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  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">Arq Bras Cardiol</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</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id" specific-use="scielo-v3">vCdwpsrbFc7mZ6XvzYwPD4B</article-id>
      <article-id pub-id-type="publisher-id" specific-use="scielo-v2">S0066-782X2015000500003</article-id>
      <article-id pub-id-type="other">00003</article-id>
      <article-id pub-id-type="publisher-id" specific-use="previous-pid">S0066-782X2015005050019</article-id>
      <article-id pub-id-type="doi">10.5935/abc.20150019</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Original Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Evolution of Cardiovascular Diseases Mortality in the Counties of the
               State of Rio de Janeiro from 1979 to 2010</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Soares</surname>
            <given-names>Gabriel Porto</given-names>
          </name>
          <xref ref-type="aff" rid="aff01">1</xref>
          <xref ref-type="aff" rid="aff02">2</xref>
          <xref ref-type="aff" rid="aff03">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Klein</surname>
            <given-names>Carlos Henrique</given-names>
          </name>
          <xref ref-type="aff" rid="aff04">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Silva</surname>
            <given-names>Nelson Albuquerque de Souza e</given-names>
          </name>
          <xref ref-type="aff" rid="aff01">1</xref>
          <xref ref-type="aff" rid="aff02">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Oliveira</surname>
            <given-names>Glaucia Maria Moraes de</given-names>
          </name>
          <xref ref-type="aff" rid="aff01">1</xref>
          <xref ref-type="aff" rid="aff02">2</xref>
          <xref ref-type="corresp" rid="c01"/>
        </contrib>
      </contrib-group>
      <aff id="aff01">
        <label>1</label>
        <institution content-type="orgname">Universidade Federal do Rio de Janeiro</institution>
        <addr-line>
          <named-content content-type="city">Rio de Janeiro</named-content>
          <named-content content-type="state">RJ</named-content>
        </addr-line>
        <country country="BR">Brazil</country>
        <institution content-type="normalized">Universidade Federal do Rio de
               Janeiro</institution>
        <institution content-type="original">Universidade Federal do Rio de Janeiro, Rio de
               Janeiro, RJ - Brazil</institution>
      </aff>
      <aff id="aff02">
        <label>2</label>
        <institution content-type="orgname">Instituto do Cora&#231;&#227;o Edson Saad</institution>
        <addr-line>
          <named-content content-type="city">Rio de Janeiro</named-content>
          <named-content content-type="state">RJ</named-content>
        </addr-line>
        <country country="BR">Brazil</country>
        <institution content-type="normalized">Universidade Federal do Rio de
               Janeiro</institution>
        <institution content-type="original">Instituto do Cora&#231;&#227;o Edson Saad, Rio de Janeiro, RJ
               - Brazil</institution>
      </aff>
      <aff id="aff03">
        <label>3</label>
        <institution content-type="orgname">Universidade Severino Sombra</institution>
        <addr-line>
          <named-content content-type="city">Rio de Janeiro</named-content>
          <named-content content-type="state">RJ</named-content>
        </addr-line>
        <country country="BR">Brazil</country>
        <institution content-type="original">Universidade Severino Sombra, Rio de Janeiro, RJ -
               Brazil</institution>
        <institution content-type="normalized">Universidade Severino Sombra</institution>
      </aff>
      <aff id="aff04">
        <label>4</label>
        <institution content-type="orgname">Escola Nacional de Sa&#250;de P&#250;blica</institution>
        <addr-line>
          <named-content content-type="city">Rio de Janeiro</named-content>
          <named-content content-type="state">RJ</named-content>
        </addr-line>
        <country country="BR">Brazil</country>
        <institution content-type="normalized">Funda&#231;&#227;o Oswaldo Cruz</institution>
        <institution content-type="original">Escola Nacional de Sa&#250;de P&#250;blica, Rio de Janeiro,
               RJ - Brazil</institution>
      </aff>
      <author-notes>
        <corresp id="c01"><bold>Mailing address: Glaucia Maria Moraes de Oliveira,</bold> Rua
               Jo&#227;o Lira, 128,101, Leblon. Postal Code 22430-210, Rio de Janeiro, RJ &#8211; Brazil.
               Email: <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: Soares GP, Klein CH, Silva NAS, Oliveira
                  GMM. Acquisition of data: Soares GP, Klein CH, Silva NAS, Oliveira GMM. Analysis
                  and interpretation of the data: Soares GP, Klein CH, Silva NAS, Oliveira GMM.
                  Statistical analysis: Soares GP, Klein CH, Silva NAS, Oliveira GMM. Writing of the
                  manuscript: Soares GP, Klein CH, Silva NAS, Oliveira GMM. Critical revision of the
                  manuscript for intellectual content: Soares GP, Klein CH, Silva NAS, Oliveira
                  GMM.</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">
        <day>17</day>
        <month>03</month>
        <year>2015</year>
      </pub-date>
      <pub-date pub-type="collection">
        <month>05</month>
        <year>2015</year>
      </pub-date>
      <volume>104</volume>
      <issue>5</issue>
      <fpage>356</fpage>
      <lpage>365</lpage>
      <history>
        <date date-type="received">
          <day>22</day>
          <month>10</month>
          <year>2014</year>
        </date>
        <date date-type="rev-recd">
          <day>09</day>
          <month>01</month>
          <year>2015</year>
        </date>
        <date date-type="accepted">
          <day>12</day>
          <month>01</month>
          <year>2015</year>
        </date>
      </history>
      <permissions>
        <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by-nc/3.0/">
          <license-p>This is an Open Access article distributed under the terms of the Creative
                  Commons Attribution Non-Commercial License which permits unrestricted
                  non-commercial use, distribution, and reproduction in any medium, provided the
                  original work is properly cited.</license-p>
        </license>
      </permissions>
      <abstract>
        <sec>
          <title>Background:</title>
          <p>Cardiovascular Diseases (CVD) are the leading cause of death in Brazil.</p>
        </sec>
        <sec>
          <title>Objective:</title>
          <p>To estimate total CVD, cerebrovascular disease (CBVD), and ischemic heart disease
                  (IHD) mortality rates in adults in the counties of the state of Rio de Janeiro
                  (SRJ), from 1979 to 2010.</p>
        </sec>
        <sec>
          <title>Methods:</title>
          <p>The counties of the SRJ were analysed according to their denominations stablished
                  by the geopolitical structure of 1950, Each new county that have since been
                  created, splitting from their original county, was grouped according to their
                  former origin. Population Data were obtained from the Brazilian Institute of
                  Geography and Statistics (IBGE), and data on deaths were obtained from DataSus/MS.
                  Mean CVD, CBVD, and IHD mortality rates were estimated, compensated for deaths
                  from ill-defined causes, and adjusted for age and sex using the direct method for
                  three periods: 1979&#8211;1989, 1990&#8211;1999, and 2000&#8211;2010, Such results were spatially
                  represented in maps. Tables were also constructed showing the mortality rates for
                  each disease and year period.</p>
        </sec>
        <sec>
          <title>Results:</title>
          <p>There was a significant reduction in mortality rates across the three disease
                  groups over the the three defined periods in all the county clusters analysed,
                  Despite an initial mortality rate variation among the counties, it was observed a
                  homogenization of such rates at the final period (2000&#8211;2010). The drop in CBVD
                  mortality was greater than that in IHD mortality.</p>
        </sec>
        <sec>
          <title>Conclusion:</title>
          <p>Mortality due to CVD has steadily decreased in the SRJ in the last three decades.
                  This reduction cannot be explained by greater access to high technology procedures
                  or better control of cardiovascular risk factors as these facts have not occurred
                  or happened in low proportion of cases with the exception of smoking which has
                  decreased significantly. Therefore, it is necessary to seek explanations for this
                  decrease, which may be related to improvements in the socioeconomic conditions of
                  the population.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="en">
        <kwd>Cardiovascular Diseases/mortality</kwd>
        <kwd>Demographic Data</kwd>
        <kwd>Data Interpretation, Statistical</kwd>
        <kwd>Local Government</kwd>
      </kwd-group>
      <counts>
        <fig-count count="6"/>
        <table-count count="6"/>
        <equation-count count="0"/>
        <ref-count count="37"/>
        <page-count count="10"/>
      </counts>
    </article-meta>
  </front>
  <body>
    <sec sec-type="intro">
      <title>Introduction</title>
      <p>Cardiovascular diseases (CVD) are the primary cause of death worldwide, irrespective of
            the per capita income of a country. According to the World Health Organization (WHO),
            cardiovascular diseases were responsible for 17 million deaths in 2011, which represents
            three out of every ten deaths. Of these, seven million people died from ischemic heart
            diseases (IHD) and 6.2 million from stroke<xref ref-type="bibr" rid="B01">1</xref>.</p>
      <p>In Brazil, CVD also represent the main cause of deaths, corresponding to 28.6% of all
            causes of mortality in 2011. This is also the case in the state of Rio de Janeiro (SRJ),
            where CVD were responsible for 29.1% of all deaths. The two main groups of deaths from
            CVD are IHD and cerebrovascular diseases (CBVD), which respectively comprised 30.8% and
            30% of CVD deaths in Brazil and 31.6% and 27.6% of CVD deaths in the SRJ<xref ref-type="bibr" rid="B02">2</xref>.</p>
      <p>Though it is still the major cause of mortality worldwide, mortality due to CVD began to
            decline in industrialized countries after the 1950s. In Brazil, this downturn began to
            be noted in the late 1970s<xref ref-type="bibr" rid="B03">3</xref><sup>,</sup><xref ref-type="bibr" rid="B04">4</xref>, with a significant reduction in CVD mortality
            rates, despite some significant regional differences<xref ref-type="bibr" rid="B05">5</xref>.</p>
      <p>There are no studies assessing the evolution of mortality due to CVD and their two main
            groups, IHD and CBVD, by county units, which prompted us to conduct this study in the
            counties of the SRJ. </p>
      <p>According to the 2010 census, the SRJ had 15,989,929 inhabitants, or 8.4% of the
            country's population; it is divided into 92 counties, with a population density of
            365.23 inhabitants/km<xref ref-type="bibr" rid="B02">2</xref> according to IBGE<xref ref-type="bibr" rid="B06">6</xref>. The state's gross domestic product (GDP)
            corresponds to 11.3% of the national GDP. Theses counties of the state have a very
            heterogeneous socioeconomic structure<xref ref-type="bibr" rid="B07">7</xref>.</p>
      <p>The aim of this study was to estimate mortality rates due to CVD, CBVD, and IHD in
            adults from the counties of the state of Rio of Janeiro, from 1979 to 2010.</p>
    </sec>
    <sec sec-type="materials|methods">
      <title>Materials and methods</title>
      <p>A descriptive study of historical series of adults, i.e., people aged 20 years or over,
            in the counties of the SRJ, from 1979 to 2010.</p>
      <p>The counties of SRJ were analyzed according to their denomination established by the
            geopolitical structure of the year 1950, Each new county that have since been created,
            splitting from their original county, was grouped according to their former origin. This
            grouping led to a reduction in the total number of counties in existence in 2010 in SRJ,
            from 92 to 56 clusters for purposes of analysis in this study. These groupings were
            created with a view to future analyses that will consider information on county clusters
            available since 1950. Eight new counties were created in SRJ between 1950 and 1980, 28
            new counties were subsequently added. These new counties, in general still have small
            population sizes which also justified to group the data according to the original county
            cluster.</p>
      <p>The population data were obtained from the website of the Brazilian Institute of
            Geography and Statistics (IBGE)<xref ref-type="bibr" rid="B06">6</xref>, for the years
            of the 1980, 1991, 2000 and 2010 censuses years, and the 1996 population count.
