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 <!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.0 20120330//EN" "http://jats.nlm.nih.gov/publishing/1.0/JATS-journalpublishing1.dtd"> <article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" article-type="research-article" dtd-version="1.0" xml:lang="en">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">IJN</journal-id>
      <journal-title-group>
        <journal-title>International Journal of Nutrition</journal-title>
      </journal-title-group>
      <issn pub-type="epub">2379-7835</issn>
      <publisher>
        <publisher-name>Open Access Pub</publisher-name>
        <publisher-loc>United States</publisher-loc>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">IJN-20-3463</article-id>
      <article-id pub-id-type="doi">10.14302/issn.2379-7835.ijn-20-3463</article-id>
      <article-categories>
        <subj-group>
          <subject>research-article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Impact of Low Birth Weight on Early Vascular Aging and Cardiometabolic Phenotypes in Later Life Among Cameroonian Adults </article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Daniel</surname>
            <given-names>Lemogoum</given-names>
          </name>
          <xref ref-type="aff" rid="idm1842673828">1</xref>
          <xref ref-type="aff" rid="idm1842672892">2</xref>
          <xref ref-type="aff" rid="idm1842674116">3</xref>
          <xref ref-type="aff" rid="idm1842672172">*</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Philippe</surname>
            <given-names>van de Borne</given-names>
          </name>
          <xref ref-type="aff" rid="idm1842674116">3</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Michel</surname>
            <given-names>P. Hermans</given-names>
          </name>
          <xref ref-type="aff" rid="idm1842673036">4</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Danielle</surname>
            <given-names>Christiane Kedy Mangamba</given-names>
          </name>
          <xref ref-type="aff" rid="idm1842673828">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Aurel</surname>
            <given-names>Sikamo</given-names>
          </name>
          <xref ref-type="aff" rid="idm1842673828">1</xref>
          <xref ref-type="aff" rid="idm1842672892">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Elysée</surname>
            <given-names>Claude Bika Lele</given-names>
          </name>
          <xref ref-type="aff" rid="idm1842672532">5</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Marie</surname>
            <given-names>Solange Ndom Idejen</given-names>
          </name>
          <xref ref-type="aff" rid="idm1842673828">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Jacques</surname>
            <given-names>Doumbe</given-names>
          </name>
          <xref ref-type="aff" rid="idm1842673828">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>William</surname>
            <given-names>Ngatchou</given-names>
          </name>
          <xref ref-type="aff" rid="idm1842673828">1</xref>
          <xref ref-type="aff" rid="idm1842672892">2</xref>
        </contrib>
      </contrib-group>
      <aff id="idm1842673828">
        <label>1</label>
        <addr-line>Faculty of Medicine and Pharmaceutical Sciences, University of Douala, Douala, Cameroon</addr-line>
      </aff>
      <aff id="idm1842672892">
        <label>2</label>
        <addr-line>Cameroon Heart Institute, Cameroon Heart Foundation, Douala, Cameroon.</addr-line>
      </aff>
      <aff id="idm1842674116">
        <label>3</label>
        <addr-line>Department of Cardiology, Erasme University Hospital, Université Libre de Bruxelles, Brussels, Belgium.</addr-line>
      </aff>
      <aff id="idm1842673036">
        <label>4</label>
        <addr-line>Endocrinology and Nutrition Unit, Cliniques Universitaires St-Luc, Université Catholique de Louvain, Brussels, Belgium.</addr-line>
      </aff>
      <aff id="idm1842672532">
        <label>5</label>
        <addr-line>Physiology and Medicine of Physical Activities and Sports Unit, Faculty of Sciences, University of Douala, Douala, Cameroon.</addr-line>
      </aff>
      <aff id="idm1842672172">
        <label>*</label>
        <addr-line>corresponding author</addr-line>
      </aff>
      <contrib-group>
        <contrib contrib-type="editor">
          <name>
            <surname>Kavitha</surname>
            <given-names>Menon</given-names>
          </name>
          <xref ref-type="aff" rid="idm1842666340">1</xref>
        </contrib>
      </contrib-group>
      <aff id="idm1842666340">
        <label>1</label>
        <addr-line>Public Health Foundation of India| Indian Institute of Public Health Gandhinagar (IIPHG) Sardar Patel Institute Campus, Drive-In Road, Thaltej, Ahmedabad- 380 054, Gujarat, India</addr-line>
      </aff>
      <author-notes>
        <corresp>
    
    Daniel Lemogoum, <addr-line>Faculty of Medicine and Pharmaceutical Sciences, Douala                 University, Cameroon</addr-line>, Phone: +<phone>237676642626</phone>. Email: <email>dlems2002@yahoo.fr</email></corresp>
        <fn fn-type="conflict" id="idm1849749028">
          <p>The authors have no conflicts of interest to declare. </p>
        </fn>
      </author-notes>
      <pub-date pub-type="epub" iso-8601-date="2020-07-06">
        <day>06</day>
        <month>07</month>
        <year>2020</year>
      </pub-date>
      <volume>5</volume>
      <issue>4</issue>
      <fpage>30</fpage>
      <lpage>41</lpage>
      <history>
        <date date-type="received">
          <day>27</day>
          <month>06</month>
          <year>2020</year>
        </date>
        <date date-type="accepted">
          <day>03</day>
          <month>07</month>
          <year>2020</year>
        </date>
        <date date-type="online">
          <day>06</day>
          <month>07</month>
          <year>2020</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>© </copyright-statement>
        <copyright-year>2020</copyright-year>
        <copyright-holder>Daniel Lemogoum, et al.</copyright-holder>
        <license xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">
          <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 author and source are credited.</license-p>
        </license>
      </permissions>
      <self-uri xlink:href="http://openaccesspub.org/ijn/article/1393">This article is available from http://openaccesspub.org/ijn/article/1393</self-uri>
      <abstract>
        <sec id="idm1842662788">
          <title>Background</title>
          <p>Evidence suggests that low birth weight (LBW) is associated with increased cardiovascular and metabolic risk in adulthood, including increased arterial stiffness, a marker of early vascular aging (EVA)                     assessable by pulse wave velocity (PWV), obesity and glucose homeostasis abnormalities. The present study aimed to explore the late impact of LBW on PWV and cardiometabolic phenotypes among young adult                Cameroonians.</p>
        </sec>
        <sec id="idm1842663148">
          <title>Methods</title>
