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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">YbbkGvFjdCgXVZdpn9SCzQb</article-id>
      <article-id specific-use="scielo-v2" pub-id-type="publisher-id">S0066-782X2023000400308</article-id>
      <article-id pub-id-type="other">00308</article-id>
      <article-id pub-id-type="doi">10.36660/abc.20211009</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Artigo Original</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Associa&#231;&#227;o entre a Mortalidade por Doen&#231;as Cr&#244;nicas N&#227;o Transmiss&#237;veis e o &#205;ndice de Desenvolvimento Humano no Brasil entre 1980 e 2019</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Feliciano</surname>
            <given-names>Sandra Chagas da Costa</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</role>
          <role>An&#225;lise estat&#237;stica</role>
          <role>Obten&#231;&#227;o de financiamento</role>
          <role>Reda&#231;&#227;o do manuscrito</role>
          <role>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">
          <contrib-id contrib-id-type="orcid">0000-0001-8121-5959</contrib-id>
          <name>
            <surname>Villela</surname>
            <given-names>Paolo Blanco</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</role>
          <role>An&#225;lise estat&#237;stica</role>
          <role>Obten&#231;&#227;o de financiamento</role>
          <role>Reda&#231;&#227;o do manuscrito</role>
          <role>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">
          <contrib-id contrib-id-type="orcid">0000-0002-0737-6188</contrib-id>
          <name>
            <surname>Oliveira</surname>
            <given-names>Gl&#225;ucia Maria Moraes de</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</role>
          <role>An&#225;lise estat&#237;stica</role>
          <role>Obten&#231;&#227;o de financiamento</role>
          <role>Reda&#231;&#227;o do manuscrito</role>
          <role>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-group>
      <aff id="aff1">
        <label>1</label>
        <institution content-type="orgname">Universidade Federal do Rio de Janeiro</institution>
        <addr-line>
          <named-content content-type="city">Rio de Janeiro</named-content>
          <named-content content-type="state">RJ</named-content>
        </addr-line>
        <country country="BR">Brasil</country>
        <institution content-type="original">Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ &#8211; Brasil</institution>
      </aff>
      <author-notes>
        <corresp id="c01"> Correspond&#234;ncia: Paolo Blanco Villela &#8226; Rua Professor Rodolpho Paulo Rocco, 255 / 8<sup>o</sup>. Andar. CEP 21941-913, Rio de Janeiro, RJ &#8211; Brasil E-mail: <email>pbvillela@gmail.com</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>
      </author-notes>
      <pub-date date-type="pub" publication-format="electronic">
        <day>21</day>
        <month>04</month>
        <year>2023</year>
      </pub-date>
      <pub-date date-type="collection" publication-format="electronic">
        <year>2023</year>
      </pub-date>
      <volume>120</volume>
      <issue>4</issue>
      <elocation-id>e20211009</elocation-id>
      <history>
        <date date-type="received">
          <day>08</day>
          <month>12</month>
          <year>2022</year>
        </date>
        <date date-type="received">
          <day>04</day>
          <month>12</month>
          <year>2022</year>
        </date>
        <date date-type="accepted">
          <day>14</day>
          <month>12</month>
          <year>2022</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>
      <abstract>
        <title>Resumo</title>
        <sec>
          <title>Fundamento</title>
          <p> No Brasil, em 2019, as doen&#231;as cr&#244;nicas n&#227;o transmiss&#237;veis (DCNT) acarretaram mais de 734 mil &#243;bitos, 55% de todas as mortes, com importante impacto socioecon&#244;mico.</p>
        </sec>
        <sec>
          <title>Objetivos</title>
          <p> Analisar as taxas de mortalidade das DCNT, no Brasil, de 1980 a 2019, e sua associa&#231;&#227;o com indicadores socioecon&#244;micos.</p>
        </sec>
        <sec>
          <title>M&#233;todos</title>
          <p> Trata-se de um estudo descritivo, de s&#233;ries temporais dos &#243;bitos por DCNT, no Brasil, de 1980 a 2019. Os dados relativos &#224;s frequ&#234;ncias anuais de mortes e da popula&#231;&#227;o foram obtidos do DATASUS. Foram estimadas as taxas de mortalidade brutas e padronizadas por 100.000 habitantes, pelo m&#233;todo direto (popula&#231;&#227;o do Brasil de 2000). Foram calculados os quartis de cada DCNT, onde a mudan&#231;a de quartil, por aumento das taxas de mortalidade, foi representada por gradiente crom&#225;tico. O &#205;ndice de Desenvolvimento Humano Municipal (IDHM) de cada unidade da federa&#231;&#227;o (UF) foi extra&#237;do do site Atlas Brasil e correlacionado com as taxas de mortalidade por DCNT.</p>
        </sec>
        <sec>
          <title>Resultados</title>
          <p> Ocorreu redu&#231;&#227;o nas taxas de mortalidade por doen&#231;as do aparelho circulat&#243;rio no per&#237;odo, exceto na regi&#227;o Nordeste. Houve tamb&#233;m aumento da mortalidade por neoplasia e diabetes, enquanto as taxas das doen&#231;as respirat&#243;rias apresentaram poucas varia&#231;&#245;es. Houve correla&#231;&#227;o inversa entre as UF com maior redu&#231;&#227;o nas taxas de mortalidade por DCNT e o IDHM.</p>
        </sec>
        <sec>
          <title>Conclus&#245;es</title>
          <p> A redu&#231;&#227;o observada na mortalidade por doen&#231;as do aparelho circulat&#243;rio pode refletir melhoria dos indicadores socioecon&#244;micos, no Brasil, nesse per&#237;odo. O aumento da taxa de mortalidade por neoplasias provavelmente se relaciona com o envelhecimento da popula&#231;&#227;o. As maiores taxas de mortalidade por diabetes parecem ser associadas com o aumento da preval&#234;ncia da obesidade nas mulheres brasileiras.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="pt">
        <kwd>Doen&#231;as N&#227;o Transmissiveis</kwd>
        <kwd>Indicadores de Desenvolvimento</kwd>
        <kwd>Sa&#250;de P&#250;blica</kwd>
        <kwd>Sa&#250;de de Pessoa com Defici&#234;ncia</kwd>
        <kwd>Epidemiologia</kwd>
        <kwd>Mortalidade</kwd>
      </kwd-group>
      <counts>
        <fig-count count="8"/>
        <table-count count="4"/>
        <equation-count count="0"/>
        <ref-count count="31"/>
      </counts>
    </article-meta>
  </front>
  <body>
    <sec sec-type="intro">
      <title>Introdu&#231;&#227;o</title>
      <p>As doen&#231;as cr&#244;nicas n&#227;o transmiss&#237;veis (DCNT) s&#227;o representadas pelas doen&#231;as do aparelho circulat&#243;rio (DAC), neoplasias (NEO), diabetes mellitus (DM) e doen&#231;as respirat&#243;rias cr&#244;nicas (DRC).<sup><xref ref-type="bibr" rid="B1">1</xref></sup> Em geral, caracterizam-se por longo per&#237;odo de lat&#234;ncia e evolu&#231;&#227;o, les&#245;es irrevers&#237;veis e complica&#231;&#245;es que acarretam diferentes graus de incapacidade ou &#243;bito,<sup><xref ref-type="bibr" rid="B2">2</xref></sup> e s&#227;o consideradas um grande problema de sa&#250;de p&#250;blica, por representarem as principais causas de morte e incapacidade prematura em todo o mundo.<sup><xref ref-type="bibr" rid="B3">3</xref></sup></p>
      <p>Em 2015, foram estimados 41 milh&#245;es de &#243;bitos por DCNT no mundo, 36,6% destes em pessoas com idade entre 30 e 69 anos, e mais de 85% dessas mortes prematuras ocorreram em pa&#237;ses de baixa e m&#233;dia renda, causando impacto no desenvolvimento econ&#244;mico e no sistema de sa&#250;de.<sup><xref ref-type="bibr" rid="B4">4</xref>,<xref ref-type="bibr" rid="B5">5</xref></sup> No Brasil, o Departamento de Inform&#225;tica do Sistema &#218;nico de Sa&#250;de (DATASUS), em 2019, atribuiu &#224;s DCNT mais de 734 mil &#243;bitos, o que representou 55% de todas as mortes ocorridas no pa&#237;s. As DAC, representadas principalmente pelas doen&#231;as isqu&#234;micas do cora&#231;&#227;o (DIC) e pelas doen&#231;as cerebrovasculares (DCBV), ocupam o primeiro lugar, com mais de 362 mil &#243;bitos nesse per&#237;odo.<sup><xref ref-type="bibr" rid="B6">6</xref></sup></p>
      <p>S&#227;o v&#225;rios os fatores de risco comuns &#224;s DCNT. Al&#233;m dos fatores de riscos cl&#225;ssicos &#8211; modific&#225;veis ou comportamentais, existem os determinantes da sa&#250;de, que s&#227;o fatores sociais, econ&#244;micos, culturais, educacionais, &#233;tnicos/raciais, psicol&#243;gicos e comportamentais e influenciam de forma indireta nas condi&#231;&#245;es de sa&#250;de da popula&#231;&#227;o, e s&#227;o interdependentes para a ocorr&#234;ncia de doen&#231;as.<sup><xref ref-type="bibr" rid="B7">7</xref>-<xref ref-type="bibr" rid="B9">9</xref></sup></p>
      <p>Estudos realizados no Brasil demonstraram que a melhoria dos indicadores socioecon&#244;micos se associou a redu&#231;&#227;o da mortalidade por DAC,<sup><xref ref-type="bibr" rid="B10">10</xref></sup> e que as taxas de mortalidade por DAC, DCBV, e doen&#231;as hipertensivas variaram de maneira inversa ao &#205;ndice de Desenvolvimento Humano (IDH).<sup><xref ref-type="bibr" rid="B11">11</xref></sup> Apesar deste fato, no Brasil, existem poucos estudos que relacionaram as taxas de mortalidade por DCNT com o IDH.<sup><xref ref-type="bibr" rid="B10">10</xref>-<xref ref-type="bibr" rid="B12">12</xref></sup></p>
      <p>O conhecimento do comportamento e a distribui&#231;&#227;o das doen&#231;as na popula&#231;&#227;o por um longo per&#237;odo s&#227;o &#250;teis na proposi&#231;&#227;o de pol&#237;ticas p&#250;blicas, assim como na avalia&#231;&#227;o, gest&#227;o e planejamento de a&#231;&#245;es de promo&#231;&#227;o e preven&#231;&#227;o dos servi&#231;os de sa&#250;de. Desta forma, este estudo tem por objetivo analisar as taxas de mortalidade das DCNT no Brasil, no per&#237;odo de 1980 a 2019, avaliando a rela&#231;&#227;o entre as taxas de mortalidade por cada DCNT e suas associa&#231;&#245;es com o IDH.</p>
    </sec>
    <sec sec-type="methods">
      <title>M&#233;todos</title>
      <p>Trata-se de um estudo ecol&#243;gico, descritivo e de s&#233;ries temporais dos registros de &#243;bitos por DCNT, em todas as faixas et&#225;rias e em ambos os sexos, ocorridos no Brasil, no per&#237;odo de 1980 a 2019. Os dados relativos &#224;s frequ&#234;ncias anuais de mortes foram obtidos do Sistema de Informa&#231;&#245;es sobre Mortalidade (SIM), disponibilizados no site do DATASUS do Minist&#233;rio da Sa&#250;de.<sup><xref ref-type="bibr" rid="B6">6</xref></sup></p>
      <p>Para classifica&#231;&#227;o dos &#243;bitos no per&#237;odo de 1980 a 1995 foram utilizadas as categorias da 9&#170; Revis&#227;o da Classifica&#231;&#227;o Estat&#237;stica Internacional de Doen&#231;as e Problemas Relacionados &#224; Sa&#250;de (CID-09): DAC (Cap&#237;tulo VII), DIC (Categorias 410-414), DCBV (430-438), NEO (Categorias 140-208; 239), DM (Categoria 250) e DRC (Categorias 490-516 e 518-519), (OMS, 1978). Para os &#243;bitos no per&#237;odo de 1996 a 2019 foram utilizadas as categorias da 10&#170;. Revis&#227;o da Classifica&#231;&#227;o Estat&#237;stica Internacional de Doen&#231;as e Problemas Relacionados &#224; Sa&#250;de (CID-10): DAC (Categorias 100-199), DIC (Categorias I20 a I25), DCBV (Categorias I60-I69), NEO (Categorias C00-C97), DM (Categorias E10-E14) e DRC (Categorias J30-J98), sendo desconsiderados os &#243;bitos com o sexo ignorado em todo o recorte temporal. As taxas de mortalidade por todas as causas, tamb&#233;m foram obtidas para o mesmo per&#237;odo do estudo.<sup><xref ref-type="bibr" rid="B13">13</xref>,<xref ref-type="bibr" rid="B14">14</xref></sup></p>
      <p>Os dados referentes &#224; popula&#231;&#227;o do Brasil, das regi&#245;es geogr&#225;ficas (RG) &#8211; Norte, Nordeste, Sudeste, Sul, e Centro-Oeste &#8211; e unidades federativas (UF), foram obtidos do DATASUS, baseados nos censos de 1980, 1991, 2000 e 2010, proje&#231;&#245;es intercensit&#225;rias at&#233; 2012, e proje&#231;&#245;es populacionais de 2013 em diante, do Instituto Brasileiro de Geografia e Estat&#237;stica (IBGE). Os dados foram estratificados por sexo em oito grupos et&#225;rios (at&#233; 19 anos; 20 a 29 anos; 30 a 39 anos; 40 a 49 anos; 50 a 59 anos; 60 a 69 anos; 70 a 79 anos; e 80 anos ou mais).</p>
      <p>Foram estimadas as taxas anuais brutas e padronizadas de mortalidade por 100.000 habitantes das DCNT (DAC, NEO, DRC e DM), no decorrer dos 40 anos de observa&#231;&#227;o, por RG e UF pelo m&#233;todo direto, em ambos os sexos, utilizando a popula&#231;&#227;o do Brasil do ano 2000 como padr&#227;o. Cabe ressaltar que, para compara&#231;&#227;o das taxas de mortalidade em diferentes popula&#231;&#245;es &#233; indispens&#225;vel a padroniza&#231;&#227;o por uma popula&#231;&#227;o padr&#227;o com os mesmos grupos et&#225;rios, a fim de anular o efeito da distribui&#231;&#227;o demogr&#225;fica desigual. Assim, o produto final &#233; o n&#250;mero de &#243;bitos esperados caso as taxas brutas encontradas para cada regi&#227;o geogr&#225;fica fossem aplicadas &#224; mesma popula&#231;&#227;o (no caso, a do ano 2000).<sup><xref ref-type="bibr" rid="B15">15</xref></sup></p>
      <p>Observou-se a rela&#231;&#227;o entre as taxas de mortalidade por DCNT padronizadas por 100.000 habitantes, entre 1980, 1994 e 2019 e sua associa&#231;&#227;o com o total de &#243;bitos no Brasil. Os dados de Tocantins foram considerados somente ap&#243;s o ano de 1989.</p>
      <p>Para cada UF do Brasil nos anos de 1980, 1994 e 2019, foram calculadas as taxas de mortalidade padronizadas por 100.000 habitantes para cada DCNT, que foram representadas por cores diferentes. Para permitir uma compara&#231;&#227;o proporcional entre as DCNT, foram calculadas as medianas e os quartis para DAC, DM, NEO e DRC, e a varia&#231;&#227;o entre os quartis ao longo dos anos foi representada pela varia&#231;&#227;o na intensidade das respectivas cores, deixando-as mais intensas em caso de aumento das taxas com mudan&#231;a de quartil, e menos intensas em caso de redu&#231;&#227;o nas taxas com consequente mudan&#231;a de quartil.</p>
      <p>Para cada regi&#227;o foram estimadas as taxas brutas de mortalidade nos sexos masculino e feminino, de acordo com as DCNT, em oito per&#237;odos de cinco anos, de 1980 a 2019, com posterior c&#225;lculo da raz&#227;o das taxas. Ressalta-se que a partir de 1989, a regi&#227;o Norte passou a computar os dados de Tocantins, UF criada em 1988.</p>
      <p>Por fim, foram constru&#237;dos gr&#225;ficos de dispers&#227;o e calculados os coeficientes de correla&#231;&#227;o de Pearson para cada DCNT e o IDH de 2010, adotando n&#237;vel de signific&#226;ncia estat&#237;stica de 5%. O IDH e suas dimens&#245;es estadual e municipal, tamb&#233;m denominadas IDHM, foram extra&#237;dos do site Atlas Brasil.<sup><xref ref-type="bibr" rid="B16">16</xref>,<xref ref-type="bibr" rid="B17">17</xref></sup> Assim, foram avaliadas as rela&#231;&#245;es entre as taxas de mortalidade por cada DCNT e o &#205;ndice de Desenvolvimento Humano Municipal (IDHM) de cada UF. Para a an&#225;lise dos dados e constru&#231;&#227;o das tabelas e gr&#225;ficos, foi utilizado o programa Microsoft Office Excel&#174; 2016 (Microsoft Corporation, EUA).</p>
    </sec>
    <sec sec-type="results">
      <title>Resultados</title>
