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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">ijcs</journal-id>
      <journal-title-group>
        <journal-title>International Journal of Cardiovascular Sciences</journal-title>
        <abbrev-journal-title abbrev-type="publisher">Int. J. Cardiovasc. Sci.</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">2359-4802</issn>
      <issn pub-type="epub">2359-5647</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">BLjmZ8JSv3b6rbTyQpV3rBP</article-id>
      <article-id pub-id-type="publisher-id" specific-use="scielo-v2">S2359-56472018000300250</article-id>
      <article-id pub-id-type="doi">10.5935/2359-4802.20180017</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Original Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Spatial Analysis and Mortality Trends Associated with Hypertensive Diseases in the States and Regions of Brazil from 2010 to 2014</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Almeida-Santos</surname>
            <given-names>Marcos Antonio</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
          <xref ref-type="corresp" rid="c1"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Prado</surname>
            <given-names>Beatriz Santana</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Santos</surname>
            <given-names>Deyse Mirelle Souza</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
        <aff id="aff1">
          <institution content-type="orgname">Universidade Tiradentes</institution>
          <institution content-type="orgdiv1">Programa de P&#243;s-gradua&#231;&#227;o em Sa&#250;de e Ambiente</institution>
          <addr-line>
            <city>Aracaju</city>
            <state>SE</state>
          </addr-line>
          <country country="BR">Brazil</country>
          <institution content-type="original">Programa de P&#243;s-gradua&#231;&#227;o em Sa&#250;de e Ambiente da Universidade Tiradentes, Aracaju, SE - Brazil</institution>
          <institution content-type="normalized">Universidade Tiradentes</institution>
        </aff>
      </contrib-group>
      <author-notes>
        <corresp id="c1"><bold>Mailing Address: Marcos Antonio Almeida-Santos.</bold> Avenida Gon&#231;alo Prado Rollemberg, 211, sala: 210. Postal Code: 49010-410, S&#227;o Jos&#233;, Aracaju, SE - Brazil. E-mail: <email>maasantos@cardiol.br</email>, <email>marcosalmeida2010@yahoo.com.br</email>
				</corresp>
        <fn fn-type="con">
          <p>
            <bold>Author contributions</bold>
          </p>
          <p>Conception and design of the research: Santos MAA. Acquisition of data: Santos MAA. Analysis and interpretation of the data: Santos MAA. Statistical analysis: Santos MAA. Writing of the manuscript: Santos MAA, Prado BS, Santos DMS. Critical revision of the manuscript for intellectual content: Santos MAA, Prado BS, Santos DMS.</p>
        </fn>
        <fn fn-type="conflict">
          <p>
            <bold>Potential Conflict of Interest</bold>
          </p>
          <p>No potential conflict of interest relevant to this article was reported.</p>
        </fn>
      </author-notes>
      <pub-date pub-type="epub-ppub">
        <season>May-Jun</season>
        <year>2018</year>
      </pub-date>
      <volume>31</volume>
      <issue>3</issue>
      <fpage>250</fpage>
      <lpage>257</lpage>
      <history>
        <date date-type="received">
          <day>09</day>
          <month>06</month>
          <year>2017</year>
        </date>
        <date date-type="rev-recd">
          <day>20</day>
          <month>10</month>
          <year>2017</year>
        </date>
        <date date-type="accepted">
          <day>19</day>
          <month>12</month>
          <year>2017</year>
        </date>
      </history>
      <permissions>
        <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/" xml:lang="en">
          <license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
        </license>
      </permissions>
      <abstract>
        <title>Abstract</title>
        <sec>
          <title>Background:</title>
          <p>Systemic Arterial Hypertension (SAH) represents the most relevant worsening factor and one of the major risk factors for cardiovascular diseases.</p>
        </sec>
        <sec>
          <title>Objectives:</title>
          <p>To analyze trends in the mortality rate associated with hypertensive diseases in Brazil from 2010 to 2014, for states as well as regions.</p>
        </sec>
        <sec>
          <title>Methods:</title>
          <p>An epidemiological study was performed from aggregate data obtained in populational strata. Cartographic data of the Brazilian territory in "shapefile" were provided by IBGE. Records of mortality associated with arterial hypertension were obtained in DATASUS, through notifications filtered by category I.10 of the International Classification of Diseases (ICD-10). The criterion of statistical significance was a two-tailed p-value &lt; 0.05.</p>
        </sec>
        <sec>
          <title>Results:</title>
          <p>The increase in age was progressively associated with an increase in the mean number of deaths related to hypertensive diseases between the years 2010 and 2014. In the age groups between 50-59 years, 60-69 years, 70-79 years and 80 or more years, the mean and standard deviation for the mortality rate were, respectively: 15.11% (35.35); 24.14% (55.34); 35.07% (81.03) and 57.87% (139.08). The overall mortality rate per 10,000 inhabitants varied between the regions: north (1.25); northeast (2.69); center-west (2.06); southeast (2.48) and south (2.04).</p>
        </sec>
        <sec>
          <title>Conclusions:</title>
          <p>The mortality rate associated with hypertensive diseases was higher in the southeastern and northeastern states of Brazil, and remained stable between 2010 and 2014. Increased age and brown color were predictors of higher mortality.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="en">
        <title>Keywords:</title>
        <kwd>Cardiovascular Diseases / mortality</kwd>
        <kwd>Hypertension / epidemiology</kwd>
        <kwd>Hypertension / etiology</kwd>
        <kwd>Ethnicity and Health</kwd>
        <kwd>Stroke</kwd>
        <kwd>Epidemiologic Studies</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec sec-type="intro">
      <title>Introduction</title>
      <p>Cerebrovascular diseases have been classified among those with the greatest impact in terms of morbimortality.<xref ref-type="bibr" rid="B1">1</xref> Among the major cardiovascular risk factors, systemic arterial hypertension (SAH) represents the most relevant worsening factor, requiring health actions in order to minimize the factors of impact that are determinant for the populations' health.<xref ref-type="bibr" rid="B2">2</xref>
			</p>
      <p>The global prevalence of arterial hypertension was 22%, in 2014, in adults aged 18 years and over.<xref ref-type="bibr" rid="B3">3</xref> SAH is characterized by increased blood pressure levels (&#8805; 140 and/or 90 mmHg), in which the clinical condition can be caused by several reasons and may be worsened by other risk factors, such as dyslipidemia, abdominal obesity, glucose intolerance, diabetes mellitus (DM), in addition to other modifiable factors, socioeconomic determinants and inadequate access to health care.<xref ref-type="bibr" rid="B3">3</xref><sup>,</sup><xref ref-type="bibr" rid="B4">4</xref>
			</p>
      <p>Several studies point to the influence of ethnic aspects in the emergence of hypertensive diseases.<xref ref-type="bibr" rid="B5">5</xref> Often it is difficult to dissociate the role represented by an ethnic group of the socioeconomic factors simultaneously active.<xref ref-type="bibr" rid="B6">6</xref> In Brazil, cerebrovascular mortality rates were higher in black people, followed by brown and white people.<xref ref-type="bibr" rid="B7">7</xref>
			</p>
      <p>About 32.6% of adults and more than 60% of elderly people suffer from high blood pressure in Brazil, which contributes direct or indirectly to 50% of deaths due to cardiovascular diseases (CVD).<xref ref-type="bibr" rid="B4">4</xref> In low- and medium-income countries, where treatment and control are lower than in developed countries, it is estimated that the prevalence of HBP-related diseases is of about 80%.<xref ref-type="bibr" rid="B8">8</xref> The impact of this illness reflects in high costs for the Brazilian Unified National Health System (SUS), with an annual treatment cost of approximately US$ 398.9 million, that is, about 1.43% of overall healthcare expenditures.<xref ref-type="bibr" rid="B9">9</xref>
			</p>
      <p>The objective of this research is to estimate the impact of arterial hypertension in the Brazilian territory in a period of five years. For such purpose, we analyzed trends in mortality rates associated with hypertensive diseases in Brazil, between 2010 and 2014, stratified according to skin color and age group, both for states and regions.</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <p>An epidemiological study was performed from aggregate data obtained in population strata and combined with a spatial analysis.</p>
      <p>Data regarding the organization of the Brazilian territory, including the coordinates and the estimated population for the years studied, were taken from the Brazilian Institute of Geography and Statistics (IBGE) website in shapefile format.<xref ref-type="bibr" rid="B10">10</xref><sup>,</sup><xref ref-type="bibr" rid="B11">11</xref>
			</p>
      <p>Epidemiological information regarding mortality due to arterial hypertension was obtained from the Ministry of Health database, DATASUS.<xref ref-type="bibr" rid="B12">12</xref> These data refer to notifications from the Mortality Data System (SIM).<xref ref-type="bibr" rid="B13">13</xref> Deaths were filtered by category I.10 of the International Classification of Diseases (ICD-10). Then, the aggregate data were obtained per year, state, sex, age and skin color.</p>
      <p>The selection of the analysis period, between 2010 and 2014, occurred due to the following reasons. First, because we consider that more recent analysis provides greater reliability in data collection, due to progressive improvements in the process of computerization with technological advances. Second, because it potentially portrays the transition scenario resulting from the introduction of losartan, an effective antihypertensive drug, which has been distributed free of charge by the "Popular Pharmacy Program" since 2010, and became in 2014 the most demanded medication in units of the Unified Health System (SUS), including in the countryside of Brazil.<xref ref-type="bibr" rid="B14">14</xref><sup>,</sup><xref ref-type="bibr" rid="B15">15</xref>
			</p>
      <p>However, one must consider that the program's effect may occur unevenly across the regions, which would potentially influence the analysis. Finally, the end of the period under consideration, the year of 2014, arose from the fact that it is the most recent date available in DATASUS to obtain vital statistics all over the Brazilian territory.</p>
      <p>The selected variables were year, sex, age, skin color, state, region and number of deaths. Since it is a chronic illness, the selected age groups used to calculate the rate of mortality associated with arterial hypertension were as follows: 50-59 years; 60-69 years; 70-79 years; 80 or more years. This calculation was computed for the twenty-six Brazilian states and the Federal District. The variable "skin color" basically portrays the skin color and ethnic traits, based on the death certificate data, and may be classified as "white", "yellow", "brown", "black", "indigenous" or "ignored".</p>
      <sec>
        <title>Statistical analysis</title>
        <p>The categorical variables were presented as absolute number and percentage. The numerical variables were presented as average and standard error. Regression models (Poisson and negative binomial) for analyzing countable data have been used in longitudinal studies to estimate future mortality rates. Due to overdispersion, negative binomial regression was preferred. The estimate of the "effect size" was adjusted to sex, age groups, skin color, country region and year, and presented in the form of incidence rate ratio (IRR) and confidence intervals at 95%.</p>
        <p>In order to minimize distortions resulting from spatial and temporal differences between the populations, random-effect models included annual population estimates for each state as an "exposition" factor, that is, the coefficient was restricted, producing an IRR equal to 1, with standard error (virtually) zero, adjusting the calculation for the other coefficients. In order to select the model that provides the best predictive adequacy, the Akaike information criterion (AIC) was used. For the spatial analysis, the "spmap" command was used to draw choropleth maps containing the Brazilian states and the Federal District, and representing the distribution of mortality rates associated with arterial hypertension in quintiles. Statistical significance was considered as a two-tailed p value &lt; 0.05. The statistical calculations and the spatial analysis were conducted in Stata, version 14.2 (College Station, Texas, USA).</p>
      </sec>
      <sec>
        <title>Ethnical aspects</title>
        <p>Since these were public data, and there were no elements of identification of the individuals studied, there was no need to use an informed consent term.</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Results</title>
      <p>The progressive increase in age was associated with an increase in the mean number of deaths related to hypertensive diseases between the years 2010 and 2014. In the age groups between 50-59 years, 60-69 years, 70-79 years and 80 or more years, the mean and standard deviation for the mortality rate were, respectively: 15.11% (35.35); 24.14% (55.34); 35.07% (81.03) and 57.87% (139.08).</p>
      <p>In the graphic representation of the binomial regression model extended to longitudinal data (<xref ref-type="fig" rid="f1">Figure 1</xref>), adjusted to age, higher incidence rate ratios can be observed in the southeast and northeast regions, compared to the south, north and center-west regions.</p>
      <p>
        <fig id="f1">
          <label>Figure 1</label>
          <caption>
            <title>Graphical representation of the binomial regression model extended for longitudinal data, with incidence rate ratio adjusted to age group and in accordance with Brazilian regions, in the period from 2010 to 2014.</title>
          </caption>
          <graphic xlink:href="2359-5647-ijcs-31-03-0250-80017-gf01.jpg"/></fig>
      </p>