          <p>The study evaluated 120 subjects (mean age: 26 ± 5 years; 54% male sex) at the Cameroon Heart Institute, Douala, Cameroon, between January and June 2018. Birth weight (BW) and gestational age,               sociodemographic, anthropometrics and fasting capillary blood glucose were recorded in all participants. Blood pressure (BP) and PWV were measured using an automatic oscillometric device (Mobil-O-Graph®).                    Multiple-adjusted linear regression was used to determine predictive factors for PWV. For assessment of potential impact of BW on EVA, PWV was adjusted for age, sex, body mass index (BMI) and mean arterial pressure (MAP).</p>
        </sec>
        <sec id="idm1842664660">
          <title>Results</title>
          <p>28 participants (23.3%) of the study sample had LBW (&lt;3000g). There was no gender difference between LBW or normal birth weight patients (NBW; controls). Age- and MAP-adjusted PWV (aPWV) were higher in women with LBW compared to NBW (5.6 m/s and 5.3 m/s respectively, P = 0.038). In men, aPWV was similar in LBW and NBW. In this study population, aPWV was higher (on average +15 cm/s) in LBW than in controls, although the difference was not statistically significant (P=0.083). Multivariate regression analysis showed age, male sex, BMI and MAP were independent determinants of PWV, but not LBW. Compared to NBW controls, the prevalence of overweight/obesity, impaired glucose homeostasis and diabetes was higher in LBW: 42.9% vs 37%; 10.7% vs 3.3%, and 3.6 % vs 1.1%, respectively.  Moreover, compared with controls, LBW individuals who were overweight/obese in adulthood had a much higher mean fasting capillary glucose (1.54 ±0.17 g/l vs 0.87 ±0.11 g/l in NBW, p=0.003). </p>
        </sec>
        <sec id="idm1842663868">
          <title>Conclusion</title>
          <p>This study suggests that although LBW is associated with increased aortic stiffness in young adulthood, mainly in women, the association was predominantly driven by aging, MAP, BMI and male sex. In adulthood, LBW subjects exhibited higher obesity indices and altered glucose homeostasis. </p>
        </sec>
      </abstract>
      <kwd-group>
        <kwd>Birth weight</kwd>
        <kwd>early vascular aging</kwd>
        <kwd>glucose homeostasis</kwd>
        <kwd>pulse wave velocity</kwd>
        <kwd>overweight/obesity</kwd>
      </kwd-group>
      <counts>
        <fig-count count="1"/>
        <table-count count="5"/>
        <page-count count="12"/>
      </counts>
    </article-meta>
  </front>
  <body>
    <sec id="idm1842660772" sec-type="intro">
      <title>Introduction</title>
      <p>Growing evidence suggests that low birth weight (LBW) adjusted for gestational age could adversely               influence arterial stiffness, a marker of early vascular            aging (EVA) measured by aortic pulse wave velocity (PWV), and blood pressure (BP) regulation <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842320516">2</xref><xref ref-type="bibr" rid="ridm1842421764">3</xref><xref ref-type="bibr" rid="ridm1842170164">4</xref><xref ref-type="bibr" rid="ridm1842156020">5</xref>,                thereby increasing risk of cardiovascular (CV) events in adulthood <xref ref-type="bibr" rid="ridm1842421764">3</xref><xref ref-type="bibr" rid="ridm1842170164">4</xref><xref ref-type="bibr" rid="ridm1842156020">5</xref><xref ref-type="bibr" rid="ridm1842151628">6</xref><xref ref-type="bibr" rid="ridm1842146388">7</xref><xref ref-type="bibr" rid="ridm1842141204">8</xref><xref ref-type="bibr" rid="ridm1842128180">9</xref><xref ref-type="bibr" rid="ridm1842125084">10</xref><xref ref-type="bibr" rid="ridm1842122996">11</xref>. Indeed, an inverse relationship                 between birth weight (BW) and BP has been             demonstrated, with higher risk of hypertension in                 adulthood <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842320516">2</xref><xref ref-type="bibr" rid="ridm1842151628">6</xref><xref ref-type="bibr" rid="ridm1842146388">7</xref><xref ref-type="bibr" rid="ridm1842141204">8</xref><xref ref-type="bibr" rid="ridm1842128180">9</xref><xref ref-type="bibr" rid="ridm1842125084">10</xref>. This association could be related either to renal organogenesis abnormalityor to            decreased elastin synthesis within large arteries’ wall during fetal life <xref ref-type="bibr" rid="ridm1842151628">6</xref><xref ref-type="bibr" rid="ridm1842117740">12</xref><xref ref-type="bibr" rid="ridm1842079548">13</xref><xref ref-type="bibr" rid="ridm1842073716">14</xref>. In individuals with LBW, early remodeling of large arteries, such as the aorta, might occur during adult life, with increase in caliber and wall remodeling, with a decrease in elastic fibers content  and an increase in collagen fibers in the media. This                      remodeling of large arteries’ wall was attributed to                  mechanical effects and growth factors, as well as               cytokines and/or proteases <xref ref-type="bibr" rid="ridm1842320516">2</xref><xref ref-type="bibr" rid="ridm1842117740">12</xref><xref ref-type="bibr" rid="ridm1842079548">13</xref><xref ref-type="bibr" rid="ridm1842073716">14</xref>.  Several studies have shown that the loss of elasticity in large arteries, leading to EVA, the latter characterized by raised arterial stiffness as measured by aortic pulse wave velocity (PWV), is an independent predictor of CV risk and                overall mortality <xref ref-type="bibr" rid="ridm1842073716">14</xref><xref ref-type="bibr" rid="ridm1842084948">15</xref><xref ref-type="bibr" rid="ridm1842063452">16</xref><xref ref-type="bibr" rid="ridm1842059636">17</xref><xref ref-type="bibr" rid="ridm1842052652">18</xref><xref ref-type="bibr" rid="ridm1842066260">19</xref><xref ref-type="bibr" rid="ridm1842037708">20</xref>. It was also observed that              individuals with fetal malnutrition and LBW were at              increased cardiometabolic risk in adulthood, including      incident type 2 diabetes mellitus (T2DM), obesity, and metabolic syndrome <xref ref-type="bibr" rid="ridm1842033676">21</xref><xref ref-type="bibr" rid="ridm1842028420">22</xref><xref ref-type="bibr" rid="ridm1842006092">23</xref>. </p>
      <p>In Cameroon, despite a large number of                   subjects with a history of LBW, mostly caused by foetal growth retardation and materno-fetal malnutrition                   during high-risk pregnancies <xref ref-type="bibr" rid="ridm1842001340">24</xref>, to the best of our knowledge, no study has explored the late effects of LBW on EVA and cardiometabolic phenotypes in            Cameroonian adolescents and adults. The present study was aimed to address this issue.</p>
    </sec>
    <sec id="idm1842662356" sec-type="methods">
      <title>Methods</title>
