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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Presence of the Metabolic Syndrome Is Not a Better Predictor of Cardiovascular Disease Than the Sum of Its Components in HIV-Infected Individuals</title><author><name sortKey="Worm, Signe W" sort="Worm, Signe W" uniqKey="Worm S" first="Signe W." last="Worm">Signe W. Worm</name><affiliation><nlm:aff id="aff1">Copenhagen HIV Programme, University of Copenhagen, Copenhagen, Denmark</nlm:aff></affiliation></author><author><name sortKey="Sabin, Caroline A" sort="Sabin, Caroline A" uniqKey="Sabin C" first="Caroline A." last="Sabin">Caroline A. Sabin</name><affiliation><nlm:aff id="aff2">Royal Free and University College, London, U.K.</nlm:aff></affiliation></author><author><name sortKey="Reiss, Peter" sort="Reiss, Peter" uniqKey="Reiss P" first="Peter" last="Reiss">Peter Reiss</name><affiliation><nlm:aff id="aff3">Academic Medical Center, Amsterdam, the Netherlands</nlm:aff></affiliation></author><author><name sortKey="El Sadr, Wafaa" sort="El Sadr, Wafaa" uniqKey="El Sadr W" first="Wafaa" last="El-Sadr">Wafaa El-Sadr</name><affiliation><nlm:aff id="aff4">Harlem Hospital Center, Division of Infectious Diseases, New York, New York</nlm:aff></affiliation></author><author><name sortKey="D Arminio Monforte, Antonella" sort="D Arminio Monforte, Antonella" uniqKey="D Arminio Monforte A" first="Antonella" last="D'Arminio Monforte">Antonella D'Arminio Monforte</name><affiliation><nlm:aff id="aff5">University of Milan, Milan, Italy</nlm:aff></affiliation></author><author><name sortKey="Pradier, Christian" sort="Pradier, Christian" uniqKey="Pradier C" first="Christian" last="Pradier">Christian Pradier</name><affiliation><nlm:aff id="aff6">Hôpital Archet 1, Nice, France</nlm:aff></affiliation></author><author><name sortKey="Thiebaut, Rodolphe" sort="Thiebaut, Rodolphe" uniqKey="Thiebaut R" first="Rodolphe" last="Thiebaut">Rodolphe Thiebaut</name><affiliation><nlm:aff id="aff7">Université Victor Segalen, Bordeaux, France</nlm:aff></affiliation></author><author><name sortKey="Law, Matthew" sort="Law, Matthew" uniqKey="Law M" first="Matthew" last="Law">Matthew Law</name><affiliation><nlm:aff id="aff8">National Centre in HIV Epidemiology and Clinical Research, Sydney, Australia</nlm:aff></affiliation></author><author><name sortKey="Rickenbach, Martin" sort="Rickenbach, Martin" uniqKey="Rickenbach M" first="Martin" last="Rickenbach">Martin Rickenbach</name><affiliation><nlm:aff id="aff9">University Hospital, Lausanne, Switzerland</nlm:aff></affiliation></author><author><name sortKey="De Wit, Stephane" sort="De Wit, Stephane" uniqKey="De Wit S" first="Stephane" last="De Wit">Stephane De Wit</name><affiliation><nlm:aff id="aff10">University Hospital St. Pierre, Brussels, Belgium</nlm:aff></affiliation></author><author><name sortKey="Lundgren, Jens D" sort="Lundgren, Jens D" uniqKey="Lundgren J" first="Jens D." last="Lundgren">Jens D. Lundgren</name><affiliation><nlm:aff id="aff1">Copenhagen HIV Programme, University of Copenhagen, Copenhagen, Denmark</nlm:aff></affiliation></author><author><name sortKey="Friis M Ller, Nina" sort="Friis M Ller, Nina" uniqKey="Friis M Ller N" first="Nina" last="Friis-M Ller">Nina Friis-M Ller</name><affiliation><nlm:aff id="aff1">Copenhagen HIV Programme, University of Copenhagen, Copenhagen, Denmark</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">19056612</idno><idno type="pmc">2646032</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2646032</idno><idno type="RBID">PMC:2646032</idno><idno type="doi">10.2337/dc08-1394</idno><date when="2009">2009</date><idno type="wicri:Area/Pmc/Corpus">001110</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">001110</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Presence of the Metabolic Syndrome Is Not a Better Predictor of Cardiovascular Disease Than the Sum of Its Components in HIV-Infected Individuals</title><author><name sortKey="Worm, Signe W" sort="Worm, Signe W" uniqKey="Worm S" first="Signe W." last="Worm">Signe W. Worm</name><affiliation><nlm:aff id="aff1">Copenhagen HIV Programme, University of Copenhagen, Copenhagen, Denmark</nlm:aff></affiliation></author><author><name sortKey="Sabin, Caroline A" sort="Sabin, Caroline A" uniqKey="Sabin C" first="Caroline A." last="Sabin">Caroline A. Sabin</name><affiliation><nlm:aff id="aff2">Royal Free and University College, London, U.K.</nlm:aff></affiliation></author><author><name sortKey="Reiss, Peter" sort="Reiss, Peter" uniqKey="Reiss P" first="Peter" last="Reiss">Peter Reiss</name><affiliation><nlm:aff id="aff3">Academic Medical Center, Amsterdam, the Netherlands</nlm:aff></affiliation></author><author><name sortKey="El Sadr, Wafaa" sort="El Sadr, Wafaa" uniqKey="El Sadr W" first="Wafaa" last="El-Sadr">Wafaa El-Sadr</name><affiliation><nlm:aff id="aff4">Harlem Hospital Center, Division of Infectious Diseases, New York, New York</nlm:aff></affiliation></author><author><name sortKey="D Arminio Monforte, Antonella" sort="D Arminio Monforte, Antonella" uniqKey="D Arminio Monforte A" first="Antonella" last="D'Arminio Monforte">Antonella D'Arminio Monforte</name><affiliation><nlm:aff id="aff5">University of Milan, Milan, Italy</nlm:aff></affiliation></author><author><name sortKey="Pradier, Christian" sort="Pradier, Christian" uniqKey="Pradier C" first="Christian" last="Pradier">Christian Pradier</name><affiliation><nlm:aff id="aff6">Hôpital Archet 1, Nice, France</nlm:aff></affiliation></author><author><name sortKey="Thiebaut, Rodolphe" sort="Thiebaut, Rodolphe" uniqKey="Thiebaut R" first="Rodolphe" last="Thiebaut">Rodolphe Thiebaut</name><affiliation><nlm:aff id="aff7">Université Victor Segalen, Bordeaux, France</nlm:aff></affiliation></author><author><name sortKey="Law, Matthew" sort="Law, Matthew" uniqKey="Law M" first="Matthew" last="Law">Matthew Law</name><affiliation><nlm:aff id="aff8">National Centre in HIV Epidemiology and Clinical Research, Sydney, Australia</nlm:aff></affiliation></author><author><name sortKey="Rickenbach, Martin" sort="Rickenbach, Martin" uniqKey="Rickenbach M" first="Martin" last="Rickenbach">Martin Rickenbach</name><affiliation><nlm:aff id="aff9">University