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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 pub-id-type="publisher-id" specific-use="scielo-v3">kRLBQhC7fDSzqYy3HxR9LNn</article-id>
      <article-id pub-id-type="publisher-id" specific-use="scielo-v2">S0066-782X2018000600500</article-id>
      <article-id pub-id-type="doi">10.5935/abc.20180098</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Original Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Cardiovascular Disease Epidemiology in Portuguese-Speaking Countries: data from the Global Burden of Disease, 1990 to 2016</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Nascimento</surname>
            <given-names>Bruno Ramos</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Brant</surname>
            <given-names>Luisa Campos Caldeira</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Oliveira</surname>
            <given-names>Gl&#225;ucia Maria Moraes de</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="corresp" rid="c1"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Malachias</surname>
            <given-names>Marcus Vin&#237;cius Bol&#237;var</given-names>
          </name>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Reis</surname>
            <given-names>Gabriel Moreira Alves</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Teixeira</surname>
            <given-names>Renato Azeredo</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Malta</surname>
            <given-names>Deborah Carvalho</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Fran&#231;a</surname>
            <given-names>Elisabeth</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Souza</surname>
            <given-names>Maria de F&#225;tima Marinho</given-names>
          </name>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Roth</surname>
            <given-names>Gregory A.</given-names>
          </name>
          <xref ref-type="aff" rid="aff5">5</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Ribeiro</surname>
            <given-names>Antonio Luiz P.</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label>1</label>
        <institution content-type="orgname">Universidade Federal de Minas Gerais</institution>
        <addr-line>
          <city>Belo Horizonte</city>
          <state>MG</state>
        </addr-line>
        <country country="BR">Brazil</country>
        <institution content-type="original">Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG - Brazil</institution>
        <institution content-type="normalized">Universidade Federal de Minas Gerais</institution>
      </aff>
      <aff id="aff2">
        <label>2</label>
        <institution content-type="orgname">Universidade Federal do Rio de Janeiro</institution>
        <addr-line>
          <city>Rio de Janeiro</city>
          <state>RJ</state>
        </addr-line>
        <country country="BR">Brazil</country>
        <institution content-type="original">Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ - Brazil</institution>
        <institution content-type="normalized">Universidade Federal do Rio de Janeiro</institution>
      </aff>
      <aff id="aff3">
        <label>3</label>
        <institution content-type="orgname">Faculdade Ci&#234;ncias M&#233;dicas de Minas Gerais</institution>
        <addr-line>
          <city>Belo Horizonte</city>
          <state>MG</state>
        </addr-line>
        <country country="BR">Brazil</country>
        <institution content-type="original">Faculdade Ci&#234;ncias M&#233;dicas de Minas Gerais, Belo Horizonte, MG - Brazil</institution>
      </aff>
      <aff id="aff4">
        <label>4</label>
        <institution content-type="orgname">Minist&#233;rio da Sa&#250;de</institution>
        <addr-line>
          <city>Bras&#237;lia</city>
          <state>DF</state>
        </addr-line>
        <country country="BR">Brazil</country>
        <institution content-type="original">Minist&#233;rio da Sa&#250;de, Bras&#237;lia, DF - Brazil</institution>
        <institution content-type="normalized">Minist&#233;rio da Sa&#250;de</institution>
      </aff>
      <aff id="aff5">
        <label>5</label>
        <institution content-type="orgname">University of Washington</institution>
        <addr-line>
          <city>Seattle</city>
          <state>WA</state>
        </addr-line>
        <country country="US">USA</country>
        <institution content-type="original">University of Washington, Seattle, WA - USA</institution>
        <institution content-type="normalized">University of Washington</institution>
      </aff>
      <author-notes>
        <corresp id="c1"><bold>Mailing Address: Gl&#225;ucia Maria Moraes de Oliveira</bold>. Universidade Federal do Rio de Janeiro - R. Prof. Rodolpho P. Rocco, 255 - Pr&#233;dio do HU 8&#186; andar - sala 6, UFRJ. Postal Code 21941-913, Cidade Universit&#225;ria, RJ - Brazil. E-mail: <email>glauciam@cardiol.br</email>, <email>glauciamoraesoliveira@gmail.com</email>
				</corresp>
        <fn fn-type="con">
          <p>
            <bold>Author contributions</bold>
          </p>
          <p>Conception and design of the research: Oliveira GMM, Malachias, MVB, Ribeiro AL; Acquisition of data: Reis GMA, Ribeiro AL, Brant LCC, Souza MFM, Malta DC, Teixeira RA; Roth GA; Analysis and interpretation of data: Brant LCC, Reis GMA, Ribeiro AL, Nascimento BR; Statistical analysis: Teixeira RA, Brant LCC, Ribeiro, AL, Roth GA; Obtaining financing: Souza MFM, Fran&#231;a E; Writing of the manuscript: Nascimento, BR, Brant, LCC, Oliveira GMM; Critical revision of the manuscript for intellectual content: Todos os autores.</p>
        </fn>
        <fn fn-type="conflict">
          <p>
            <bold>Potential Conflict of Interest</bold>
          </p>
          <p>No potential conflict of interest relevant to this article was reported.</p>
        </fn>
      </author-notes>
      <pub-date pub-type="epub-ppub">
        <month>06</month>
        <year>2018</year>
      </pub-date>
      <volume>110</volume>
      <issue>6</issue>
      <fpage>500</fpage>
      <lpage>511</lpage>
      <history>
        <date date-type="received">
          <day>08</day>
          <month>12</month>
          <year>2017</year>
        </date>
        <date date-type="rev-recd">
          <day>21</day>
          <month>03</month>
          <year>2018</year>
        </date>
        <date date-type="accepted">
          <day>21</day>
          <month>03</month>
          <year>2018</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>Abstract</title>
        <sec>
          <title>Background:</title>
          <p>Portuguese-speaking countries (PSC) share the influence of the Portuguese culture but have socioeconomic development patterns that differ from that of Portugal.</p>
        </sec>
        <sec>
          <title>Objective:</title>
          <p>To describe trends in cardiovascular disease (CVD) morbidity and mortality in the PSC between 1990 and 2016, stratified by sex, and their association with the respective sociodemographic indexes (SDI).</p>
        </sec>
        <sec>
          <title>Methods:</title>
          <p>This study used the Global Burden of Disease (GBD) 2016 data and methodology. Data collection followed international standards for death certification, through information systems on vital statistics and mortality surveillance, surveys, and hospital registries. Techniques were used to standardize causes of death by the direct method, as were corrections for underreporting of deaths and garbage codes. To determine the number of deaths due to each cause, the CODEm (Cause of Death Ensemble Model) algorithm was applied. Disability-adjusted life years (DALYs) and SDI (income per capita, educational attainment and total fertility rate) were estimated for each country. A p-value &lt;0.05 was considered significant.</p>
        </sec>
        <sec>
          <title>Results:</title>
          <p>There are large differences, mainly related to socioeconomic conditions, in the relative impact of CVD burden in PSC. Among CVD, ischemic heart disease was the leading cause of death in all PSC in 2016, except for Mozambique and Sao Tome and Principe, where cerebrovascular diseases have supplanted it. The most relevant attributable risk factors for CVD among all PSC are hypertension and dietary factors.</p>
        </sec>
        <sec>
          <title>Conclusion: </title>
          <p>Collaboration among PSC may allow successful experiences in combating CVD to be shared between those countries.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="en">
        <title>Keywords</title>
        <kwd>Cardiovascular Diseases</kwd>
        <kwd>Epidemiology</kwd>
        <kwd>Mortality</kwd>
        <kwd>Global Burden of Disease / trends</kwd>
      </kwd-group>
      <funding-group>
        <award-group>
          <funding-source>Fundo Nacional de Sa&#250;de</funding-source>
          <award-id>17217.9850001 /17-018</award-id>
        </award-group>
        <award-group>
          <funding-source>Bolsa de produtividade em pesquisa</funding-source>
          <award-id>310679/2016-8</award-id>
        </award-group>
        <award-group>
          <funding-source>IATS</funding-source>
          <award-id>465518/2014-1</award-id>
        </award-group>
        <award-group>
          <funding-source>FAPEMIG</funding-source>
          <award-id>PPM-00428-17</award-id>
        </award-group>
        <funding-statement>The Ministry of Health of Brazil was responsible for funding the GBD Brazil Study (Fundo Nacional de Sa&#250;de, grant number (17217.9850001 /17-018). Ribeiro was supported in part by CNPq (Bolsa de produtividade em pesquisa, 310679/2016-8 and IATS, 465518/2014-1) and by FAPEMIG (Programa Pesquisador Mineiro, PPM-00428-17).</funding-statement>
      </funding-group>
    </article-meta>
  </front>
  <body>
    <sec sec-type="intro">
      <title>Introduction</title>
      <p>Cardiovascular diseases (CVD) are a major cause of death worldwide. Although CVD are not the first cause of death in many low- and middle-income countries, they account for 80% of the deaths and 88% of the premature deaths in those countries.<xref ref-type="bibr" rid="B1">1</xref> The control of infectious, maternal and child diseases, the increase in life expectancy and the growing urbanization have contributed to the trend towards increasing the importance of CVD in low- and middle-income countries. The implementation of health policies, such as promotion of a healthy lifestyle, access to primary and secondary prevention of CVD and treatment of acute cardiovascular events, is, thus, essential for CVD control in all countries.<xref ref-type="bibr" rid="B1">1</xref>
			</p>
      <p>Portuguese-speaking countries (PSC) were culturally influenced by Portugal at different levels.<xref ref-type="bibr" rid="B2">2</xref> The study of the trends in morbidity and mortality from CVD in those countries can provide us useful data regarding the similarities and differences between them. Those data can provide an exchange of information between countries regarding well-succeeded actions for fighting CVD, in addition to allowing reflections on the influence of culture on the burden of CVD.</p>
      <p>The "Global Burden of Disease Study" (GBD Study) is an important epidemiological observational study that uses metrics of morbidity and mortality related to major diseases, injuries and risk factors at global, at national and regional levels. One of the GBD Study objectives is to understand, by assessing the trends, the changes in the profile of the diseases that affect the 21st century populations.<xref ref-type="bibr" rid="B3">3</xref>
			</p>
      <p>This study was aimed at describing the trends of CVD morbidity and mortality in the PSC between 1990 and 2016, based on the estimates of the GBD 2016 Study, and to assess the association between those trends and the sociodemographic index (SDI) of those countries.</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec>
        <title>Portuguese-speaking countries</title>
        <p>The PSC are the official members of the Community of Portuguese-Speaking Countries (CPLP), an international organization created in July 17, 1996, aimed at "deepening the mutual friendship and cooperation between its members".<xref ref-type="bibr" rid="B2">2</xref> The initial list of countries included Angola, Brazil, Cape Verde, Guinea-Bissau, Mozambique, Portugal and Sao Tome and Principe. In 2002, after its independence, Timor-Leste was accepted as a member. In 2014, Equatorial Guinea was accepted as a member, after Portuguese was adopted as the official language of the country. <xref ref-type="table" rid="t1">Table 1</xref> and <xref ref-type="fig" rid="f1">Figure 1</xref> show the location and the demographic, social and economic characteristics of the PSC.</p>
        <table-wrap id="t1">
          <label>Table 1</label>
          <caption>
            <title>Demographic, social and economic characteristics of the Portuguese-speaking countries, 2013</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup>
              <col width="10%"/>
              <col width="10%"/>
              <col width="10%"/>
              <col width="10%"/>
              <col width="10%"/>