      <p>This was a cross-sectional study performed at the Cameroon Heart Institute, based in Douala,                    Cameroon between November 2017 and June 2018. We consecutively recruited apparently healthy Cameroonian individuals aged 15 to 30 years old, all non-smokers, in whom full data on BW and gestational age at birth were documented in the register of births. Individuals were excluded if they were taking medications or had any medical conditions that may have affected growth,                maturation, physical activity, nutritional status, or                  their cardiometabolic health. Subjects with missing                         information for any of the variables were also                             excluded. All participants completed a validated                     questionnaire on personal and familial histories of CV or metabolic diseases, socio-demographics, and lifestyle habits. Anthropometric, hemodynamic and biological              parameters collected included height, weight, waist                  circumference, BP, heart rate (HR), PWV, and fasting       capillary blood glucose. </p>
      <sec id="idm1842661708">
        <title>Hemodynamic Parameters </title>
        <p>All hemodynamic measurements were                            performed, after a 15 minutes rest, in the sitting position and in standardized conditions <xref ref-type="bibr" rid="ridm1841996948">25</xref>. BP and PWV were recorded on the dominant arm. Systolic BP (SBP),             diastolic BP (DBP), mean arterial pressure (MAP)                     calculed as DBP plus 1/3(SBP-DBP), HR, and PWV were measured using a validated brachial cuff-based                    oscillometric device (Mobil-O-Graph®; IEM; Stolberg, Germany). Two consecutive measurements were taken at time intervals of 5 minutes, using a cuff’s width                 adjusted to the arm’s circumference. In case of             inaccurate recording, the measurement was repeated. The mean of two accurate hemodynamic readings was used. The device used was approved by the Food and Drug Administration, with its BP detection unit validated according to the European Society of Hypertension <xref ref-type="bibr" rid="ridm1841991980">26</xref> recommendations. All procedures were performed by a single medical investigator. </p>
      </sec>
      <sec id="idm1842660916">
        <title>Anthropometric and Biological Measurements</title>
        <p>Height (m) was measured using a height gauge graduated in cm (Seca, Germany) and weight (kg) was measured using an electronic scale (Seca, Germany). The body mass index (BMI) was determined by dividing the weight (kilogram) by the square of the height (meter). Overweight was considered for a BMI ≥ 25 and &lt;30.0 kg/m² and obesity for a BMI ≥30 kg/m². Waist circumference (cm) was measured, and abdominal               obesity was considered for a waist circumference ≥102 cm (men) and ≥88 cm (women) <xref ref-type="bibr" rid="ridm1841990756">27</xref>. LBW for             gestational age was defined BW adjusted for gestational age was below the 10th percentile or &lt; -2 on the              standard deviations from mean <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1841986004">28</xref>. </p>
        <p>Participants were instructed to fast for at least 8h overnight and fasting capillary blood glucose was              determined using a glucometer (Accu-Chek Aviva, Roche, Mannheim, Germany). Diabetes mellitus was             defined by a fasting capillary blood glucose ≥126 mg/dl, and impaired fasting glucose (“prediabetes”) defined as a fasting blood glucose between 100-125 mg/dl, in the absence of self-reported diabetes <xref ref-type="bibr" rid="ridm1842012644">29</xref>. </p>
      </sec>
      <sec id="idm1842660700">
        <title>Ethical Considerations</title>
        <p>Participation to the study was voluntary, and each participant gave prior informed consent. The            confidentiality of data was ensured by anonymity of              patients in data sheets. We obtained an ethical                   clearance from the Institutional Ethics Committee of the University of Douala (N°1259 CEI-Udo/02/2018/T). </p>
      </sec>
      <sec id="idm1842661132">
        <title>Statistical Analyses</title>
        <p>Quantitative data are presented as mean ± standard deviation while qualitative data are              presented as count and percentages. Non-parametric Mann-Whitney and Chi2 tests have been used to                compare quantitative and quantitative data respectively according to BW ranges. Multivariable linear regression model has been used to determine predictive factors for PWV. For assessment of potential impact of BW on EVA, PWV was adjusted for age, sex, MAP and BMI.                  Differences have been considered significant for p&lt;0.05. All statistical analysis was performed using SPSS 20    software. </p>
      </sec>
    </sec>
    <sec id="idm1842660628" sec-type="results">
      <title>Results</title>
      <sec id="idm1842661780">
        <title>Anthropometric, Hemodynamic and Biological                Characteristics</title>
        <p>The mean gestational age at delivery for our study participants was 39 weeks (Ranging from from 37 to 41 weeks) and the mean birth weight was 3267 g. Among the 120 participants, 28 (23.3%) had a history of LBW. Mean age was comparable between subjects with LBW and those with normal birth weight (NBW). The sex ratio was also similar between LBW and NBW groups (<xref ref-type="table" rid="idm1849686116">Table 1</xref>).</p>
        <table-wrap id="idm1849686116">
          <label>Table 1.</label>
          <caption>
            <title> characteristics of study participants according to birth weight</title>
          </caption>
          <table rules="all" frame="box">
            <tbody>
              <tr>
                <td> </td>
                <td>Total(N=120)</td>
                <td>BW &lt; 3000g(N=28)</td>
                <td>BW≥3000g(N=92)</td>
                <td>p</td>
              </tr>
              <tr>
                <td>Age (years)</td>
                <td>26 ±5</td>
                <td>27±6</td>
                <td>25±5</td>
                <td>0.084</td>
              </tr>
              <tr>
                <td>Female</td>
                <td>55 (45.8)</td>
                <td>12 (42.9)</td>
                <td>43 (46.7)</td>
                <td>0.885</td>
              </tr>
              <tr>
                <td>BW (g)</td>
                <td>3267 ±560</td>
                <td>2496±410</td>
                <td>3501±354</td>
                <td>&lt; 0.0001</td>
              </tr>
              <tr>
                <td>Weight (kg)</td>
                <td>72.4 ±13.9</td>
                <td>72.1±14</td>
                <td>72.5±14.1</td>
                <td>0.68</td>
              </tr>
              <tr>
                <td>Height (m)</td>
                <td>1.71 ±0.09</td>
                <td>1.70±0.09</td>
                <td>1.71±0.09</td>
                <td>0.601</td>
              </tr>
              <tr>
                <td>BMI (kg/m²)</td>
                <td>24.8 ±4.8</td>
                <td>24.9±4.3</td>
                <td>24.7±5</td>
                <td>0.814</td>
              </tr>
              <tr>
                <td>Waist (cm)</td>
                <td>81 ±13</td>
                <td>81.3±11.4</td>
                <td>80.6±13</td>
                <td>0.818</td>
              </tr>
              <tr>
                <td>Glycemia (mg/dl)</td>
                <td>99 ±8.9</td>
                <td>114±13.1</td>
                <td>94±7.3</td>
                <td>0.105</td>
              </tr>
              <tr>
                <td>aPWV (m/s)</td>