            Population fractions corresponding to sex and age bracket were obtained, for each
            10-year interval. To estimate the intercensal interpolations and the extrapolations for
            the year 1979, the arithmetic progression method was used for each fraction of sex and
            age. The intercensal estimates provided by IBGE were not used, due to the change of
            method adopted in 2007, which caused abrupt and improbable inflections in all age
            brackets. These inflections alone could cause disruptions in the estimations of the
            mortality rates.</p>
      <p>The data relating to deaths were obtained from the DataSus website<xref ref-type="bibr" rid="B02">2</xref> and itemized by the fractions that were our primary interest of
            the study: CVD, corresponding to those recorded in chapters VII of ICD-9<xref ref-type="bibr" rid="B08">8</xref> or IX of ICD-10<xref ref-type="bibr" rid="B09">9</xref>; IHD, corresponding to codes 410-414 of ICD-9 or I20-I25 of ICD-10; and
            CBVD, corresponding to codes 430-438 of ICD-9 or I60-I69 of ICD 10. Deaths due to
            ill-defined causes, covered in chapter XVI of ICD-9 and XVIII of ICD-10, and total
            deaths due to all causes were also used for compensation. ICD-9 remained in effect until
            1995, while ICD-10 took effect from 1996. </p>
      <p>As the rates of mortality due to ill-defined causes in SRJ increased significantly after
               1990<xref ref-type="bibr" rid="B10">10</xref>, the decision was made to compensate
            this increase by proportionally allocating the deaths from ill-defined causes to the
            deaths resulting from CVD, IHD, and CBVD, in the same proportion that these deaths
            occurred i.e., excluding ill defined deaths. After adding the deaths due to CVD, IHD and
            CBVD with the corresponding proportion of deaths from ill-defined causes, the mortality
            rates of the study participants, adjusted for sex and age, were estimated using the
            direct method<xref ref-type="bibr" rid="B11">11</xref><sup>,</sup><xref ref-type="bibr" rid="B12">12</xref>. The standard population used for the adjustments was from the
            2000 census in the SRJ, stratified into seven age groups (20-29 years; 30-39 years;
            40-49 years; 50-59 years; 60-69 years; 70-79 years; and 80 years or over) for each sex.
            These rates were considered compensated and adjusted. </p>
      <p>The compensated and adjusted mean CVD, IHD, and CBVD mortality rates were calculated in
            three periods: 1979-1989; 1990-1999; and 2000-2010. The decision was made to construct
            rates for these periods rather than annual rates, which fluctuate substantially for a
            high percentage of the counties, due to their small populations, even considering the
            clustering described previously. Each of these periods was represented spatially on
               maps<xref ref-type="bibr" rid="B13">13</xref> with the geopolitical division of the
            counties of SRJ of 1950. A colour scale was attributed to CVD according to the variation
            of the mortality rates in the periods, starting from 200 deaths per 100,000 and
            thereafter at intervals of 100 deaths per 100,000 inhabitants. For IHD and CBVD, the
            scale starts at 50 deaths per 100,000 inhabitants and continues at intervals of 50
            deaths per 100,000 inhabitants.</p>
      <p>Tables were constructed with the compensated and adjusted mean CVD, CBVD, and IHD
            mortality rates, in the same three periods, grouping the counties by SRJ healthcare
            regions. In this study, the regional division used by the Rio de Janeiro State
            Department of Health (SESRJ) was modified in the Metropolitan Region, which henceforth
            constituted the Metropolitan Belt, encompassing all the counties of the region except
            for the counties of Rio de Janeiro and Niter&#243;i, which became two independent regions.
            The other regions, Middle Para&#237;ba, Mountain, North, Coastal Lowlands, Northwest,
            Mid-South, and Ilha Grande Bay, are those defined by the SESRJ. The standard deviations
            between the mean mortality rates of the counties of each region, and between all the
            counties in the three periods for the CVD, CBVD, and IHD mortality rates, were also
            estimated.</p>
      <p>The quantitative procedures were conducted using the Excel-Microsoft<xref ref-type="bibr" rid="B14">14</xref> and STATA<xref ref-type="bibr" rid="B15">15</xref> programs. Maps were created using the cartographic base of IBGE<xref ref-type="bibr" rid="B16">16</xref> and drawn using the Microsoft Paint<xref ref-type="bibr" rid="B17">17</xref> program.</p>
    </sec>
    <sec sec-type="results">
      <title>Results</title>
      <p>We noted that the mean CVD mortality rates (<xref ref-type="fig" rid="f01">Figure
               1</xref> and <xref ref-type="table" rid="t01">Table 1</xref>) decreased gradually
            over the three periods analysed. In the first period, from 1979 to 1989, all but three
            of the county clusters had mean CVD mortality rates above 500 deaths per 100,000
            inhabitants, while 13 had rates of more than 700 deaths per 100,000 inhabitants. These
            rates decreased gradually until the last period, when all the county clusters had rates
            of between 200 and 500 deaths per 100,000 inhabitants due to CVD. The mean CVD mortality
            rate in the state was 347.1 deaths per 100.000 inhabitants in the most recent period,
            compared to 656.8 deaths per 100.000 inhabitants in the earliest period. Besides the
            gradual decrease in cardiovascular mortality, we also noted a tendency towards
            homogenization of mortality rates among the county clusters and regions over time, which
            can be observed in the maps, and in the reduction of standard deviations (<xref ref-type="fig" rid="f01">Figure 1</xref> and <xref ref-type="table" rid="t01">Table
               1</xref>).</p>
      <fig id="f01" fig-type="other">
        <label>Figure 1</label>
        <caption>
          <title>Mean CVD mortality rates per 100,000 inhabitants, compensated and adjusted by
                  sex and age, in the counties of the state of Rio de Janeiro in three periods, from
                  1979 to 2010.</title>
        </caption>
        <graphic xlink:href="1678-4170-abc-104-05-0356-50019-gf01.jpg"/></fig>
      <table-wrap id="t01">
        <label>Table 1</label>
        <caption>
          <title>Mean CVD mortality rates per 100,000 inhabitants of the counties, compensated
                  and adjusted by sex and age, according to the healthcare regions of the State of
                  Rio de Janeiro, in three periods, from 1979 to 2010</title>
        </caption>
        <table frame="hsides" rules="groups">
          <thead>
            <tr>
              <th>Healthcare region</th>
              <th align="center">mean (79-89)</th>
              <th align="center">sd <xref ref-type="table-fn" rid="TFN01">*</xref>
                        (79-89)</th>
              <th align="center">mean (90-99)</th>
              <th align="center">sd<xref ref-type="table-fn" rid="TFN01">*</xref>
                        (90-99)</th>
              <th align="center">mean (00-10)</th>
              <th align="center">sd<xref ref-type="table-fn" rid="TFN01">*</xref>
                        (00-10)</th>
              <th align="center">No. of counties</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td>Rio de Janeiro</td>
              <td align="center">601,8</td>
              <td align="center">&#160;</td>
              <td align="center">461,2</td>
              <td align="center">&#160;</td>
              <td align="center">309,6</td>
              <td align="center">&#160;</td>
              <td align="center">1</td>
            </tr>
            <tr>
              <td>Metropolitan Belt</td>
              <td align="center">669,9</td>
              <td align="center">111,3</td>
              <td align="center">550,8</td>
              <td align="center">80,0</td>
              <td align="center">364,4</td>
              <td align="center">43,1</td>
              <td align="center">11</td>
            </tr>
            <tr>
              <td>Mid-South</td>
              <td align="center">691,4</td>
              <td align="center">77,6</td>
              <td align="center">549,9</td>
              <td align="center">46,4</td>
              <td align="center">359,7</td>
              <td align="center">25,1</td>
              <td align="center">7</td>
            </tr>
            <tr>
              <td>Mountain</td>
              <td align="center">687,9</td>
              <td align="center">105,3</td>
              <td align="center">483,4</td>
              <td align="center">62,3</td>
              <td align="center">350,8</td>
              <td align="center">37,7</td>
              <td align="center">13</td>
            </tr>
            <tr>
              <td>North</td>
              <td align="center">604,1</td>
              <td align="center">96,2</td>
              <td align="center">444,5</td>
              <td align="center">48,9</td>
              <td align="center">319,2</td>
              <td align="center">17,2</td>
              <td align="center">4</td>
            </tr>
            <tr>
              <td>Coastal Lowlands</td>
              <td align="center">578,0</td>
              <td align="center">72,2</td>
              <td align="center">472,0</td>
              <td align="center">47,6</td>
              <td align="center">322,6</td>
              <td align="center">34,3</td>
              <td align="center">5</td>
            </tr>
            <tr>
              <td>Niter&#243;i</td>
              <td align="center">550,1</td>
              <td align="center">&#160;</td>
              <td align="center">425,6</td>
              <td align="center">&#160;</td>
              <td align="center">259,4</td>
              <td align="center">&#160;</td>
              <td align="center">1</td>
            </tr>
            <tr>
              <td>Northwest</td>
              <td align="center">643,4</td>
              <td align="center">47,5</td>
              <td align="center">487,5</td>
              <td align="center">56,2</td>
              <td align="center">347,7</td>
              <td align="center">14,4</td>
              <td align="center">7</td>
            </tr>
            <tr>
              <td>Middle Paraiba</td>
              <td align="center">718,2</td>
              <td align="center">75,5</td>
              <td align="center">539,3</td>
              <td align="center">107,5</td>
              <td align="center">377,3</td>
              <td align="center">35,7</td>
              <td align="center">4</td>
            </tr>
            <tr>
              <td>Ilha Grande Bay</td>
              <td align="center">598,6</td>
              <td align="center">43,3</td>
              <td align="center">511,6</td>
              <td align="center">25,0</td>
              <td align="center">315,8</td>
              <td align="center">28,5</td>
              <td align="center">3</td>
            </tr>
            <tr>
              <td>
                <bold>Total</bold>
              </td>
              <td align="center">
                <bold>656,8</bold>
              </td>
              <td align="center">
                <bold>93,6</bold>
              </td>
              <td align="center">
                <bold>505,8</bold>
              </td>
              <td align="center">
                <bold>70,5</bold>
              </td>
              <td align="center">
                <bold>347,1</bold>
              </td>
              <td align="center">
                <bold>37,7</bold>
              </td>
              <td align="center">
                <bold>56</bold>
              </td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN01">
            <label>*</label>
            <p>
              <italic>sd: standard deviation of the means of the counties of the
                        region.</italic>
            </p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>The highest CVD mortality rates from 1979 to 1989 occurred in the region of Middle
            Para&#237;ba; from 1990 to 1999, the highest rates were in the Metropolitan Belt Region; and
            from 2000 to 2010, the highest values again occurred in Middle Para&#237;ba. The lowest CVD
            mortality rates for the three periods were recorded in the county of Niter&#243;i.</p>
      <p>CBVD (<xref ref-type="fig" rid="f02">Figure 2</xref> and <xref ref-type="table" rid="t02">Table 2</xref>) and IHD (<xref ref-type="fig" rid="f03">Figure 3</xref> and
               <xref ref-type="table" rid="t03">Table 3</xref>) mortality rates exhibited a behavior
            that closely resembled that of the CVD mortality rates, with a gradual reduction in
            rates over the periods, and a tendency towards homogenization of the rates for the SRJ,
            regions, and county clusters in the last period. In the SRJ, in the most remote and
            intermediate periods, there were higher mortality rates due to CBVD than due to IHD;
            however, in the last period, the figures were very similar, with a slight predominance
            of deaths due to IHD. This did not mean there was an increase in IHD mortality rates, as
            these also decreased over time, but only that there was a greater reduction in mortality
            rates due to CBVD than those resulting from IHD. </p>
      <fig id="f02" fig-type="other">
        <label>Figure 2</label>
        <caption>
          <title>Mean CBVD mortality rates per 100,000 inhabitants, compensated and adjusted by
                  sex and age, in the counties of the state of Rio de Janeiro in three periods, from
                  1979 to 2010.</title>
        </caption>
        <graphic xlink:href="1678-4170-abc-104-05-0356-50019-gf02.jpg"/></fig>
      <table-wrap id="t02">
        <label>Table 2</label>
        <caption>
          <title>Mean CBVD mortality rates per 100,000 inhabitants of the counties, compensated
