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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">ZHJP4wPBxpnsMCqDgBMXGDf</article-id>
      <article-id specific-use="scielo-v2" pub-id-type="publisher-id">S0066-782X2023001100502</article-id>
      <article-id pub-id-type="other">00502</article-id>
      <article-id pub-id-type="doi">10.36660/abc.20230347</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Carta Cient&#237;fica</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Excesso de Press&#227;o Arterial Sist&#243;lica Associada com Polui&#231;&#227;o A&#233;rea por Material Particulado Fino Acima da Diretriz da OMS no Brasil</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-5116-5062</contrib-id>
          <name>
            <surname>Salerno</surname>
            <given-names>Pedro Rafael Vieira de Oliveira</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa e Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</role>
          <role>Obten&#231;&#227;o de dados</role>
          <role>An&#225;lise e interpreta&#231;&#227;o dos dados</role>
          <role>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>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Motairek</surname>
            <given-names>Issam</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa e Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</role>
          <role>Obten&#231;&#227;o de dados</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Dallan</surname>
            <given-names>Luis Augusto Palma</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa e Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Bourges-Sevenier</surname>
            <given-names>Brendan</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa e Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</role>
          <role>Reda&#231;&#227;o do manuscrito</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Rajagopalan</surname>
            <given-names>Sanjay</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa e Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</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">
          <name>
            <surname>Al-Kindi</surname>
            <given-names>Sadeer G.</given-names>
          </name>
          <role>Concep&#231;&#227;o e desenho da pesquisa e Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante</role>
          <role>An&#225;lise estat&#237;stica</role>
          <xref ref-type="aff" rid="aff1">
            <sup>1</sup>
          </xref>
          <xref ref-type="aff" rid="aff2">
            <sup>2</sup>
          </xref>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label> 1 </label>
        <institution content-type="orgdiv1">Harrington Heart and Vascular Institute</institution>
        <institution content-type="orgname">University Hospitals Cleveland Medical Center</institution>
        <addr-line>
          <named-content content-type="city">Cleveland</named-content>
          <named-content content-type="state">Ohio</named-content>
        </addr-line>
        <country country="US">EUA</country>
        <institution content-type="original"> Harrington Heart and Vascular Institute , University Hospitals Cleveland Medical Center , Cleveland , Ohio &#8211; EUA </institution>
      </aff>
      <aff id="aff2">
        <label> 2 </label>
        <institution content-type="orgname">Case Western Reserve University</institution>
        <institution content-type="orgdiv1">School of Medicine</institution>
        <addr-line>
          <named-content content-type="city">Cleveland</named-content>
          <named-content content-type="state">Ohio</named-content>
        </addr-line>
        <country country="US">EUA</country>
        <institution content-type="original"> Case Western Reserve University School of Medicine , Cleveland , Ohio &#8211; EUA </institution>
      </aff>
      <author-notes>
        <corresp id="c01">Correspond&#234;ncia: Sadeer Al-Kindi &#8226; University Hospitals Harrington Heart and Vascular Institute Case Western Reserve University School of Medicine &#8211; 11100 Euclid Ave, Cleveland, OH 44106 &#8211; EUA E-mail: <email>Sadeer.Al-Kindi@uhhospitals.org</email> </corresp>
        <fn fn-type="conflict">
          <p>Potencial conflito de interesse</p>
          <p>N&#227;o h&#225; conflito com o presente artigo</p>
        </fn>
        <fn fn-type="edited-by">
          <p>Editor respons&#225;vel pela revis&#227;o: Paulo B. Veiga Jardim</p>
        </fn>
      </author-notes>
      <pub-date date-type="pub" publication-format="electronic">
        <day>18</day>
        <month>12</month>
        <year>2023</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <month>11</month>
        <year>2023</year>
      </pub-date>
      <volume>120</volume>
      <issue>11</issue>
      <elocation-id>e20230347</elocation-id>
      <history>
        <date date-type="received">
          <day>21</day>
          <month>05</month>
          <year>2023</year>
        </date>
        <date date-type="rev-recd">
          <day>01</day>
          <month>08</month>
          <year>2023</year>
        </date>
        <date date-type="accepted">
          <day>04</day>
          <month>10</month>
          <year>2023</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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
        </license>
      </permissions>
      <kwd-group xml:lang="pt">
        <kwd>Polui&#231;&#227;o do Ar</kwd>
        <kwd>Press&#227;o Arterial</kwd>
        <kwd>Meio Ambiente</kwd>
        <kwd>Sa&#250;de P&#250;blica</kwd>
      </kwd-group>
      <counts>
        <fig-count count="4"/>
        <table-count count="2"/>
        <equation-count count="4"/>
        <ref-count count="18"/>
      </counts>
    </article-meta>
  </front>
  <body>
    <sec sec-type="intro">
      <title>Introdu&#231;&#227;o</title>
      <p>A doen&#231;a cardiovascular continua sendo a principal causa mundial de mortalidade, e a hipertens&#227;o tem sido implicada como tendo a maior associa&#231;&#227;o de causa&#231;&#227;o entre todos os fatores de risco de doen&#231;as cardiovasculares. <sup><xref ref-type="bibr" rid="B1">1</xref></sup> Assim, n&#227;o &#233; de surpreender que a hipertens&#227;o seja o principal fator de risco de morte e a segunda maior causa de anos de vida ajustados por incapacidade no Brasil, fortemente impactando sua popula&#231;&#227;o e o sistema nacional de sa&#250;de. <sup><xref ref-type="bibr" rid="B2">2</xref></sup> A hipertens&#227;o tamb&#233;m est&#225; diretamente ligada &#224; polui&#231;&#227;o do ar, especialmente ao material particulado fino &lt; 2,5 m&#237;crons (PM <sub>2,5</sub> ), que tem sido identificado como um fator de risco independente para aumento da press&#227;o arterial sist&#243;lica (PAS). <sup><xref ref-type="bibr" rid="B3">3</xref></sup> No Brasil, como na maioria dos pa&#237;ses, a principal fonte de exposi&#231;&#227;o &#224; polui&#231;&#227;o do ar em &#225;reas urbanas resulta principalmente da queima de combust&#237;veis f&#243;sseis pelo tr&#226;nsito de ve&#237;culos e pela gera&#231;&#227;o de energia industrial, enquanto, em &#225;reas rurais do Brasil, a polui&#231;&#227;o do ar resulta principalmente da queima de biomassa. <sup><xref ref-type="bibr" rid="B4">4</xref></sup></p>
      <p>No Brasil, foram realizados estudos anteriores investigando os efeitos da exposi&#231;&#227;o ao PM <sub>2,5</sub> na press&#227;o arterial em trabalhadores ao ar livre que s&#227;o mais suscet&#237;veis &#224; polui&#231;&#227;o do ar ambiente por emiss&#245;es veiculares, como controladores de tr&#225;fego, demonstrando a liga&#231;&#227;o entre a concentra&#231;&#227;o de PM <sub>2,5</sub> e o aumento da PAS. <sup><xref ref-type="bibr" rid="B5">5</xref> , <xref ref-type="bibr" rid="B6">6</xref></sup> No entanto, esses estudos tendem a concentrar-se nas regi&#245;es metropolitanas e urbanas. <sup><xref ref-type="bibr" rid="B5">5</xref> , <xref ref-type="bibr" rid="B6">6</xref></sup> Assim, devido ao grande tamanho geogr&#225;fico e &#224; diversidade regional do Brasil, existe uma lacuna substancial no conhecimento em rela&#231;&#227;o &#224;s &#225;reas menos povoadas. No presente estudo, visamos estimar o excesso de PAS atribu&#237;vel &#224;s concentra&#231;&#245;es de PM <sub>2,5</sub> acima do limite da diretriz da Organiza&#231;&#227;o Mundial da Sa&#250;de (OMS) no Brasil, bem como em todos os seus estados e regi&#245;es.</p>
    </sec>
    <sec sec-type="methods">
      <title>M&#233;todos</title>
      <p>Obtivemos as concentra&#231;&#245;es de PM <sub>2,5</sub> ponderadas pela popula&#231;&#227;o de 2019 para os 26 estados brasileiros e o Distrito Federal a partir do estudo <italic>Global Burden of Disease</italic> (GBD), um esfor&#231;o de colabora&#231;&#227;o internacional para quantificar os n&#237;veis e tend&#234;ncias na sa&#250;de e fornecer dados publicamente dispon&#237;veis. <sup><xref ref-type="bibr" rid="B7">7</xref></sup> Modelos de sistemas de monitoramento ao n&#237;vel do solo e de sat&#233;lite, bem como modelos de transporte qu&#237;mico, foram utilizados pelo GBD para estimar as concentra&#231;&#245;es de PM <sub>2,5</sub> em &#956;g/m <sup>3</sup> Os estados tamb&#233;m foram estratificados de acordo com as regi&#245;es (Norte, Nordeste, Centro-Oeste, Sudeste e Sul) determinados pelo Instituto Brasileiro de Geografia e Estat&#237;stica (IBGE) <sup><xref ref-type="bibr" rid="B9">9</xref></sup> e de acordo com quartis do &#205;ndice Sociodemogr&#225;fico (SDI). <sup><xref ref-type="bibr" rid="B7">7</xref></sup> O SDI, uma ferramenta desenvolvida pelo GBD, &#233; um indicador composto de condi&#231;&#245;es socioecon&#244;micas que afetam os desfechos de sa&#250;de que varia de 0 a 1. <sup><xref ref-type="bibr" rid="B7">7</xref></sup> Uma faixa de exposi&#231;&#227;o ao PM <sub>2,5</sub> e da resposta da PAS foi obtida a partir de uma metan&#225;lise de estudos observacionais (aumento de 0,06 mmHg na PAS por aumento de 1 &#181;g/m <sup>3</sup> na concentra&#231;&#227;o de PM <sub>2,5</sub> ) e de uma revis&#227;o de ensaios de filtra&#231;&#227;o de ar (0,19 mmHg por aumento de 1 &#181;g/m <sup>3</sup> na concentra&#231;&#227;o de PM <sub>2,5</sub> ), <sup><xref ref-type="bibr" rid="B10">10</xref> , <xref ref-type="bibr" rid="B11">11</xref></sup> resultando assim em uma faixa de resposta &#224; exposi&#231;&#227;o de 0,06 a 0,19 mmHg por aumento de 1 &#956;g/m <sup>3</sup> na concentra&#231;&#227;o de PM <sub>2,5</sub> . A metan&#225;lise incluiu 28 estudos observacionais (10 estudos de coorte e 18 estudos transversais) que examinaram a exposi&#231;&#227;o de longo prazo (&gt; 1 ano) ao PM <sub>2,5</sub> e hipertens&#227;o em popula&#231;&#245;es saud&#225;veis. <sup><xref ref-type="bibr" rid="B10">10</xref></sup> A revis&#227;o sistem&#225;tica incluiu um total de 10 ensaios cl&#237;nicos randomizados em humanos que avaliaram filtros de ar pessoais (incluindo filtros de ar particulado de alta efici&#234;ncia e precipitadores eletrost&#225;ticos) em um ambiente dom&#233;stico ou residencial, observando os efeitos da filtra&#231;&#227;o versus nenhuma filtra&#231;&#227;o na press&#227;o arterial. <sup><xref ref-type="bibr" rid="B11">11</xref></sup> O excesso de PAS foi considerado como o aumento da PAS devido ao n&#237;vel de concentra&#231;&#227;o de PM <sub>2,5</sub> acima de 5 &#956;g/m <sup>3</sup> , com base nas atuais Diretrizes de Qualidade do Ar da OMS. <sup><xref ref-type="bibr" rid="B8">8</xref></sup> A aprova&#231;&#227;o do conselho de revis&#227;o institucional n&#227;o foi necess&#225;ria devido &#224; natureza dos dados publicamente dispon&#237;veis. As an&#225;lises estat&#237;sticas e os mapas foram produzidos utilizando o software de acesso aberto R v 4.1.2.</p>