                <td>5.45 ±0.34</td>
                <td>5.52 ±0.39</td>
                <td>5.37±0.27</td>
                <td>0.083</td>
              </tr>
              <tr>
                <td>SBP (mmHg)</td>
                <td>128 ±2</td>
                <td>129.0±2.6</td>
                <td>128.0±2.1</td>
                <td>0.084</td>
              </tr>
              <tr>
                <td>DBP (mmHg)</td>
                <td>76 ±5</td>
                <td>78.1±5.9</td>
                <td>75.8±4.6</td>
                <td>0.084</td>
              </tr>
              <tr>
                <td>MAP (mmHg)</td>
                <td>100 ±4</td>
                <td>101.1±4.2</td>
                <td>99.4±3.3</td>
                <td>0.084</td>
              </tr>
              <tr>
                <td>HR (bpm)</td>
                <td>74 ±10</td>
                <td>74±9</td>
                <td>74±10</td>
                <td>0.557</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="idm1842577940">
              <label/>
              <p>BW = Birth weight for gestational age; BMI=Body Mass Index; SDP= Systolic Blood Pressure, DBP = Diastolic Blood Pressure, MAP= Mean Arterial Pressure; HR= Heart Rate; aPWV = Pulse Wave Velocity adjusted for age and MAP ; N : number of participants</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>Compared to NBW, the age- and MAP-adjusted PWV (aPWV) of LBW individuals in general was        higher (on average +15 cm/s), although the observed difference did not reach statistical significance (P=0.089). The age adjusted SBP, DBP, and MAP levels were slightly higher, albeit non-significantly in subjects with LBW compared to NBW (p=0.084). Mean blood            glucose was higher and in the pre-diabetes thresholds in those with LBW compared to subjects with NBW (P=0.105).</p>
      </sec>
      <sec id="idm1842578156">
        <title>Association Between PWV and Age or MAP </title>
        <p>As expected, the PWV was proportionally and positively correlated with chronological age (r=0.35; p&lt;0.0001), while the increase in MAP resulted in a             proportional acceleration of PWV (r=0.58; p&lt;0.0001).</p>
        <p><italic>Distribution of CV Risk Factors as a Function of BW </italic>As shown in <xref ref-type="fig" rid="idm1849587156">Figure 1</xref>, the prevalence of                  overweight/obesity, visceral obesity, prediabetes and                  diabetes was higher in individuals with LBW: 42.9% vs 37%, 35.7% vs 31.5%, 10.7% vs 3.3% and 3.6% vs 1.1% in individuals with NBW, respectively. By contrast, the age-adjusted prevalence of hypertension was higher in NBW subjects compared to those with LBW: 25 vs 21%.</p>
        <fig id="idm1849587156">
          <label>Figure 1.</label>
          <caption>
            <title> Prevalence of cardiometabolic risk factors according to birth weight</title>
          </caption>
          <graphic xlink:href="images/image1.jpg" mime-subtype="jpg"/>
        </fig>
      </sec>
      <sec id="idm1842574988">
        <title>Hemodynamic and Metabolic Characteristics According to BW in Women (<xref ref-type="table" rid="idm1849600476">Table 2</xref>) and in Overweight/Obese Subjects (<xref ref-type="table" rid="idm1849530292">Table 3</xref>)</title>
        <p>Mean aPWV was significantly (p=0.038) higher (on average +3 cm/s) in women with LBW compared to women with NBW (<xref ref-type="table" rid="idm1849600476">Table 2</xref>). Moreover, as compared to controls, women with LBW had significantly higher              mean blood glucose levels, above the 126 mg/dL       threshold defining diabetes mellitus; however, the                    observed difference was not statistically significant. In men, all hemodynamic and metabolic parameters were comparable between subjects with LBW and those with NBW (<italic>data not shown</italic>). </p>
        <table-wrap id="idm1849600476">
          <label>Table 2.</label>
          <caption>
            <title> Clinical, hemodynamic and biological data in women according to birth weight </title>
          </caption>
          <table rules="all" frame="box">
            <tbody>
              <tr>
                <td> </td>
                <td>≥ 3000 gN=43</td>
                <td>&lt; 3000 gN=12</td>
                <td>P</td>
              </tr>
              <tr>
                <td>  Age (years)</td>
                <td>24 ±5</td>
                <td>29 ±6</td>
                <td>0.036</td>
              </tr>
              <tr>
                <td>  BMI (kg /m<xref ref-type="bibr" rid="ridm1842320516">2</xref>)</td>
                <td>25.7 ±5.6</td>
                <td>26.1 ±4.7</td>
                <td>0.768</td>
              </tr>
              <tr>
                <td>  Glycemia (mg/dl)</td>
                <td>103 ±10.6</td>
                <td>148 ±20.0</td>
                <td>0.213</td>
              </tr>
              <tr>
                <td> aPWV (m/s)</td>
                <td>5.3 ±0.3</td>
                <td>5.6 ±0.4</td>
                <td>0.038</td>
              </tr>
              <tr>
                <td>    SBP (mmHg)</td>
                <td>125 ±12</td>
                <td>120 ±8</td>
                <td>0.262</td>
              </tr>
              <tr>
                <td>   DBP (mmHg)</td>
                <td>76 ±12</td>
                <td>76 ±6</td>
                <td>0.386</td>
              </tr>
              <tr>
                <td>   MAP (mmHg)</td>
                <td>99 ±10</td>
                <td>94 ±7</td>
                <td>0.262</td>
              </tr>
              <tr>
                <td>    PP (mmHg)</td>
                <td>38 ±9</td>
                <td>36 ±8</td>
                <td>0.698</td>
              </tr>
              <tr>
                <td>    HR (bpm)</td>
                <td>77 ±11</td>
                <td>78 ±10</td>
                <td>0.807</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="idm1842541908">
              <label/>
              <p>BMI=Body Mass Index; SDP= Systolic Blood Pressure, DBP= Diastolic Blood Pressure,            MBP= Mean Arterial Pressure; HR= Heart Rate; aPWV = Pulse Wave Velocity adjusted for age and MAP; N : number of participants; PP= Pulse Pressure , </p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>As shown in <xref ref-type="table" rid="idm1849530292">Table 3</xref>, mean blood glucose levels were significantly higher in overweight/obese individuals with LBW, also above the threshold defining diabetes mellitus, compared to overweight/obese subjects with NBW (P=0.003). Furthermore, the aPWV was slightly higher (on average +2 cm/s) in overweight/obese               subjects with LBW, albeit non-significantly (p=0.15). </p>
        <table-wrap id="idm1849530292">
          <label>Table 3.</label>
          <caption>
            <title> Anthropometric, hemodynamic and biologic parameters according to birth weight in overweight/obese participants (Body mass index ≥ 25 kg/m²)</title>
          </caption>
          <table rules="all" frame="box">
            <tbody>
              <tr>
                <td> </td>
                <td>
                  <bold>BW ≥ 3000 g</bold>
                  <bold>N=34</bold>