Hospital, Lausanne, Switzerland</nlm:aff></affiliation></author><author><name sortKey="De Wit, Stephane" sort="De Wit, Stephane" uniqKey="De Wit S" first="Stephane" last="De Wit">Stephane De Wit</name><affiliation><nlm:aff id="aff10">University Hospital St. Pierre, Brussels, Belgium</nlm:aff></affiliation></author><author><name sortKey="Lundgren, Jens D" sort="Lundgren, Jens D" uniqKey="Lundgren J" first="Jens D." last="Lundgren">Jens D. Lundgren</name><affiliation><nlm:aff id="aff1">Copenhagen HIV Programme, University of Copenhagen, Copenhagen, Denmark</nlm:aff></affiliation></author><author><name sortKey="Friis M Ller, Nina" sort="Friis M Ller, Nina" uniqKey="Friis M Ller N" first="Nina" last="Friis-M Ller">Nina Friis-M Ller</name><affiliation><nlm:aff id="aff1">Copenhagen HIV Programme, University of Copenhagen, Copenhagen, Denmark</nlm:aff></affiliation></author></analytic><series><title level="j">Diabetes Care</title><idno type="ISSN">0149-5992</idno><idno type="eISSN">1935-5548</idno><imprint><date when="2009">2009</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><bold>OBJECTIVE</bold>—It is much debated whether the metabolic syndrome contributes additional information over and above that provided by the individual components of the syndrome alone. Among HIV-infected individuals, we investigated whether any particular combinations of the components included in the definition of the metabolic syndrome are associated with a higher risk of cardiovascular disease (CVD).</p><p><bold>RESEARCH DESIGN AND METHODS</bold>—We followed 33,347 HIV-infected individuals in a prospective observational study. The effect of combinations of components of the metabolic syndrome (low HDL cholesterol, high triglycerides, high BMI, hypertension, and diabetes) on the risk of CVD was assessed by Poisson regression incorporating interactions between each component pair and adjusting for age, sex, family history of CVD, smoking status, calendar year, and exposure to antiretroviral therapy. We reduced the risk of type 1 errors by randomly splitting the data set for training (70% of sample) and validation (remaining 30%).</p><p><bold>RESULTS</bold>—In the training data set, 671 patients experienced a CVD event over 110,652 person-years. Unadjusted, the presence of metabolic syndrome at study enrollment (≥3 of the factors) was associated with a 2.89 higher risk of CVD (95% CI 2.34–3.59; <italic>P</italic> = 0.0001) compared with individuals without the metabolic syndrome. After adjustment for the individual components, the metabolic syndrome as an entity no longer predicted the risk of CVD (adjusted relative risk 0.85; 95% CI 0.61–1.17; <italic>P</italic> = 0.32). No significant positive interactions were found among the components of the metabolic syndrome.</p><p><bold>CONCLUSIONS</bold>—The presence of the metabolic syndrome in HIV-infected individuals did not appear to increase the CVD risk over and above that conferred by the components of the syndrome separately.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Diabetes Care</journal-id><journal-id journal-id-type="publisher-id">diacare</journal-id><journal-title>Diabetes Care</journal-title><issn pub-type="ppub">0149-5992</issn><issn pub-type="epub">1935-5548</issn><publisher><publisher-name>American Diabetes Association</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">19056612</article-id><article-id pub-id-type="pmc">2646032</article-id><article-id pub-id-type="publisher-id">323474</article-id><article-id pub-id-type="doi">10.2337/dc08-1394</article-id><article-categories><subj-group subj-group-type="heading"><subject>Cardiovascular and Metabolic Risk</subject></subj-group></article-categories><title-group><article-title>Presence of the Metabolic Syndrome Is Not a Better Predictor of Cardiovascular Disease Than the Sum of Its Components in HIV-Infected Individuals</article-title><subtitle>Data Collection on Adverse events of Anti-HIV Drugs (D:A:D) study<xref ref-type="fn" rid="fn1">*</xref></subtitle></title-group><contrib-group><contrib contrib-type="author"><name><surname>Worm</surname><given-names>Signe W.</given-names></name><degrees>MD</degrees><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Sabin</surname><given-names>Caroline A.</given-names></name><degrees>PHD</degrees><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author"><name><surname>Reiss</surname><given-names>Peter</given-names></name><degrees>PHD</degrees><xref ref-type="aff" rid="aff3">3</xref></contrib><contrib contrib-type="author"><name><surname>El-Sadr</surname><given-names>Wafaa</given-names></name><degrees>MD, MPH</degrees><xref ref-type="aff" rid="aff4">4</xref></contrib><contrib contrib-type="author"><name><surname>d'Arminio Monforte</surname><given-names>Antonella</given-names></name><degrees>DMSC</degrees><xref ref-type="aff" rid="aff5">5</xref></contrib><contrib contrib-type="author"><name><surname>Pradier</surname><given-names>Christian</given-names></name><degrees>MD</degrees><xref ref-type="aff" rid="aff6">6</xref></contrib><contrib contrib-type="author"><name><surname>Thiebaut</surname><given-names>Rodolphe</given-names></name><degrees>PHD</degrees><xref ref-type="aff" rid="aff7">7</xref></contrib><contrib contrib-type="author"><name><surname>Law</surname><given-names>Matthew</given-names></name><degrees>PHD</degrees><xref ref-type="aff" rid="aff8">8</xref></contrib><contrib contrib-type="author"><name><surname>Rickenbach</surname><given-names>Martin</given-names></name><degrees>MD</degrees><xref ref-type="aff" rid="aff9">9</xref></contrib><contrib contrib-type="author"><name><surname>De Wit</surname><given-names>Stephane</given-names></name><degrees>PHD</degrees><xref ref-type="aff" rid="aff10">10</xref></contrib><contrib contrib-type="author"><name><surname>Lundgren</surname><given-names>Jens D.</given-names></name><degrees>DMSC</degrees><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Friis-Møller</surname><given-names>Nina</given-names></name><degrees>PHD</degrees><xref ref-type="aff" rid="aff1">1</xref></contrib></contrib-group><aff id="aff1"><label>1</label>Copenhagen HIV Programme, University of Copenhagen, Copenhagen, Denmark</aff><aff id="aff2"><label>2</label>Royal Free and University College, London, U.K.