      <p>According to IBGE's population estimates for each year and state,<xref ref-type="bibr" rid="B11">11</xref> the global mortality rate related to hypertensive diseases was calculated per 10,000 inhabitants, between 2010 and 2014, which varied between regions: north (1.25); northeast (2.69); center-west (2.06); southeast (2.48) and south (2.04). <xref ref-type="table" rid="t1">Table 1</xref> shows the numbers per year and region.</p>
      <table-wrap id="t1">
        <label>Table 1</label>
        <caption>
          <title>Annual mortality rate associated with hypertensive diseases in Brazil, adjusted to 10,000 inhabitantes (average and standard error), between 2010 and 2014</title>
        </caption>
        <table frame="hsides" rules="groups">
          <colgroup>
            <col width="9%"/>
            <col width="9%"/>
            <col width="9%"/>
            <col width="9%"/>
            <col width="9%"/>
            <col width="9%"/>
            <col width="9%"/>
            <col width="9%"/>
            <col width="9%"/>
            <col width="9%"/>
            <col width="9%"/>
          </colgroup>
          <thead>
            <tr>
              <th align="left" rowspan="2" style="background-color:#C5C6C8">Year</th>
              <th align="center" colspan="2" style="background-color:#C5C6C8">North</th>
              <th align="center" colspan="2" style="background-color:#C5C6C8">Northeast</th>
              <th align="center" colspan="2" style="background-color:#C5C6C8">Central-West</th>
              <th align="center" colspan="2" style="background-color:#C5C6C8">Southeast</th>
              <th align="center" colspan="2" style="background-color:#C5C6C8">South</th>
            </tr>
            <tr>
              <th align="center" style="background-color:#C5C6C8">Deaths</th>
              <th align="center" style="background-color:#C5C6C8">SE</th>
              <th align="center" style="background-color:#C5C6C8">Deaths</th>
              <th align="center" style="background-color:#C5C6C8">SE</th>
              <th align="center" style="background-color:#C5C6C8">Deaths</th>
              <th align="center" style="background-color:#C5C6C8">SE</th>
              <th align="center" style="background-color:#C5C6C8">Deaths</th>
              <th align="center" style="background-color:#C5C6C8">SE</th>
              <th align="center" style="background-color:#C5C6C8">Deaths</th>
              <th align="center" style="background-color:#C5C6C8">SE</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td align="left">2010</td>
              <td align="center">1.12</td>
              <td align="center">0.02</td>
              <td align="center">2.67</td>
              <td align="center">0.02</td>
              <td align="center">2.02</td>
              <td align="center">0.04</td>
              <td align="center">2.52</td>
              <td align="center">0.05</td>
              <td align="center">1.96</td>
              <td align="center">0.02</td>
            </tr>
            <tr>
              <td align="left">2011</td>
              <td align="center">1.38</td>
              <td align="center">0.02</td>
              <td align="center">2.77</td>
              <td align="center">0.02</td>
              <td align="center">2.11</td>
              <td align="center">0.05</td>
              <td align="center">2.57</td>
              <td align="center">0.05</td>
              <td align="center">2.12</td>
              <td align="center">0.02</td>
            </tr>
            <tr>
              <td align="left">2012</td>
              <td align="center">1.31</td>
              <td align="center">0.02</td>
              <td align="center">2.02</td>
              <td align="center">0.02</td>
              <td align="center">2.09</td>
              <td align="center">0.04</td>
              <td align="center">2.52</td>
              <td align="center">0.04</td>
              <td align="center">2.02</td>
              <td align="center">0.02</td>
            </tr>
            <tr>
              <td align="left">2013</td>
              <td align="center">1.17</td>
              <td align="center">0.03</td>
              <td align="center">2.77</td>
              <td align="center">0.03</td>
              <td align="center">2.09</td>
              <td align="center">0.04</td>
              <td align="center">2.41</td>
              <td align="center">0.04</td>
              <td align="center">2.06</td>
              <td align="center">0.02</td>
            </tr>
            <tr>
              <td align="left">2014</td>
              <td align="center">1.26</td>
              <td align="center">0.01</td>
              <td align="center">2.56</td>
              <td align="center">0.02</td>
              <td align="center">2.03</td>
              <td align="center">0.04</td>
              <td align="center">2.39</td>
              <td align="center">0.03</td>
              <td align="center">2.06</td>
              <td align="center">0.02</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN1">
            <p>SE: standard error.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>It is possible to observe clearly, on the map of Brazil, the regions with the highest mortality rates related to hypertensive diseases in the year of 2014, as well as the regions with the lowest rates (<xref ref-type="fig" rid="f2">Figure 2</xref>).</p>
      <p>
        <fig id="f2">
          <label>Figure 2</label>
          <caption>
            <title>Choropleth map of Brazil, referring to deaths per 10,000 inhabitants associated with hypertensive disease, in the year 2014.</title>
          </caption>
          <graphic xlink:href="2359-5647-ijcs-31-03-0250-80017-gf02.jpg"/></fig>
      </p>
      <p>The analysis per state showed that Rio de Janeiro had the highest mean, with 3.66% of deaths associated with hypertensive diseases in the year of 2010, progressively decreasing until the year 2014, with a mean of 3.02% in that same year. On the other hand, in the years 2011, 2012, 2013 and 2014, the state of Piau&#237; had the highest death average compared to the other states, with 3.80%, 3.58%, 3.87% and 3.61%, respectively (<xref ref-type="table" rid="t2">Table 2</xref>). The highest death rates occurred in the southeastern and northeastern regions of Brazil.</p>
      <table-wrap id="t2">
        <label>Table 2</label>
        <caption>
          <title>Average of deaths related to hypertensive diseases per 10,000 inhabitants in each Brazilian state, between 2010 and 2014</title>
        </caption>
        <table frame="hsides" rules="groups">
          <colgroup>
            <col width="16%"/>
            <col width="16%"/>
            <col width="16%"/>
            <col width="16%"/>
            <col width="16%"/>
            <col width="16%"/>
          </colgroup>
          <thead>
            <tr>
              <th align="left" style="background-color:#C5C6C8">State</th>
              <th align="center" style="background-color:#C5C6C8">2010</th>
              <th align="center" style="background-color:#C5C6C8">2011</th>
              <th align="center" style="background-color:#C5C6C8">2012</th>
              <th align="center" style="background-color:#C5C6C8">2013</th>
              <th align="center" style="background-color:#C5C6C8">2014</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td align="left">Acre</td>
              <td align="center">1.20</td>
              <td align="center">1.63</td>
              <td align="center">1.62</td>
              <td align="center">1.39</td>
              <td align="center">1.39</td>
            </tr>
            <tr>
              <td align="left">Alagoas</td>
              <td align="center">2.64</td>
              <td align="center">2.81</td>
              <td align="center">2.87</td>
              <td align="center">2.98</td>
              <td align="center">2.64</td>
            </tr>
            <tr>
              <td align="left">Amap&#225;</td>
              <td align="center">0.61</td>
              <td align="center">1.02</td>
              <td align="center">0.80</td>
              <td align="center">0.71</td>
              <td align="center">0.95</td>
            </tr>
            <tr>
              <td align="left">Amazonas</td>
              <td align="center">1.00</td>
              <td align="center">0.98</td>
              <td align="center">0.99</td>
              <td align="center">1.06</td>
              <td align="center">1.02</td>
            </tr>
            <tr>
              <td align="left">Bahia</td>
              <td align="center">2.27</td>
              <td align="center">2.24</td>
              <td align="center">2.33</td>
              <td align="center">2.35</td>
              <td align="center">2.33</td>
            </tr>
            <tr>
              <td align="left">Cear&#225;</td>
              <td align="center">2.60</td>
              <td align="center">2.85</td>
              <td align="center">2.48</td>
              <td align="center">2.66</td>
              <td align="center">2.49</td>
            </tr>
            <tr>
              <td align="left">Distrito Federal</td>
              <td align="center">1.13</td>
              <td align="center">1.30</td>
              <td align="center">0.99</td>
              <td align="center">1.10</td>
              <td align="center">1.08</td>
            </tr>
            <tr>
              <td align="left">Esp&#237;rito Santo</td>
              <td align="center">2.32</td>
              <td align="center">2.62</td>
              <td align="center">2.64</td>
              <td align="center">2.42</td>
              <td align="center">2.55</td>
            </tr>
            <tr>
              <td align="left">Goi&#225;s</td>
              <td align="center">1.43</td>
              <td align="center">1.52</td>
              <td align="center">1.77</td>
              <td align="center">1.69</td>
              <td align="center">1.81</td>
            </tr>
            <tr>
              <td align="left">Maranh&#227;o</td>
              <td align="center">2.00</td>
              <td align="center">2.13</td>
              <td align="center">1.97</td>
              <td align="center">2.11</td>
              <td align="center">2.07</td>
            </tr>
            <tr>
              <td align="left">Mato Grosso</td>
              <td align="center">2.22</td>
              <td align="center">2.13</td>
              <td align="center">1.97</td>
              <td align="center">2.11</td>
              <td align="center">2.07</td>
            </tr>
            <tr>
              <td align="left">Mato Grosso do Sul</td>
              <td align="center">2.39</td>
              <td align="center">2.68</td>
              <td align="center">2.74</td>
              <td align="center">2.83</td>
              <td align="center">2.52</td>
            </tr>
            <tr>
              <td align="left">Minas Gerais</td>
              <td align="center">2.26</td>
              <td align="center">2.36</td>
              <td align="center">2.40</td>
              <td align="center">2.29</td>
              <td align="center">2.29</td>
            </tr>
            <tr>
              <td align="left">Par&#225;</td>
              <td align="center">1.05</td>
              <td align="center">1.21</td>
              <td align="center">1.27</td>
              <td align="center">1.27</td>
              <td align="center">1.30</td>
            </tr>
            <tr>
              <td align="left">Para&#237;ba</td>
              <td align="center">3.10</td>
              <td align="center">3.26</td>
              <td align="center">3.26</td>
              <td align="center">3.23</td>
              <td align="center">2.88</td>
            </tr>
            <tr>
              <td align="left">Paran&#225;</td>
              <td align="center">2.26</td>
              <td align="center">2.47</td>
              <td align="center">2.26</td>
              <td align="center">2.35</td>
              <td align="center">2.36</td>
            </tr>
            <tr>
              <td align="left">Pernambuco</td>
              <td align="center">2.41</td>
              <td align="center">2.44</td>
              <td align="center">2.29</td>
              <td align="center">2.18</td>
              <td align="center">2.13</td>
            </tr>
            <tr>
              <td align="left">Piau&#237;</td>
              <td align="center">3.51</td>
              <td align="center">3.80</td>
              <td align="center">3.58</td>
              <td align="center">3.87</td>
              <td align="center">3.61</td>
            </tr>
            <tr>
              <td align="left">Rio de Janeiro</td>
              <td align="center">3.66</td>
              <td align="center">3.52</td>
              <td align="center">3.37</td>
              <td align="center">3.23</td>
              <td align="center">3.02</td>
            </tr>
            <tr>
              <td align="left">Rio Grande do Norte</td>
              <td align="center">2.22</td>
              <td align="center">2.54</td>
              <td align="center">2.34</td>
              <td align="center">2.56</td>
              <td align="center">2.44</td>
            </tr>
            <tr>
              <td align="left">Rio Grande do Sul</td>
              <td align="center">1.80</td>
              <td align="center">1.96</td>
              <td align="center">1.99</td>
              <td align="center">1.93</td>
              <td align="center">1.91</td>
            </tr>
            <tr>
              <td align="left">Roraima</td>
              <td align="center">1.07</td>
              <td align="center">1.65</td>
              <td align="center">1.62</td>
              <td align="center">1.54</td>
              <td align="center">1.29</td>
            </tr>
            <tr>
              <td align="left">Santa Catarina</td>
              <td align="center">1.81</td>
              <td align="center">1.92</td>
              <td align="center">1.81</td>
              <td align="center">1.89</td>
              <td align="center">1.92</td>
            </tr>
            <tr>
              <td align="left">S&#227;o Paulo</td>
              <td align="center">1.82</td>
              <td align="center">1.79</td>
              <td align="center">1.69</td>
              <td align="center">1.70</td>
              <td align="center">1.69</td>
            </tr>
            <tr>
              <td align="left">Sergipe</td>
              <td align="center">3.31</td>
              <td align="center">2.88</td>
              <td align="center">3.12</td>
              <td align="center">3.02</td>
              <td align="center">2.49</td>
            </tr>
            <tr>
              <td align="left">Tocantins</td>
              <td align="center">2.91</td>
              <td align="center">3.01</td>
              <td align="center">2.74</td>
              <td align="center">2.72</td>
              <td align="center">2.84</td>
            </tr>
            <tr>
              <td align="left">Rond&#244;nia</td>
              <td align="center">1.79</td>