                </td>
                <td>
                  <bold>BW &lt; 3000 g</bold>
                  <bold>N=12</bold>
                </td>
                <td>
                  <bold>P</bold>
                </td>
              </tr>
              <tr>
                <td>
                  <bold>Age (</bold>
                  <bold>years</bold>
                  <bold>)</bold>
                </td>
                <td>27 ±5</td>
                <td>31 ±7</td>
                <td>0.146</td>
              </tr>
              <tr>
                <td>
                  <bold>BMI (kg /m</bold>
                  <xref ref-type="bibr" rid="ridm1842320516">2</xref>
                  <bold>)</bold>
                </td>
                <td>29.9 ±4.0</td>
                <td>29.0 ±2.8</td>
                <td>0.634</td>
              </tr>
              <tr>
                <td>
                  <bold>Glycemia</bold>
                  <bold> (mg /dl)</bold>
                </td>
                <td>87 ±1.1</td>
                <td>154 ±19.7</td>
                <td>0.003</td>
              </tr>
              <tr>
                <td>
                  <bold>aPMW</bold>
                  <bold> (m/s)</bold>
                </td>
                <td>5.5 ±0.3</td>
                <td>5.7 ±0.4</td>
                <td>0.146</td>
              </tr>
              <tr>
                <td>
                  <bold>SBP (</bold>
                  <bold>mmHg</bold>
                  <bold>)</bold>
                </td>
                <td>134 ±11</td>
                <td>127 ±10</td>
                <td>0.127</td>
              </tr>
              <tr>
                <td>
                  <bold>DBP (</bold>
                  <bold>mmHg</bold>
                  <bold>)</bold>
                </td>
                <td>80 ±13</td>
                <td>81 ±9</td>
                <td>0.557</td>
              </tr>
              <tr>
                <td>
                  <bold>MAP (</bold>
                  <bold>mmHg</bold>
                  <bold>)</bold>
                </td>
                <td>104 ±10</td>
                <td>102 ±9</td>
                <td>0.507</td>
              </tr>
              <tr>
                <td>
                  <bold>PP (</bold>
                  <bold>mmHg</bold>
                  <bold>)</bold>
                </td>
                <td>41 ±9</td>
                <td>39 ±10</td>
                <td>0.438</td>
              </tr>
              <tr>
                <td>
                  <bold>HR (</bold>
                  <bold>mmHg</bold>
                  <bold>)</bold>
                </td>
                <td>76 ±12</td>
                <td>73 ±10</td>
                <td>0.556</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="idm1842503164">
              <label/>
              <p>BMI=Body Mass Index; SDP= Systolic Blood Pressure, DBP= Diastolic Blood Pressure, MAP= Mean Arterial Pressure; HR= Heart Rate; aPWV = Pulse Wave Velocity adjusted for age and MAP; N : number of participants; PP= Pulse Pressure</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </sec>
      <sec id="idm1842503668">
        <title>Independent Determinants of Pulse Wave Velocity in the Overall Study Population and in Age Groups</title>
        <p>In multivariate regression analysis performed in all participants (<xref ref-type="table" rid="idm1849491772">Table 4</xref>), age, BMI, male sex and MAP were independently associated with premature aortic             aging assessed by PWV (Model 1). Birth weight adjusted for gestational age did not show a significant positive    association with PWV when adjusting for age and sex (Model 2), and for age, sex, BMI and MAP (Model 3). For multiple regression in both two age groups (<xref ref-type="table" rid="idm1849421324">Table 5</xref>), PWV was independently associated with age and MAP, while in youngest age group (18-27 years), BMI and male sex were also independently related to early aortic aging (All p&lt;0.05). Birth weight was not significantly and independently associated with PWV in the both two age groups when adjusting for covariates in Model 1, Model 2 and Model 3, respectively. Of note, in              youngest age group, heart rate emerged as independent determinant of PWV after adjusting for age and sex (Modele2), and  for age, sex, BMI and MAP (<xref ref-type="table" rid="idm1849530292">Table 3</xref>).</p>
        <table-wrap id="idm1849491772">
          <label>Table 4.</label>
          <caption>
            <title> Multiple regression with pulse wave velocity as dependent variable in all participants</title>
          </caption>
          <table rules="all" frame="box">
            <tbody>
              <tr>
                <td> </td>
                <td>
                  <bold>Model 1</bold>
                </td>
                <td> </td>
                <td>
                  <bold>Model 2</bold>
                </td>
                <td> </td>
                <td>
                  <bold>Model 3</bold>
                </td>
                <td> </td>
              </tr>
              <tr>
                <th>
                  <bold>Variables</bold>
                </th>
                <td>
                  <bold>β (IC à 95%)</bold>
                </td>
                <td>
                  <bold>p</bold>
                </td>
                <td>
                  <bold>β (IC à 95%)</bold>
                </td>
                <td>
                  <bold>p</bold>
                </td>
                <td>
                  <bold>β (IC à 95%)</bold>
                </td>
                <td>
                  <bold>p</bold>
                </td>
              </tr>
              <tr>
                <td>
                  <bold>Age (years)</bold>
                </td>
                <td>0.07 (0.05; 0.08)</td>
                <td>&lt; 0.001</td>
                <td>0.06 (0.05; 0.08)</td>
                <td>&lt; 0.001</td>
                <td>0.03 (0.02; 0.05)</td>
                <td>&lt; 0.001</td>
              </tr>
              <tr>
                <td>
                  <bold>Male sex</bold>
                </td>
                <td>0.24 (0.04; 0.44)</td>
                <td>0.022</td>
                <td>0.21 (0.05; 0.38)</td>
                <td>0.011</td>
                <td>0.15 (0.03; 0.26)</td>
                <td>0.011</td>
              </tr>
              <tr>
                <td>
                  <bold>BW (kg)</bold>
                </td>
                <td>0.07 (0.45; -0.11)</td>
                <td>0.761</td>
                <td>0.12 (-0.03; 0.26)</td>
                <td>0.117</td>
                <td>0.05 (-0.04; 0.15)</td>
                <td>0.265</td>
              </tr>
              <tr>
                <td>
                  <bold>MAP (mmHg)</bold>
                </td>
                <td>0.04 (0.03; 0.05)</td>
                <td>&lt; 0.001</td>
                <td>0.03 (0.03; 0.04)</td>
                <td>&lt; 0.001</td>
                <td>0.03 (0.02; 0.04)</td>
                <td>&lt; 0.001</td>
              </tr>
              <tr>
                <td>
                  <bold>BMI (kg/m²)</bold>
                </td>