</aff><aff id="aff3"><label>3</label>Academic Medical Center, Amsterdam, the Netherlands</aff><aff id="aff4"><label>4</label>Harlem Hospital Center, Division of Infectious Diseases, New York, New York</aff><aff id="aff5"><label>5</label>University of Milan, Milan, Italy</aff><aff id="aff6"><label>6</label>Hôpital Archet 1, Nice, France</aff><aff id="aff7"><label>7</label>Université Victor Segalen, Bordeaux, France</aff><aff id="aff8"><label>8</label>National Centre in HIV Epidemiology and Clinical Research, Sydney, Australia</aff><aff id="aff9"><label>9</label>University Hospital, Lausanne, Switzerland</aff><aff id="aff10"><label>10</label>University Hospital St. Pierre, Brussels, Belgium</aff><author-notes><fn><p>Corresponding author: Signe W. Worm, <email>sww@cphiv.dk</email></p></fn></author-notes><pub-date pub-type="ppub"><month>3</month><year>2009</year></pub-date><volume>32</volume><issue>3</issue><fpage>474</fpage><lpage>480</lpage><history><date date-type="received"><day>28</day><month>7</month><year>2008</year></date><date date-type="accepted"><day>20</day><month>11</month><year>2008</year></date></history><permissions><copyright-statement>Copyright © 2009, American Diabetes Association</copyright-statement><license license-type="open-access"><p>Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by-nc-nd/3.0/">http://creativecommons.org/licenses/by-nc-nd/3.0/</ext-link> for details.</p></license></permissions><self-uri xlink:title="pdf" xlink:href="zdc00309000474.pdf"></self-uri><abstract><p><bold>OBJECTIVE</bold>—It is much debated whether the metabolic syndrome contributes additional information over and above that provided by the individual components of the syndrome alone. Among HIV-infected individuals, we investigated whether any particular combinations of the components included in the definition of the metabolic syndrome are associated with a higher risk of cardiovascular disease (CVD).</p><p><bold>RESEARCH DESIGN AND METHODS</bold>—We followed 33,347 HIV-infected individuals in a prospective observational study. The effect of combinations of components of the metabolic syndrome (low HDL cholesterol, high triglycerides, high BMI, hypertension, and diabetes) on the risk of CVD was assessed by Poisson regression incorporating interactions between each component pair and adjusting for age, sex, family history of CVD, smoking status, calendar year, and exposure to antiretroviral therapy. We reduced the risk of type 1 errors by randomly splitting the data set for training (70% of sample) and validation (remaining 30%).</p><p><bold>RESULTS</bold>—In the training data set, 671 patients experienced a CVD event over 110,652 person-years. Unadjusted, the presence of metabolic syndrome at study enrollment (≥3 of the factors) was associated with a 2.89 higher risk of CVD (95% CI 2.34–3.59; <italic>P</italic> = 0.0001) compared with individuals without the metabolic syndrome. After adjustment for the individual components, the metabolic syndrome as an entity no longer predicted the risk of CVD (adjusted relative risk 0.85; 95% CI 0.61–1.17; <italic>P</italic> = 0.32). No significant positive interactions were found among the components of the metabolic syndrome.</p><p><bold>CONCLUSIONS</bold>—The presence of the metabolic syndrome in HIV-infected individuals did not appear to increase the CVD risk over and above that conferred by the components of the syndrome separately.</p></abstract></article-meta><notes><fn-group><fn><p>Published ahead of print at <ext-link ext-link-type="uri" xlink:href="http://care.diabetesjournals.org">http://care.diabetesjournals.org</ext-link> on 3 December 2008.</p></fn><fn><p>The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C Section 1734 solely to indicate this fact.</p></fn></fn-group></notes></front><body><p>HIV-1 infection is treated with combination antiretroviral therapy (cART). Although treatment is usually highly effective, the success of treatment is frequently complicated by lipodystrophy (peripheral fat loss and accumulation of central adiposity), dyslipidemia, insulin resistance, and overt diabetes (<xref ref-type="bibr" rid="r1">1</xref>,<xref ref-type="bibr" rid="r2">2</xref>). The clustering of these abnormalities has striking similarities to the metabolic syndrome, a term used to describe a clustering of risk factors for cardiovascular disease (CVD), including high triglycerides, low HDL cholesterol, hypertension, hyperglycemia/insulin resistance, and abdominal obesity. Prior studies have reported that the relative frequency of the components of the metabolic syndrome differ between HIV-infected individuals and the general population, with hypertriglyceridemia and low HDL cholesterol being predominant features in “HIV metabolic syndrome” (<xref ref-type="bibr" rid="r3">3</xref>,<xref ref-type="bibr" rid="r4">4</xref>). However, most of the studies that have explored the metabolic syndrome in HIV-infected individuals have been cross-sectional and have not considered its relationship with clinical end points as such as CVD (<xref ref-type="bibr" rid="r3">3</xref>,<xref ref-type="bibr" rid="r5">5</xref>,<xref ref-type="bibr" rid="r6">6</xref>). Several reports from HIV-infected patients receiving cART suggested increased incidence of CVD and related mortality (<xref ref-type="bibr" rid="r7">7</xref>). Because many components of the metabolic syndrome may be induced by cART, it is important to investigate the predictive ability of the metabolic syndrome for CVD in this population.</p><p>The metabolic syndrome is recognized as a “CVD risk enhancer” by the U.S. National Cholesterol Educational Program (NCEP) (<xref ref-type="bibr" rid="r8">8</xref>), and the presence of metabolic syndrome is associated with an increased risk of CVD (<xref ref-type="bibr" rid="r9">9</xref>,<xref ref-type="bibr" rid="r10">10</xref>). However, whether the syndrome has any independent prognostic value over and above its components is controversial (<xref ref-type="bibr" rid="r11">11</xref>). The aim of this study was to investigate whether the presence of the metabolic syndrome in an HIV-infected individual constitutes an additional risk for CVD over and above that which would be expected for the individual given his or her known risk factors for CVD. In particular, we wished to investigate whether any particular combinations of the components included in the definition of metabolic syndrome are associated with a higher risk of CVD than would be expected from combining the risk attributable to each component separately.