      <p>
        <bold>Excesso de PAS, estimativas observacionais</bold>
      </p>
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        <bold>Excesso de PAS, estimativas de interven&#231;&#227;o</bold>
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    </sec>
    <sec sec-type="results">
      <title>Resultados</title>
      <p>A concentra&#231;&#227;o m&#233;dia de PM <sub>2,5</sub> ponderada pela popula&#231;&#227;o do Brasil foi de 10,68 &#956;g/m <sup>3</sup> , o que resultou em uma faixa de excesso de PAS de 0,40 a 1,26 mmHg com base em estimativas observacionais e de interven&#231;&#227;o, respectivamente. A <xref ref-type="table" rid="t1">Tabela 1</xref> descreve a concentra&#231;&#227;o m&#233;dia de PM <sub>2,5</sub> espec&#237;fica por estado e o excesso de PAS em 2019. A <xref ref-type="fig" rid="f01">Figura 1</xref> mapeia a variabilidade interestadual da concentra&#231;&#227;o m&#233;dia de PM <sub>2,5</sub> , e a <xref ref-type="fig" rid="f02">Figura 2</xref> ilustra o excesso de PAS de acordo com a regi&#227;o e os quartis do SDI. Rio de Janeiro (0,53 a 1,69 mmHg) e S&#227;o Paulo (0,53 a 1,68 mmHg) tiveram os maiores n&#237;veis de excesso de PAS, enquanto Rond&#244;nia (0,20 a 0,62 mmHg) e Amazonas (0,21 a 0,66 mmHg) tiveram os menores. Comparando os estados com carga mais baixa (Rond&#244;nia) e com carga mais alta (Rio de Janeiro), foi observada uma diferen&#231;a percentual relativa de aproximadamente 90% a 92% (faixa da estimativa observacional para a de interven&#231;&#227;o) para o excesso de PAS. As diferen&#231;as regionais e os quartis do SDI no excesso de PAS s&#227;o exibidas na <xref ref-type="fig" rid="f02">Figura 2</xref> . O Sudeste (0,47 a 1,49 mmHg) foi a regi&#227;o que teve a maior carga de excesso de PAS, enquanto o Norte (0,28 a 0,88 mmHg) foi a regi&#227;o menos afetada. Em rela&#231;&#227;o aos quartis do SDI, o terceiro (0,36 a 1,15 mmHg) e o quarto (0,39 a 1,25 mmHg) apresentaram a maior carga, e o segundo quartil (0,28 a 0,88 mmHg) a menor.</p>
      <p>
        <table-wrap id="t1">
          <label>Tabela 1</label>
          <caption>
            <title>&#8211; Concentra&#231;&#227;o m&#233;dia de PM <bold>2,5</bold> e &#205;ndice Sociodemogr&#225;fico (SDI) para os estados brasileiros em 2019 e excesso de press&#227;o arterial sist&#243;lica (PAS) com base em estimativas observacionais e de interven&#231;&#227;o atribu&#237;das &#224; exposi&#231;&#227;o ao PM <bold>2,5</bold></title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup width="14%">
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead>
              <tr>
                <th>Regi&#227;o</th>
                <th>Estado</th>
                <th>SDI</th>
                <th>Quartil do SDI</th>
                <th>PM <sub><bold>2,5</bold></sub> m&#233;dia (&#956;g/m <sup><bold>3</bold></sup> )</th>
                <th>Excesso de PAS (mmHg) Estimativas observacionais</th>
                <th>Excesso de PAS (mmHg) Estimativas de interven&#231;&#227;o</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="center">Norte</td>
                <td align="center">Acre</td>
                <td align="center">0,56</td>
                <td align="center">1</td>
                <td align="center">9,01</td>
                <td align="center">0,24</td>
                <td align="center">0,76</td>
              </tr>
              <tr>
                <td align="center">Nordeste</td>
                <td align="center">Alagoas</td>
                <td align="center">0,52</td>
                <td align="center">1</td>
                <td align="center">10,20</td>
                <td align="center">0,31</td>
                <td align="center">0,99</td>
              </tr>
              <tr>
                <td align="center">Norte</td>
                <td align="center">Amap&#225;</td>
                <td align="center">0,64</td>
                <td align="center">3</td>
                <td align="center">10,97</td>
                <td align="center">0,36</td>
                <td align="center">1,13</td>
              </tr>
              <tr>
                <td align="center">Norte</td>
                <td align="center">Amazonas</td>
                <td align="center">0,6</td>
                <td align="center">2</td>
                <td align="center">8,47</td>
                <td align="center">0,21</td>
                <td align="center">0,66</td>
              </tr>
              <tr>
                <td align="center">Nordeste</td>
                <td align="center">Bahia</td>
                <td align="center">0,56</td>
                <td align="center">1</td>
                <td align="center">9,92</td>
                <td align="center">0,30</td>
                <td align="center">0,94</td>
              </tr>
              <tr>
                <td align="center">Nordeste</td>
                <td align="center">Cear&#225;</td>
                <td align="center">0,56</td>
                <td align="center">1</td>
                <td align="center">11,11</td>
                <td align="center">0,37</td>
                <td align="center">1,16</td>
              </tr>
              <tr>
                <td align="center">Centro-Oeste</td>
                <td align="center">Distrito Federal</td>
                <td align="center">0,78</td>
                <td align="center">4</td>
                <td align="center">11,34</td>
                <td align="center">0,38</td>
                <td align="center">1,20</td>
              </tr>
              <tr>
                <td align="center">Sudeste</td>
                <td align="center">Esp&#237;rito Santo</td>
                <td align="center">0,66</td>
                <td align="center">4</td>
                <td align="center">10,77</td>
                <td align="center">0,35</td>
                <td align="center">1,10</td>
              </tr>
              <tr>
                <td align="center">Centro-Oeste</td>
                <td align="center">Goi&#225;s</td>
                <td align="center">0,63</td>
                <td align="center">3</td>
                <td align="center">11,29</td>
                <td align="center">0,38</td>
                <td align="center">1,20</td>
              </tr>
              <tr>
                <td align="center">Nordeste</td>
                <td align="center">Maranh&#227;o</td>
                <td align="center">0,44</td>
                <td align="center">1</td>
                <td align="center">10,61</td>
                <td align="center">0,34</td>
                <td align="center">1,07</td>
              </tr>
              <tr>
                <td align="center">Centro-Oeste</td>
                <td align="center">Mato Grosso</td>
                <td align="center">0,64</td>
                <td align="center">3</td>
                <td align="center">9,52</td>
                <td align="center">0,27</td>
                <td align="center">0,86</td>
              </tr>
              <tr>
                <td align="center">Centro-Oeste</td>
                <td align="center">Mato Grosso do Sul</td>
                <td align="center">0,64</td>
                <td align="center">3</td>
                <td align="center">10,36</td>
                <td align="center">0,32</td>
                <td align="center">1,02</td>
              </tr>
              <tr>
                <td align="center">Sudeste</td>
                <td align="center">Minas Gerais</td>
                <td align="center">0,64</td>
                <td align="center">3</td>
                <td align="center">12,89</td>
                <td align="center">0,47</td>
                <td align="center">1,50</td>
              </tr>
              <tr>
                <td align="center">Norte</td>
                <td align="center">Par&#225;</td>
                <td align="center">0,57</td>
                <td align="center">2</td>
                <td align="center">10,08</td>
                <td align="center">0,30</td>
                <td align="center">0,96</td>
              </tr>
              <tr>
                <td align="center">Nordeste</td>
                <td align="center">Para&#237;ba</td>
                <td align="center">0,55</td>
                <td align="center">1</td>
                <td align="center">10,74</td>
                <td align="center">0,34</td>
                <td align="center">1,09</td>
              </tr>
              <tr>
                <td align="center">Sul</td>
                <td align="center">Paran&#225;</td>
                <td align="center">0,66</td>
                <td align="center">4</td>
                <td align="center">9,79</td>
                <td align="center">0,29</td>
                <td align="center">0,91</td>
              </tr>
              <tr>
                <td align="center">Nordeste</td>
                <td align="center">Pernambuco</td>
                <td align="center">0,57</td>
                <td align="center">2</td>
                <td align="center">10,50</td>
                <td align="center">0,33</td>
                <td align="center">1,05</td>
              </tr>
              <tr>
                <td align="center">Nordeste</td>
                <td align="center">Piau&#237;</td>