              <col width="10%"/>
              <col width="10%"/>
              <col width="10%"/>
              <col width="10%"/>
              <col width="10%"/>
            </colgroup>
            <thead>
              <tr>
                <th align="left">
								</th>
                <th align="center">Angola</th>
                <th align="center">Brazil</th>
                <th align="center">Cape Verde</th>
                <th align="center">Equatorial Guinea</th>
                <th align="center">Guinea-Bissau</th>
                <th align="center">Mozambique</th>
                <th align="center">Portugal</th>
                <th align="center">Sao Tome and Principe</th>
                <th align="center">Timor-Leste</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Population (millions)</td>
                <td align="center">19</td>
                <td align="center">201</td>
                <td align="center">1</td>
                <td align="center">1</td>
                <td align="center">2</td>
                <td align="center">24</td>
                <td align="center">10</td>
                <td align="center">0.2</td>
                <td align="center">1</td>
              </tr>
              <tr>
                <td align="left">Population density (inhab/km&#178;)</td>
                <td align="center">15</td>
                <td align="center">24</td>
                <td align="center">127</td>
                <td align="center">39</td>
                <td align="center">44</td>
                <td align="center">31</td>
                <td align="center">113</td>
                <td align="center">190</td>
                <td align="center">79</td>
              </tr>
              <tr>
                <td align="left">Area (1,000 km&#178;)</td>
                <td align="center">1247</td>
                <td align="center">8516</td>
                <td align="center">4</td>
                <td align="center">28</td>
                <td align="center">36</td>
                <td align="center">786</td>
                <td align="center">92</td>
                <td align="center">1.0</td>
                <td align="center">15</td>
              </tr>
              <tr>
                <td align="left">GDP (USD, billions)</td>
                <td align="center">125</td>
                <td align="center">2473</td>
                <td align="center">2</td>
                <td align="center">22</td>
                <td align="center">1</td>
                <td align="center">16</td>
                <td align="center">226</td>
                <td align="center">0.3</td>
                <td align="center">1</td>
              </tr>
              <tr>
                <td align="left">GDP per capita (USD)</td>
                <td align="center">4805</td>
                <td align="center">12217</td>
                <td align="center">3589</td>
                <td align="center">20247</td>
                <td align="center">611</td>
                <td align="center">606</td>
                <td align="center">21619</td>
                <td align="center">1620</td>
                <td align="center">1108</td>
              </tr>
              <tr>
                <td align="left">Major religion</td>
                <td align="center">Catholicism</td>
                <td align="center">Catholicism</td>
                <td align="center">Catholicism</td>
                <td align="center">Catholicism</td>
                <td align="center">Islam</td>
                <td align="center">Catholicism</td>
                <td align="center">Catholicism</td>
                <td align="center">Catholicism</td>
                <td align="center">Catholicism</td>
              </tr>
              <tr>
                <td align="left">Public expenditure with health (%GDP)</td>
                <td align="center">2.6</td>
                <td align="center">4.0</td>
                <td align="center">2.5</td>
                <td align="center">2.6</td>
                <td align="center">1.1</td>
                <td align="center">2.1</td>
                <td align="center">9.1</td>
                <td align="center">2.0</td>
                <td align="center">10.4</td>
              </tr>
              <tr>
                <td align="left">Public expenditure with education (%GDP)</td>
                <td align="center">4.9</td>
                <td align="center">6.2</td>
                <td align="center">5.5</td>
                <td align="center">2.2</td>
                <td align="center">2.2</td>
                <td align="center">5.7</td>
                <td align="center">4.2</td>
                <td align="center">5.6</td>
                <td align="center">16.2</td>
              </tr>
              <tr>
                <td align="left">Illiteracy rate (% population)</td>
                <td align="center">28.4</td>
                <td align="center">8.5</td>
                <td align="center">12.8</td>
                <td align="center">6.0</td>
                <td align="center">40.1</td>
                <td align="center">41.2</td>
                <td align="center">5.2</td>
                <td align="center">9.6</td>
                <td align="center">35.9</td>
              </tr>
              <tr>
                <td align="left">Sociodemographic index<xref ref-type="table-fn" rid="TFN01">*</xref>
								</td>
                <td align="center">0.42</td>
                <td align="center">0.66</td>
                <td align="center">0.55</td>
                <td align="center">0.61</td>
                <td align="center">0.29</td>
                <td align="center">0.28</td>
                <td align="center">0.75</td>
                <td align="center">0.45</td>
                <td align="center">0.45</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN01">
              <label>*</label>
              <p>Data from 2015. GDP: gross domestic product. USD: United States dollars.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>
          <fig id="f1">
            <label>Figure 1</label>
            <caption>
              <title>Global map showing the location of the Portuguese-speaking countries, 2017.</title>
            </caption>
            <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf01.jpg"/></fig>
        </p>
      </sec>
      <sec>
        <title>The GBD Study</title>
        <p>The GBD Study is a multinational collaborative research project with the goal of producing consistent estimates of health loss due to over 333 diseases and injuries. A wide range of data sources (data of national surveillance, verbal autopsy and vital registration, published and unpublished registries of diseases, and published scientific literature) and methods are applyed to produce specific results with uncertainty intervals for age, sex and country for the years 1990-2016, and such results are annually updated for the entire temporal series. The present study is based on data from the GBD 2016 Study and its previously detailed methodology.<xref ref-type="bibr" rid="B4">4</xref><sup>-</sup><xref ref-type="bibr" rid="B6">6</xref>
				</p>
      </sec>
      <sec>
        <title>Definitions of CVD</title>
        <p>The nine most common global causes of death and morbidity related to CVD and an additional category for 'other CVD' were considered, in addition to the estimates of global morbidity and mortality grouped by CVD.<xref ref-type="bibr" rid="B7">7</xref> The underlying cause of death was defined as CVD according to the International Classification of Diseases (ICD) codes, from the death certificate (DC), the basic document that informs the causes of death in countries with systems of vital statistics, such as Brazil. The following causes were analyzed, with their corresponding ICD-10 codes according to the GBD Study's classification list of causes: 1- rheumatic fever with cardiac involvement (codes I01-I01.9, I02.0, I05-I09.9); 2-ischemic heart disease (codes I20-I25.9); 3- cerebrovascular disease (CbVD) (G45-G46.8, I60-I69.9); 4- hypertensive heart disease (I11); 5- cardiomyopathy and myocarditis (A39.52, B33.2-B33.24, D86.85, I40-I43.9, I51.4-I51.5); 6- atrial fibrillation and flutter (I48); 7- aortic aneurysm (I71); 8- peripheral artery disease (I70.2-I70.7, I73-I73.9); 9-endocarditis (A39.51, I33-I33.9, I38-I39.9). Garbage codes, such as heart failure (I50) and pulmonary embolism (I26), which do not define the pathology that caused the death, were redistributed to those specific causes based on the GBD methodology, according to algorithms defined in that study.</p>
        <p>Regarding mortality, those causes were grouped based on the specific sequelae of disease (for example, ischemic heart disease due to acute coronary syndrome, chronic stable angina, chronic ischemic heart disease and ischemic cardiomyopathy). Adjustments were performed for data that did not comply with the specific definition of case (for example, electronic confirmation for the clinical diagnosis).<xref ref-type="bibr" rid="B4">4</xref><sup>,</sup><xref ref-type="bibr" rid="B8">8</xref><sup>,</sup><xref ref-type="bibr" rid="B9">9</xref>
				</p>
      </sec>
      <sec>
        <title>Statistical analysis</title>
        <p>The statistical models of the GBD 2016 Study previously reported were used.<xref ref-type="bibr" rid="B4">4</xref><sup>-</sup><xref ref-type="bibr" rid="B6">6</xref> The source of data for the models are available on-line at Global Health Data Exchange (<ext-link ext-link-type="uri" xlink:href="http://ghdx.healthdata.org/">http://ghdx.healthdata.org/</ext-link>).</p>
      </sec>
      <sec>
        <title>Metrics of mortality and prevalence</title>
        <p>The GBD 2016 Study used data available on causes of death in 195 countries. The information was collected according to international standards of death certification, using of information systems on vital statistics, mortality surveillance systems, survey, hospital registries and police registries.<xref ref-type="bibr" rid="B4">4</xref> The data sources have regional particularities, such as in Brazil, where data were mainly obtained from the Mortality Information System (SIM) of the Brazilian Health Ministry, by using an automated coding system.<xref ref-type="bibr" rid="B10">10</xref> In Brazil, all deaths require a medical DC provided by the attending physician. For the deaths occurring outside a healthcare facility, the causes are verified by the Death Verification Service, or by a civil agent when a physician is not available, and, in such cases, the causes of death are not registered.<xref ref-type="bibr" rid="B11">11</xref> Deaths due to external causes are identified by a medical examiner at the Forensic Pathologist Service.</p>
        <p>In addition, techniques to correct quality problems regarding the information about the causes of death were used.<xref ref-type="bibr" rid="B9">9</xref> Corrections were made for underreporting of deaths and for causes considered not useful for the public health analysis, known as Garbage Codes. That term is used to describe causes that cannot or should not be considered as underlying causes of death, or that are unspecified within larger groups of causes. Algorithms of redistribution of Garbage Codes were developed by the GBD Study to increase the validity of the estimates. For this redistribution into specific causes of death, evidence from several sources, such as medical literature, expert opinion and statistical techniques, was considered.<xref ref-type="bibr" rid="B4">4</xref><sup>,</sup><xref ref-type="bibr" rid="B8">8</xref><sup>,</sup><xref ref-type="bibr" rid="B12">12</xref>
				</p>
        <p>After treatment of data quality, the GBD 2016 Study used a variety of statistical models to determine the number of deaths per each cause, mainly by use of the Cause of Death Ensemble Model (CODEm) algorithm. To ensure that the number of deaths per cause does not exceed the total estimated number of deaths, a correction technique (CoCorrect) was used. Adjustment by this technique ensures that the sum of the estimated number of deaths per each cause does not exceed 100% of the estimated deaths in a certain year.<xref ref-type="bibr" rid="B13">13</xref>
				</p>
        <p>The disease prevalence was estimated at a more detailed level of specific sequelae of disease, using as entry data the published systematic reviews of the scientific literature, as well as unpublished data of administrative registries and databases of the health system. Regression equations were used for data adjustment to define the standard case. The data presented were analyzed for the period from 1990 to 2016, and all analyses were stratified by sex and presented as absolute and age-standardized estimates, for the different PSC.</p>
      </sec>
      <sec>
        <title>Metrics of burden of disease</title>
