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  <front>
    <journal-meta>
      <journal-id journal-id-type="nlm-ta">Arq Bras Cardiol</journal-id>
      <journal-id journal-id-type="publisher-id">abc</journal-id>
      <journal-title-group>
        <journal-title>Arquivos Brasileiros de Cardiologia</journal-title>
        <abbrev-journal-title abbrev-type="publisher">Arq. Bras. Cardiol.</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">0066-782X</issn>
      <issn pub-type="epub">1678-4170</issn>
      <publisher>
        <publisher-name>Sociedade Brasileira de Cardiologia - SBC</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id" specific-use="scielo-v3">FyrYw75pbfrrdspN89DscbC</article-id>
      <article-id pub-id-type="publisher-id" specific-use="scielo-v2">S0066-782X2017000800140</article-id>
      <article-id pub-id-type="doi">10.5935/abc.20170095</article-id>
      <article-id pub-id-type="publisher-id" specific-use="previous-pid">S0066-782X2017005001302</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Original Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Plasma Total Antioxidant Capacity and Cardiometabolic Risk in Non-Obese and Clinically Healthy Young Adults</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Costa</surname>
            <given-names>Jamille Oliveira</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>V&#225;squez</surname>
            <given-names>Cec&#237;lia M. Passos</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Santana</surname>
            <given-names>Gleiciane de Jesus</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Silva</surname>
            <given-names>Natanael de Jesus</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Braz</surname>
            <given-names>Juciene de Matos</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Jesus</surname>
            <given-names>Am&#233;lia M. Ribeiro de</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Silva</surname>
            <given-names>Danielle G&#243;es da</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Cunha</surname>
            <given-names>Luana Celina Seraphim</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Barbosa</surname>
            <given-names>Kiriaque Barra Ferreira</given-names>
          </name>
          <xref ref-type="aff" rid="aff1"/>
          <xref ref-type="corresp" rid="c1"/>
        </contrib>
        <aff id="aff1">
          <institution content-type="orgname">Universidade Federal de Sergipe</institution>
          <addr-line>
            <named-content content-type="city">Aracaju</named-content>
            <named-content content-type="state">SE</named-content>
          </addr-line>
          <country country="BR">Brazil</country>
          <institution content-type="original">Universidade Federal de Sergipe (UFS), Aracaju, SE - Brazil</institution>
          <institution content-type="normalized">Universidade Federal de Sergipe</institution>
        </aff>
      </contrib-group>
      <author-notes>
        <corresp id="c1"><bold>Mailing Address: Kiriaque Barra Ferreira Barbosa,</bold> Av. Marechal Rondon, s/n - Jardim Rosa Else. CEP 49100-000, S&#227;o Crist&#243;v&#227;o, SE - Brazil. E-mail: <email>kiribarra@yahoo.com.br</email>
				</corresp>
        <fn fn-type="con">
          <p>
            <bold>Author contributions</bold>
          </p>
          <p>Conception and design of the research: Jesus AMR, Barbosa KBF; Acquisition of data: Costa JO, V&#225;squez CMP, Santana GJ, Silva NJ, Braz JM, Cunha LCS, Barbosa KBF; Analysis and interpretation of the data: Costa JO; Statistical analysis: Silva DG, Barbosa KBF; Obtaining funding: Barbosa KBF; Writing of the manuscript: Costa JO; Critical revision of the manuscript for intellectual content: Costa JO, Barbosa KBF.</p>
        </fn>
        <fn fn-type="conflict">
          <p>
            <bold>Potential Conflict of Interest</bold>
          </p>
          <p>No potential conflict of interest relevant to this article was reported.</p>
        </fn>
      </author-notes>
      <pub-date pub-type="epub">
        <day>10</day>
        <month>07</month>
        <year>2017</year>
      </pub-date>
      <pub-date pub-type="collection">
        <season>Jul-Aug</season>
        <year>2017</year>
      </pub-date>
      <volume>109</volume>
      <issue>2</issue>
      <fpage>140</fpage>
      <lpage>147</lpage>
      <history>
        <date date-type="received">
          <day>29</day>
          <month>07</month>
          <year>2016</year>
        </date>
        <date date-type="rev-recd">
          <day>10</day>
          <month>11</month>
          <year>2016</year>
        </date>
        <date date-type="accepted">
          <day>15</day>
          <month>03</month>
          <year>2017</year>
        </date>
      </history>
      <permissions>
        <license license-type="open-access" xlink:href="http://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>The oxidative biomarkers play an important role in the genesis of cardiometabolic risk-related processes.</p>
        </sec>
        <sec>
          <title>Objective:</title>
          <p>To investigate the total antioxidant capacity of plasma and its association with cardiometabolic risk in non-obese and clinically healthy young adults.</p>
        </sec>
        <sec>
          <title>Methods:</title>
          <p>University students of the state of Sergipe, Brazil, aged between 18 and 25 years, were recruited for this study from May of 2013 and October of 2014. Anthropometric, clinical and biochemical parameters were measured and analyzed using protocols which were previously standardized and described in the literature. The measurement of plasma total antioxidant capacity was based on the ability that all the antioxidants present in the sample (plasma) have to inhibit the oxidation of the oxidizable substrate ABTS (2,2`- Azino-di-[3-ethylbenzthiazoline sulphonate]) to ABTS&#8226;+ by metmyoglobin.</p>
        </sec>
        <sec>
          <title>Results:</title>
          <p>Approximately 25% of the sample presented more than one component of cardiometabolic risk. Low HDL-cholesterol was the most prevalent component. Compared to absence of components, the subjects with at least one component presented greater body weight and waist circumference, higher levels of diastolic blood pressure and fasting glucose, greater total cholesterol/HDL-c ratio, and lower levels of HDL-c (p &lt; 0.05). Fasting glycemia was the only parameter which was associated with total antioxidant capacity (R<sup>2</sup> = 0.10; &#946; = 0.17; p = 0.001).</p>
        </sec>
        <sec>
          <title>Conclusions:</title>
          <p>The plasma total antioxidant capacity was not able to predict the cardiometabolic risk components due possibly to the establishment of compensatory mechanisms that become activated in physiological conditions.</p>
        </sec>
      </abstract>
      <kwd-group xml:lang="en">
        <title>Keywords:</title>
        <kwd>Cardiovascular Diseases</kwd>
        <kwd>Risk Factors</kwd>
        <kwd>Metabolic Syndrome</kwd>
        <kwd>Oxidative Stress</kwd>
        <kwd>Antioxidants</kwd>
        <kwd>Young Adult</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec sec-type="intro">
      <title>Introduction</title>
      <p>The presence of cardiometabolic risk (CMR) components, such as systemic arterial hypertension, hyperglycemia, abdominal obesity, and lipid profile alterations (e.g. high triglycerides and low HDL-c)<xref ref-type="bibr" rid="B1">1</xref><sup>,</sup><xref ref-type="bibr" rid="B2">2</xref> has been strongly associated with oxidative stress (OS) which is established by the increased expression of oxidizing substances to the detriment of antioxidants.<xref ref-type="bibr" rid="B3">3</xref>
			</p>
      <p>The association between OS and the CMR components has been evidenced due to intense production of reactive oxygen species (ROS) from metabolic alterations, such as increased insulin resistance and visceral adiposity.<xref ref-type="bibr" rid="B4">4</xref>
			</p>
      <p>Total antioxidant capacity (TAC) of plasma is an important biomarker of OS since it defines the synergistic effect between the various antioxidant compounds in the sample.<xref ref-type="bibr" rid="B5">5</xref> The presence of CMR components and chronic non-communicable diseases (NCD) has been associated to lower TAC levels in the population.<xref ref-type="bibr" rid="B6">6</xref> Studies have demonstrated that this decrease in the TAC occurs because of the greater amount ROS as compared to the antioxidant compounds.<xref ref-type="bibr" rid="B7">7</xref><sup>,</sup><xref ref-type="bibr" rid="B8">8</xref>
			</p>
      <p>The presence of CMR components in individuals with NCD is predictable and largely described in the literature since these components are predisposing factors of NCDs.<xref ref-type="bibr" rid="B9">9</xref> OS and inflammation have also been associated with CMR and NCD.<xref ref-type="bibr" rid="B4">4</xref> However, there is still a dearth of investigations with representative data about frequency of CMR components and their predisposing factors among healthy populations in Brazil.</p>
      <p>Therefore, the association between TAC and anthropometric, clinical, and biochemical components of the CMR in non-obese, clinically healthy young adults is still not well elucidated in the literature. The hypothesis of this study is that decreased TAC increases CMR, even in non-obese, healthy young adults. Evaluating changes in CMR components, as well as in their predisposing factors, may be a preventive measure to the development of NCDs, since clinical consequences of NCDs, such as clinical complications, increasing prevalence of premature death, and its social and economic costs may be prevented by interventions.<xref ref-type="bibr" rid="B10">10</xref> The objective of the study was to evaluate the association between TAC of plasma and CMR components in non-obese and clinically healthy young adults.</p>
    </sec>
    <sec sec-type="methods">
      <title>Methods</title>
      <sec>
        <title>Study design</title>
        <p>This is a cross-sectional study on a convenience sample. The volunteers&#8217; recruitment occurred through invitations by email, posters, and classroom visits. The data collection was performed between May of 2013 and October of 2014 at two universities, one public and one private, located in the city of Aracaju, Northeast, Brazil.</p>
      </sec>
      <sec>
        <title>Participants</title>
        <p>Non-obese, clinically healthy young adults, who were students of schools of health sciences, aged between 18 and 25 years of both sexes, participated in the study. Exclusion criteria included the evidence of any disease related to OS, chronic inflammation, gestation, lactation, water-electrolyte imbalance, and self-reported changes in body composition or in absorption and/or metabolism of nutrients. Exclusion criteria still included recent use of medicaments and/or dietary supplements, follow-up of nutritional treatment that may affect energy balance, food consumption, lipid profile, plasma insulin levels, and metabolism of glucose; regular use of birth control pills in the 2 months before the participation in the study; unstable body weight in the past 6 months (10% variation above or below allowed); being an elite athlete or planning to change lifestyle during the period of the study; and follow-up of special diets (e.g. vegetarian diet, Atkins diet, etc.) in the 3 months prior to the participation of the study.</p>