              <td align="center">1.78</td>
              <td align="center">1.71</td>
              <td align="center">1.67</td>
              <td align="center">1.63</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>In the period of 2010 to 2014, The Federal District presented mortality rates similar to the state of Goi&#225;s, except for the year 2012, which showed one of the lowest death rates in the country.</p>
      <p>A predictive model for fatality rates was estimated (<xref ref-type="table" rid="t3">Table 3</xref>). There were no sex differences in mortality, when adjusted to the other predictors. In relation to the age groups, the greater the age, the greater the risk of death associated with systemic arterial hypertension. Skin color, taking "whites" as reference group, indicated greater association between hypertensive diseases and mortality in "browns", and lower association in "blacks", "yellows", "indigenous" and in the cases in which this variable was "ignored". It should be stressed that the total number of "indigenous" and "yellows" added to the "ignored" group corresponded to less than 6%. "Blacks" represented less than 12% of the "brown", "white" and "black" groups, with the vast majority among the "whites".</p>
      <table-wrap id="t3">
        <label>Table 3</label>
        <caption>
          <title>Longitudinal analysis using a negative binomial model, having as dependent variable the number of deaths associated with hypertensive diseases, and as predictors "age group", "sex", "color", "region" and "year", adjusted to the annual population estimate for each location, between 2010 and 2014</title>
        </caption>
        <table frame="hsides" rules="groups">
          <colgroup>
            <col width="20%"/>
            <col width="20%"/>
            <col width="20%"/>
            <col width="20%"/>
            <col width="20%"/>
          </colgroup>
          <thead>
            <tr>
              <th align="left" style="background-color:#C5C6C8">Deaths</th>
              <th align="center" style="background-color:#C5C6C8">IRR</th>
              <th align="center" colspan="2" style="border-bottom-width:thin;border-bottom-style:solid;background-color:#C5C6C8">95% CI</th>
              <th align="center" style="background-color:#C5C6C8">p-value</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td align="left">Sex</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
            </tr>
            <tr>
              <td align="left">Female (reference)</td>
              <td align="center">-</td>
              <td align="center">-</td>
              <td align="center">-</td>
              <td align="center">-</td>
            </tr>
            <tr>
              <td align="left">Male</td>
              <td align="center">1.03</td>
              <td align="center">0.99</td>
              <td align="center">1.08</td>
              <td align="center">0.158</td>
            </tr>
            <tr>
              <td align="left">Age group</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
            </tr>
            <tr>
              <td align="left">50 - 59 years old (reference)</td>
              <td align="center">-</td>
              <td align="center">-</td>
              <td align="center">-</td>
              <td align="center">-</td>
            </tr>
            <tr>
              <td align="left">60 - 69 years old</td>
              <td align="center">1.63</td>
              <td align="center">1.53</td>
              <td align="center">1.73</td>
              <td align="center">&lt; 0.0001</td>
            </tr>
            <tr>
              <td align="left">70 - 79 years old</td>
              <td align="center">2.40</td>
              <td align="center">2.25</td>
              <td align="center">2.55</td>
              <td align="center">&lt; 0.0001</td>
            </tr>
            <tr>
              <td align="left">&#8805; 80 years old</td>
              <td align="center">3.99</td>
              <td align="center">3.76</td>
              <td align="center">4.26</td>
              <td align="center">&lt; 0.0001</td>
            </tr>
            <tr>
              <td align="left">Color</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
            </tr>
            <tr>
              <td align="left">White (reference)</td>
              <td align="center">-</td>
              <td align="center">-</td>
              <td align="center">-</td>
              <td align="center">-</td>
            </tr>
            <tr>
              <td align="left">Black</td>
              <td align="center">0.27</td>
              <td align="center">0.25</td>
              <td align="center">0.29</td>
              <td align="center">&lt; 0.0001</td>
            </tr>
            <tr>
              <td align="left">Brown</td>
              <td align="center">1.28</td>
              <td align="center">1.20</td>
              <td align="center">1.36</td>
              <td align="center">&lt; 0.0001</td>
            </tr>
            <tr>
              <td align="left">Yellow</td>
              <td align="center">0.01</td>
              <td align="center">0.00</td>
              <td align="center">0.01</td>
              <td align="center">&lt; 0.0001</td>
            </tr>
            <tr>
              <td align="left">Ind&#237;genous</td>
              <td align="center">0.01</td>
              <td align="center">0.01</td>
              <td align="center">0.01</td>
              <td align="center">&lt; 0.0001</td>
            </tr>
            <tr>
              <td align="left">Ignored</td>
              <td align="center">0.13</td>
              <td align="center">0.12</td>
              <td align="center">0.14</td>
              <td align="center">&lt; 0.0001</td>
            </tr>
            <tr>
              <td align="left">Region</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
            </tr>
            <tr>
              <td align="left">Southeast (reference)</td>
              <td align="center">-</td>
              <td align="center">-</td>
              <td align="center">-</td>
              <td align="center">-</td>
            </tr>
            <tr>
              <td align="left">North</td>
              <td align="center">0.43</td>
              <td align="center">0.40</td>
              <td align="center">0.47</td>
              <td align="center">&lt; 0.0001</td>
            </tr>
            <tr>
              <td align="left">Northeast</td>
              <td align="center">0.96</td>
              <td align="center">0.90</td>
              <td align="center">1.03</td>
              <td align="center">0.237</td>
            </tr>
            <tr>
              <td align="left">Central-West</td>
              <td align="center">0.73</td>
              <td align="center">0.67</td>
              <td align="center">0.78</td>
              <td align="center">&lt; 0.0001</td>
            </tr>
            <tr>
              <td align="left">South</td>
              <td align="center">0.61</td>
              <td align="center">0.57</td>
              <td align="center">0.67</td>
              <td align="center">&lt; 0.0001</td>
            </tr>
            <tr>
              <td align="left">Year</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
              <td align="center">
							</td>
            </tr>
            <tr>
              <td align="left">2010 (reference)</td>
              <td align="center">-</td>
              <td align="center">-</td>
              <td align="center">-</td>
              <td align="center">-</td>
            </tr>
            <tr>
              <td align="left">2011</td>
              <td align="center">106</td>
              <td align="center">0.99</td>
              <td align="center">1.14</td>
              <td align="center">0.112</td>
            </tr>
            <tr>
              <td align="left">2012</td>
              <td align="center">1.00</td>
              <td align="center">0.94</td>
              <td align="center">1.08</td>
              <td align="center">0.898</td>
            </tr>
            <tr>
              <td align="left">2013</td>
              <td align="center">0.96</td>
              <td align="center">0.90</td>
              <td align="center">1.03</td>
              <td align="center">0.267</td>
            </tr>
            <tr>
              <td align="left">2014</td>
              <td align="center">0.96</td>
              <td align="center">0.90</td>
              <td align="center">1.03</td>
              <td align="center">0.261</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN2">
            <p>IRR: incidence rate ratio; CI: confidence interval.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>Since this is not an ethnical study, but still taking into account that skin color, as stated in the death certificate, has been considered a relevant data in the development of public health policies, the inclusion of this predictor has been less useful in producing racial inferences, than in adjusting this data to the other predictors and establishing iterative algorithms. In addition, it was observed that the models that include the variable "skin color", compared to the models that exclude this predictor, in addition to presenting predictors with similar IRRs, also achieved convergence in less time and provided lower AIC values, which indicates higher adequacy from a statistical point of view.</p>
      <p>Taking the southeast region as a reference, due to its highest development level and public policies applied for longer, there was no statistical difference compared to the northeast region, and the other regions presented a lower incidence rate ratio than the southeast Brazil.</p>
      <p>The predictive model showed that there was no significantly statistical difference in the incidence rate ratio of mortality between the years, when adjusted to the other predictors. Similarly, sex differences had no influence. High-age group, brown skin and southeast and northeast regions were predictors of the greatest mortality during the period under study.</p>
    </sec>
    <sec sec-type="discussion">
      <title>Discussion</title>
      <p>An epidemiological study was carried out based on aggregate data, obtained in population strata. Therefore, in order to avoid the "ecological fallacy", the applicability of the results cannot be extended to the individual level, to the doctor's practice level, but only to state, regional and national levels.</p>
      <p>Since the data were collected from public organizations, which, in turn, came from constant notifications in death certificates, the outline of this article does not include methodological elements able to test their veracity. This also applies to the matter of item selection in the death certificates, which may potentially present differences related to preferences in each state or region to highlight, more or less often, hypertension as a relevant cause of death.</p>
      <p>The number of deaths associated with hypertensive diseases is related with the increase in age, as can be observed in this study. The impact of this illness tends to aggravate, since the elderly population increases every year, corresponding nowadays to 15% of the world's population. World projections indicate that this population will continue to increase, and it is estimated that this number may nearly double to 30% by the year 2050. This demands special attention to the development of measures that can help prevent and control hypertensive diseases.<xref ref-type="bibr" rid="B16">16</xref>
			</p>
      <p>In another study, this time about the prevalence of arterial hypertension, the south and southeast regions of Brazil presented higher rates, compared to the other regions: 25% (95% CI: 23.8 - 26.1) and 25% (95% CI: 23.5 - 26.5), respectively.<xref ref-type="bibr" rid="B17">17</xref> However, the present study focused on mortality rates associated with hypertensive diseases, and the regions with the highest rates were the northeast and the southeast. Although this issue is beyond the scope of the present research, it is speculated that the discrepancy between higher prevalence and lower mortality in the south could result from more intensive application of therapeutic strategies, both in health care and drug provision.</p>
      <p>An opposite phenomenon could be observed in a northeastern state. This study showed that the state of Piau&#237; presented, for four consecutive years, the highest mortality rate associated with hypertensive diseases. Nevertheless, a research conducted with elderly people in 2013, in the same state, indicated that the prevalence of SAH in this population is 40.2%, below than expected for that age group, whose prevalence is 68% among the population over 60 years of age.<xref ref-type="bibr" rid="B4">4</xref><sup>,</sup><xref ref-type="bibr" rid="B18">18</xref> Once again, speculatively speaking, but still beyond the scope of this research, this finding could be a result of obstacles to health care and access to medications.</p>
      <p>These considerations are mainly intended to formulate hypotheses that remain to be analyzed in future research.</p>
      <p>Death rates associated with hypertensive diseases were higher among the brown population in Brazil, compared to blacks, something that might have been influenced by eventual subjectivity in skin color identification and due to the predominance of miscegenation in Brazil.<xref ref-type="bibr" rid="B19">19</xref> There are still few studies conducted in South America on the higher prevalence of arterial hypertension in blacks, with most scientific information concerning ethnicity coming from studies carried out in the United States.<xref ref-type="bibr" rid="B20">20</xref>
			</p>
      <p>Several limitations arise from this type of study, which deals with aggregate data. For example, we cannot rule out the possibility of having occurred increased notifications, on the one hand, and hypertension control improvement, on the other hand, something that would generate an apparent constancy of the illness in the time series analysis of the data. However, from a methodological point of view, the research design sought to adjust the analysis for eventual influences of both temporal and geographic factors in the same region or state.</p>
      <p>It is also important to highlight that we used the data considered more relevant for the elaboration of public policies nowadays, something that reflects in the planning, execution and evaluation of health actions towards the combat of the diseases of greatest impact in Brazil.<xref ref-type="bibr" rid="B21">21</xref> Therefore, the implementation of Pharmaceutical Assistance by the Ministry of Health's department has arisen as a major impact resource to reduce mortality due to non-transmitted chronic diseases, including arterial hypertension.<xref ref-type="bibr" rid="B9">9</xref>
			</p>