        <p>The disability-adjusted life years (DALYs) combine information regarding premature death (years of life lost: YLLs) and disability caused by the condition (years lived with disability: YLDs) to provide a brief measure of the healthy years lost due to the condition. The YLLs were calculated by multiplying the deaths observed at each specific age in one year of interest by the reference age-specific life expectancy estimated by use of life table methods. The YLDs were calculated by multiplying disease prevalence (in number of cases/year) by a health-state-specific disability weight representing a degree of lost functional capacity. The process of estimating the burden of the disability has been previously described in details.<xref ref-type="bibr" rid="B6">6</xref> Briefly, the burdens of disability were determined via home interviews in several countries, in which the participants were asked to choose between lay descriptions of different health states.<xref ref-type="bibr" rid="B14">14</xref><sup>,</sup><xref ref-type="bibr" rid="B15">15</xref> Adjustment for comorbidity was performed, simulating 40,000 individuals in each age-sex-country-year stratum exposed to the independent likelihood of developing each condition, based on the disease prevalence, with 95% uncertainty intervals (95% UI) reported for each estimate. Age-standardization was obtained via the direct method, applying a global age structure.</p>
      </sec>
      <sec>
        <title>Sociodemographic index</title>
        <p>The SDI is used as an estimate of the socioeconomic level of each country to assess its association with the CVD burden, as a function of global epidemiological transition.<xref ref-type="bibr" rid="B4">4</xref><sup>,</sup><xref ref-type="bibr" rid="B8">8</xref> Similarly to the method used to calculate the Human Development Index, the SDI was calculated for each country or territory from 1990 to 2016. The SDI is the weighted geometric mean of income per capita, educational attainment and total fertility rate, and allows the comparison of the performance of each country to those of countries with a similar socioeconomic level.</p>
        <p>The SPSS software, version 22.0 for Mac OSX (<italic>SPSS Inc., Chicago, Illinois</italic>), was used to perform the correlation (Spearman correlation) between the country's SDI and the variation of the age-standardized mortality rates from CVD between 1990 and 2016. A p-value &lt; 0.05 was considered statistically significant.</p>
      </sec>
      <sec>
        <title>Ethical considerations</title>
        <p>This study was conducted in a public secondary database, without nominal identification, according to Decree 7.724, of May 16, 2012, and the Resolution 510, of April 7, 2016. The Brazilian GBD 2015 Study was approved by the Committee in Ethics and Research of the Minas Gerais Federal University (Project CAAE 62803316.7.0000.5149).</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Results</title>
      <sec>
        <title>Causes of mortality from CVD</title>
        <p>The importance of CVD as the cause of death has increased in the PSC. In 1990, CVD were the main cause of death only in Brazil and Portugal, while, in the other countries, infectious diseases, such as diarrhea and respiratory infections, were the leading causes. In 2016, however, CVD became the leading cause of death in Cape Verde, Sao Tome and Principe and Timor-Leste, and ranked higher or maintained their ranks in the other countries (<xref ref-type="fig" rid="f2">Figure 2A</xref>). Considering the causes of CVD, there was an increase in the proportional mortality from ischemic heart disease, which, in 2016, was the first cause of death in most countries studied, except for Mozambique and Sao Tome and Principe. In general, there was a reduction in proportional mortality from rheumatic heart disease (<xref ref-type="fig" rid="f2">Figure 2B</xref>).</p>
        <p>
          <fig id="f2">
            <label>Figure 2</label>
            <caption>
              <title>Most common causes of death, considering age-standardized mortality, in the Portuguese-speaking countries in 1990 and 2016. A: All causes; B: From cardiovascular diseases. LRI = lower respiratory tract infection; NTD = neglected tropical diseases.</title>
            </caption>
            <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf02.jpg"/></fig>
        </p>
      </sec>
      <sec>
        <title>Trends in the mortality rates from CVD between 1990 and 2016</title>
        <p><xref ref-type="fig" rid="f3">Figure 3</xref> shows an important reduction in proportional mortality from CVD and in the age-standardized mortality rate from CVD in Portugal, revealing that the decline in mortality occurred at all age groups. In Brazil and in Equatorial Guinea, the proportion of deaths from CVD remained stable, while a consistent reduction was observed over the past 15 years in the age-standardized mortality rate, suggesting there was mainly a reduction in premature mortality from CVD. In the other countries, the proportion of deaths due to CVD increased, and the reduction in age-standardized mortality rate from CVD declined less expressively, suggesting an increasing impact of CVD in those countries.</p>
        <p>
          <fig id="f3">
            <label>Figure 3</label>
            <caption>
              <title>Mortality attributed to cardiovascular diseases in the Portuguese-speaking countries from 1990 to 2016. A. Proportional mortality from cardiovascular diseases (%), B. Age-standardized mortality rate from cardiovascular diseases (deaths/100,000).</title>
            </caption>
            <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf03.jpg"/></fig>
        </p>
        <p>Although the proportional mortality from CVD decreased in the PSC from 1990 to 2016, the decline was heterogeneous among the countries. <xref ref-type="fig" rid="f4">Figure 4</xref> shows the age-standardized mortality rates for each PSC in 1990 and 2016.</p>
        <p>
          <fig id="f4">
            <label>Figure 4</label>
            <caption>
              <title>Age-standardized mortality rate in the Portuguese-speaking countries in 1990 and 2016.</title>
            </caption>
            <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf04.jpg"/></fig>
        </p>
        <p><xref ref-type="fig" rid="f5">Figure 5</xref> reveals the positive correlation between the reduction in age-standardized mortality rates from CVD between 1990 and 2016 and the SDI of the country (r<sub>s</sub> = 0.7; p = 0.04), suggesting a reduction in mortality from CVD follows the improvement in the local socioeconomic conditions of the PSC.</p>
        <p>
          <fig id="f5">
            <label>Figure 5</label>
            <caption>
              <title>Correlation between the change in mortality from cardiovascular diseases between 1990 and 2016 and the sociodemographic index (r<sub>s</sub> = 0.7; p = 0.04).</title>
            </caption>
            <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf05.jpg"/></fig>
        </p>
      </sec>
      <sec>
        <title>Lost of healthy life years (DALY) due to CVD</title>
        <p>The trend in DALYs between 1990 and 2015 (<xref ref-type="fig" rid="f8">Supplementary Figure 1</xref>) in the PSC is similar to that reported for the age-standardized mortality rate: there was a heterogeneous reduction in all countries, more expressive in those with better SDI. Regarding the specific causes of CVD, <xref ref-type="fig" rid="f6">Figure 6</xref> shows the importance of ischemic heart disease and CbVD in all countries, for both sexes. The loss of healthy life years was greater for men in all countries, except for Equatorial Guinea, Sao Tome and Principe and Angola, being mainly due to the other heart diseases. The importance of rheumatic heart disease, which is strictly related to socioeconomic conditions, for the loss of healthy years is evident in the countries with the lowest SDI.</p>
        <p>
          <fig id="f6">
            <label>Figure 6</label>
            <caption>
              <title>Disability-adjusted life years (DALYs) for each cardiovascular disease for each Portuguese-speaking country, 2016.</title>
            </caption>
            <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf06.jpg"/></fig>
        </p>
      </sec>
      <sec>
        <title>Influence of the risk factors on CVD</title>
        <p><xref ref-type="fig" rid="f7">Figure 7</xref> reveals the risk factors attributed to the YLLs in each PSC. In general, of the classical risk factors and their determinants, arterial hypertension and dietary factors are the most important. The relevance of obesity is greater among women, being less important in Timor-Leste, despite the importance of metabolic risk factors in that country. The metabolic risk factors (high cholesterol, high blood sugar) have higher influence on the premature mortality from CVD in the countries with higher SDI (Portugal, Brazil and Equatorial Guinea). The relevance of the smoking habit is evenly greater for men, but heterogeneous among the countries. In addition, environmental risk factors, such as air pollution, are heterogeneous among the countries.</p>
        <p>
          <fig id="f7">
            <label>Figure 7</label>
            <caption>
              <title>Influence of the risk factors on the years of life lost (YLLs) because of cardiovascular diseases, according to sex, in each Portuguese-speaking country in 2016.</title>
            </caption>
            <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf07.jpg"/></fig>
        </p>
        <p>Detailed information about the metrics of the disease burden related to CVD and stratified by the PSC is shown in the <xref ref-type="app" rid="app1">Supplementary Tables</xref>.</p>
      </sec>
    </sec>
    <sec sec-type="discussion">
      <title>Discussion</title>
      <p>Portuguese is the sixth most spoken language worldwide, by 244 million speakers,<xref ref-type="bibr" rid="B16">16</xref> the fifth most commonly used language over the Internet, by 82.5 million cybernauts, and the third most commonly used language in the social media <italic>Facebook</italic> and <italic>Twitter</italic>, by 58.5 million people.<xref ref-type="bibr" rid="B17">17</xref> According to estimates of the Portuguese government, considering the demographic evolution, by 2050, the number of Portuguese speakers will increase to 335 million. Africa should exceed Brazil in the use of Portuguese within 50 years.<xref ref-type="bibr" rid="B16">16</xref>
			</p>
      <p>Portuguese is the official language of eight countries (Portugal, Brazil, Angola, Mozambique, Guinea-Bissau, Cape Verde, Sao Tome and Principe, and Timor-Leste). Despite the incorporation of native words and the grammatical and pronunciation changes characteristic of each country, their languages remain united to the Portuguese from Portugal, from which the PSC were colonies during the expansion of that nation. Independence from the Portuguese domination occurred at different points in time: Equatorial Guinea belonged to the Portuguese Empire only until 1778, being then given to Spain, while Brazil was a Portuguese colony until 1822. The other nations had their independence recognized by Portugal between 1973 and 1975. However, the cultural influence of Portugal on those countries has been striking, an example being Catholicism, the official religion in most of those countries, the predominance of the Portuguese surnames, in addition to the organization of the healthcare systems, which are similar in several aspects.<xref ref-type="bibr" rid="B2">2</xref><sup>,</sup><xref ref-type="bibr" rid="B18">18</xref>
			</p>
      <p>Despite their cultural identity, the socioeconomic development was heterogeneous among the PSC. In 2015, the SDI was as low as 0.28 and 0.29 in Guinea-Bissau and Mozambique, respectively, although, in Brazil (0.66) and Equatorial Guinea (0.61), the SDI was closer to that of Portugal (0.75). The same occurred with the Gross Domestic Product per capita (GDP per capita), quantified in United States dollars in that same year, ranging from 606 to 611 in Guinea-Bissau and Mozambique, and from 20,247 to 21,619 in Equatorial Guinea and Portugal, respectively. The percentages of public expenditures on health differed, representing, in 2013, 2% to 3% of the GDP of most PSC, except for Portugal and Timor-Leste, whose percentages were higher, ranging from 9.1% to 10.4%, respectively, while Brazil was at an intermediate level, currently at 4% of the GDP.<xref ref-type="bibr" rid="B2">2</xref>
			</p>
      <p>An important result of this study was to show that in all the PSC, except for Guinea-Bissau, reductions in age-standardized mortality rates from CVD were observed from 1990 to 2016. From a global perspective, the period was marked by a reduction in age-standardized mortality from CVD in all high-income and some middle-income countries, although little change could be observed in most Sub-Saharan countries.<xref ref-type="bibr" rid="B7">7</xref> In the PSC, a strong positive correlation was observed between the SDI and the reduction in the age-standardized mortality rates from CVD in the past 27 years. However, that pattern was not homogeneous, suggesting that other factors<xref ref-type="bibr" rid="B19">19</xref> could be associated with the observed mortality reduction.</p>