        <p>The sample was calculated according to Miot (2011),<xref ref-type="bibr" rid="B11">11</xref> considering a prevalence of 9.9% for high waist circumference among university students,<xref ref-type="bibr" rid="B12">12</xref> significance level of 5.0%, sampling error of 5.0% and population size of 8,951, considering the number of university students enrolled in health majors. A minimum sample size of 135 individuals was estimated.</p>
      </sec>
      <sec>
        <title>Anthropometric and body composition parameters</title>
        <p>Height was measured to the nearest 1 mm using a stadiometer (Altura Exata, Minas Gerais, Brazil). Weight was measured to the nearest 100 grams using an electronic digital balance (L&#237;der, P 180M, S&#227;o Paulo, Brazil) with maximum capacity of 180 kilograms. Body Mass Index (BMI) was calculated by dividing body weight (kg) by height squared (m) and classified according to the cutoff points proposed by the World Health Organization (WHO).<xref ref-type="bibr" rid="B13">13</xref>
				</p>
        <p>Waist circumference was measured to the nearest 1 mm between the last rib and the iliac crest using a flexible and inelastic tape measure.<xref ref-type="bibr" rid="B13">13</xref>
				</p>
        <p>Triceps, biceps, subscapular, and suprailiac skinfolds thickness were measured to the nearest 1 mm using a skinfold caliper (<italic>Lange caliper, Cambridge Scientific Industries Inc., Cambridge, Maryland, USA</italic>). Truncal fat percentage was calculated from the ratio of the sum of subscapular and suprailiac skinfolds and the sum of the four skinfolds.<xref ref-type="bibr" rid="B14">14</xref>
				</p>
        <p>Body fat percentage was obtained by bioelectrical impedance analysis using a quadrupole device (Biodynamics model 310, Washington, USA), from which body fat and fat-free mass were calculated in kilograms. </p>
      </sec>
      <sec>
        <title>Biochemical measures</title>
        <p>Blood collection was performed by venipuncture after fasting of 12 hours and no intake of alcohol, coffee or tea for 24 hours. Samples of heparin and plasma were separated by centrifugation at 2,465 g to 5&#176;C for 15 minutes and stored at -80&#176;C.</p>
        <p>Serum concentration (mg/dL) of glucose, total cholesterol, high-density lipoprotein (HDL-c), and triglycerides (TG) were analyzed by a colorimetric or turbidimetric assay by an automatic analyzer using specific assay kits.</p>
        <p>TAC in plasma was determined by colorimetric assay using a specific assay kit (Cayman Chemical, Ann Arbor, MI, catalog no. 709001). The assay was based on the ability that all the antioxidants present in the sample (plasma) have to inhibit the oxidation of the oxidizable substrate ABTS (2,2`- Azino-di-[3-ethylbenzthiazoline sulphonate]) to ABTS&#8226;+ by metmyoglobin. The amount of oxidized substrate (ABTS&#8226;+) was monitored by absorbance reading at 750 nm. The decrease in absorbance at 750 nm was directly proportional to the concentration of antioxidants in plasma expressed as mM Trolox equivalents, a synthetic water-soluble analogue of vitamin E.</p>
      </sec>
      <sec>
        <title>Blood pressure</title>
        <p>Systolic and diastolic blood pressure levels were measured to the nearest 2 mmHg using a mercury sphygmomanometer according to Perloff et al.<xref ref-type="bibr" rid="B15">15</xref>
				</p>
      </sec>
      <sec>
        <title>CMR components</title>
        <p>The CMR components were diagnosed according to the criteria of the International Diabetes Federation (2005):<xref ref-type="bibr" rid="B1">1</xref> abdominal obesity (waist circumference &gt;80 cm for women and &gt; 94 cm for men); fasting hyperglycemia (&gt; 100 mg/dL); hypertriglyceridemia (&gt; 150 mg/dL); low HDL-C (&lt; 50 mg/dL for women and &lt; 40 mg/dL for men); and hypertension (systolic pressure &gt; 130 mmHg; diastolic pressure &gt; 85 mmHg).</p>
      </sec>
      <sec>
        <title>Food Consumption and lifestyle variables</title>
        <p>Usual dietary intake was obtained by the application of a semiquantitative food frequency questionnaire (FFQ), developed for this study population. The Virtual Nutri software was used to quantify energy and nutrient intake. Inadequate intake was evaluated according to the recommendation proposed by the Dietary Reference Intakes (DRI) (National Research Council, NRC, 2011),<xref ref-type="bibr" rid="B16">16</xref><sup>,</sup><xref ref-type="bibr" rid="B17">17</xref> using the Estimated Average Requirement (EAR) and the Adequate Intake (AI) values as cutoff points. Inadequate energy intake was determined by the intake &lt; 90% or &gt; 110% from the Estimated Energy Requirement (EER), calculated by predictive equations proposed by the Institute of Medicine (2005).<xref ref-type="bibr" rid="B15">15</xref> Some methodological precautions were adopted around the food consumption assessment, such as the use of visual aids to assist the participants estimate the portion sizes during the FFQ application, training of interviewers, pilot test to clarify questions and inadequacies in the FFQ, and standardization of recipes.</p>
        <p>We collected information on vitamin supplements, smoking, number of cigarettes per day, regular physical activity, and its intensity. To characterize and quantify physical activity, we used the short version of the International Physical Activity Questionnaire (IPAQ), which is recommended by the World Health Organization and has been validated in Brazil by the Center of Studies of the Physical Fitness Research Laboratory of S&#227;o Caetano do Sul - CELAFISCS.<xref ref-type="bibr" rid="B18">18</xref>
				</p>
      </sec>
      <sec>
        <title>Statistical analysis</title>
        <p>Continuous variables were presented as mean &#177; standard deviation while categorical variables as absolute (n) or relative frequency (%).</p>
        <p>Kolmogorov-Smirnov test was used to verify the normality of the distribution. Unpaired Student&#8217;s t-test was adopted to compare the categorized groups by the presence of the CMR components. To track the correlation between TAC and other variables of interest related to the components of the CMR, we used Pearson test. Multivariate linear regression was performed with the fasting glucose values (mg/dL) as being the dependent variable and TAC value (mM), sex and age as being the independent variables. A 95% confidence interval was used to describe the values of the linear regression coefficient (&#946;).</p>
        <p>Statistical significance was accepted at p &lt; 0.05. All analyses were conducted using Statistical Package for Social Science, SPSS version 20.0, for Windows.</p>
      </sec>
      <sec>
        <title>Ethical aspects</title>
        <p>The study was approved by the Human Research Ethics Committee of the Federal University of Sergipe (C.A.A.E.: 0113.0.107.000-11).</p>
        <p>In accordance with the principles of the declaration of Helsinki, all volunteers were informed about the study protocol and then signed the consent form. The volunteers were informed about the methods and procedures used in the data collection, the possible benefits and inconveniences, the privacy of results and the voluntariness of participation.</p>
      </sec>
    </sec>
    <sec sec-type="results">
      <title>Results</title>
      <p>A total of 139 non-obese and clinically healthy young individuals, aged 21.4 &#177; 1.9 years, participated of the study. Women predominated in the distribution of gender (77%). The anthropometric, clinical and biochemical parameters are described in <xref ref-type="table" rid="t1">Table 1</xref>.</p>
      <table-wrap id="t1">
        <label>Table 1</label>
        <caption>
          <title>Demographic, anthropometric, clinical and biochemical characteristics (mean and standard deviation) of non-obese and clinically healthy young adults</title>
        </caption>
        <table frame="hsides" rules="groups">
          <colgroup>
            <col width="33%"/>
            <col width="33%"/>
            <col width="33%"/>
          </colgroup>
          <thead>
            <tr>
              <th align="left">Total (n=139)</th>
              <th align="center">X</th>
              <th align="center">SD</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td align="left">Age (years)</td>
              <td align="center">21.4</td>
              <td align="center">1.9</td>
            </tr>
            <tr>
              <td align="left">Weight (kg)<xref ref-type="table-fn" rid="TFN2">a</xref>
							</td>
              <td align="center">55.9</td>
              <td align="center">7.4</td>
            </tr>
            <tr>
              <td align="left">BMI (kg/m<sup>2</sup>)<xref ref-type="table-fn" rid="TFN2">a</xref>
							</td>
              <td align="center">20.6</td>
              <td align="center">2.1</td>
            </tr>
            <tr>
              <td align="left">WC (cm)<xref ref-type="table-fn" rid="TFN2">a</xref>
							</td>
              <td align="center">71.1</td>
              <td align="center">5.6</td>
            </tr>
            <tr>
              <td align="left">TSF (mm)<xref ref-type="table-fn" rid="TFN2">a</xref>
							</td>
              <td align="center">18.6</td>
              <td align="center">6.8</td>
            </tr>
            <tr>
              <td align="left">BSF (mm)<xref ref-type="table-fn" rid="TFN2">a</xref>
							</td>
              <td align="center">9.6</td>
              <td align="center">5.4</td>
            </tr>
            <tr>
              <td align="left">SISF (mm)<xref ref-type="table-fn" rid="TFN2">a</xref>
							</td>
              <td align="center">16.1</td>
              <td align="center">6.5</td>
            </tr>
            <tr>
              <td align="left">SSF (mm)<xref ref-type="table-fn" rid="TFN2">a</xref>
							</td>
              <td align="center">14.8</td>
              <td align="center">4.4</td>
            </tr>
            <tr>
              <td align="left">Total fat (%)<xref ref-type="table-fn" rid="TFN2">a</xref>
							</td>
              <td align="center">23.0</td>
              <td align="center">9.7</td>
            </tr>
            <tr>
              <td align="left">Truncal fat (%)<xref ref-type="table-fn" rid="TFN2">a</xref>
							</td>
              <td align="center">53.2</td>
              <td align="center">7.0</td>
            </tr>
            <tr>
              <td align="left">Fat mass (kg)<xref ref-type="table-fn" rid="TFN2">a</xref>
							</td>
              <td align="center">12.7</td>
              <td align="center">5.5</td>
            </tr>
            <tr>
              <td align="left">Fat-free mass (kg)<xref ref-type="table-fn" rid="TFN2">a</xref>
							</td>
              <td align="center">43.1</td>
              <td align="center">8.6</td>
            </tr>
            <tr>
              <td align="left">SBP (mmHg)<xref ref-type="table-fn" rid="TFN3">b</xref>
							</td>
              <td align="center">108.8</td>
              <td align="center">8.0</td>
            </tr>
            <tr>
              <td align="left">DBP (mmHg)<xref ref-type="table-fn" rid="TFN3">b</xref>
							</td>
              <td align="center">74.8</td>
              <td align="center">7.8</td>