                  and adjusted by sex and age, according to the healthcare regions of the State of
                  Rio de Janeiro in three periods, from 1979 to 2010</title>
        </caption>
        <table frame="hsides" rules="groups">
          <thead>
            <tr>
              <th>Healthcare region</th>
              <th align="center">mean (79-89)</th>
              <th align="center">sd<xref ref-type="table-fn" rid="TFN02">*</xref>
                        (79-89)</th>
              <th align="center">mean (90-99)</th>
              <th align="center">sd<xref ref-type="table-fn" rid="TFN02">*</xref>
                        (90-99)</th>
              <th align="center">mean (00-10)</th>
              <th align="center">sd<xref ref-type="table-fn" rid="TFN02">*</xref>
                        (00-10)</th>
              <th align="center">No. of counties</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td>Rio de Janeiro</td>
              <td align="center">190,4</td>
              <td align="center">&#160;</td>
              <td align="center">146,2</td>
              <td align="center">&#160;</td>
              <td align="center">95,3</td>
              <td align="center">&#160;</td>
              <td align="center">1</td>
            </tr>
            <tr>
              <td>Metropolitan Belt</td>
              <td align="center">247,9</td>
              <td align="center">46,7</td>
              <td align="center">208,5</td>
              <td align="center">35,0</td>
              <td align="center">121,2</td>
              <td align="center">16,7</td>
              <td align="center">11</td>
            </tr>
            <tr>
              <td>Mid-South</td>
              <td align="center">242,4</td>
              <td align="center">31,9</td>
              <td align="center">182,4</td>
              <td align="center">19,8</td>
              <td align="center">102,9</td>
              <td align="center">10,7</td>
              <td align="center">7</td>
            </tr>
            <tr>
              <td>Mountain</td>
              <td align="center">264,5</td>
              <td align="center">58,8</td>
              <td align="center">181,2</td>
              <td align="center">28,4</td>
              <td align="center">97,8</td>
              <td align="center">14,7</td>
              <td align="center">13</td>
            </tr>
            <tr>
              <td>North</td>
              <td align="center">261,4</td>
              <td align="center">49,8</td>
              <td align="center">191,7</td>
              <td align="center">35,8</td>
              <td align="center">113,0</td>
              <td align="center">18,3</td>
              <td align="center">4</td>
            </tr>
            <tr>
              <td>Coastal Lowlands</td>
              <td align="center">248,1</td>
              <td align="center">36,4</td>
              <td align="center">171,0</td>
              <td align="center">18,6</td>
              <td align="center">105,7</td>
              <td align="center">17,2</td>
              <td align="center">5</td>
            </tr>
            <tr>
              <td>Niter&#243;i</td>
              <td align="center">178,9</td>
              <td align="center">&#160;</td>
              <td align="center">146,4</td>
              <td align="center">&#160;</td>
              <td align="center">95,1</td>
              <td align="center">&#160;</td>
              <td align="center">1</td>
            </tr>
            <tr>
              <td>Northwest</td>
              <td align="center">263,7</td>
              <td align="center">36,8</td>
              <td align="center">186,8</td>
              <td align="center">30,0</td>
              <td align="center">100,0</td>
              <td align="center">10,6</td>
              <td align="center">7</td>
            </tr>
            <tr>
              <td>Middle Paraiba</td>
              <td align="center">244,0</td>
              <td align="center">22,6</td>
              <td align="center">161,4</td>
              <td align="center">50,3</td>
              <td align="center">103,9</td>
              <td align="center">14,9</td>
              <td align="center">4</td>
            </tr>
            <tr>
              <td>Ilha Grande Bay</td>
              <td align="center">241,0</td>
              <td align="center">49,6</td>
              <td align="center">188,3</td>
              <td align="center">24,9</td>
              <td align="center">95,2</td>
              <td align="center">2,3</td>
              <td align="center">3</td>
            </tr>
            <tr>
              <td>
                <bold>Total</bold>
              </td>
              <td align="center">
                <bold>253,5</bold>
              </td>
              <td align="center">
                <bold>44,5</bold>
              </td>
              <td align="center">
                <bold>186,8</bold>
              </td>
              <td align="center">
                <bold>32,8</bold>
              </td>
              <td align="center">
                <bold>105,9</bold>
              </td>
              <td align="center">
                <bold>16,3</bold>
              </td>
              <td align="center">
                <bold>56</bold>
              </td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN02">
            <label>*</label>
            <p>
              <italic>sd: standard deviation of the means of the counties of the
                        region.</italic>
            </p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <fig id="f03" fig-type="other">
        <label>Figure 3</label>
        <caption>
          <title>Mean mortality IHD rates per 100,000 inhabitants, compensated and adjusted by
                  sex and age, in the counties of the state of Rio de Janeiro in three periods, from
                  1979 to 2010.</title>
        </caption>
        <graphic xlink:href="1678-4170-abc-104-05-0356-50019-gf03.jpg"/></fig>
      <table-wrap id="t03">
        <label>Table 3</label>
        <caption>
          <title>Mean IHD mortality rates per 100,000 inhabitants of the counties, compensated
                  and adjusted by sex and age, according to the healthcare regions of the State of
                  Rio de Janeiro in three periods, from 1979 to 2010.</title>
        </caption>
        <table frame="hsides" rules="groups">
          <thead>
            <tr>
              <th>Healthcare region</th>
              <th align="center">mean (79-89)</th>
              <th align="center">sd<xref ref-type="table-fn" rid="TFN03">*</xref>
                        (79-89)</th>
              <th align="center">mean (90-99)</th>
              <th align="center">sd<xref ref-type="table-fn" rid="TFN03">*</xref>
                        (90-99)</th>
              <th align="center">mean (00-10)</th>
              <th align="center">sd<xref ref-type="table-fn" rid="TFN03">*</xref>
                        (00-10)</th>
              <th align="center">No. of counties</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td>Rio de Janeiro</td>
              <td align="center">217,3</td>
              <td align="center">&#160;</td>
              <td align="center">160,0</td>
              <td align="center">&#160;</td>
              <td align="center">106,2</td>
              <td align="center">&#160;</td>
              <td align="center">1</td>
            </tr>
            <tr>
              <td>Metropolitan Belt</td>
              <td align="center">186,0</td>
              <td align="center">56,2</td>
              <td align="center">151,7</td>
              <td align="center">38,5</td>
              <td align="center">102,9</td>
              <td align="center">12,5</td>
              <td align="center">11</td>
            </tr>
            <tr>
              <td>Mid-South</td>
              <td align="center">199,0</td>
              <td align="center">41,2</td>
              <td align="center">164,1</td>
              <td align="center">31,7</td>
              <td align="center">112,9</td>
              <td align="center">13,1</td>
              <td align="center">7</td>
            </tr>
            <tr>
              <td>Mountain</td>
              <td align="center">186,1</td>
              <td align="center">39,2</td>
              <td align="center">135,7</td>
              <td align="center">29,7</td>
              <td align="center">117,6</td>
              <td align="center">17,8</td>
              <td align="center">13</td>
            </tr>
            <tr>
              <td>North</td>
              <td align="center">137,6</td>
              <td align="center">57,3</td>
              <td align="center">101,1</td>
              <td align="center">21,3</td>
              <td align="center">89,7</td>
              <td align="center">6,2</td>
              <td align="center">4</td>
            </tr>
            <tr>
              <td>Coastal Lowlands</td>
              <td align="center">140,3</td>
              <td align="center">22,8</td>
              <td align="center">131,4</td>
              <td align="center">16,4</td>
              <td align="center">100,6</td>
              <td align="center">14,0</td>
              <td align="center">5</td>
            </tr>
            <tr>
              <td>Niter&#243;i</td>
              <td align="center">212,4</td>
              <td align="center">&#160;</td>
              <td align="center">156,2</td>
              <td align="center">&#160;</td>
              <td align="center">95,3</td>
              <td align="center">&#160;</td>
              <td align="center">1</td>
            </tr>
            <tr>
              <td>Northwest</td>
              <td align="center">168,9</td>
              <td align="center">34,3</td>
              <td align="center">143,4</td>
              <td align="center">18,3</td>
              <td align="center">115,5</td>
              <td align="center">16,0</td>
              <td align="center">7</td>
            </tr>
            <tr>
              <td>Middle Paraiba</td>
              <td align="center">203,6</td>
              <td align="center">25,3</td>
              <td align="center">183,3</td>
              <td align="center">43,1</td>
              <td align="center">132,9</td>
              <td align="center">18,3</td>
              <td align="center">4</td>
            </tr>
            <tr>
              <td>Ilha Grande Bay</td>
              <td align="center">162,4</td>
              <td align="center">21,7</td>
              <td align="center">159,2</td>
              <td align="center">33,0</td>
              <td align="center">94,8</td>
              <td align="center">14,5</td>
              <td align="center">3</td>
            </tr>
            <tr>
              <td>Total</td>
              <td align="center">179,0</td>
              <td align="center">44,1</td>
              <td align="center">146,0</td>
              <td align="center">33,9</td>
              <td align="center">109,6</td>
              <td align="center">17,5</td>
              <td align="center">56</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN03">
            <label>*</label>
            <p>
              <italic>sd: standard deviation of the means of the counties of the
                        region.</italic>
            </p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
    </sec>
    <sec sec-type="discussion">
      <title>Discussion</title>
      <p>Based on the data submitted, it can be seen that the mortality rates due to CVD, CBVD,
            and IHD gradually decreased in all the county clusters and regions of the SRJ over the
            study periods analysed, similar to the global tendency towards a reduction in
            cardiovascular mortality in recent decades<xref ref-type="bibr" rid="B18">18</xref><sup>,</sup><xref ref-type="bibr" rid="B19">19</xref>. The mean
            cardiovascular mortality rates in SRJ occupy intermediate values when compared with
            those of several countries. In the last period of the study, from 2000 to 2010, the mean
            CVD mortality rate was 347.1, the mean CBVD mortality rate was 105.9, and the mean IHD
            mortality rate was 109.6 deaths per 100,000 inhabitants. We can compare these with the
            mortality rates from the same causes in other regions worldwide in a similar period. In
            the decade of 2000-2010, the lowest CVD mortality rates were observed in Japan, with
            about 100 deaths per 100,000 inhabitants. As for IHD, the lowest rates occurred in Japan
            and Korea, with 38 and 37 deaths per 100,000 inhabitants, respectively; the lowest CBVD
            mortality rates are those of Israel and Switzerland, with 28 and 29 deaths per 100,000
            inhabitants, respectively. The highest IHD and CBVD mortality rates are reported for the
            Russian Federation, with 524 and 313 deaths per 100,000 inhabitants, respectively.
            Evidence allows us to assume that the CVD mortality rate in the Russian Federation is
            higher than 1000 deaths per 100,000 inhabitants. With such high rates, Russia leads the
            ranking of 35 countries in terms of mortality by cardiovascular disease, well ahead of
            the country occupying the second place, Slovakia, which had IHD and CBVD mortality rates
            of 324 and 112 deaths per 100,000 inhabitants, respectively. If we were to include SRJ
            in this ranking, it would occupy fourth place in CBVD mortality, only coming behind
            Russia, Slovakia, and Hungary. As for IHD mortality, SRJ is in 18<sup>th</sup> place,
            with lower mortality than countries like the United States, the United Kingdom, and
            Canada, but above Latin American countries like Chile and Mexico<xref ref-type="bibr" rid="B20">20</xref>.</p>
      <p>A similar reduction in CVD, IHD, and CBVD mortality rates in the county clusters of SRJ
            was also observed in Brazil, in the Metropolitan Region of S&#227;o Paulo<xref ref-type="bibr" rid="B21">21</xref>, but with a shorter analysis period, from 1990 to
            2009. The trend towards a reduction of cardiovascular mortality was the same as in SRJ,
            which had a drop in IHD mortality, but the most accentuated reduction occurred in CBVD.