      <p>In Brazil and Portugal, that correlation was closer. The decline in age-standardized mortality rates in Brazil, associated with the increase in life expectancy, and the maintenance of a proportional mortality around 30%, from 1990 to 2016, point towards a greater relevance of the reduction in the premature mortality component.<xref ref-type="bibr" rid="B20">20</xref> The improvement in social inequality observed in Brazil and in some PSC might have contributed to that heterogeneous reduction in mortality as compared to the other Sub-Saharan countries.<xref ref-type="bibr" rid="B21">21</xref>
			</p>
      <p>It is worth noting that, of the total number of deaths occurring in the Sub-Saharan Africa in 2015, ischemic heart disease was the fifth cause of death, preceded by the infectious causes in both sexes, while hemorrhagic stroke was the seventh, diabetes <italic>mellitus</italic>, the eighth, and ischemic stroke, the fifteenth cause of death in both sexes.<xref ref-type="bibr" rid="B18">18</xref> In 2016, however, CVD were the first cause of death in almost all PSC, except for Guinea-Bissau, where CVD were the second cause of death, and Mozambique and Equatorial Guinea, where CVD were the third cause of death in both sexes. Ischemic heart diseases predominated in all PSC, except for Mozambique and Sao Tome and Principe, a different pattern from that observed in the other Sub-Saharan countries,<xref ref-type="bibr" rid="B18">18</xref> suggesting a similarity between the PSC.</p>
      <p>The DALYs were reduced in the PSC over the temporal series, from 1990 to 2016, probably reflecting an improvement in the health care provided to those populations.<xref ref-type="bibr" rid="B22">22</xref> The DALYs were mainly due to ischemic heart disease and CbVD in those PSC. That reduction was greater in the countries with the highest SDI. However, in an analysis of the GBD Study from 1990 to 2013, the SDI did not explain the reduction in the DALYs due to CVD, mainly because of the heterogeneity of the set of countries considered.<xref ref-type="bibr" rid="B22">22</xref>
			</p>
      <p>The systolic and diastolic blood pressure levels decreased from 1995 to 2015 in most high-income countries.<xref ref-type="bibr" rid="B23">23</xref> That effect was not observed in most Sub-Saharan countries,<xref ref-type="bibr" rid="B23">23</xref> and that could explain the predominance of the CbVD as the most important component of the mortality from CVD in Sub-Saharan countries, with the contribution of the increase in body mass and dietary factors.<xref ref-type="bibr" rid="B24">24</xref> The same has occurred in the PSC, where arterial hypertension and dietary factors had a more relevant influence in both sexes for the DALYs due to CVD. It is worth noting the importance of the dietary risk factors in most PSC under the influence of the global dietary pattern, with ultra-processed foods and excessive amounts of sugars and fats, modifying healthier traditional dietary patterns. Those risk factors can be modified by promoting policies that favor healthy dietary habits, the taxation of ultra-processed foods, and the subsidies to healthy food, such as fruits and vegetables.<xref ref-type="bibr" rid="B25">25</xref><sup>,</sup><xref ref-type="bibr" rid="B26">26</xref>
			</p>
      <p>The African populations are characterized by a great genetic diversity, representing the repository of genetic material of modern humans, who spread around the world over the past 100,000 years, having genetic adaptations in response to different climates, diets, geographic environments and infectious agents to which they have been exposed.<xref ref-type="bibr" rid="B27">27</xref> The genetic variations of Sub-Saharan Africa have been modelled by geographical and ethnolinguistic similarities.<xref ref-type="bibr" rid="B28">28</xref> In addition, in the European populations, linguistic similarities have shown to be better predictors of genome differences as compared to geographic differences.<xref ref-type="bibr" rid="B29">29</xref> The complex genetic interactions with the environmental and sociodemographic factors will be able to help us understand the heterogeneous occurrence of CVD.<xref ref-type="bibr" rid="B30">30</xref>
			</p>
      <p>Although the quality of the completeness of the data collected and estimates has varied between the different PSC, there was an improvement in the recent years of the temporal series,<xref ref-type="bibr" rid="B4">4</xref> indicating the importance of the investment in national systems of vital registration and verbal autopsy to understand the burden of CVD in those countries.</p>
      <sec>
        <title>Limitations and strengths</title>
        <p>The limitations of the analytical models of the GBD Study have been previously discussed in detail.<xref ref-type="bibr" rid="B4">4</xref><sup>-</sup><xref ref-type="bibr" rid="B6">6</xref><sup>,</sup><xref ref-type="bibr" rid="B8">8</xref> Despite the improvement in the completeness of the data on prevalence and morbidity in some PSC, the estimates of the GBD 2016 Study indicate that the integrity and quality of those data are heterogeneous. For example, in Brazil and Portugal, the coverage of the data on death exceeds 95%, in contrast to very low or even absent indices in PSC of Sub-Saharan Africa.<xref ref-type="bibr" rid="B4">4</xref><sup>,</sup><xref ref-type="bibr" rid="B8">8</xref> The GBD Study models may have been inadequate for the different countries in some groups of diseases, mainly the non-communicable ones and those under less strict epidemiological surveillance, such as the classification of Latin America as a non-endemic region for rheumatic heart disease, which differs from primary data of prevalence.<xref ref-type="bibr" rid="B31">31</xref><sup>,</sup><xref ref-type="bibr" rid="B32">32</xref>
				</p>
        <p>In addition, the sociocultural, demographic, economic and ethnic differences and particularities between the PSC are not captured by the GBD Study models. Such differences are frequently associated with life habits, health behaviors and risk factors that affect the global burden of CVD. Moreover, despite having the same colonization and cultural similarities, the historical factors and development pattern of the societies differ significantly between the PSC.<xref ref-type="bibr" rid="B2">2</xref>
				</p>
        <p>Despite those limitations, from the epidemiological point of view, the GBD Study is the most solid and comprehensive initiative to estimate the burden of CVD, being especially useful to enable standardized comparisons between countries, including the PSC, whose primary data are still scarce. Those limitations do not invalidate the importance of this study for the epidemiological evaluation of CVD in the PSC, aiming at the elaboration of educational, preventive and therapeutic strategies more adequate for each country's reality, considering their sociodemographic, economic and cultural differences.</p>
        <p>The major strength of this analysis is to consistently demonstrate that the importance of the CVD as a cause of death has grown in the PSC. Although mortality has decreased or remained stable in countries with better SDI - with a significant reduction in age-standardized mortality rates - the same pattern has not been observed in the countries with worse SDI, indicating the important impact of CVD and their association with socioeconomic factors. The GBD Study estimates have great relevance for the continuous reassessment of policies of prevention and health promotion, as well as for the formulation, planning and adequacy of new strategies to be implemented. Regional trends of morbidity and premature mortality from certain groups of CVD, especially in countries with lower SDI and less-structured health systems, should be considered, aiming at the individualization of action plans for countries with similar cultural origin, but very different health realities.</p>
      </sec>
    </sec>
    <sec sec-type="conclusions">
      <title>Conclusion</title>
      <p>The data presented show great differences in the relative importance of the burden of CVD in the PSC and indicate that such differences relate to the socioeconomic conditions of the countries. Of the CVD, ischemic heart disease is the major cause of death in all PSC, except for Mozambique and Sao Tome and Principe, where CbVD is the major cause. The PSC share the most relevant risk factors for CVD: hypertension and dietary factors. Genetic factors, implicit in the cultural identity, factors inherent in the host, as well as the huge social inequality might have contributed to explain the mortality rates observed. Collaboration between the PSC might allow sharing successful experiences to confront CVD between those countries.</p>
    </sec>
  </body>
  <back>
    <app-group>
      <app id="app1">
        <label/>
        <p>
          <fig id="f8">
            <label>Supplementary Figure 1</label>
            <caption>
              <title>Age-standardized Disability Adjusted Life Years (DALY) attributable to cardiovascular disease (CVD) in Portuguese-speaking countries, from 1990 to 2016.</title>
            </caption>
            <alternatives>
              <graphic xlink:href=""/>
              <graphic xlink:href="https://minio.scielo.br/documentstore/1678-4170/kRLBQhC7fDSzqYy3HxR9LNn/855948bca87e5f9ed0a0c6a2cdbcffc3b3ced671.jpg"/>
            </alternatives>
          </fig>
          <fig id="f9">
            <label>Supplementary Figure 2</label>
            <caption>
              <title>Mortality attibutable to risk factors in Portuguese-speaking countries, in 1990 and 2016.</title>
            </caption>
            <alternatives>
              <graphic xlink:href=""/>
              <graphic xlink:href="https://minio.scielo.br/documentstore/1678-4170/kRLBQhC7fDSzqYy3HxR9LNn/41b29f23b54e3f38aea6f998dc0363b54117cb0d.jpg"/>
            </alternatives>
          </fig>
        </p>
      </app>
    </app-group>
    <fn-group>
      <fn fn-type="financial-disclosure">
        <p>
          <bold>Sources of Funding</bold>
        </p>
        <p>The Ministry of Health of Brazil was responsible for funding the GBD Brazil Study (Fundo Nacional de Sa&#250;de, grant number (17217.9850001 /17-018). Ribeiro was supported in part by CNPq (Bolsa de produtividade em pesquisa, 310679/2016-8 and IATS, 465518/2014-1) and by FAPEMIG (Programa Pesquisador Mineiro, PPM-00428-17).</p>
      </fn>
      <fn fn-type="other">
        <p>
          <bold>Study Association</bold>
        </p>
        <p>This study is not associated with any thesis or dissertation work.</p>
      </fn>
      <fn fn-type="other">
        <p>
          <bold>Ethics approval and consent to participate</bold>
        </p>
        <p>This study was approved by the Ethics Committee of the Universidade Federal de Minas Gerais under the protocol number 62803316.7.0000.5149. All the procedures in this study were in accordance with the 1975 Helsinki Declaration, updated in 2013. Informed consent was obtained from all participants included in the study.</p>
      </fn>
    </fn-group>
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  </back>
  <sub-article article-type="translation" id="s1" xml:lang="pt">
    <front-stub>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Artigo Original</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Epidemiologia das Doen&#231;as Cardiovasculares em Pa&#237;ses de L&#237;ngua Portuguesa: Dados do "<italic>Global Burden of Disease</italic>", 1990 a 2016</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Nascimento</surname>
            <given-names>Bruno Ramos</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Brant</surname>
            <given-names>Luisa Campos Caldeira</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Oliveira</surname>
            <given-names>Gl&#225;ucia Maria Moraes de</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">2</xref>
          <xref ref-type="corresp" rid="c2"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Malachias</surname>
            <given-names>Marcus Vin&#237;cius Bol&#237;var</given-names>
          </name>
          <xref ref-type="aff" rid="aff3">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Reis</surname>
            <given-names>Gabriel Moreira Alves</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Teixeira</surname>
            <given-names>Renato Azeredo</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Malta</surname>
            <given-names>Deborah Carvalho</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Fran&#231;a</surname>
            <given-names>Elisabeth</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Souza</surname>
            <given-names>Maria de F&#225;tima Marinho</given-names>
          </name>
          <xref ref-type="aff" rid="aff4">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Roth</surname>
            <given-names>Gregory A.</given-names>
          </name>
          <xref ref-type="aff" rid="aff5">5</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Ribeiro</surname>
            <given-names>Antonio Luiz P.</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
      </contrib-group>
      <aff id="aff6">
        <label>1</label>
        <country>Brasil</country>
        <institution content-type="original">Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG - Brasil</institution>
      </aff>
      <aff id="aff7">
        <label>2</label>
        <country>Brasil</country>