            </tr>
            <tr>
              <td align="left">Fasting glucose (mg/dL)<xref ref-type="table-fn" rid="TFN4">c</xref>
							</td>
              <td align="center">85.6</td>
              <td align="center">8.4</td>
            </tr>
            <tr>
              <td align="left">Total cholesterol (mg/dL)<xref ref-type="table-fn" rid="TFN5">d</xref>
							</td>
              <td align="center">170.7</td>
              <td align="center">38.5</td>
            </tr>
            <tr>
              <td align="left">HDL-c (mg/dL)<xref ref-type="table-fn" rid="TFN5">d</xref>
							</td>
              <td align="center">56.0</td>
              <td align="center">10.9</td>
            </tr>
            <tr>
              <td align="left">LDL-c (mg/dL)<xref ref-type="table-fn" rid="TFN5">d</xref>
							</td>
              <td align="center">98.9</td>
              <td align="center">33.0</td>
            </tr>
            <tr>
              <td align="left">Triglyceride (mg/dL)<xref ref-type="table-fn" rid="TFN5">d</xref>
							</td>
              <td align="center">78.4</td>
              <td align="center">35.2</td>
            </tr>
            <tr>
              <td align="left">Total cholesterol/HDL-c<xref ref-type="table-fn" rid="TFN5">d</xref>
							</td>
              <td align="center">3.0</td>
              <td align="center">0.7</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN1">
            <p>BMI: body mass index; WC: waist circumference; TSF: triceps skinfold; BSF: biceps skinfold; SISF: suprailiac skinfold; SSF: subscapular skinfold; SBP: systolic blood pressure; DBP: diastolic blood pressure; HDL-c: high-density lipoprotein; LDL-c: low-density lipoprotein.</p>
          </fn>
          <fn id="TFN2">
            <label>a</label>
            <p>n = 123;</p>
          </fn>
          <fn id="TFN3">
            <label>b</label>
            <p>n = 122;</p>
          </fn>
          <fn id="TFN4">
            <label>c</label>
            <p>n = 136;</p>
          </fn>
          <fn id="TFN5">
            <label>d</label>
            <p>n = 137.</p>
          </fn>
          <fn id="TFN6">
            <p>Reference values: waist circumference &lt; 80 cm for women and &lt; 94 cm for men; fasting glucose &#8804; 100 mg/dL; triglyceride &#8804; 150 mg/dL; HDL-c &gt; 50 mg/dL for women and &gt; 40 mg/dL for men; SBP &#8804; 130 mmHg; DBP &#8804; 85 mmHg.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>Although the individuals of this study were non-obese and clinically healthy, they already presented CMR components. About 15% (n = 20) of the sample had low HDL-c concentrations followed by high diastolic blood pressure levels (n = 9; 7%), triglyceride (n = 8; 6%), glucose (n = 6; 4%), and abdominal obesity (n = 3; 2%). Almost one-quarter of the sample (n = 34; 24.5%) had at least one component of the CMR followed by 2 (n = 11; 8%) and 3 or more CMR components (n = 1; 0.7%), respectively.</p>
      <p>Among the nutrient intake inadequacies were considerable those relating to the consumption of saturated fat (n = 114; 92%), fiber (n = 89; 72%), and vitamin D (n = 107; 86%).</p>
      <p>The individuals were categorized by the presence of the CMR components (<xref ref-type="table" rid="t2">Table 2</xref>). Those with at least one component showed greater body weight, TG/HDL-c ratio, and total cholesterol/HDL-c ratio when compared with the individuals who did not present any of the CMR components (p &lt; 0.05).</p>
      <table-wrap id="t2">
        <label>Table 2</label>
        <caption>
          <title>Demographic, anthropometric, clinical and biochemical characteristics (mean and standard deviation) according to the presence of cardiometabolic risk components among non-obese, clinically healthy young adults (n = 139)</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 style="border-bottom-style:solid;border-bottom-width:thin">
              <th align="left" rowspan="2">
							</th>
              <th align="center" colspan="2">No component</th>
              <th align="center" colspan="2">&#8805; 1 component</th>
              <th align="center">
							</th>
            </tr>
            <tr>
              <th align="center">X</th>
              <th align="center">SD</th>
              <th align="center">X</th>
              <th align="center">SD</th>
              <th align="center">p</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td align="left">Age (years)</td>
              <td align="center">21.4</td>
              <td align="center">2.0</td>
              <td align="center">21.9</td>
              <td align="center">1.8</td>
              <td align="center">0.73</td>
            </tr>
            <tr>
              <td align="left">Weight (kg)<xref ref-type="table-fn" rid="TFN8">a</xref>
							</td>
              <td align="center">54.5</td>
              <td align="center">6.7</td>
              <td align="center">60.6</td>
              <td align="center">7.7</td>
              <td align="center">&lt; 0.01</td>
            </tr>
            <tr>
              <td align="left">BMI (kg/m<sup>2</sup>)<xref ref-type="table-fn" rid="TFN8">a</xref>
							</td>
              <td align="center">20.5</td>
              <td align="center">2.0</td>
              <td align="center">29.0</td>
              <td align="center">2.3</td>
              <td align="center">0.28</td>
            </tr>
            <tr>
              <td align="left">Total cholesterol (mg/dL)<xref ref-type="table-fn" rid="TFN11">d</xref>
							</td>
              <td align="center">171.9</td>
              <td align="center">39.5</td>
              <td align="center">166.8</td>
              <td align="center">35.5</td>
              <td align="center">0.50</td>
            </tr>
            <tr>
              <td align="left">LDL-c (mg/dL)<xref ref-type="table-fn" rid="TFN11">d</xref>
							</td>
              <td align="center">99.1</td>
              <td align="center">34.9</td>
              <td align="center">98.3</td>
              <td align="center">26.7</td>
              <td align="center">0.90</td>
            </tr>
            <tr>
              <td align="left">Triglyceride/HDL-c (mg/dL)<xref ref-type="table-fn" rid="TFN11">d</xref>
							</td>
              <td align="center">1.2</td>
              <td align="center">0.5</td>
              <td align="center">2.0</td>
              <td align="center">0.9</td>
              <td align="center">0.00</td>
            </tr>
            <tr>
              <td align="left">Total cholesterol/HDL-<xref ref-type="table-fn" rid="TFN10">c</xref>
								<xref ref-type="table-fn" rid="TFN11">d</xref>
							</td>
              <td align="center">2.9</td>
              <td align="center">0.6</td>
              <td align="center">3.5</td>
              <td align="center">0.8</td>
              <td align="center">&lt; 0.01</td>
            </tr>
            <tr>
              <td align="left">TAC (mM)<xref ref-type="table-fn" rid="TFN11">d</xref>
							</td>
              <td align="center">3.1</td>
              <td align="center">0.6</td>
              <td align="center">2.9</td>
              <td align="center">0.8</td>
              <td align="center">0.23</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN7">
            <p>BMI: body mass index; TAC: total antioxidant capacity; LDL-c: low-density lipoprotein. Data present as mean &#177; standard deviation (X &#177; SD); statistical signicance level of 5%; Student's t-test.</p>
          </fn>
          <fn id="TFN8">
            <label>a</label>
            <p>n = 123;</p>
          </fn>
          <fn id="TFN9">
            <label>b</label>
            <p>n = 122;</p>
          </fn>
          <fn id="TFN10">
            <label>c</label>
            <p>n = 136;</p>
          </fn>
          <fn id="TFN11">
            <label>d</label>
            <p>n = 137</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>Glycemia was the only CMR component which correlated with plasma TAC (<xref ref-type="fig" rid="f1">Figure 1</xref>).</p>
      <p>
        <fig id="f1">
          <label>Figure 1</label>
          <caption>
            <title>Pearson correlation between plasma total antioxidant capacity (TAC) and fasting glycemia values (n = 139).</title>
          </caption>
          <graphic xlink:href="1678-4170-abc-109-02-0140-70095-gf01.jpg"/></fig>
      </p>
      <p>After adjusting the multivariate linear analysis by sex and age, fasting glycemia was positively associated with the TAC values (R<sup>2</sup>= 0.10; &#946; = 0.17; p = 0.001). TAC had a positive predictive effect on the serum glucose levels. An increase by 1 unit in the levels of TAC was associated with an increase by 0.17 mg/dL in fasting glycemia. It is noteworthy that 10.0% of the increase in glycemia was due to the effect of TAC (<xref ref-type="table" rid="t3">Table 3</xref>).</p>
      <table-wrap id="t3">
        <label>Table 3</label>
        <caption>
          <title>Multivariate linear regression analysis with the glycemia (mg/dL) as dependent variable adjusted by sex and age (n = 139)</title>
        </caption>
        <table frame="hsides" rules="groups">
          <colgroup>
            <col width="33%"/>
            <col width="33%"/>
            <col width="33%"/>
          </colgroup>
          <thead>
            <tr>
              <th align="left">
							</th>
              <th align="center">&#946; (95% confidence interval)</th>
              <th align="center">p</th>
            </tr>
          </thead>
          <tbody>
            <tr>
              <td align="left">TAC (mM)</td>
              <td align="center">0.174 (0.135-3.957)</td>
              <td align="center">0.030</td>
            </tr>
            <tr>
              <td align="left">Sex</td>
              <td align="center">0.267 (2.099-8.553)</td>
              <td align="center">0.001</td>
            </tr>
            <tr>
              <td align="left">Age</td>
              <td align="center">&#8211;0.132 (-1.243-0.128)</td>
              <td align="center">0.110</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn id="TFN12">
            <p>R<sup>2</sup> = 0.100, p = 0.001. TAC: total antioxidant capacity.</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
    </sec>
    <sec sec-type="discussion">
      <title>Discussion</title>
      <p>The study about the CMR components has attracted attention since they are strongly related to the development of diseases associated with insulin resistance and cardiovascular events, which are the major causes of morbidity and mortality in the population.<xref ref-type="bibr" rid="B19">19</xref> These diseases have direct and indirect impact on social and state economy, including low productivity, loss of working days, damage to the productive sector, and intangible costs of people affected by these conditions.<xref ref-type="bibr" rid="B10">10</xref><sup>,</sup><xref ref-type="bibr" rid="B20">20</xref>
			</p>
      <p>Determining the presence of CMR components in young populations is relevant for the early diagnosis, and establishment of specific interventions and preventive measures. In our study population, although the prevalence of alterations in the outcome measures was low - according to the proposed reference values - almost one-quarter of the sample had at least one component of the CMR. Low HDL-c was the most prevalent component (15%). On the other hand, studies on college students, both in Brazil<xref ref-type="bibr" rid="B20">20</xref> and in other countries,<xref ref-type="bibr" rid="B21">21</xref><sup>,</sup><xref ref-type="bibr" rid="B22">22</xref> have found higher prevalence. This controversy may be related to the characteristics of our population, composed of physically active (65%), non-smoking, university students from health sciences area, mainly nutrition (39%), and with low prevalence of alcohol consumption.</p>