                <td>0.46 (0.27; 0.66)</td>
                <td>&lt; 0.001</td>
                <td>0.04 (0.02; 0.06)</td>
                <td>&lt; 0.001</td>
                <td>0.02 (0.01; 0.04)</td>
                <td>0.002</td>
              </tr>
              <tr>
                <td>
                  <bold>HR (bpm)</bold>
                </td>
                <td>0,003 (-0,01; 0,01)</td>
                <td>0,504</td>
                <td>0,01 (0,00; 0,02)</td>
                <td>0,047</td>
                <td>0,001 (-0,01; 0,01)</td>
                <td>0,835</td>
              </tr>
              <tr>
                <td>
                  <bold>Glycemia (g/L)</bold>
                </td>
                <td>-0.06 (-0.15; 0.03)</td>
                <td>0.205</td>
                <td>-0.06 (-0.15; 0.03)</td>
                <td>0.205</td>
                <td>-0.03 (-0.10; 0.03)</td>
                <td>0.273</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="idm1842505540">
              <label/>
              <p>Model 1: unadjusted</p>
            </fn>
            <fn id="idm1842505324">
              <label/>
              <p>Model 2: adjusted for age and sex</p>
            </fn>
            <fn id="idm1842455420">
              <label/>
              <p>Model 3: adjusted for age, sex, MAP and BMI</p>
            </fn>
            <fn id="idm1842454772">
              <label/>
              <p>BW: birth weight adjusted for gestational age. MAP: mean arterial pressure; HR: heart rate; BMI: body mass index</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <table-wrap id="idm1849421324">
          <label>Table 5.</label>
          <caption>
            <title> Multiple regression with pulse wave velocity as dependent variable in different age groups </title>
          </caption>
          <table rules="all" frame="box">
            <tbody>
              <tr>
                <td>  </td>
                <td colspan="6">Age 18 - 27</td>
                <td colspan="10">Age 28 - 42 </td>
              </tr>
              <tr>
                <td/>
                <td colspan="2">Model 1</td>
                <td colspan="2">Model 2</td>
                <td colspan="2">Model 3</td>
                <td colspan="3">Model 1</td>
                <td colspan="4">Model 2</td>
                <td colspan="3">Model 3</td>
              </tr>
              <tr>
                <td>Variables</td>
                <td>β</td>
                <td>p</td>
                <td>β</td>
                <td>p</td>
                <td>β</td>
                <td>p</td>
                <td>β</td>
                <td>p</td>
                <td>p</td>
                <td>β</td>
                <td>β</td>
                <td>p</td>
                <td>p</td>
                <td>β</td>
                <td>β</td>
                <td>p</td>
              </tr>
              <tr>
                <td>Age (years)</td>
                <td>0,05</td>
                <td>6</td>
                <td>0,05</td>
                <td>12</td>
                <td>0,01</td>
                <td>418</td>
                <td>0,09</td>
                <td>1</td>
                <td>1</td>
                <td>0,10</td>
                <td>0,10</td>
                <td>&lt; 0,001</td>
                <td>&lt; 0,001</td>
                <td>0,05</td>
                <td>0,05</td>
                <td>1</td>
              </tr>
              <tr>
                <td>Male sex</td>
                <td>0,25</td>
                <td>17</td>
                <td>0,21</td>
                <td>36</td>
                <td>0,16</td>
                <td>24</td>
                <td>-0,10</td>
                <td>579</td>
                <td>579</td>
                <td>0,34</td>
                <td>0,34</td>
                <td>37</td>
                <td>37</td>
                <td>0,23</td>
                <td>0,23</td>
                <td>35</td>
              </tr>
              <tr>
                <td>BW (kg)</td>
                <td>0,00</td>
                <td>968</td>
                <td>0,06</td>
                <td>542</td>
                <td>0,02</td>
                <td>730</td>
                <td>0,18</td>
                <td>0,18</td>
                <td>257</td>
                <td>257</td>
                <td>0,19</td>
                <td>0,19</td>
                <td>120</td>
                <td>120</td>
                <td>0,06</td>
                <td>461</td>
              </tr>
              <tr>
                <td>MAP (mmHg)</td>
                <td>0,03</td>
                <td>&lt; 0,001</td>
                <td>0,03</td>
                <td>&lt; 0,001</td>
                <td>0,03</td>
                <td>&lt; 0,001</td>
                <td>0,05</td>
                <td>0,05</td>
                <td>&lt; 0,001</td>
                <td>&lt; 0,001</td>
                <td>0,04</td>
                <td>0,04</td>
                <td>&lt; 0,001</td>
                <td>&lt; 0,001</td>
                <td>0,04</td>
                <td>&lt; 0,0001</td>
              </tr>
              <tr>
                <td>HR (bpm)</td>
                <td>5</td>
                <td>346</td>
                <td>12</td>
                <td>16</td>
                <td>12</td>
                <td>16</td>
                <td>5</td>
                <td>5</td>
                <td>606</td>
                <td>606</td>
                <td>-0,03</td>
                <td>-0,03</td>
                <td>726</td>
                <td>726</td>
                <td>-3</td>
                <td>534</td>
              </tr>
              <tr>
                <td>BMI (kg/m²)</td>
                <td>0,05</td>
                <td>&lt; 0,001</td>
                <td>0,06</td>
                <td>&lt; 0,001</td>
                <td>0,03</td>
                <td>3</td>
                <td>0,03</td>
                <td>0,03</td>
                <td>51</td>
                <td>51</td>
                <td>0,03</td>
                <td>0,03</td>
                <td>58</td>
                <td>58</td>
                <td>0,02</td>
                <td>54</td>
              </tr>
              <tr>
                <td>Glycemia (g/L)</td>
                <td>-0,05</td>
                <td>287</td>
                <td>-0,06</td>
                <td>223</td>
                <td>-0,03</td>
                <td>285</td>
                <td>0,59</td>
                <td>0,59</td>
                <td>468</td>
                <td>468</td>
                <td>-0,29</td>
                <td>-0,29</td>
                <td>675</td>
                <td>675</td>
                <td>-0,79</td>
                <td>63</td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn id="idm1842416012">
              <label/>
              <p>Model 1: unadjusted</p>
            </fn>
            <fn id="idm1842417668">
              <label/>
              <p>Model 2: adjusted for age and sex</p>
            </fn>
            <fn id="idm1842417164">
              <label/>
              <p>Model 3: adjusted for age, sex, MAP and BMI</p>
            </fn>
            <fn id="idm1842417812">
              <label/>