        <institution content-type="original">Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ - Brasil</institution>
      </aff>
      <aff id="aff8">
        <label>3</label>
        <country>Brasil</country>
        <institution content-type="original">Faculdade Ci&#234;ncias M&#233;dicas de Minas Gerais, Belo Horizonte, MG - Brasil</institution>
      </aff>
      <aff id="aff9">
        <label>4</label>
        <country>Brasil</country>
        <institution content-type="original">Minist&#233;rio da Sa&#250;de, Bras&#237;lia, DF - Brasil</institution>
      </aff>
      <aff id="aff10">
        <label>5</label>
        <country>USA</country>
        <institution content-type="original">University of Washington, Seattle, WA - USA</institution>
      </aff>
      <author-notes>
        <corresp id="c2"><bold>Correspond&#234;ncia: Gl&#225;ucia Maria Moraes de Oliveira</bold>. Universidade Federal do Rio de Janeiro - R. Prof. Rodolpho P. Rocco, 255 - Pr&#233;dio do HU 8&#186; andar - sala 6, UFRJ. CEP 21941-913, Cidade Universit&#225;ria, RJ - Brasil. E-mail: <email>glauciam@cardiol.br</email>, <email>glauciamoraesoliveira@gmail.com</email>
				</corresp>
        <fn fn-type="con">
          <p>
            <bold>Contribui&#231;&#227;o dos autores</bold>
          </p>
          <p>Concep&#231;&#227;o e desenho da pesquisa: Oliveira GMM, Malachias, MVB, Ribeiro AL; Obten&#231;&#227;o de dados: Reis GMA, Ribeiro AL, Brant LCC, Souza MFM, Malta DC, Teixeira RA; Roth GA, An&#225;lise e interpreta&#231;&#227;o dos dados: Brant LCC, Reis GMA, Ribeiro AL, Nascimento BR; An&#225;lise estat&#237;stica: Teixeira RA, Brant LCC, Ribeiro, AL, Roth GA; Obten&#231;&#227;o de financiamento: Souza MFM, Fran&#231;a E; Reda&#231;&#227;o do manuscrito: Nascimento, BR, Brant, LCC, Oliveira GMM; Roth GA; Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante: Todos os autores.</p>
        </fn>
        <fn fn-type="conflict">
          <p>
            <bold>Potencial conflito de interesses</bold>
          </p>
          <p>Declaro n&#227;o haver conflito de interesses pertinentes.</p>
        </fn>
      </author-notes>
      <abstract>
        <title>Resumo</title>
        <sec>
          <title>Fundamento:</title>
          <p>Os pa&#237;ses de l&#237;ngua portuguesa (PLP) partilham a influ&#234;ncia da cultura portuguesa com desenvolvimento socioecon&#244;mico diverso de Portugal.</p>
        </sec>
        <sec>
          <title>Objetivo:</title>
          <p>Descrever as tend&#234;ncias de morbidade e mortalidade por doen&#231;as cardiovasculares (DCV) nos PLP, entre 1990 e 2016, estratificadas por sexo, e sua associa&#231;&#227;o com os respectivos &#237;ndices sociodemogr&#225;ficos (SDI).</p>
        </sec>
        <sec>
          <title>M&#233;todos:</title>
          <p>O estudo utilizou dados e metodologia do Global Burden of Disease (GBD) 2016. As informa&#231;&#245;es seguiram padr&#245;es internacionais de certifica&#231;&#227;o de &#243;bito, atrav&#233;s de sistemas de informa&#231;&#227;o sobre estat&#237;sticas vitais e vigil&#226;ncia da mortalidade, pesquisas e registros hospitalares. Empregaram-se t&#233;cnicas para padroniza&#231;&#227;o das causas de morte pelo m&#233;todo direto, e corre&#231;&#245;es para sub-registro dos &#243;bitos e <italic>garbage codes.</italic> Para determinar o n&#250;mero de mortes por cada causa, aplicou-se o algoritmo CODEm (Modelagem Agrupada de Causas de Morte). Estimaram-se os anos saud&#225;veis de vida perdidos (DALYs) e o SDI (renda per capita, n&#237;vel de escolaridade e taxa de fertilidade total) para cada pa&#237;s.</p>
        </sec>
        <sec>
          <title>Resultados:</title>
          <p>Existem grandes diferen&#231;as na import&#226;ncia relativa da carga de DCV nos PLP relacionadas principalmente &#224;s condi&#231;&#245;es socioecon&#244;micas. Entre as DCV, a doen&#231;a isqu&#234;mica do cora&#231;&#227;o foi a principal causa de morte nos PLP em 2016, com exce&#231;&#227;o de Mo&#231;ambique e S&#227;o Tom&#233; e Pr&#237;ncipe, onde as doen&#231;as cerebrovasculares a suplantaram. Os fatores de risco atribu&#237;veis mais relevantes para as DCV entre os PLP foram a hipertens&#227;o arterial e os fatores diet&#233;ticos. Um valor de p &lt; 0,05 foi considerado significativo.</p>
        </sec>
        <sec>
          <title>Conclus&#227;o:</title>
          <p>A colabora&#231;&#227;o entre os PLP poder&#225; permitir que experi&#234;ncias exitosas no combate &#224;s DCV sejam compartilhadas entre esses pa&#237;ses.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="pt">
        <title>Palavras-chave</title>
        <kwd>Doen&#231;as Cardiovasculares</kwd>
        <kwd>Epidemiologia</kwd>
        <kwd>Mortalidade</kwd>
        <kwd>Carga Global da Doen&#231;a / tend&#234;ncias</kwd>
      </kwd-group>
      <funding-group>
        <award-group>
          <funding-source>Fundo Nacional de Sa&#250;de</funding-source>
          <award-id>17217.9850001 /17-018</award-id>
        </award-group>
        <award-group>
          <funding-source>CNPq</funding-source>
          <award-id>310679/2016-8</award-id>
          <award-id>465518/2014-1</award-id>
        </award-group>
        <award-group>
          <funding-source>FAPEMIG</funding-source>
          <award-id>PPM-00428-17</award-id>
        </award-group>
        <funding-statement>O Minist&#233;rio da Sa&#250;de &#233; respons&#225;vel pelo financiamento do estudo GBD Brasil (Fundo Nacional de Sa&#250;de, projeto numero 17217.9850001 /17-018).Ribeiro &#233; apoiado em parte pelo CNPq (Bolsa de produtividade em pesquisa, 310679/2016-8 e IATS, 465518/2014-1) e pela FAPEMIG (Programa Pesquisador Mineiro, PPM-00428-17).</funding-statement>
      </funding-group>
    </front-stub>
    <body>
      <sec sec-type="intro">
        <title>Introdu&#231;&#227;o</title>
        <p>As doen&#231;as cardiovasculares (DCV) s&#227;o a principal causa de morte no mundo. Apesar de n&#227;o serem a primeira causa de morte em muitos pa&#237;ses de baixa e m&#233;dia renda, 80% das mortes e 88% das mortes prematuras por DCV ocorrem nesses pa&#237;ses.<xref ref-type="bibr" rid="B1">1</xref> Com o controle das doen&#231;as infecciosas e materno-infantis, o aumento da expectativa de vida e a crescente urbaniza&#231;&#227;o, a import&#226;ncia das DCV tende a crescer - principalmente nos pa&#237;ses de baixa e m&#233;dia renda. A implementa&#231;&#227;o de pol&#237;ticas de sa&#250;de - entre elas, o est&#237;mulo aos h&#225;bitos de vida saud&#225;veis, o acesso &#224;s preven&#231;&#245;es prim&#225;ria e secund&#225;ria de DCV e ao tratamento dos eventos cardiovasculares agudos - &#233;, portanto, essencial para o controle das DCV em todos os pa&#237;ses.<xref ref-type="bibr" rid="B1">1</xref>
				</p>
        <p>Os pa&#237;ses de l&#237;ngua portuguesa (PLP) sofreram influ&#234;ncias culturais de Portugal com distintas intensidades.<xref ref-type="bibr" rid="B2">2</xref> O estudo das tend&#234;ncias na morbimortalidade por DCV nesses pa&#237;ses pode nos trazer dados &#250;teis quanto &#224;s similaridades e diferen&#231;as entre eles. Esses dados podem propiciar uma troca de informa&#231;&#245;es entre os pa&#237;ses no que concerne a&#231;&#245;es bem-sucedidas de enfrentamento &#224;s DCV, al&#233;m de permitir uma reflex&#227;o sobre a influ&#234;ncia da cultura na carga de DCV.</p>
        <p>O "Global Burden of Disease Study" (GBD) &#233; um importante estudo epidemiol&#243;gico observacional que utiliza m&#233;tricas de morbimortalidade relativas &#224;s principais doen&#231;as, agravos e fatores de risco em n&#237;veis global, nacional e regional. Um dos objetivos do GBD &#233; compreender, atrav&#233;s da avalia&#231;&#227;o de tend&#234;ncias, as mudan&#231;as no perfil das doen&#231;as que afetam as popula&#231;&#245;es do s&#233;culo XXI.<xref ref-type="bibr" rid="B3">3</xref>
				</p>
        <p>O objetivo do presente estudo &#233; descrever as tend&#234;ncias de morbidade e mortalidade por DCV nos PLP entre 1990 e 2016, usando como base as estimativas do estudo "GBD 2016", e avaliar a associa&#231;&#227;o entre essas tend&#234;ncias e o &#237;ndice sociodemogr&#225;fico (SDI) desses pa&#237;ses.</p>
      </sec>
      <sec sec-type="methods">
        <title>M&#233;todos</title>
        <sec>
          <title>Os pa&#237;ses de l&#237;ngua portuguesa</title>
          <p>Foram considerados PLP aqueles oficialmente membros da Comunidade dos Pa&#237;ses de L&#237;ngua Portuguesa (CPLP), uma organiza&#231;&#227;o internacional criada em 17 de julho de 1996, cujo objetivo &#233; o "aprofundamento da amizade m&#250;tua e da coopera&#231;&#227;o entre os seus membros".<xref ref-type="bibr" rid="B2">2</xref> A lista inicial de pa&#237;ses inclu&#237;a Angola, Brasil, Cabo Verde, Guin&#233;-Bissau, Mo&#231;ambique, Portugal e S&#227;o Tom&#233; e Pr&#237;ncipe. Em 2002, ap&#243;s sua independ&#234;ncia, o Timor-Leste foi acolhido como pa&#237;s integrante. E, em 2014, a Guin&#233;-Equatorial tamb&#233;m foi aceita como membro, ap&#243;s a l&#237;ngua portuguesa ser oficializada no pa&#237;s. A localiza&#231;&#227;o e as caracter&#237;sticas demogr&#225;ficas, sociais e econ&#244;micas dos PLP encontram-se na <xref ref-type="table" rid="t2">Tabela 1</xref> e na <xref ref-type="fig" rid="f10">Figura 1</xref>.</p>
          <table-wrap id="t2">
            <label>Tabela 1</label>
            <caption>
              <title>Caracter&#237;sticas demogr&#225;ficas, sociais e econ&#244;micas dos pa&#237;ses de l&#237;ngua portuguesa, 2013</title>
            </caption>
            <table frame="hsides" rules="groups">
              <colgroup>
                <col width="10%"/>
                <col width="10%"/>
                <col width="10%"/>
                <col width="10%"/>
                <col width="10%"/>
                <col width="10%"/>
                <col width="10%"/>
                <col width="10%"/>
                <col width="10%"/>
                <col width="10%"/>
              </colgroup>
              <thead>
                <tr>
                  <th align="left">
									</th>
                  <th align="center">Angola</th>
                  <th align="center">Brasil</th>
                  <th align="center">Cabo Verde</th>
                  <th align="center">Guin&#233; Equatorial</th>
                  <th align="center">Guin&#233;-Bissau</th>
                  <th align="center">Mo&#231;ambique</th>
                  <th align="center">Portugal</th>
                  <th align="center">S&#227;o Tom&#233; e Pr&#237;ncipe</th>
                  <th align="center">Timor-Leste</th>
                </tr>
              </thead>
              <tbody>
                <tr>
                  <td align="left">Popula&#231;&#227;o (milh&#245;es)</td>
                  <td align="center">19</td>
                  <td align="center">201</td>
                  <td align="center">1</td>
                  <td align="center">1</td>
                  <td align="center">2</td>
                  <td align="center">24</td>
                  <td align="center">10</td>
                  <td align="center">0,2</td>
                  <td align="center">1</td>
                </tr>
                <tr>
                  <td align="left">Densidade populacional (hab/km&#178;)</td>
                  <td align="center">15</td>
                  <td align="center">24</td>
                  <td align="center">127</td>
                  <td align="center">39</td>
                  <td align="center">44</td>
                  <td align="center">31</td>
                  <td align="center">113</td>
                  <td align="center">190</td>
                  <td align="center">79</td>
                </tr>
                <tr>
                  <td align="left">&#193;rea (mil km&#178;)</td>
                  <td align="center">1247</td>
                  <td align="center">8516</td>
                  <td align="center">4</td>
                  <td align="center">28</td>
                  <td align="center">36</td>
                  <td align="center">786</td>
                  <td align="center">92</td>
                  <td align="center">1,0</td>
                  <td align="center">15</td>
                </tr>
                <tr>
                  <td align="left">PIB (USD, bilh&#245;es)</td>
                  <td align="center">125</td>
                  <td align="center">2473</td>
                  <td align="center">2</td>
                  <td align="center">22</td>
                  <td align="center">1</td>
                  <td align="center">16</td>
                  <td align="center">226</td>
                  <td align="center">0,3</td>
                  <td align="center">1</td>
                </tr>
                <tr>
                  <td align="left">PIB per capita (USD)</td>
                  <td align="center">4805</td>
                  <td align="center">12217</td>
                  <td align="center">3589</td>
                  <td align="center">20247</td>
                  <td align="center">611</td>
                  <td align="center">606</td>
                  <td align="center">21619</td>
                  <td align="center">1620</td>
                  <td align="center">1108</td>
                </tr>