      <p>The prevalence of CMR components in college populations in national<xref ref-type="bibr" rid="B23">23</xref> and international<xref ref-type="bibr" rid="B21">21</xref><sup>,</sup><xref ref-type="bibr" rid="B22">22</xref> studies varied from 30 to 77% among individuals with at least one risk component, from 12 to 13% for those with two, and from 3 to 16% for those with three components. Low HDL-c and high blood pressure are the most prevalent CMR components.</p>
      <p>The early development of these components in young adults has been attributed to poor eating habits, commonly observed in young populations, due to factors related to this life stage, including independence, inability to make healthy food choices, lack of time, convenience, costs, and influence of both physical and social environments.<xref ref-type="bibr" rid="B24">24</xref> The result of this combination is the greater weight gain in the first year of college when compared to adulthood.<xref ref-type="bibr" rid="B25">25</xref>
			</p>
      <p>In this study, it was observed that the presence of at least one risk component in the study population was associated with greater anthropometric (body weight) and biochemical (TG/HDL-c and total cholesterol/HDL-c ratios) parameters. These results are corroborated by studies conducted with college students from Brazil<xref ref-type="bibr" rid="B23">23</xref> and from other countries.<xref ref-type="bibr" rid="B21">21</xref><sup>,</sup><xref ref-type="bibr" rid="B22">22</xref>
			</p>
      <p>TG/HDL-c ratio has been largely discussed as an atherogenic risk indicator for predicting the development of coronary artery disease,<xref ref-type="bibr" rid="B26">26</xref> acute myocardial infarction,<xref ref-type="bibr" rid="B27">27</xref> and atherosclerosis.<xref ref-type="bibr" rid="B28">28</xref> Studies have showed that high values of TG/HDL-c are correlated with increased CMR in the population.<xref ref-type="bibr" rid="B22">22</xref><sup>,</sup><xref ref-type="bibr" rid="B29">29</xref> In addition, TG/HDL-c ratio has been positively correlated with biochemical (total cholesterol, LDL-c, and TG) and anthropometric parameters (BMI, waist circumference, and body fat percentage) and negatively with HDL-c.<xref ref-type="bibr" rid="B30">30</xref>
			</p>
      <p>The presence of the CMR components, such as abdominal obesity,<xref ref-type="bibr" rid="B31">31</xref> hypertriglyceridemia, low HDL-c and hypertension,<xref ref-type="bibr" rid="B32">32</xref><sup>,</sup><xref ref-type="bibr" rid="B33">33</xref> has been associated to the development of NCDs, especially, type 2 diabetes, cardiovascular diseases, and cancer. In Brazil, a study was conducted to evaluate the association between cardiovascular risk factors and anthropometric indicators in patients with NCD.<xref ref-type="bibr" rid="B34">34</xref> The authors found that 74% of the sample presented glycemia &gt; 100 mg/dL, 56% low HDL-c, 82% high waist circumference, and 78% overweight.<xref ref-type="bibr" rid="B34">34</xref>
			</p>
      <p>Excessive ROS production is another factor that has been associated with the presence of CMR components and, consequently, to the development of NCDs.<xref ref-type="bibr" rid="B4">4</xref><sup>,</sup><xref ref-type="bibr" rid="B6">6</xref> Several studies have identified the association between plasma TAC -an important biomarker of OS for expressing the synergistic action between various antioxidant compounds<xref ref-type="bibr" rid="B5">5</xref> - and alterations in the anthropometric, clinical and biochemical CMR components.<xref ref-type="bibr" rid="B6">6</xref> It is worth mentioning that all these studies were conducted with individuals with NCDs. There is still a dearth of studies with healthy individuals.</p>
      <p>Although the individuals of the present study were non-obese and clinically healthy, it was possible to identify an association between TAC and fasting glycemia after adjustment by sex and age (R<sup>2</sup>= 0.10, &#946; = 0.17, p = 0.001). The positive correlation between TAC and fasting glucose found in the study does not corroborate with the literature.<xref ref-type="bibr" rid="B35">35</xref> Hyperglycemia increases the expression of OS by the increase of NADPH concentrations and ROS production due to the intense mitochondrial metabolism of glucose.<xref ref-type="bibr" rid="B36">36</xref> This results in an increased production of electron donors (FADH2 and NADH) in the Krebs cycle and, hence, in a high mitochondrial membrane potential (DmH+) by pumping protons across the inner membrane, inhibiting electron transport at complex III, and increasing the half-life of free-radical intermediates of coenzyme Q (ubiquinone) which reduces O<sub>2</sub> to superoxide. Thus, studies have shown a negative correlation between fasting glycemia and plasma and dietary TAC,<xref ref-type="bibr" rid="B37">37</xref> as well as greater amount of products from oxidative reactions, which reduce the level of the substances that make up the antioxidant system.<xref ref-type="bibr" rid="B38">38</xref> However, all these studies were conducted with individuals with NCD already established.</p>
      <p>Due to the characteristics of the participants of this study -young, clinically healthy, and non-obese, and the high TAC, one may suggest the establishment of an adaptive mechanism based on the evidence that the increase of 1 unit in the TAC levels (1mM) is associated to the increase of 0.17 mg/dL in the fasting glycemia levels, <italic>i.e</italic>., increased glycemia in homeostasis would determine a compensatory increase of the TAC. This occurs through negative feedback which may activate the enzymatic pathways of the antioxidant system to reduce the intracellular levels of ROS, thereby minimizing oxidative damage.<xref ref-type="bibr" rid="B39">39</xref> The findings by Demirbag et al.<xref ref-type="bibr" rid="B35">35</xref> corroborate this assumption. The increase in TAC becomes impracticable in pathologic conditions already set in, different from what occurs in health individuals.</p>
      <p>The lack of associations between TAC and the other anthropometric, clinical and biochemical variables in the study may be explained by the low prevalence of alterations on these parameters and by the characteristics of the studied population: young, predominantly women, non-obese, clinically healthy, physically active, students of health sciences, low alcohol consumption, non-smokers, and markers of adiposity - waist circumference (71.1 &#177; 5.6 cm) and body fat percentage (23.0 &#177; 9.7%) - below the risk for triggering metabolic alterations. Nevertheless, it is worth pointing out the high TAC value found in the present study (3.10 &#177; 0.71; median = 3.09 mM) compared to the values found by Barbosa et al.<xref ref-type="bibr" rid="B40">40</xref> in young adults (1.60 mM). This result may be associated with the low prevalence of behavioral risk factors, such as sedentary life style (36%), low consumption of alcohol, being non-smoker, in addition to be university students in health sciences.</p>
      <p>Some limitations in this study must be acknowledged: the sample loss of some variables due to incomplete information and/or study dropout; the assessment of food consumption by instruments available in the literature are subject to error because of their large inter- and intra-individual variability, as well as the dependence on the respondents' memory about past habits, low accuracy in quantifying the intake due to the use of standardized measures and food lists. Finally, the methods used to evaluate plasma TAC strictly reflect chemical reactions <italic>in vitro</italic>, without similarity to biological systems. Their results should therefore be interpreted with caution since they do not measure bioavailability, <italic>in vivo</italic> stability, retention of antioxidants in the tissues, and <italic>in situ</italic> reactivity.</p>
    </sec>
    <sec sec-type="conclusions">
      <title>Conclusions</title>
      <p>In this study, CMR components were present in some young, clinically healthy, non-obese, and high-TAC adults.</p>
      <p>The observed positive correlation between plasma TAC and fasting glycemia suggests the establishment of an adaptive mechanism. The increase in glycemia in a biological system, in homeostasis, would determine a compensatory increase of the plasma TAC.</p>
      <p>Thus, different from what occurs in populations with NCD already set in, TAC was not associated with CMR components in this sample of young, non-obese and clinically healthy individuals due possibly to the establishment of compensatory mechanisms that become activated in physiological conditions.</p>
    </sec>
  </body>
  <back>
    <fn-group>
      <fn fn-type="supported-by">
        <p>
          <bold>Sources of Funding</bold>
        </p>
        <p>This study was funded by Funda&#231;&#227;o de Apoio &#224; Pesquisa e &#224; Inova&#231;&#227;o Tecnol&#243;gica do Estado de Sergipe.</p>
      </fn>
      <fn fn-type="other">
        <p>
          <bold>Study Association</bold>
        </p>
        <p>This article is part of the thesis of master submitted by de Jamille Oliveira Costa, from Universidade Federal de Sergipe.</p>
      </fn>
    </fn-group>
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  <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>Capacidade Antioxidante Total do Plasma e Risco Cardiometab&#243;lico em Adultos Jovens, N&#227;o Obesos e Clinicamente Saud&#225;veis</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Costa</surname>
            <given-names>Jamille Oliveira</given-names>
          </name>
          <xref ref-type="aff" rid="aff2"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>V&#225;squez</surname>
            <given-names>Cec&#237;lia M. Passos</given-names>
          </name>
          <xref ref-type="aff" rid="aff2"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Santana</surname>
            <given-names>Gleiciane de Jesus</given-names>
          </name>
          <xref ref-type="aff" rid="aff2"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Silva</surname>
            <given-names>Natanael de Jesus</given-names>
          </name>
          <xref ref-type="aff" rid="aff2"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Braz</surname>
            <given-names>Juciene de Matos</given-names>
          </name>
          <xref ref-type="aff" rid="aff2"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Jesus</surname>
            <given-names>Am&#233;lia M. Ribeiro de</given-names>
          </name>
          <xref ref-type="aff" rid="aff2"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Silva</surname>
            <given-names>Danielle G&#243;es da</given-names>
          </name>
          <xref ref-type="aff" rid="aff2"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Cunha</surname>
            <given-names>Luana Celina Seraphim</given-names>
          </name>