              <p>BW: birth weight adjusted for gestational age. MAP: mean arterial pressure; HR: heart rate; BMI: body mass index</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </sec>
    </sec>
    <sec id="idm1842416588" sec-type="discussion">
      <title>Discussion</title>
      <p>The findings of this observational study suggest that LBW can have deleterious late effects on arterial distensibility, but mainly in women who might suffer premature vascular aging. However, age, sex, BMI              and MAP emerged as independent determinants of PWV, unlike BW adjusted for gestational age, which was not independently associated with EVA. Our results also show that individuals with LBW have an increased risk of glucose homeostasis abnormalities and obesity in late adolescence and adulthood. To our knowledge, this study is the first to evaluate the long-term effects of LBW on cardiometabolic risk in Cameroonian subjects.</p>
      <p>Evidence suggests that unfavorable <italic>in utero</italic>             environment, induced by a (quantitative and/or                qualitative) fetal undernutrition or maternal placental              insufficiency, may program the fetus, via epigenetic                  effects in particular, to subsequent development of CV and metabolic diseases, and to risk factors such as       abnormal PWV, obesity and T2DM as phenotypic                 hallmarks <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842033676">21</xref><xref ref-type="bibr" rid="ridm1842028420">22</xref><xref ref-type="bibr" rid="ridm1842006092">23</xref>. </p>
      <p>To provide further insight into possible                   pathophysiological mechanisms linking LBW to CVD risk in adulthood, we measured aortic PWV which has                previously been shown to be a powerful marker of                   EVA <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842320516">2</xref><xref ref-type="bibr" rid="ridm1842421764">3</xref> and an independent determinant of CV                    morbidity and mortality <xref ref-type="bibr" rid="ridm1842063452">16</xref><xref ref-type="bibr" rid="ridm1842059636">17</xref>. Age and BP are two major determinants of arterial stiffening <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842320516">2</xref><xref ref-type="bibr" rid="ridm1842421764">3</xref>. This was also the case in this study, in which we found that age and SBP were independently associated with PWV, reflecting aortic elasticity loss as a result of                chronological aging and hypertension. Stiffening of large arteries, a major consequence of aging, results from           alteration of their viscoelastic properties following wall remodeling (from eg. accumulation of calcium, decrease in elastin content, and increase in collagen). This leads to increased arterial stiffness (PWV), with rapid and  early wave reflections from peripheral arteries                    towards the aorta, leading to increased SBP, PP and                    decreased DBP <xref ref-type="bibr" rid="ridm1842084948">15</xref><xref ref-type="bibr" rid="ridm1842063452">16</xref>. Consistent with previous                  observations <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842059636">17</xref><xref ref-type="bibr" rid="ridm1842052652">18</xref>, BMI and male sex emerged as independent determinant of PWV, even in the whole study populations, and especially in the youngest                participants age group, 8-27 years old. Moreover, in youngest age group, HR shows significant positive                 association with PWV after adjusting for age, sex, BMI and MAP. This finding was in keeping with previous               observations in young adults <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842066260">19</xref>.</p>
      <p>Beyond age, several CV risk factors such as                LBW may also promote premature aging of the                     aorta <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842320516">2</xref><xref ref-type="bibr" rid="ridm1842421764">3</xref>.  Although our study did not find an independent association between LBW and PWV,        likely as a result of the small sample size of the study, we nevertheless found that in young Cameroonian adults with a history of LBW, overweight and obesity were significantly associated with an increased PWV, even after adjusting for age and MAP. The association between LBW and PWV remains debated. Indeed, Miles et al <xref ref-type="bibr" rid="ridm1842156020">5</xref> studied 882 participants in the United Kingdom, in whom increased arterial stiffness was not associated with LBW. By contrast, some studies have also                    documented stiffer arteries in apparently healthy                 children and adults with LBW <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842141204">8</xref><xref ref-type="bibr" rid="ridm1842073716">14</xref><xref ref-type="bibr" rid="ridm1842010124">30</xref>.</p>
      <p>A major finding of the present study was the markedly increased PWV observed in women with LBW, that persisted even after adjustment for age and         MAP compared to those with NBW. This observation     corroborates that of Martyn et al <xref ref-type="bibr" rid="ridm1842320516">2</xref> on 338 individuals born between 1939 and 1940, in whom intrauterine growth retardation was associated with increased                 aorto-iliac and femoro-popliteal-tibial PWV by the                 age of 50 years, regardless of adult lifestyles. The                  putative mechanisms underlying the increase in           arterial stiffness in adulthood include be changes in                         angiogenesis during critical phases of intrauterine life caused by episodes of fetal growth inhibition and local hemodynamic anomalies <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842320516">2</xref><xref ref-type="bibr" rid="ridm1842421764">3</xref><xref ref-type="bibr" rid="ridm1842170164">4</xref> and early endothelial dysfunction as well as premature remodeling of large      arteries, ascribed to mechanical and growth factors, fetal protein deficiency, and detrimental effects of cytokines and proteases <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842320516">2</xref><xref ref-type="bibr" rid="ridm1842079548">13</xref><xref ref-type="bibr" rid="ridm1842073716">14</xref>.  </p>