      <p>Nevertheless, based on the information available on mortality associated with hypertensive diseases in public registries, and by submitting these data to a complex evaluation, corroborated by several analytical models, the absence of major reduction in mortality rates in the period of five years suggests that it is necessary, among other measures, to broaden the pharmacological scope of free distribution drugs and enhance healthcare programs.</p>
    </sec>
    <sec sec-type="conclusions">
      <title>Conclusion</title>
      <p>Death rates associated with hypertensive diseases were higher in the southeastern and northeastern Brazil, compared to the other regions. This rate did not show significant alterations between the years 2010 and 2014, when assessed in relation to the same state and region of Brazil. Other predictors of higher rates of mortality were brown skin color and increase in age. Public health policies, concerning medical care for hypertensive patients and prevention of complications, must be preferably applied in the states with the highest rates.</p>
    </sec>
  </body>
  <back>
    <fn-group>
      <fn fn-type="financial-disclosure">
        <p>Sources of Funding</p>
        <p>There were no external funding sources for this study.</p>
      </fn>
      <fn fn-type="other">
        <p>Study Association</p>
        <p>This study is not associated with any thesis or dissertation work.</p>
      </fn>
      <fn fn-type="other">
        <p>Ethics approval and consent to participate</p>
        <p>This article does not contain any studies with human participants or animals performed by any of the authors.</p>
      </fn>
    </fn-group>
    <ref-list>
      <title>References</title>
      <ref id="B1">
        <label>1</label>
        <mixed-citation>1 Guimar&#227;es RM, Andrade SS, Machado EL, Bahia CA, Oliveira MM, Jacques FV. Regional differences in cardiovascular mortality transition in Brazil, 1980 to 2012. Rev Panam Salud Publica. 2015;37(2):83-9.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Guimar&#227;es</surname>
              <given-names>RM</given-names>
            </name>
            <name>
              <surname>Andrade</surname>
              <given-names>SS</given-names>
            </name>
            <name>
              <surname>Machado</surname>
              <given-names>EL</given-names>
            </name>
            <name>
              <surname>Bahia</surname>
              <given-names>CA</given-names>
            </name>
            <name>
              <surname>Oliveira</surname>
              <given-names>MM</given-names>
            </name>
            <name>
              <surname>Jacques</surname>
              <given-names>FV</given-names>
            </name>
          </person-group>
          <article-title>Regional differences in cardiovascular mortality transition in Brazil, 1980 to 2012</article-title>
          <source>Rev Panam Salud Publica</source>
          <year>2015</year>
          <volume>37</volume>
          <issue>2</issue>
          <fpage>83</fpage>
          <lpage>89</lpage>
        </element-citation>
      </ref>
      <ref id="B2">
        <label>2</label>
        <mixed-citation>2 Andrade SS, Rizzato S, Scalioni A, Landmann C, Malta DC. Self-reported hypertension prevalence in the Brazilian population: analysis of the National Health Survey, 2013. Epidemiol Serv Sa&#250;de. 2015;24(2):297-304.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Andrade</surname>
              <given-names>SS</given-names>
            </name>
            <name>
              <surname>Rizzato</surname>
              <given-names>S</given-names>
            </name>
            <name>
              <surname>Scalioni</surname>
              <given-names>A</given-names>
            </name>
            <name>
              <surname>Landmann</surname>
              <given-names>C</given-names>
            </name>
            <name>
              <surname>Malta</surname>
              <given-names>DC</given-names>
            </name>
          </person-group>
          <article-title>Self-reported hypertension prevalence in the Brazilian population: analysis of the National Health Survey, 2013</article-title>
          <source>Epidemiol Serv Sa&#250;de</source>
          <year>2015</year>
          <volume>24</volume>
          <issue>2</issue>
          <fpage>297</fpage>
          <lpage>304</lpage>
        </element-citation>
      </ref>
      <ref id="B3">
        <label>3</label>
        <mixed-citation>3 World Health Organization (WHO). Global status report on noncommunicable diseases. Geneva; 2014.</mixed-citation>
        <element-citation publication-type="book">
          <person-group person-group-type="author">
            <collab>World Health Organization (WHO)</collab>
          </person-group>
          <source>Global status report on noncommunicable diseases</source>
          <publisher-loc>Geneva</publisher-loc>
          <year>2014</year>
        </element-citation>
      </ref>
      <ref id="B4">
        <label>4</label>
        <mixed-citation>4 Malachias MV, Souza WK, Plavnik FL, Rodrigues CI, Brand&#227;o AA, Neves MF, et al; Sociedade Brasileira de Cardiologia. 7a Diretriz Brasileira de hipertens&#227;o arterial. Arq Bras Cardiol. 2016;107(3 supl 3):1-83.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Malachias</surname>
              <given-names>MV</given-names>
            </name>
            <name>
              <surname>Souza</surname>
              <given-names>WK</given-names>
            </name>
            <name>
              <surname>Plavnik</surname>
              <given-names>FL</given-names>
            </name>
            <name>
              <surname>Rodrigues</surname>
              <given-names>CI</given-names>
            </name>
            <name>
              <surname>Brand&#227;o</surname>
              <given-names>AA</given-names>
            </name>
            <name>
              <surname>Neves</surname>
              <given-names>MF</given-names>
            </name>
            <etal/>
            <collab>Sociedade Brasileira de Cardiologia</collab>
          </person-group>
          <article-title>7a Diretriz Brasileira de hipertens&#227;o arterial</article-title>
          <source>Arq Bras Cardiol</source>
          <year>2016</year>
          <volume>107</volume>
          <issue>3</issue>
          <supplement>Suppl 3</supplement>
          <fpage>1</fpage>
          <lpage>83</lpage>
        </element-citation>
      </ref>
      <ref id="B5">
        <label>5</label>
        <mixed-citation>5 Thorpe RJ Jr, Bowie JV, Smolen JR, Bell CN, Jenkins ML Jr, Jackson J, et al. Racial disparities in hypertension awareness and management: are there differences among African Americans and Whites living in similar social and healthcare resource environments? Ethn Dis. 2014;24(3):269-75.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Thorpe</surname>
              <given-names>RJ</given-names>
              <suffix>Jr</suffix>
            </name>
            <name>
              <surname>Bowie</surname>
              <given-names>JV</given-names>
            </name>
            <name>
              <surname>Smolen</surname>
              <given-names>JR</given-names>
            </name>
            <name>
              <surname>Bell</surname>
              <given-names>CN</given-names>
            </name>
            <name>
              <surname>Jenkins</surname>
              <given-names>ML</given-names>
              <suffix>Jr</suffix>
            </name>
            <name>
              <surname>Jackson</surname>
              <given-names>J</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Racial disparities in hypertension awareness and management: are there differences among African Americans and Whites living in similar social and healthcare resource environments?</article-title>
          <source>Ethn Dis</source>
          <year>2014</year>
          <volume>24</volume>
          <issue>3</issue>
          <fpage>269</fpage>
          <lpage>275</lpage>
        </element-citation>
      </ref>
      <ref id="B6">
        <label>6</label>
        <mixed-citation>6 Judd SE, Kleindorfer DO, McClure LA, Rhodes JD, Howard G, Cushman M, et al. Self-report of stroke, transient ischemic attack, or stroke symptoms and risk of future stroke in the reasons for geographic and racial differences in stroke (REGARDS) study. Stroke. 2013;44(1):55-60.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Judd</surname>
              <given-names>SE</given-names>
            </name>
            <name>
              <surname>Kleindorfer</surname>
              <given-names>DO</given-names>
            </name>
            <name>
              <surname>McClure</surname>
              <given-names>LA</given-names>
            </name>
            <name>
              <surname>Rhodes</surname>
              <given-names>JD</given-names>
            </name>
            <name>
              <surname>Howard</surname>
              <given-names>G</given-names>
            </name>
            <name>
              <surname>Cushman</surname>
              <given-names>M</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Self-report of stroke, transient ischemic attack, or stroke symptoms and risk of future stroke in the reasons for geographic and racial differences in stroke (REGARDS) study</article-title>
          <source>Stroke</source>
          <year>2013</year>
          <volume>44</volume>
          <issue>1</issue>
          <fpage>55</fpage>
          <lpage>60</lpage>
        </element-citation>
      </ref>
      <ref id="B7">
        <label>7</label>
        <mixed-citation>7 Lotufo PA, Bensenor IJ. [Race and stroe mortality in Brazil]. Rev Saude Publica. 2013;47(6):1201-4.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Lotufo</surname>
              <given-names>PA</given-names>
            </name>
            <collab>Bensenor IJ</collab>
          </person-group>
          <article-title>Race and stroe mortality in Brazil</article-title>
          <source>Rev Saude Publica</source>
          <year>2013</year>
          <volume>47</volume>
          <issue>6</issue>
          <fpage>1201</fpage>
          <lpage>1204</lpage>
        </element-citation>
      </ref>
      <ref id="B8">
        <label>8</label>
        <mixed-citation>8 Chor D, Pinho Ribeiro AL, S&#225; Carvalho M, Duncan BB, Andrade Lotufo P, Ara&#250;jo Nobre A, et al. Prevalence, awareness, treatment and influence of socioeconomic variables on control of high blood pressure: results of the ELSA Brasil Study. PLoS One. 2015;10(6):e0127382.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Chor</surname>
              <given-names>D</given-names>
            </name>
            <name>
              <surname>Pinho Ribeiro</surname>
              <given-names>AL</given-names>
            </name>
            <name>
              <surname>S&#225; Carvalho</surname>
              <given-names>M</given-names>
            </name>
            <name>
              <surname>Duncan</surname>
              <given-names>BB</given-names>
            </name>
            <name>
              <surname>Andrade Lotufo</surname>
              <given-names>P</given-names>
            </name>
            <name>
              <surname>Ara&#250;jo Nobre</surname>
              <given-names>A</given-names>
            </name>
            <etal/>
          </person-group>
          <article-title>Prevalence, awareness, treatment and influence of socioeconomic variables on control of high blood pressure: results of the ELSA Brasil Study</article-title>
          <source>PLoS One</source>
          <year>2015</year>
          <volume>10</volume>
          <issue>6</issue>
          <elocation-id>e0127382</elocation-id>
        </element-citation>
      </ref>
      <ref id="B9">
        <label>9</label>
        <mixed-citation>9 Oliveira PA, Menezes FG. Aten&#231;&#227;o farmac&#234;utica a pacientes hipertensos. Revista Eletr&#244;nica de Farm&#225;cia. 2013;10(1):51-68.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Oliveira</surname>
              <given-names>PA</given-names>
            </name>
            <name>
              <surname>Menezes</surname>
              <given-names>FG</given-names>
            </name>
          </person-group>
          <article-title>Aten&#231;&#227;o farmac&#234;utica a pacientes hipertensos</article-title>
          <source>Revista Eletr&#244;nica de Farm&#225;cia</source>
          <year>2013</year>
          <volume>10</volume>
          <issue>1</issue>
          <fpage>51</fpage>
          <lpage>68</lpage>
        </element-citation>
      </ref>
      <ref id="B10">
        <label>10</label>
        <mixed-citation>10 Instituto Brasileiro de Geografia e Estat&#237;stica. (IBGE). [Internet]. Organiza&#231;&#227;o do territ&#243;rio, malhas territoriais e municipais em 2015 [Acesso em 2017 jan 20]. Dispon&#237;vel em: <ext-link ext-link-type="uri" xlink:href="ftp://geoftp.ibge.gov.br/organizacao_do_territorio/malhas_territoriais/malhas_municipais/municipio_2015/Brasil/BR/">ftp://geoftp.ibge.gov.br/organizacao_do_territorio/malhas_territoriais/malhas_municipais/municipio_2015/Brasil/BR/</ext-link>.</mixed-citation>
        <element-citation publication-type="webpage">
          <person-group person-group-type="author">
            <collab>Instituto Brasileiro de Geografia e Estat&#237;stica. (IBGE)</collab>
          </person-group>
          <source>[Internet]. Organiza&#231;&#227;o do territ&#243;rio, malhas territoriais e municipais em 2015</source>
          <date-in-citation content-type="access-date">2017 jan 20</date-in-citation>
          <comment>Dispon&#237;vel em: <ext-link ext-link-type="uri" xlink:href="ftp://geoftp.ibge.gov.br/organizacao_do_territorio/malhas_territoriais/malhas_municipais/mun icipio_2015/Brasil/BR/">ftp://geoftp.ibge.gov.br/organizacao_do_territorio/malhas_territoriais/malhas_municipais/mun icipio_2015/Brasil/BR/</ext-link>
					</comment>
        </element-citation>
      </ref>
      <ref id="B11">
        <label>11</label>
        <mixed-citation>11 Instituto Brasileiro de Geografia e Estat&#237;stica. (IBGE). [Internet]. Estimativas da popula&#231;&#227;o residente no Brasil e unidades da federa&#231;&#227;o com data de refer&#234;ncia em 1&#186; de julho de 2011. [Acesso em 2017 jan 20]. Dispon&#237;vel em: <ext-link ext-link-type="uri" xlink:href="http://www.ibge.gov.br/home/estatistica/populacao/estimativa2011/tab_Brasil_UF.pdf">http://www.ibge.gov.br/home/estatistica/populacao/estimativa2011/tab_Brasil_UF.pdf</ext-link>
				</mixed-citation>
        <element-citation publication-type="webpage">
          <person-group person-group-type="author">
            <collab>Instituto Brasileiro de Geografia e Estat&#237;stica. (IBGE)</collab>
          </person-group>