      <p>As taxas brutas de todas as DCNT, no decorrer dos 40 anos de observa&#231;&#227;o, apresentaram leves oscila&#231;&#245;es, mas com tend&#234;ncia a eleva&#231;&#227;o, sobretudo para as DAC e as NEO. Com a padroniza&#231;&#227;o das taxas de mortalidade &#233; observada queda nas DAC enquanto as demais apresentam leves oscila&#231;&#245;es com tend&#234;ncia a estabilidade, de uma forma geral, no per&#237;odo estudado (<xref ref-type="fig" rid="f02">Figura 1</xref>).</p>
      <p>
        <fig id="f02">
          <label>Figura 1</label>
          <caption>
            <title>&#8211; Taxas brutas (1A) e padronizadas (1B) de mortalidade por 100,000 habitantes das doen&#231;as cr&#244;nicas n&#227;o transmiss&#237;veis (DAC: doen&#231;as do aparelho circulat&#243;rio; DRC: doen&#231;as respirat&#243;rias cr&#244;nicas; DM: diabetes mellitus e NEO: neoplasias), em ambos os sexos, em todas as faixas et&#225;rias, no Brasil, no per&#237;odo de 1980 a 2019.</title>
          </caption>
          <graphic xlink:href="1678-4170-abc-120-04-e20211009-11009-gf01.tif"/></fig>
      </p>
      <p>Observou-se decl&#237;nio na taxa de mortalidade padronizada das DCNT com 339,27 por 100.000 habitantes no ano de 1980 para 229,35 por 100.000 habitantes em 2019, fato que tamb&#233;m ocorreu com as taxas padronizadas por demais causas, de 425,47 por 100.000 habitantes em 1980 para 222,08 mortes por 100.000 habitantes em 2019. Nota-se que as DAC apresentaram redu&#231;&#227;o das taxas, e as DRC que mostraram oscila&#231;&#245;es com eleva&#231;&#227;o em 1994 e queda em 2019. As DAC apresentaram redu&#231;&#227;o de 67% para 49% nos anos observados, enquanto as NEO apresentaram eleva&#231;&#227;o de 21 % para 31% na mortalidade proporcional (<xref ref-type="fig" rid="f01">Figura Central</xref> e <ext-link ext-link-type="uri" xlink:href="http://abccardiol.org/supplementary-material/2023/12004/2021-1009_AO_Material-Suplementar.pdf">Material Suplementar &#8211; Figuras 1A e 1B</ext-link>).</p>
      <p>
        <fig id="f01">
          <label>Figura Central</label>
          <caption>
            <title>: Associa&#231;&#227;o entre a Mortalidade por Doen&#231;as Cr&#244;nicas N&#227;o Transmiss&#237;veis e o &#205;ndice de Desenvolvimento Humano no Brasil entre 1980 e 2019</title>
          </caption>
          <attrib>Defini&#231;&#227;o das doen&#231;as cr&#244;nicas n&#227;o transmiss&#237;veis; mortalidade no Brasil com percentual de &#243;bitos em 2019 e taxas de mortalidade padronizadas por idade em 1980 e 2019; rela&#231;&#227;o entre os sexos masculino/feminino das taxas de mortalidade; e poss&#237;vel associa&#231;&#227;o da mortalidade com o &#205;ndice de Desenvolvimento Humano.</attrib>
          <graphic xlink:href="1678-4170-abc-120-04-e20211009-11009-gf02.tif"/></fig>
      </p>
      <p>Na <xref ref-type="table" rid="t1">Tabela 1</xref>, observa-se que a regi&#227;o Norte apresentou aumento dos quartis das taxas de mortalidade por NEO e DM, em todas as UF. Rond&#244;nia, Acre e Amap&#225; apresentaram aumento das taxas por DRC, sobretudo no &#250;ltimo ano, e ao observar as taxas de mortalidade por DAC, nota-se queda em todas UF no &#250;ltimo ano, exceto em Roraima e Tocantins (<xref ref-type="table" rid="t1">Tabela 1</xref>).</p>
      <p>
        <table-wrap id="t1">
          <label>Tabela 1</label>
          <caption>
            <title>&#8211; Taxas padronizadas de mortalidade por 100.000 habitantes, por UF, distribu&#237;das de acordo com as doen&#231;as cr&#244;nicas n&#227;o transmiss&#237;veis (cores) e seus respectivos quartis (intensidade das cores) - Brasil, 1980, 1994 e 2019.</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead>
              <tr>
                <th align="left" scope="col">UF / Ano</th>
                <th colspan="4" scope="col">1980</th>
                <th colspan="4" scope="col">1994</th>
                <th colspan="4" scope="col">2019</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Rond&#244;nia</td>
                <td>189,71</td>
                <td>25,73</td>
                <td>49,39</td>
                <td>3,37</td>
                <td>143,17</td>
                <td>33,24</td>
                <td>51,50</td>
                <td>23,36</td>
                <td>111,45</td>
                <td>29,56</td>
                <td>74,92</td>
                <td>26,50</td>
              </tr>
              <tr>
                <td>Acre</td>
                <td align="center">143,14</td>
                <td align="center">22,62</td>
                <td align="center">52,66</td>
                <td align="center">1,98</td>
                <td align="center">143,72</td>
                <td align="center">23,85</td>
                <td align="center">42,03</td>
                <td align="center">8,25</td>
                <td align="center">124,60</td>
                <td align="center">48,59</td>
                <td align="center">71,93</td>
                <td align="center">22,25</td>
              </tr>
              <tr>
                <td>Amazonas</td>
                <td align="center">192,64</td>
                <td align="center">10,60</td>
                <td align="center">54,54</td>
                <td align="center">4,06</td>
                <td align="center">106,57</td>
                <td align="center">17,16</td>
                <td align="center">59,38</td>
                <td align="center">13,05</td>
                <td align="center">100,69</td>
                <td align="center">21,57</td>
                <td align="center">74,04</td>
                <td align="center">32,09</td>
              </tr>
              <tr>
                <td>Roraima</td>
                <td align="center">156,06</td>
                <td align="center">25,42</td>
                <td align="center">50,58</td>
                <td align="center">2,36</td>
                <td align="center">142,99</td>
                <td align="center">18,60</td>
                <td align="center">63,28</td>
                <td align="center">14,51</td>
                <td align="center">159,57</td>
                <td align="center">27,07</td>
                <td align="center">97,83</td>
                <td align="center">34,84</td>
              </tr>
              <tr>
                <td>Par&#225;</td>
                <td align="center">144,72</td>
                <td align="center">10,18</td>
                <td align="center">41,74</td>
                <td align="center">5,28</td>
                <td align="center">125,39</td>
                <td align="center">17,96</td>
                <td align="center">46,25</td>
                <td align="center">13,23</td>
                <td align="center">116,01</td>
                <td align="center">23,48</td>
                <td align="center">60,50</td>
                <td align="center">27,99</td>
              </tr>
              <tr>
                <td>Amap&#225;</td>
                <td align="center">140,80</td>
                <td align="center">11,40</td>
                <td align="center">60,64</td>
                <td align="center">13,71</td>
                <td align="center">161,30</td>
                <td align="center">28,47</td>
                <td align="center">85,82</td>
                <td align="center">14,99</td>
                <td align="center">116,38</td>
                <td align="center">32,35</td>
                <td align="center">72,58</td>
                <td align="center">27,97</td>
              </tr>
              <tr>
                <td>Tocantins</td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">82,68</td>
                <td align="center">7,84</td>
                <td align="center">25,07</td>
                <td align="center">6,65</td>
                <td align="center">129,23</td>
                <td align="center">24,02</td>
                <td align="center">63,25</td>
                <td align="center">32,18</td>
              </tr>
              <tr>
                <td>Maranh&#227;o</td>
                <td align="center">64,95</td>
                <td align="center">3,71</td>
                <td align="center">13,95</td>
                <td align="center">2,89</td>
                <td align="center">62,01</td>
                <td align="center">5,71</td>
                <td align="center">18,52</td>
                <td align="center">4,76</td>
                <td align="center">136,99</td>
                <td align="center">18,98</td>
                <td align="center">57,22</td>
                <td align="center">34,25</td>
              </tr>
              <tr>
                <td>Piau&#237;</td>
                <td align="center">67,44</td>
                <td align="center">4,56</td>
                <td align="center">14,76</td>
                <td align="center">2,15</td>
                <td align="center">91,90</td>
                <td align="center">8,75</td>
                <td align="center">23,76</td>
                <td align="center">7,35</td>
                <td align="center">149,33</td>
                <td align="center">19,54</td>
                <td align="center">68,84</td>
                <td align="center">31,53</td>
              </tr>
              <tr>
                <td>Cear&#225;</td>
                <td align="center">70,91</td>
                <td align="center">6,29</td>
                <td align="center">23,88</td>
                <td align="center">2,97</td>
                <td align="center">83,99</td>
                <td align="center">11,12</td>
                <td align="center">34,99</td>
                <td align="center">6,63</td>
                <td align="center">119,58</td>
                <td align="center">22,31</td>
                <td align="center">77,32</td>
                <td align="center">16,29</td>
              </tr>
              <tr>
                <td>Rio Grande do Norte</td>
                <td align="center">82,29</td>
                <td align="center">8,62</td>
                <td align="center">29,75</td>
                <td align="center">4,05</td>
                <td align="center">102,18</td>
                <td align="center">9,90</td>
                <td align="center">40,97</td>
                <td align="center">15,69</td>
                <td align="center">118,35</td>
                <td align="center">16,79</td>
                <td align="center">73,45</td>
                <td align="center">26,88</td>
              </tr>
              <tr>
                <td>Para&#237;ba</td>
                <td align="center">81,41</td>
                <td align="center">4,33</td>
                <td align="center">22,58</td>
                <td align="center">5,17</td>
                <td align="center">80,50</td>
                <td align="center">8,25</td>
                <td align="center">23,41</td>
                <td align="center">8,39</td>
                <td align="center">126,14</td>
                <td align="center">21,99</td>
                <td align="center">72,36</td>
                <td align="center">28,95</td>
              </tr>
              <tr>
                <td>Pernambuco</td>
                <td align="center">135,83</td>
                <td align="center">12,94</td>
                <td align="center">34,49</td>
                <td align="center">10,22</td>
                <td align="center">162,37</td>
                <td align="center">20,83</td>
                <td align="center">49,15</td>
                <td align="center">19,47</td>
                <td align="center">133,16</td>
                <td align="center">36,72</td>
                <td align="center">72,86</td>
                <td align="center">27,94</td>
              </tr>
              <tr>
                <td>Alagoas</td>
                <td align="center">123,47</td>
                <td align="center">10,06</td>
                <td align="center">33,41</td>
                <td align="center">10,12</td>
                <td align="center">125,41</td>
                <td align="center">15,92</td>
                <td align="center">31,67</td>
                <td align="center">15,28</td>
                <td align="center">153,87</td>
                <td align="center">21,57</td>
                <td align="center">61,66</td>
                <td align="center">39,11</td>
              </tr>
              <tr>
                <td>Sergipe</td>
                <td align="center">110,36</td>
                <td align="center">11,59</td>
                <td align="center">32,05</td>
                <td align="center">13,43</td>
                <td align="center">97,30</td>
                <td align="center">16,95</td>
                <td align="center">43,12</td>
                <td align="center">17,55</td>
                <td align="center">113,30</td>
                <td align="center">20,85</td>
                <td align="center">66,71</td>
                <td align="center">28,97</td>
              </tr>
              <tr>
                <td>Bahia</td>
                <td align="center">111,81</td>
                <td align="center">13,88</td>
                <td align="center">31,28</td>
                <td align="center">5,83</td>
                <td align="center">115,46</td>
                <td align="center">18,92</td>
                <td align="center">36,30</td>
                <td align="center">13,89</td>
                <td align="center">99,32</td>
                <td align="center">21,59</td>
                <td align="center">61,49</td>
                <td align="center">22,66</td>
              </tr>
              <tr>
                <td>Minas Gerais</td>
                <td align="center">256,67</td>
                <td align="center">29,72</td>
                <td align="center">69,83</td>
                <td align="center">11,63</td>
                <td align="center">206,35</td>
                <td align="center">37,25</td>
                <td align="center">68,44</td>
                <td align="center">15,30</td>
                <td align="center">94,92</td>
                <td align="center">22,85</td>
                <td align="center">68,27</td>
                <td align="center">16,60</td>
              </tr>
              <tr>
                <td>Esp&#237;rito Santo</td>
                <td align="center">219,94</td>
                <td align="center">24,11</td>
                <td align="center">60,68</td>
                <td align="center">5,22</td>
                <td align="center">206,60</td>
                <td align="center">22,49</td>
                <td align="center">74,42</td>
                <td align="center">17,20</td>
                <td align="center">109,86</td>
                <td align="center">18,55</td>
                <td align="center">75,88</td>
                <td align="center">19,58</td>
              </tr>
              <tr>
                <td>Rio de Janeiro</td>
                <td align="center">354,95</td>
                <td align="center">44,29</td>
                <td align="center">102,68</td>
                <td align="center">27,00</td>
                <td align="center">265,42</td>
                <td align="center">53,50</td>
                <td align="center">98,24</td>
                <td align="center">32,09</td>
                <td align="center">123,65</td>
                <td align="center">20,58</td>
                <td align="center">74,46</td>
                <td align="center">22,18</td>
              </tr>
              <tr>
                <td>S&#227;o Paulo</td>