                <td align="center">0,51</td>
                <td align="center">1</td>
                <td align="center">11,11</td>
                <td align="center">0,37</td>
                <td align="center">1,16</td>
              </tr>
              <tr>
                <td align="center">Sudeste</td>
                <td align="center">Rio de Janeiro</td>
                <td align="center">0,7</td>
                <td align="center">4</td>
                <td align="center">13,91</td>
                <td align="center">0,53</td>
                <td align="center">1,69</td>
              </tr>
              <tr>
                <td align="center">Nordeste</td>
                <td align="center">Rio Grande do Norte</td>
                <td align="center">0,58</td>
                <td align="center">2</td>
                <td align="center">11,15</td>
                <td align="center">0,37</td>
                <td align="center">1,17</td>
              </tr>
              <tr>
                <td align="center">Sul</td>
                <td align="center">Rio Grande do Sul</td>
                <td align="center">0,68</td>
                <td align="center">4</td>
                <td align="center">10,50</td>
                <td align="center">0,33</td>
                <td align="center">1,04</td>
              </tr>
              <tr>
                <td align="center">Norte</td>
                <td align="center">Rond&#244;nia</td>
                <td align="center">0,61</td>
                <td align="center">2</td>
                <td align="center">8,26</td>
                <td align="center">0,20</td>
                <td align="center">0,62</td>
              </tr>
              <tr>
                <td align="center">Norte</td>
                <td align="center">Roraima</td>
                <td align="center">0,61</td>
                <td align="center">3</td>
                <td align="center">10,74</td>
                <td align="center">0,34</td>
                <td align="center">1,09</td>
              </tr>
              <tr>
                <td align="center">Sul</td>
                <td align="center">Santa Catarina</td>
                <td align="center">0,69</td>
                <td align="center">4</td>
                <td align="center">10,93</td>
                <td align="center">0,36</td>
                <td align="center">1,13</td>
              </tr>
              <tr>
                <td align="center">Sudeste</td>
                <td align="center">S&#227;o Paulo</td>
                <td align="center">0,7</td>
                <td align="center">4</td>
                <td align="center">13,87</td>
                <td align="center">0,53</td>
                <td align="center">1,68</td>
              </tr>
              <tr>
                <td align="center">Nordeste</td>
                <td align="center">Sergipe</td>
                <td align="center">0,58</td>
                <td align="center">2</td>
                <td align="center">9,28</td>
                <td align="center">0,26</td>
                <td align="center">0,81</td>
              </tr>
              <tr>
                <td align="center">Norte</td>
                <td align="center">Tocantins</td>
                <td align="center">0,58</td>
                <td align="center">2</td>
                <td align="center">10,01</td>
                <td align="center">0,30</td>
                <td align="center">0,95</td>
              </tr>
              <tr>
                <td align="center" colspan="2">
                  <bold>Brasil</bold>
                </td>
                <td align="center">0,64</td>
                <td align="center">3</td>
                <td align="center">11,65</td>
                <td align="center">0,40</td>
                <td align="center">1,26</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
      </p>
      <p>
        <fig id="f01">
          <label>Figura 1</label>
          <caption>
            <title>&#8211; Varia&#231;&#227;o da exposi&#231;&#227;o ao material particulado fino &lt; 2,5 m&#237;crons (PM 2,5 ) em n&#237;vel estadual no Brasil. Medido em &#956;g/m 3 .</title>
          </caption>
          <graphic xlink:href="1678-4170-abc-120-11-e20230347-30347-gf01.tif"/></fig>
      </p>
      <p>
        <fig id="f02">
          <label>Figura 2</label>
          <caption>
            <title>&#8211; Excesso de press&#227;o arterial sist&#243;lica (PAS) com base em estimativas observacionais e de interven&#231;&#227;o atribu&#237;das &#224; exposi&#231;&#227;o ao PM 2,5 no Brasil de acordo com regi&#227;o e quartis do &#205;ndice Sociodemogr&#225;fico (SDI).</title>
          </caption>
          <graphic xlink:href="1678-4170-abc-120-11-e20230347-30347-gf02.tif"/></fig>
      </p>
    </sec>
    <sec sec-type="discussion">
      <title>Discuss&#227;o</title>
      <p>No contexto da crise de hipertens&#227;o no Brasil, com 1 a cada 4 brasileiros relatando hipertens&#227;o, nossos resultados destacam a contribui&#231;&#227;o menos reconhecida da exposi&#231;&#227;o ao PM <sub>2,5</sub> para o aumento da PAS. <sup><xref ref-type="bibr" rid="B2">2</xref></sup> Embora a eleva&#231;&#227;o da PAS no Brasil seja inferior &#224; m&#233;dia global (0,40 versus 2,4 mmHg, estimativas observacionais), foram observadas disparidades interestaduais, regionais e sociodemogr&#225;ficas substanciais em rela&#231;&#227;o &#224; magnitude do excesso de PAS, particularmente na Regi&#227;o Sudeste, onde os n&#237;veis de PM <sub>2,5</sub> tamb&#233;m s&#227;o os mais altos. <sup><xref ref-type="bibr" rid="B8">8</xref></sup> Al&#233;m disso, o achado de que todos os estados brasileiros possuem concentra&#231;&#245;es de PM <sub>2,5</sub> acima do limite atual da OMS enfatiza a necessidade de programas nacionais de polui&#231;&#227;o do ar mais fortes e coesos, especialmente nos estados do Rio de Janeiro e de S&#227;o Paulo, que cont&#234;m as maiores &#225;reas urbanas do Brasil. <sup><xref ref-type="bibr" rid="B12">12</xref></sup> Dado o impacto dos combust&#237;veis f&#243;sseis na polui&#231;&#227;o do ar em &#225;reas urbanas, essas iniciativas devem se concentrar na prioriza&#231;&#227;o do uso de fontes de energia n&#227;o f&#243;sseis, bem como na melhoria da infraestrutura para apoiar sistemas maiores de transporte p&#250;blico e promover o uso de ve&#237;culos de energia limpa. <sup><xref ref-type="bibr" rid="B13">13</xref></sup> Al&#233;m disso, devido &#224;s altas concentra&#231;&#245;es de PM <sub>2,5</sub> no estado de S&#227;o Paulo, o maior produtor de a&#231;&#250;car do Brasil, deve-se tamb&#233;m considerar o impacto da queima de cana-de-a&#231;&#250;car antes da colheita e da imposi&#231;&#227;o de maiores restri&#231;&#245;es industriais, especialmente porque o polui&#231;&#227;o do ar durante a temporada das queimadas tem sido associada ao aumento de interna&#231;&#245;es hospitalares. <sup><xref ref-type="bibr" rid="B4">4</xref> , <xref ref-type="bibr" rid="B14">14</xref></sup></p>
      <p>Embora, no presente estudo, a Regi&#227;o Norte tenha a menor concentra&#231;&#227;o de PM <sub>2,5</sub> , outros estudos que utilizaram diferentes m&#233;todos de estimativa de PM <sub>2,5</sub> descreveram uma maior carga de polui&#231;&#227;o do ar na regi&#227;o. <sup><xref ref-type="bibr" rid="B15">15</xref></sup> De fato, a Regi&#227;o Norte desempenha um papel crucial na polui&#231;&#227;o do ar no Brasil. <sup><xref ref-type="bibr" rid="B16">16</xref></sup> A queima de biomassa que ocorre na Amaz&#244;nia, por exemplo, emite grandes quantidades de PM <sub>2,5</sub> , que n&#227;o somente impactam &#225;reas pr&#243;ximas aos inc&#234;ndios, mas tamb&#233;m causam doen&#231;as e mortes prematuras em &#225;reas distantes deles. <sup><xref ref-type="bibr" rid="B16">16</xref></sup> Al&#233;m disso, a regi&#227;o tamb&#233;m &#233; descrita como um <italic>hotspot</italic> socioclim&#225;tico, combinando altos n&#237;veis de vulnerabilidade social e ambiental, aumentando a necessidade de interven&#231;&#245;es socioambientais e de sa&#250;de direcionadas na regi&#227;o. <sup><xref ref-type="bibr" rid="B16">16</xref></sup></p>
      <p>Por &#250;ltimo, embora o valor num&#233;rico do aumento da PAS possa parecer dispens&#225;vel, deve ser visto &#224; luz do seu impacto em um grande n&#250;mero de indiv&#237;duos e considerado como um componente de um continuum de exposi&#231;&#245;es que t&#234;m um efeito aditivo na press&#227;o arterial. Al&#233;m disso, t&#234;m sido propostas m&#250;ltiplas vias biol&#243;gicas que medeiam o impacto do PM <sub>2,5</sub> na press&#227;o arterial, incluindo inflama&#231;&#227;o sist&#234;mica, respostas oxidativas e disfun&#231;&#227;o endotelial. <sup><xref ref-type="bibr" rid="B17">17</xref></sup> Estudos recentes da China tamb&#233;m implicam a ativa&#231;&#227;o do eixo hipot&#225;lamo-hip&#243;fise-adrenal em resposta &#224; exposi&#231;&#227;o a altos n&#237;veis de PM <sub>2,5</sub> , culminando em aumentos significativos nos horm&#244;nios s&#233;ricos do estresse (cortisol, cortisona, epinefrina e norepinefrina). <sup><xref ref-type="bibr" rid="B17">17</xref> , <xref ref-type="bibr" rid="B18">18</xref></sup></p>
      <p>As limita&#231;&#245;es do presente estudo incluem aquelas inerentes ao seu car&#225;ter ecol&#243;gico, sua depend&#234;ncia de dados secund&#225;rios e an&#225;lise em n&#237;vel estadual, que pode subestimar o efeito nas popula&#231;&#245;es de &#225;reas metropolitanas industrializadas.</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <title>Refer&#234;ncias</title>
      <ref id="B1">
        <label>1</label>
        <mixed-citation>1. Fuchs FD, Whelton PK. High Blood Pressure and Cardiovascular Disease. Hypertension. 2020;75(2):285-92. doi: 10.1161/HYPERTENSIONAHA.119.14240.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Fuchs</surname>
              <given-names>FD</given-names>
            </name>
            <name>
              <surname>Whelton</surname>
              <given-names>PK</given-names>
            </name>
          </person-group>
          <article-title>High Blood Pressure and Cardiovascular Disease</article-title>
          <source>Hypertension</source>
          <year>2020</year>
          <volume>75</volume>
          <issue>2</issue>
          <fpage>285</fpage>
          <lpage>292</lpage>
          <pub-id pub-id-type="doi">10.1161/HYPERTENSIONAHA.119.14240</pub-id>
        </element-citation>
      </ref>
      <ref id="B2">