          <xref ref-type="aff" rid="aff2"/>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Barbosa</surname>
            <given-names>Kiriaque Barra Ferreira</given-names>
          </name>
          <xref ref-type="aff" rid="aff2"/>
          <xref ref-type="corresp" rid="c2"/>
        </contrib>
        <aff id="aff2">
          <institution content-type="original">Universidade Federal de Sergipe (UFS), Aracaju, SE - Brasil</institution>
        </aff>
      </contrib-group>
      <author-notes>
        <corresp id="c2"><bold>Correspond&#234;ncia: Kiriaque Barra Ferreira Barbosa,</bold> Av. Marechal Rondon, s/n - Jardim Rosa Else. CEP 49100-000, S&#227;o Crist&#243;v&#227;o, SE - Brasil. E-mail: <email>kiribarra@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: Jesus AMR, Barbosa KBF, Obten&#231;&#227;o de dados: Costa JO, V&#225;squez CMP, Santana GJ, Silva NJ, Braz JM, Cunha LCS, Barbosa KBF; An&#225;lise e interpreta&#231;&#227;o dos dados: Costa JO; An&#225;lise estat&#237;stica: Silva DG, Barbosa KBF; Obten&#231;&#227;o de financiamento: Barbosa KBF; Reda&#231;&#227;o do manuscrito: Costa JO; Revis&#227;o cr&#237;tica do manuscrito quanto ao conte&#250;do intelectual importante: Costa JO, Barbosa KBF.</p>
        </fn>
        <fn fn-type="conflict">
          <p>
            <bold>Potencial conflito de interesses</bold>
          </p>
          <p>Declaro n&#227;o haver conflito de interesses pertinentes.</p>
        </fn>
      </author-notes>
      <abstract>
        <title>Resumo</title>
        <sec>
          <title>Fundamentos:</title>
          <p>Os biomarcadores oxidativos exercem um importante papel na g&#234;nese dos processos relacionados ao risco cardiometab&#243;lico.</p>
        </sec>
        <sec>
          <title>Objetivo:</title>
          <p>Investigar a capacidade antioxidante total do plasma e sua associa&#231;&#227;o com risco cardiometab&#243;lico em adultos jovens, n&#227;o obesos e clinicamente saud&#225;veis.</p>
        </sec>
        <sec>
          <title>M&#233;todos:</title>
          <p>Estudantes universit&#225;rios do estado de Sergipe, Brasil, com idade entre 18 e 25 anos, foram recrutados entre maio de 2013 e outubro de 2014. Par&#226;metros antropom&#233;tricos, cl&#237;nicos e bioqu&#237;micos foram medidos e analisados usando protocolos previamente padronizados e descritos na literatura. A medida da capacidade antioxidante total do plasma baseou-se na capacidade de todos os antioxidantes presentes na amostra (plasma) em inibir a oxida&#231;&#227;o do substrato oxid&#225;vel ABTS (2,2-Azino-bis-(3-etilbenzotiazolina-6-sulfonato) a ABTS&#8226;+ pela metamioglobina.</p>
        </sec>
        <sec>
          <title>Resultados:</title>
          <p>Aproximadamente 25% da amostra apresentaram mais de um componente do risco cardiometab&#243;lico. Valores baixos de HDL foram o componente mais prevalente. Em compara&#231;&#227;o &#224; aus&#234;ncia de componentes, os indiv&#237;duos com pelo menos um componente apresentou valores mais altos de peso corporal, circunfer&#234;ncia da cintura, press&#227;o sangu&#237;nea diast&#243;lica, glicemia de jejum e raz&#227;o colesterol total/HDL-c, e valores mais baixos de HDL-c (p &lt; 0,05). A glicemia de jejum foi o &#250;nico par&#226;metro que se associou com a capacidade antioxidante total (R<sup>2</sup> = 0,10; &#946; = 0,17; p = 0,001).</p>
        </sec>
        <sec>
          <title>Conclus&#245;es:</title>
          <p>A capacidade antioxidante total n&#227;o foi capaz de predizer os componentes do risco cardiometab&#243;lico possivelmente devido ao estabelecimento de mecanismos compensat&#243;rios que se tornam ativados em condi&#231;&#245;es fisiol&#243;gicas. </p>
        </sec>
      </abstract>
      <kwd-group xml:lang="pt">
        <title>Palavras-chave:</title>
        <kwd>Doen&#231;as Cardiovasculares</kwd>
        <kwd>Fatores de Risco</kwd>
        <kwd>S&#237;ndrome Metab&#243;lica</kwd>
        <kwd>Estresse Oxidativo</kwd>
        <kwd>Antioxidantes</kwd>
        <kwd>Adulto Jovem</kwd>
      </kwd-group>
    </front-stub>
    <body>
      <sec sec-type="intro">
        <title>Introdu&#231;&#227;o</title>
        <p>A presen&#231;a de componentes do risco cardiometab&#243;lico (RCM), tais como hipertens&#227;o arterial sist&#234;mica, hiperglicemia, obesidade abdominal, e mudan&#231;as no perfil lip&#237;dico (p.ex. valores altos de triglicer&#237;deos e baixos de HDL-c),<xref ref-type="bibr" rid="B1">1</xref><sup>,</sup><xref ref-type="bibr" rid="B2">2</xref> tem sido fortemente associada com estresse oxidativo (EO), o qual &#233; estabelecido pela express&#227;o aumentada de subst&#226;ncias oxidantes em detrimento das subst&#226;ncias antioxidantes.<xref ref-type="bibr" rid="B3">3</xref>
				</p>
        <p>A associa&#231;&#227;o entre EO e componentes do RCM foi evidenciada devido &#224; intensa produ&#231;&#227;o de esp&#233;cies reativas de oxig&#234;nio (EROS) a partir de mudan&#231;as metab&#243;licas, tais como aumento da resist&#234;ncia &#224; insulina e adiposidade visceral.<xref ref-type="bibr" rid="B4">4</xref>
				</p>
        <p>A capacidade antioxidante total (CAT) &#233; um importante biomarcador de EO, uma vez que ela define o efeito sin&#233;rgico entre os v&#225;rios componentes antioxidantes na amostra.<xref ref-type="bibr" rid="B5">5</xref> A presen&#231;a de componentes do RCM e doen&#231;a cr&#244;nicas n&#227;o transmiss&#237;veis (DCNT) foi associada com menor CAT na popula&#231;&#227;o.<xref ref-type="bibr" rid="B6">6</xref> Estudos demonstraram que essa diminui&#231;&#227;o da CAT ocorre devido &#224; maior quantidade de EROS em compara&#231;&#227;o aos componentes antioxidantes.<xref ref-type="bibr" rid="B7">7</xref><sup>,</sup><xref ref-type="bibr" rid="B8">8</xref>
				</p>
        <p>A presen&#231;a de componentes do RCM em indiv&#237;duos com DCNT &#233; previs&#237;vel e amplamente descrita na literatura, uma vez que esses componentes s&#227;o fatores que predisp&#245;em essas doen&#231;as.<xref ref-type="bibr" rid="B9">9</xref> O EO e a inflama&#231;&#227;o tamb&#233;m foram associados com RCM e DCNT.<xref ref-type="bibr" rid="B4">4</xref> No entanto, h&#225; ainda poucos estudos com dados representativos sobre a frequ&#234;ncia de componentes do RCM e seus fatores predisponentes nas popula&#231;&#245;es sadias no Brasil.</p>
        <p>Portanto, ainda n&#227;o est&#225; bem elucidada na literatura cient&#237;fica a associa&#231;&#227;o da CAT com par&#226;metros antropom&#233;tricos, bioqu&#237;micos e cl&#237;nicos e componentes do RCM em adultos jovens n&#227;o-obesos e clinicamente saud&#225;veis. A hip&#243;tese deste estudo &#233; que uma CAT reduzida aumenta o RCM, mesmo em adultos jovens sadios n&#227;o-obesos. A avalia&#231;&#227;o da presen&#231;a de altera&#231;&#245;es nesses componentes, bem como em seus fatores predisponentes, pode ser uma medida preventiva ao desenvolvimento de DCNTs, uma vez que essas doen&#231;as s&#227;o pass&#237;veis de interven&#231;&#245;es a fim de se evitar consequ&#234;ncias cl&#237;nicas, tais como aumento da preval&#234;ncia da mortalidade prematura, suas complica&#231;&#245;es e custos sociais e econ&#244;micos.<xref ref-type="bibr" rid="B10">10</xref> O objetivo deste estudo foi avaliar a associa&#231;&#227;o entre CAT no plasma e componentes do RCM em jovens adultos n&#227;o obesos e clinicamente saud&#225;veis.</p>
      </sec>
      <sec sec-type="methods">
        <title>M&#233;todos</title>
        <sec>
          <title>Delineamento do estudo</title>
          <p>Este &#233; um estudo transversal de uma amostra de conveni&#234;ncia. O recrutamento dos volunt&#225;rios foi feito por convites via e-mail, p&#244;steres, e visitas &#224;s salas de aula. A coleta de dados foi realizada entre maio de 2013 e outubro de 2014 em duas universidades, uma p&#250;blica e uma privada, localizadas em Aracaju, Brasil.</p>
        </sec>
        <sec>
          <title>Participantes</title>
          <p>Participaram do estudo adultos jovens, n&#227;o obesos e clinicamente saud&#225;veis de ambos os sexos, com idade entre 18 e 25 anos, estudantes de faculdades de cursos da &#225;rea da sa&#250;de. Os crit&#233;rios de exclus&#227;o inclu&#237;ram evid&#234;ncia de qualquer doen&#231;a relacionada a EO, inflama&#231;&#227;o cr&#244;nica, gesta&#231;&#227;o, lacta&#231;&#227;o, desequil&#237;brio hidroeletrol&#237;tico, e mudan&#231;as relatadas pelo participante na composi&#231;&#227;o corporal, ou na absor&#231;&#227;o e/ou no metabolismo de nutrientes. Os crit&#233;rios de exclus&#227;o tamb&#233;m inclu&#237;ram o uso recente de medicamentos e/ou suplementos diet&#233;ticos, tratamento nutricional que pudesse afetar o equil&#237;brio energ&#233;tico, consumo de alimentos, perfil lip&#237;dico, n&#237;veis plasm&#225;ticos de insulina, e metabolismo da glicose; uso regular de p&#237;lulas anticoncepcionais nos 2 meses anteriores ao estudo, peso inst&#225;vel nos &#250;ltimos 6 meses (10% de varia&#231;&#227;o acima ou abaixo o permitido); ser um atleta de elite ou planejar mudar seu estilo de vida durante o per&#237;odo de estudo; e seguimento de dietas especiais (p.ex. dieta vegetariana, Atkins etc.) nos 3 meses anteriores ao estudo.</p>
          <p>A amostra foi calculada de acordo com Miot,<xref ref-type="bibr" rid="B11">11</xref> considerando uma preval&#234;ncia de 9,9% de circunfer&#234;ncia elevada entre estudantes universit&#225;rios,<xref ref-type="bibr" rid="B12">12</xref> n&#237;vel de signific&#226;ncia de 5%, erro de amostragem de 5%, e tamanho populacional de 8951, considerando o n&#250;mero de estudantes universit&#225;rios matriculados em disciplinas da sa&#250;de. Foi estimado um tamanho amostral m&#237;nimo de 135 indiv&#237;duos.</p>
        </sec>
        <sec>
          <title>Par&#226;metros antropom&#233;tricos e de composi&#231;&#227;o corporal</title>
          <p>A altura foi medida usando-se um estadi&#244;metro com 1 mm de precis&#227;o (Altura Exata, Minas Gerais, Brasil). O peso foi medido usando uma balan&#231;a digital com precis&#227;o de 100 g (L&#237;der, P 180M, S&#227;o Paulo, Brasil) e capacidade m&#225;xima de 180 kg. O &#237;ndice de massa corporal (IMC) foi calculado dividindo-se o peso (kg) pela altura ao quadrado (m), e classificado de acordo com os pontos de corte propostos pela Organiza&#231;&#227;o Mundial de Sa&#250;de (OMS).<xref ref-type="bibr" rid="B13">13</xref>
					</p>
          <p>A circunfer&#234;ncia da cintura foi aferida na menor curvatura entre a &#250;ltima costela e a crista il&#237;aca, utilizando-se fita m&#233;trica flex&#237;vel e inel&#225;stica, com sensibilidade de 1 mil&#237;metro.<xref ref-type="bibr" rid="B13">13</xref>
					</p>
          <p>As pregas cut&#226;neas tricipital, subescapular, e suprail&#237;aca foram medidas com um adip&#244;metro (Lange caliper, Cambridge Scientific Industries Inc., Cambridge, Maryland, USA) com 1 mm de precis&#227;o. A porcentagem da gordura do tronco foi calculada a partir da raz&#227;o entre a soma das pregas subescapular e suprail&#237;aca e a soma das quatro pregas.<xref ref-type="bibr" rid="B14">14</xref>
					</p>
          <p>A porcentagem de gordura corporal foi obtida por bioimped&#234;ncia el&#233;trica, usando um aparelho quadripolar (Biodynamics model 310, Washington, USA), com o qual a massa de gordura corporal e a massa livre de gordura foram calculadas em quilogramas.</p>
        </sec>
        <sec>