</p><sec><title>RESEARCH DESIGN AND METHODS</title><p>The Data Collection on Adverse events of Anti-HIV Drugs (D:A:D) study is a prospective, observational study formed by the collaboration of 11 cohorts following 33,347 HIV-infected subjects at 212 clinics in Europe, Australia, and the U.S. The primary objective of the study is to investigate the possible association between cART and the onset of myocardial infarction. The D:A:D study methodology has been described in detail elsewhere (<xref ref-type="bibr" rid="r12">12</xref>).</p><sec><title>Data collection</title><p>Patients are followed prospectively during visits to outpatient clinics as a part of regular medical care. At enrollment and at least every 8 months thereafter, standardized data collection forms are completed at the sites, providing information from physical examination, patient interview concerning family history of coronary heart disease, prior history of CVD and diabetes, cigarette smoking, blood pressure, lipid-lowering and antihypertensive therapy, and the presence of physician-defined lipodystrophy and serum lipid levels (total cholesterol, HDL cholesterol, and triglycerides and information on fasting conditions), as well as HIV-related information (antiviral therapy, CD4 cell counts, HIV viral loads, and dates of diagnoses of all AIDS-defining diseases).</p><p>We considered a modified NCEP definition of the metabolic syndrome (<xref ref-type="bibr" rid="r13">13</xref>), which incorporated five criteria: triglycerides ≥1.7mmol/l; HDL cholesterol ≤1.0 mmol/l in men or ≤1.3 mmol/l in women; high blood pressure indicated by systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg; BMI >30 kg/m<sup>2</sup> as a surrogate of waist circumference; and a diagnosis of diabetes as a surrogate of fasting glucose. A patient was defined as having the metabolic syndrome on the first date that at least three of the five components were present. When information was missing for an individual for any component of the definition, that component was assumed to be absent. Furthermore, for our main analyses, the various components of the metabolic syndrome were assumed to be irreversible; thus, once an individual had met one of the criteria, it was assumed that he or she would always meet that criterion.</p></sec><sec><title>Ascertainment of outcomes</title><p>All incident cases of myocardial infarction, all invasive procedures involving the coronary arteries (angioplasty or bypass), and all deaths (irrespective of cause) are reported to the coordinating office for validation and coding as described in earlier reports from the study (<xref ref-type="bibr" rid="r14">14</xref>).</p><p>The incidence of a composite CVD end point of myocardial infarction, stroke, invasive coronary procedure (ICP), or death from other cardiovascular cause was calculated by dividing the number of such events by the total person-years of follow-up in the cohort. Patient follow-up was counted from the time of enrollment in D:A:D until the date of the first CVD event, 1 February 2007, or 6 months after the patient's last clinic visit. Only the first new CVD event during prospective follow-up was considered in the analyses.</p><p>Diabetes has been collected as a secondary D:A:D end point since the start of the study. New-onset diabetes was considered as a definite diagnosis if fasting plasma glucose ≥7.0 mmol/l (126 mg/dl) was measured on two consecutive occasions or as a possible diagnosis if the patient had a physician-reported date of diabetes onset and was known to have initiated antidiabetes therapy.</p></sec><sec><title>Statistical analysis</title><p>Because of the potential for a high type 1 error rate due to multiple testing, we investigated the possible presence of interactions between the various components of the metabolic syndrome in a random sample of 70% of the cohort (training sample: <italic>n</italic> = 23,202). Initially, for exploratory purposes, patients were grouped on the basis of their status at entry in D:A:D into the four strata that resulted from the combination of each component pair, and the incidence of the CVD end point was calculated for each strata. We then explored whether the components of the definition acted synergistically on the end point by the incorporation of each component into a multivariable Poisson regression analysis along with each pairwise interaction term. Any statistically significant interaction (<italic>P</italic> < 0.05) with a rate ratio (RR) >1 would suggest a positive synergistic effect between the metabolic syndrome components. These analyses were adjusted for other potential confounders for CVD (sex, age, family history of CVD, smoking status, calendar year, cohort, HIV risk group, ethnic group, and exposure to the protease inhibitor, nucleoside reverse transcriptase inhibitor [NRTI], and non-nucleoside reverse transcriptase inhibitor [NNRTI] classes of drugs). Finally, we examined whether the presence of the metabolic syndrome as an entity was associated with the risk of CVD, both before and after controlling for each of the five individual components of the definition and other possible confounders as listed above. These analyses were then repeated using information on changes over follow-up (a time-updated analysis) to assess whether the results were robust to any such changes. To rule out the possibility that any significant interactions may have reflected chance findings, the analysis was then repeated using the remaining 30% of the study cohort (validation sample: <italic>n</italic> = 10,145).