        <label>2</label>
        <mixed-citation>2. Malta DC, Bernal RTI, Prates EJS, Vasconcelos NM, Gomes CS, Stopa SR, et al. Self-Reported Arterial Hypertension, Use of Health Services and Guidelines for Care in Brazilian Population: National Health Survey, 2019. Epidemiol Serv Saude. 2022;31():e2021369. doi: 10.1590/SS2237-9622202200012.especial</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Malta</surname>
              <given-names>DC</given-names>
            </name>
            <name>
              <surname>Bernal</surname>
              <given-names>RTI</given-names>
            </name>
            <name>
              <surname>Prates</surname>
              <given-names>EJS</given-names>
            </name>
            <name>
              <surname>Vasconcelos</surname>
              <given-names>NM</given-names>
            </name>
            <name>
              <surname>Gomes</surname>
              <given-names>CS</given-names>
            </name>
            <name>
              <surname>Stopa</surname>
              <given-names>SR</given-names>
            </name>
            <etal>et al</etal>
          </person-group>
          <article-title>Self-Reported Arterial Hypertension, Use of Health Services and Guidelines for Care in Brazilian Population: National Health Survey, 2019</article-title>
          <source>Epidemiol Serv Saude</source>
          <year>2022</year>
          <volume>31</volume>
          <elocation-id>e2021369</elocation-id>
          <pub-id pub-id-type="doi">10.1590/SS2237-9622202200012.especial</pub-id>
        </element-citation>
      </ref>
      <ref id="B3">
        <label>3</label>
        <mixed-citation>3. Rajagopalan S, Al-Kindi SG, Brook RD. Air Pollution and Cardiovascular Disease: JACC State-of-the-Art Review. J Am Coll Cardiol. 2018;72(17):2054-70. doi: 10.1016/j.jacc.2018.07.099.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Rajagopalan</surname>
              <given-names>S</given-names>
            </name>
            <name>
              <surname>Al-Kindi</surname>
              <given-names>SG</given-names>
            </name>
            <name>
              <surname>Brook</surname>
              <given-names>RD</given-names>
            </name>
          </person-group>
          <article-title>Air Pollution and Cardiovascular Disease: JACC State-of-the-Art Review</article-title>
          <source>J Am Coll Cardiol</source>
          <year>2018</year>
          <volume>72</volume>
          <issue>17</issue>
          <fpage>2054</fpage>
          <lpage>2070</lpage>
          <pub-id pub-id-type="doi">10.1016/j.jacc.2018.07.099</pub-id>
        </element-citation>
      </ref>
      <ref id="B4">
        <label>4</label>
        <mixed-citation>4. Santos UP, Arbex MA, Braga ALF, Mizutani RF, Can&#231;ado JED, Terra-Filho M, et al. Environmental Air Pollution: Respiratory Effects. J Bras Pneumol. 2021;47(1):e20200267. doi: 10.36416/1806-3756/e20200267.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Santos</surname>
              <given-names>UP</given-names>
            </name>
            <name>
              <surname>Arbex</surname>
              <given-names>MA</given-names>
            </name>
            <name>
              <surname>Braga</surname>
              <given-names>ALF</given-names>
            </name>
            <name>
              <surname>Mizutani</surname>
              <given-names>RF</given-names>
            </name>
            <name>
              <surname>Can&#231;ado</surname>
              <given-names>JED</given-names>
            </name>
            <name>
              <surname>Terra-Filho</surname>
              <given-names>M</given-names>
            </name>
            <etal>et al</etal>
          </person-group>
          <article-title>Environmental Air Pollution: Respiratory Effects</article-title>
          <source>J Bras Pneumol</source>
          <year>2021</year>
          <volume>47</volume>
          <issue>1</issue>
          <elocation-id>e20200267</elocation-id>
          <pub-id pub-id-type="doi">10.36416/1806-3756/e20200267</pub-id>
        </element-citation>
      </ref>
      <ref id="B5">
        <label>5</label>
        <mixed-citation>5. Chiarelli PS, Pereira LAA, Saldiva PHN, Ferreira Filho C, Garcia MLB, Braga ALF, et al. The Association Between Air Pollution and Blood Pressure in Traffic Controllers in Santo Andr&#233;, S&#227;o Paulo, Brazil. Environ Res. 2011;111(5):650-5. doi: 10.1016/j.envres.2011.04.007.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Chiarelli</surname>
              <given-names>PS</given-names>
            </name>
            <name>
              <surname>Pereira</surname>
              <given-names>LAA</given-names>
            </name>
            <name>
              <surname>Saldiva</surname>
              <given-names>PHN</given-names>
            </name>
            <name>
              <surname>Ferreira</surname>
              <given-names>C</given-names>
              <suffix>Filho</suffix>
            </name>
            <name>
              <surname>Garcia</surname>
              <given-names>MLB</given-names>
            </name>
            <name>
              <surname>Braga</surname>
              <given-names>ALF</given-names>
            </name>
            <etal>et al</etal>
          </person-group>
          <article-title>The Association Between Air Pollution and Blood Pressure in Traffic Controllers in Santo Andr&#233;, S&#227;o Paulo, Brazil</article-title>
          <source>Environ Res</source>
          <year>2011</year>
          <volume>111</volume>
          <issue>5</issue>
          <fpage>650</fpage>
          <lpage>655</lpage>
          <pub-id pub-id-type="doi">10.1016/j.envres.2011.04.007</pub-id>
        </element-citation>
      </ref>
      <ref id="B6">
        <label>6</label>
        <mixed-citation>6. Santos UP, Braga ALF, Garcia MLB, Pereira LAA, Lin CA, Chiarelli PS, et al. Exposure to Fine Particles Increases Blood Pressure of Hypertensive Outdoor Workers: a Panel Study. Environ Res. 2019;174:88-94. doi: 10.1016/j.envres.2019.04.021.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Santos</surname>
              <given-names>UP</given-names>
            </name>
            <name>
              <surname>Braga</surname>
              <given-names>ALF</given-names>
            </name>
            <name>
              <surname>Garcia</surname>
              <given-names>MLB</given-names>
            </name>
            <name>
              <surname>Pereira</surname>
              <given-names>LAA</given-names>
            </name>
            <name>
              <surname>Lin</surname>
              <given-names>CA</given-names>
            </name>
            <name>
              <surname>Chiarelli</surname>
              <given-names>PS</given-names>
            </name>
            <etal>et al</etal>
          </person-group>
          <article-title>Exposure to Fine Particles Increases Blood Pressure of Hypertensive Outdoor Workers: a Panel Study</article-title>
          <source>Environ Res</source>
          <year>2019</year>
          <volume>174</volume>
          <fpage>88</fpage>
          <lpage>94</lpage>
          <pub-id pub-id-type="doi">10.1016/j.envres.2019.04.021</pub-id>
        </element-citation>
      </ref>
      <ref id="B7">
        <label>7</label>
        <mixed-citation>7. GBD 2019 Risk Factors Collaborators. Global Burden of 87 Risk Factors in 204 Countries and Territories, 1990-2019: a Systematic Analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396(10258):1223-49. doi: 10.1016/S0140-6736(20)30752-2.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <collab>GBD</collab>
            <collab>2019 Risk Factors Collaborators</collab>
          </person-group>
          <article-title>Global Burden of 87 Risk Factors in 204 Countries and Territories, 1990-2019: a Systematic Analysis for the Global Burden of Disease Study 2019</article-title>
          <source>Lancet</source>
          <year>2020</year>
          <volume>396</volume>
          <issue>10258</issue>
          <fpage>1223</fpage>
          <lpage>1249</lpage>
          <pub-id pub-id-type="doi">10.1016/S0140-6736(20)30752-2</pub-id>
        </element-citation>
      </ref>
      <ref id="B8">
        <label>8</label>
        <mixed-citation>8. Brook RD, Motairek I, Rajagopalan S, Al-Kindi S. Excess Global Blood Pressure Associated with Fine Particulate Matter Air Pollution Levels Exceeding World Health Organization Guidelines. J Am Heart Assoc. 2023;12(8):e029206. doi: 10.1161/JAHA.122.029206.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Brook</surname>
              <given-names>RD</given-names>
            </name>
            <name>
              <surname>Motairek</surname>
              <given-names>I</given-names>
            </name>
            <name>
              <surname>Rajagopalan</surname>
              <given-names>S</given-names>
            </name>
            <name>
              <surname>Al-Kindi</surname>
              <given-names>S</given-names>
            </name>
          </person-group>
          <article-title>Excess Global Blood Pressure Associated with Fine Particulate Matter Air Pollution Levels Exceeding World Health Organization Guidelines</article-title>
          <source>J Am Heart Assoc</source>
          <year>2023</year>
          <volume>12</volume>
          <issue>8</issue>
          <elocation-id>e029206</elocation-id>
          <pub-id pub-id-type="doi">10.1161/JAHA.122.029206</pub-id>
        </element-citation>
      </ref>
      <ref id="B9">
        <label>9</label>
        <mixed-citation>9. Instituto Brasileiro de Geografia e Estat&#237;stica. Divis&#245;es Regionais do Brasil. IBGE [Internet]. 2023 [cited 2023 Nov 6]. Available from: <ext-link ext-link-type="uri" xlink:href="https://www.ibge.gov.br/geociencias/organizacao-do-territorio/divisao-regional/15778-divisoes-regionais-do-brasil.html">https://www.ibge.gov.br/geociencias/organizacao-do-territorio/divisao-regional/15778-divisoes-regionais-do-brasil.html</ext-link>.</mixed-citation>
        <element-citation publication-type="webpage">
          <person-group person-group-type="author">
            <collab>Instituto Brasileiro de Geografia e Estat&#237;stica</collab>
          </person-group>
          <source>Divis&#245;es Regionais do Brasil</source>
          <publisher-name>IBGE</publisher-name>
          <comment>Internet</comment>
          <year>2023</year>