                <td align="center">328,54</td>
                <td align="center">24,47</td>
                <td align="center">94,45</td>
                <td align="center">19,58</td>
                <td align="center">246,49</td>
                <td align="center">38,42</td>
                <td align="center">97,23</td>
                <td align="center">20,25</td>
                <td align="center">114,23</td>
                <td align="center">21,66</td>
                <td align="center">76,74</td>
                <td align="center">14,64</td>
              </tr>
              <tr>
                <td>Paran&#225;</td>
                <td align="center">299,72</td>
                <td align="center">23,03</td>
                <td align="center">88,41</td>
                <td align="center">9,27</td>
                <td align="center">266,11</td>
                <td align="center">43,23</td>
                <td align="center">92,01</td>
                <td align="center">15,77</td>
                <td align="center">105,50</td>
                <td align="center">24,16</td>
                <td align="center">79,38</td>
                <td align="center">19,36</td>
              </tr>
              <tr>
                <td>Santa Catarina</td>
                <td align="center">244,17</td>
                <td align="center">31,96</td>
                <td align="center">74,37</td>
                <td align="center">10,94</td>
                <td align="center">205,84</td>
                <td align="center">44,60</td>
                <td align="center">94,10</td>
                <td align="center">18,21</td>
                <td align="center">99,62</td>
                <td align="center">23,63</td>
                <td align="center">82,05</td>
                <td align="center">17,27</td>
              </tr>
              <tr>
                <td>Rio Grande do Sul</td>
                <td align="center">294,03</td>
                <td align="center">41,78</td>
                <td align="center">109,92</td>
                <td align="center">6,74</td>
                <td align="center">232,87</td>
                <td align="center">55,84</td>
                <td align="center">118,45</td>
                <td align="center">15,94</td>
                <td align="center">93,77</td>
                <td align="center">26,37</td>
                <td align="center">89,52</td>
                <td align="center">20,88</td>
              </tr>
              <tr>
                <td>Mato Grosso do Sul</td>
                <td align="center">241,86</td>
                <td align="center">28,07</td>
                <td align="center">66,09</td>
                <td align="center">8,19</td>
                <td align="center">224,07</td>
                <td align="center">36,40</td>
                <td align="center">79,30</td>
                <td align="center">16,38</td>
                <td align="center">127,05</td>
                <td align="center">24,28</td>
                <td align="center">75,53</td>
                <td align="center">18,88</td>
              </tr>
              <tr>
                <td>Mato Grosso</td>
                <td align="center">132,64</td>
                <td align="center">15,48</td>
                <td align="center">30,87</td>
                <td align="center">2,82</td>
                <td align="center">159,20</td>
                <td align="center">24,64</td>
                <td align="center">46,30</td>
                <td align="center">12,78</td>
                <td align="center">109,91</td>
                <td align="center">27,64</td>
                <td align="center">68,32</td>
                <td align="center">23,48</td>
              </tr>
              <tr>
                <td>Goi&#225;s</td>
                <td align="center">168,28</td>
                <td align="center">20,26</td>
                <td align="center">44,23</td>
                <td align="center">5,18</td>
                <td align="center">218,97</td>
                <td align="center">31,28</td>
                <td align="center">65,08</td>
                <td align="center">14,59</td>
                <td align="center">115,68</td>
                <td align="center">31,61</td>
                <td align="center">73,81</td>
                <td align="center">20,39</td>
              </tr>
              <tr>
                <td>Distrito Federal</td>
                <td align="center">252,91</td>
                <td align="center">46,44</td>
                <td align="center">102,71</td>
                <td align="center">20,86</td>
                <td align="center">242,99</td>
                <td align="center">38,02</td>
                <td align="center">109,77</td>
                <td align="center">29,10</td>
                <td align="center">74,66</td>
                <td align="center">16,71</td>
                <td align="center">67,97</td>
                <td align="center">13,61</td>
              </tr>
              <tr>
                <td colspan="13">
                  <bold>Quartis das doen&#231;as cr&#244;nicas n&#227;o transmiss&#237;veis de acordo com cores e intensidade das cores</bold>
                </td>
              </tr>
              <tr>
                <td>Doen&#231;as do aparelho circulat&#243;rio</td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>0-24%</bold>
                </td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>25-49%</bold>
                </td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>50-75%</bold>
                </td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>&gt;75%</bold>
                </td>
              </tr>
              <tr>
                <td>Doen&#231;as respirat&#243;rias cr&#244;nicas</td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>0-24%</bold>
                </td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>25-49%</bold>
                </td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>50-75%</bold>
                </td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>&gt;75%</bold>
                </td>
              </tr>
              <tr>
                <td>Neoplasias</td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>0-24%</bold>
                </td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>25-49%</bold>
                </td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>50-75%</bold>
                </td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>&gt;75%</bold>
                </td>
              </tr>
              <tr>
                <td>Diabetes mellitus</td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>0-24%</bold>
                </td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>25-49%</bold>
                </td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>50-75%</bold>
                </td>
                <td align="center" colspan="3" rowspan="1">
                  <bold>&gt;75%</bold>
                </td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
      </p>
      <p>Na regi&#227;o Nordeste, todas as DCNT apresentaram aumento nas taxas de mortalidade, com exce&#231;&#227;o para as DAC na Bahia e Pernambuco, que permaneceu no mesmo quartil nos tr&#234;s anos observados. DM foi a doen&#231;a que atingiu os maiores quartis em todas as UF &#224; exce&#231;&#227;o do Cear&#225; que, apesar do aumento, n&#227;o atingiu o maior quartil. Ap&#243;s DM, as NEO, seguidas da DRC e DAC foram, na sequ&#234;ncia, nesta regi&#227;o, as doen&#231;as que mais afetaram a popula&#231;&#227;o. Ainda na regi&#227;o Nordeste, Pernambuco se destaca por ser a UF que obteve os maiores quartis em todas as doen&#231;as (<xref ref-type="table" rid="t1">Tabela 1</xref>).</p>
      <p>Por outro lado, nas regi&#245;es Sudeste, Sul e Centro-Oeste, com elevadas taxas em 1980, houve tend&#234;ncia a redu&#231;&#227;o da mortalidade por todas as DCNT, como observado pela redu&#231;&#227;o da intensidade de cores dos quartis, exceto para as NEO nas duas primeiras regi&#245;es que apresentaram estabilidade e, no Centro-Oeste da DRC em Goi&#225;s e DM em Mato Grosso. O DF se sobressai com queda em todas as DCNT (<xref ref-type="table" rid="t1">Tabela 1</xref>).</p>
      <p>A <xref ref-type="table" rid="t2">Tabela 2</xref> mostra a raz&#227;o entre os sexos masculino/feminino. Assim, os n&#250;meros superiores a 1,0 significam que os valores para o sexo masculino s&#227;o superiores aos femininos, e os n&#250;meros inferiores a 1,0 que os valores no sexo feminino s&#227;o maiores que no masculino.</p>
      <p>
        <table-wrap id="t2">
          <label>Tabela 2</label>
          <caption>
            <title>&#8211; Raz&#227;o entre as taxas brutas de mortalidade nos sexos masculino e feminino, de acordo com as doen&#231;as cr&#244;nicas n&#227;o transmiss&#237;veis, em per&#237;odos de cinco anos, por regi&#227;o geogr&#225;fica</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
              <col/>
            </colgroup>
            <thead>
              <tr>
                <th align="left" style="font-weight:normal"> </th>
                <th align="left">Regi&#227;o / Per&#237;odo</th>
                <th>1980-1984</th>
                <th>1985-1989</th>
                <th>1990-1994</th>
                <th>1995-1999</th>
                <th>2000-2004</th>
                <th>2005-2009</th>
                <th>2010-2014</th>
                <th>2015-2019</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td rowspan="5">Doen&#231;as do aparelho circulat&#243;rio</td>
                <td>Norte</td>
                <td align="center">1,14</td>
                <td align="center">1,15</td>
                <td align="center">1,18</td>
                <td align="center">1,19</td>
                <td align="center">1,26</td>
                <td align="center">1,29</td>
                <td align="center">1,31</td>
                <td align="center">1,29</td>
              </tr>
              <tr>
                <td>Nordeste</td>
                <td align="center">1,12</td>
                <td align="center">1,16</td>
                <td align="center">1,17</td>
                <td align="center">1,11</td>
                <td align="center">1,12</td>
                <td align="center">1,11</td>
                <td align="center">1,13</td>
                <td align="center">1,13</td>
              </tr>
              <tr>
                <td>Sudeste</td>
                <td align="center">1,19</td>
                <td align="center">1,21</td>
                <td align="center">1,19</td>
                <td align="center">1,15</td>
                <td align="center">1,15</td>
                <td align="center">1,14</td>
                <td align="center">1,13</td>
                <td align="center">1,12</td>
              </tr>
              <tr>
                <td>Sul</td>
                <td align="center">1,22</td>
                <td align="center">1,19</td>
                <td align="center">1,16</td>
                <td align="center">1,12</td>
                <td align="center">1,11</td>
                <td align="center">1,09</td>
                <td align="center">1,08</td>
                <td align="center">1,10</td>
              </tr>
              <tr>
                <td>Centro-Oeste</td>
                <td align="center">1,27</td>
                <td align="center">1,30</td>
                <td align="center">1,31</td>
                <td align="center">1,26</td>
                <td align="center">1,31</td>
                <td align="center">1,31</td>
                <td align="center">1,29</td>
                <td align="center">1,28</td>
              </tr>
              <tr>
                <td rowspan="5">Doen&#231;as respirat&#243;rias cr&#244;nicas</td>
                <td>Norte</td>
                <td align="center">1,24</td>
                <td align="center">1,25</td>
                <td align="center">1,26</td>
                <td align="center">1,22</td>
                <td align="center">1,28</td>
                <td align="center">1,31</td>
                <td align="center">1,28</td>
                <td align="center">1,20</td>
              </tr>
              <tr>
                <td>Nordeste</td>
                <td align="center">1,22</td>
                <td align="center">1,25</td>
                <td align="center">1,25</td>
                <td align="center">1,16</td>
                <td align="center">1,14</td>
                <td align="center">1,13</td>
                <td align="center">1,11</td>
                <td align="center">1,03</td>
              </tr>
              <tr>
                <td>Sudeste</td>
                <td align="center">1,48</td>
                <td align="center">1,53</td>
                <td align="center">1,49</td>
                <td align="center">1,40</td>
                <td align="center">1,38</td>
                <td align="center">1,36</td>
                <td align="center">1,29</td>
                <td align="center">1,20</td>
              </tr>
              <tr>
                <td>Sul</td>
                <td align="center">1,77</td>
                <td align="center">1,76</td>
                <td align="center">1,76</td>
                <td align="center">1,55</td>
                <td align="center">1,52</td>
                <td align="center">1,45</td>
                <td align="center">1,32</td>
                <td align="center">1,19</td>
              </tr>
              <tr>
                <td>Centro-Oeste</td>
                <td align="center">1,28</td>
                <td align="center">1,30</td>
                <td align="center">1,32</td>
                <td align="center">1,32</td>
                <td align="center">1,35</td>
                <td align="center">1,36</td>
                <td align="center">1,29</td>
                <td align="center">1,28</td>
              </tr>
              <tr>
                <td rowspan="5">Neoplasias</td>
                <td>Norte</td>
                <td align="center">1,12</td>
                <td align="center">1,10</td>
                <td align="center">1,06</td>
                <td align="center">1,06</td>
                <td align="center">1,11</td>
                <td align="center">1,09</td>
                <td align="center">1,11</td>
                <td align="center">1,09</td>
              </tr>
              <tr>
                <td>Nordeste</td>
                <td align="center">0,99</td>
                <td align="center">1,01</td>
                <td align="center">1,03</td>
                <td align="center">1,02</td>
                <td align="center">1,05</td>
                <td align="center">1,09</td>
                <td align="center">1,10</td>
                <td align="center">1,08</td>
              </tr>
              <tr>
                <td>Sudeste</td>
                <td align="center">1,26</td>
                <td align="center">1,26</td>
                <td align="center">1,22</td>
                <td align="center">1,23</td>
                <td align="center">1,23</td>
                <td align="center">1,22</td>
                <td align="center">1,19</td>
                <td align="center">1,14</td>
              </tr>
              <tr>
                <td>Sul</td>
                <td align="center">1,43</td>
                <td align="center">1,39</td>
                <td align="center">1,36</td>
                <td align="center">1,34</td>