</p><p>A series of sensitivity analyses were performed for the time-updated analyses on the training set. First, we allowed the lipid and hypertension components of the metabolic syndrome to be reversible. Thus, if a patient experienced a drop in triglycerides or blood pressure below the threshold or an increase in HDL cholesterol above the threshold, irrespective of the cause (including the use of lipid-lowering or antihypertensive drugs), he or she no longer met that criterion. Secondly, we reran the analyses after excluding follow-up (and events) that occurred while a patient had incomplete information for any metabolic syndrome component. Finally, the metabolic syndrome definition was further adapted to ensure that measurements (triglycerides, HDL cholesterol, or blood pressure) had been obtained in the previous year; if a patient did not have a measurement within any 1-year period, he or she was temporarily excluded from the risk set until a new measurement became available.</p><p>To ensure that our results were not overly influenced by patients having diabetes and CVD at baseline, the analyses were repeated after <italic>1</italic>) adjustment for baseline myocardial infarction status (fixed analyses) and <italic>2</italic>) excluding those with a myocardial infarction and/or diabetes at entry in the D:A:D study (time-updated analyses). The results from these analyses showed conclusions similar to those of the primary analyses (data not shown).</p><p>Analyses were performed using the GENMOD procedure in SAS version 9.1. <italic>P</italic> < 0.05 was considered to be statistically significant.</p></sec></sec><sec><title>RESULTS</title><p>Of the 23,202 patients in the training set, 1,025 (4.4%) had the metabolic syndrome at enrollment (<xref ref-type="table" rid="t1">Table 1</xref>). The most common components of the metabolic syndrome at study entry were elevated triglycerides (95.5% of those with the metabolic syndrome), low HDL cholesterol (85.1%), and high blood pressure (81.8%). As expected, compared with those without the metabolic syndrome at study enrollment, those with the metabolic syndrome at enrollment were significantly more likely to be male, to be older, to be current smokers, to have lipodystrophy, and to have previously experienced a myocardial infarction (all <italic>P</italic> < 0.001). Furthermore, those with the metabolic syndrome at enrollment were more likely to have received the NRTI and protease inhibitor classes of drugs and had higher CD4 counts and lower HIV RNA levels at enrollment than those without the metabolic syndrome (all <italic>P</italic> < 0.001).</p><p>Individuals included in the training set were followed for a median (range) of 5.1 (3.2–6.5) person-years (total follow-up 110,652 person-years), with no significant difference in follow-up time between those with and without the metabolic syndrome at enrollment (<italic>P</italic> = 0.93, Mann-Whitney <italic>U</italic> test). Over this time, 671 (2.0%) patients experienced a CVD event, with the first event being a myocardial infarction in 51.9%, a stroke in 27.9%, an ICP in 18.0% (angioplasty 12.8%, coronary bypass 4.3%, and endarterectomy 0.9%), and cardiovascular death in 2.2%. There were no major differences in the distribution of first events among those with and without the metabolic syndrome at study enrollment (data not shown).</p><sec><title>Incidence of CVD according to components of the metabolic syndrome at study enrollment</title><p>When patients were categorized according to the presence of the metabolic syndrome components at enrollment in the D:A:D study, event rates ranged from 3.7 (95% CI 3.2–4.2) per 1,000 person-years among patients with a normal triglyceride level and no hypertension to 43.3 (25.2–69.3) per 1,000 person-years among patients with diabetes and a BMI >30 kg/m<sup>2</sup> (<xref ref-type="table" rid="t2">Table 2</xref>). In multivariable analysis adjusting for other potential confounders, there was no evidence of any synergistic associations between the metabolic syndrome component pairs. Whereas weak negative interactions were noted between high triglycerides and hypertension and between low HDL cholesterol and hypertension, these were of borderline significance. For example, individuals with low HDL cholesterol and high blood pressure appeared to have a lower risk of CVD than would be expected based on the effects of these factors alone.</p><p>The CVD event rate increased as the number of metabolic syndrome components present at study enrollment increased, from 3.2 (95% CI 2.7–3.8) per 1,000 person-years in those with no components present to 33.9 (41.0–122.5) in those with five components present. In unadjusted analyses, the rate of CVD increased by 65% (RR 1.65, 95% CI 1.54–1.77; <italic>P</italic> = 0.0001) for each additional component that was present at study enrollment; after adjusting for potential confounders, the effect of an increasing number of metabolic syndrome components remained significant (adjusted RR [ARR] 1.33, 95% CI 1.23–1.44; <italic>P</italic> = 0.0001). Individuals with the metabolic syndrome at study enrollment (≥3 of the factors) were almost three times as likely (RR 2.89, 95% CI 2.34–3.59; <italic>P</italic> = 0.0001) to develop CVD as those without the metabolic syndrome at study enrollment. However, after adjustment for the components of the metabolic syndrome themselves and for other potential confounders, the metabolic syndrome as an entity no longer predicted the risk of CVD (ARR 0.85, 95% CI 0.61–1.17; <italic>P</italic> = 0.32).</p></sec><sec><title>Incidence of CVD according to components of the metabolic syndrome over follow-up</title><p>When patients were categorized according to the presence of the metabolic syndrome components over prospective follow-up, event rates were lowest in those with a normal triglyceride level and normal HDL cholesterol (ARR 1.2, 95% CI 0.8–1.6 per 1,000 person-years) and highest in those with diabetes and a BMI >30 kg/m<sup>2</sup> (28.7, 17.7–39.8 per 1,000 person-years) (<xref ref-type="table" rid="t2">Table 2</xref>).