          <date-in-citation content-type="cited-date">cited 2023 Nov 6</date-in-citation>
          <comment>
            <ext-link ext-link-type="uri" xlink:href="https://www.ibge.gov.br/geociencias/organizacao-do-territorio/divisao-regional/15778-divisoes-regionais-do-brasil.html">https://www.ibge.gov.br/geociencias/organizacao-do-territorio/divisao-regional/15778-divisoes-regionais-do-brasil.html</ext-link>
          </comment>
        </element-citation>
      </ref>
      <ref id="B10">
        <label>10</label>
        <mixed-citation>10. Niu Z, Duan Z, Yu H, Xue L, Liu F, Yu D, et al. Association Between Long-Term Exposure to Ambient Particulate Matter and Blood Pressure, Hypertension: an Updated Systematic Review and Meta-Analysis. Int J Environ Health Res. 2023;33(3):268-83. doi: 10.1080/09603123.2021.2022106.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Niu</surname>
              <given-names>Z</given-names>
            </name>
            <name>
              <surname>Duan</surname>
              <given-names>Z</given-names>
            </name>
            <name>
              <surname>Yu</surname>
              <given-names>H</given-names>
            </name>
            <name>
              <surname>Xue</surname>
              <given-names>L</given-names>
            </name>
            <name>
              <surname>Liu</surname>
              <given-names>F</given-names>
            </name>
            <name>
              <surname>Yu</surname>
              <given-names>D</given-names>
            </name>
            <etal>et al</etal>
          </person-group>
          <article-title>Association Between Long-Term Exposure to Ambient Particulate Matter and Blood Pressure, Hypertension: an Updated Systematic Review and Meta-Analysis</article-title>
          <source>Int J Environ Health Res</source>
          <year>2023</year>
          <volume>33</volume>
          <issue>3</issue>
          <fpage>268</fpage>
          <lpage>283</lpage>
          <pub-id pub-id-type="doi">10.1080/09603123.2021.2022106</pub-id>
        </element-citation>
      </ref>
      <ref id="B11">
        <label>11</label>
        <mixed-citation>11. Walzer D, Gordon T, Thorpe L, Thurston G, Xia Y, Zhong H, et al. Effects of Home Particulate Air Filtration on Blood Pressure: a Systematic Review. Hypertension. 2020;76(1):44-50. doi: 10.1161/HYPERTENSIONAHA.119.14456.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Walzer</surname>
              <given-names>D</given-names>
            </name>
            <name>
              <surname>Gordon</surname>
              <given-names>T</given-names>
            </name>
            <name>
              <surname>Thorpe</surname>
              <given-names>L</given-names>
            </name>
            <name>
              <surname>Thurston</surname>
              <given-names>G</given-names>
            </name>
            <name>
              <surname>Xia</surname>
              <given-names>Y</given-names>
            </name>
            <name>
              <surname>Zhong</surname>
              <given-names>H</given-names>
            </name>
            <etal>et al</etal>
          </person-group>
          <article-title>Effects of Home Particulate Air Filtration on Blood Pressure: a Systematic Review</article-title>
          <source>Hypertension</source>
          <year>2020</year>
          <volume>76</volume>
          <issue>1</issue>
          <fpage>44</fpage>
          <lpage>50</lpage>
          <pub-id pub-id-type="doi">10.1161/HYPERTENSIONAHA.119.14456</pub-id>
        </element-citation>
      </ref>
      <ref id="B12">
        <label>12</label>
        <mixed-citation>12. Instituto Brasileiro de Geografia e Estat&#237;stica. 2022 Census [Internet]. Rio de Janeiro: IBGE; 2022 [cited 2023 Nov 6]. Available from: <ext-link ext-link-type="uri" xlink:href="https://www.ibge.gov.br/en/statistics/social/population/22836-2020-census-censo4.html">https://www.ibge.gov.br/en/statistics/social/population/22836-2020-census-censo4.html</ext-link> </mixed-citation>
        <element-citation publication-type="report">
          <person-group person-group-type="author">
            <collab>Instituto Brasileiro de Geografia e Estat&#237;stica</collab>
          </person-group>
          <source>2022 Census</source>
          <comment>Internet</comment>
          <publisher-loc>Rio de Janeiro</publisher-loc>
          <publisher-name>IBGE</publisher-name>
          <year>2022</year>
          <date-in-citation content-type="cited-date">cited 2023 Nov 6</date-in-citation>
          <comment>
            <ext-link ext-link-type="uri" xlink:href="https://www.ibge.gov.br/en/statistics/social/population/22836-2020-census-censo4.html">https://www.ibge.gov.br/en/statistics/social/population/22836-2020-census-censo4.html</ext-link>
          </comment>
        </element-citation>
      </ref>
      <ref id="B13">
        <label>13</label>
        <mixed-citation>13. Landrigan PJ, Fuller R, Acosta NJR, Adeyi O, Arnold R, Basu NN, et al. The Lancet Commission on Pollution and Health. Lancet. 2018;391(10119):462-512. doi: 10.1016/S0140-6736(17)32345-0.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Landrigan</surname>
              <given-names>PJ</given-names>
            </name>
            <name>
              <surname>Fuller</surname>
              <given-names>R</given-names>
            </name>
            <name>
              <surname>Acosta</surname>
              <given-names>NJR</given-names>
            </name>
            <name>
              <surname>Adeyi</surname>
              <given-names>O</given-names>
            </name>
            <name>
              <surname>Arnold</surname>
              <given-names>R</given-names>
            </name>
            <name>
              <surname>Basu</surname>
              <given-names>NN</given-names>
            </name>
            <etal>et al</etal>
          </person-group>
          <article-title>The Lancet Commission on Pollution and Health</article-title>
          <source>Lancet</source>
          <year>2018</year>
          <volume>391</volume>
          <issue>10119</issue>
          <fpage>462</fpage>
          <lpage>512</lpage>
          <pub-id pub-id-type="doi">10.1016/S0140-6736(17)32345-0</pub-id>
        </element-citation>
      </ref>
      <ref id="B14">
        <label>14</label>
        <mixed-citation>14. Arbex MA, Martins LC, Oliveira RC, Pereira LA, Arbex FF, Can&#231;ado JE, et al. Air Pollution from Biomass Burning and Asthma Hospital Admissions in a Sugar Cane Plantation Area in Brazil. J Epidemiol Community Health. 2007;61(5):395-400. doi: 10.1136/jech.2005.044743.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Arbex</surname>
              <given-names>MA</given-names>
            </name>
            <name>
              <surname>Martins</surname>
              <given-names>LC</given-names>
            </name>
            <name>
              <surname>Oliveira</surname>
              <given-names>RC</given-names>
            </name>
            <name>
              <surname>Pereira</surname>
              <given-names>LA</given-names>
            </name>
            <name>
              <surname>Arbex</surname>
              <given-names>FF</given-names>
            </name>
            <name>
              <surname>Can&#231;ado</surname>
              <given-names>JE</given-names>
            </name>
            <etal>et al</etal>
          </person-group>
          <article-title>Air Pollution from Biomass Burning and Asthma Hospital Admissions in a Sugar Cane Plantation Area in Brazil</article-title>
          <source>J Epidemiol Community Health</source>
          <year>2007</year>
          <volume>61</volume>
          <issue>5</issue>
          <fpage>395</fpage>
          <lpage>400</lpage>
          <pub-id pub-id-type="doi">10.1136/jech.2005.044743</pub-id>
        </element-citation>
      </ref>
      <ref id="B15">
        <label>15</label>
        <mixed-citation>15. Yu P, Xu R, Li S, Coelho MSZS, Saldiva PHN, Sim MR, et al. Loss of Life Expectancy from PM2.5 in Brazil: A National Study from 2010 to 2018. Environ Int. 2022;166:107350. doi: 10.1016/j.envint.2022.107350.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Yu</surname>
              <given-names>P</given-names>
            </name>
            <name>
              <surname>Xu</surname>
              <given-names>R</given-names>
            </name>
            <name>
              <surname>Li</surname>
              <given-names>S</given-names>
            </name>
            <name>
              <surname>Coelho</surname>
              <given-names>MSZS</given-names>
            </name>
            <name>
              <surname>Saldiva</surname>
              <given-names>PHN</given-names>
            </name>
            <name>
              <surname>Sim</surname>
              <given-names>MR</given-names>
            </name>
            <etal>et al</etal>
          </person-group>
          <article-title>Loss of Life Expectancy from PM2.5 in Brazil: A National Study from 2010 to 2018</article-title>
          <source>Environ Int</source>
          <year>2022</year>
          <volume>166</volume>
          <fpage>107350</fpage>
          <pub-id pub-id-type="doi">10.1016/j.envint.2022.107350</pub-id>
        </element-citation>
      </ref>
      <ref id="B16">
        <label>16</label>
        <mixed-citation>16. Moura FR, Silva FMR Jr. 2030 Agenda: Discussion on Brazilian Priorities Facing air Pollution and Climate Change Challenges. Environ Sci Pollut Res Int. 2023;30(3):8376-90. doi: 10.1007/s11356-022-24601-5.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Moura</surname>
              <given-names>FR</given-names>
            </name>
            <name>
              <surname>Silva</surname>
              <given-names>FMR</given-names>
              <suffix>Jr</suffix>
            </name>
          </person-group>
          <article-title>2030 Agenda: Discussion on Brazilian Priorities Facing air Pollution and Climate Change Challenges</article-title>
          <source>Environ Sci Pollut Res Int</source>
          <year>2023</year>
          <volume>30</volume>
          <issue>3</issue>
          <fpage>8376</fpage>
          <lpage>8390</lpage>
          <pub-id pub-id-type="doi">10.1007/s11356-022-24601-5</pub-id>
        </element-citation>
      </ref>
      <ref id="B17">
        <label>17</label>