                <td align="center">1,36</td>
                <td align="center">1,34</td>
                <td align="center">1,31</td>
                <td align="center">1,24</td>
              </tr>
              <tr>
                <td>Centro-Oeste</td>
                <td align="center">1,13</td>
                <td align="center">1,12</td>
                <td align="center">1,17</td>
                <td align="center">1,19</td>
                <td align="center">1,20</td>
                <td align="center">1,23</td>
                <td align="center">1,22</td>
                <td align="center">1,17</td>
              </tr>
              <tr>
                <td rowspan="5">Diabetes mellitus</td>
                <td>Norte</td>
                <td align="center">0,74</td>
                <td align="center">0,70</td>
                <td align="center">0,75</td>
                <td align="center">0,75</td>
                <td align="center">0,80</td>
                <td align="center">0,80</td>
                <td align="center">0,85</td>
                <td align="center">0,91</td>
              </tr>
              <tr>
                <td>Nordeste</td>
                <td align="center">0,77</td>
                <td align="center">0,77</td>
                <td align="center">0,75</td>
                <td align="center">0,74</td>
                <td align="center">0,73</td>
                <td align="center">0,76</td>
                <td align="center">0,80</td>
                <td align="center">0,84</td>
              </tr>
              <tr>
                <td>Sudeste</td>
                <td align="center">0,68</td>
                <td align="center">0,68</td>
                <td align="center">0,70</td>
                <td align="center">0,73</td>
                <td align="center">0,78</td>
                <td align="center">0,82</td>
                <td align="center">0,83</td>
                <td align="center">0,86</td>
              </tr>
              <tr>
                <td>Sul</td>
                <td align="center">0,67</td>
                <td align="center">0,66</td>
                <td align="center">0,67</td>
                <td align="center">0,70</td>
                <td align="center">0,74</td>
                <td align="center">0,78</td>
                <td align="center">0,81</td>
                <td align="center">0,88</td>
              </tr>
              <tr>
                <td>Centro-Oeste</td>
                <td align="center">0,79</td>
                <td align="center">0,72</td>
                <td align="center">0,72</td>
                <td align="center">0,76</td>
                <td align="center">0,79</td>
                <td align="center">0,84</td>
                <td align="center">0,88</td>
                <td align="center">0,95</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
      </p>
      <p>As taxas no sexo masculino foram maiores em todo o per&#237;odo para as DAC, DRC e NEO. A exce&#231;&#227;o foi NEO no per&#237;odo de 1980 a 1984 na regi&#227;o Nordeste com raz&#227;o inferior a 1. Para as taxas de mortalidade relacionadas a DM, em todo o per&#237;odo observado, foram superiores no sexo feminino em todas as regi&#245;es geogr&#225;ficas.</p>
      <p>Na <xref ref-type="fig" rid="f03">Figura 2</xref> nota-se que, em todos os casos, as UF que apresentaram maior redu&#231;&#227;o nas taxas de mortalidade foram as que apresentaram a menor varia&#231;&#227;o no IDHM, como Rio de Janeiro, S&#227;o Paulo, Distrito Federal, Rio Grande do Sul, Santa Catarina, Esp&#237;rito Santo e Paran&#225;. Ao contr&#225;rio, Maranh&#227;o, Piau&#237; e Para&#237;ba, que apresentaram as maiores varia&#231;&#245;es no IDHM, apresentaram as menores quedas nas taxas de mortalidade (<xref ref-type="fig" rid="f03">Figura 2</xref>). Adicionalmente, a <xref ref-type="fig" rid="f04">Figura 3</xref> demonstra redu&#231;&#227;o nas taxas de mortalidade em todas as UF que apresentaram IDHM igual ou acima de 0,7, como nas regi&#245;es Sudeste, Sul e Centro-Oeste. As UF com menor varia&#231;&#227;o na mortalidade eram as que tinham o maior IDHM (<xref ref-type="fig" rid="f04">Figura 3</xref>). Os coeficientes de correla&#231;&#227;o encontrados entre o IDHM de 2010 e as varia&#231;&#245;es percentuais nas taxas de mortalidade foram: &#8722;0,62 para DAC, &#8722;0,59 para DRC, &#8722;0,45 para DM e &#8722;0,64 para NEO, todos com n&#237;vel de signific&#226;ncia inferior a 0,05.</p>
      <p>
        <fig id="f03">
          <label>Figura 2</label>
          <caption>
            <title>&#8211; Gr&#225;fico de dispers&#227;o. Correla&#231;&#227;o entre a varia&#231;&#227;o percentual do &#205;ndice de Desenvolvimento Humano Municipal (IDHM) 1991 e 2010 com a varia&#231;&#227;o percentual da taxa de mortalidade das doen&#231;as cr&#244;nicas n&#227;o transmiss&#237;veis: doen&#231;a do aparelho circulat&#243;rio (DAC); doen&#231;as respirat&#243;rias cr&#244;nicas (DRC); neoplasias (NEO); diabetes mellitus (DM), 1990 e 2019, no Brasil nas UF, em ambos os sexos.</title>
          </caption>
          <graphic xlink:href="1678-4170-abc-120-04-e20211009-11009-gf03.tif"/></fig>
      </p>
      <p>
        <fig id="f04">
          <label>Figura 3</label>
          <caption>
            <title>&#8211; Gr&#225;fico de dispers&#227;o. Correla&#231;&#227;o entre &#205;ndice de Desenvolvimento Humano Municipal (IDHM) absoluto no ano de 2010 com a varia&#231;&#227;o percentual da taxa de mortalidade das doen&#231;as cr&#244;nicas n&#227;o transmiss&#237;veis: doen&#231;a do aparelho circulat&#243;rio (DAC); doen&#231;as respirat&#243;rias cr&#244;nicas (DRC); neoplasias (NEO); diabetes mellitus (DM), 1990 e 2019, no Brasil nas UF, em ambos os sexos.</title>
          </caption>
          <graphic xlink:href="1678-4170-abc-120-04-e20211009-11009-gf04.tif"/></fig>
      </p>
    </sec>
    <sec sec-type="discussion">
      <title>Discuss&#227;o</title>
      <p>O presente estudo evidenciou o decl&#237;nio das taxas de mortalidade padronizadas por DCNT no Brasil, em todas as idades e sexo, no per&#237;odo de 40 anos de observa&#231;&#227;o. Estes resultados s&#227;o semelhantes ao encontrado por Cardoso et al.,<sup><xref ref-type="bibr" rid="B18">18</xref></sup> no qual os autores observaram redu&#231;&#227;o nas taxas de doen&#231;as cardiovasculares em todas as regi&#245;es brasileiras, entretanto, estas apresentaram as taxas m&#233;dias mais altas em ambos os per&#237;odos, seguidas pelas taxas de NEO, DM e DRC.</p>
      <p>A queda das taxas padronizadas de mortalidade por DCNT tamb&#233;m foi observada por Malta et al.,<sup><xref ref-type="bibr" rid="B19">19</xref>,<xref ref-type="bibr" rid="B20">20</xref></sup> que descreveram as tend&#234;ncias de mortalidade entre 1990 e 2017 no Brasil. Al&#233;m da redu&#231;&#227;o de 35% nas taxas de mortalidade padronizada das DCNT, os autores evidenciaram redu&#231;&#227;o na mortalidade por doen&#231;as cardiovasculares em 47,9% e a mortalidade por DRC, DM e NEO diminuiu 41,3%, 18% e 11,9%, respectivamente, com 15 anos ininterruptos de queda, com tend&#234;ncia de aumento dos &#243;bitos para todas as DCNT, em cada grupo, ap&#243;s 2015. Em nosso estudo, por outro lado, observou-se eleva&#231;&#245;es nas taxas de mortalidade por NEO e DM (<xref ref-type="fig" rid="f02">Figura 1</xref>).</p>
      <p>As taxas de mortalidade por DCNT foram avaliadas por Silva e Ramalho,<sup><xref ref-type="bibr" rid="B21">21</xref></sup> que analisaram a situa&#231;&#227;o do perfil de morbimortalidade do Brasil e compararam as modifica&#231;&#245;es ocorridas para a mortalidade proporcional dos grandes grupos de causa, atrav&#233;s da representa&#231;&#227;o do crescimento da popula&#231;&#227;o desde 1980 com proje&#231;&#245;es at&#233; 2033. Os autores observaram que a mortalidade por DCNT j&#225; representava cerca de 70% da mortalidade total do pa&#237;s e que as DAC s&#227;o o grupo de mortalidade com maior peso proporcional durante todo o per&#237;odo, com proje&#231;&#227;o de redu&#231;&#227;o em 2033 (113,1 por 100.000 habitantes), quando comparada com 1980 (273,9 por 100.000 habitantes). De forma semelhante, em nosso estudo, notou-se que apesar da redu&#231;&#227;o das DCNT ao longo do per&#237;odo, a partir de 2019 suas taxas ultrapassaram as demais causas de morte (<ext-link ext-link-type="uri" xlink:href="http://abccardiol.org/supplementary-material/2023/12004/2021-1009_AO_Material-Suplementar.pdf">Material Suplementar - Figura 1A</ext-link>). Por outro lado, apesar da elevada taxa de mortalidade das DCNT, as DAC apresentaram decl&#237;nio em seu percentual de &#243;bito de 67% para 49% (<ext-link ext-link-type="uri" xlink:href="http://abccardiol.org/supplementary-material/2023/12004/2021-1009_AO_Material-Suplementar.pdf">Material Suplementar - Figura 1B</ext-link>).</p>
      <p>Quando s&#227;o avaliadas as taxas padronizadas de mortalidade, o presente estudo apresentou resultados semelhantes a um estudo transversal que utilizou estimativas do estudo Carga Global de Doen&#231;as 2015 para o Brasil.<sup><xref ref-type="bibr" rid="B20">20</xref></sup> Em ambos os estudos, observaram-se taxas mais elevadas ao longo do per&#237;odo, entretanto com tend&#234;ncias a decl&#237;nio para doen&#231;as cardiovasculares e doen&#231;as respirat&#243;rias cr&#244;nicas, enquanto neoplasias e diabetes apresentaram taxas est&#225;veis, com tend&#234;ncia a eleva&#231;&#227;o, entre 1990 e 2015 no Brasil.<sup><xref ref-type="bibr" rid="B20">20</xref></sup></p>
      <p>De uma forma geral, as compara&#231;&#245;es entre as pr&#243;prias DCNT s&#227;o dif&#237;ceis justamente pelo fato de apresentarem diferentes ordens de grandeza dos &#243;bitos. Assim, no presente estudo, optou-se pela constru&#231;&#227;o de uma tabela din&#226;mica com os quartis de cada DCNT, identificando as intensidades de varia&#231;&#245;es entre os intervalos ao longo dos anos, permitindo a compara&#231;&#227;o proporcional entre elas (<xref ref-type="table" rid="t1">Tabela 1</xref>). Na regi&#227;o Nordeste, todas as DCNT apresentaram aumento nas taxas de mortalidade, sendo DM a doen&#231;a que atingiu os maiores quartis. Por outro lado, os menores quartis foram observados nas regi&#245;es Sudeste, Sul e Centro Oeste, com exce&#231;&#227;o do Mato Grosso. Estes resultados s&#227;o semelhantes a outro estudo j&#225; mencionado.<sup><xref ref-type="bibr" rid="B18">18</xref></sup></p>
      <p>As DAC apresentaram as maiores quedas na mortalidade, preponderando com maiores mudan&#231;as no quartis nas regi&#245;es mais ricas do pa&#237;s (Sudeste, Sul e Centro-Oeste) e em menor grau na regi&#227;o Norte, enquanto a regi&#227;o Nordeste apresentou aumento nas taxas de mortalidade por essas doen&#231;as. Mansur et al.,<sup><xref ref-type="bibr" rid="B22">22</xref></sup> em estudo que analisou os dados das tend&#234;ncias da mortalidade por doen&#231;as cardiovasculares em homens e mulheres com mais de 30 anos de idade nas cinco regi&#245;es do Brasil, observaram aumento na mortalidade por estas doen&#231;as na regi&#227;o Nordeste com redu&#231;&#245;es nas demais regi&#245;es, sendo as mais significativas nas regi&#245;es Sul e Sudeste. Em rela&#231;&#227;o &#224;s DRC, observou-se tend&#234;ncia a aumento para regi&#245;es orte e Nordeste e queda para as regi&#245;es Sul, Sudeste e Centro-Oeste. Quanto &#224;s NEO, as regi&#245;es Sudeste e Sul apresentaram as taxas nos quartis mais elevados. Cardoso et al.,<sup><xref ref-type="bibr" rid="B18">18</xref></sup>confirmaram os dados descritos acima com estudo que encontrou redu&#231;&#227;o nas taxas m&#233;dias de mortalidade por DRC nas regi&#245;es Centro-Oeste, Norte, Sudeste e Sul. Entretanto, contrastando com o presente estudo, encontroaram redu&#231;&#227;o nas taxas medias por NEO na regi&#227;o Sul. Estes resultados observados, podem pelo menos em parte, estar relacionados a varia&#231;&#245;es nos indicadores sociais, como j&#225; demonstrado em estudo anterior.<sup><xref ref-type="bibr" rid="B13">13</xref></sup></p>
      <p>Em rela&#231;&#227;o &#224; raz&#227;o da mortalidade entre homens e mulheres, para as DAC, DRC e NEO, a mortalidade prevaleceu no sexo masculino, ao contr&#225;rio do ocorrido na DM onde as taxas foram mais elevadas no sexo feminino (<xref ref-type="table" rid="t2">Tabela 2</xref>), semelhante aos resultados de outros estudos.<sup><xref ref-type="bibr" rid="B23">23</xref>,<xref ref-type="bibr" rid="B24">24</xref></sup></p>
      <p>Quando foram avaliadas as rela&#231;&#245;es com o IDH, observou-se que a mortalidade por DCNT no Brasil apresentou comportamento epidemiol&#243;gico desigual entre as regi&#245;es, como observado nas <xref ref-type="fig" rid="f03">Figuras 2</xref> e <xref ref-type="fig" rid="f04">3</xref>. Na primeira, observa-se que h&#225; rela&#231;&#227;o inversa entre a varia&#231;&#227;o do IDH e a varia&#231;&#227;o das taxas de mortalidade para todas as DCNT. Entretanto, nota-se o mesmo padr&#227;o de dispers&#227;o quando s&#227;o observadas as posi&#231;&#245;es das UF nos gr&#225;ficos, com as UF das regi&#245;es Norte e Nordeste apresentando as maiores varia&#231;&#245;es no IDH, entretanto com as varia&#231;&#245;es mais baixas (ou inversas) nas taxas de mortalidade. Este achado pode ser explicado pelo fato da posi&#231;&#227;o inicial do IDH destas regi&#245;es, que mesmo diante de uma melhora importante, ainda continuam insuficientes para provocarem impactos positivos nas taxas de mortalidade quando observados isoladamente.</p>
      <p>Ao contr&#225;rio, quando as varia&#231;&#245;es nas taxas de mortalidade s&#227;o comparadas ao valor absoluto do IDH (<xref ref-type="fig" rid="f04">Figura 3</xref>), nota-se rela&#231;&#227;o direta entre as vari&#225;veis. Nesta figura, para todas as DCNT, observa-se, de uma forma geral, que as UF que apresentaram IDH em 2010 acima de 0,7 apresentaram as melhores varia&#231;&#245;es nas taxas de mortalidade, demonstrando que, provavelmente, mais importante que a varia&#231;&#227;o no IDH &#233; o valor que ele atinge, como observado em estudos anteriores.<sup><xref ref-type="bibr" rid="B12">12</xref>,<xref ref-type="bibr" rid="B26">26</xref>-<xref ref-type="bibr" rid="B31">31</xref></sup></p>
      <p>O presente estudo n&#227;o aborda as causas m&#250;ltiplas de &#243;bito, n&#227;o sendo poss&#237;vel avaliar a presen&#231;a de mais de uma DCNT nas mesmas declara&#231;&#245;es de &#243;bito. Al&#233;m disso, ao trabalhar com a causa b&#225;sica selecionada e disponibilizada no DATASUS, o banco de dados se torna mais sens&#237;vel &#224; incompletude das declara&#231;&#245;es de &#243;bito e aos seus erros de preenchimento. Por fim, a indisponibilidade de dados referentes ao IDHM nos &#250;ltimos anos n&#227;o permite compara&#231;&#245;es temporais mais pr&#243;ximas com as taxas de mortalidade.</p>
    </sec>
    <sec sec-type="conclusions">
      <title>Conclus&#245;es</title>
      <p>A mortalidade por DCNT diminuiu ao longo dos 40 anos de observa&#231;&#227;o, sobretudo nas DAC. Quanto &#224;s DRC, apresentaram leves oscila&#231;&#245;es, enquanto as NEO e DM apresentaram eleva&#231;&#227;o ao longo do per&#237;odo. No final do per&#237;odo do estudo, tendem a estabiliza&#231;&#227;o. Os estados das regi&#245;es Nordeste e Norte tenderam a apresentar taxas de mortalidade mais elevadas quando comparados aos das regi&#245;es Sudeste, Sul e Centro Oeste. O estudo aponta correla&#231;&#227;o do IDH com a redu&#231;&#227;o nas taxas de mortalidade das DCNT, sobretudo as DAC, a partir de um n&#237;vel alto de desenvolvimento humano. Estes achados apontam n&#227;o somente para a import&#226;ncia de medidas que reduzam a mortalidade por DCNT, mas que estas incluam necessariamente medidas que melhorem as condi&#231;&#245;es socioecon&#244;micas da popula&#231;&#227;o, considerando o contexto regional e visando reduzir as desigualdades crescentes no acesso aos recursos de preven&#231;&#227;o e tratamento.</p>
