in the <italic>CYP1A2</italic> gene). Since these metabolic pathways are not directly involved in cardiovascular pathophysiology, changes in their concentrations may not be sensitive indicators of CHD. Additionally, theophylline's longer half-life may dampen the effects of transient metabolic fluctuations.</p>
        <p>Theobromine, a cocoa-derived alkaloid and secondary caffeine metabolite, has low metabolic efficiency and relatively stable levels in the body, making it less likely to reflect cardiovascular metabolic shifts. Caffeine concentration differences were only significant in select subgroups, with no consistent trend overall, suggesting a weak or indirect association with CHD or confounding from external factors. The elevated caffeine levels in males may be explained by higher intake (e.g., greater coffee consumption) and faster metabolic rates, while in females, estrogen may modulate caffeine metabolism, reducing observed differences.</p>
        <p>The significantly higher levels in Mexican Americans may be attributed to population-specific polymorphisms in caffeine-metabolizing genes, as well as cultural and dietary habits. Additionally, elevated caffeine levels in non-diabetic individuals suggest that T2DM may impair caffeine clearance through disrupted metabolism. Taken together, the observed reduction in xanthine levels may represent a valuable metabolic marker for CHD, supporting its use in early screening and clinical intervention. Identifying subgroup-specific patterns may also facilitate the development of personalized strategies for prevention and disease management.</p>
        <p>Our study offers several strengths. First, it utilizes data from NHANES to perform a large-sample analysis, effectively minimizing bias associated with small sample sizes. Second, data were stratified by sex, age, and race, and multivariable confounders such as hypertension and BMI were considered in the regression analysis. This approach enabled a more precise investigation into the relationship between urinary caffeine and its metabolites and the incidence of CHD. Third, rather than relying on self-reported caffeine intake through questionnaires, we used urinary concentrations of caffeine and its metabolites as exposure variables, thereby avoiding recall bias, misclassification, and variability in food sources. Fourth, by constructing multiple models and incorporating a range of covariates, we were able to generate more robust and reliable findings regarding the association between caffeine, its metabolites, and CHD.</p>
        <p>Nonetheless, this study has certain limitations. First, being a cross-sectional study, it cannot establish a causal relationship between caffeine metabolites and CHD. Second, the participants were primarily from the United States, which may limit the generalizability of the findings to other populations. Third, due to the NHANES stratification strategy and the relatively low prevalence of CHD, the number of cases in the CHD group was limited, potentially introducing bias into the results. Therefore, future longitudinal studies and multi-regional, multi-center investigations are needed to confirm these findings and further elucidate the relationship between caffeine, its metabolites, and CHD.</p>
      </sec>
      <sec sec-type="conclusions">
        <title>Conclusion</title>
        <p>This study found an inverse association between urinary paraxanthine levels and the risk of CHD. In contrast, urinary caffeine levels were positively associated with CHD among Mexican Americans, while no significant association was observed in other ethnic groups. Overall, higher urinary caffeine concentrations were associated with increased CHD incidence, although this trend was not evident in sex-stratified analyses. These findings may contribute to clinical prediction and diagnosis; however, further large-scale prospective studies are needed to confirm these results.</p>
      </sec>
      <sec sec-type="data-availability" specific-use="data-in-article">
        <label>Data Availability</label>
        <p>The underlying content of the research text is contained within the manuscript.</p>
      </sec>
      <sec sec-type="supplementary-material">
        <title>Supplementar Material</title>
        <supplementary-material id="suppl2">
          <label>*Supplemental Materials</label>
          <p>For additional information, please <media mimetype="application" mime-subtype="pdf" xlink:href="https://minio.scielo.br/documentstore/1678-4170/7k3zrFh4x78yWB4NC57xFDh/1cf3184cd55244a29b59a49c9745a7dcb31108f5.pdf">click here</media> .</p>
        </supplementary-material>
      </sec>
    </body>
    <back>
      <fn-group>
        <fn fn-type="financial-disclosure" id="fn1">
          <label>Sources of funding</label>
          <p>This study was partially funded by Shenzhen Science and Technology Innovation Foundation (No. JCYJ20180228162359914) and the Guangdong-Shenzhen Joint Fund Youth Project (No. 2021A1515111110).</p>
        </fn>
        <fn fn-type="other" id="fn2">
          <label>Study association</label>
          <p>This study is not associated with any thesis or dissertation work.</p>
        </fn>
        <fn fn-type="other" id="fn3">
          <label>Ethics approval and consent to participate</label>
          <p>This article does not contain any studies with human participants or animals performed by any of the authors.</p>
        </fn>
        <fn fn-type="other" id="fn4">
          <label>Use of Artificial Intelligence</label>
          <p>The authors did not use any artificial intelligence tools in the development of this work.</p>
        </fn>
      </fn-group>
      <ack>
        <title>Acknowledgments</title>
        <p>We thank the NHANES program for providing publicly accessible data.</p>
        <p>Shijian Wang and Kunfu Ouyang - These authors are listed in the articles declarations, but they are not listed in the article submission system.</p>
        <p>Luo Y and Liangxian Qiu - these authors are not in the statement sent.</p>
      </ack>
    </back>
  </sub-article>
</article>