        <mixed-citation>17. Lin H, Guo Y, Zheng Y, Di Q, Liu T, Xiao J, et al. Long-Term Effects of Ambient PM2.5 on Hypertension and Blood Pressure and Attributable Risk Among Older Chinese Adults. Hypertension. 2017;69(5):806-12. doi: 10.1161/HYPERTENSIONAHA.116.08839.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Lin</surname>
              <given-names>H</given-names>
            </name>
            <name>
              <surname>Guo</surname>
              <given-names>Y</given-names>
            </name>
            <name>
              <surname>Zheng</surname>
              <given-names>Y</given-names>
            </name>
            <name>
              <surname>Di</surname>
              <given-names>Q</given-names>
            </name>
            <name>
              <surname>Liu</surname>
              <given-names>T</given-names>
            </name>
            <name>
              <surname>Xiao</surname>
              <given-names>J</given-names>
            </name>
            <etal>et al</etal>
          </person-group>
          <article-title>Long-Term Effects of Ambient PM2.5 on Hypertension and Blood Pressure and Attributable Risk Among Older Chinese Adults</article-title>
          <source>Hypertension</source>
          <year>2017</year>
          <volume>69</volume>
          <issue>5</issue>
          <fpage>806</fpage>
          <lpage>812</lpage>
          <pub-id pub-id-type="doi">10.1161/HYPERTENSIONAHA.116.08839</pub-id>
        </element-citation>
      </ref>
      <ref id="B18">
        <label>18</label>
        <mixed-citation>18. Fan F, Wang S, Zhang Y, Xu D, Jia J, Li J, et al. Acute Effects of High-Level PM2.5 Exposure on Central Blood Pressure. Hypertension. 2019;74(6):1349-56. doi: 10.1161/HYPERTENSIONAHA.119.13408.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Fan</surname>
              <given-names>F</given-names>
            </name>
            <name>
              <surname>Wang</surname>
              <given-names>S</given-names>
            </name>
            <name>
              <surname>Zhang</surname>
              <given-names>Y</given-names>
            </name>
            <name>
              <surname>Xu</surname>
              <given-names>D</given-names>
            </name>
            <name>
              <surname>Jia</surname>
              <given-names>J</given-names>
            </name>
            <name>
              <surname>Li</surname>
              <given-names>J</given-names>
            </name>
            <etal>et al</etal>
          </person-group>
          <article-title>Acute Effects of High-Level PM2.5 Exposure on Central Blood Pressure</article-title>
          <source>Hypertension</source>
          <year>2019</year>
          <volume>74</volume>
          <issue>6</issue>
          <fpage>1349</fpage>
          <lpage>1356</lpage>
          <pub-id pub-id-type="doi">10.1161/HYPERTENSIONAHA.119.13408</pub-id>
        </element-citation>
      </ref>
    </ref-list>
    <fn-group>
      <fn fn-type="other">
        <p>Vincula&#231;&#227;o acad&#234;mica</p>
        <p>N&#227;o h&#225; vincula&#231;&#227;o deste estudo a programas de p&#243;s-gradua&#231;&#227;o.</p>
        <p>Aprova&#231;&#227;o &#233;tica e consentimento informado</p>
        <p>Este artigo n&#227;o cont&#233;m estudos com humanos ou animais realizados por nenhum dos autores.</p>
      </fn>
    </fn-group>
    <fn-group>
      <fn fn-type="supported-by">
        <p>Fontes de financiamento: O presente estudo n&#227;o teve fontes de financiamento externas.</p>
      </fn>
    </fn-group>
  </back>
  <sub-article article-type="translation" id="TRen" xml:lang="en">
    <front-stub>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Letter</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Excess Systolic Blood Pressure Associated with Fine Particulate Matter Air Pollution above the WHO Guidelines in Brazil</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">0000-0002-5116-5062</contrib-id>
          <name>
            <surname>Salerno</surname>
            <given-names>Pedro Rafael Vieira de Oliveira</given-names>
          </name>
          <role>Conception and design of the research and Critical revision of the manuscript for important intellectual content</role>
          <role>Acquisition of data</role>
          <role>Analysis and interpretation of the data</role>
          <role>Statistical analysis</role>
          <role>Writing of the manuscript</role>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Motairek</surname>
            <given-names>Issam</given-names>
          </name>
          <role>Conception and design of the research and Critical revision of the manuscript for important intellectual content</role>
          <role>Acquisition of data</role>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Dallan</surname>
            <given-names>Luis Augusto Palma</given-names>
          </name>
          <role>Conception and design of the research and Critical revision of the manuscript for important intellectual content</role>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Bourges-Sevenier</surname>
            <given-names>Brendan</given-names>
          </name>
          <role>Conception and design of the research and Critical revision of the manuscript for important intellectual content</role>
          <role>Writing of the manuscript</role>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Rajagopalan</surname>
            <given-names>Sanjay</given-names>
          </name>
          <role>Conception and design of the research and Critical revision of the manuscript for important intellectual content</role>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
          <xref ref-type="aff" rid="aff2001">
            <sup>2</sup>
          </xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Al-Kindi</surname>
            <given-names>Sadeer G.</given-names>
          </name>
          <role>Conception and design of the research and Critical revision of the manuscript for important intellectual content</role>
          <role>Statistical analysis</role>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
          <xref ref-type="aff" rid="aff2001">
            <sup>2</sup>
          </xref>
        </contrib>
      </contrib-group>
      <aff id="aff1001">
        <label> 1 </label>
        <country country="US">USA</country>
        <institution content-type="original"> Harrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, Ohio &#8211; USA </institution>
      </aff>
      <aff id="aff2001">
        <label> 2 </label>
        <country country="US">USA</country>
        <institution content-type="original"> Case Western Reserve University School of Medicine, Cleveland, Ohio &#8211; USA </institution>
      </aff>
      <author-notes>
        <corresp id="c01001">Mailing Address: Sadeer Al-Kindi &#8226; University Hospitals Harrington Heart and Vascular Institute Case Western Reserve University School of Medicine &#8211; 11100 Euclid Ave, Cleveland, OH 44106 &#8211; USA E-mail: Sadeer.Al-Kindi@uhhospitals.org</corresp>
        <fn fn-type="conflict">
          <p>Potential conflict of interest</p>
          <p>No potential conflict of interest relevant to this article was reported.</p>
          <p>Editor responsible for the review: Paulo B. Veiga Jardim</p>
        </fn>
      </author-notes>
      <kwd-group xml:lang="en">
        <kwd>Air Pollution</kwd>
        <kwd>Arterial Pressure</kwd>
        <kwd>Environment</kwd>
        <kwd>Public Health</kwd>
      </kwd-group>
    </front-stub>
    <body>
      <sec sec-type="intro">
        <title>Introduction</title>
        <p>Cardiovascular disease remains the leading cause of mortality worldwide, and hypertension has been implicated as having the highest association of causation among all of the cardiovascular disease risk factors. <sup><xref ref-type="bibr" rid="B1">1</xref></sup> Thus, unsurprisingly, hypertension is the main risk factor for death and the second major cause of disability-adjusted life years in Brazil, heavily impacting its population and national healthcare system. <sup><xref ref-type="bibr" rid="B2">2</xref></sup> It is also directly linked to air pollution, especially fine particulate matter &lt; 2.5 microns (PM <sub>2.5</sub> ), which has been identified as an independent risk factor for increased systolic blood pressure (SBP). <sup><xref ref-type="bibr" rid="B3">3</xref></sup> In Brazil, as in most countries, the main source of exposure to air pollution in urban areas primarily results from the burning of fossil fuels via vehicular traffic and industrial power generation, while, in rural Brazil, air pollution mainly results from the burning of biomass as well as deforestation. <sup><xref ref-type="bibr" rid="B4">4</xref></sup></p>
        <p>In Brazil, previous studies have been conducted investigating the effects of PM <sub>2.5</sub> exposure on blood pressure in outdoor workers who are most susceptible to ambient air pollution from vehicular emissions, such as traffic controllers, demonstrating the link between PM <sub>2.5</sub> concentration and increased SBP. <sup><xref ref-type="bibr" rid="B5">5</xref> , <xref ref-type="bibr" rid="B6">6</xref></sup> However, these studies tend to focus on metropolitan and urban regions. <sup><xref ref-type="bibr" rid="B5">5</xref> , <xref ref-type="bibr" rid="B6">6</xref></sup> Thus, due to Brazil&#8217;s large geographical size and regional diversity, there exists a substantial gap in knowledge in the less populated areas. In this study, we aimed to estimate the excess SBP attributable to PM <sub>2.5</sub> concentrations above the threshold of the World Health Organization (WHO) guidelines in Brazil, as well as in all its states and regions.</p>
      </sec>
      <sec sec-type="methods">
        <title>Methods</title>