    </sec>
  </body>
  <back>
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  <sub-article article-type="translation" id="TRen" xml:lang="en">
    <front-stub>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Original Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Association between Mortality from Chronic Noncommunicable Diseases and Human Development Index in Brazil between 1980 and 2019</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Feliciano</surname>
            <given-names>Sandra Chagas da Costa</given-names>
          </name>
          <role>Conception and design of the research</role>
          <role>Acquisition of data</role>
          <role>Analysis and interpretation of the data</role>
          <role>Statistical analysis</role>
          <role>Obtaining financing</role>
          <role>Writing of the manuscript</role>
          <role>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">
          <contrib-id contrib-id-type="orcid">0000-0001-8121-5959</contrib-id>
          <name>
            <surname>Villela</surname>
            <given-names>Paolo Blanco</given-names>
          </name>
          <role>Conception and design of the research</role>
          <role>Acquisition of data</role>
          <role>Analysis and interpretation of the data</role>
          <role>Statistical analysis</role>
          <role>Obtaining financing</role>
          <role>Writing of the manuscript</role>
          <role>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">
          <contrib-id contrib-id-type="orcid">0000-0002-0737-6188</contrib-id>
          <name>
            <surname>Oliveira</surname>
            <given-names>Gl&#225;ucia Maria Moraes de</given-names>
          </name>
          <role>Conception and design of the research</role>
          <role>Acquisition of data</role>
          <role>Analysis and interpretation of the data</role>
          <role>Statistical analysis</role>
          <role>Obtaining financing</role>
          <role>Writing of the manuscript</role>
          <role>Critical revision of the manuscript for important intellectual content</role>
          <xref ref-type="aff" rid="aff1001">
            <sup>1</sup>
          </xref>
        </contrib>
      </contrib-group>
      <aff id="aff1001">
        <label>1</label>
        <country country="BR">Brazil</country>
        <institution content-type="original">Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ &#8211; Brazil</institution>
      </aff>
      <author-notes>
        <corresp id="c01001"> Mailing Address: Paolo Blanco Villela &#8226; Rua Professor Rodolpho Paulo Rocco, 255 / 8<sup>o</sup>. Andar. Postal Code 21941-913, Rio de Janeiro, RJ &#8211; Brazil E-mail: pbvillela@gmail.com </corresp>
        <fn fn-type="conflict">
          <p>Potential conflict of interest</p>
          <p>No potential conflict of interest relevant to this article was reported.</p>
        </fn>
      </author-notes>
      <abstract>
        <title>Abstract</title>
        <sec>
          <title>Background</title>
          <p> Chronic noncommunicable diseases (CNCDs) caused more than 734,000 deaths (55% of all deaths) in Brazil in 2019, with an important socioeconomic impact.</p>
        </sec>
        <sec>
          <title>Objectives</title>
          <p> To analyze the mortality rates from CNCDs in Brazil from 1980 to 2019 and their association with socioeconomic indicators.</p>
        </sec>
        <sec>
          <title>Method</title>
          <p> This was a descriptive, time-series study of deaths from CNCDs in Brazil from 1980 to 2019. Data on the annual frequencies of deaths and on population were obtained from the Department of Informatics of the Brazilian Unified Health System. Crude and standardized mortality rates per 100,000 inhabitants were estimated using the direct method (Brazilian population in 2000). The quartiles of each CNCD were calculated, where a quartile change, due to an increase in mortality rate, was represented by a chromatic gradient. The Municipal Human Development Index (MHDI) of each Brazilian federative unit was extracted from the Atlas Brasil website and correlated with the rates of CNCD mortality.</p>
        </sec>
        <sec>
          <title>Results</title>
          <p> There was a reduction in mortality rates due to diseases of the circulatory system during the period, except in the Northeast Region. There was also an increase in mortality from neoplasia and diabetes, while the rates of chronic respiratory diseases showed little variation. There was an inverse correlation between the federative units with greater reduction in CNCD mortality rates and the MHDI.</p>
        </sec>
        <sec>
          <title>Conclusions</title>
          <p> The observed decrease in mortality due to diseases of the circulatory system may reflect an improvement in socioeconomic indicators in Brazil during the period. The increase in mortality rates due to neoplasms is probably related to the aging of the population. The higher mortality rates of diabetes seem to be associated with an increase in the prevalence of obesity in Brazilian women.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>Non Communicable Diseases</kwd>
        <kwd>Development Indicators</kwd>
        <kwd>Public Health</kwd>
        <kwd>Health of the Disabled</kwd>
        <kwd>Epidemiology</kwd>
        <kwd>Mortality</kwd>
      </kwd-group>
    </front-stub>
    <body>
      <sec sec-type="intro">
        <title>Introduction</title>
        <p>Chronic noncommunicable diseases (CNCDs) are represented by diseases of the circulatory system (DCS), neoplasms, diabetes mellitus (DM), and chronic respiratory diseases (CRDs).<sup><xref ref-type="bibr" rid="B1">1</xref></sup> They are generally characterized by a long period of latency and progression, irreversible lesions, and complications that lead to different degrees of disability or death,<sup><xref ref-type="bibr" rid="B2">2</xref></sup> and they are considered a major public health problem, as they represent the main causes of death and premature disability worldwide.<sup><xref ref-type="bibr" rid="B3">3</xref></sup></p>
        <p>In 2015, there were an estimated 41 million deaths from CNCDs worldwide, 36.6% of which occurred in people aged 30 to 69 years; more than 85% of these premature deaths occurred in low- and middle-income countries, causing an impact on their economic development and health care systems.<sup><xref ref-type="bibr" rid="B4">4</xref>,<xref ref-type="bibr" rid="B5">5</xref></sup> In Brazil, the Department of Informatics of the Brazilian Unified Health System (DATASUS, acronym in Portuguese) attributed more than 734,000 deaths to CNCDs in 2019, representing 55% of all deaths that occurred in the country. DCS, mainly represented by ischemic heart diseases (IHDs) and cerebrovascular diseases (CBVDs), occupy first place, with more than 362,000 deaths in this period.<sup><xref ref-type="bibr" rid="B6">6</xref></sup></p>
        <p>Several risk factors are common among CNCDs. In addition to the classic modifiable or behavioral risk factors, health determinants, i.e., social, economic, cultural, educational, ethnic/racial, psychological, and behavioral factors, influence indirectly the health conditions of the population and are interdependent regarding the occurrence of diseases.<sup><xref ref-type="bibr" rid="B7">7</xref>-<xref ref-type="bibr" rid="B9">9</xref></sup></p>
        <p>Studies carried out in Brazil have demonstrated that the improvement in socioeconomic indicators has been associated with a reduction in mortality from DCS,<sup><xref ref-type="bibr" rid="B10">10</xref></sup> and mortality rates from DCS, CBVDs, and hypertensive diseases varied inversely to the Human Development Index (HDI).<sup><xref ref-type="bibr" rid="B11">11</xref></sup> Despite this fact, few studies in Brazil have related the mortality rates from CNCDs to the HDI.<sup><xref ref-type="bibr" rid="B10">10</xref>-<xref ref-type="bibr" rid="B12">12</xref></sup></p>
        <p>The knowledge of the behavior and the distribution of diseases in the population over a long period are useful for the recommendation of public policies, as well as the evaluation, management, and planning of promotional and preventive actions by health care services. Thus, the aim of this study is to analyze the mortality rates of CNCDs in Brazil between 1980 to 2019, evaluating the relationship between the mortality rates for each CNCD and their associations with the HDI.</p>
      </sec>
      <sec sec-type="methods">
        <title>Methods</title>
        <p>This was as ecological, descriptive, time-series study of records of deaths from CNCDs, across all age groups and in both sexes, that occurred in Brazil in the period from 1980 to 2019. Data related to the annual frequency of deaths were obtained from the Mortality Information System (SIM), available on the website of the DATASUS of the Brazilian Ministry of Health.<sup><xref ref-type="bibr" rid="B6">6</xref></sup></p>
        <p>For the classification of deaths from 1980 to 1995, the categories of the 9th Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-9) were used: DCS (Chapter VII), IHD (Categories 410&#8211;414), CBVD (430&#8211;438), neoplasms (Categories 140&#8211;208; 239), DM (Category 250), and CRD (Categories 490&#8211;516 and 518&#8211;519), (WHO, 1978). For deaths from 1996 to 2019, the categories of the 10th Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) were used: DCS (Categories 100&#8211;199), IHD (Categories I20&#8211;I25), CBVD (Categories I60&#8211;I69), neoplasms (Categories C00&#8211;C97), DM (Categories E10&#8211;E14), and CRD (Categories J30&#8211;J98). Deaths throughout the time frame without known sex information were disregarded. All-cause mortality rates were also obtained for the same study period.<sup><xref ref-type="bibr" rid="B13">13</xref>,<xref ref-type="bibr" rid="B14">14</xref></sup></p>
        <p>Data referring to the Brazilian population, from the geographic regions (North, Northeast, Southeast, South, and Central-West) and the federative units were obtained from the DATASUS, based on the censuses of 1980, 1991, 2000, and 2010, intercensal projections until 2012, and population projections by the Brazilian Institute of Geography and Statistics (IBGE, acronym in Portuguese) from 2013 onwards. The data were stratified by sex into 8 age groups as follows: up to 19 years, 20 to 29 years, 30 to 39 years, 40 to 49 years, 50 to 59 years, 60 to 69 years, 70 to 79 years, and 80 years or more.</p>
        <p>The crude and standardized annual mortality rates from the CNCDs (DCS, neoplasms, CRD, and DM) per 100,000 inhabitants were estimated over the 40 years of observation by geographic region and federative unit, by the direct method, in both sexes, using the Brazilian population of the year 2000 as the standard. It should be emphasized that, in order to compare mortality rates in different populations, standardization by a standard population with the same age groups is indispensable to nullify the effect of uneven demographic distribution. Thus, the final product is the expected number of deaths if the crude rates found for each geographic region were applied to the same population (in this case, the year 2000).<sup><xref ref-type="bibr" rid="B15">15</xref></sup></p>
        <p>The analysis included the relationship between the standardized CNCD mortality rates per 100,000 inhabitants between 1980, 1994, and 2019 and their association with the total number of deaths in Brazil. Data from the federative unit of Tocantins were considered only after the year 1989.</p>
        <p>Standardized mortality rates per 100,000 inhabitants were calculated for each CNCD in each Brazilian federative unit for the years 1980, 1994, and 2019 and are represented by different colors. To allow a proportional comparison between CNCDs, medians and quartiles were calculated for DCS, DM, neoplasms, and CRD. The variation between quartiles over the years was represented by the variation in the intensity of the respective colors, in which they were more intense in cases of increase in rates with change in quartiles and less intense in cases of a decrease in rates with consequent changes in quartiles.</p>
        <p>For each region, crude mortality rates were estimated for sex (male and female), according to the CNCDs, in 8 periods of 5 years, from 1980 to 2019, with subsequent calculation of the rate ratio. It is worth noting that, from 1989 onwards, the North Region began to compute data from Tocantins, a federative unit created in 1988.</p>
        <p>Finally, scatter plots were constructed, and Pearson&#8217;s correlation coefficients were calculated for each CNCD and the 2010 HDI, adopting a statistical significance level of 5%. The HDI and its state and municipal dimensions, also called the Municipal Human Development Index (MHDI), were extracted from the Atlas Brasil website.<sup><xref ref-type="bibr" rid="B16">16</xref>,<xref ref-type="bibr" rid="B17">17</xref></sup></p>
        <p>Thus, the relationships between the mortality rates for each CNCD and the MHDI of each federative unit were evaluated. For data analysis and construction of tables and graphs, we used Microsoft Office Excel&#174; 2016 (Microsoft Corporation, USA).</p>
      </sec>
      <sec sec-type="results">
        <title>Results</title>
        <p>The crude rates of all CNCDs over the 40 years of observation showed slight oscillations, but a trend toward an increase, especially for DCS and neoplasms. With the standardization of the mortality rates, a decrease in DCS was observed, while the others showed slight oscillations, with a general trend toward stability during the analyzed period (<xref ref-type="fig" rid="f02001">Figure 1</xref>).</p>
        <p>
          <fig id="f02001">
            <label>Figure 1</label>
            <caption>
              <title>&#8211; Crude (1A) and standardized (1B) mortality rates from chronic noncommunicable diseases (DCS: diseases of the circulatory system; CRD: chronic respiratory diseases; DM: diabetes mellitus and NEO: neoplasms) per 100,000 inhabitants, in both sexes and across all age groups from 1980 to 2019 in Brazil.</title>
            </caption>
            <graphic xlink:href="1678-4170-abc-120-04-e20211009-11009-gf01-en.tif"/></fig>
        </p>
        <p>There was a decline in the standardized mortality rate for CNCDs, from 339.27 per 100,000 inhabitants in the year 1980 to 229.35 per 100,000 inhabitants in 2019, which also occurred with the standardized rates for the other causes, from 425.47 per 100,000 inhabitants in 1980 to 222.08 deaths per 100,000 inhabitants in 2019. Notably, DCS showed a reduction in rates, and CRDs showed oscillations with an increase in 1994 and a decrease in 2019. The DCS showed a reduction from 67% to 49% in the observed years, while neoplasms showed an increase from 21% to 31% in proportional mortality (<xref ref-type="fig" rid="f01001">Central Illustration</xref> and <ext-link ext-link-type="uri" xlink:href="http://abccardiol.org/supplementary-material/2023/12004/2021-1009_AO_Material-Suplementar.pdf">Supplementary Material &#8211; Figures 1A and 1B</ext-link>).</p>