          <title>Medidas bioqu&#237;micas</title>
          <p>A coleta de sangue foi realizada por pun&#231;&#227;o venosa ap&#243;s 12 horas de jejum e sem ingest&#227;o de &#225;lcool, caf&#233; ou ch&#225; por 24 horas. As amostras de heparina e plasma foram separadas por centrifuga&#231;&#227;o a 2465 g a 5&#176;C por 15 minutos e armazenadas a -80&#176;C.</p>
          <p>Concentra&#231;&#245;es s&#233;rias (mg/dL) de glicose, colesterol total, lipoprote&#237;na de alta densidade (HDL-c) e triglicer&#237;deos, foram analisadas por m&#233;todo colorim&#233;trico ou turbidim&#233;trico por um aparelho autom&#225;tico e kits espec&#237;ficos.</p>
          <p>A CAT foi determinada por teste colorim&#233;trico usando um kit espec&#237;fico (Cayman Chemical, Ann Arbor, MI, catalog no. 709001). O teste foi baseado na capacidade de todos os antioxidantes presentes na amostra (plasma) em inibir a oxida&#231;&#227;o do substrato oxid&#225;vel ABTS (2,2-Azino-bis-(3-etilbenzotiazolina-6-sulfonato) a ABTS&#8226;+ pela metamioglobina. A quantidade de substrato oxidado (ABTS&#8226;+) foi monitorada pela leitura de absorb&#226;ncia a 750 nm. A diminui&#231;&#227;o na absorb&#226;ncia a 740 nm foi diretamente proporcional &#224; concentra&#231;&#227;o de antioxidantes no plasma, expressos como equivalentes de Trolox (mM), um an&#225;logo sint&#233;tico hidrossol&#250;vel da vitamina E.</p>
        </sec>
        <sec>
          <title>Press&#227;o sangu&#237;nea</title>
          <p>A press&#227;o sist&#243;lica e diast&#243;lica foram medidas usando um esfigmoman&#244;metro de merc&#250;rio com precis&#227;o de 2 mmHg de acordo com Perloff et al.<xref ref-type="bibr" rid="B15">15</xref>
					</p>
        </sec>
        <sec>
          <title>Componentes do RCM</title>
          <p>Os componentes do RCM foram diagnosticados segundo crit&#233;rios da Federa&#231;&#227;o Internacional do Diabetes:<xref ref-type="bibr" rid="B1">1</xref> obesidade abdominal (circunfer&#234;ncia da cintura &gt; 80 cm para mulheres e &gt; 94 cm para homens); hiperglicemia de jejum (&gt; 100 mg/dL); hipertrigliceridemia (&gt; 150 mg/dL); baixo HDL-c (&lt; 50 mg/dL para mulheres e &lt; 40/dL para homens); e hipertens&#227;o (press&#227;o sist&#243;lica &gt; 130 mmHg; press&#227;o diast&#243;lica &gt; 85 mmHg).</p>
        </sec>
        <sec>
          <title>Consumo alimentar e vari&#225;veis de estilo de vida</title>
          <p>A ingest&#227;o diet&#233;tica di&#225;ria habitual foi obtido pela aplica&#231;&#227;o de um question&#225;rio de frequ&#234;ncia alimentar (QFA) semiquantitativo desenvolvido para a popula&#231;&#227;o deste estudo. O programa Virtual Nutri foi usado para quantificar a ingest&#227;o energ&#233;tica e de nutrientes. A ingest&#227;o inadequada foi avaliada de acordo com as recomenda&#231;&#245;es propostas pelo <italic>Dietary Reference Intakes</italic> (DRI) (<italic>National Research Council, NRC</italic>,<xref ref-type="bibr" rid="B16">16</xref><sup>,</sup><xref ref-type="bibr" rid="B17">17</xref> utilizando os valores da necessidade m&#233;dia estimada (<italic>Estimated Average Requirement, EAR</italic>) e da ingest&#227;o adequada (<italic>Adequate Intake, AI</italic>) como pontos de corte. A inadequa&#231;&#227;o do consumo energ&#233;tico foi estabelecida para a ingest&#227;o &lt; 90% ou &gt; 110% da Necessidade Energ&#233;tica Estimada (NEE), calculada por equa&#231;&#245;es preditivas proposta pelo Institute of Medicine.<xref ref-type="bibr" rid="B16">16</xref> Foram adotadas algumas precau&#231;&#245;es metodol&#243;gicas em rela&#231;&#227;o &#224; avalia&#231;&#227;o do consumo alimentar, tais como o uso de recursos visuais para auxiliar os participantes a estimarem os tamanhos das por&#231;&#245;es durante a aplica&#231;&#227;o do QFA, treinamento dos entrevistadores, teste piloto para esclarecer quest&#245;es e inadequa&#231;&#245;es do question&#225;rio, e padroniza&#231;&#227;o das receitas.</p>
          <p>Coletamos informa&#231;&#245;es sobre suplementos vitam&#237;nicos, tabagismo, n&#250;mero de cigarros por dia, atividade f&#237;sica regular e sua intensidade. Para caracterizar e quantificar atividade f&#237;sica, usamos a vers&#227;o reduzida do Question&#225;rio Internacional de Atividade F&#237;sica (<italic>International Physical Activity Questionnaire</italic>, QIAF). Esse instrumento &#233; recomendado pela Organiza&#231;&#227;o Mundial de Sa&#250;de, e foi validado no Brasil pelo Centro de Estudos do Laborat&#243;rio de Aptid&#227;o F&#237;sica de S&#227;o Caetano do Sul - CELAFISCS.<xref ref-type="bibr" rid="B18">18</xref>
					</p>
        </sec>
        <sec>
          <title>An&#225;lise estat&#237;stica</title>
          <p>As vari&#225;veis cont&#237;nuas foram apresentadas em m&#233;dia &#177; desvio padr&#227;o e as vari&#225;veis categ&#243;ricas como frequ&#234;ncia absoluta (n) ou relativa (%).</p>
          <p>O teste de Kolmogorov-Smirnov foi usado para verificar a normalidade da distribui&#231;&#227;o. O teste t de Student n&#227;o pareado foi adotado para comparar os grupos categorizados pela presen&#231;a de componentes do RCM. Usamos o teste de Pearson para verificar correla&#231;&#227;o entre CAT e outras vari&#225;veis de interesse relacionadas aos componentes do RCM. Regress&#227;o linear multivariada foi realizada com valores de glicemia de jejum (mg/dL) como vari&#225;vel dependente e CAT (mM), sexo e idade como vari&#225;veis independentes. Um intervalo de confian&#231;a de 95% foi usado para descrever os valores do coeficiente de regress&#227;o linear (&#946;).</p>
          <p>Signific&#226;ncia estat&#237;stica aceita foi estabelecida para p &lt; 0,05. Todas as an&#225;lises foram conduzidas usando o programa de estat&#237;stica <italic>Statistical Package for Social Science, SPSS</italic> vers&#227;o 20.0 para Windows.</p>
        </sec>
        <sec>
          <title>Aspectos &#233;ticos</title>
          <p>O estudo foi aprovado pelo Comit&#234; de &#201;tica em Pesquisa com Humanos da Universidade Federal de Sergipe (C.A.A.E.: 0113.0.107.000-11).</p>
          <p>De acordo com os princ&#237;pios da declara&#231;&#227;o de Helsinki, todos os volunt&#225;rios foram informados sobre o protocolo do estudo e em seguida assinaram o termo de consentimento. Os volunt&#225;rios foram informados sobre os m&#233;todos e procedimentos usados na coleta de dados, os poss&#237;veis benef&#237;cios e inconveni&#234;ncias, privacidade dos resultados, e voluntariedade na participa&#231;&#227;o.</p>
        </sec>
      </sec>
      <sec sec-type="results">
        <title>Resultados</title>
        <p>Um total de 139 indiv&#237;duos n&#227;o obesos e clinicamente sadios, com idade de 21,4 &#177; 1,9 anos, participou do estudo. As mulheres predominaram na distribui&#231;&#227;o por sexo (77%). Os par&#226;metros antropom&#233;tricos, cl&#237;nicos e bioqu&#237;micos est&#227;o descritos na <xref ref-type="table" rid="t4">Tabela 1</xref>.</p>
        <table-wrap id="t4">
          <label>Tabela 1</label>
          <caption>
            <title>Caracter&#237;sticas demogr&#225;ficas, antropom&#233;tricas, cl&#237;nicas e bioqu&#237;micas (m&#233;dia e desvio padr&#227;o) de adultos jovens, n&#227;o obesos e clinicamente saud&#225;veis</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup>
              <col width="33%"/>
              <col width="33%"/>
              <col width="33%"/>
            </colgroup>
            <thead>
              <tr>
                <th align="left">Total (n = 139)</th>
                <th align="center">m&#233;dia</th>
                <th align="center">Desvio padr&#227;o</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Idade (anos)</td>
                <td align="center">21,4</td>
                <td align="center">1,9</td>
              </tr>
              <tr>
                <td align="left">Peso (kg)<xref ref-type="table-fn" rid="TFN14">a</xref>
								</td>
                <td align="center">55,9</td>
                <td align="center">7,4</td>
              </tr>
              <tr>
                <td align="left">IMC (kg/m<sup>2</sup>)<xref ref-type="table-fn" rid="TFN14">a</xref>
								</td>
                <td align="center">20,6</td>
                <td align="center">2,1</td>
              </tr>
              <tr>
                <td align="left">CC (cm)<xref ref-type="table-fn" rid="TFN14">a</xref>
								</td>
                <td align="center">71,1</td>
                <td align="center">5,6</td>
              </tr>
              <tr>
                <td align="left">PCT (mm)<xref ref-type="table-fn" rid="TFN14">a</xref>
								</td>
                <td align="center">18,6</td>
                <td align="center">6,8</td>
              </tr>
              <tr>
                <td align="left">PCB (mm)<xref ref-type="table-fn" rid="TFN14">a</xref>
								</td>
                <td align="center">9,6</td>
                <td align="center">5,4</td>
              </tr>
              <tr>
                <td align="left">PCSI (mm)<xref ref-type="table-fn" rid="TFN14">a</xref>
								</td>
                <td align="center">16,1</td>
                <td align="center">6,5</td>
              </tr>
              <tr>
                <td align="left">PCSE (mm)<xref ref-type="table-fn" rid="TFN14">a</xref>
								</td>
                <td align="center">14,8</td>
                <td align="center">4,4</td>
              </tr>
              <tr>
                <td align="left">Gordura total (%)<xref ref-type="table-fn" rid="TFN14">a</xref>
								</td>
                <td align="center">23,0</td>
                <td align="center">9,7</td>
              </tr>
              <tr>
                <td align="left">Gordura do tronco (%)<xref ref-type="table-fn" rid="TFN14">a</xref>
								</td>
                <td align="center">53,2</td>
                <td align="center">7,0</td>
              </tr>
              <tr>
                <td align="left">Massa de gordura (kg)<xref ref-type="table-fn" rid="TFN14">a</xref>
								</td>
                <td align="center">12,7</td>
                <td align="center">5,5</td>
              </tr>
              <tr>
                <td align="left">Massa livre de gordura (kg)<xref ref-type="table-fn" rid="TFN14">a</xref>
								</td>
                <td align="center">43,1</td>
                <td align="center">8,6</td>
              </tr>
              <tr>
                <td align="left">PSS (mmHg)<xref ref-type="table-fn" rid="TFN15">b</xref>
								</td>
                <td align="center">108,8</td>
                <td align="center">8,0</td>
              </tr>
              <tr>
                <td align="left">PSD (mmHg)<xref ref-type="table-fn" rid="TFN15">b</xref>
								</td>
                <td align="center">74,8</td>
                <td align="center">7,8</td>
              </tr>
              <tr>
                <td align="left">Glicose de jejum (mg/dL)<xref ref-type="table-fn" rid="TFN16">c</xref>
								</td>
                <td align="center">85,6</td>
                <td align="center">8,4</td>
              </tr>
              <tr>
                <td align="left">Colesterol total (mg/dL)<xref ref-type="table-fn" rid="TFN17">d</xref>
								</td>
                <td align="center">170,7</td>
                <td align="center">38,5</td>
              </tr>
              <tr>
                <td align="left">HDL-c (mg/dL)<xref ref-type="table-fn" rid="TFN17">d</xref>