                <tr>
                  <td align="left">Religi&#227;o principal</td>
                  <td align="center">Cat&#243;lica</td>
                  <td align="center">Cat&#243;lica</td>
                  <td align="center">Cat&#243;lica</td>
                  <td align="center">Cat&#243;lica</td>
                  <td align="center">Mu&#231;ulmana</td>
                  <td align="center">Cat&#243;lica</td>
                  <td align="center">Cat&#243;lica</td>
                  <td align="center">Cat&#243;lica</td>
                  <td align="center">Cat&#243;lica</td>
                </tr>
                <tr>
                  <td align="left">Gasto p&#250;blico com sa&#250;de (%PIB)</td>
                  <td align="center">2,6</td>
                  <td align="center">4,0</td>
                  <td align="center">2,5</td>
                  <td align="center">2,6</td>
                  <td align="center">1,1</td>
                  <td align="center">2,1</td>
                  <td align="center">9,1</td>
                  <td align="center">2,0</td>
                  <td align="center">10,4</td>
                </tr>
                <tr>
                  <td align="left">Gasto p&#250;blico com educa&#231;&#227;o (%PIB)</td>
                  <td align="center">4,9</td>
                  <td align="center">6,2</td>
                  <td align="center">5,5</td>
                  <td align="center">2,2</td>
                  <td align="center">2,2</td>
                  <td align="center">5,7</td>
                  <td align="center">4,2</td>
                  <td align="center">5,6</td>
                  <td align="center">16,2</td>
                </tr>
                <tr>
                  <td align="left">Taxa de analfabetismo (% popula&#231;&#227;o)</td>
                  <td align="center">28,4</td>
                  <td align="center">8,5</td>
                  <td align="center">12,8</td>
                  <td align="center">6,0</td>
                  <td align="center">40,1</td>
                  <td align="center">41,2</td>
                  <td align="center">5,2</td>
                  <td align="center">9,6</td>
                  <td align="center">35,9</td>
                </tr>
                <tr>
                  <td align="left">&#205;ndice sociodemogr&#225;fico<xref ref-type="table-fn" rid="TFN02">*</xref>
									</td>
                  <td align="center">0,42</td>
                  <td align="center">0,66</td>
                  <td align="center">0,55</td>
                  <td align="center">0,61</td>
                  <td align="center">0,29</td>
                  <td align="center">0,28</td>
                  <td align="center">0,75</td>
                  <td align="center">0,45</td>
                  <td align="center">0,45</td>
                </tr>
              </tbody>
            </table>
            <table-wrap-foot>
              <fn id="TFN02">
                <label>*</label>
                <p>Dados referentes a 2015. PIB: produto interno bruto. USD: d&#243;lares norte-americanos.</p>
              </fn>
            </table-wrap-foot>
          </table-wrap>
          <p>
            <fig id="f10">
              <label>Figura 1</label>
              <caption>
                <title>Mapa global com a localiza&#231;&#227;o dos pa&#237;ses de l&#237;ngua portuguesa, 2017.</title>
              </caption>
              <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf01-pt.jpg"/></fig>
          </p>
        </sec>
        <sec>
          <title>O estudo GBD</title>
          <p>O estudo GBD &#233; um projeto de pesquisa multinacional colaborativo que objetiva produzir estimativas consistentes de agravos &#224; sa&#250;de relacionados a mais de 333 doen&#231;as e les&#245;es. Uma ampla gama de fontes de dados (dados de vigil&#226;ncia em &#226;mbito nacional, aut&#243;psia verbal e registro vital, registros de doen&#231;as publicados e n&#227;o publicados e literatura cient&#237;fica publicada) e m&#233;todos foram empregados para produzir resultados espec&#237;ficos com intervalos de incerteza por idade, sexo e pa&#237;s para os anos 1990-2016, que s&#227;o atualizados anualmente para toda a s&#233;rie temporal. Este estudo &#233; baseado em dados do GBD 2016 e tamb&#233;m na metodologia empregada pelo mesmo, j&#225; descrita previamente em detalhes.<xref ref-type="bibr" rid="B4">4</xref><sup>-</sup><xref ref-type="bibr" rid="B6">6</xref>
					</p>
        </sec>
        <sec>
          <title>Defini&#231;&#245;es de DCV</title>
          <p>Foram consideradas as nove causas globais mais comuns de morte e morbidade relacionadas com DCV e uma categoria adicional para outras DCV, al&#233;m das estimativas de morbidade e mortalidade globais agrupadas por DCV.<xref ref-type="bibr" rid="B7">7</xref> A causa b&#225;sica de morte foi definida como DCV pela categoriza&#231;&#227;o dos c&#243;digos CID, a partir da declara&#231;&#227;o da causa da morte (DO), o documento b&#225;sico de informa&#231;&#227;o sobre causas de morte no caso de pa&#237;ses com sistemas de estat&#237;sticas vitais como o Brasil, por exemplo. Foram analisadas as seguintes causas, com c&#243;digos da CID-10 correspondentes segundo a lista de classifica&#231;&#227;o de causas do estudo GBD: 1- doen&#231;a card&#237;aca reum&#225;tica (c&#243;digos I01-I01.9, I02.0, I05-I09.9); 2- cardiopatia isqu&#234;mica (c&#243;digos I20-I25.9); 3- doen&#231;a cerebrovascular (DCbV) (G45-G46.8, I60-I69.9); 4- doen&#231;a card&#237;aca hipertensiva (I11); 5- cardiomiopatia e miocardite (A39.52, B33.2-B33.24, D86.85, I40-I43.9, I51.4-I51.5); 6- fibrila&#231;&#227;o atrial e <italic>flutter</italic> (I48); 7- aneurisma de aorta (I71); 8- doen&#231;a vascular perif&#233;rica (I70.2-I70.7, I73-I73.9); 9- endocardite (A39.51, I33-I33.9, I38-I39.9). C&#243;digos <italic>garbage</italic> como insufici&#234;ncia card&#237;aca (I50) e embolia pulmonar (I26), que n&#227;o definem a patologia que ocasionou o &#243;bito, segundo o m&#233;todo do estudo GBD foram redistribu&#237;das para essas causas espec&#237;ficas, conforme algoritmos definidos no estudo.</p>
          <p>No caso da mortalidade, o agrupamento dessas causas foi realizado no n&#237;vel das sequelas espec&#237;ficas da doen&#231;a (por exemplo, cardiopatia isqu&#234;mica devido &#224; s&#237;ndrome coronariana aguda, angina est&#225;vel cr&#244;nica, cardiopatia isqu&#234;mica cr&#244;nica e cardiomiopatia isqu&#234;mica). Foram feitos ajustes para dados que n&#227;o seguiram a defini&#231;&#227;o de caso espec&#237;fica (por exemplo, confirma&#231;&#245;es eletr&#244;nicas para o diagn&#243;stico cl&#237;nico).<xref ref-type="bibr" rid="B4">4</xref><sup>,</sup><xref ref-type="bibr" rid="B8">8</xref><sup>,</sup><xref ref-type="bibr" rid="B9">9</xref>
					</p>
        </sec>
        <sec>
          <title>An&#225;lise estat&#237;stica</title>
          <p>Foram empregados os modelos estat&#237;sticos do estudo GBD 2016 previamente relatados.<xref ref-type="bibr" rid="B4">4</xref><sup>-</sup><xref ref-type="bibr" rid="B6">6</xref> As fontes de dados para modelos est&#227;o dispon&#237;veis <italic>on-line</italic> a partir do Global Health Data Exchange (<ext-link ext-link-type="uri" xlink:href="http://ghdx.healthdata.org/">http://ghdx.healthdata.org/</ext-link>).</p>
        </sec>
        <sec>
          <title>M&#233;tricas de mortalidade e preval&#234;ncia</title>
          <p>O GBD 2016 utilizou dados dispon&#237;veis sobre causas de morte em 195 pa&#237;ses. Essas informa&#231;&#245;es foram coletadas de acordo com padr&#245;es internacionais de certifica&#231;&#227;o de &#243;bito, por meio de sistemas de informa&#231;&#227;o sobre estat&#237;sticas vitais, sistemas de vigil&#226;ncia da mortalidade, pesquisas, registros hospitalares e registros policiais.<xref ref-type="bibr" rid="B4">4</xref> As fontes de dados t&#234;m particularidades regionais como, por exemplo, no Brasil, onde os dados foram obtidos principalmente do Sistema de Informa&#231;&#227;o sobre Mortalidade (SIM), do Minist&#233;rio da Sa&#250;de, utilizando um sistema de codifica&#231;&#227;o automatizado.<xref ref-type="bibr" rid="B10">10</xref> No pa&#237;s, todas as mortes requerem a DO por um m&#233;dico. Para as mortes que ocorrem fora de servi&#231;os de sa&#250;de, as causas s&#227;o verificadas pelo Servi&#231;o de Verifica&#231;&#227;o de &#211;bitos ou funcion&#225;rio civil quando n&#227;o h&#225; m&#233;dico, e nesses casos as causas de morte n&#227;o s&#227;o registradas.<xref ref-type="bibr" rid="B11">11</xref> Os &#243;bitos por causa externa s&#227;o identificados por m&#233;dico legista no Instituto M&#233;dico Legal.</p>
          <p>Foram utilizadas, al&#233;m disso, t&#233;cnicas para corre&#231;&#227;o de problemas de qualidade na informa&#231;&#227;o sobre causas de morte.<xref ref-type="bibr" rid="B9">9</xref> Foram feitas corre&#231;&#245;es para sub-registro dos &#243;bitos e para causas consideradas pouco &#250;teis para a sa&#250;de p&#250;blica, denominadas <italic>garbage codes</italic>. Esse termo &#233; utilizado para descrever causas que n&#227;o podem ser consideradas causas b&#225;sicas de morte, ou s&#227;o causas inespec&#237;ficas. Algoritmos de redistribui&#231;&#227;o dos <italic>garbage codes</italic> foram desenvolvidos pelo estudo GBD para aumentar a validade das estimativas. Para essa redistribui&#231;&#227;o em causas de morte espec&#237;ficas, foram consideradas evid&#234;ncias de v&#225;rias fontes, tais como literatura m&#233;dica, opini&#227;o de especialistas e t&#233;cnicas estat&#237;sticas.<xref ref-type="bibr" rid="B4">4</xref><sup>,</sup><xref ref-type="bibr" rid="B8">8</xref><sup>,</sup><xref ref-type="bibr" rid="B12">12</xref>
					</p>
          <p>Ap&#243;s o tratamento de qualidade dos dados, o estudo GBD 2016 utilizou uma variedade de modelos estat&#237;sticos para determinar o n&#250;mero de mortes por cada causa, principalmente atrav&#233;s do algoritmo CODEm (<italic>Cause of Death Ensemble Model</italic>, ou Modelagem Agrupada de Causas de Morte). Para garantir que o n&#250;mero de mortes por causa n&#227;o exceda o n&#250;mero total de mortes estimadas, uma t&#233;cnica de corre&#231;&#227;o (CoCorrect) foi realizada. O ajuste por essa t&#233;cnica garante que a soma das estimativas do n&#250;mero de mortes por cada causa n&#227;o ultrapasse 100% dos &#243;bitos estimados em um determinado ano.<xref ref-type="bibr" rid="B13">13</xref>
					</p>
          <p>A preval&#234;ncia de doen&#231;a foi estimada em um n&#237;vel mais detalhado de sequelas espec&#237;ficas da doen&#231;a, utilizando como dados de entrada revis&#245;es sistem&#225;ticas da literatura cient&#237;fica publicadas, dados n&#227;o publicados de registros e de bancos de dados administrativos do sistema de sa&#250;de. Equa&#231;&#245;es de regress&#227;o foram usadas para ajustar os dados no sentido da defini&#231;&#227;o de caso padr&#227;o. Os dados apresentados foram analisados para o per&#237;odo de 1990 a 2016, e todas as an&#225;lises apresentadas foram estratificadas por sexo e apresentadas na forma de estimativas absolutas e padronizadas por idade, para os diferentes PLP.</p>
        </sec>
        <sec>
          <title>M&#233;tricas de carga de doen&#231;a</title>
          <p>Os anos saud&#225;veis de vida perdidos (<italic>Disability-Adjusted Life Years</italic>: DALYs) combinam informa&#231;&#245;es sobre morte prematura (anos de vida perdidos [<italic>Years of Life Lost</italic>: YLLs]) e defici&#234;ncia causada pela condi&#231;&#227;o (anos vividos com incapacidade [<italic>Years Lived with Disability</italic>: YLDs]) para fornecer uma medida sum&#225;ria dos anos saud&#225;veis de vida perdidos devido a essa condi&#231;&#227;o. As YLLs foram calculadas multiplicando as mortes observadas em cada idade espec&#237;fica em um ano de interesse pela expectativa de vida de refer&#234;ncia espec&#237;fica &#224; idade estimada pelo uso de m&#233;todos de tabela de vida. Os YLDs foram calculados multiplicando a preval&#234;ncia da doen&#231;a (em n&#250;mero de casos/ano) por um peso de incapacidade espec&#237;fica do estado de sa&#250;de, representando um grau de capacidade funcional perdida. O processo de estimativa do peso da incapacidade foi previamente descrito em detalhes.<xref ref-type="bibr" rid="B6">6</xref> Em resumo, os pesos de incapacidade foram desenvolvidos por meio de entrevistas domiciliares em v&#225;rios pa&#237;ses, com solicita&#231;&#227;o aos participantes da pesquisa que fizessem escolhas entre descri&#231;&#245;es leigas de diferentes estados de sa&#250;de.<xref ref-type="bibr" rid="B14">14</xref><sup>,</sup><xref ref-type="bibr" rid="B15">15</xref> Foi realizado ajuste por comorbidade, simulando 40 mil indiv&#237;duos em cada estrato de idade-sexo-pa&#237;s-ano exposto &#224; probabilidade independente de adquirir cada condi&#231;&#227;o, com base na preval&#234;ncia da doen&#231;a, com intervalos de incerteza de 95% (95% UI) relatados para cada estimativa. A padroniza&#231;&#227;o da idade foi por meio do m&#233;todo direto, aplicando uma estrutura et&#225;ria global.</p>
        </sec>
        <sec>
          <title>&#205;ndice sociodemogr&#225;fico</title>