        <p>
          <fig id="f01001">
            <label>Central Illustration</label>
            <caption>
              <title>: Association between Mortality from Chronic Noncommunicable Diseases and Human Development Index in Brazil between 1980 and 2019</title>
              <p>Definition of chronic noncommunicable diseases; mortality in Brazil with the percentage of deaths in 2019 and age-standardized mortality rates in 1980 and 2019; relationship between male and female sex regarding mortality rates; and possible association of mortality with the Human Development Index. CNCDs: chronic noncommunicable diseases.</p>
            </caption>
            <graphic xlink:href="1678-4170-abc-120-04-e20211009-11009-gf02-en.tif"/></fig>
        </p>
        <p>As seen in <xref ref-type="table" rid="t1001">Table 1</xref>, the North Region presented an increase in the quartiles of mortality rates due to neoplasms and DM across all federative units. Rond&#244;nia, Acre, and Amap&#225; showed an increase in CRD rates, especially in the last year, while, regarding the mortality rates for DCS, a decrease was observed across all federative units in the final year, except for Roraima and Tocantins (<xref ref-type="table" rid="t1001">Table 1</xref>).</p>
        <p>
          <table-wrap id="t1001">
            <label>Table 1</label>
            <caption>
              <title>&#8211; Standardized mortality rates per 100,000 inhabitants, by federative unit, distributed according to chronic noncommunicable diseases (colors) and their respective quartiles (color intensity) &#8211; Brazil, 1980, 1994, and 2019.</title>
            </caption>
            <table frame="hsides" rules="groups">
              <colgroup>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
              </colgroup>
              <thead>
                <tr>
                  <th align="left" scope="col">FU/Year</th>
                  <th colspan="4" scope="col">1980</th>
                  <th colspan="4" scope="col">1994</th>
                  <th colspan="4" scope="col">2019</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="left">Rond&#244;nia</td>
                  <td>189.71</td>
                  <td>25.73</td>
                  <td>49.39</td>
                  <td>3.37</td>
                  <td>143.17</td>
                  <td>33.24</td>
                  <td>51.50</td>
                  <td>23.36</td>
                  <td>111.45</td>
                  <td>29.56</td>
                  <td>74.92</td>
                  <td>26.50</td>
                </tr>
                <tr>
                  <td>Acre</td>
                  <td align="center">143.14</td>
                  <td align="center">22.62</td>
                  <td align="center">52.66</td>
                  <td align="center">1.98</td>
                  <td align="center">143.72</td>
                  <td align="center">23.85</td>
                  <td align="center">42.03</td>
                  <td align="center">8.25</td>
                  <td align="center">124.60</td>
                  <td align="center">48.59</td>
                  <td align="center">71.93</td>
                  <td align="center">22.25</td>
                </tr>
                <tr>
                  <td>Amazonas</td>
                  <td align="center">192.64</td>
                  <td align="center">10.60</td>
                  <td align="center">54.54</td>
                  <td align="center">4.06</td>
                  <td align="center">106.57</td>
                  <td align="center">17.16</td>
                  <td align="center">59.38</td>
                  <td align="center">13.05</td>
                  <td align="center">100.69</td>
                  <td align="center">21.57</td>
                  <td align="center">74.04</td>
                  <td align="center">32.09</td>
                </tr>
                <tr>
                  <td>Roraima</td>
                  <td align="center">156.06</td>
                  <td align="center">25.42</td>
                  <td align="center">50.58</td>
                  <td align="center">2.36</td>
                  <td align="center">142.99</td>
                  <td align="center">18.60</td>
                  <td align="center">63.28</td>
                  <td align="center">14.51</td>
                  <td align="center">159.57</td>
                  <td align="center">27.07</td>
                  <td align="center">97.83</td>
                  <td align="center">34.84</td>
                </tr>
                <tr>
                  <td>Par&#225;</td>
                  <td align="center">144.72</td>
                  <td align="center">10.18</td>
                  <td align="center">41.74</td>
                  <td align="center">5.28</td>
                  <td align="center">125.39</td>
                  <td align="center">17.96</td>
                  <td align="center">46.25</td>
                  <td align="center">13.23</td>
                  <td align="center">116.01</td>
                  <td align="center">23.48</td>
                  <td align="center">60.50</td>
                  <td align="center">27.99</td>
                </tr>
                <tr>
                  <td>Amap&#225;</td>
                  <td align="center">140.80</td>
                  <td align="center">11.40</td>
                  <td align="center">60.64</td>
                  <td align="center">13.71</td>
                  <td align="center">161.30</td>
                  <td align="center">28.47</td>
                  <td align="center">85.82</td>
                  <td align="center">14.99</td>
                  <td align="center">116.38</td>
                  <td align="center">32.35</td>
                  <td align="center">72.58</td>
                  <td align="center">27.97</td>
                </tr>
                <tr>
                  <td>Tocantins</td>
                  <td align="center">-</td>
                  <td align="center">-</td>
                  <td align="center">-</td>
                  <td align="center">-</td>
                  <td align="center">82.68</td>
                  <td align="center">7.84</td>
                  <td align="center">25.07</td>
                  <td align="center">6.65</td>
                  <td align="center">129.23</td>
                  <td align="center">24.02</td>
                  <td align="center">63.25</td>
                  <td align="center">32.18</td>
                </tr>
                <tr>
                  <td>Maranh&#227;o</td>
                  <td align="center">64.95</td>
                  <td align="center">3.71</td>
                  <td align="center">13.95</td>
                  <td align="center">2.89</td>
                  <td align="center">62.01</td>
                  <td align="center">5.71</td>
                  <td align="center">18.52</td>
                  <td align="center">4.76</td>
                  <td align="center">136.99</td>
                  <td align="center">18.98</td>
                  <td align="center">57.22</td>
                  <td align="center">34.25</td>
                </tr>
                <tr>
                  <td>Piau&#237;</td>
                  <td align="center">67.44</td>
                  <td align="center">4.56</td>
                  <td align="center">14.76</td>
                  <td align="center">2.15</td>
                  <td align="center">91.90</td>
                  <td align="center">8.75</td>
                  <td align="center">23.76</td>
                  <td align="center">7.35</td>
                  <td align="center">149.33</td>
                  <td align="center">19.54</td>
                  <td align="center">68.84</td>
                  <td align="center">31.53</td>
                </tr>
                <tr>
                  <td>Cear&#225;</td>
                  <td align="center">70.91</td>
                  <td align="center">6.29</td>
                  <td align="center">23.88</td>
                  <td align="center">2.97</td>
                  <td align="center">83.99</td>
                  <td align="center">11.12</td>
                  <td align="center">34.99</td>
                  <td align="center">6.63</td>
                  <td align="center">119.58</td>
                  <td align="center">22.31</td>
                  <td align="center">77.32</td>
                  <td align="center">16.29</td>
                </tr>
                <tr>
                  <td>Rio Grande do Norte</td>
                  <td align="center">82.29</td>
                  <td align="center">8.62</td>
                  <td align="center">29.75</td>
                  <td align="center">4.05</td>
                  <td align="center">102.18</td>
                  <td align="center">9.90</td>
                  <td align="center">40.97</td>
                  <td align="center">15.69</td>
                  <td align="center">118.35</td>
                  <td align="center">16.79</td>
                  <td align="center">73.45</td>
                  <td align="center">26.88</td>
                </tr>
                <tr>
                  <td>Para&#237;ba</td>
                  <td align="center">81.41</td>
                  <td align="center">4.33</td>
                  <td align="center">22.58</td>
                  <td align="center">5.17</td>
                  <td align="center">80.50</td>
                  <td align="center">8.25</td>
                  <td align="center">23.41</td>
                  <td align="center">8.39</td>
                  <td align="center">126.14</td>
                  <td align="center">21.99</td>
                  <td align="center">72.36</td>
                  <td align="center">28.95</td>
                </tr>
                <tr>
                  <td>Pernambuco</td>
                  <td align="center">135.83</td>
                  <td align="center">12.94</td>
                  <td align="center">34.49</td>
                  <td align="center">10.22</td>
                  <td align="center">162.37</td>
                  <td align="center">20.83</td>
                  <td align="center">49.15</td>
                  <td align="center">19.47</td>
                  <td align="center">133.16</td>
                  <td align="center">36.72</td>
                  <td align="center">72.86</td>
                  <td align="center">27.94</td>
                </tr>
                <tr>
                  <td>Alagoas</td>
                  <td align="center">123.47</td>
                  <td align="center">10.06</td>
                  <td align="center">33.41</td>
                  <td align="center">10.12</td>
                  <td align="center">125.41</td>
                  <td align="center">15.92</td>
                  <td align="center">31.67</td>
                  <td align="center">15.28</td>
                  <td align="center">153.87</td>
                  <td align="center">21.57</td>
                  <td align="center">61.66</td>
                  <td align="center">39.11</td>
                </tr>
                <tr>
                  <td>Sergipe</td>
                  <td align="center">110.36</td>
                  <td align="center">11.59</td>
                  <td align="center">32.05</td>
                  <td align="center">13.43</td>
                  <td align="center">97.30</td>
                  <td align="center">16.95</td>
                  <td align="center">43.12</td>
                  <td align="center">17.55</td>
                  <td align="center">113.30</td>
                  <td align="center">20.85</td>
                  <td align="center">66.71</td>
                  <td align="center">28.97</td>
                </tr>
                <tr>
                  <td>Bahia</td>
                  <td align="center">111.81</td>
                  <td align="center">13.88</td>
                  <td align="center">31.28</td>
                  <td align="center">5.83</td>
                  <td align="center">115.46</td>
                  <td align="center">18.92</td>
                  <td align="center">36.30</td>
                  <td align="center">13.89</td>
                  <td align="center">99.32</td>
                  <td align="center">21.59</td>
                  <td align="center">61.49</td>
                  <td align="center">22.66</td>
                </tr>
                <tr>
                  <td>Minas Gerais</td>
                  <td align="center">256.67</td>
                  <td align="center">29.72</td>
                  <td align="center">69.83</td>
                  <td align="center">11.63</td>
                  <td align="center">206.35</td>
                  <td align="center">37.25</td>
                  <td align="center">68.44</td>
                  <td align="center">15.30</td>
                  <td align="center">94.92</td>
                  <td align="center">22.85</td>
                  <td align="center">68.27</td>
                  <td align="center">16.60</td>
                </tr>
                <tr>
                  <td>Esp&#237;rito Santo</td>
                  <td align="center">219.94</td>
                  <td align="center">24.11</td>
                  <td align="center">60.68</td>
                  <td align="center">5.22</td>
                  <td align="center">206.60</td>
                  <td align="center">22.49</td>
                  <td align="center">74.42</td>
                  <td align="center">17.20</td>
                  <td align="center">109.86</td>
                  <td align="center">18.55</td>
                  <td align="center">75.88</td>
                  <td align="center">19.58</td>
                </tr>
                <tr>
                  <td>Rio de Janeiro</td>
                  <td align="center">354.95</td>
                  <td align="center">44.29</td>
                  <td align="center">102.68</td>
                  <td align="center">27.00</td>
                  <td align="center">265.42</td>
                  <td align="center">53.50</td>
                  <td align="center">98.24</td>
                  <td align="center">32.09</td>
                  <td align="center">123.65</td>
                  <td align="center">20.58</td>
                  <td align="center">74.46</td>
                  <td align="center">22.18</td>
                </tr>
                <tr>
                  <td>S&#227;o Paulo</td>
                  <td align="center">328.54</td>
                  <td align="center">24.47</td>
                  <td align="center">94.45</td>
                  <td align="center">19.58</td>
                  <td align="center">246.49</td>
                  <td align="center">38.42</td>
                  <td align="center">97.23</td>
                  <td align="center">20.25</td>
                  <td align="center">114.23</td>
                  <td align="center">21.66</td>
                  <td align="center">76.74</td>
                  <td align="center">14.64</td>
                </tr>
                <tr>
                  <td>Paran&#225;</td>
                  <td align="center">299.72</td>
                  <td align="center">23.03</td>
                  <td align="center">88.41</td>
                  <td align="center">9.27</td>
                  <td align="center">266.11</td>
                  <td align="center">43.23</td>