            All the SRJ regions showed a drop in IHD and CBVD mortality rates. However, in the
            comparison between CBVD and IHD, presented variable mortality rates behaviours among the
            healthcare regions. In the Metropolitan Belt, the North, and Ilha Grande Bay, the
            predominance of CBVD was maintained from the most remote to the most recent period, for
            the county of Rio de Janeiro the opposite was seen with predominance of IHD mortality
            over CRVD throughout the entire period. The Mid-South, Mountain, Northwest, and Middle
            Para&#237;ba CRVD mortality rates predominate over IHD for the period of 1979-1989 and IHD
            mortality rates predominate over CRVD for the period of 2000-2010. In Ilha Grande Bay,
            the highest rate in the period of 1979-1989 was for CBVD, while in the last period, the
            rates of CBVD and IHD were similar (<xref ref-type="table" rid="t02">Tables 2</xref> and
               <xref ref-type="table" rid="t03">3</xref>). </p>
      <p>Niter&#243;i, which had a clearly higher rate of mortality from IHD than CBVD in the most
            remote period, began to have similar rates of IHD and CBVD in the last period. It should
            be emphasized that a less notable decline in the CBVD mortality rate was to be expected
            in Niter&#243;i, as this was the county with the lowest mortality rate for this cause in the
            initial period of the study. If we observe the relative reduction mortality rates for
            the total period [(1979-1989) &#8722; (2000-2010) / (1979-1989) ] for CVD, we see that Niter&#243;i
            had the greatest relative reduction (53%), and the Middle Para&#237;ba region had the
            smallest reduction (44%). The county of Niter&#243;i, in our study, was separated from the
            Metropolitan Region because its socioeconomic pattern differs considerably from that of
            the other counties of this region. Niter&#243;i has the third highest human development index
            in Brazil and the highest in SRJ<xref ref-type="bibr" rid="B06">6</xref>. Moreover,
            according to a survey by Funda&#231;&#227;o Getulio Vargas (FGV), Niter&#243;i has the largest number
            of people from Brazil's highest socioeconomic class (30.7%), based on data from the
            Demographic Census of 2010<xref ref-type="bibr" rid="B22">22</xref>. The county clusters
            of the Middle Para&#237;ba region, in turn, are those that underwent early industrialization
            due to the establishment of the first steel plant in Brazil, in Volta Redonda. The steel
            industry is admittedly one which causes great environmental pollution and unhealthy
            working conditions.</p>
      <p>In addition to the gradual decrease in mortality rates in the periods studied, it can
            also be noted that the mortality rates in the county clusters across the three groups of
            causes studied were homogenized, as is evident in the maps for the period 2000 to 2010.
            This analysis can be summarized in two aspects. Mortality due to CVD has dropped in the
            last three decades in the SRJ; this phenomenon was not isolated, and has also been noted
            in other countries and in other Brazilian states. This reduction was not uniform among
            the counties, with a relative overall reduction (between the first and last periods
            studied) in CVD for the counties of Niter&#243;i (53%), the Mid South Region (49%) and Rio de
            Janeiro (49%), and lesser reductions in the Middle Para&#237;ba (44%), Ilha Grande Bay, (46%)
            and Northwest regions (46%). This asymmetrical or diverse reduction of cardiovascular
            mortality rates cannot be explained by increasing access to high technology procedures
            such as myocardial revascularization surgery and angioplasty because of their poor
               performance<xref ref-type="bibr" rid="B23">23</xref><sup>-</sup><xref ref-type="bibr" rid="B25">25</xref> and limited scope in Brazil, or by better control of classic
            cardiovascular risk factors<xref ref-type="bibr" rid="B26">26</xref><sup>-</sup><xref ref-type="bibr" rid="B34">34</xref>. </p>
      <p>These findings need a search for other explanations for these reduction in
            cardiovascular mortality, such as improvements in the population's socioeconomic or
            environmental. Throughout the 20<sup>th</sup> century and particularly after the 1950s,
            Brazil experienced a period of progress that brought improvements in socioeconomic
            indicators, although social inequalities still remains high and have only begun to
            decrease in recent years, nevertheless preceding the drop in CVD mortality<xref ref-type="bibr" rid="B35">35</xref>. All over the world, social inequalities, even in
            so-called developed countries, are clearly associated with various diseases, including
            cardiovascular conditions. It is estimated that the cost of social inequality is as high
            as 39 billion pounds/year in the United Kingdom due to reduced life expectancy, murders,
            worsening of mental health, and other health problems<xref ref-type="bibr" rid="B36">36</xref>. In a recent study in the counties of Rio de Janeiro, we showed that the
            differences between CBVD mortality between the administrative regions of this county
            were ten times higher in the region with the lowest economic development index (Santa
            Cruz-Campo Grande) than in the region with the highest HDI (G&#225;vea). This increase in
            mortality occurred 10 years earlier<xref ref-type="bibr" rid="B37">37</xref>. </p>
      <p>The evaluations performed in this article depend on the quality of information recorded
            in the death certificates. Therefore, this might be a limitation for the interpretations
            made herein. We must thus reinforce the attention that should be given for the constant
            improvement of information provided by the physicians and other related professionals at
            the moment of deaths. This improvement involves continuing education of healthcare
            professionals and the provision of adequate working conditions by public and private
            institutions. Other limits relate to the scope of the data, and the methods used to
            estimate population and deaths according to the causes. None of the methods used
            guarantee certainty, but they are simple, logical, and easily reproducible.</p>
      <p>Future studies are necessary to relate the mortality due to the CVD and all the
            diagnostic components of this class to socioeconomic and social inequality indicators,
            as well as to environmental pollution in county clusters, which include variability of
            indicators and mortality. These socioeconomic and environmental variables appear to have
            a much greater impact on cardiovascular mortality than "classic" risk factors. </p>
    </sec>
  </body>
  <back>
    <fn-group>
      <fn fn-type="financial-disclosure">
        <p>
          <bold>Sources of Funding</bold>
        </p>
        <p>There were no external funding sources for this study.</p>
      </fn>
      <fn fn-type="other">
        <p>
          <bold>Study Association</bold>
        </p>
        <p>This article is part of the thesis of Doctoral submitted by Gabriel Porto Soares,
               from Universidade Federal do Rio de Janeiro.</p>
      </fn>
    </fn-group>
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  </back>
  <sub-article article-type="translation" id="SA1" xml:lang="pt">
    <front-stub>
      <title-group>
        <article-title>Evolu&#231;&#227;o da Mortalidade por Doen&#231;as do Aparelho Circulat&#243;rio nos
               Munic&#237;pios do Estado do Rio de Janeiro, de 1979 a 2010</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Soares</surname>
            <given-names>Gabriel Porto</given-names>
          </name>
          <xref ref-type="aff" rid="aff05">1</xref>
          <xref ref-type="aff" rid="aff06">2</xref>
          <xref ref-type="aff" rid="aff07">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Klein</surname>
            <given-names>Carlos Henrique</given-names>
          </name>
          <xref ref-type="aff" rid="aff08">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Silva</surname>
            <given-names>Nelson Albuquerque de Souza e</given-names>
          </name>
          <xref ref-type="aff" rid="aff05">1</xref>
          <xref ref-type="aff" rid="aff06">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Oliveira</surname>
            <given-names>Glaucia Maria Moraes de</given-names>
          </name>
          <xref ref-type="aff" rid="aff05">1</xref>
          <xref ref-type="aff" rid="aff06">2</xref>
          <xref ref-type="corresp" rid="c02"/>
        </contrib>
      </contrib-group>
      <aff id="aff05">
        <label>1</label>
        <institution content-type="orgname">Universidade Federal do Rio de Janeiro</institution>
        <addr-line>
          <named-content content-type="city">Rio de Janeiro</named-content>
          <named-content content-type="state">RJ</named-content>
        </addr-line>
        <country>Brasil</country>
        <institution content-type="normalized">Universidade Federal do Rio de
               Janeiro</institution>
        <institution content-type="original">Universidade Federal do Rio de Janeiro, Rio de
               Janeiro, RJ &#8211; Brasil</institution>
      </aff>
      <aff id="aff06">
        <label>2</label>
        <institution content-type="orgname">Instituto do Cora&#231;&#227;o Edson Saad</institution>
        <addr-line>
          <named-content content-type="city">Rio de Janeiro</named-content>
          <named-content content-type="state">RJ</named-content>
        </addr-line>
        <country>Brasil</country>
        <institution content-type="normalized">Universidade Federal do Rio de
               Janeiro</institution>
        <institution content-type="original">Instituto do Cora&#231;&#227;o Edson Saad, Rio de Janeiro, RJ
               &#8211; Brasil</institution>
      </aff>
      <aff id="aff07">
        <label>3</label>
        <institution content-type="orgname">Universidade Severino Sombra</institution>
        <addr-line>
          <named-content content-type="city">Rio de Janeiro</named-content>
          <named-content content-type="state">RJ</named-content>
        </addr-line>
        <country>Brasil</country>
        <institution content-type="original">Universidade Severino Sombra, Rio de Janeiro, RJ &#8211;
               Brasil</institution>
      </aff>
      <aff id="aff08">
        <label>4</label>
        <institution content-type="orgname">Escola Nacional de Sa&#250;de P&#250;blica</institution>
        <addr-line>
          <named-content content-type="city">Rio de Janeiro</named-content>
          <named-content content-type="state">RJ</named-content>
        </addr-line>
        <country>Brasil</country>
        <institution content-type="normalized">Funda&#231;&#227;o Oswaldo Cruz</institution>
        <institution content-type="original">Escola Nacional de Sa&#250;de P&#250;blica, Rio de Janeiro,
               RJ &#8211; Brasil</institution>
      </aff>
      <author-notes>
        <corresp id="c02">Correspond&#234;ncia: Glaucia Maria Moraes de Oliveira, Rua Jo&#227;o Lira,
               128,101, Leblon. CEP 22430-210, Rio de Janeiro, RJ &#8211; 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: Soares GP, Klein CH, Silva NAS, Oliveira GMM.
                  Obten&#231;&#227;o de dados: Soares GP, Klein CH, Silva NAS, Oliveira GMM. An&#225;lise e
                  interpreta&#231;&#227;o dos dados: Soares GP, Klein CH, Silva NAS, Oliveira GMM. An&#225;lise
                  estat&#237;stica: Soares GP, Klein CH, Silva NAS, Oliveira GMM. Reda&#231;&#227;o do manuscrito:
                  Soares GP, Klein CH, Silva NAS, Oliveira GMM. Revis&#227;o cr&#237;tica do manuscrito quanto
                  ao conte&#250;do intelectual importante: Soares GP, Klein CH, Silva NAS, Oliveira
                  GMM.</p>
        </fn>
        <fn fn-type="conflict">
          <p>
            <bold>Potencial conflito de interesse</bold>
          </p>
          <p>Declaro n&#227;o haver conflito de interesses pertinentes.</p>
        </fn>
      </author-notes>
      <abstract>
        <sec>
          <title>Fundamento:</title>
          <p>Doen&#231;as do aparelho circulat&#243;rio s&#227;o a primeira causa de morte no Brasil.</p>
        </sec>
        <sec>
          <title>Objetivo:</title>
          <p>Estimar taxas de mortalidade por Doen&#231;as do Aparelho Circulat&#243;rio (DAC), Doen&#231;as
                  Cerebrovasculares (DCBV) e Doen&#231;as Isqu&#234;micas do Cora&#231;&#227;o (DIC) nos adultos dos
                  munic&#237;pios do estado do Rio de Janeiro (ERJ), de 1979 a 2010.</p>
        </sec>
        <sec>
          <title>M&#233;todos:</title>
          <p>Os munic&#237;pios do ERJ foram analisados de acordo com a estrutura geopol&#237;tica do ano
                  1950, agrupando os munic&#237;pios emancipados a partir dessa data com sua sede
                  original. Popula&#231;&#245;es foram obtidas no IBGE e &#243;bitos obtidos no DataSus/MS.