								</td>
                <td align="center">56,0</td>
                <td align="center">10,9</td>
              </tr>
              <tr>
                <td align="left">LDL-c (mg/dL)<xref ref-type="table-fn" rid="TFN17">d</xref>
								</td>
                <td align="center">98,9</td>
                <td align="center">33,0</td>
              </tr>
              <tr>
                <td align="left">Triglicer&#237;deos (mg/dL)<xref ref-type="table-fn" rid="TFN17">d</xref>
								</td>
                <td align="center">78,4</td>
                <td align="center">35,2</td>
              </tr>
              <tr>
                <td align="left">Colesterol total /HDL-c<xref ref-type="table-fn" rid="TFN17">d</xref>
								</td>
                <td align="center">3,0</td>
                <td align="center">0,7</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN13">
              <p>IMC: &#237;ndice de massa corporal; CC: circunfer&#234;ncia da cintura; PCT: prega cut&#226;nea tricipital; PCB: prega cut&#226;nea bicipital; PCSI: prega cut&#226;nea suprail&#237;aca; PCSE: prega cut&#226;nea subescapular; PSS: press&#227;o sangu&#237;nea sist&#243;lica; PSD: press&#227;o sangu&#237;nea diast&#243;lica; HDL-c: lipoprote&#237;na de alta densidade; LDL-c: lipoprote&#237;na de baixa densidade.</p>
            </fn>
            <fn id="TFN14">
              <label>a</label>
              <p>n = 123;</p>
            </fn>
            <fn id="TFN15">
              <label>b</label>
              <p>n = 122;</p>
            </fn>
            <fn id="TFN16">
              <label>c</label>
              <p>n = 136;</p>
            </fn>
            <fn id="TFN17">
              <label>d</label>
              <p>n = 137.</p>
            </fn>
            <fn id="TFN18">
              <p>Valores de refer&#234;ncia: circunfer&#234;ncia da cintura &lt; 80 cm para mulheres e &lt; 94 cm para homens; glicose de jejum &#8804; 100 mg/dL; triglicer&#237;deos &#8804; 150 mg/dL; HDL-c &gt; 50 mg/dL para mulheres e &gt; 40 mg/dL para homens; PSS &#8804; 130 mmHg; PSD &#8804; 85 mmHg.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>Apesar de serem n&#227;o obesos e clinicamente sadios, os indiv&#237;duos deste estudo apresentaram componentes do RCM. Cerca de 15% (n = 20) da amostra tinha baixos n&#237;veis de HDL, seguidos de n&#237;veis elevados de press&#227;o sangu&#237;nea diast&#243;lica (n = 9; 7%), triglicer&#237;deos (n = 8; 6%), glicose (n = 6; 4%), e obesidade abdominal (n = 3; 2%). Quase um quarto da amostra (n = 34; 24,5%) apresentou pelo menos um componente do RCM, seguido por 2 (n = 11; 8%) e 3 ou mais componentes (n = 1; 0,7%), respectivamente.</p>
        <p>As principais inadequa&#231;&#245;es de ingest&#227;o de nutrientes foram o consumo de gordura saturada (n = 114; 92%), fibra (n = 89; 72%), e vitamina D (n = 107; 86%).</p>
        <p>Os indiv&#237;duos foram categorizados pela presen&#231;a de componentes do RCM (<xref ref-type="table" rid="t5">Tabela 2</xref>). Aqueles com pelo menos um componente apresentaram valores maiores de peso corporal, raz&#227;o triglicer&#237;deos/HDL-c e raz&#227;o colesterol total/HDL quando comparados &#224;queles que n&#227;o apresentaram nenhum componente de RCM (p &lt; 0,05).</p>
        <table-wrap id="t5">
          <label>Tabela 2</label>
          <caption>
            <title>Caracter&#237;sticas demogr&#225;ficas, antropom&#233;tricas e bioqu&#237;micas (m&#233;dia &#177; desvio padr&#227;o) segundo a presen&#231;a de componentes do risco cardiometab&#243;lico em adultos jovens, n&#227;o obesos e clinicamente saud&#225;veis (n = 139)</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 style="border-bottom-style:solid;border-bottom-width:thin">
                <th align="left" rowspan="2">
								</th>
                <th align="center" colspan="2">Nenhum componente</th>
                <th align="center" colspan="2">&#8805;1 componente</th>
                <th align="center">
								</th>
              </tr>
              <tr>
                <th align="center">M&#233;dia</th>
                <th align="center">Desvio padr&#227;o</th>
                <th align="center">M&#233;dia</th>
                <th align="center">Desvio padr&#227;o</th>
                <th align="center">p</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">Idade (anos)</td>
                <td align="center">21,4</td>
                <td align="center">2,0</td>
                <td align="center">21,9</td>
                <td align="center">1,8</td>
                <td align="center">0,73</td>
              </tr>
              <tr>
                <td align="left">Peso (kg)<xref ref-type="table-fn" rid="TFN20">a</xref>
								</td>
                <td align="center">54,5</td>
                <td align="center">6,7</td>
                <td align="center">60,6</td>
                <td align="center">7,7</td>
                <td align="center">&lt; 0,01</td>
              </tr>
              <tr>
                <td align="left">IMC (kg/m<sup>2</sup>)<xref ref-type="table-fn" rid="TFN20">a</xref>
								</td>
                <td align="center">20,5</td>
                <td align="center">2,0</td>
                <td align="center">29,0</td>
                <td align="center">2,3</td>
                <td align="center">0,28</td>
              </tr>
              <tr>
                <td align="left">Colesterol total (mg/dL)<xref ref-type="table-fn" rid="TFN23">d</xref>
								</td>
                <td align="center">171,9</td>
                <td align="center">39,5</td>
                <td align="center">166,8</td>
                <td align="center">35,5</td>
                <td align="center">0,50</td>
              </tr>
              <tr>
                <td align="left">LDL-c (mg/dL)<xref ref-type="table-fn" rid="TFN23">d</xref>
								</td>
                <td align="center">99,1</td>
                <td align="center">34,9</td>
                <td align="center">98,3</td>
                <td align="center">26,7</td>
                <td align="center">0,90</td>
              </tr>
              <tr>
                <td align="left">Triglicer&#237;deos /HDL-c (mg/dL)<xref ref-type="table-fn" rid="TFN23">d</xref>
								</td>
                <td align="center">1,2</td>
                <td align="center">0,5</td>
                <td align="center">2,0</td>
                <td align="center">0,9</td>
                <td align="center">0,00</td>
              </tr>
              <tr>
                <td align="left">Colesterol total /HDL-c<xref ref-type="table-fn" rid="TFN23">d</xref>
								</td>
                <td align="center">2,9</td>
                <td align="center">0,6</td>
                <td align="center">3,5</td>
                <td align="center">0,8</td>
                <td align="center">&lt; 0,01</td>
              </tr>
              <tr>
                <td align="left">CAT (mM)<xref ref-type="table-fn" rid="TFN23">d</xref>
								</td>
                <td align="center">3,1</td>
                <td align="center">0,6</td>
                <td align="center">2,9</td>
                <td align="center">0,8</td>
                <td align="center">0,23</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN19">
              <p>IMC: &#237;ndice de massa corporal; CAT: capacidade antioxidante total; LDL-c: lipoprote&#237;na de baixa densidade. Diferen&#231;a estat&#237;stica: 5%, teste t de Student.</p>
            </fn>
            <fn id="TFN20">
              <label>a</label>
              <p>n = 123;</p>
            </fn>
            <fn id="TFN21">
              <label>b</label>
              <p>n = 122;</p>
            </fn>
            <fn id="TFN22">
              <label>c</label>
              <p>n = 136;</p>
            </fn>
            <fn id="TFN23">
              <label>d</label>
              <p>n = 137</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>A glicemia foi o &#250;nico componente do RCM que apresentou correla&#231;&#227;o com a CAT do plasma (<xref ref-type="fig" rid="f2">Figura 1</xref>).</p>
        <p>
          <fig id="f2">
            <label>Figura 1</label>
            <caption>
              <title>Correla&#231;&#227;o de Pearson entre capacidade antioxidante total (CAT) do plasma e valores de glicemia de jejum (n = 139).</title>
            </caption>
            <graphic xlink:href="1678-4170-abc-109-02-0140-70095-gf01-pt.jpg"/></fig>
        </p>
        <p>Ap&#243;s o ajuste da an&#225;lise linear multivariada por sexo e idade, a glicemia de jejum foi positivamente associada com os valores de CAT (R<sup>2</sup>= 0,10; &#946; = 0,17; p = 0,001). A CAT teve um efeito preditivo positivo sobre os n&#237;veis s&#233;ricos de glicose. Um aumento em 1 unidade nos n&#237;veis de CAT foi associado com um aumento em 0,17 mg/dL na glicemia de jejum. Vale destacar que 10% do aumento na glicemia foi devido ao efeito da CAT (<xref ref-type="table" rid="t6">Tabela 3</xref>).</p>
        <table-wrap id="t6">
          <label>Tabela 3</label>
          <caption>
            <title>An&#225;lise de regress&#227;o linear multivariada com a glicemia (mg/dL) como vari&#225;vel dependente ajustada por sexo e idade (n = 139)</title>
          </caption>
          <table frame="hsides" rules="groups">
            <colgroup>
              <col width="33%"/>
              <col width="33%"/>
              <col width="33%"/>
            </colgroup>
            <thead>
              <tr>
                <th align="left">
								</th>
                <th align="center">&#946; (intervalo de confian&#231;a de 95%)</th>
                <th align="center">p</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">CAT (mM)</td>
                <td align="center">0,174 (0,135-3,957)</td>
                <td align="center">0,030</td>
              </tr>
              <tr>
                <td align="left">Sexo</td>
                <td align="center">0,267 (2,099-8,553)</td>
                <td align="center">0,001</td>
              </tr>
              <tr>
                <td align="left">Idade</td>
                <td align="center">&#8211;0,132 (&#8211;1,243-0,128)</td>
                <td align="center">0,110</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="TFN24">
              <p>R<sup>2</sup> = 0,100, p = 0,001. CAT: capacidade antioxidante total.</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </sec>
      <sec sec-type="discussion">
        <title>Discuss&#227;o</title>
        <p>O estudo sobre os componentes do RCM tem atra&#237;do aten&#231;&#227;o, uma vez que eles est&#227;o fortemente relacionados ao desenvolvimento de doen&#231;as associadas com resist&#234;ncia &#224; insulina e eventos cardiovasculares, os quais s&#227;o as principais causas de morbimortalidade nesta popula&#231;&#227;o.<xref ref-type="bibr" rid="B19">19</xref> Essas doen&#231;as t&#234;m impacto direto e indireto sobre a economia social e do estado, incluindo baixa produtividade, perda de dias de trabalho, danos ao setor produtivo, e custos intang&#237;veis das pessoas afetadas.<xref ref-type="bibr" rid="B10">10</xref><sup>,</sup><xref ref-type="bibr" rid="B20">20</xref>
				</p>