        <p>We obtained the 2019 population-weighted PM <sub>2.5</sub> concentrations for the 26 Brazilian states and the Federal District from the Global Burden of Disease (GBD), an international collaboration effort to quantify levels and trends in health and provide publicly available data. <sup><xref ref-type="bibr" rid="B7">7</xref></sup> Both satellite and ground-level monitoring system models, as well as chemical transport models, were used by the GBD to estimate PM <sub>2.5</sub> concentrations in &#956;g/m <sup>3</sup> . <sup><xref ref-type="bibr" rid="B8">8</xref></sup> The states were also stratified according to the regions (North, Northeast, Midwest, Southeast, and South) determined by the Brazilian Institute of Geography and Statistics (IBGE) <sup><xref ref-type="bibr" rid="B9">9</xref></sup> and according to quartiles of the Socio-demographic Index (SDI). <sup><xref ref-type="bibr" rid="B7">7</xref></sup> The SDI, a tool developed by the GBD, is a composite indicator of background social and economic conditions affecting health outcomes that ranges from 0 to 1. <sup><xref ref-type="bibr" rid="B7">7</xref></sup> A range of exposure to PM <sub>2.5</sub> and blood pressure response was obtained from a metanalysis of observational studies (0.06 mmHg increase in SBP per 1 &#181;g/m <sup>3</sup> increase in PM <sub>2.5</sub> concentration) and from a review of trials of air filtration (0.19 mmHg per 1 &#956;g/m <sup>3</sup> increase in PM <sub>2.5</sub> concentration), <sup><xref ref-type="bibr" rid="B10">10</xref> , <xref ref-type="bibr" rid="B11">11</xref></sup> thus resulting in an exposure response range of 0.06 to 0.19 mmHg per 1 &#956;g/m <sup>3</sup> increase in PM <sub>2.5</sub> concentration. The metanalysis included 28 observational studies (10 cohort and 18 cross-sectional studies) examining long-term exposure (&gt; 1 year) to PM <sub>2.5</sub> and hypertension in healthy populations. <sup><xref ref-type="bibr" rid="B10">10</xref></sup> The systematic review included a total of 10 randomized controlled trials in humans that evaluated personal air cleaners (including high-efficiency particulate air filters and electrostatic precipitators) in a home or residential setting observing the effects of filtration versus no filtration on blood pressure. <sup><xref ref-type="bibr" rid="B11">11</xref></sup> Excess SBP was considered as the increase in SBP due to the level of PM <sub>2.5</sub> concentration above 5 &#956;g/m <sup><xref ref-type="bibr" rid="B3">3</xref></sup> , based on the current WHO Air Quality Guidelines. <sup><xref ref-type="bibr" rid="B8">8</xref></sup> Institutional review board approval was not required due to the nature of the publicly available data. Statistical analyses and maps were produced using the open-access software R v 4.1.2.</p>
        <p>
          <bold>Excess SBP, observational estimates</bold>
        </p>
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        <p>
          <bold>Excess SBP, interventional estimates</bold>
        </p>
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      </sec>
      <sec sec-type="results">
        <title>Results</title>
        <p>The mean population-weighted PM <sub>2.5</sub> concentration for Brazil was 10.68 &#956;g/m <sup>3</sup> , which resulted in an excess SBP range of 0.40 to 1.26 mmHg based on observational and interventional estimates, respectively. <xref ref-type="table" rid="t1001">Table 1</xref> describes the state-specific mean PM <sub>2.5</sub> concentration and excess SBP in 2019. <xref ref-type="fig" rid="f01001">Figure 1</xref> maps the inter-state variability of the mean PM <sub>2.5</sub> concentration, and <xref ref-type="fig" rid="f02001">Figure 2</xref> illustrates the excess SBP according to region and SDI quartiles. Rio de Janeiro (0.53 to 1.69 mmHg) and S&#227;o Paulo (0.53 to 1.68 mmHg) had the highest excess SBP, while Rond&#244;nia (0.20 to 0.62 mmHg) and Amazonas (0.21 to 0.66 mmHg) had the lowest. Comparing the lowest (Rond&#244;nia) to the highest (Rio de Janeiro) burden states, a relative percent difference of approximately 90% to 92% (observational to interventional range) was observed for excess SBP. Regional and SDI quartile differences in excess SBP are shown in <xref ref-type="fig" rid="f02001">Figure 2</xref> . The Southeast (0.47 to 1.49 mmHg) had the highest excess SBP burden, while the North (0.28 to 0.88 mmHg) was the least affected. Concerning SDI quartiles, the third (0.36 to 1.15 mmHg) and fourth (0.39 to 1.25 mmHg) quartiles observed the highest burden, and the second quartile (0.28 to 0.88 mmHg) the lowest.</p>
        <p>
          <table-wrap id="t1001">
            <label>Table 1</label>
            <caption>
              <title>&#8211; Mean PM <bold>2.5</bold> concentration and Socio-demographic Index (SDI) for Brazilian states in 2019 and excess systolic blood pressure (SBP) based on observational and interventional estimates attributed to PM <bold>2.5</bold> exposure</title>
            </caption>
            <table frame="hsides" rules="groups">
              <colgroup>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
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              <thead>
                <tr>
                  <th>Region</th>
                  <th>State</th>
                  <th>SDI</th>
                  <th>SDI quartile</th>
                  <th>Mean PM <sub><bold>2.5</bold></sub> (&#956;g/m <sup><bold>3</bold></sup> )</th>
                  <th>Excess SBP (mmHg) Observational estimates</th>
                  <th>Excess SBP (mmHg) Interventional Estimates</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="center">North</td>
                  <td align="center">Acre</td>
                  <td align="center">0.56</td>
                  <td align="center">1</td>
                  <td align="center">9.01</td>
                  <td align="center">0.24</td>
                  <td align="center">0.76</td>
                </tr>
                <tr>
                  <td align="center">Northeast</td>
                  <td align="center">Alagoas</td>
                  <td align="center">0.52</td>
                  <td align="center">1</td>
                  <td align="center">10.20</td>
                  <td align="center">0.31</td>
                  <td align="center">0.99</td>
                </tr>
                <tr>
                  <td align="center">North</td>
                  <td align="center">Amap&#225;</td>
                  <td align="center">0.64</td>
                  <td align="center">3</td>
                  <td align="center">10.97</td>
                  <td align="center">0.36</td>
                  <td align="center">1.13</td>
                </tr>
                <tr>
                  <td align="center">North</td>
                  <td align="center">Amazonas</td>
                  <td align="center">0.6</td>
                  <td align="center">2</td>
                  <td align="center">8.47</td>
                  <td align="center">0.21</td>
                  <td align="center">0.66</td>
                </tr>
                <tr>
                  <td align="center">Northeast</td>
                  <td align="center">Bahia</td>
                  <td align="center">0.56</td>
                  <td align="center">1</td>
                  <td align="center">9.92</td>
                  <td align="center">0.30</td>
                  <td align="center">0.94</td>
                </tr>
                <tr>
                  <td align="center">Northeast</td>
                  <td align="center">Cear&#225;</td>
                  <td align="center">0.56</td>
                  <td align="center">1</td>
                  <td align="center">11.11</td>
                  <td align="center">0.37</td>
                  <td align="center">1.16</td>
                </tr>
                <tr>
                  <td align="center">Midwest</td>
                  <td align="center">Distrito Federal</td>
                  <td align="center">0.78</td>
                  <td align="center">4</td>
                  <td align="center">11.34</td>
                  <td align="center">0.38</td>
                  <td align="center">1.20</td>
                </tr>
                <tr>
                  <td align="center">Southeast</td>
                  <td align="center">Esp&#237;rito Santo</td>
                  <td align="center">0.66</td>
                  <td align="center">4</td>
                  <td align="center">10.77</td>
                  <td align="center">0.35</td>
                  <td align="center">1.10</td>
                </tr>
                <tr>
                  <td align="center">Midwest</td>
                  <td align="center">Goi&#225;s</td>
                  <td align="center">0.63</td>
                  <td align="center">3</td>
                  <td align="center">11.29</td>
                  <td align="center">0.38</td>
                  <td align="center">1.20</td>
                </tr>
                <tr>
                  <td align="center">Northeast</td>
                  <td align="center">Maranh&#227;o</td>
                  <td align="center">0.44</td>
                  <td align="center">1</td>
                  <td align="center">10.61</td>
                  <td align="center">0.34</td>
                  <td align="center">1.07</td>
                </tr>
                <tr>
                  <td align="center">Midwest</td>
                  <td align="center">Mato Grosso</td>
                  <td align="center">0.64</td>
                  <td align="center">3</td>
                  <td align="center">9.52</td>
                  <td align="center">0.27</td>
                  <td align="center">0.86</td>
                </tr>
                <tr>
                  <td align="center">Midwest</td>
                  <td align="center">Mato Grosso do Sul</td>
                  <td align="center">0.64</td>
                  <td align="center">3</td>
                  <td align="center">10.36</td>
                  <td align="center">0.32</td>
                  <td align="center">1.02</td>
                </tr>
                <tr>
                  <td align="center">Southeast</td>
                  <td align="center">Minas Gerais</td>
                  <td align="center">0.64</td>
                  <td align="center">3</td>
                  <td align="center">12.89</td>
                  <td align="center">0.47</td>
                  <td align="center">1.50</td>
                </tr>
                <tr>
                  <td align="center">North</td>
                  <td align="center">Par&#225;</td>
                  <td align="center">0.57</td>
                  <td align="center">2</td>
                  <td align="center">10.08</td>
                  <td align="center">0.30</td>
                  <td align="center">0.96</td>
                </tr>
                <tr>
                  <td align="center">Northeast</td>
                  <td align="center">Para&#237;ba</td>
                  <td align="center">0.55</td>
                  <td align="center">1</td>
                  <td align="center">10.74</td>
                  <td align="center">0.34</td>
                  <td align="center">1.09</td>