</p><p>The CVD event rate again increased as the number of metabolic syndrome components present over prospective follow-up increased with rates of 2.3 (95% CI 1.6–3.0), 3.5 (2.8–4.1), 6.4 (5.6–7.3), 9.6 (8.3–10.8), 14.4 (10.6–18.2), and 39.8 (23.6–62.8) per 1,000 person-years in those with zero, one, two, three, four, and five components present, respectively. In unadjusted analyses, the rate of CVD increased by 64% (RR 1.64, 95% CI 1.53–1.76; <italic>P</italic> = 0.0001) for each additional component present; after adjustment for potential confounders, the rate of CVD increased by 46% (ARR 1.46, 95% CI 1.34–1.58; <italic>P</italic> = 0.0001) for each additional component. Before adjustment, individuals with the metabolic syndrome over follow-up were 2.4 times as likely (RR 2.40, 95% CI 2.06–2.79; <italic>P</italic> = 0.0001) to develop CVD than those without the metabolic syndrome (<xref ref-type="table" rid="t3">Table 3</xref>). However, as before, after adjustment for the components of the metabolic syndrome themselves and for other potential confounders, the metabolic syndrome as an entity no longer predicted the risk of CVD (ARR 0.94, 95% CI 0.69–1.27; <italic>P</italic> = 0.67). The results were confirmed in the validation data set (303 events over 48,741 person-years), and all sensitivity analyses reached similar conclusions (<xref ref-type="table" rid="t3">Table 3</xref>).</p><p>In the main analyses, of the metabolic syndrome components diabetes was the strongest independent predictor of CVD with an ARR of 2.31 (95% CI 1.83–2.92; <italic>P</italic> = 0.0001) followed by high triglycerides (1.50, 1.18–1.91; <italic>P</italic> = 0.001) and low HDL cholesterol (1.41, 1.12–1.76; <italic>P</italic> = 0.003). A high BMI was more weakly associated with CVD (1.33, 1.01–1.74; <italic>P</italic> = 0.04), whereas high blood pressure was not independently associated with the risk of CVD (1.26, 0.98–1.62; <italic>P</italic> = 0.07). Similar results were obtained in the validation data set (<xref ref-type="table" rid="t3">Table 3</xref>).</p></sec></sec><sec><title>CONCLUSIONS</title><p>There is a strong association between the presence of an increasing number of the components of the metabolic syndrome in HIV-infected patients and an increased CVD risk in the D:A:D study. In particular, the CVD rate was 2.4–2.8 times higher in those with the metabolic syndrome than in those without the metabolic syndrome. However, there was no evidence from our study that the metabolic syndrome as a specific entity was associated with a higher CVD risk than would be anticipated based on the presence of the individual components alone. In particular, there was no evidence that any of the components of the metabolic syndrome acted synergistically on an individual's risk of CVD, and the presence of the metabolic syndrome did not increase CVD risk over and above that conferred by the components of the syndrome. The results from our sensitivity analyses, which explored the robustness of the findings to missing data and to changes in lipid and blood pressure measurements, were all consistent with our main analyses.</p><p>The components included in the definition of the metabolic syndrome are all established independent risk factors for CVD in populations not infected with HIV. If the metabolic syndrome provides additional information on the CVD risk over and above that provided by these components separately, we would expect to see some synergism between the components. So far, only a few studies exploring the predictive ability of metabolic syndrome on a CVD outcome have specifically addressed this question by adjusting for the components of the syndrome. These studies either showed lower hazard ratios for the metabolic syndrome compared with the individual risk factors or showed that metabolic syndrome by itself does not contribute any additional information (<xref ref-type="bibr" rid="r15">15</xref>–<xref ref-type="bibr" rid="r17">17</xref>).</p><p>To date, although several studies of HIV-infected individuals have assessed the impact of the various components of the metabolic syndrome on the risk of CVD, no study has been able to consider the impact of the metabolic syndrome itself on clinical end points. However, data from a post hoc analysis of the naive substudy of the INITIO trial (based on 21 CVD events) suggested that incident metabolic syndrome was associated with CVD with a hazard ratio of 2.56 (95% CI 0.86–7.60) (<xref ref-type="bibr" rid="r18">18</xref>). This result did not reach statistical significance and, as noted by the authors, should be interpreted with caution. With the aging of the HIV-infected population, brought about by an increased life expectancy after the widespread use of cART, it is likely that the long-term metabolic complications among HIV-infected individuals will place this group at risk of CVD in the future. An increasing number of HIV-infected patients are starting to develop diabetes (<xref ref-type="bibr" rid="r19">19</xref>). The results from the present analysis confirm our previous finding that diabetes is an important risk factor for myocardial infarction and CVD among HIV-infected individuals (<xref ref-type="bibr" rid="r12">12</xref>). Although dyslipidemia remains an important predictor of CVD, this condition appears to be decreasing in frequency, largely due to increased use of lipid-lowering drugs (<xref ref-type="bibr" rid="r19">19</xref>).</p><p>We have recently reported an increased risk of myocardial infarction associated with the use of the protease inhibitor drug class (<xref ref-type="bibr" rid="r12">12</xref>), which was partly explained by dyslipidemia. From the NRTI drug class, abacavir was recently reported to be associated with myocardial infarction and CVD (<xref ref-type="bibr" rid="r20">20</xref>,<xref ref-type="bibr" rid="r21">21</xref>), which might be due to changes in inflammation, i.e., interleukin-6 and high-sensitivity C-reactive protein (<xref ref-type="bibr" rid="r21">21</xref>). Both biomarkers are independently associated with CVD (<xref ref-type="bibr" rid="r15">15</xref>,<xref ref-type="bibr" rid="r22">22</xref>). Increased inflammation is reported to be associated with the metabolic syndrome among HIV-infected (<xref ref-type="bibr" rid="r6">6</xref>) and uninfected (<xref ref-type="bibr" rid="r15">15</xref>) individuals. However, neither C-reactive protein nor other biomarkers are included in the definition of the metabolic syndrome, although the inclusion of such biomarkers may provide useful information. Unfortunately, the D:A:D study does not collect information on these biomarkers, so it is unclear whether their inclusion would have changed our conclusion. Future research will provide further insight into HIV-induced as well as antiretroviral therapy–induced inflammation.