                  <td align="center">92.01</td>
                  <td align="center">15.77</td>
                  <td align="center">105.50</td>
                  <td align="center">24.16</td>
                  <td align="center">79.38</td>
                  <td align="center">19.36</td>
                </tr>
                <tr>
                  <td>Santa Catarina</td>
                  <td align="center">244.17</td>
                  <td align="center">31.96</td>
                  <td align="center">74.37</td>
                  <td align="center">10.94</td>
                  <td align="center">205.84</td>
                  <td align="center">44.60</td>
                  <td align="center">94.10</td>
                  <td align="center">18.21</td>
                  <td align="center">99.62</td>
                  <td align="center">23.63</td>
                  <td align="center">82.05</td>
                  <td align="center">17.27</td>
                </tr>
                <tr>
                  <td>Rio Grande do Sul</td>
                  <td align="center">294.03</td>
                  <td align="center">41.78</td>
                  <td align="center">109.92</td>
                  <td align="center">6.74</td>
                  <td align="center">232.87</td>
                  <td align="center">55.84</td>
                  <td align="center">118.45</td>
                  <td align="center">15.94</td>
                  <td align="center">93.77</td>
                  <td align="center">26.37</td>
                  <td align="center">89.52</td>
                  <td align="center">20.88</td>
                </tr>
                <tr>
                  <td>Mato Grosso do Sul</td>
                  <td align="center">241.86</td>
                  <td align="center">28.07</td>
                  <td align="center">66.09</td>
                  <td align="center">8.19</td>
                  <td align="center">224.07</td>
                  <td align="center">36.40</td>
                  <td align="center">79.30</td>
                  <td align="center">16.38</td>
                  <td align="center">127.05</td>
                  <td align="center">24.28</td>
                  <td align="center">75.53</td>
                  <td align="center">18.88</td>
                </tr>
                <tr>
                  <td>Mato Grosso</td>
                  <td align="center">132.64</td>
                  <td align="center">15.48</td>
                  <td align="center">30.87</td>
                  <td align="center">2.82</td>
                  <td align="center">159.20</td>
                  <td align="center">24.64</td>
                  <td align="center">46.30</td>
                  <td align="center">12.78</td>
                  <td align="center">109.91</td>
                  <td align="center">27.64</td>
                  <td align="center">68.32</td>
                  <td align="center">23.48</td>
                </tr>
                <tr>
                  <td>Goi&#225;s</td>
                  <td align="center">168.28</td>
                  <td align="center">20.26</td>
                  <td align="center">44.23</td>
                  <td align="center">5.18</td>
                  <td align="center">218.97</td>
                  <td align="center">31.28</td>
                  <td align="center">65.08</td>
                  <td align="center">14.59</td>
                  <td align="center">115.68</td>
                  <td align="center">31.61</td>
                  <td align="center">73.81</td>
                  <td align="center">20.39</td>
                </tr>
                <tr>
                  <td>Distrito Federal</td>
                  <td align="center">252.91</td>
                  <td align="center">46.44</td>
                  <td align="center">102.71</td>
                  <td align="center">20.86</td>
                  <td align="center">242.99</td>
                  <td align="center">38.02</td>
                  <td align="center">109.77</td>
                  <td align="center">29.10</td>
                  <td align="center">74.66</td>
                  <td align="center">16.71</td>
                  <td align="center">67.97</td>
                  <td align="center">13.61</td>
                </tr>
                <tr>
                  <td colspan="13">
                    <bold>Chronic noncommunicable disease quartiles according to color and color intensity</bold>
                  </td>
                </tr>
                <tr>
                  <td>Diseases of the circulatory system</td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>0-24%</bold>
                  </td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>25-49%</bold>
                  </td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>50-75%</bold>
                  </td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>&gt;75%</bold>
                  </td>
                </tr>
                <tr>
                  <td>Chronic respiratory diseases</td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>0-24%</bold>
                  </td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>25-49%</bold>
                  </td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>50-75%</bold>
                  </td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>&gt;75%</bold>
                  </td>
                </tr>
                <tr>
                  <td>Neoplasms</td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>0-24%</bold>
                  </td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>25-49%</bold>
                  </td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>50-75%</bold>
                  </td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>&gt;75%</bold>
                  </td>
                </tr>
                <tr>
                  <td>Diabetes mellitus</td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>0-24%</bold>
                  </td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>25-49%</bold>
                  </td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>50-75%</bold>
                  </td>
                  <td align="center" colspan="3" rowspan="1">
                    <bold>&gt;75%</bold>
                  </td>
                </tr>
              </tbody>
            </table>
          </table-wrap>
        </p>
        <p>In the Northeast region, all CNCDs showed an increase in mortality rates, with the exception of DCS in Bahia and Pernambuco, which remained in the same quartile in the 3 years analyzed. Notably, DM was the disease that reached the highest quartiles in all federative units, except for Cear&#225;, which, despite an increase, did not reach the highest quartile. After DM, neoplasms, followed by CRD and DCS, were, in this sequence and region, the diseases that most affected the population. Still in the Northeast region, Pernambuco stands out as the federative unit that obtained the highest quartiles in all diseases (<xref ref-type="table" rid="t1001">Table 1</xref>).</p>
        <p>On the other hand, in the Southeast, South, and Central-West Regions, with high rates in 1980, there was a trend toward a reduction in mortality from all CNCDs, as observed by the reduction in the color intensity of the quartiles, except for neoplasms in the first two regions, which were stable, and in the Central-West for CRD in Goi&#225;s and DM in Mato Grosso. Distrito Federal stands out with a reduction in all CNCDs (<xref ref-type="table" rid="t1001">Table 1</xref>).</p>
        <p><xref ref-type="table" rid="t2001">Table 2</xref> shows the sex ratios (male/female), where numbers &gt; 1.0 represent higher values for the male than the female sex, and numbers &lt; 1.0 represent higher values for the female sex than the male sex.</p>
        <p>
          <table-wrap id="t2001">
            <label>Table 2</label>
            <caption>
              <title>&#8211; Ratio between crude mortality rates in the male and female sex for chronic noncommunicable disease in 5-year periods and by geographic region</title>
            </caption>
            <table frame="hsides" rules="groups">
              <colgroup>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
                <col/>
              </colgroup>
              <thead>
                <tr>
                  <th align="left" style="font-weight:normal"> </th>
                  <th align="left">Region / Period</th>
                  <th>1980-1984</th>
                  <th>1985-1989</th>
                  <th>1990-1994</th>
                  <th>1995-1999</th>
                  <th>2000-2004</th>
                  <th>2005-2009</th>
                  <th>2010-2014</th>
                  <th>2015-2019</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td rowspan="5">Diseases of the circulatory system</td>
                  <td>North</td>
                  <td align="center">1.14</td>
                  <td align="center">1.15</td>
                  <td align="center">1.18</td>
                  <td align="center">1.19</td>
                  <td align="center">1.26</td>
                  <td align="center">1.29</td>
                  <td align="center">1.31</td>
                  <td align="center">1.29</td>
                </tr>
                <tr>
                  <td>Northeast</td>
                  <td align="center">1.12</td>
                  <td align="center">1.16</td>
                  <td align="center">1.17</td>
                  <td align="center">1.11</td>
                  <td align="center">1.12</td>
                  <td align="center">1.11</td>
                  <td align="center">1.13</td>
                  <td align="center">1.13</td>
                </tr>
                <tr>
                  <td>Southeast</td>
                  <td align="center">1.19</td>
                  <td align="center">1.21</td>
                  <td align="center">1.19</td>
                  <td align="center">1.15</td>
                  <td align="center">1.15</td>
                  <td align="center">1.14</td>
                  <td align="center">1.13</td>
                  <td align="center">1.12</td>
                </tr>
                <tr>
                  <td>South</td>
                  <td align="center">1.22</td>
                  <td align="center">1.19</td>
                  <td align="center">1.16</td>
                  <td align="center">1.12</td>
                  <td align="center">1.11</td>
                  <td align="center">1.09</td>
                  <td align="center">1.08</td>
                  <td align="center">1.10</td>
                </tr>
                <tr>
                  <td>Central-West</td>
                  <td align="center">1.27</td>
                  <td align="center">1.30</td>
                  <td align="center">1.31</td>
                  <td align="center">1.26</td>
                  <td align="center">1.31</td>
                  <td align="center">1.31</td>
                  <td align="center">1.29</td>
                  <td align="center">1.28</td>
                </tr>
                <tr>
                  <td rowspan="5">Chronic respiratory diseases</td>
                  <td>North</td>
                  <td align="center">1.24</td>
                  <td align="center">1.25</td>
                  <td align="center">1.26</td>
                  <td align="center">1.22</td>
                  <td align="center">1.28</td>
                  <td align="center">1.31</td>
                  <td align="center">1.28</td>
                  <td align="center">1.20</td>
                </tr>
                <tr>
                  <td>Northeast</td>
                  <td align="center">1.22</td>
                  <td align="center">1.25</td>
                  <td align="center">1.25</td>
                  <td align="center">1.16</td>
                  <td align="center">1.14</td>
                  <td align="center">1.13</td>
                  <td align="center">1.11</td>
                  <td align="center">1.03</td>
                </tr>
                <tr>
                  <td>Southeast</td>
                  <td align="center">1.48</td>
                  <td align="center">1.53</td>
                  <td align="center">1.49</td>
                  <td align="center">1.40</td>
                  <td align="center">1.38</td>
                  <td align="center">1.36</td>
                  <td align="center">1.29</td>
                  <td align="center">1.20</td>
                </tr>
                <tr>
                  <td>South</td>
                  <td align="center">1.77</td>
                  <td align="center">1.76</td>
                  <td align="center">1.76</td>
                  <td align="center">1.55</td>
                  <td align="center">1.52</td>
                  <td align="center">1.45</td>
                  <td align="center">1.32</td>
                  <td align="center">1.19</td>
                </tr>
                <tr>
                  <td>Central-West</td>
                  <td align="center">1.28</td>
                  <td align="center">1.30</td>
                  <td align="center">1.32</td>
                  <td align="center">1.32</td>
                  <td align="center">1.35</td>
                  <td align="center">1.36</td>
                  <td align="center">1.29</td>
                  <td align="center">1.28</td>
                </tr>
                <tr>
                  <td rowspan="5">Neoplasms</td>
                  <td>North</td>
                  <td align="center">1.12</td>
                  <td align="center">1.10</td>
                  <td align="center">1.06</td>
                  <td align="center">1.06</td>
                  <td align="center">1.11</td>
                  <td align="center">1.09</td>
                  <td align="center">1.11</td>
                  <td align="center">1.09</td>
                </tr>
                <tr>
                  <td>Northeast</td>
                  <td align="center">0.99</td>
                  <td align="center">1.01</td>
                  <td align="center">1.03</td>
                  <td align="center">1.02</td>
                  <td align="center">1.05</td>
                  <td align="center">1.09</td>
                  <td align="center">1.10</td>
                  <td align="center">1.08</td>
                </tr>
                <tr>
                  <td>Southeast</td>
                  <td align="center">1.26</td>
                  <td align="center">1.26</td>
                  <td align="center">1.22</td>
                  <td align="center">1.23</td>
                  <td align="center">1.23</td>
                  <td align="center">1.22</td>
                  <td align="center">1.19</td>
                  <td align="center">1.14</td>
                </tr>
                <tr>
                  <td>South</td>
                  <td align="center">1.43</td>
                  <td align="center">1.39</td>
                  <td align="center">1.36</td>
                  <td align="center">1.34</td>
                  <td align="center">1.36</td>
                  <td align="center">1.34</td>
                  <td align="center">1.31</td>
                  <td align="center">1.24</td>
                </tr>
                <tr>
                  <td>Central-West</td>
                  <td align="center">1.13</td>
                  <td align="center">1.12</td>
                  <td align="center">1.17</td>