          <p>O SDI est&#225; sendo usado como estimativa do n&#237;vel socioecon&#244;mico de cada pa&#237;s para avalia&#231;&#227;o de sua associa&#231;&#227;o com a carga de DCV, como uma fun&#231;&#227;o da transi&#231;&#227;o epidemiol&#243;gica global.<xref ref-type="bibr" rid="B4">4</xref><sup>,</sup><xref ref-type="bibr" rid="B8">8</xref> &#192; semelhan&#231;a do m&#233;todo utilizado para calcular o &#205;ndice de Desenvolvimento Humano (IDH), o SDI foi calculado para cada pa&#237;s ou territ&#243;rio de 1990 a 2016. O SDI &#233; a m&#233;dia geom&#233;trica ponderada da renda per capita, n&#237;vel de escolaridade e taxa de fecundidade total, e permite comparar o desempenho de cada pa&#237;s em rela&#231;&#227;o a pa&#237;ses com n&#237;vel s&#243;cio econ&#244;mico semelhante.</p>
          <p>Foi utilizado o software SPSS vers&#227;o 22.0 para Mac OSX (<italic>SPSS Inc., Chicago, Illinois</italic>) para realiza&#231;&#227;o de correla&#231;&#227;o (m&#233;todo de Spearman) entre a varia&#231;&#227;o das taxas de mortalidade por DCV padronizadas por idade entre 1990 e 2016 e o SDI do pa&#237;s. Um valor p &lt; 0.05 foi considerado estatisticamente significativo.</p>
        </sec>
        <sec>
          <title>Considera&#231;&#245;es &#233;ticas</title>
          <p>O estudo foi realizado em banco de dados secund&#225;rios de dom&#237;nio p&#250;blico, sem identifica&#231;&#227;o nominal, em conformidade com o Decreto n&#186; 7.724, 16 de maio de 2012 e a Resolu&#231;&#227;o n&#186; 510, de 7 de abril de 2016. O estudo GBD Brasil 2015 foi aprovado pelo Comit&#234; de &#201;tica em Pesquisa da Universidade Federal de Minas Gerais (Projeto CAAE 62803316.7.0000.5149).</p>
        </sec>
      </sec>
      <sec sec-type="results">
        <title>Resultados</title>
        <sec>
          <title>Causas de mortalidade por DCV</title>
          <p>A import&#226;ncia das DCV como causa de morte vem crescendo nos PLP. Em 1990, as DCV eram a principal causa de morte apenas no Brasil e em Portugal, enquanto nos demais pa&#237;ses estavam atr&#225;s de doen&#231;as infecciosas, como diarreia e infec&#231;&#245;es respirat&#243;rias. J&#225; em 2016, as DCV tamb&#233;m se tornaram a primeira causa de morte em Cabo Verde, S&#227;o Tom&#233; e Pr&#237;ncipe e Timor-Leste, al&#233;m de terem subido ou mantido posi&#231;&#245;es nos demais pa&#237;ses (<xref ref-type="fig" rid="f11">Figura 2A</xref>). Entre as causas de DCV, houve um aumento da mortalidade proporcional por cardiopatia isqu&#234;mica que, em 2016, foi a primeira causa de morte na maioria dos pa&#237;ses estudados, exceto em Mo&#231;ambique e S&#227;o Tom&#233; e Pr&#237;ncipe. De forma geral, nota-se tamb&#233;m uma redu&#231;&#227;o da mortalidade proporcional por cardiopatia reum&#225;tica (<xref ref-type="fig" rid="f11">Figura 2B</xref>).</p>
          <p>
            <fig id="f11">
              <label>Figura 2</label>
              <caption>
                <title>Causas de morte mais comuns, considerando-se a mortalidade ajustada por idade, nos pa&#237;ses de l&#237;ngua portuguesa, em 1990 e 2016.A) Todas as causas; B) Por doen&#231;as cardiovasculares. ITRI: infec&#231;&#227;o trato respirat&#243;rio inferior; DTN: doen&#231;as tropicais negligenciadas.</title>
              </caption>
              <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf02-pt.jpg"/></fig>
          </p>
        </sec>
        <sec>
          <title>Tend&#234;ncias nas taxas de mortalidade por DCV entre 1990 e 2016</title>
          <p>A <xref ref-type="fig" rid="f12">Figura 3</xref> mostra que em Portugal houve uma importante redu&#231;&#227;o na mortalidade proporcional por DCV e na taxa de mortalidade por DCV padronizada por idade, revelando que a queda na mortalidade aconteceu em todas as faixas et&#225;rias. No Brasil e na Guin&#233;-Equatorial, a propor&#231;&#227;o de mortes por DCV manteve-se praticamente est&#225;vel, enquanto houve redu&#231;&#227;o consistente ao longo dos &#250;ltimos 15 anos da taxa de mortalidade padronizada por idade, sugerindo que houve, principalmente, redu&#231;&#227;o da mortalidade prematura por DCV. Nos demais pa&#237;ses, a propor&#231;&#227;o de mortes por DCV aumentou e a redu&#231;&#227;o da taxa de mortalidade cardiovascular padronizada por idade caiu de forma menos expressiva, sugerindo crescente impacto das DCV nesses pa&#237;ses.</p>
          <p>
            <fig id="f12">
              <label>Figura 3</label>
              <caption>
                <title>Mortalidade atribu&#237;da &#224;s doen&#231;as cardiovasculares (DCV) nos pa&#237;ses de l&#237;ngua portuguesa, de 1990 a 2016. A) Mortalidade proporcional por DCV (%), B) Taxa de mortalidade por DCV padronizada por idade (mortes/100.000).</title>
              </caption>
              <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf03-pt.jpg"/></fig>
          </p>
          <p>Apesar das mortalidades proporcionais por DCV estarem em queda nos PLP de 1990 a 2016, a queda ocorreu de forma heterog&#234;nea entre os pa&#237;ses. Na <xref ref-type="fig" rid="f13">Figura 4</xref>, os valores das taxas de mortalidade padronizadas por idade para cada pa&#237;s de l&#237;ngua portuguesa em 1990 e 2016 podem ser observados.</p>
          <p>
            <fig id="f13">
              <label>Figura 4</label>
              <caption>
                <title>Taxa de mortalidade padronizada por idade nos pa&#237;ses de l&#237;ngua portuguesa em 1990 e 2016.</title>
              </caption>
              <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf04-pt.jpg"/></fig>
          </p>
          <p>A <xref ref-type="fig" rid="f14">Figura 5</xref> revela uma correla&#231;&#227;o positiva entre a redu&#231;&#227;o das taxas de mortalidade por DCV padronizadas por idade entre 1990 e 2016 e o SDI do pa&#237;s (r<sub>s</sub> = 0,7; p = 0,04), sugerindo que a redu&#231;&#227;o da mortalidade por DCV acompanha a melhoria das condi&#231;&#245;es socioecon&#244;micas locais nos PLP.</p>
          <p>
            <fig id="f14">
              <label>Figura 5</label>
              <caption>
                <title>Correla&#231;&#227;o entre mudan&#231;a na mortalidade por doen&#231;as cardiovasculares entre 1990 e 2016 e &#237;ndice sociodemogr&#225;fico (r<sub>s</sub> = 0,7; p = 0,04).</title>
              </caption>
              <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf05-pt.jpg"/></fig>
          </p>
        </sec>
        <sec>
          <title>Anos de vida saud&#225;veis perdidos (DALY) por DCV</title>
          <p>A tend&#234;ncia dos anos de vida perdidos entre 1990 e 2015 (<xref ref-type="fig" rid="f17">Figura Suplementar 1</xref>) nos PLP &#233; semelhante &#224;quela descrita para a taxa de mortalidade padronizada por idade: houve redu&#231;&#227;o em todos os pa&#237;ses, por&#233;m de forma heterog&#234;nea, sendo mais expressiva nos pa&#237;ses com melhor SDI. Em rela&#231;&#227;o &#224;s causas espec&#237;ficas de DCV, a <xref ref-type="fig" rid="f15">Figura 6</xref> mostra a import&#226;ncia da cardiopatia isqu&#234;mica e das DCbV em todos os pa&#237;ses, para ambos os sexos. A perda de anos saud&#225;veis de vida foi maior para os homens em todos os pa&#237;ses, exceto em Guin&#233;-Equatorial, S&#227;o Tom&#233; e Pr&#237;ncipe e Angola, e foi devida principalmente a outras cardiopatias. A import&#226;ncia da cardiopatia reum&#225;tica, doen&#231;a muito relacionada &#224;s condi&#231;&#245;es socioecon&#244;micas, para perda de anos saud&#225;veis de vida fica evidente nos pa&#237;ses com menor SDI.</p>
          <p>
            <fig id="f15">
              <label>Figura 6</label>
              <caption>
                <title>Anos saud&#225;veis de vida perdidos (DALYs) para cada doen&#231;a cardiovascular por pa&#237;s de l&#237;ngua portuguesa, 2016.</title>
              </caption>
              <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf06-pt.jpg"/></fig>
          </p>
        </sec>
        <sec>
          <title>Influ&#234;ncia dos fatores de risco sobre as DCV</title>
          <p>A <xref ref-type="fig" rid="f16">Figura 7</xref> revela os fatores de risco atribu&#237;veis aos anos de vida perdidos em cada pa&#237;s de l&#237;ngua portuguesa. De forma geral, entre os fatores de risco cl&#225;ssicos e seus determinantes, a hipertens&#227;o arterial e os fatores diet&#233;ticos s&#227;o os mais importantes. A relev&#226;ncia da obesidade &#233; maior entre as mulheres e mostra-se pouco relevante no Timor-Leste, apesar de nesse pa&#237;s os fatores de risco metab&#243;licos serem importantes. Os fatores de risco metab&#243;licos (colesterol alto, glicemia alta) t&#234;m maior influ&#234;ncia na mortalidade precoce por DCV nos pa&#237;ses com SDI mais alto (Portugal, Brasil e Guin&#233;-Equatorial), quando comparados aos demais. A relev&#226;ncia do tabagismo &#233; uniformemente maior para os homens, mas &#233; heterog&#234;nea entre os pa&#237;ses. Fatores de risco ambientais, como polui&#231;&#227;o do ar, tamb&#233;m mostram heterogeneidade entre os pa&#237;ses.</p>
          <p>
            <fig id="f16">
              <label>Figura 7</label>
              <caption>
                <title>Influ&#234;ncia dos fatores de risco nos anos de vida perdidos (YLLs) devido &#224;s doen&#231;as cardiovasculares estratificada por sexo, em cada pa&#237;s de l&#237;ngua portuguesa, em 2016.</title>
              </caption>
              <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf07-pt.jpg"/></fig>
          </p>
          <p>Informa&#231;&#245;es detalhadas das m&#233;tricas de carga de doen&#231;a relacionadas &#224;s DCV e estratificadas pelos PLP est&#227;o dispon&#237;veis nas <xref ref-type="app" rid="app2">Tabelas Suplementares</xref>.</p>
        </sec>
      </sec>
      <sec sec-type="discussion">
        <title>Discuss&#227;o</title>
        <p>O portugu&#234;s &#233; a sexta l&#237;ngua mais falada do globo, por 244 milh&#245;es de pessoas,<xref ref-type="bibr" rid="B16">16</xref> a quinta mais usada na <italic>Internet</italic>, por 82,5 milh&#245;es de cibernautas, e a terceira nas redes sociais <italic>Facebook</italic> e <italic>Twitter</italic>, por 58,5 milh&#245;es de utilizadores.<xref ref-type="bibr" rid="B17">17</xref> Segundo estimativas do governo portugu&#234;s, tendo em conta a evolu&#231;&#227;o demogr&#225;fica, at&#233; 2050 o n&#250;mero de pessoas no mundo que falar&#225; a l&#237;ngua portuguesa dever&#225; aumentar para 335 milh&#245;es. A previs&#227;o &#233; de que a &#193;frica dever&#225; superar o Brasil em crescimento do uso do portugu&#234;s dentro de 50 anos.<xref ref-type="bibr" rid="B16">16</xref>
				</p>
        <p>O portugu&#234;s &#233; l&#237;ngua oficial de oito pa&#237;ses (Portugal, Brasil, Angola, Mo&#231;ambique, Guin&#233;-Bissau, Cabo Verde, S&#227;o Tom&#233; e Pr&#237;ncipe, Timor Leste). Apesar da incorpora&#231;&#227;o de voc&#225;bulos nativos e de modifica&#231;&#245;es gramaticais e de pron&#250;ncia pr&#243;prias de cada pa&#237;s, as l&#237;nguas mant&#234;m uma unidade com o portugu&#234;s de Portugal, de onde foram col&#244;nias quando do processo expansivo daquela na&#231;&#227;o. A independ&#234;ncia do dom&#237;nio portugu&#234;s ocorreu em per&#237;odos diversos, sendo que a Guin&#233; Equatorial pertenceu ao imp&#233;rio portugu&#234;s somente at&#233; 1778, sendo posteriormente foi cedida para a Espanha, e o Brasil foi col&#244;nia at&#233; 1822. As demais na&#231;&#245;es tiveram sua independ&#234;ncia reconhecida por Portugal entre os anos de 1973 e 1975. Por&#233;m, a influ&#234;ncia cultural de Portugal nesses pa&#237;ses foi bastante marcante, exemplificada pela religi&#227;o oficial ser a cat&#243;lica em sua maioria, os sobrenomes de origem portuguesa serem predominantes, bem como a organiza&#231;&#227;o dos sistemas de sa&#250;de, que s&#227;o semelhantes em v&#225;rios aspectos.<xref ref-type="bibr" rid="B2">2</xref><sup>,</sup><xref ref-type="bibr" rid="B18">18</xref>
				</p>
        <p>Ainda que mantenham uma identidade cultural, o desenvolvimento socioecon&#244;mico ocorreu de forma heterog&#234;nea. O SDI, em 2015, era t&#227;o baixo quanto 0,28 e 0,29 na Guin&#233;-Bissau e Mo&#231;ambique, respectivamente, embora no Brasil (0,66) e na Guin&#233; Equatorial (0,61) se aproximasse mais daquele observado em Portugal (0,75). O mesmo ocorreu com o Produto Interno Bruto per capita (PIB per capita), quantificado em d&#243;lares americanos no mesmo ano, que variaram entre 606 e 611 - na Guin&#233;-Bissau e Mo&#231;ambique, 20.247 e 21.619 - na Guin&#233; Equatorial e Portugal, respectivamente. Os gastos p&#250;blicos com sa&#250;de representaram percentuais diversos, estando em 2013 na faixa de 2% a 3% do PIB da maioria desses pa&#237;ses, destacando-se Portugal e Timor-Leste com percentuais mais elevados, que variaram entre 9,1% e 10,4%, respectivamente, enquanto o Brasil se encontra em um n&#237;vel intermedi&#225;rio, atualmente com 4% do PIB.<xref ref-type="bibr" rid="B2">2</xref>
				</p>