                </tr>
                <tr>
                  <td align="center">South</td>
                  <td align="center">Paran&#225;</td>
                  <td align="center">0.66</td>
                  <td align="center">4</td>
                  <td align="center">9.79</td>
                  <td align="center">0.29</td>
                  <td align="center">0.91</td>
                </tr>
                <tr>
                  <td align="center">Northeast</td>
                  <td align="center">Pernambuco</td>
                  <td align="center">0.57</td>
                  <td align="center">2</td>
                  <td align="center">10.50</td>
                  <td align="center">0.33</td>
                  <td align="center">1.05</td>
                </tr>
                <tr>
                  <td align="center">Northeast</td>
                  <td align="center">Piau&#237;</td>
                  <td align="center">0.51</td>
                  <td align="center">1</td>
                  <td align="center">11.11</td>
                  <td align="center">0.37</td>
                  <td align="center">1.16</td>
                </tr>
                <tr>
                  <td align="center">Southeast</td>
                  <td align="center">Rio de Janeiro</td>
                  <td align="center">0.7</td>
                  <td align="center">4</td>
                  <td align="center">13.91</td>
                  <td align="center">0.53</td>
                  <td align="center">1.69</td>
                </tr>
                <tr>
                  <td align="center">Northeast</td>
                  <td align="center">Rio Grande do Norte</td>
                  <td align="center">0.58</td>
                  <td align="center">2</td>
                  <td align="center">11.15</td>
                  <td align="center">0.37</td>
                  <td align="center">1.17</td>
                </tr>
                <tr>
                  <td align="center">South</td>
                  <td align="center">Rio Grande do Sul</td>
                  <td align="center">0.68</td>
                  <td align="center">4</td>
                  <td align="center">10.50</td>
                  <td align="center">0.33</td>
                  <td align="center">1.04</td>
                </tr>
                <tr>
                  <td align="center">North</td>
                  <td align="center">Rond&#244;nia</td>
                  <td align="center">0.61</td>
                  <td align="center">2</td>
                  <td align="center">8.26</td>
                  <td align="center">0.20</td>
                  <td align="center">0.62</td>
                </tr>
                <tr>
                  <td align="center">North</td>
                  <td align="center">Roraima</td>
                  <td align="center">0.61</td>
                  <td align="center">3</td>
                  <td align="center">10.74</td>
                  <td align="center">0.34</td>
                  <td align="center">1.09</td>
                </tr>
                <tr>
                  <td align="center">South</td>
                  <td align="center">Santa Catarina</td>
                  <td align="center">0.69</td>
                  <td align="center">4</td>
                  <td align="center">10.93</td>
                  <td align="center">0.36</td>
                  <td align="center">1.13</td>
                </tr>
                <tr>
                  <td align="center">Southeast</td>
                  <td align="center">S&#227;o Paulo</td>
                  <td align="center">0.7</td>
                  <td align="center">4</td>
                  <td align="center">13.87</td>
                  <td align="center">0.53</td>
                  <td align="center">1.68</td>
                </tr>
                <tr>
                  <td align="center">Northeast</td>
                  <td align="center">Sergipe</td>
                  <td align="center">0.58</td>
                  <td align="center">2</td>
                  <td align="center">9.28</td>
                  <td align="center">0.26</td>
                  <td align="center">0.81</td>
                </tr>
                <tr>
                  <td align="center">North</td>
                  <td align="center">Tocantins</td>
                  <td align="center">0.58</td>
                  <td align="center">2</td>
                  <td align="center">10.01</td>
                  <td align="center">0.30</td>
                  <td align="center">0.95</td>
                </tr>
                <tr>
                  <td align="center" colspan="2">
                    <bold>Brazil</bold>
                  </td>
                  <td align="center">0.64</td>
                  <td align="center">3</td>
                  <td align="center">11.65</td>
                  <td align="center">0.40</td>
                  <td align="center">1.26</td>
                </tr>
              </tbody>
            </table>
          </table-wrap>
        </p>
        <p>
          <fig id="f01001">
            <label>Figure 1</label>
            <caption>
              <title>&#8211; Particulate matter 2.5 (PM 2.5 ) state-level exposure variation in Brazil. Measured in &#956;g/m 3 .</title>
            </caption>
            <graphic xlink:href="1678-4170-abc-120-11-e20230347-30347-gf01-en.tif"/></fig>
        </p>
        <p>
          <fig id="f02001">
            <label>Figure 2</label>
            <caption>
              <title>&#8211; Excess systolic blood pressure (SBP) based on observational and interventional estimates attributed to PM 2.5 exposure in Brazil according to region and Socio-demographic Index (SDI) quartiles.</title>
            </caption>
            <graphic xlink:href="1678-4170-abc-120-11-e20230347-30347-gf02-en.tif"/></fig>
        </p>
      </sec>
      <sec sec-type="discussion">
        <title>Discussion</title>
        <p>In the context of the Brazilian hypertension crisis, with 1 in every 4 Brazilians reporting hypertension, our findings highlight the less recognized contribution of PM <sub>2.5</sub> exposure to increased SBP. <sup><xref ref-type="bibr" rid="B2">2</xref></sup> Although Brazil&#8217;s SBP elevation is lower than the global average (0.40 versus 2.4 mmHg, observational estimates), substantial inter-state, regional, and socio-demographic disparities regarding the magnitude of excess SBP were observed, particularly in the Southeast Region, where PM <sub>2.5</sub> levels are also the highest. <sup><xref ref-type="bibr" rid="B8">8</xref></sup> In addition, the finding that all Brazilian states possess PM <sub>2.5</sub> concentrations above the current WHO threshold emphasizes the need for stronger cohesive nationwide air pollution programs, especially in the southeastern states of Rio de Janeiro and S&#227;o Paulo, which contain the largest urban areas in Brazil. <sup><xref ref-type="bibr" rid="B12">12</xref></sup> Given the impact of fossil fuels on air pollution in urban areas, these initiatives should focus on prioritizing the use of non-fossil energy sources, as well as improving infrastructure to support larger public transport systems and promote the use of clean energy vehicles. <sup><xref ref-type="bibr" rid="B13">13</xref></sup> Additionally, due to high PM <sub>2.5</sub> concentrations in S&#227;o Paulo, Brazil&#8217;s largest sugar-producing state, one must also consider the impact of pre-harvest sugarcane burning and placing greater industrial restrictions, especially since the air pollution from the burning season has been associated with increased hospital admissions. <sup><xref ref-type="bibr" rid="B4">4</xref> , <xref ref-type="bibr" rid="B14">14</xref></sup></p>
        <p>Although, in this study, the North Region was found to have the smallest PM <sub>2.5</sub> concentration, other studies using different PM <sub>2.5</sub> estimation methods described a greater air pollution burden in the region. <sup><xref ref-type="bibr" rid="B15">15</xref></sup> In fact, the North Region plays a crucial role in air pollution in Brazil. <sup><xref ref-type="bibr" rid="B16">16</xref></sup> The burning of biomass occurring in the Amazon, for instance, emits large amounts of PM <sub>2.5</sub> , which not only impact areas close to the fires, but also cause illness and premature deaths in areas far away from them. <sup><xref ref-type="bibr" rid="B16">16</xref></sup> Furthermore, this region is also described as a socio-climatic hotspot, combining high levels of social and environmental vulnerability, enhancing the need for targeted socio-environmental and health interventions in the region. <sup><xref ref-type="bibr" rid="B16">16</xref></sup></p>
        <p>Ultimately, although the numeric SBP increase value might seem dismissible, it must be viewed in the light of its impact on an extensive number of individuals and considered as a component of a continuum of exposures that have an additive effect on blood pressure. In addition, multiple biological pathways mediating the impact of PM <sub>2.5</sub> on blood pressure have been proposed, including systemic inflammation, oxidative responses, and endothelial dysfunction. <sup><xref ref-type="bibr" rid="B17">17</xref></sup> Recent studies from China also implicate the activation of the hypothalamus-pituitary-adrenal axis in response to exposure to high levels of PM <sub>2.5</sub> , culminating in significant increases in serum stress hormones (i.e., cortisol, cortisone, epinephrine, and norepinephrine). <sup><xref ref-type="bibr" rid="B17">17</xref> , <xref ref-type="bibr" rid="B18">18</xref></sup></p>
        <p>This study&#8217;s limitations include those inherent to its ecological nature, its dependence on secondary data, and analysis on a state level, which can underestimate the effect in populations of industrialized metropolitan areas.</p>
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      <fn-group>
        <fn fn-type="other">
          <p>Study association</p>
          <p>This study is not associated with any thesis or dissertation work.</p>
          <p>Ethics approval and consent to participate</p>
          <p>This article does not contain any studies with human participants or animals performed by any of the authors.</p>
        </fn>
      </fn-group>
      <fn-group>
        <fn fn-type="supported-by">
          <p>Sources of funding: There were no external funding sources for this study.</p>
        </fn>
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