</p><p>The debate about the existence of the metabolic syndrome as an entity and its prognostic value is ongoing (<xref ref-type="bibr" rid="r11">11</xref>,<xref ref-type="bibr" rid="r23">23</xref>,<xref ref-type="bibr" rid="r24">24</xref>). Some of the critique has focused on the independent predictive ability of the metabolic syndrome for CVD. We aimed in this study to investigate whether the presence of the metabolic syndrome in an HIV-infected individual constitutes an additional risk for CVD, over and above that which would be expected in the individual given his or her known risk factors for CVD. A priori, we believed that certain combinations of risk factors would be more frequent than others. If these combinations were of any independent prognostic information, we would then expect to find positive interactions between these risk factor combinations (i.e., the presence of both factors would be associated with a greater than expected increase in the risk of CVD). However, this was not the case. Even by including “overt diabetes” in the syndrome definition instead of fasting glucose, we still did not find the metabolic syndrome as an independent predictor of CVD. We do not believe that the inclusion of fasting glucose would have resulted in major differences.</p><sec><title>Limitations</title><p>Our study population is largely male (70%), and so our results should be extrapolated to women with some caution. As the D:A:D study does not collect waist circumference, we used increased BMI to reflect this component of the metabolic syndrome, as in other studies (<xref ref-type="bibr" rid="r17">17</xref>). The use of BMI may have resulted in lower estimated effects compared with waist circumference, because BMI includes total fat mass. However, it has been suggested that waist circumference more closely reflects visceral fat mass that is directly related to insulin resistance (<xref ref-type="bibr" rid="r6">6</xref>). Furthermore, the lipodystrophic changes with central fat accumulation and loss of peripheral subcutaneous fat may underestimate the prevalence of the metabolic syndrome, as these patients may have a normal BMI and might not have been sufficiently captured by our modified NCEP definition. Furthermore, many of the metabolic changes in HIV are induced by antiretroviral therapy, and their impact on CVD risk may differ from that in the general population. Of note, measurements of hypertension and lipids were generally obtained through routine clinical care and, as such, are not always based on the standardized protocols that may be used in a trial setting. As a result, we may have overestimated the frequency of these conditions in this study.</p><p>In summary, we did not find that the metabolic syndrome was an independent predictor of CVD in HIV-infected individuals once we had considered the risk conferred by the components of the syndrome. However, we found a strong association between an increasing number of the components of the metabolic syndrome and CVD risk, emphasizing the importance of the identification and management of all CVD factors in this population, including those not included in the metabolic syndrome definition (e.g., smoking); the identification of one CVD risk factor should immediately lead the physician to search for other CVD risk factors. Patients should also be evaluated for CVD risk at least annually (<xref ref-type="bibr" rid="r25">25</xref>).</p></sec></sec><sec sec-type="supplementary-material"><title>Supplementary Material</title><supplementary-material id="PMC_1" content-type="local-data"><caption><title>Online-Only Appendix</title></caption><media mimetype="text" mime-subtype="html" xlink:href="dc08-1394_index.html"></media><media xlink:role="associated-file" mimetype="application" mime-subtype="msword" xlink:href="dc08-1394_dc08-1394_APPENDIX.doc"></media></supplementary-material></sec></body><back><ack><p>No potential conflicts of interest relevant to this article were reported.</p></ack><ref-list><title>References</title><ref id="r1"><label>1</label><citation citation-type="journal">Carr A, Samaras K, Burton S, Law M, Freund J, Chisholm DJ, Cooper DA: A syndrome of peripheral lipodystrophy, hyperlipidaemia and insulin resistance in patients receiving HIV protease inhibitors. <source>AIDS</source> <volume>12</volume>:<fpage>F51</fpage>–F58, <year>1998</year><pub-id pub-id-type="pmid">9619798</pub-id></citation></ref><ref id="r2"><label>2</label><citation citation-type="journal">De Wit S, Sabin CA, Weber R, Worm SW, Reiss P, Cazanave C, El-Sadr W, Monforte A, Fontas E, Law MG, Friis-Moller N, Phillips A: Incidence and risk factors for new-onset diabetes in HIV-infected patients: the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study. <source>Diabetes Care</source> <volume>31</volume>:<fpage>1224</fpage>–1229, <year>2008</year><pub-id pub-id-type="pmid">18268071</pub-id></citation></ref><ref id="r3"><label>3</label><citation citation-type="journal">Jerico C, Knobel H, Montero M, Ordonez-Llanos J, Guelar A, Gimeno JL, Saballs P, Lopez-Colomes JL, Pedro-Botet J: Metabolic syndrome among HIV-infected patients: prevalence, characteristics, and related factors. <source>Diabetes Care</source> <volume>28</volume>:<fpage>132</fpage>–137, <year>2005</year><pub-id pub-id-type="pmid">15616246</pub-id></citation></ref><ref id="r4"><label>4</label><citation citation-type="journal">Jacobson DL, Tang AM, Spiegelman D, Thomas AM, Skinner S, Gorbach SL, Wanke C: Incidence of metabolic syndrome in a cohort of HIV-infected adults and prevalence relative to the US population (National Health and Nutrition Examination Survey). <source>J Acquir Immune Defic Syndr</source> <volume>43</volume>:<fpage>458</fpage>–466, <year>2006</year><pub-id pub-id-type="pmid">16980905</pub-id></citation></ref><ref id="r5"><label>5</label><citation