                  Calcularam-se taxas m&#233;dias de mortalidade por DIC, DCBV e DAC, compensadas pelas
                  causas mal definidas e ajustadas pelo m&#233;todo direto em tr&#234;s per&#237;odos: 1979 a 1989,
                  1990 a 1999 e 2000 a 2010, representadas espacialmente em mapas. Tamb&#233;m foram
                  constru&#237;das tabelas com as taxas de mortalidade.</p>
        </sec>
        <sec>
          <title>Resultados:</title>
          <p>Houve redu&#231;&#227;o da mortalidade pelos tr&#234;s grupos de causas no decorrer dos per&#237;odos
                  em todos os agregados municipais analisados, com importante redu&#231;&#227;o das taxas e
                  homogeneiza&#231;&#227;o dessas no &#250;ltimo per&#237;odo. A queda da mortalidade por DCBV foi maior
                  do que a por DIC.</p>
        </sec>
        <sec>
          <title>Conclus&#227;o:</title>
          <p>A mortalidade por doen&#231;as do aparelho circulat&#243;rio apresentou queda nas &#250;ltimas
                  tr&#234;s d&#233;cadas no ERJ. Essa redu&#231;&#227;o n&#227;o pode ser explicada pelo acesso aos
                  procedimentos de alta tecnologia, nem tampouco pelo melhor controle dos fatores de
                  risco cardiovasculares. Tornando necess&#225;ria a busca de explica&#231;&#245;es para a queda da
                  mortalidade cardiovascular, que podem estar relacionadas com melhorias nas
                  condi&#231;&#245;es socioecon&#244;micos da popula&#231;&#227;o.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="pt">
        <kwd>Doen&#231;as Cardiovasculares/mortalidade</kwd>
        <kwd>Dados demogr&#225;ficos</kwd>
        <kwd>Interpreta&#231;&#227;o Estat&#237;stica de Dados</kwd>
        <kwd>Governo Local</kwd>
      </kwd-group>
    </front-stub>
    <body>
      <sec sec-type="intro">
        <title>Introdu&#231;&#227;o</title>
        <p>As Doen&#231;as do Aparelho Circulat&#243;rio (DAC) s&#227;o as principais causas de &#243;bitos em todo
               o mundo, independentemente do n&#237;vel de renda dos pa&#237;ses. De acordo com a Organiza&#231;&#227;o
               Mundial de Sa&#250;de (OMS), as doen&#231;as cardiovasculares foram respons&#225;veis por 17 milh&#245;es
               de mortes em 2011, o que representa tr&#234;s em cada dez &#243;bitos. Desses, sete milh&#245;es de
               pessoas morreram por doen&#231;as isqu&#234;micas do cora&#231;&#227;o, e 6,2 milh&#245;es, por acidente
               vascular cerebral<xref ref-type="bibr" rid="B01">1</xref>.</p>
        <p>No Brasil, as doen&#231;as do aparelho circulat&#243;rio tamb&#233;m representam as principais
               causas de &#243;bitos, correspondendo a 28,6% de todas as causas de mortalidade no ano
               2011. Assim como no estado do Rio de Janeiro, onde as DAC foram respons&#225;veis por
               29,1% de todos os &#243;bitos. Os dois principais grupos de &#243;bitos por DAC s&#227;o as Doen&#231;as
               Isqu&#234;micas do Cora&#231;&#227;o (DIC) e as Doen&#231;as Cerebrovasculares (DCBV) que compuseram,
               respectivamente, 30,8% e 30% dos &#243;bitos por DAC no Brasil, e 31,6% e 27,6% dos &#243;bitos
               por DAC no estado do Rio de Janeiro<xref ref-type="bibr" rid="B02">2</xref>.</p>
        <p>Apesar de ainda serem as principais causas de mortalidade em todo o globo, a partir
               do final da d&#233;cada de 1950, iniciou se um decl&#237;nio da mortalidade por Doen&#231;as do
               Aparelho Circulat&#243;rio (DAC) nos pa&#237;ses industrializados. No Brasil, essa queda come&#231;a
               a ser observada nos &#250;ltimos anos da d&#233;cada de 1970<xref ref-type="bibr" rid="B03">3</xref><sup>,</sup><xref ref-type="bibr" rid="B04">4</xref>. Com significativa
               redu&#231;&#227;o das taxas de mortalidade pelas DAC, apesar de importantes diferen&#231;as
                  regionais<xref ref-type="bibr" rid="B05">5</xref>.</p>
        <p>N&#227;o existem estudos com avalia&#231;&#227;o da evolu&#231;&#227;o da mortalidade por doen&#231;as do aparelho
               circulat&#243;rio e seus dois principais grupos, DIC e DCBV, por unidades municipais, o
               que nos motivou a desenvolver deste estudo nos munic&#237;pios do estado do Rio de
               Janeiro. </p>
        <p>O estado do Rio de Janeiro possu&#237;a, de acordo com o censo de 2010, 15.989.929
               habitantes, 8,4% da popula&#231;&#227;o do pa&#237;s, e &#233; dividido em 92 munic&#237;pios, com uma
               densidade populacional de 365,23 habitantes/km<xref ref-type="bibr" rid="B02">2</xref>, segundo o IBGE<xref ref-type="bibr" rid="B06">6</xref>. O PIB do estado
               corresponde a 11,3% do PIB nacional. Os munic&#237;pios do estado apresentam estrutura
               socioecon&#244;mica bastante heterog&#234;nea<xref ref-type="bibr" rid="B07">7</xref>.</p>
        <p>O objetivo deste estudo &#233; estimar taxas de mortalidade por doen&#231;as do aparelho
               circulat&#243;rio, doen&#231;as cerebrovasculares e doen&#231;as isqu&#234;micas do cora&#231;&#227;o nos adultos
               dos munic&#237;pios do estado do Rio de Janeiro, de 1979 a 2010.</p>
        <p>Estudo descritivo de s&#233;ries hist&#243;ricas, de adultos; isto &#233;, de pessoas de 20 anos ou
               mais, nos munic&#237;pios do estado do Rio de Janeiro (ERJ), de 1979 a 2010.</p>
      </sec>
      <sec sec-type="materials|methods">
        <title>Materiais e m&#233;todos</title>
        <p>Os munic&#237;pios do ERJ foram analisados de acordo com a estrutura geopol&#237;tica do ano
               1950, agrupando os munic&#237;pios emancipados a partir dessa data com sua sede original.
               Essas agrega&#231;&#245;es municipais implicaram a redu&#231;&#227;o do n&#250;mero total de munic&#237;pios
               existentes em 2010 no ERJ, que era de 92, para 56 agregados para fins de an&#225;lise
               neste estudo. Esses agrupamentos foram feitos visando futuras an&#225;lises que ir&#227;o
               considerar informa&#231;&#245;es sobre agregados municipais dispon&#237;veis desde 1950.Entre 1950 e
               1980 foram criados oito munic&#237;pios no ERJ, e a partir da&#237;, mais 28. Esses novos
               munic&#237;pios contam ainda com popula&#231;&#245;es pequenas.</p>
        <p>Os dados referentes &#224;s popula&#231;&#245;es foram obtidos no site do Instituto Brasileiro de
               Geografia e Estat&#237;stica (IBGE)<xref ref-type="bibr" rid="B06">6</xref>, referentes
               aos anos dos censos de 1980, 1991, 2000 e 2010, e da contagem populacional de 1996.
               Foram obtidas as fra&#231;&#245;es populacionais correspondentes a cada sexo e faixas et&#225;rias
               com intervalos de dez anos. Para estimar as interpola&#231;&#245;es intercensit&#225;rias e as
               extrapola&#231;&#245;es referentes ao ano 1979 foi utilizado o m&#233;todo de progress&#227;o aritm&#233;tica
               para cada fra&#231;&#227;o de sexo e idade. N&#227;o foram utilizadas as estimativas
               intercensit&#225;rias fornecidas pelo IBGE devido &#224; mudan&#231;a de m&#233;todo adotada a partir de
               2007, que causou inflex&#245;es abruptas e improv&#225;veis em todas as faixas et&#225;rias. Essas
               inflex&#245;es poderiam causar perturba&#231;&#245;es nas estimativas das taxas de mortalidade por
               mero artefato.</p>
        <p>Os dados referentes aos &#243;bitos foram obtidos no site do DataSus<xref ref-type="bibr" rid="B02">2</xref> discriminados nas fra&#231;&#245;es de interesse principal do estudo:
               Doen&#231;as do Aparelho Circulat&#243;rio (DAC), correspondentes &#224;quelas registradas nos
               cap&#237;tulos VII da CID 9<xref ref-type="bibr" rid="B08">8</xref> ou IX da CID-10<xref ref-type="bibr" rid="B09">9</xref>; Doen&#231;as Isqu&#234;micas do Cora&#231;&#227;o (DIC),
               correspondentes aos c&#243;digos 410-414 da CID-9 ou I20-I25 da CID-10; Doen&#231;as
               Cerebrovasculares (DCBV), correspondentes aos c&#243;digos 430-438 da CID-9 ou I60-I69 da
               CID-10. Tamb&#233;m foram utilizados para compensa&#231;&#227;o os &#243;bitos por causas mal definidas,
               abrigados no cap&#237;tulo XVI da CID-9 e XVIII da CID-10, e o total de &#243;bitos por todas
               as causas. A CID-9 vigorou at&#233; o ano 1995 e a CID 10, a partir de 1996. </p>
        <p>Como as taxas de mortalidade por causas mal definidas no ERJ aumentaram de forma
               relevante a partir de 1990<xref ref-type="bibr" rid="B10">10</xref>, optou-se pela
               realiza&#231;&#227;o de compensa&#231;&#227;o, que consistiu em alocar para os &#243;bitos por DAC, DIC e DCBV
               sua parte dos &#243;bitos por causas mal definidas, correspondente &#224;s suas fra&#231;&#245;es
               observadas entre os &#243;bitos definidos, isto &#233;, exclu&#237;dos os mal definidos. Ap&#243;s a
               compensa&#231;&#227;o dos &#243;bitos por DAC, DIC e DCBV pelos de causas mal definidas, foram
               estimadas taxas de mortalidade, ajustadas por sexo e idade, pelo m&#233;todo direto<xref ref-type="bibr" rid="B11">11</xref><sup>,</sup><xref ref-type="bibr" rid="B12">12</xref>. A popula&#231;&#227;o padr&#227;o para os ajustamentos foi a do censo de 2000 no
               estado do Rio de Janeiro, estratificada em sete grupos et&#225;rios (20 a 29 anos; 30 a 39
               anos; 40 a 49 anos; 50 a 59 anos; 60 a 69 anos; 70 a 79 anos; e 80 anos ou mais) em
               cada um dos sexos. Essas taxas foram denominadas compensadas e ajustadas. </p>
        <p>Foram calculadas as taxas m&#233;dias de mortalidade, compensadas e ajustadas, por DAC,
               DIC e DCBV, em tr&#234;s per&#237;odos: de 1979 a 1989; de 1990 e 1999; e de 2000 a 2010.
               Optou-se pela constru&#231;&#227;o de taxas para esses per&#237;odos e n&#227;o por taxas anuais porque
               essas sofrem flutua&#231;&#245;es relevantes para boa parte dos munic&#237;pios devido ao reduzido
               tamanho de suas popula&#231;&#245;es, mesmo considerando a agrega&#231;&#227;o descrita anteriormente.