        <p>Determinar a presen&#231;a de componentes do RCM em popula&#231;&#245;es jovens &#233; relevante para o diagn&#243;stico precoce, e estabelecimento de interven&#231;&#245;es espec&#237;ficas e medidas preventivas. Na popula&#231;&#227;o de nosso estudo, apesar de a preval&#234;ncia de altera&#231;&#245;es nos par&#226;metros avaliados ter sido baixa - de acordo com os valores de refer&#234;ncia adotados - quase um quarto da amostra apresentou pelo menos um componente do RCM. Um baixo HDL-c foi o componente mais prevalente (15%). Por outro lado, estudos com alunos universit&#225;rios realizados no Brasil<xref ref-type="bibr" rid="B20">20</xref> e em outros pa&#237;ses,<xref ref-type="bibr" rid="B21">21</xref><sup>,</sup><xref ref-type="bibr" rid="B22">22</xref> mostraram maior preval&#234;ncia. Tal controv&#233;rsia pode estar relacionada &#224;s caracter&#237;sticas de nossa popula&#231;&#227;o, composta de estudantes universit&#225;rios da &#225;rea da sa&#250;de (principalmente nutri&#231;&#227;o, 39%), fisicamente ativos (65%), n&#227;o fumantes, e com baixa preval&#234;ncia de consumo de &#225;lcool.</p>
        <p>A preval&#234;ncia dos componentes do RCM em popula&#231;&#245;es de estudantes universit&#225;rios de estudos nacionais<xref ref-type="bibr" rid="B23">23</xref> e internacionais<xref ref-type="bibr" rid="B21">21</xref><sup>,</sup><xref ref-type="bibr" rid="B22">22</xref> varia de 30 a 77% entre aqueles que apresentam um ou mais componente do risco, de 12% a 13% entre aqueles com dois, e de 3 a 16% entre aqueles com tr&#234;s componentes. Baixo HDL-c e press&#227;o sangu&#237;nea elevada s&#227;o os componentes do RCM mais prevalentes.</p>
        <p>O desenvolvimento precoce desses componentes em jovens adultos foi atribu&#237;do a h&#225;bitos alimentares ruins, comumente observados entre jovens, devido a fatores relacionados a essa fase da vida, tais como independ&#234;ncia, incapacidade de fazer escolhas saud&#225;veis, falta de tempo, conveni&#234;ncia, custos, e influ&#234;ncia do meio ambiente f&#237;sico e social.<xref ref-type="bibr" rid="B24">24</xref> O resultado dessa combina&#231;&#227;o &#233; o maior ganho de peso no primeiro ano da faculdade em compara&#231;&#227;o &#224; fase adulta.<xref ref-type="bibr" rid="B25">25</xref>
				</p>
        <p>Neste estudo, observou-se que a presen&#231;a de pelo menos um componente do RCM na popula&#231;&#227;o estudada associou-se com maiores valores antropom&#233;tricos (peso corporal) e bioqu&#237;micos (raz&#227;o triglicer&#237;deos/HDL-c e raz&#227;o colesterol total/HDL-c). Esses resultados s&#227;o corroborados por estudos conduzidos com estudantes universit&#225;rios do Brasil<xref ref-type="bibr" rid="B23">23</xref> e de outros pa&#237;ses.<xref ref-type="bibr" rid="B21">21</xref><sup>,</sup><xref ref-type="bibr" rid="B22">22</xref>
				</p>
        <p>A raz&#227;o TG/HDL-c tem sido amplamente discutida como um indicador de risco aterog&#234;nico na predi&#231;&#227;o de desenvolvimento de doen&#231;a arterial coronariana,<xref ref-type="bibr" rid="B26">26</xref> infarto agudo do mioc&#225;rdio,<xref ref-type="bibr" rid="B27">27</xref> e aterosclerose.<xref ref-type="bibr" rid="B28">28</xref> Estudos mostraram que valores elevados de TG/HDL-c est&#227;o correlacionados com um RCM aumentado na popula&#231;&#227;o.<xref ref-type="bibr" rid="B22">22</xref><sup>,</sup><xref ref-type="bibr" rid="B29">29</xref> Al&#233;m disso, a raz&#227;o TG/HDL-c foi positivamente correlacionada com par&#226;metros bioqu&#237;micos (colesterol total, LDL-c, e TG) e antropom&#233;tricos (IMC, circunfer&#234;ncia da cintura, e porcentagem de gordura), e negativamente com HDL-c.<xref ref-type="bibr" rid="B30">30</xref>
				</p>
        <p>A presen&#231;a de componentes do RCM, tais como obesidade abdominal,<xref ref-type="bibr" rid="B31">31</xref> hipertrigliceridemia, baixo HDL-c e hipertens&#227;o,<xref ref-type="bibr" rid="B32">32</xref><sup>,</sup><xref ref-type="bibr" rid="B33">33</xref> foi associada com o desenvolvimento de DCNTs, especialmente diabetes tipo 2, doen&#231;as cardiovasculares, e c&#226;ncer. No Brasil, um estudo foi conduzido para avaliar a associa&#231;&#227;o entre fatores de risco cardiovasculares e indicadores antropom&#233;tricos em pacientes com DCNT.<xref ref-type="bibr" rid="B34">34</xref> Os autores encontraram que 74% da amostra apresentou glicemia &gt; 100 mg/dL, 56% baixo HDL-c, 82% circunfer&#234;ncia da cintura elevada, e 78% sobrepeso.<xref ref-type="bibr" rid="B34">34</xref>
				</p>
        <p>Produ&#231;&#227;o excessiva de EROS &#233; outro fator que foi associado com a presen&#231;a de componentes do RCM e, consequentemente, ao desenvolvimento de DCNTs.<xref ref-type="bibr" rid="B4">4</xref><sup>,</sup><xref ref-type="bibr" rid="B6">6</xref> V&#225;rios estudos identificaram a associa&#231;&#227;o de CAT no plasma - um importante biomarcador de EO por expressar a a&#231;&#227;o sin&#233;rgica entre v&#225;rios componentes do RCM<xref ref-type="bibr" rid="B5">5</xref> - e altera&#231;&#245;es nos componentes antropom&#233;tricos, cl&#237;nicos e bioqu&#237;micos do RCM.<xref ref-type="bibr" rid="B6">6</xref> Vale ressaltar que todos esses estudos foram conduzidos com indiv&#237;duos com DCNTs. Estudos com indiv&#237;duos saud&#225;veis ainda s&#227;o escassos.</p>
        <p>Apesar de os indiv&#237;duos do presente estudo serem n&#227;o obesos e clinicamente saud&#225;veis, foi poss&#237;vel identificar uma associa&#231;&#227;o entre CAT e glicemia de jejum ap&#243;s ajuste por sexo e idade (R2 = 0,10; &#946; = 0,17; p = 0.001). A correla&#231;&#227;o positiva entre CAT e glicemia de jejum encontrada neste estudo n&#227;o corrobora com a literatura.<xref ref-type="bibr" rid="B35">35</xref> A hiperglicemia aumenta a express&#227;o do EO pelo aumento nas concentra&#231;&#245;es de NADPH e produ&#231;&#227;o de EROS, dado o intenso metabolismo mitocondrial da glicose.<xref ref-type="bibr" rid="B36">36</xref> Isso resulta em uma produ&#231;&#227;o aumentada de doadores de el&#233;trons (FADH2 e NADH) no ciclo de Krebs e, assim, em um alto potencial da membrana mitocondrial (DmH+) pelo bombeamento de pr&#243;tons atrav&#233;s da membrana interna, inibi&#231;&#227;o do transporte de el&#233;trons no complexo III, aumento da meia-vida de intermedi&#225;rios de radicais livres da coenzima Q (ubiquinona) que reduz O<sub>2</sub> a super&#243;xido. Portanto, estudos mostraram correla&#231;&#227;o negativa entre glicemia de jejum e CAT plasm&#225;tica e diet&#233;tica,<xref ref-type="bibr" rid="B37">37</xref> bem como maiores quantidades de produtos de rea&#231;&#245;es oxidativas, o que reduz o n&#237;vel de subst&#226;ncias que constituem o sistema antioxidante.<xref ref-type="bibr" rid="B38">38</xref> No entanto, todos esses estudos foram realizados com indiv&#237;duos com DCNTs j&#225; estabelecidas.</p>
        <p>Devido &#224;s caracter&#237;sticas dos participantes deste estudo - jovens, clinicamente sadios, e n&#227;o obesos, al&#233;m da alta CAT, pode-se sugerir o estabelecimento de um mecanismo adaptativo baseando-se na evid&#234;ncia de que o aumento de 1 unidade nos n&#237;veis de CAT (1mM) est&#225; associado com o aumento de 0,17 mg/dL nos n&#237;veis de glicemia de jejum, <italic>i.e</italic>., uma glicemia aumentada, na homeostase, determinaria um aumento compensat&#243;rio da CAT. Esse processo ocorre por meio de um <italic>feedback</italic> negativo, que pode ativar as vias enzim&#225;ticas do sistema antioxidante para reduzir os n&#237;veis intracelulares de EROS e, assim minimizar o dano oxidativo.<xref ref-type="bibr" rid="B39">39</xref> Os achados de Demirbag et al.<xref ref-type="bibr" rid="B35">35</xref> corroboram essa hip&#243;tese. O aumento na CAT torna-se impratic&#225;vel em condi&#231;&#245;es patol&#243;gicas j&#225; estabelecidas, diferente do que ocorre em indiv&#237;duos saud&#225;veis.</p>
        <p>A falta de associa&#231;&#245;es entre CAT e outras vari&#225;veis antropom&#233;tricas, cl&#237;nicas e bioqu&#237;micas no estudo pode ser explicada pela baixa preval&#234;ncia de altera&#231;&#245;es nesses par&#226;metros e pelas caracter&#237;sticas da popula&#231;&#227;o estudada: jovem, predominantemente feminina, n&#227;o obesa, clinicamente sadia, fisicamente ativa, estudantes de &#225;rea da sa&#250;de, baixo consumo de &#225;lcool, n&#227;o fumantes, e com marcadores de adiposidade - circunfer&#234;ncia da cintura (71,1 &#177; 5,6 cm) e porcentagem de gordura (23,0 &#177; 9,7%) abaixo do risco de causar altera&#231;&#245;es metab&#243;licas. No entanto, &#233; importante destacar os altos valores de CAT encontrados no presente estudo (3,10 &#177; 0,71; m&#233;dia = 3,09 mM) em compara&#231;&#227;o aos valores encontrados por Barbosa et al.<xref ref-type="bibr" rid="B40">40</xref> em jovens adultos (1,60 mM). Esse resultado pode estar associado com a baixa preval&#234;ncia de fatores de risco comportamentais no grupo estudado, tais como sedentarismo (36,2%), baixo consumo de &#225;lcool, n&#227;o ser fumante, al&#233;m de serem estudantes universit&#225;rios na &#225;rea da sa&#250;de.</p>
        <p>Algumas limita&#231;&#245;es deste estudo devem ser reconhecidas: a perda na amostra de algumas vari&#225;veis devido &#224; informa&#231;&#227;o incompleta e/ou abandono do estudo; a avalia&#231;&#227;o do consumo alimentar por instrumentos dispon&#237;veis na literatura est&#225; sujeita a erros devido &#224; ampla variabilidade inter- e intraindividual, &#224; mem&#243;ria dos entrevistados sobre h&#225;bitos passados, baixa acur&#225;cia em quantificar a ingest&#227;o devido ao uso de medidas e listas de alimentos padronizados. Finalmente, os m&#233;todos utilizados para avaliar a CAT refletem rea&#231;&#245;es qu&#237;micas <italic>in vitro</italic>, sem similaridade com sistemas biol&#243;gicos. Seus resultados devem, assim, serem interpretados com cautela, uma vez que esses m&#233;todos n&#227;o medem a biodisponibilidade, a estabilidade <italic>in vivo</italic>, a reten&#231;&#227;o de antioxidantes nos tecidos, e a reatividade <italic>in situ</italic>.</p>
      </sec>
      <sec sec-type="conclusions">
        <title>Conclus&#245;es</title>
        <p>Neste estudo, componentes do RCM estiveram presentes em alguns adultos jovens, clinicamente sadios, n&#227;o obesos e com alta CAT.</p>
        <p>A correla&#231;&#227;o positiva observada entre CAT plasm&#225;tica e glicemia de jejum sugere o estabelecimento de um mecanismo de adapta&#231;&#227;o. O aumento na glicemia em um sistema biol&#243;gico, em homeostase, determinaria um aumento compensat&#243;rio da CAT plasm&#225;tica.</p>
        <p>Assim, diferente do que ocorre em popula&#231;&#245;es com DCNTs j&#225; estabelecidas, a CAT n&#227;o se associou com componentes do RCM nesta amostra de indiv&#237;duos jovens, n&#227;o obesos, e clinicamente sadios, possivelmente devido ao estabelecimento de mecanismos compensat&#243;rios que se tornam ativados em condi&#231;&#245;es fisiol&#243;gicas.</p>
      </sec>
    </body>
    <back>
      <fn-group>
        <fn fn-type="supported-by">
          <p>
            <bold>Fontes de financiamento</bold>
          </p>
          <p>O presente estudo foi financiado pela Funda&#231;&#227;o de Apoio &#224; Pesquisa e &#224; Inova&#231;&#227;o Tecnol&#243;gica do Estado de Sergipe.</p>
        </fn>
        <fn fn-type="other">
          <p>
            <bold>Vincula&#231;&#227;o acad&#234;mica</bold>
          </p>
          <p>Este artigo &#233; parte de disserta&#231;&#227;o de Mestrado de Jamille Oliveira Costa pela Universidade Federal de Sergipe.</p>
        </fn>
      </fn-group>
    </back>
  </sub-article>
</article>