      <p>We also observed that the MAP of participants with LBW for gestational age was approximately 2 mmHg higher than that of NBW participants (≥ 3000g). However, this difference was not statistically significant. Nevertheless, this finding is consistent with data in the literature, which reported an association between LBW and increased BP in adulthood <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842320516">2</xref><xref ref-type="bibr" rid="ridm1842421764">3</xref>. However, this association is debated <xref ref-type="bibr" rid="ridm1842141204">8</xref><xref ref-type="bibr" rid="ridm1841949604">33</xref><xref ref-type="bibr" rid="ridm1841946580">34</xref>. In the present study the prevalence of hypertension was higher                  among participants with NBW compared to those with LBW. This finding is inconsistent with observational                     studies that reported an increased risk of                             adult-onset hypertension in Caucasians with                         LBW <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842320516">2</xref><xref ref-type="bibr" rid="ridm1842421764">3</xref><xref ref-type="bibr" rid="ridm1842170164">4</xref>, and also with data from a study conducted in Nigeria, showing a high prevalence               of hypertension in participants born during the Biafra war (1968-1970) and exposed to severe famine and materno-fetal and infantile malnutrition, compared with controls born in the same region just before the war, i.e. between 1965-1967 <xref ref-type="bibr" rid="ridm1841958100">31</xref>. Our findings, although based on a small sample of subjects, are nevertheless in                     line with data from international epidemiological                          surveys <xref ref-type="bibr" rid="ridm1842141204">8</xref><xref ref-type="bibr" rid="ridm1842128180">9</xref><xref ref-type="bibr" rid="ridm1842125084">10</xref>. </p>
      <p>A component of hypertension in adulthood was associated with unfavorable intrauterine conditions in mid- and late gestation, leading to disproportionate fetal growth <xref ref-type="bibr" rid="ridm1842310604">1</xref><xref ref-type="bibr" rid="ridm1842320516">2</xref><xref ref-type="bibr" rid="ridm1842421764">3</xref><xref ref-type="bibr" rid="ridm1842170164">4</xref>. The presumed role of fetal and/or early childhood malnutrition in driving the late burden of hypertension has not been examined in Africa, neither in Cameroon nor in other sub-Saharan African countries. Further large-scale studies are needed to better assess the impact of uterine malnutrition and LBW on the            burden of hypertension in adulthood.</p>
      <p>Of note, participants with LBW had an increased prevalence of overweight/obesity and visceral obesity. Our findings are consistent with previous observations showing a greater propensity to develop central and           visceral obesity in adulthood in subjects with                       LBW <xref ref-type="bibr" rid="ridm1842037708">20</xref><xref ref-type="bibr" rid="ridm1842033676">21</xref><xref ref-type="bibr" rid="ridm1842006092">23</xref><xref ref-type="bibr" rid="ridm1841958100">31</xref><xref ref-type="bibr" rid="ridm1841941684">35</xref><xref ref-type="bibr" rid="ridm1841935636">36</xref>. Despite LBW and substantial risk of early postnatal underweight, former                   fetal-malnourished fetuses have higher subsequent                     obesity indices than controls with NBW, suggesting                potential catch-up growth in adolescence of early                   adulthood. The latter, apparently beneficial, probably          reflects rapid weight gain associated with poor linear growth, defining a phenotype of "obese stunted" subject with unfavorable body composition, including fat                   accumulation (especially visceral) and sarcopenia                 without height gain <xref ref-type="bibr" rid="ridm1842006092">23</xref><xref ref-type="bibr" rid="ridm1841991980">26</xref><xref ref-type="bibr" rid="ridm1841958100">31</xref><xref ref-type="bibr" rid="ridm1841941684">35</xref><xref ref-type="bibr" rid="ridm1841935636">36</xref>. </p>
      <p>Another relevant finding of the present study is the high rate of glucometabolic abnormalities in subjects with LBW, globally and particularly in those with                    overweight/obesity in adulthood. This finding is in line with previous observations showing that subjects with LBW are at increased risk for incident metabolic                 syndrome <xref ref-type="bibr" rid="ridm1842033676">21</xref><xref ref-type="bibr" rid="ridm1842028420">22</xref><xref ref-type="bibr" rid="ridm1842006092">23</xref> and T2DM <xref ref-type="bibr" rid="ridm1842028420">22</xref><xref ref-type="bibr" rid="ridm1841931748">37</xref><xref ref-type="bibr" rid="ridm1841928148">38</xref><xref ref-type="bibr" rid="ridm1841912804">39</xref>. This                   suggests that insulin resistance acquired in the context of visceral obesity is insufficiently compensated by                   compensatory hyperinsulinemia in many of these                    subjects with LBW, and that their insulin-secretory                   function is also less efficient in counteracting these                    effects of obesity <xref ref-type="bibr" rid="ridm1842006092">23</xref><xref ref-type="bibr" rid="ridm1841931748">37</xref><xref ref-type="bibr" rid="ridm1841912804">39</xref>. Experimental models                  suggest that protein deficiency resulting from                     materno-fetal nutritional imbalance may lead to                          developmental programming of carbohydrate                           homeostasis abnormalities in adulthood <xref ref-type="bibr" rid="ridm1841928148">38</xref><xref ref-type="bibr" rid="ridm1841908484">40</xref>.</p>
      <sec id="idm1842414716">
        <title>Study Limitations</title>
        <p>This study has several obvious limitations. First, this was a cross-sectional study with limited sample size and hence limited statistical power to detect magnitude of the effects of BW on risk of CV and metabolic              diseases and exhibiting their associated major risk                     factors in adulthood in the general Cameroonian                  population. Further studies are needed, relying on larger samples size and including other regions of Cameroon. Second, several potentially confounding factors,                    such as socio-economic status, lipid profile,                    glycated hemoglobin, insulinemia, c-reactive protein, were not assessed due to financial and logistical                   constraints. Last, BW represents a single measurement and does not account for <italic>in utero</italic> growth trajectory and is not adjusted to parents’ heights. Proportionality                indices assessing body size including body length, BMI at birth, and/or birth’s ponderal index (birth weight/birth length³), more accurately reflect fetal growth trajectory and may help differentiate fetuses who are                       constitutionally small for gestational age from fetuses who failed to reach their <italic>in utero</italic> growth potential, were not available for this survey <xref ref-type="bibr" rid="ridm1841908484">40</xref>. A strength of the              present study is its originality and its design as stringent as possible, and the use of validated standard                  procedures to assess the variables of interest. </p>
      </sec>
    </sec>
    <sec id="idm1842415580" sec-type="conclusions">
      <title>Conclusion </title>
      <p>This study suggests that, whereas LBW is                associated with increased aortic stiffness in young    adulthood, mainly in women, the association was                        predominantly driven by age and blood pressure. Once adult, subjects with LBW exhibited higher obesity indices and poorer glucose homeostasis. Further large-scale studies are needed to assess the impact of BW and body size on arterial stiffness and metabolic disorders in later life.</p>
    </sec>
  </body>
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