               Cada um desses per&#237;odos foi representado espacialmente em mapas<xref ref-type="bibr" rid="B13">13</xref> com a divis&#227;o geopol&#237;tica dos munic&#237;pios do ERJ de 1950. Para
               a DAC foi atribu&#237;da uma escala de cores de acordo com a varia&#231;&#227;o das taxas de
               mortalidade nos per&#237;odos a partir de 200 &#243;bitos por 100 mil, e a seguir com
               intervalos de 100 &#243;bitos por 100 mil habitantes. Para DIC e DCBV a escala inicia a
               partir de 50 &#243;bitos por 100 mil habitantes, e segue com intervalos de 50 &#243;bitos por
               100 mil habitantes.</p>
        <p>Foram constru&#237;das tabelas com as taxas m&#233;dias de mortalidade, compensadas e
               ajustadas, por DAC, DCBV e DIC, nos mesmos tr&#234;s per&#237;odos, agrupando os munic&#237;pios
               pelas regi&#245;es de sa&#250;de do ERJ. Neste estudo, a divis&#227;o regional utilizada pela
               Secretaria Estadual de Sa&#250;de do Estado do Rio de Janeiro (SESRJ) foi modificada na
               Regi&#227;o Metropolitana, que passou a se constituir em Cintur&#227;o Metropolitano,
               compreendendo todos os munic&#237;pios da regi&#227;o, excetuados os munic&#237;pios do Rio de
               Janeiro e de Niter&#243;i, que passaram a ser duas regi&#245;es aut&#244;nomas. As demais regi&#245;es:
               M&#233;dio-Para&#237;ba, Serrana, Norte, Baixada Litor&#226;nea, Noroeste, Centro-Sul, e Ba&#237;a da
               Ilha Grande s&#227;o aquelas definidas pela SESRJ. Tamb&#233;m foram calculados os
               desvios-padr&#227;o entre as taxas m&#233;dias de mortalidade dos munic&#237;pios de cada regi&#227;o e
               entre todos os munic&#237;pios nos tr&#234;s per&#237;odos estudados para as taxas de mortalidade
               por DAC, DCBV e DIC.</p>
        <p>Os procedimentos quantitativos foram realizados com os programas Excel-Microsoft<xref ref-type="bibr" rid="B14">14</xref> e STATA<xref ref-type="bibr" rid="B15">15</xref>. Os mapas foram elaborados a partir da base cartogr&#225;fica do IBGE<xref ref-type="bibr" rid="B16">16</xref> e confeccionados com o uso do programa
                  Paint-Microsoft<xref ref-type="bibr" rid="B17">17</xref>.</p>
      </sec>
      <sec sec-type="results">
        <title>Resultados</title>
        <p>Observamos que as taxas m&#233;dias de mortalidade por DAC (<xref ref-type="fig" rid="f04">Figura 1</xref> e <xref ref-type="table" rid="t04">Tabela 1</xref>) apresentaram
               progressiva redu&#231;&#227;o nos seus valores no decorrer dos tr&#234;s per&#237;odos analisados. No
               primeiro per&#237;odo, de 1979 a 1989, todos os agregados municipais apresentavam taxas
               m&#233;dias de mortalidade por DAC superiores a 500 &#243;bitos por 100 mil habitantes, com
               exce&#231;&#227;o de apenas tr&#234;s, enquanto 13 tiveram taxas superiores a 700 &#243;bitos por 100 mil
               habitantes. Essas taxas diminu&#237;ram progressivamente at&#233; que no &#250;ltimo per&#237;odo todos
               os agregados municipais apresentaram taxas no intervalo de 200 a 500 &#243;bitos por DAC
               por 100 mil habitantes. A taxa m&#233;dia de mortalidade por DAC no estado foi de 347,1
               &#243;bitos no per&#237;odo mais recente comparada com a de 656,8 &#243;bitos no per&#237;odo mais
               remoto. Al&#233;m da queda progressiva da mortalidade cardiovascular observamos uma
               tend&#234;ncia &#224; homogeneiza&#231;&#227;o das taxas de mortalidade dos agregados municipais e das
               regi&#245;es ao longo do tempo, o que pode ser observado nos mapas e na redu&#231;&#227;o dos
               valores dos desvios padr&#227;o (<xref ref-type="fig" rid="f04">Figura 1</xref> e <xref ref-type="table" rid="t04">Tabela 1</xref>).</p>
        <fig id="f04" fig-type="other">
          <label>Figura 1</label>
          <caption>
            <title>Taxas m&#233;dias de mortalidade por DAC, compensadas e ajustadas por sexo e
                     idade, por 100 mil habitantes, nos munic&#237;pios do estado do Rio de Janeiro em
                     tr&#234;s per&#237;odos, de 1979 a 2010.</title>
          </caption>
          <graphic xlink:href="1678-4170-abc-104-05-0356-50019-gf01-pt.jpg"/></fig>
        <table-wrap id="t04">
          <label>Tabela 1</label>
          <caption>
            <title>Taxas m&#233;dias de mortalidade por DAC, compensadas e ajustadas por sexo e
                     Idade, por 100 mil habitantes dos munic&#237;pios segundo as regi&#245;es de sa&#250;de do
                     Estado do Rio de Janeiro em tr&#234;s per&#237;odos, de 1979 a 2010</title>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <th align="left">Regi&#227;o de sa&#250;de</th>
                <th align="center">m&#233;dia (79-89)</th>
                <th align="center">dp<xref ref-type="table-fn" rid="TFN04">*</xref>
                           (79-89)</th>
                <th align="center">m&#233;dia (90-99)</th>
                <th align="center">dp<xref ref-type="table-fn" rid="TFN04">*</xref>
                           (90-99)</th>
                <th align="center">m&#233;dia (00-10)</th>
                <th align="center">dp<xref ref-type="table-fn" rid="TFN04">*</xref>
                           (00-10)</th>
                <th align="center">N de munic&#237;pios</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Rio de Janeiro</td>
                <td align="center">601,8</td>
                <td align="center">&#160;</td>
                <td align="center">461,2</td>
                <td align="center">&#160;</td>
                <td align="center">309,6</td>
                <td align="center">&#160;</td>
                <td align="center">1</td>
              </tr>
              <tr>
                <td align="left">Cintur&#227;o Metropolitano</td>
                <td align="center">669,9</td>
                <td align="center">111,3</td>
                <td align="center">550,8</td>
                <td align="center">80,0</td>
                <td align="center">364,4</td>
                <td align="center">43,1</td>
                <td align="center">11</td>
              </tr>
              <tr>
                <td align="left">Centro-Sul</td>
                <td align="center">691,4</td>
                <td align="center">77,6</td>
                <td align="center">549,9</td>
                <td align="center">46,4</td>
                <td align="center">359,7</td>
                <td align="center">25,1</td>
                <td align="center">7</td>
              </tr>
              <tr>
                <td align="left">Serrana</td>
                <td align="center">687,9</td>
                <td align="center">105,3</td>
                <td align="center">483,4</td>
                <td align="center">62,3</td>
                <td align="center">350,8</td>
                <td align="center">37,7</td>
                <td align="center">13</td>
              </tr>
              <tr>
                <td align="left">Norte</td>
                <td align="center">604,1</td>
                <td align="center">96,2</td>
                <td align="center">444,5</td>
                <td align="center">48,9</td>
                <td align="center">319,2</td>
                <td align="center">17,2</td>
                <td align="center">4</td>
              </tr>
              <tr>
                <td align="left">Baixada Litor&#226;nea</td>
                <td align="center">578,0</td>
                <td align="center">72,2</td>
                <td align="center">472,0</td>
                <td align="center">47,6</td>
                <td align="center">322,6</td>
                <td align="center">34,3</td>
                <td align="center">5</td>
              </tr>
              <tr>
                <td align="left">Niter&#243;i</td>
                <td align="center">550,1</td>
                <td align="center">&#160;</td>
                <td align="center">425,6</td>
                <td align="center">&#160;</td>
                <td align="center">259,4</td>
                <td align="center">&#160;</td>
                <td align="center">1</td>
              </tr>
              <tr>
                <td align="left">Noroeste</td>
                <td align="center">643,4</td>
                <td align="center">47,5</td>
                <td align="center">487,5</td>
                <td align="center">56,2</td>
                <td align="center">347,7</td>
                <td align="center">14,4</td>
                <td align="center">7</td>
              </tr>
              <tr>
                <td align="left">M&#233;dio Paraiba</td>
                <td align="center">718,2</td>
                <td align="center">75,5</td>
                <td align="center">539,3</td>
                <td align="center">107,5</td>
                <td align="center">377,3</td>
                <td align="center">35,7</td>
                <td align="center">4</td>
              </tr>
              <tr>
                <td align="left">Baia da Ilha Grande</td>
                <td align="center">598,6</td>
                <td align="center">43,3</td>
                <td align="center">511,6</td>
                <td align="center">25,0</td>
                <td align="center">315,8</td>
                <td align="center">28,5</td>
                <td align="center">3</td>
              </tr>
              <tr>
                <td align="left">
                  <bold>Total</bold>
                </td>
                <td align="center">
                  <bold>656,8</bold>
                </td>
                <td align="center">
                  <bold>93,6</bold>
                </td>
                <td align="center">
                  <bold>505,8</bold>
                </td>
                <td align="center">
                  <bold>70,5</bold>
                </td>
                <td align="center">
                  <bold>347,1</bold>
                </td>
                <td align="center">
                  <bold>37,7</bold>
                </td>
                <td align="center">
                  <bold>56</bold>
                </td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN04">
              <label>*</label>
              <p>
                <italic>dp: desvio padr&#227;o das m&#233;dias dos munic&#237;pios da regi&#227;o.</italic>
              </p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>Os maiores valores das taxas de mortalidade por DAC de 1979 a 1989 ocorreram na
               regi&#227;o do M&#233;dio Para&#237;ba; de 1990 a 1999, no Cintur&#227;o Metropolitano; e de 2000 a 2010,
               os maiores valores foram novamente encontrados no M&#233;dio Para&#237;ba. As menores taxas de
               mortalidade por DAC, nos tr&#234;s per&#237;odos, foram apresentadas pelo munic&#237;pio de
               Niter&#243;i.</p>
        <p>As taxas de mortalidade por DCBV (<xref ref-type="fig" rid="f05">Figura 2</xref> e
                  <xref ref-type="table" rid="t05">Tabela 2</xref>) e DIC (<xref ref-type="fig" rid="f06">Figura 3</xref> e <xref ref-type="table" rid="t06">Tabela 3</xref>)
               apresentaram comportamento muito parecido com aquele das taxas de mortalidade por
               DAC, com progressiva redu&#231;&#227;o dos valores no decorrer dos per&#237;odos e com tend&#234;ncia &#224;
               homogeneiza&#231;&#227;o das taxas do ERJ, das regi&#245;es e dos agregados municipais no &#250;ltimo
               per&#237;odo. No ERJ, nos per&#237;odos mais remoto e intermedi&#225;rio, ocorreram taxas mais
               elevadas de &#243;bitos por doen&#231;as cerebrovasculares do que por doen&#231;as isqu&#234;micas do
               cora&#231;&#227;o; por&#233;m, no &#250;ltimo per&#237;odo, passaram a ser muito semelhantes, com discreta
               predomin&#226;ncia dos &#243;bitos por DIC. Entretanto, isso n&#227;o implicoueleva&#231;&#227;o das taxas de
               mortalidade por DIC, j&#225; que essas tamb&#233;m diminu&#237;ram no decorrer do tempo, mas apenas
               que a redu&#231;&#227;o das taxas de &#243;bito por doen&#231;as cerebrovasculares foi superior &#224; redu&#231;&#227;o
               da mortalidade por doen&#231;a isqu&#234;mica do cora&#231;&#227;o. </p>
        <fig id="f05" fig-type="other">
          <label>Figura 2</label>
          <caption>
            <title>Taxas m&#233;dias de mortalidade por DCBV, compensadas e ajustadas por sexo e
                     idade, por 100 mil habitantes nos munic&#237;pios do estado do Rio de Janeiro em
                     tr&#234;s per&#237;odos, de 1979 a 2010.</title>
          </caption>
          <graphic xlink:href="1678-4170-abc-104-05-0356-50019-gf02-pt.jpg"/></fig>
        <table-wrap id="t05">
          <label>Tabela 2</label>
          <caption>
            <title>Taxas m&#233;dias de mortalidade por DCBV, compensadas e ajustadas por sexo e
                     idade, por 100 mil habitantes dos munic&#237;pios segundo as regi&#245;es de sa&#250;de do
                     Estado do Rio de Janeiro em tr&#234;s per&#237;odos, de 1979 a 2010</title>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <th align="left">Regi&#227;o de sa&#250;de</th>
                <th align="center">m&#233;dia (79-89)</th>