        <p>Um aspecto importante dos resultados deste estudo &#233; mostrar que em todos os PLP, com exce&#231;&#227;o de Guin&#233; Bissau, foram observadas as redu&#231;&#245;es das taxas de mortalidade por DCV padronizadas por idade de 1990 a 2016. De forma global, o per&#237;odo foi marcado pela redu&#231;&#227;o da mortalidade por DCV padronizada por idade em todos os pa&#237;ses de alta renda e em alguns de renda intermedi&#225;ria, embora pouca modifica&#231;&#227;o p&#244;de ser observada na maioria dos pa&#237;ses da &#193;frica Subsaariana (ASS).<xref ref-type="bibr" rid="B7">7</xref> Nos PLP, houve uma forte correla&#231;&#227;o positiva entre o SDI e a redu&#231;&#227;o das taxas de mortalidade por DCV padronizadas por idade observada nos &#250;ltimos 27 anos. No entanto, esse padr&#227;o n&#227;o foi homog&#234;neo sugerindo que outros fatores<xref ref-type="bibr" rid="B19">19</xref> poderiam estar associados com as redu&#231;&#245;es de mortalidade observadas.</p>
        <p>No Brasil e em Portugal essa correla&#231;&#227;o foi mais estreita. A queda nas taxas de mortalidade padronizadas por idade no Brasil, associadas ao aumento da expectativa de vida, e manuten&#231;&#227;o da mortalidade proporcional em torno de 30%, de 1990 a 2016, apontam para maior relev&#226;ncia da redu&#231;&#227;o do componente de mortalidade precoce.<xref ref-type="bibr" rid="B20">20</xref> A melhoria das desigualdades sociais observadas no Brasil e em alguns PLP pode ter contribu&#237;do para essa redu&#231;&#227;o de mortalidade heterog&#234;nea em rela&#231;&#227;o aos demais pa&#237;ses da ASS.<xref ref-type="bibr" rid="B21">21</xref>
				</p>
        <p>&#201; importante ressaltar que, no total de &#243;bitos ocorridos na ASS, em 2015, a cardiopatia isqu&#234;mica representou a quinta causa de morte, precedida pelas causas infecciosas, em ambos os sexos; o acidente vascular encef&#225;lico (AVE) hemorr&#225;gico, a s&#233;tima; o diabetes <italic>mellitus</italic>, a oitava; e o AVE isqu&#234;mico, a d&#233;cima-quinta causa de &#243;bitos, em ambos os sexos.<xref ref-type="bibr" rid="B18">18</xref> Por outro lado, em 2016, nos PLP, as DCV representaram a primeira causa de &#243;bito em quase todos os pa&#237;ses, excetuando-se na Guin&#233;-Bissau, onde foi a segunda, e em Mo&#231;ambique e na Guin&#233; Equatorial, onde foi a terceira maior causa de &#243;bito, em ambos os sexos. As cardiopatias isqu&#234;micas predominaram em todos os PLP, excetuando-se em Mo&#231;ambique e S&#227;o Tom&#233; e Pr&#237;ncipe. Esse padr&#227;o discordou do observado nos demais pa&#237;ses da ASS,<xref ref-type="bibr" rid="B18">18</xref> sugerindo uma similaridade entre os PLP.</p>
        <p>Os DALYs foram reduzidos nos PLP ao longo da s&#233;rie temporal, de 1990 a 2016, provavelmente refletindo uma melhoria nos cuidados de sa&#250;de dessas popula&#231;&#245;es.<xref ref-type="bibr" rid="B22">22</xref> Os DAYLs se deveram principalmente &#224;s cardiopatias isqu&#234;micas e &#224;s DCbV nesse grupo de pa&#237;ses. Essa redu&#231;&#227;o foi maior nos que apresentaram maiores SDI. Por&#233;m, o SDI n&#227;o explicou de forma relevante a redu&#231;&#227;o dos DALYs por DCV em uma an&#225;lise do GBD de 1990-2013, principalmente devido a heterogeneidade do conjunto dos pa&#237;ses observados.<xref ref-type="bibr" rid="B22">22</xref>
				</p>
        <p>Os n&#237;veis de press&#227;o sist&#243;lica e diast&#243;lica diminu&#237;ram de 1995 a 2015 em grande parte dos pa&#237;ses de alta renda.<xref ref-type="bibr" rid="B23">23</xref> Esse efeito n&#227;o ocorreu na maioria dos pa&#237;ses da ASS,<xref ref-type="bibr" rid="B23">23</xref> o que poderia explicar a predomin&#226;ncia da DCbV como componente mais importante da mortalidade por DCV nos pa&#237;ses da ASS, para a qual tamb&#233;m contribu&#237;ram o aumento da massa corporal e os fatores diet&#233;ticos.<xref ref-type="bibr" rid="B24">24</xref> O mesmo ocorreu nos PLP, onde a hipertens&#227;o arterial e os fatores diet&#233;ticos tiveram influ&#234;ncia mais relevante, em ambos os sexos, para os DAYLs em decorr&#234;ncia das DCV. Destaca-se a import&#226;ncia dos fatores de risco diet&#233;ticos na maioria dos PLP, sob influ&#234;ncia do padr&#227;o alimentar globalizado, com alimentos ultra processados, com excesso de a&#231;ucares e gorduras, modificando padr&#245;es alimentares tradicionais mais saud&#225;veis. Esses fatores de risco podem ser modificados mediante a promo&#231;&#227;o de pol&#237;ticas de alimenta&#231;&#227;o saud&#225;vel, taxa&#231;&#227;o de alimentos ultra processados, subs&#237;dios a alimentos saud&#225;veis como frutas, legumes e hortali&#231;as.<xref ref-type="bibr" rid="B25">25</xref><sup>,</sup><xref ref-type="bibr" rid="B26">26</xref>
				</p>
        <p>As popula&#231;&#245;es africanas s&#227;o caracterizadas por uma grande diversidade gen&#233;tica e representam o reposit&#243;rio do material gen&#233;tico do homem moderno que se espalhou pelo mundo nos &#250;ltimos 100 mil anos, possuindo adapta&#231;&#245;es gen&#233;ticas em resposta aos diferentes climas, dietas, ambientes geogr&#225;ficos e agentes infecciosos aos quais foram expostos.<xref ref-type="bibr" rid="B27">27</xref> As varia&#231;&#245;es gen&#233;ticas da ASS foram modeladas por similaridades geogr&#225;ficas e etnolingu&#237;sticas.<xref ref-type="bibr" rid="B28">28</xref> Tamb&#233;m foi observado que, nas popula&#231;&#245;es europeias, similaridades lingu&#237;sticas se mostraram melhores preditores das diferen&#231;as gen&#244;micas, quando comparadas &#224;s diferen&#231;as geogr&#225;ficas.<xref ref-type="bibr" rid="B29">29</xref> As complexas intera&#231;&#245;es gen&#233;ticas com os fatores ambientais e sociodemogr&#225;ficos poder&#227;o nos ajudar no entendimento da ocorr&#234;ncia heterog&#234;nea das DCV.<xref ref-type="bibr" rid="B30">30</xref>
				</p>
        <p>Ainda que a qualidade da completude dos dados coletados e estimados tenha variado entre os diferentes PLP, houve melhora evolutiva nos anos mais recentes da s&#233;rie temporal,<xref ref-type="bibr" rid="B4">4</xref> apontando para a import&#226;ncia de investimento nos sistemas nacionais de registros vitais e de autopsia verbal para o entendimento da carga das DCV nesses pa&#237;ses.</p>
        <sec>
          <title>Limita&#231;&#245;es e for&#231;as</title>
          <p>As limita&#231;&#245;es dos modelos anal&#237;ticos do estudo GBD foram detalhadamente discutidas previamente.<xref ref-type="bibr" rid="B4">4</xref><sup>-</sup><xref ref-type="bibr" rid="B6">6</xref><sup>,</sup><xref ref-type="bibr" rid="B8">8</xref> Apesar da melhora progressiva na completude dos dados de preval&#234;ncia e morbidade em alguns PLP, as estimativas do estudo GBD 2016 indicam que a integridade e a qualidade desses dados t&#234;m ampla heterogeneidade. Como exemplo, a cobertura dos dados sobre &#243;bitos &#233; superior a 95% em pa&#237;ses como Brasil e Portugal, contrastando com &#237;ndices muito baixos ou dados inexistentes de PLP da ASS.<xref ref-type="bibr" rid="B4">4</xref><sup>,</sup><xref ref-type="bibr" rid="B8">8</xref> &#201; poss&#237;vel ter ocorrido uma inadequa&#231;&#227;o dos modelos do estudo GBD para os diferentes pa&#237;ses em alguns grupos de doen&#231;as, sobretudo aquelas n&#227;o notific&#225;veis e sob menor aten&#231;&#227;o epidemiol&#243;gica como, por exemplo, o enquadramento da Am&#233;rica Latina como regi&#227;o n&#227;o end&#234;mica para cardiopatia reum&#225;tica, que contrasta com dados prim&#225;rios de preval&#234;ncia.<xref ref-type="bibr" rid="B31">31</xref><sup>,</sup><xref ref-type="bibr" rid="B32">32</xref>
					</p>
          <p>Al&#233;m disso, as diferen&#231;as e particularidades socioculturais, demogr&#225;ficas, econ&#244;micas e &#233;tnicas entre os PLP dificultam sua captura pelos modelos do GBD. Tais diferen&#231;as s&#227;o frequentemente associadas a h&#225;bitos de vida, comportamentos de sa&#250;de e fatores de risco que afetam a carga global de DCV. Ademais, apesar da coloniza&#231;&#227;o em comum e das similaridades culturais, os fatores hist&#243;ricos e o padr&#227;o de desenvolvimento das sociedades diferem significativamente entre os PLP.<xref ref-type="bibr" rid="B2">2</xref>
					</p>
          <p>Apesar dessas limita&#231;&#245;es, o GBD constitui-se na iniciativa mais robusta e abrangente do ponto de vista epidemiol&#243;gico para as estimativas da carga de DCV, sendo especialmente &#250;til por possibilitar compara&#231;&#245;es padronizadas entre os pa&#237;ses, inclusive com os PLP nos quais dados prim&#225;rios s&#227;o ainda escassos. As limita&#231;&#245;es relatadas em geral n&#227;o invalidam a import&#226;ncia deste estudo para a avalia&#231;&#227;o epidemiol&#243;gica das DCV nos PLP, visando &#224; elabora&#231;&#227;o de estrat&#233;gias educativas, preventivas e terap&#234;uticas mais adequadas &#224; realidade de cada pa&#237;s, conhecidas suas diferen&#231;as sociodemogr&#225;ficas, econ&#244;micas e culturais.</p>
          <p>A principal for&#231;a desta an&#225;lise &#233; demonstrar consistentemente que a import&#226;ncia das DCV como causa de morte vem crescendo nos PLP. Apesar de a mortalidade ter reduzido ou se mantido est&#225;vel em pa&#237;ses com melhores SDI - com redu&#231;&#227;o significativa das taxas padronizadas por idade - o mesmo padr&#227;o n&#227;o foi observado naqueles com piores SDI, indicando um importante impacto das DCV e sua associa&#231;&#227;o com fatores socioecon&#244;micos. As estimativas do GBD t&#234;m grande relev&#226;ncia para a cont&#237;nua reavalia&#231;&#227;o de pol&#237;ticas preventivas e de promo&#231;&#227;o de sa&#250;de e tamb&#233;m para a formula&#231;&#227;o, planejamento e adequa&#231;&#227;o de novas estrat&#233;gias a serem implantadas. Tend&#234;ncias regionais de morbidade e mortalidade precoce por alguns grupos de DCV, especialmente nos pa&#237;ses com menores SDI e sistemas de sa&#250;de menos estruturados, devem ser levadas em conta, buscando-se a individualiza&#231;&#227;o dos modelos de a&#231;&#227;o para pa&#237;ses com origem cultural semelhante, mas realidades de sa&#250;de t&#227;o diversas.</p>
        </sec>
      </sec>
      <sec sec-type="conclusions">
        <title>Conclus&#227;o</title>
        <p>Os dados apresentados mostram que existem grandes diferen&#231;as na import&#226;ncia relativa da carga de DCV nos PLP e indicam que essas diferen&#231;as est&#227;o relacionadas &#224;s condi&#231;&#245;es socioecon&#244;micas de determinado pa&#237;s. Entre as DCV, a DIC &#233; a principal causa de morte em todos os PLP, com exce&#231;&#227;o de Mo&#231;ambique e S&#227;o Tom&#233; e Pr&#237;ncipe, onde as DCbV s&#227;o a principal causa. Os fatores de risco atribu&#237;veis mais relevantes para as DCV s&#227;o comuns entre os PLP, sendo eles a hipertens&#227;o arterial e os fatores diet&#233;ticos. Possivelmente os fatores gen&#233;ticos, impl&#237;citos na identidade cultural, os fatores inerentes ao hospedeiro, bem como as enormes desigualdades sociais tenham contribu&#237;do para a explica&#231;&#227;o das mortalidades observadas. A colabora&#231;&#227;o entre os PLP poder&#225; permitir que experi&#234;ncias exitosas no combate &#224;s DCV sejam compartilhadas entre esses pa&#237;ses.</p>
      </sec>
    </body>
    <back>
      <app-group>
        <app id="app2">
          <label/>
          <p>
            <fig id="f17">
              <label>Figura Suplementar 1</label>
              <caption>
                <title>Anos saud&#225;veis de vida perdidos (DALY) ajustados por idade atribu&#237;dos &#224;s doen&#231;as cardiovasculares (DCV) nos pa&#237;ses de l&#237;ngua portuguesa, de 1990 a 2016.</title>
              </caption>
              <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf08-pt.jpg"/></fig>
            <fig id="f18">
              <label>Figura Suplementar 2</label>
              <caption>
                <title>Mortalidade atribu&#237;vel a fatores de risco nos pa&#237;ses de l&#237;ngua portuguesa, em 1990 e 2016.</title>
              </caption>
              <graphic xlink:href="1678-4170-abc-110-06-0500-80098-gf09-pt.jpg"/></fig>
          </p>
        </app>
      </app-group>
      <fn-group>
        <fn fn-type="financial-disclosure">
          <p>
            <bold>Fontes de financiamento</bold>
          </p>
          <p>O Minist&#233;rio da Sa&#250;de &#233; respons&#225;vel pelo financiamento do estudo GBD Brasil (Fundo Nacional de Sa&#250;de, projeto numero 17217.9850001 /17-018).Ribeiro &#233; apoiado em parte pelo CNPq (Bolsa de produtividade em pesquisa, 310679/2016-8 e IATS, 465518/2014-1) e pela FAPEMIG (Programa Pesquisador Mineiro, PPM-00428-17).</p>
        </fn>
        <fn fn-type="other">
          <p>
            <bold>Vincula&#231;&#227;o acad&#234;mica</bold>
          </p>
          <p>N&#227;o h&#225; vincula&#231;&#227;o deste estudo a programas de p&#243;s-gradua&#231;&#227;o.</p>
        </fn>
        <fn fn-type="other">
          <p>
            <bold>Aprova&#231;&#227;o &#233;tica e consentimento informado</bold>
          </p>
          <p>Este estudo foi aprovado pelo Comit&#234; de &#201;tica da Universidade Federal de Minas Gerais sob o n&#250;mero de protocolo 62803316.7.0000.5149. Todos os procedimentos envolvidos nesse estudo est&#227;o de acordo com a Declara&#231;&#227;o de Helsinki de 1975, atualizada em 2013. O consentimento informado foi obtido de todos os participantes inclu&#237;dos no estudo.</p>
        </fn>
      </fn-group>
    </back>
  </sub-article>
</article>