          <source>[Internet]. Estimativas da popula&#231;&#227;o residente no Brasil e unidades da federa&#231;&#227;o com data de refer&#234;ncia em 1&#186; de julho de 2011</source>
          <date-in-citation content-type="access-date">2017 jan 20</date-in-citation>
          <comment>Dispon&#237;vel em: <ext-link ext-link-type="uri" xlink:href="http://www.ibge.gov.br/home/estatistica/populacao/ estimativa2011/tab_Brasil_UF.pdf">http://www.ibge.gov.br/home/estatistica/populacao/ estimativa2011/tab_Brasil_UF.pdf</ext-link>
					</comment>
        </element-citation>
      </ref>
      <ref id="B12">
        <label>12</label>
        <mixed-citation>12 Brasil. Minist&#233;rio da Sa&#250;de [Internet]. Departamento de Inform&#225;tica do SUS. Datasus. Informa&#231;&#245;es de Sa&#250;de. Estat&#237;sticas vitais. [Acesso em 2016 dez 10]. Dispon&#237;vel em: <ext-link ext-link-type="uri" xlink:href="http://www2.datasus.gov.br/DATASUS/index.php?area=0205">http://www2.datasus.gov.br/DATASUS/index.php?area=0205</ext-link>.</mixed-citation>
        <element-citation publication-type="webpage">
          <person-group person-group-type="author">
            <collab>Brasil</collab>
            <collab>Minist&#233;rio da Sa&#250;de [Internet]</collab>
            <collab>Departamento de Inform&#225;tica do SUS</collab>
            <collab>Datasus</collab>
          </person-group>
          <source>Informa&#231;&#245;es de Sa&#250;de. Estat&#237;sticas vitais</source>
          <date-in-citation content-type="access-date">2016 dez 10</date-in-citation>
          <comment>Dispon&#237;vel em: <ext-link ext-link-type="uri" xlink:href="http://www2.datasus.gov.br/DATASUS/index.php?area=0205">http://www2.datasus.gov.br/DATASUS/index.php?area=0205</ext-link>
					</comment>
        </element-citation>
      </ref>
      <ref id="B13">
        <label>13</label>
        <mixed-citation>13 Brasil. Minist&#233;rio da Sa&#250;de. Sistema de Informa&#231;&#245;es sobre Mortalidade - SIM. Consolida&#231;&#227;o da base de dados de 2011. Bras&#237;lia; 2013.</mixed-citation>
        <element-citation publication-type="book">
          <person-group person-group-type="author">
            <collab>Brasil. Minist&#233;rio da Sa&#250;de</collab>
          </person-group>
          <source>Sistema de Informa&#231;&#245;es sobre Mortalidade - SIM. Consolida&#231;&#227;o da base de dados de 2011</source>
          <publisher-loc>Bras&#237;lia</publisher-loc>
          <year>2013</year>
        </element-citation>
      </ref>
      <ref id="B14">
        <label>14</label>
        <mixed-citation>14 Silva RM, Caetano R. "Farm&#225;cia Popular do Brasil" Program: characterization and evolution between 2004 and 2012. Cienc Saude Colet. 2015;20(10):2943-56.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Silva</surname>
              <given-names>RM</given-names>
            </name>
            <name>
              <surname>Caetano</surname>
              <given-names>R</given-names>
            </name>
          </person-group>
          <article-title>Farm&#225;cia Popular do Brasil" Program: characterization and evolution between 2004 and 2012</article-title>
          <source>Cienc Saude Colet</source>
          <year>2015</year>
          <volume>20</volume>
          <issue>10</issue>
          <fpage>2943</fpage>
          <lpage>2956</lpage>
        </element-citation>
      </ref>
      <ref id="B15">
        <label>15</label>
        <mixed-citation>15 Amorim ME, Ferreira MR, Oliveira SA, Fernandes CK. Programa Farm&#225;cia Popular no Brasil em uma drogaria de S&#227;o Lu&#237;s de Montes Belos (GO). Revista Faculdade Montes Belos (FMB). 2015;8(1):1-13.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Amorim</surname>
              <given-names>ME</given-names>
            </name>
            <name>
              <surname>Ferreira</surname>
              <given-names>MR</given-names>
            </name>
            <name>
              <surname>Oliveira</surname>
              <given-names>SA</given-names>
            </name>
            <name>
              <surname>Fernandes</surname>
              <given-names>CK</given-names>
            </name>
          </person-group>
          <article-title>Programa Farm&#225;cia Popular no Brasil em uma drogaria de S&#227;o Lu&#237;s de Montes Belos (GO)</article-title>
          <source>Revista Faculdade Montes Belos (FMB)</source>
          <year>2015</year>
          <volume>8</volume>
          <issue>1</issue>
          <fpage>1</fpage>
          <lpage>13</lpage>
        </element-citation>
      </ref>
      <ref id="B16">
        <label>16</label>
        <mixed-citation>16 Coelho J&#250;nior HJ, Sampaio RA, Gon&#231;alvez IO, Aguiar SS, Palmeira R. Cutoffs and cardiovascular risk factors associated with neck circumference among community-dwelling elderly adults: a cross-sectional study. Sao Paulo Med J. 2016;134(6):519-27.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Coelho</surname>
              <given-names>HJ</given-names>
              <suffix>J&#250;nior</suffix>
            </name>
            <name>
              <surname>Sampaio</surname>
              <given-names>RA</given-names>
            </name>
            <name>
              <surname>Gon&#231;alvez</surname>
              <given-names>IO</given-names>
            </name>
            <name>
              <surname>Aguiar</surname>
              <given-names>SS</given-names>
            </name>
            <name>
              <surname>Palmeira</surname>
              <given-names>R</given-names>
            </name>
          </person-group>
          <article-title>Cutoffs and cardiovascular risk factors associated with neck circumference among community-dwelling elderly adults: a cross-sectional study</article-title>
          <source>Sao Paulo Med J</source>
          <year>2016</year>
          <volume>134</volume>
          <issue>6</issue>
          <fpage>519</fpage>
          <lpage>527</lpage>
        </element-citation>
      </ref>
      <ref id="B17">
        <label>17</label>
        <mixed-citation>17 Malta DC, Santos NB, Perillo RD, Szwarcwald CL. Prevalence of high blood pressure measured in the Brazilian population, National Health Survey, 2013. Sao Paulo Med J. 2016;134(2):163-70.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Malta</surname>
              <given-names>DC</given-names>
            </name>
            <name>
              <surname>Santos</surname>
              <given-names>NB</given-names>
            </name>
            <name>
              <surname>Perillo</surname>
              <given-names>RD</given-names>
            </name>
            <name>
              <surname>Szwarcwald</surname>
              <given-names>CL</given-names>
            </name>
          </person-group>
          <article-title>Prevalence of high blood pressure measured in the Brazilian population, National Health Survey, 2013</article-title>
          <source>Sao Paulo Med J</source>
          <year>2016</year>
          <volume>134</volume>
          <issue>2</issue>
          <fpage>163</fpage>
          <lpage>170</lpage>
        </element-citation>
      </ref>
      <ref id="B18">
        <label>18</label>
        <mixed-citation>18 Oliveira Neto JG, Carvalho DA, Moura GG, Monteiro MM, Lopes KD, Martins MC. Press&#227;o arterial e perfil socioecon&#244;mico de idosos atendidos na estrat&#233;gia sa&#250;de da fam&#237;lia de Floriano-Piau&#237;. Rev Sa&#250;de P&#250;bl Santa Cat. 2014,7(2):17-28.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Oliveira</surname>
              <given-names>JG</given-names>
              <suffix>Neto</suffix>
            </name>
            <name>
              <surname>Carvalho</surname>
              <given-names>DA</given-names>
            </name>
            <name>
              <surname>Moura</surname>
              <given-names>GG</given-names>
            </name>
            <name>
              <surname>Monteiro</surname>
              <given-names>MM</given-names>
            </name>
            <name>
              <surname>Lopes</surname>
              <given-names>KD</given-names>
            </name>
            <name>
              <surname>Martins</surname>
              <given-names>MC</given-names>
            </name>
          </person-group>
          <article-title>Press&#227;o arterial e perfil socioecon&#244;mico de idosos atendidos na estrat&#233;gia sa&#250;de da fam&#237;lia de Floriano-Piau&#237;</article-title>
          <source>Rev Sa&#250;de P&#250;bl Santa Cat</source>
          <year>2014</year>
          <volume>7</volume>
          <issue>2</issue>
          <fpage>17</fpage>
          <lpage>28</lpage>
        </element-citation>
      </ref>
      <ref id="B19">
        <label>19</label>
        <mixed-citation>19 Menezes TN, Oliveira EC, Fischer MA, Esteves GH. Prevalence and control of hypertension in the elderly: a population study. Rev Port Sa&#250;de P&#250;blica. 2016;34(2):117-24.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <name>
              <surname>Menezes</surname>
              <given-names>TN</given-names>
            </name>
            <name>
              <surname>Oliveira</surname>
              <given-names>EC</given-names>
            </name>
            <name>
              <surname>Fischer</surname>
              <given-names>MA</given-names>
            </name>
            <name>
              <surname>Esteves</surname>
              <given-names>GH</given-names>
            </name>
          </person-group>
          <article-title>Prevalence and control of hypertension in the elderly: a population study</article-title>
          <source>Rev Port Sa&#250;de P&#250;blica</source>
          <year>2016</year>
          <volume>34</volume>
          <issue>2</issue>
          <fpage>117</fpage>
          <lpage>124</lpage>
        </element-citation>
      </ref>
      <ref id="B20">
        <label>20</label>
        <mixed-citation>20 Task Force of the Latin American Society of Hypertension. Guidelines on the management of arterial hypertension and related comorbidities in Latin America. J Hypertens. 2017;35(8):1529-45.</mixed-citation>
        <element-citation publication-type="journal">
          <person-group person-group-type="author">
            <collab>Task Force of the Latin American Society of Hypertension</collab>
          </person-group>
          <article-title>Guidelines on the management of arterial hypertension and related comorbidities in Latin America</article-title>
          <source>J Hypertens</source>
          <year>2017</year>
          <volume>35</volume>
          <issue>8</issue>
          <fpage>1529</fpage>
          <lpage>1545</lpage>
        </element-citation>
      </ref>
      <ref id="B21">
        <label>21</label>
        <mixed-citation>21 Marinho F, Passos VM, Fran&#231;a EB. New century, new challenges: changes in the burden of disease profile in Brazil, 1990-2010. Epidemiol Serv Saude. 2016,25(4):713-24.</mixed-citation>
        <element-citation publication-type="book">
          <person-group person-group-type="author">
            <name>
              <surname>Marinho</surname>
              <given-names>F</given-names>
            </name>
            <name>
              <surname>Passos</surname>
              <given-names>VM</given-names>
            </name>
            <name>
              <surname>Fran&#231;a</surname>
              <given-names>EB</given-names>
            </name>
          </person-group>
          <chapter-title>New century, new challenges: changes in the burden of disease profile in Brazil, 1990-2010</chapter-title>
          <source>Epidemiol Serv Saude</source>
          <year>2016</year>
          <volume>4</volume>
          <fpage>713</fpage>
          <lpage>724</lpage>
        </element-citation>
      </ref>
    </ref-list>
  </back>
  <sub-article article-type="translation" id="s1" xml:lang="pt">
    <front-stub>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Artigos Originais</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>An&#225;lise Espacial e Tend&#234;ncias de Mortalidade Associada a Doen&#231;as Hipertensivas nos Estados e Regi&#245;es do Brasil entre 2010 e 2014</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Almeida-Santos</surname>
            <given-names>Marcos Antonio</given-names>
          </name>
          <xref ref-type="aff" rid="aff2"/>
          <xref ref-type="corresp" rid="c2"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Prado</surname>
            <given-names>Beatriz Santana</given-names>
          </name>
          <xref ref-type="aff" rid="aff2"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Santos</surname>
            <given-names>Deyse Mirelle Souza</given-names>
          </name>
          <xref ref-type="aff" rid="aff2"/>
        </contrib>
        <aff id="aff2">
          <institution content-type="original">Programa de P&#243;s-gradua&#231;&#227;o em Sa&#250;de e Ambiente da Universidade Tiradentes, Aracaju, SE - Brasil</institution>
        </aff>
      </contrib-group>
      <author-notes>
        <corresp id="c2"><bold>Correspond&#234;ncia: Marcos Antonio Almeida-Santos</bold>. Avenida Gon&#231;alo Prado Rollemberg, 211, sala: 210. CEP: 49010-410, S&#227;o Jos&#233;, Aracaju, SE - Brasil. E-mail: <email>maasantos@cardiol.br</email>, <email>marcosalmeida2010@yahoo.com.br</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: Santos MAA. Obten&#231;&#227;o de dados: Santos MAA. An&#225;lise e interpreta&#231;&#227;o dos dados: Santos MAA. An&#225;lise estat&#237;stica: Santos MAA. Reda&#231;&#227;o do manuscrito: Santos MAA, Prado BS, Santos DMS. Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante: Santos MAA, Prado BS, Santos DMS.</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>
        <title>Resumo</title>
        <sec>
          <title>Fundamentos:</title>
          <p>A hipertens&#227;o arterial sist&#234;mica (HAS) representa o agravo de maior relev&#226;ncia, sendo um dos principais fatores de risco para doen&#231;as cardiovasculares.</p>
        </sec>
        <sec>
          <title>Objetivo:</title>
          <p>Analisar tend&#234;ncias da taxa de mortalidade associada a doen&#231;as hipertensivas no Brasil, de 2010 a 2014, tanto para os estados quanto para as regi&#245;es.</p>
        </sec>
        <sec>
          <title>M&#233;todos:</title>
          <p>Estudo epidemiol&#243;gico a partir de dados agregados, obtidos em estratos populacionais. Dados cartogr&#225;ficos em "shapefile" do territ&#243;rio brasileiro foram fornecidos pelo IBGE. Registros de mortalidade associada &#224; hipertens&#227;o arterial obtidos no DATASUS, mediante notifica&#231;&#245;es filtradas por categoria I.10 do C&#243;digo Internacional das Doen&#231;as (CID-10). Adotou-se como crit&#233;rio de signific&#226;ncia estat&#237;stica o valor de p bicaudal &lt; 0,05.</p>
        </sec>
        <sec>
          <title>Resultado:</title>