                <th align="center">dp<xref ref-type="table-fn" rid="TFN05">*</xref>
                           (79-89)</th>
                <th align="center">m&#233;dia (90-99)</th>
                <th align="center">dp<xref ref-type="table-fn" rid="TFN05">*</xref>
                           (90-99)</th>
                <th align="center">m&#233;dia (00-10)</th>
                <th align="center">dp<xref ref-type="table-fn" rid="TFN05">*</xref>
                           (00-10)</th>
                <th align="center">N de munic&#237;pios</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Rio de Janeiro</td>
                <td align="center">190,4</td>
                <td align="center">&#160;</td>
                <td align="center">146,2</td>
                <td align="center">&#160;</td>
                <td align="center">95,3</td>
                <td align="center">&#160;</td>
                <td align="center">1</td>
              </tr>
              <tr>
                <td align="left">Cintur&#227;o Metropolitano</td>
                <td align="center">247,9</td>
                <td align="center">46,7</td>
                <td align="center">208,5</td>
                <td align="center">35,0</td>
                <td align="center">121,2</td>
                <td align="center">16,7</td>
                <td align="center">11</td>
              </tr>
              <tr>
                <td align="left">Centro-Sul</td>
                <td align="center">242,4</td>
                <td align="center">31,9</td>
                <td align="center">182,4</td>
                <td align="center">19,8</td>
                <td align="center">102,9</td>
                <td align="center">10,7</td>
                <td align="center">7</td>
              </tr>
              <tr>
                <td align="left">Serrana</td>
                <td align="center">264,5</td>
                <td align="center">58,8</td>
                <td align="center">181,2</td>
                <td align="center">28,4</td>
                <td align="center">97,8</td>
                <td align="center">14,7</td>
                <td align="center">13</td>
              </tr>
              <tr>
                <td align="left">Norte</td>
                <td align="center">261,4</td>
                <td align="center">49,8</td>
                <td align="center">191,7</td>
                <td align="center">35,8</td>
                <td align="center">113,0</td>
                <td align="center">18,3</td>
                <td align="center">4</td>
              </tr>
              <tr>
                <td align="left">Baixada Litor&#226;nea</td>
                <td align="center">248,1</td>
                <td align="center">36,4</td>
                <td align="center">171,0</td>
                <td align="center">18,6</td>
                <td align="center">105,7</td>
                <td align="center">17,2</td>
                <td align="center">5</td>
              </tr>
              <tr>
                <td align="left">Niter&#243;i</td>
                <td align="center">178,9</td>
                <td align="center">&#160;</td>
                <td align="center">146,4</td>
                <td align="center">&#160;</td>
                <td align="center">95,1</td>
                <td align="center">&#160;</td>
                <td align="center">1</td>
              </tr>
              <tr>
                <td align="left">Noroeste</td>
                <td align="center">263,7</td>
                <td align="center">36,8</td>
                <td align="center">186,8</td>
                <td align="center">30,0</td>
                <td align="center">100,0</td>
                <td align="center">10,6</td>
                <td align="center">7</td>
              </tr>
              <tr>
                <td align="left">M&#233;dio Paraiba</td>
                <td align="center">244,0</td>
                <td align="center">22,6</td>
                <td align="center">161,4</td>
                <td align="center">50,3</td>
                <td align="center">103,9</td>
                <td align="center">14,9</td>
                <td align="center">4</td>
              </tr>
              <tr>
                <td align="left">Baia da Ilha Grande</td>
                <td align="center">241,0</td>
                <td align="center">49,6</td>
                <td align="center">188,3</td>
                <td align="center">24,9</td>
                <td align="center">95,2</td>
                <td align="center">2,3</td>
                <td align="center">3</td>
              </tr>
              <tr>
                <td align="left">
                  <bold>Total</bold>
                </td>
                <td align="center">
                  <bold>253,5</bold>
                </td>
                <td align="center">
                  <bold>44,5</bold>
                </td>
                <td align="center">
                  <bold>186,8</bold>
                </td>
                <td align="center">
                  <bold>32,8</bold>
                </td>
                <td align="center">
                  <bold>105,9</bold>
                </td>
                <td align="center">
                  <bold>16,3</bold>
                </td>
                <td align="center">
                  <bold>56</bold>
                </td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN05">
              <label>*</label>
              <p>
                <italic>dp: desvio padr&#227;o das m&#233;dias dos munic&#237;pios da regi&#227;o.</italic>
              </p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <fig id="f06" fig-type="other">
          <label>Figura 3</label>
          <caption>
            <title>Taxas m&#233;dias de mortalidade por DIC, compensadas e ajustadas por sexo e
                     idade, por 100 mil habitantes nos munic&#237;pios do estado do Rio de Janeiro em
                     tr&#234;s per&#237;odos, de 1979 a 2010.</title>
          </caption>
          <graphic xlink:href="1678-4170-abc-104-05-0356-50019-gf03-pt.jpg"/></fig>
        <table-wrap id="t06">
          <label>Tabela 3</label>
          <caption>
            <title>Taxas m&#233;dias de mortalidade por DIC, compensadas e ajustadas por sexo e
                     idade, por 100 mil habitantes dos munic&#237;pios segundo as regi&#245;es de sa&#250;de do
                     Estado do Rio de Janeiro em tr&#234;s per&#237;odos, de 1979 a 2010</title>
          </caption>
          <table frame="hsides" rules="groups">
            <thead>
              <tr>
                <th align="left">Regi&#227;o de sa&#250;de</th>
                <th align="center">m&#233;dia (79-89)</th>
                <th align="center">dp<xref ref-type="table-fn" rid="TFN06">*</xref>
                           (79-89)</th>
                <th align="center">m&#233;dia (90-99)</th>
                <th align="center">dp<xref ref-type="table-fn" rid="TFN06">*</xref>
                           (90-99)</th>
                <th align="center">m&#233;dia (00-10)</th>
                <th align="center">dp<xref ref-type="table-fn" rid="TFN06">*</xref>
                           (00-10)</th>
                <th align="center">N de munic&#237;pios</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Rio de Janeiro</td>
                <td align="center">217,3</td>
                <td align="center">&#160;</td>
                <td align="center">160,0</td>
                <td align="center">&#160;</td>
                <td align="center">106,2</td>
                <td align="center">&#160;</td>
                <td align="center">1</td>
              </tr>
              <tr>
                <td align="left">Cintur&#227;o Metropolitano</td>
                <td align="center">186,0</td>
                <td align="center">56,2</td>
                <td align="center">151,7</td>
                <td align="center">38,5</td>
                <td align="center">102,9</td>
                <td align="center">12,5</td>
                <td align="center">11</td>
              </tr>
              <tr>
                <td align="left">Centro-Sul</td>
                <td align="center">199,0</td>
                <td align="center">41,2</td>
                <td align="center">164,1</td>
                <td align="center">31,7</td>
                <td align="center">112,9</td>
                <td align="center">13,1</td>
                <td align="center">7</td>
              </tr>
              <tr>
                <td align="left">Serrana</td>
                <td align="center">186,1</td>
                <td align="center">39,2</td>
                <td align="center">135,7</td>
                <td align="center">29,7</td>
                <td align="center">117,6</td>
                <td align="center">17,8</td>
                <td align="center">13</td>
              </tr>
              <tr>
                <td align="left">Norte</td>
                <td align="center">137,6</td>
                <td align="center">57,3</td>
                <td align="center">101,1</td>
                <td align="center">21,3</td>
                <td align="center">89,7</td>
                <td align="center">6,2</td>
                <td align="center">4</td>
              </tr>
              <tr>
                <td align="left">Baixada Litor&#226;nea</td>
                <td align="center">140,3</td>
                <td align="center">22,8</td>
                <td align="center">131,4</td>
                <td align="center">16,4</td>
                <td align="center">100,6</td>
                <td align="center">14,0</td>
                <td align="center">5</td>
              </tr>
              <tr>
                <td align="left">Niter&#243;i</td>
                <td align="center">212,4</td>
                <td align="center">&#160;</td>
                <td align="center">156,2</td>
                <td align="center">&#160;</td>
                <td align="center">95,3</td>
                <td align="center">&#160;</td>
                <td align="center">1</td>
              </tr>
              <tr>
                <td align="left">Noroeste</td>
                <td align="center">168,9</td>
                <td align="center">34,3</td>
                <td align="center">143,4</td>
                <td align="center">18,3</td>
                <td align="center">115,5</td>
                <td align="center">16,0</td>
                <td align="center">7</td>
              </tr>
              <tr>
                <td align="left">M&#233;dio Paraiba</td>
                <td align="center">203,6</td>
                <td align="center">25,3</td>
                <td align="center">183,3</td>
                <td align="center">43,1</td>
                <td align="center">132,9</td>
                <td align="center">18,3</td>
                <td align="center">4</td>
              </tr>
              <tr>
                <td align="left">Baia da Ilha Grande</td>
                <td align="center">162,4</td>
                <td align="center">21,7</td>
                <td align="center">159,2</td>
                <td align="center">33,0</td>
                <td align="center">94,8</td>
                <td align="center">14,5</td>
                <td align="center">3</td>
              </tr>
              <tr>
                <td align="left">
                  <bold>Total</bold>
                </td>
                <td align="center">
                  <bold>179,0</bold>
                </td>
                <td align="center">
                  <bold>44,1</bold>
                </td>
                <td align="center">
                  <bold>146,0</bold>
                </td>
                <td align="center">
                  <bold>33,9</bold>
                </td>
                <td align="center">
                  <bold>109,6</bold>
                </td>
                <td align="center">
                  <bold>17,5</bold>
                </td>
                <td align="center">
                  <bold>56</bold>
                </td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN06">
              <label>*</label>
              <p>
                <italic>dp: desvio padr&#227;o das m&#233;dias dos munic&#237;pios da regi&#227;o.</italic>
              </p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </sec>
      <sec sec-type="discussion">
        <title>Discuss&#227;o</title>
        <p>A partir dos dados apresentados nota-se que as taxas de mortalidade por doen&#231;as do
               aparelho circulat&#243;rio, doen&#231;as cerebrovasculares e doen&#231;as isqu&#234;micas do cora&#231;&#227;o
               apresentaram progressiva queda em todos os munic&#237;pios e regi&#245;es do estado do Rio de
               Janeiro, ao longo dos per&#237;odos analisados no estudo, seguindo uma tend&#234;ncia mundial
               de redu&#231;&#227;o da mortalidade cardiovascular nas &#250;ltimas d&#233;cadas<xref ref-type="bibr" rid="B18">18</xref><sup>,</sup><xref ref-type="bibr" rid="B19">19</xref>. As taxas
               m&#233;dias de mortalidade cardiovascular do ERJ ocupam valores intermedi&#225;rios quando
               comparadas com as de diversos pa&#237;ses. No &#250;ltimo per&#237;odo do estudo, de 2000 a 2010, a
               taxa m&#233;dia de mortalidade por DAC foi de 347,1; por DCBV, foi de 105,9; e por DIC.