                  <td align="center">1.19</td>
                  <td align="center">1.20</td>
                  <td align="center">1.23</td>
                  <td align="center">1.22</td>
                  <td align="center">1.17</td>
                </tr>
                <tr>
                  <td rowspan="5">Diabetes mellitus</td>
                  <td>North</td>
                  <td align="center">0.74</td>
                  <td align="center">0.70</td>
                  <td align="center">0.75</td>
                  <td align="center">0.75</td>
                  <td align="center">0.80</td>
                  <td align="center">0.80</td>
                  <td align="center">0.85</td>
                  <td align="center">0.91</td>
                </tr>
                <tr>
                  <td>Northeast</td>
                  <td align="center">0.77</td>
                  <td align="center">0.77</td>
                  <td align="center">0.75</td>
                  <td align="center">0.74</td>
                  <td align="center">0.73</td>
                  <td align="center">0.76</td>
                  <td align="center">0.80</td>
                  <td align="center">0.84</td>
                </tr>
                <tr>
                  <td>Southeast</td>
                  <td align="center">0.68</td>
                  <td align="center">0.68</td>
                  <td align="center">0.70</td>
                  <td align="center">0.73</td>
                  <td align="center">0.78</td>
                  <td align="center">0.82</td>
                  <td align="center">0.83</td>
                  <td align="center">0.86</td>
                </tr>
                <tr>
                  <td>South</td>
                  <td align="center">0.67</td>
                  <td align="center">0.66</td>
                  <td align="center">0.67</td>
                  <td align="center">0.70</td>
                  <td align="center">0.74</td>
                  <td align="center">0.78</td>
                  <td align="center">0.81</td>
                  <td align="center">0.88</td>
                </tr>
                <tr>
                  <td>Central-West</td>
                  <td align="center">0.79</td>
                  <td align="center">0.72</td>
                  <td align="center">0.72</td>
                  <td align="center">0.76</td>
                  <td align="center">0.79</td>
                  <td align="center">0.84</td>
                  <td align="center">0.88</td>
                  <td align="center">0.95</td>
                </tr>
              </tbody>
            </table>
          </table-wrap>
        </p>
        <p>The rates in the male sex were higher throughout the period for DCS, CRDs, and neoplasms. One exception was for neoplasms in the period from 1980 to 1984 in the Northeast Region, which had a ratio below 1. For mortality rates related to DM, throughout the observed period, they were higher in the female sex across all geographic regions.</p>
        <p><xref ref-type="table" rid="t2001">Table 2</xref> - Ratio between crude mortality rates in the male and female sex for chronic noncommunicable disease in 5-year periods and by geographic region.</p>
        <p>As seen in <xref ref-type="fig" rid="f03001">Figure 2</xref>, the federative units that presented the greatest reduction in mortality rates in all cases were those that presented the smallest MHDI variation, including Rio de Janeiro, S&#227;o Paulo, Distrito Federal, Rio Grande do Sul, Santa Catarina, Esp&#237;rito Santo, and Paran&#225;. In contrast, Maranh&#227;o, Piau&#237;, and Para&#237;ba, which presented the greatest MHDI variations, had the smallest decreases in mortality rates (<xref ref-type="fig" rid="f03001">Figure 2</xref>). Additionally, <xref ref-type="fig" rid="f04001">Figure 3</xref> shows a reduction in mortality rates in all federative units with MHDI equal to or above 0.7, including the Southeast, South, and Central-West Regions. The federative units with the lowest variation in mortality were those with the highest MHDI (<xref ref-type="fig" rid="f04001">Figure 3</xref>). The correlation coefficients found between the 2010 MHDI and the percentage variations in mortality rates were: &#8722;0.62 for DCS, &#8722;0.59 for CRDs, &#8722;0.45 for DM, and &#8722;0.64 for neoplasms, all of which had a significance level below 0.05.</p>
        <p>
          <fig id="f03001">
            <label>Figure 2</label>
            <caption>
              <title>&#8211; Scatter plot. Correlation between the percentage change in the 1991 and 2010 Municipal Human Development Index (MHDI) with the percentage change in mortality rate for chronic noncommunicable diseases: diseases of the circulatory system (DCS); chronic respiratory diseases (CRD); neoplasms; diabetes mellitus (DM), 1990 and 2019, in Brazil in the federative units, in both sexes.</title>
            </caption>
            <graphic xlink:href="1678-4170-abc-120-04-e20211009-11009-gf03-en.tif"/></fig>
        </p>
        <p>
          <fig id="f04001">
            <label>Figure 3</label>
            <caption>
              <title>&#8211; Scatter plot. Correlation between the absolute Municipal Human Development Index (MHDI) in the year 2010 with the percentage change in mortality rate for chronic noncommunicable diseases: diseases of the circulatory system (DCS); chronic respiratory diseases (CRD); neoplasms; diabetes mellitus (DM), 1990 and 2019, in Brazil in the federative units, in both sexes.</title>
            </caption>
            <graphic xlink:href="1678-4170-abc-120-04-e20211009-11009-gf04-en.tif"/></fig>
        </p>
      </sec>
      <sec sec-type="discussion">
        <title>Discussion</title>
        <p>The present study showed a decline in standardized mortality rates for CNCDs in Brazil, across all ages and in both sexes, over a 40-year period of observation. These results are similar to those found by Cardoso et al.,<sup><xref ref-type="bibr" rid="B18">18</xref></sup> who observed a reduction in the rates of cardiovascular diseases in all Brazilian regions; however, these showed the highest average rates in both periods, followed by the rates of neoplasms, DM, and CRD.</p>
        <p>The decline in standardized mortality rates for CNCDs has also been observed by Malta et al.,<sup><xref ref-type="bibr" rid="B19">19</xref>,<xref ref-type="bibr" rid="B20">20</xref></sup> who described mortality trends between 1990 and 2017 in Brazil. In addition to the 35% reduction in the standardized mortality rates for CNCDs, the authors showed a reduction in mortality from cardiovascular diseases by 47.9%, while the mortality from CRD, DM, and neoplasms decreased by 41.3%, 18%, and 11.9%, respectively, with 15 uninterrupted years of decline, followed by a trend toward an increase in deaths for all CNCDs, in each group, after 2015. In our study, on the other hand, we observed increases in mortality rates due to neoplasms and DM (<xref ref-type="fig" rid="f02001">Figure 1</xref>).</p>
        <p>The mortality rates for CNCDs have been evaluated by Silva and Ramalho,<sup><xref ref-type="bibr" rid="B21">21</xref></sup> who analyzed the profile of morbidity and mortality in Brazil and compared the changes that occurred in the proportional mortality of the major groups of causes, through the representation of population growth since 1980 with projections until 2033. The authors observed that mortality from CNCDs already represented about 70% of the total mortality in the country and that DCS comprised the mortality group with the highest proportional weight throughout the period, with a projected reduction in 2033 (113.1 per 100,000 inhabitants) when compared with 1980 (273.9 per 100,000 inhabitants). Similarly, in our study, we noted that despite the reduction in CNCDs over the period, their rates surpassed those of other causes of death after 2019 (<ext-link ext-link-type="uri" xlink:href="http://abccardiol.org/supplementary-material/2023/12004/2021-1009_AO_Material-Suplementar.pdf">Supplementary Material - Figure 1A</ext-link>). On the other hand, despite the high mortality rate from CNCDs, the percentage of deaths from DCS declined from 67% to 49% (<ext-link ext-link-type="uri" xlink:href="http://abccardiol.org/supplementary-material/2023/12004/2021-1009_AO_Material-Suplementar.pdf">Supplementary Material - Figure 1B</ext-link>).</p>
        <p>When the standardized mortality rates were evaluated in the present study, they showed results similar to those from a cross-sectional study that used estimates from the 2015 Global Burden of Disease study for Brazil.<sup><xref ref-type="bibr" rid="B20">20</xref></sup> In both studies, higher rates were observed over the period, but with declining trends for cardiovascular diseases and CRD, while neoplasms and DM showed stable rates, with a tendency to increase, between 1990 and 2015 in Brazil.<sup><xref ref-type="bibr" rid="B20">20</xref></sup></p>
        <p>In general, comparisons among CNCDs are difficult, precisely because the magnitude of the deaths differs among them. Thus, in the present study, we opted to construct a dynamic table with the quartiles of each CNCD, identifying the intensities of variations between the intervals over the years and allowing the proportional comparison between them (<xref ref-type="table" rid="t1001">Table 1</xref>). In the Northeast Region, all CNCDs showed an increase in mortality rates, with DM reaching the highest quartiles. In contrast, the lowest quartiles were observed in the Southeast, South, and Central-West Regions, except for Mato Grosso. These results are similar to those of another previously cited study.<sup><xref ref-type="bibr" rid="B18">18</xref></sup></p>
        <p>The DCS showed the greatest decreases in mortality, with greater changes in quartiles observed in the wealthiest regions of the country (Southeast, South, and Central-West) and, to a lesser extent, the North Region, while the Northeast Region showed an increase in mortality rates due to these diseases. Mansur et al.<sup><xref ref-type="bibr" rid="B22">22</xref></sup> analyzed data on trends in mortality from cardiovascular diseases in men and women older than 30 years in the 5 regions of Brazil and observed that mortality from these diseases increased in the Northeast Region and decreased in the other regions, with the most significant being in the South and Southeast Regions. Regarding CRDs, there was an upward trend for the North and Northeast Regions and a downward trend for the South, Southeast, and Central-West Regions, while for neoplasms, the Southeast and South Regions had rates in the highest quartiles. The data described above were confirmed by the study by Cardoso et al.,<sup><xref ref-type="bibr" rid="B18">18</xref></sup> which reported a reduction in mean mortality rates from CRD in the Central-West, North, Southeast, and South Regions. However, different than the present study, theirs found a reduction in the average rates of neoplasms in the South Region. These observed results may, at least in part, be related to variations in social indicators, as demonstrated in a previous study.<sup><xref ref-type="bibr" rid="B13">13</xref></sup></p>
        <p>Regarding the mortality ratios between men and women for DCS, CRDs, and neoplasms, mortality prevailed in the male sex, in contrast to what occurred for DM, in which the rates were higher in the female sex (<xref ref-type="table" rid="t2001">Table 2</xref>), which is in agreement with the results of other studies.<sup><xref ref-type="bibr" rid="B23">23</xref>,<xref ref-type="bibr" rid="B24">24</xref></sup></p>
        <p>When we evaluated the associations with the HDI, we observed that the mortality from CNCDs in Brazil showed an uneven epidemiological behavior between regions, as observed in <xref ref-type="fig" rid="f03001">Figures 2</xref> and <xref ref-type="fig" rid="f04001">3</xref>. In <xref ref-type="fig" rid="f03001">Figure 2</xref>, an inverse relationship is observed between the HDI variation and the variation in mortality rates for all CNCDs. However, the same pattern of dispersion occurs when the positions of the federative units in the graphs are observed, with the federative units in the North and Northeast Regions presenting the greatest HDI variations but with the lowest (or inverse) variations in the mortality rates. This finding can be explained by the fact that the initial position of the HDI of these regions which, despite an important improvement, is still insufficient to cause positive impacts on mortality rates when observed alone.</p>
        <p>On the contrary, when variations in mortality rates are compared against absolute HDI values (<xref ref-type="fig" rid="f04001">Figure 3</xref>), a direct relationship is observed between the variables. In this figure, for all CNCDs, it is generally observed that the federative units that presented an HDI above 0.7 in 2010 had the best variations in mortality rates, demonstrating that, probably, more important than the HDI variation is the value that the HDI reaches, as observed in previous studies.<sup><xref ref-type="bibr" rid="B12">12</xref>,<xref ref-type="bibr" rid="B26">26</xref>-<xref ref-type="bibr" rid="B31">31</xref></sup></p>
        <p>The present study does not address multiple causes of death, and it is not possible to assess the presence of more than one CNCD in the same death certificates. In addition, when working with the underlying cause selected and made available in the DATASUS, the database becomes more sensitive to the incompleteness of death certificates and errors in filling them out. Finally, the unavailability of MHDI data in recent years prevents closer temporal comparisons with mortality rates.</p>
      </sec>
      <sec sec-type="conclusions">
        <title>Conclusions</title>
        <p>The mortality due to CNCDs decreased over the 40 years of observation, especially those of DCS. As for CRDs, they showed slight oscillations, while those for neoplasms and DM increased over the period. At the end of the study period, they tended to stabilize. The states in the Northeast and North Regions tended to have higher mortality rates when compared with those in the Southeast, South, and Central-West Regions. The study points to a correlation between HDI and the reduction in mortality rates from CNCDs, especially DCS, based on a high level of human development. These findings indicate the importance of measures that reduce CNCD mortality and the fact that these measures should, necessarily, include improvement to the socioeconomic conditions of the population, considering the regional context, and aim to reduce the growing inequalities in access to prevention and treatment resources.</p>
      </sec>
    </body>
    <back>
      <fn-group>
        <fn fn-type="other">
          <p>Study association</p>
          <p>This article is part of the thesis of master submitted by Sandra Chagas da Costa Feliciano, from Universidade Federal do Rio de Janeiro.</p>
        </fn>
        <fn fn-type="other">
          <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>
        <fn fn-type="supplementary-material">
          <p>* Supplemental Materials</p>
          <p>For additional information, please <ext-link ext-link-type="uri" xlink:href="http://abccardiol.org/supplementary-material/2023/12004/2021-1009_AO_Material-Suplementar.pdf">click here</ext-link>.</p>
        </fn>
      </fn-group>
    </back>
  </sub-article>
</article>