          <p>O aumento da idade se associou de maneira progressiva &#224; eleva&#231;&#227;o da m&#233;dia de &#243;bitos relacionada a doen&#231;as hipertensivas entre os anos de 2010 e 2014. Nas faixas et&#225;rias entre 50-59 anos, 60-69 anos, 70-79 anos e 80 ou mais anos, a m&#233;dia e desvio da taxa de mortalidade padr&#227;o foram, respectivamente: 15,11% (35,35); 24,14% (55,34); 35,07% (81,03) e 57,87% (139,08). A taxa global de mortalidade nas regi&#245;es brasileiras, por 10.000 habitantes, variou entre as regi&#245;es: norte (1,25); nordeste (2,69); centro-oeste (2,06); sudeste (2,48) e sul (2,04).</p>
        </sec>
        <sec>
          <title>Conclus&#227;o:</title>
          <p>A taxa de mortalidade associada a doen&#231;as hipertensivas foi superior nos estados do sudeste e nordeste do Brasil, e permaneceu est&#225;vel entre 2010 e 2014. Incremento de idade e cor parda foram preditores de maior mortalidade</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="pt">
        <title>Palavra-chave:</title>
        <kwd>Doen&#231;as Cardiovasculares / mortalidade</kwd>
        <kwd>Hipertens&#227;o / epidemiologia</kwd>
        <kwd>Hipertens&#227;o / etiologia</kwd>
        <kwd>Etnia e Sa&#250;de</kwd>
        <kwd>Acidente Vascular Cerebral</kwd>
        <kwd>Estudos Epidemiol&#243;gicos</kwd>
      </kwd-group>
    </front-stub>
    <body>
      <sec sec-type="intro">
        <title>Introdu&#231;&#227;o</title>
        <p>As doen&#231;as cerebrovasculares t&#234;m sido classificadas entre as de maior impacto em termos de morbimortalidade.<xref ref-type="bibr" rid="B1">1</xref> Dentre os principais fatores de risco cardiovascular, a hipertens&#227;o arterial sist&#234;mica (HAS) representa o agravo de maior relev&#226;ncia, fazendo-se necess&#225;rias a&#231;&#245;es de sa&#250;de visando minimizar os fatores de impacto que s&#227;o determinantes na sa&#250;de da popula&#231;&#227;o.<xref ref-type="bibr" rid="B2">2</xref>
				</p>
        <p>A preval&#234;ncia global de hipertens&#227;o arterial foi de 22%, em 2014, em adultos com idade igual ou superior a 18 anos.<xref ref-type="bibr" rid="B3">3</xref> A HAS &#233; caracterizada pela eleva&#231;&#227;o dos n&#237;veis press&#243;ricos para &#8805; 140 e/ou 90 mmHg, na qual a condi&#231;&#227;o cl&#237;nica pode ser causada por v&#225;rios motivos, podendo ser agravada por outros fatores de risco como dislipidemia, obesidade abdominal, intoler&#226;ncia &#224; glicose, diabetes mellito (DM), al&#233;m de fatores modific&#225;veis, determinantes socioecon&#244;micos e acesso inadequado aos cuidados de sa&#250;de.<xref ref-type="bibr" rid="B3">3</xref><sup>,</sup><xref ref-type="bibr" rid="B4">4</xref>
				</p>
        <p>Diversos estudos apontam para a influ&#234;ncia de aspectos &#233;tnicos no surgimento de doen&#231;as hipertensivas.<xref ref-type="bibr" rid="B5">5</xref> N&#227;o raro, existe dificuldade de se dissociar o papel representado por um grupo &#233;tnico, de fatores socioecon&#244;micos, simultaneamente atuantes.<xref ref-type="bibr" rid="B6">6</xref> No Brasil as taxas de mortalidade cerebrovascular apresentaram-se maiores em negros, seguidos por pardos e brancos.<xref ref-type="bibr" rid="B7">7</xref>
				</p>
        <p>Cerca de 32,6% de adultos e mais de 60% de idosos t&#234;m hipertens&#227;o arterial no Brasil, o que contribui direta ou indiretamente para 50% das mortes por doen&#231;a cardiovascular (DCV).4 Em pa&#237;ses de baixa e m&#233;dia renda, onde o tratamento e controle s&#227;o menores do que em pa&#237;ses desenvolvidos, estima-se em cerca de 80% a preval&#234;ncia de doen&#231;as associadas &#224; hipertens&#227;o.<xref ref-type="bibr" rid="B8">8</xref> O impacto dessa enfermidade se reflete em altos custos para o Sistema &#218;nico de Sa&#250;de (SUS). Estima-se um gasto anual de US$ 398,9 milh&#245;es, ou seja, cerca de 1,43% dos gastos totais do SUS.<xref ref-type="bibr" rid="B9">9</xref>
				</p>
        <p>O objetivo dessa pesquisa &#233; estimar o impacto da hipertens&#227;o arterial no territ&#243;rio brasileiro em um per&#237;odo de cinco anos. Para tal, s&#227;o analisadas tend&#234;ncias da taxa de mortalidade associada a doen&#231;as hipertensivas no Brasil, entre 2010 e 2014, estratificando-se de acordo com cor da pele e faixa et&#225;ria, tanto para os estados quanto para as regi&#245;es.</p>
      </sec>
      <sec sec-type="methods">
        <title>M&#233;todos</title>
        <p>Estudo epidemiol&#243;gico realizado a partir de dados agregados, obtidos em estratos populacionais, e associado &#224; an&#225;lise espacial.</p>
        <p>Os dados de organiza&#231;&#227;o do territ&#243;rio brasileiro, incluindo coordenadas, em formato "shapefile", e a estimativa da popula&#231;&#227;o dos anos estudados foram coletados no <italic>site</italic> do Instituto Brasileiro de Geografia e Estat&#237;stica, IBGE.<xref ref-type="bibr" rid="B10">10</xref><sup>,</sup><xref ref-type="bibr" rid="B11">11</xref>
				</p>
        <p>As informa&#231;&#245;es epidemiol&#243;gicas acerca da mortalidade associada &#224; hipertens&#227;o arterial foram obtidas mediante consulta ao banco de dados do Minist&#233;rio da Sa&#250;de, DATASUS.<xref ref-type="bibr" rid="B12">12</xref> Esses dados representam notifica&#231;&#245;es oriundas do Sistema de Informa&#231;&#227;o sobre Mortalidade.<xref ref-type="bibr" rid="B13">13</xref> Os &#243;bitos foram filtrados pela categoria I.10 do C&#243;digo Internacional das Doen&#231;as (CID-10). Em seguida, os dados agregados foram obtidos por ano, estado do pa&#237;s, sexo, faixa et&#225;ria e cor da pele.</p>
        <p>A sele&#231;&#227;o do per&#237;odo de an&#225;lise, entre 2010 e 2014, ocorreu devido aos seguintes motivos. Primeiramente, devido ao fato de considerarmos que an&#225;lises mais recentes apresentem maior fidedignidade na coleta de dados, em decorr&#234;ncia de progressiva melhora no processo de informatiza&#231;&#227;o com avan&#231;os da tecnologia. Em segundo lugar, por retratar, potencialmente, o cen&#225;rio de transi&#231;&#227;o resultante da introdu&#231;&#227;o da losartana, um f&#225;rmaco anti-hipertensivo de boa efic&#225;cia, que passou a ser distribu&#237;do gratuitamente no "Programa Farm&#225;cia Popular" a partir de 2010, vindo a tornar-se em 2014 o medicamento com maior demanda de consumo em unidades do Sistema &#218;nico de Sa&#250;de (SUS), inclusive no interior do pa&#237;s.<xref ref-type="bibr" rid="B14">14</xref><sup>,</sup><xref ref-type="bibr" rid="B15">15</xref>
				</p>
        <p>Entretanto, deve-se considerar que o efeito desse programa pode ocorrer de forma desigual entre as regi&#245;es, o que influenciaria potencialmente a an&#225;lise. Por fim, o t&#233;rmino do per&#237;odo, o ano de 2014, decorreu do fato de ser a data mais recente disponibilizada no DATASUS para a obten&#231;&#227;o de estat&#237;sticas vitais em todo o territ&#243;rio brasileiro.</p>
        <p>As vari&#225;veis selecionadas foram ano, sexo, faixa et&#225;ria, cor da pele, estado do pa&#237;s, regi&#227;o e n&#250;mero de ocorr&#234;ncia de &#243;bitos. Por tratar-se de enfermidade cr&#244;nica, as faixas et&#225;rias selecionadas para contagem de &#243;bitos associados &#224; hipertens&#227;o arterial foram: 50-59 anos; 60-69 anos; 70-79 anos e 80 ou mais anos. Essa contagem foi computada para os vinte e seis estados nacionais e para o Distrito Federal. A vari&#225;vel cor da pele retrata fundamentalmente a cor da pele e tra&#231;os &#233;tnicos, conforme consta na declara&#231;&#227;o de &#243;bito, sendo classificada em "branca", "amarela", "parda", "negra", "ind&#237;gena" ou "ignorado".</p>
        <sec>
          <title>An&#225;lise estat&#237;stica</title>
          <p>As vari&#225;veis categ&#243;ricas foram apresentadas em n&#250;mero absoluto e porcentagem. As vari&#225;veis num&#233;ricas foram apresentadas em m&#233;dia e erro padr&#227;o. Modelos de regress&#227;o para dados cont&#225;veis (Poisson e binomial negativo) em estudos longitudinais foram empregados em estimativas de predi&#231;&#227;o de mortalidade. Devido &#224; presen&#231;a de superdispers&#227;o, preferiu-se a regress&#227;o binomial negativa. A estimativa de "tamanho do efeito" foi ajustada para sexo, faixa et&#225;ria, cor da pele, regi&#227;o e ano, e apresentada sob a forma de raz&#227;o de taxa de incid&#234;ncia ou IRR ("incidence rate ratio") e intervalos de confian&#231;a a 95%.</p>
          <p>Com intuito de minimizar distor&#231;&#245;es decorrentes de diferen&#231;as espaciais e temporais entre popula&#231;&#245;es, os modelos de efeitos aleat&#243;rios inclu&#237;ram dados da popula&#231;&#227;o anual estimada de cada estado como fator "exposi&#231;&#227;o", isto &#233;, tendo esse coeficiente sido restringido, produzindo IRR igual a 1 e erro padr&#227;o virtualmente zero, ajustando-se o c&#225;lculo para os demais coeficientes. Para a sele&#231;&#227;o do modelo com melhor adequa&#231;&#227;o preditiva, empregou-se o crit&#233;rio de informa&#231;&#227;o de Akaike (AIC). Na an&#225;lise espacial, empregou-se o comando "spmap" para a elabora&#231;&#227;o de mapas coropl&#233;ticos, contendo os estados brasileiros e o Distrito Federal, e representando a distribui&#231;&#227;o em quintis da taxa de mortalidade associada &#224; hipertens&#227;o arterial. Considerou-se como crit&#233;rio de signific&#226;ncia estat&#237;stica um valor de p bicaudal &lt; 0,05. Os c&#225;lculos estat&#237;sticos e a an&#225;lise espacial foram realizados em Stata, vers&#227;o 14,2 (College Station, Texas, USA).</p>
        </sec>
        <sec>
          <title>Aspectos &#233;ticos</title>
          <p>Por se tratarem de dados p&#250;blicos, e n&#227;o haver elementos de identifica&#231;&#227;o dos indiv&#237;duos estudados, n&#227;o houve necessidade de emprego de termo de consentimento livre e esclarecido.</p>
        </sec>
      </sec>
      <sec sec-type="results">
        <title>Resultados</title>
        <p>O aumento progressivo da idade se associou &#224; eleva&#231;&#227;o da m&#233;dia de &#243;bitos relacionada a doen&#231;as hipertensivas, entre os anos de 2010 e 2014. Nas faixas et&#225;rias entre 50-59 anos, 60-69 anos, 70-79 anos e 80 ou mais anos, a m&#233;dia e desvio padr&#227;o da taxa de mortalidade foram, respectivamente: 15,11% (35,35); 24,14% (55,34); 35,07% (81,03) e 57,87% (139,08).</p>
        <p>Na representa&#231;&#227;o gr&#225;fica (<xref ref-type="fig" rid="f3">figura 1</xref>) de modelo de regress&#227;o binomial estendido para dados longitudinais, ajustado para as faixas et&#225;rias, observa-se maior raz&#227;o de taxa de incid&#234;ncia nas regi&#245;es sudeste e nordeste, se comparadas com as regi&#245;es sul, norte e centro-oeste.</p>
        <p>
          <fig id="f3">
            <label>Figura 1</label>
            <caption>
              <title>Representa&#231;&#227;o gr&#225;fica do modelo de regress&#227;o binomial estendido para dados longitudinais, com raz&#227;o de taxa de incid&#234;ncia ajustada para faixa et&#225;ria e de acordo com as regi&#245;es do Brasil, no per&#237;odo de 2010 a 2014.</title>
            </caption>
            <graphic xlink:href="2359-5647-ijcs-31-03-0250-80017-gf01-pt.jpg"/></fig>
        </p>
        <p>De acordo com as estimativas populacionais do IBGE para cada ano e estado do pa&#237;s,<xref ref-type="bibr" rid="B11">11</xref> calculou-se, por 10.000 habitantes, a taxa global de mortalidade associada a doen&#231;as hipertensivas entre 2010 e 2014, que variou entre as regi&#245;es: norte (1,25); nordeste (2,69); centro-oeste (2,06); sudeste (2,48) e sul (2,04). Na <xref ref-type="table" rid="t4">tabela 1</xref>, s&#227;o apresentados os valores por ano e regi&#227;o.</p>
        <table-wrap id="t4">
          <label>Tabela 1</label>
          <caption>
            <title>Taxa anual de mortalidade associada a doen&#231;as hipertensivas no Brasil, ajustada para 10.000 habitantes (m&#233;dia e erro padr&#227;o), entre 2010 a 2014</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup>
              <col width="9%"/>
              <col width="9%"/>
              <col width="9%"/>
              <col width="9%"/>
              <col width="9%"/>
              <col width="9%"/>
              <col width="9%"/>
              <col width="9%"/>
              <col width="9%"/>
              <col width="9%"/>
              <col width="9%"/>
            </colgroup>
            <thead>
              <tr>
                <th align="left" rowspan="2" style="background-color:#C5C6C8">Ano</th>
                <th align="center" colspan="2" style="background-color:#C5C6C8">Norte</th>
                <th align="center" colspan="2" style="background-color:#C5C6C8">Nordeste</th>
                <th align="center" colspan="2" style="background-color:#C5C6C8">Centro-Oeste</th>
                <th align="center" colspan="2" style="background-color:#C5C6C8">Sudeste</th>
                <th align="center" colspan="2" style="background-color:#C5C6C8">Sul</th>
              </tr>
              <tr>
                <th align="center" style="background-color:#C5C6C8">&#211;bitos</th>
                <th align="center" style="background-color:#C5C6C8">EP</th>
                <th align="center" style="background-color:#C5C6C8">&#211;bitos</th>
                <th align="center" style="background-color:#C5C6C8">EP</th>
                <th align="center" style="background-color:#C5C6C8">&#211;bitos</th>
                <th align="center" style="background-color:#C5C6C8">EP</th>
                <th align="center" style="background-color:#C5C6C8">&#211;bitos</th>
                <th align="center" style="background-color:#C5C6C8">EP</th>
                <th align="center" style="background-color:#C5C6C8">&#211;bitos</th>
                <th align="center" style="background-color:#C5C6C8">EP</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">2010</td>
                <td align="center">1,12</td>
                <td align="center">0,02</td>
                <td align="center">2,67</td>
                <td align="center">0,02</td>
                <td align="center">2,02</td>
                <td align="center">0,04</td>
                <td align="center">2,52</td>
                <td align="center">0,05</td>
                <td align="center">1,96</td>
                <td align="center">0,02</td>
              </tr>
              <tr>
                <td align="left">2011</td>
                <td align="center">1,38</td>
                <td align="center">0,02</td>
                <td align="center">2,77</td>
                <td align="center">0,02</td>
                <td align="center">2,11</td>
                <td align="center">0,05</td>
                <td align="center">2,57</td>
                <td align="center">0,05</td>
                <td align="center">2,12</td>
                <td align="center">0,02</td>
              </tr>
              <tr>
                <td align="left">2012</td>
                <td align="center">1,31</td>