               foi de 109,6 &#243;bitos por 100 mil habitantes. Podemos ent&#227;o compar&#225;-las com as taxas de
               mortalidade por essas causas em outras regi&#245;es do planeta em per&#237;odo semelhante. Na
               d&#233;cada de 2000, as menores taxas de mortalidade por DAC foram observadas no Jap&#227;o,
               com cerca de 100 &#243;bitos por 100 mil habitantes. Em rela&#231;&#227;o &#224;s DIC, no Jap&#227;o e Coreia
               ocorreram as menores taxas, com, respectivamente, 38 e 37 &#243;bitos por 100 mil
               habitantes; enquanto as menores taxas de mortalidade por DCBV s&#227;o as de Israel e
               Su&#237;&#231;a, com, respectivamente, 28 e 29 &#243;bitos por 100 mil habitantes. As maiores taxas
               de mortalidade por DIC e por DCBV s&#227;o relatadas para a Federa&#231;&#227;o Russa, de 524 e 313
               &#243;bitos por 100 mil habitantes, respectivamente. Os ind&#237;cios permitem supor que a taxa
               de mortalidade por DAC da Federa&#231;&#227;o Russa ultrapasse mil &#243;bitos por 100 mil
               habitantes. Taxas t&#227;o elevadas colocam a R&#250;ssia em primeiro lugar em mortalidade
               cardiovascular em uma classifica&#231;&#227;o com 35 pa&#237;ses, bem &#224; frente do segundo colocado,
               a Eslov&#225;quia, que apresentou, respectivamente, taxas de mortalidade por DIC e DCBV de
               324 e 112 &#243;bitos por 100 mil habitantes. Se posicionarmos o ERJ nessa classifica&#231;&#227;o,
               ele ocuparia a quarta coloca&#231;&#227;o em mortalidade por DCBV, atr&#225;s apenas de R&#250;ssia,
               Eslov&#225;quia e Hungria. Em rela&#231;&#227;o &#224; mortalidade por DIC, o ERJ estaria na 18&#170;
               coloca&#231;&#227;o com menor mortalidade do que pa&#237;ses como Estados Unidos, Reino Unido e
               Canad&#225;, por&#233;m acima de pa&#237;ses latino-americanos como Chile e M&#233;xico<xref ref-type="bibr" rid="B20">20</xref>.</p>
        <p>Comportamento semelhante de redu&#231;&#227;o das taxas de mortalidade por DAC, DIC e DCBV nos
               agregados municipais do ERJ tamb&#233;m foi observado no Brasil na Regi&#227;o Metropolitana de
               S&#227;o Paulo<xref ref-type="bibr" rid="B21">21</xref>, por&#233;m com an&#225;lise em um per&#237;odo
               mais curto, de 1990 a 2009. O padr&#227;o de redu&#231;&#227;o da mortalidade cardiovascular foi o
               mesmo do ERJ, onde houve queda da mortalidade pelas DIC, por&#233;m a redu&#231;&#227;o mais
               acentuada ocorreu nas DCBV. Todas as regi&#245;es do ERJ apresentaram queda nas taxas de
               mortalidade por DIC e DCBV. Entretanto, na compara&#231;&#227;o entre DCBV e DIC, observam-se
               comportamentos variados entre as regi&#245;es. No Cintur&#227;o Metropolitano, no Norte e Ba&#237;a
               da Ilha Grande, o predom&#237;nio da DCBV se manteve do per&#237;odo mais remoto ao mais
               recente, enquanto o mesmo aconteceu com o munic&#237;pio do Rio de Janeiro, por&#233;m em
               rela&#231;&#227;o &#224; DIC. J&#225; as regi&#245;es Centro-Sul, Serrana, Noroeste e M&#233;dio Para&#237;ba
               transitaram de taxas mais elevadas de DCBV do que de DIC no per&#237;odo 1979 1989, para
               taxas mais elevadas de DIC do que de DCBV no per&#237;odo 2000-2010. Na Ba&#237;a da Ilha
               Grande a maior taxa no per&#237;odo de 1979-1989 era por DCBV, enquanto no &#250;ltimo per&#237;odo
               as taxas de DCBV e DIC se assemelharam (<xref ref-type="table" rid="t05">Tabelas
                  2</xref> e <xref ref-type="table" rid="t06">3</xref>). </p>
        <p>Niter&#243;i, cuja taxa de mortalidade por DIC era nitidamente superior &#224; de DCBV no
               per&#237;odo mais remoto, passou a ter taxas semelhantes de DIC e DCBV no &#250;ltimo per&#237;odo.
               &#201; preciso salientar que seria esperado um decl&#237;nio menos not&#225;vel da taxa de
               mortalidade por DCBV em Niter&#243;i, j&#225; que esse foi o munic&#237;pio com a menor taxa de
               mortalidade por essa causa no per&#237;odo inicial do estudo. Se observarmos as taxas de
               redu&#231;&#227;o relativa para o per&#237;odo total ((1979-1989)-(2000-2010)/(1979-1989)) para as
               DAC, vemos que Niter&#243;i teve a maior redu&#231;&#227;o relativa (53%), e a regi&#227;odo m&#233;dio
               Para&#237;ba foi a de menor redu&#231;&#227;o (44%).Omunic&#237;pio de Niter&#243;i, em nosso estudo, foi
               separado da Regi&#227;o Metropolitana por apresentar padr&#227;o socioecon&#244;mico bastante
               diferente dos outros munic&#237;pios dessa regi&#227;o. Niter&#243;i possui o terceiro maior &#237;ndice
               de desenvolvimento humano do Brasil e o maior do ERJ<xref ref-type="bibr" rid="B06">6</xref>. Al&#233;m disso, de acordo com pesquisa da Funda&#231;&#227;o Getulio Vargas (FGV),
               Niter&#243;i concentra a maior quantidade de pessoas da classe socioecon&#244;mica mais elevada
               (30,7%) do Brasil, com base nos dados do Censo Demogr&#225;fico de 2010<xref ref-type="bibr" rid="B22">22</xref>. J&#225; os munic&#237;pios do M&#233;dio Para&#237;ba s&#227;o os que
               tiveram uma industrializa&#231;&#227;o precoce pela implanta&#231;&#227;o da primeira usina de a&#231;o no
               Brasil, em Volta Redonda. A ind&#250;stria do a&#231;o &#233; reconhecidamente uma das que causam
               mais polui&#231;&#227;o ambiental e oferecem condi&#231;&#245;es insalubres ao trabalhador.</p>
        <p>Al&#233;m da progressiva queda das taxas de mortalidade nos per&#237;odos estudados, nota-se
               que ocorreu homogeneiza&#231;&#227;o das taxas de mortalidade nos agregados municipais pelos
               tr&#234;s grupos de causas estudadas, o que fica evidente nos mapas que mostram o per&#237;odo
               de 2000 a 2010.Essa an&#225;lise pode ser resumida em dois aspectos. A mortalidade por
               doen&#231;as do aparelho circulat&#243;rio apresentou queda nas &#250;ltimas tr&#234;s d&#233;cadas no estado
               do Rio de Janeiro, esse fen&#244;meno n&#227;o foi isolado, reproduzindo-se em outros pa&#237;ses e
               em outros estados brasileiros. Essa redu&#231;&#227;o n&#227;o foi uniforme entre os munic&#237;pios, com
               redu&#231;&#227;o relativa global (entre o primeiro e o &#250;ltimo per&#237;odosestudados) nas DAC, para
               os munic&#237;pios de Niter&#243;i (53%), da Regi&#227;o Centro-Sul (49%) e Rio de Janeiro (49%), e
               redu&#231;&#245;es menores no M&#233;dio Para&#237;ba (44%), Baia de Ilha Grande (46%) e Regi&#227;o Noroeste
               (46%). Essa redu&#231;&#227;o assim&#233;trica ou diversa das taxas de mortalidade n&#227;o pode ser
               explicada pelo acesso aos procedimentos de alta tecnologia: cirurgia de
               revasculariza&#231;&#227;o do mioc&#225;rdio e angioplastia, pela m&#225; performance<xref ref-type="bibr" rid="B23">23</xref><sup>-</sup><xref ref-type="bibr" rid="B25">25</xref>dessas e baixa abrang&#234;ncia no Brasil, nem tampouco pelo melhor controle
               dos fatores de risco cl&#225;ssicos cardiovasculares<xref ref-type="bibr" rid="B26">26</xref><sup>-</sup><xref ref-type="bibr" rid="B34">34</xref>. </p>
        <p>Estas constata&#231;&#245;es tornam necess&#225;ria a busca de explica&#231;&#245;es para a queda da
               mortalidade cardiovascular, que podem estar relacionadas com melhorias nas condi&#231;&#245;es
               socioecon&#244;micos da popula&#231;&#227;o ou condi&#231;&#245;es ambientais. Em todo o decorrer do s&#233;culo
               XX, principalmente a partir da d&#233;cada de 1950, tivemos no Brasil, inclusive no ERJ,
               um per&#237;odo de avan&#231;os que se traduziram em melhoras em indicadores socioecon&#244;micos,
               embora ainda com desigualdades sociais que s&#243; nos &#250;ltimos anos come&#231;aram a se reduzir
               e que precederam a queda da mortalidade por DAC<xref ref-type="bibr" rid="B35">35</xref>. Em todo o mundo, as desigualdades sociais, mesmo nos pa&#237;ses ditos
               desenvolvidos, est&#227;o claramente associadas a diversas doen&#231;as, incluindo as
               cardiovasculares. Estima-se que o custo da desigualdade social chegue a atingir 39
               bilh&#245;es de libras/ano no Reino Unido devido a redu&#231;&#227;o da expectativa de vida,
               assassinatos, piora da sa&#250;de mental, entre outros problemas<xref ref-type="bibr" rid="B36">36</xref>. Em estudo recente, no munic&#237;pio do Rio de Janeiro,
               demonstramos que nas 33 regi&#245;es administrativas do munic&#237;pio do Rio de Janeiro havia
               uma rela&#231;&#227;o linear inversa entre a mortalidade por doen&#231;a cerebrovascular e o &#205;ndice
               de Desenvolvimento Humano (IDH). Para cada 0,05 de redu&#231;&#227;o do IDH havia um aumento de
               65% (IC 1,63 a 1,66) do risco de morte cerebrovascular. O risco relativo de morte por
               doen&#231;a cerebrovascular era 10 vezes maior na regi&#227;o com o menor IDH (Campo Grande e
               Santa Cruz: IDH = 0,74) do que na regi&#227;o com o maior IDH (Gavea: IDH = 0,97). Esta
               mortalidade maior na regi&#227;o de IDH menor ocorria em m&#233;dia de idade 10 anos menor<xref ref-type="bibr" rid="B37">37</xref>.</p>
        <p>As avalia&#231;&#245;es feitas neste artigo dependem da qualidade das informa&#231;&#245;es registradas
               nas Declara&#231;&#245;es de &#211;bito. Portanto, essa &#233; uma limita&#231;&#227;o para as interpreta&#231;&#245;es
               feitas neste artigo. Essa limita&#231;&#227;o refor&#231;a a aten&#231;&#227;o que dever ser dada &#224; melhoria
               constante das informa&#231;&#245;es prestadas pelos assistentes ao &#243;bito, pelos m&#233;dicos e
               demais profissionais relacionados. Essa melhoria envolve a educa&#231;&#227;o continuada dos
               profissionais de sa&#250;de e a oferta de condi&#231;&#245;es de trabalho adequadas por parte de
               institui&#231;&#245;es p&#250;blicas e privadas. Outras limita&#231;&#245;es se referem &#224; abrang&#234;ncia das
               informa&#231;&#245;es e aos m&#233;todos de estima&#231;&#227;o de popula&#231;&#227;o e &#243;bito segundo as causas. Nenhum
               dos m&#233;todos utilizados assegura certeza, por&#233;m s&#227;o simples, l&#243;gicos e de f&#225;cil
               reprodu&#231;&#227;o.</p>
        <p>S&#227;o necess&#225;rios estudos futuros que relacionem a mortalidade por DAC e seus
               componentes com indicadores socioecon&#244;micos e de desigualdade social, bem como com
               polui&#231;&#227;o ambiental, em agregados municipais, que incluem variabilidade de indicadores
               e mortalidade. Essas vari&#225;veis socioecon&#244;micas-ambientais parecem ter um impacto
               muito maior na mortalidade cardiovascular do que os fatores de risco cl&#225;ssicos. </p>
      </sec>
    </body>
    <back>
      <fn-group>
        <fn fn-type="supported-by">
          <p>
            <bold>Fontes de financiamento</bold>
          </p>
          <p>O presente estudo n&#227;o teve fontes de financiamento externas.</p>
        </fn>
        <fn fn-type="other">
          <p>
            <bold>Vincula&#231;&#227;o acad&#234;mica</bold>
          </p>
          <p>Este artigo &#233; parte de tese de Doutorado de Gabriel Porto Soares pela Universidade
                  Federal do Rio de Janeiro.</p>
        </fn>
      </fn-group>
    </back>
  </sub-article>
</article>