                <td align="center">0,02</td>
                <td align="center">2,02</td>
                <td align="center">0,02</td>
                <td align="center">2,09</td>
                <td align="center">0,04</td>
                <td align="center">2,52</td>
                <td align="center">0,04</td>
                <td align="center">2,02</td>
                <td align="center">0,02</td>
              </tr>
              <tr>
                <td align="left">2013</td>
                <td align="center">1,17</td>
                <td align="center">0,03</td>
                <td align="center">2,77</td>
                <td align="center">0,03</td>
                <td align="center">2,09</td>
                <td align="center">0,04</td>
                <td align="center">2,41</td>
                <td align="center">0,04</td>
                <td align="center">2,06</td>
                <td align="center">0,02</td>
              </tr>
              <tr>
                <td align="left">2014</td>
                <td align="center">1,26</td>
                <td align="center">0,01</td>
                <td align="center">2,56</td>
                <td align="center">0,02</td>
                <td align="center">2,03</td>
                <td align="center">0,04</td>
                <td align="center">2,39</td>
                <td align="center">0,03</td>
                <td align="center">2,06</td>
                <td align="center">0,02</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN3">
              <p>EP: erro padr&#227;o.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>&#201; poss&#237;vel observar no mapa do Brasil, de forma clara, as regi&#245;es com maiores taxas de mortalidade associadas &#224;s doen&#231;as hipertensivas no ano de 2014, evidenciando tamb&#233;m as regi&#245;es de menores taxas (<xref ref-type="fig" rid="f4">figura 2</xref>).</p>
        <p>
          <fig id="f4">
            <label>Figura 2</label>
            <caption>
              <title>Mapa coropl&#233;tico do Brasil, referente a &#243;bitos por 10.000 habitantes associados a doen&#231;as hipertensivas, no ano de 2014.</title>
            </caption>
            <graphic xlink:href="2359-5647-ijcs-31-03-0250-80017-gf02-pt.jpg"/></fig>
        </p>
        <p>A an&#225;lise feita por estados demonstrou que o Rio de Janeiro teve a maior m&#233;dia, sendo 3,66% de &#243;bitos associados a doen&#231;as hipertensivas no ano de 2010, diminuindo progressivamente at&#233; o ano de 2014, com m&#233;dia de 3,02%, nesse mesmo ano. Em contrapartida, nos anos 2011, 2012, 2013 e 2014, o Piau&#237; obteve a maior m&#233;dia de &#243;bito com rela&#231;&#227;o aos demais estados, sendo 3,80%, 3,58%, 3,87% e 3,61%, respectivamente (<xref ref-type="table" rid="t5">tabela 2</xref>). As maiores taxas de &#243;bito ocorreram em estados da regi&#227;o sudeste e nordeste brasileiro.</p>
        <table-wrap id="t5">
          <label>Tabela 2</label>
          <caption>
            <title>M&#233;dia de &#243;bitos associados a doen&#231;as hipertensivas por 10.000 habitantes, por estado do Brasil, entre 2010 e 2014</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup>
              <col width="16%"/>
              <col width="16%"/>
              <col width="16%"/>
              <col width="16%"/>
              <col width="16%"/>
              <col width="16%"/>
            </colgroup>
            <thead>
              <tr>
                <th align="left" style="background-color:#C5C6C8">Estado</th>
                <th align="center" style="background-color:#C5C6C8">2010</th>
                <th align="center" style="background-color:#C5C6C8">2011</th>
                <th align="center" style="background-color:#C5C6C8">2012</th>
                <th align="center" style="background-color:#C5C6C8">2013</th>
                <th align="center" style="background-color:#C5C6C8">2014</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Acre</td>
                <td align="center">1,20</td>
                <td align="center">1,63</td>
                <td align="center">1,62</td>
                <td align="center">1,39</td>
                <td align="center">1,39</td>
              </tr>
              <tr>
                <td align="left">Alagoas</td>
                <td align="center">2,64</td>
                <td align="center">2,81</td>
                <td align="center">2,87</td>
                <td align="center">2,98</td>
                <td align="center">2,64</td>
              </tr>
              <tr>
                <td align="left">Amap&#225;</td>
                <td align="center">0,61</td>
                <td align="center">1,02</td>
                <td align="center">0,80</td>
                <td align="center">0,71</td>
                <td align="center">0,95</td>
              </tr>
              <tr>
                <td align="left">Amazonas</td>
                <td align="center">1,00</td>
                <td align="center">0,98</td>
                <td align="center">0,99</td>
                <td align="center">1,06</td>
                <td align="center">1,02</td>
              </tr>
              <tr>
                <td align="left">Bahia</td>
                <td align="center">2,27</td>
                <td align="center">2,24</td>
                <td align="center">2,33</td>
                <td align="center">2,35</td>
                <td align="center">2,33</td>
              </tr>
              <tr>
                <td align="left">Cear&#225;</td>
                <td align="center">2,60</td>
                <td align="center">2,85</td>
                <td align="center">2,48</td>
                <td align="center">2,66</td>
                <td align="center">2,49</td>
              </tr>
              <tr>
                <td align="left">Distrito Federal</td>
                <td align="center">1,13</td>
                <td align="center">1,30</td>
                <td align="center">0,99</td>
                <td align="center">1,10</td>
                <td align="center">1,08</td>
              </tr>
              <tr>
                <td align="left">Esp&#237;rito Santo</td>
                <td align="center">2,32</td>
                <td align="center">2,62</td>
                <td align="center">2,64</td>
                <td align="center">2,42</td>
                <td align="center">2,55</td>
              </tr>
              <tr>
                <td align="left">Goi&#225;s</td>
                <td align="center">1,43</td>
                <td align="center">1,52</td>
                <td align="center">1,77</td>
                <td align="center">1,69</td>
                <td align="center">1,81</td>
              </tr>
              <tr>
                <td align="left">Maranh&#227;o</td>
                <td align="center">2,00</td>
                <td align="center">2,13</td>
                <td align="center">1,97</td>
                <td align="center">2,11</td>
                <td align="center">2,07</td>
              </tr>
              <tr>
                <td align="left">Mato Grosso</td>
                <td align="center">2,22</td>
                <td align="center">2,13</td>
                <td align="center">1,97</td>
                <td align="center">2,11</td>
                <td align="center">2,07</td>
              </tr>
              <tr>
                <td align="left">Mato Grosso do Sul</td>
                <td align="center">2,39</td>
                <td align="center">2,68</td>
                <td align="center">2,74</td>
                <td align="center">2,83</td>
                <td align="center">2,52</td>
              </tr>
              <tr>
                <td align="left">Minas Gerais</td>
                <td align="center">2,26</td>
                <td align="center">2,36</td>
                <td align="center">2,40</td>
                <td align="center">2,29</td>
                <td align="center">2,29</td>
              </tr>
              <tr>
                <td align="left">Par&#225;</td>
                <td align="center">1,05</td>
                <td align="center">1,21</td>
                <td align="center">1,27</td>
                <td align="center">1,27</td>
                <td align="center">1,30</td>
              </tr>
              <tr>
                <td align="left">Para&#237;ba</td>
                <td align="center">3,10</td>
                <td align="center">3,26</td>
                <td align="center">3,26</td>
                <td align="center">3,23</td>
                <td align="center">2,88</td>
              </tr>
              <tr>
                <td align="left">Paran&#225;</td>
                <td align="center">2,26</td>
                <td align="center">2,47</td>
                <td align="center">2,26</td>
                <td align="center">2,35</td>
                <td align="center">2,36</td>
              </tr>
              <tr>
                <td align="left">Pernambuco</td>
                <td align="center">2,41</td>
                <td align="center">2,44</td>
                <td align="center">2,29</td>
                <td align="center">2,18</td>
                <td align="center">2,13</td>
              </tr>
              <tr>
                <td align="left">Piau&#237;</td>
                <td align="center">3,51</td>
                <td align="center">3,80</td>
                <td align="center">3,58</td>
                <td align="center">3,87</td>
                <td align="center">3,61</td>
              </tr>
              <tr>
                <td align="left">Rio de Janeiro</td>
                <td align="center">3,66</td>
                <td align="center">3,52</td>
                <td align="center">3,37</td>
                <td align="center">3,23</td>
                <td align="center">3,02</td>
              </tr>
              <tr>
                <td align="left">Rio Grande do Norte</td>
                <td align="center">2,22</td>
                <td align="center">2,54</td>
                <td align="center">2,34</td>
                <td align="center">2,56</td>
                <td align="center">2,44</td>
              </tr>
              <tr>
                <td align="left">Rio Grande do Sul</td>
                <td align="center">1,80</td>
                <td align="center">1,96</td>
                <td align="center">1,99</td>
                <td align="center">1,93</td>
                <td align="center">1,91</td>
              </tr>
              <tr>
                <td align="left">Roraima</td>
                <td align="center">1,07</td>
                <td align="center">1,65</td>
                <td align="center">1,62</td>
                <td align="center">1,54</td>
                <td align="center">1,29</td>
              </tr>
              <tr>
                <td align="left">Santa Catarina</td>
                <td align="center">1,81</td>
                <td align="center">1,92</td>
                <td align="center">1,81</td>
                <td align="center">1,89</td>
                <td align="center">1,92</td>
              </tr>
              <tr>
                <td align="left">S&#227;o Paulo</td>
                <td align="center">1,82</td>
                <td align="center">1,79</td>
                <td align="center">1,69</td>
                <td align="center">1,70</td>
                <td align="center">1,69</td>
              </tr>
              <tr>
                <td align="left">Sergipe</td>
                <td align="center">3,31</td>
                <td align="center">2,88</td>
                <td align="center">3,12</td>
                <td align="center">3,02</td>
                <td align="center">2,49</td>
              </tr>
              <tr>
                <td align="left">Tocantins</td>
                <td align="center">2,91</td>
                <td align="center">3,01</td>
                <td align="center">2,74</td>
                <td align="center">2,72</td>
                <td align="center">2,84</td>
              </tr>
              <tr>
                <td align="left">Rond&#244;nia</td>
                <td align="center">1,79</td>
                <td align="center">1,78</td>
                <td align="center">1,71</td>
                <td align="center">1,67</td>
                <td align="center">1,63</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>No per&#237;odo de 2010 a 2014, o Distrito Federal apresentou taxas de mortalidade semelhantes ao estado de Goi&#225;s, com exce&#231;&#227;o do ano 2012, quando obteve uma das menores taxas de mortalidade no pa&#237;s.</p>
        <p>Um modelo preditivo da taxa de &#243;bitos foi estimado (<xref ref-type="table" rid="t6">tabela 3</xref>). N&#227;o houve diferen&#231;a de mortalidade associada ao sexo, quando ajustada para os demais preditores. No que se refere &#224; faixa et&#225;ria, quanto maior a idade, ocorre uma maior chance de &#243;bitos associados &#224; hipertens&#227;o arterial sist&#234;mica. A cor da pele, tomando-se "brancos" como refer&#234;ncia, indicou maior associa&#231;&#227;o de doen&#231;as hipertensivas com &#243;bitos em "pardos", e menor em "pretos", "amarelos", "ind&#237;genas" e nos casos em que essa vari&#225;vel foi desconhecida. Ressalte-se que o n&#250;mero total de "ind&#237;genas" e "amarelos", somados aos de cor ignorada, foi inferior a 6%. Os "pretos" representaram menos de 12% do grupo de "pardos", "brancos" e "pretos", tendo uma destacada maioria entre os "brancos".</p>
        <table-wrap id="t6">
          <label>Tabela 3</label>
          <caption>
            <title>An&#225;lise longitudinal com modelo binomial negativo, tendo como vari&#225;vel dependente o n&#250;mero de &#243;bitos associados a doen&#231;as hipertensivas, e preditores "faixa et&#225;ria", "sexo", "cor", "regi&#227;o" e "ano", ajustados para a popula&#231;&#227;o anual estimada para cada localidade, entre 2010 e 2014</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup>
              <col width="20%"/>
              <col width="20%"/>
              <col width="20%"/>
              <col width="20%"/>
              <col width="20%"/>
            </colgroup>
            <thead>
              <tr>
                <th align="left" style="background-color:#C5C6C8">&#211;bitos</th>
                <th align="center" style="background-color:#C5C6C8">IRR</th>
                <th align="center" colspan="2" style="border-bottom-width:thin;border-bottom-style:solid;background-color:#C5C6C8">IC a 95%</th>
                <th align="center" style="background-color:#C5C6C8">Valor de p</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Sexo</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
              </tr>
              <tr>
                <td align="left">Feminino (refer&#234;ncia)</td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-</td>
              </tr>
              <tr>
                <td align="left">Masculino</td>
                <td align="center">1,03</td>
                <td align="center">0,99</td>
                <td align="center">1,08</td>
                <td align="center">0,158</td>
              </tr>
              <tr>
                <td align="left">Faixa Et&#225;ria</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
              </tr>
              <tr>
                <td align="left">50 - 59 anos (refer&#234;ncia)</td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-</td>
              </tr>
              <tr>
                <td align="left">60 - 69 anos</td>
                <td align="center">1,63</td>
                <td align="center">1,53</td>
                <td align="center">1,73</td>
                <td align="center">&lt; 0,0001</td>
              </tr>
              <tr>
                <td align="left">70 - 79 anos</td>
                <td align="center">2,40</td>
                <td align="center">2,25</td>
                <td align="center">2,55</td>
                <td align="center">&lt; 0,0001</td>
              </tr>
              <tr>
                <td align="left">&#8805; 80 anos</td>
                <td align="center">3,99</td>
                <td align="center">3,76</td>
                <td align="center">4,26</td>
                <td align="center">&lt; 0,0001</td>
              </tr>
              <tr>
                <td align="left">Cor</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
              </tr>
              <tr>
                <td align="left">Branca (refer&#234;ncia)</td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-</td>
              </tr>
              <tr>
                <td align="left">Preta</td>
                <td align="center">0,27</td>
                <td align="center">0,25</td>
                <td align="center">0,29</td>
                <td align="center">&lt; 0,0001</td>
              </tr>
              <tr>
                <td align="left">Parda</td>
                <td align="center">1,28</td>
                <td align="center">1,20</td>
                <td align="center">1,36</td>
                <td align="center">&lt; 0,0001</td>
              </tr>
              <tr>
                <td align="left">Amarela</td>
                <td align="center">0,01</td>
                <td align="center">0,00</td>
                <td align="center">0,01</td>
                <td align="center">&lt; 0,0001</td>
              </tr>
              <tr>
                <td align="left">Ind&#237;gena</td>
                <td align="center">0,01</td>
                <td align="center">0,01</td>
                <td align="center">0,01</td>
                <td align="center">&lt; 0,0001</td>
              </tr>
              <tr>
                <td align="left">Ignorado</td>
                <td align="center">0,13</td>
                <td align="center">0,12</td>
                <td align="center">0,14</td>
                <td align="center">&lt; 0,0001</td>
              </tr>
              <tr>
                <td align="left">Regi&#227;o</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
              </tr>
              <tr>
                <td align="left">Sudeste (refer&#234;ncia)</td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-</td>
              </tr>
              <tr>
                <td align="left">Norte</td>
                <td align="center">0,43</td>
                <td align="center">0,40</td>
                <td align="center">0,47</td>
                <td align="center">&lt; 0,0001</td>
              </tr>
              <tr>
                <td align="left">Nordeste</td>
                <td align="center">0,96</td>
                <td align="center">0,90</td>
                <td align="center">1,03</td>
                <td align="center">0,237</td>
              </tr>
              <tr>
                <td align="left">Centro-Oeste</td>
                <td align="center">0,73</td>
                <td align="center">0,67</td>
                <td align="center">0,78</td>
                <td align="center">&lt; 0,0001</td>
              </tr>
              <tr>
                <td align="left">Sul</td>
                <td align="center">0,61</td>
                <td align="center">0,57</td>
                <td align="center">0,67</td>
                <td align="center">&lt; 0,0001</td>
              </tr>
              <tr>
                <td align="left">Ano</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
                <td align="center">
								</td>
              </tr>
              <tr>
                <td align="left">2010 (refer&#234;ncia)</td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-</td>
                <td align="center">-</td>
              </tr>
              <tr>
                <td align="left">2011</td>
                <td align="center">1,06</td>
                <td align="center">0,99</td>
                <td align="center">1,14</td>
                <td align="center">0,112</td>
              </tr>
              <tr>
                <td align="left">2012</td>
                <td align="center">1,00</td>
                <td align="center">0,94</td>
                <td align="center">1,08</td>
                <td align="center">0,898</td>
              </tr>
              <tr>
                <td align="left">2013</td>
                <td align="center">0,96</td>
                <td align="center">0,90</td>
                <td align="center">1,03</td>
                <td align="center">0,267</td>
              </tr>
              <tr>
                <td align="left">2014</td>
                <td align="center">0,96</td>
                <td align="center">0,90</td>
                <td align="center">1,03</td>
                <td align="center">0,261</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN4">
              <p>IRR: raz&#227;o de taxa de incid&#234;ncia; IC: &#237;ndice de confian&#231;a.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>Por n&#227;o se tratar de estudo &#233;tnico, por&#233;m levando-se em considera&#231;&#227;o que a cor de pele, como consta no atestado de &#243;bito, tem sido considerada um dado relevante para a elabora&#231;&#227;o de pol&#237;ticas p&#250;blicas de sa&#250;de, a inclus&#227;o desse preditor serviu menos para produzir infer&#234;ncias raciais do que para ajustar esse dado aos demais preditores e estabilizar algoritmos iterativos. Adicionalmente, observou-se que os modelos com inclus&#227;o da vari&#225;vel "cor da pele", se comparados a modelos com a exclus&#227;o desse preditor, al&#233;m de apresentarem preditores com IRRs semelhantes, produziram converg&#234;ncia em menor tempo e valores de AIC mais baixos, indicando maior adequa&#231;&#227;o do ponto de vista estat&#237;stico.</p>
        <p>Tomando-se a regi&#227;o sudeste como refer&#234;ncia, por ter um n&#237;vel de desenvolvimento maior e as pol&#237;ticas p&#250;blicas aplicadas h&#225; mais tempo, n&#227;o houve diferen&#231;a estat&#237;stica quando comparada &#224; regi&#227;o nordeste, apresentando as demais regi&#245;es uma raz&#227;o da taxa de incid&#234;ncia inferior ao sudeste brasileiro.</p>
        <p>O modelo preditivo demonstrou que n&#227;o houve diferen&#231;a estatisticamente significativa da raz&#227;o da taxa de incid&#234;ncia de &#243;bitos entre os anos, quando ajustada para os demais preditores. Igualmente, diferen&#231;a de sexo n&#227;o exerceu influ&#234;ncia. Faixa et&#225;ria elevada, cor parda e regi&#245;es sudeste e nordeste foram preditores de maior mortalidade no per&#237;odo estudado.</p>
      </sec>
      <sec sec-type="discussion">
        <title>Discuss&#227;o</title>
        <p>Foi realizado um estudo epidemiol&#243;gico a partir de dados agregados, obtidos em estratos populacionais. Portanto, a fim de evitar-se a "fal&#225;cia ecol&#243;gica", n&#227;o se pode estender a aplicabilidade dos resultados ao plano individual, ao do consult&#243;rio cl&#237;nico, mas apenas &#224;s esferas estadual, regional e nacional.</p>
        <p>Por tratar-se de dados colhidos em &#243;rg&#227;os p&#250;blicos, os quais, por sua vez, decorreram da notifica&#231;&#227;o constante nas declara&#231;&#245;es de &#243;bito, o presente artigo n&#227;o possui no seu delineamento elementos metodol&#243;gicos capazes de testar a veracidade dos mesmos. Isso igualmente se aplica &#224; quest&#227;o dos itens selecionados nas declara&#231;&#245;es de &#243;bito, que podem apresentar, em potencial, diferen&#231;as de acordo com prefer&#234;ncias de cada estado ou regi&#227;o no que diz respeito a assinalar, com maior ou menor frequ&#234;ncia, a hipertens&#227;o como causa relevante para o &#243;bito.</p>
        <p>O n&#250;mero de &#243;bitos associados a doen&#231;as hipertensivas est&#225; relacionado com o aumento da idade, assim como pode ser observado nesse estudo. O impacto dessa enfermidade tende a acentuar-se, pois a popula&#231;&#227;o idosa aumenta a cada ano, representando atualmente 15% da popula&#231;&#227;o mundial. Proje&#231;&#245;es mundiais indicam que haver&#225; um aumento dessa popula&#231;&#227;o, podendo dobrar esse valor e atingir aproximadamente 30% no ano de 2050. Isso exige aten&#231;&#227;o especial na elabora&#231;&#227;o de medidas preventivas e de controle das doen&#231;as hipertensivas.<xref ref-type="bibr" rid="B16">16</xref>
				</p>
        <p>Em outro estudo, dessa vez de preval&#234;ncia de hipertens&#227;o arterial, as regi&#245;es sudeste e sul do Brasil, se comparadas com as demais, obtiveram maiores taxas, 25% (95% CI: 23,8 - 26,1) e 25% (95% CI: 23,5 - 26,5), respectivamente.<xref ref-type="bibr" rid="B17">17</xref> No presente estudo, por&#233;m, focalizou-se a taxa de mortalidade associada a doen&#231;as hipertensivas, e as regi&#245;es de maiores taxas foram nordeste e sudeste. Embora esse t&#243;pico esteja fora do escopo da presente pesquisa, especula-se que a discrep&#226;ncia entre maior preval&#234;ncia e menor mortalidade na regi&#227;o sul poderia decorrer de quest&#245;es relacionadas &#224; aplica&#231;&#227;o mais intensa de estrat&#233;gias terap&#234;uticas, seja no cuidado assistencial, seja no fornecimento de f&#225;rmacos.</p>
        <p>Um fen&#244;meno oposto, ocorreu em um estado nordestino. Esse estudo mostrou que o estado do Piau&#237; apresentou, durante 4 anos consecutivos, a maior taxa de mortalidade associada a doen&#231;as hipertensivas. Entretanto, uma pesquisa realizada em idosos no ano de 2013, nesse mesmo estado, indicou uma preval&#234;ncia de HAS em idosos igual a 40,2%, sendo abaixo do esperado em idosos, que &#233; de 68% de preval&#234;ncia na popula&#231;&#227;o acima de 60 anos.<xref ref-type="bibr" rid="B4">4</xref><sup>,</sup><xref ref-type="bibr" rid="B18">18</xref> Novamente, em tom especulativo, mas de igual modo fora do escopo da presente pesquisa, esse achado poderia decorrer de obst&#225;culos na assist&#234;ncia ou no acesso a medicamentos.</p>
        <p>Essas considera&#231;&#245;es se destinam fundamentalmente a formular hip&#243;teses a serem analisadas em estudos futuros.</p>
        <p>As taxas de mortalidade associada a doen&#231;as hipertensivas foram maiores em pardos no Brasil, se comparadas a negros, algo que pode ter sido influenciado pela eventual subjetividade na identifica&#231;&#227;o da cor da pele e devido ao predom&#237;nio da miscigena&#231;&#227;o no pa&#237;s.<xref ref-type="bibr" rid="B19">19</xref> Ainda s&#227;o poucos os estudos realizados na Am&#233;rica Latina sobre maior preval&#234;ncia de hipertens&#227;o arterial em negros, e grande parte das informa&#231;&#245;es cient&#237;ficas envolvendo etnicidade prov&#234;m de estudos realizados nos Estados Unidos.<xref ref-type="bibr" rid="B20">20</xref>
				</p>
        <p>S&#227;o v&#225;rias as limita&#231;&#245;es decorrentes desse tipo de estudo, que lida com dados agregados. Por exemplo, n&#227;o se pode afastar a possibilidade de ter ocorrido, de um lado, aumento das notifica&#231;&#245;es e, de outro, melhora do controle dos n&#237;veis press&#243;ricos, algo que geraria uma aparente const&#226;ncia da enfermidade em an&#225;lise de s&#233;ries temporais. Por&#233;m, do ponto de vista metodol&#243;gico, o delineamento da pesquisa buscou ajustar as an&#225;lises para uma eventual influ&#234;ncia de fatores temporais e geogr&#225;ficos na mesma regi&#227;o ou estado.</p>
        <p>Deve-se igualmente ressaltar que foram utilizados os dados atualmente considerados os mais relevantes para a elabora&#231;&#227;o de pol&#237;ticas p&#250;blicas, algo que se reflete no planejamento, execu&#231;&#227;o e avalia&#231;&#227;o das a&#231;&#245;es de sa&#250;de no combate a enfermidades de maior impacto no Brasil.<xref ref-type="bibr" rid="B21">21</xref> Nesse sentido, a implementa&#231;&#227;o da Assist&#234;ncia Farmac&#234;utica pelo Minist&#233;rio da Sa&#250;de tem sido aventada como recurso de grande impacto para reduzir a mortalidade decorrente de doen&#231;as cr&#244;nicas n&#227;o transmiss&#237;veis, incluindo a hipertens&#227;o arterial.<xref ref-type="bibr" rid="B9">9</xref>
				</p>
        <p>N&#227;o obstante, tomando-se como base as informa&#231;&#245;es dispon&#237;veis em registros p&#250;blicos de mortalidade associada a doen&#231;as hipertensivas, e submetendo esses dados a uma avalia&#231;&#227;o complexa, corroborada em diversos modelos anal&#237;ticos, a aus&#234;ncia de redu&#231;&#227;o significativa na taxa de mortalidade no per&#237;odo de cinco anos sugere a necessidade de ampliar o espectro farmacol&#243;gico dos medicamentos de distribui&#231;&#227;o gratuita e intensificar os programas de assist&#234;ncia m&#233;dica, entre outras medidas.</p>
      </sec>
      <sec sec-type="conclusions">
        <title>Conclus&#227;o</title>
        <p>A taxa de mortalidade associada a doen&#231;as hipertensivas foi superior nos estados do sudeste e nordeste do Brasil, quando comparada aos demais estados. Essa taxa n&#227;o apresentou altera&#231;&#245;es significativas entre os anos 2010 a 2014, quando analisada em rela&#231;&#227;o ao mesmo estado e mesma regi&#227;o do Brasil. Outros preditores de maior taxa de mortalidade foram a cor parda e incremento da faixa et&#225;ria. Pol&#237;ticas p&#250;blicas de sa&#250;de, voltadas para o atendimento de hipertensos e preven&#231;&#227;o de complica&#231;&#245;es, devem ser preferencialmente aplicadas nos estados com maiores taxas.</p>
      </sec>
    </body>
    <back>
      <fn-group>
        <fn fn-type="financial-disclosure">
          <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>N&#227;o h&#225; vincula&#231;&#227;o deste estudo a programas de p&#243;s-gradua&#231;&#227;o.</p>
        </fn>
        <fn fn-type="other">
          <p>
            <bold>Aprova&#231;&#227;o &#233;tica e consentimento informado</bold>
          </p>
          <p>Este artigo n&#227;o cont&#233;m estudos com humanos ou animais realizados por nenhum dos autores.</p>
        </fn>
      </fn-group>
    </back>
  </sub-article>
</article>