citation-type="journal">Mondy K, Overton ET, Grubb J, Tong S, Seyfried W, Powderly W, Yarasheski K: Metabolic syndrome in HIV-infected patients from an urban, midwestern US outpatient population. <source>Clin Infect Dis</source> <volume>44</volume>:<fpage>726</fpage>–734, <year>2007</year><pub-id pub-id-type="pmid">17278068</pub-id></citation></ref><ref id="r6"><label>6</label><citation citation-type="journal">Samaras K, Wand H, Law M, Emery S, Cooper D, Carr A: Prevalence of metabolic syndrome in HIV-infected patients receiving highly active antiretroviral therapy using International Diabetes Foundation and Adult Treatment Panel III criteria: associations with insulin resistance, disturbed body fat compartmentalization, elevated C-reactive protein, and [corrected] hypoadiponectinemia. <source>Diabetes Care</source> <volume>30</volume>:<fpage>113</fpage>–119, <year>2007</year><pub-id pub-id-type="pmid">17192343</pub-id></citation></ref><ref id="r7"><label>7</label><citation citation-type="other">Lewden D, Tay M, Rosenthal E, Burty E, Bonnet F, Burty C, Costagliola D: Causes of death among HIV-infected adults in France in 2005 and evolution since <year>2000</year>. 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No. <source>BMJ</source> <volume>336</volume>:<fpage>641</fpage>, <year>2008</year><pub-id pub-id-type="pmid">18356232</pub-id></citation></ref><ref id="r25"><label>25</label><citation citation-type="journal">Lundgren JD, Battegay M, Behrens G, De WS, Guaraldi G, Katlama C, Martinez E, Nair D, Powderly WG, Reiss P, Sutinen J, Vigano A: European AIDS Clinical Society (EACS) guidelines on the prevention and management of metabolic diseases in HIV. <source>HIV Med</source> <volume>9</volume>:<fpage>72</fpage>–81, <year>2008</year><pub-id pub-id-type="pmid">18257770</pub-id></citation></ref></ref-list><fn-group><fn id="fn1"><label>*</label><p>A full list of members of the Data Collection on Adverse events of Anti-HIV Drugs (D:A:D) study is available in an online appendix.</p></fn></fn-group></back><floats-wrap><table-wrap position="float" id="t1"><label>Table 1</label><caption><p>Characteristics at enrollment in D:A:D of the 23,202 patients included in the training sample</p></caption><table frame="hsides" rules="groups"><thead><tr><th colspan="1" rowspan="2" align="center" valign="bottom"></th><th colspan="1" rowspan="2" align="center" valign="bottom">All patients in training sample</th><th colspan="2" rowspan="1" align="center" valign="bottom">Metabolic syndrome at enrollment
<hr></hr></th></tr><tr><th colspan="1" rowspan="1" align="center" valign="bottom">Yes</th><th colspan="1" rowspan="1" align="center" valign="bottom">No</th></tr></thead><tbody><tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>n</italic></td><td colspan="1" rowspan="1" align="center" valign="top">23,202</td><td colspan="1" rowspan="1" align="center" valign="top">1,025</td><td colspan="1" rowspan="1" align="center" valign="top">22,177</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Male sex</td><td colspan="1" rowspan="1" align="center" valign="top">17,168 (74.0)</td><td colspan="1" rowspan="1" align="center" valign="top">853 (83.2)</td><td colspan="1" rowspan="1" align="center" valign="top">16,315 (73.6)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Age (years)</td><td colspan="1" rowspan="1" align="center" valign="top">38 (33–45)</td><td colspan="1" rowspan="1" align="center" valign="top">43 (37–52)</td><td colspan="1" rowspan="1" align="center" valign="top">38 (33–44)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">CD4 count (cells/mm<sup>3</sup>)</td><td colspan="1" rowspan="1" align="center" valign="top">410 (249–600)</td><td colspan="1" rowspan="1" align="center" valign="top">449 (274–660)</td><td colspan="1" rowspan="1" align="center" valign="top">408 (248–598)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">HIV RNA (log<sub>10</sub> cp/ml)</td><td colspan="1" rowspan="1" align="center" valign="top">2.7 (1.7–4.2)</td><td colspan="1" rowspan="1" align="center" valign="top">1.9 (1.7–3.5)</td><td colspan="1" rowspan="1" align="center" valign="top">2.7 (1.7–4.3)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Current smoker</td><td colspan="1" rowspan="1" align="center" valign="top">7,823 (33.7)</td><td colspan="1" rowspan="1" align="center" valign="top">410 (40.0)</td><td colspan="1" rowspan="1" align="center" valign="top">7,413 (33.4)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Lipodystrophy</td><td colspan="1" rowspan="1" align="center" valign="top">4,309 (18.6)</td><td colspan="1" rowspan="1" align="center" valign="top">401 (39.1)</td><td colspan="1" rowspan="1" align="center" valign="top">3,908 (17.6)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Prior myocardial infarction</td><td colspan="1" rowspan="1" align="center" valign="top">172 (0.7)</td><td colspan="1" rowspan="1" align="center" valign="top">18 (1.8)</td><td colspan="1" rowspan="1" align="center" valign="top">154 (0.7)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Exposure to antiretroviral therapy</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> Any NRTI</td><td colspan="1" rowspan="1" align="center" valign="top">16,928 (73.0)</td><td colspan="1" rowspan="1" align="center" valign="top">884 (86.2)</td><td colspan="1" rowspan="1" align="center" valign="top">16,044 (72.4)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> Total exposure (years)</td><td colspan="1" rowspan="1" align="center" valign="top">3.1 (1.6–4.8)</td><td colspan="1" rowspan="1" align="center" valign="top">3.6 (2.2–5.3)</td><td colspan="1" rowspan="1" align="center" valign="top">3.0 (1.5–4.7)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> Any protease inhibitor</td><td colspan="1" rowspan="1" align="center" valign="top">13,505 (58.2)</td><td colspan="1" rowspan="1" align="center" valign="top">794 (77.5)</td><td colspan="1" rowspan="1" align="center" valign="top">12,711 (57.3)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> Total exposure (years)</td><td colspan="1" rowspan="1" align="center" valign="top">2.3 (1.2–3.2)</td><td colspan="1" rowspan="1" align="center" valign="top">2.7 (1.7–3.6)</td><td colspan="1" rowspan="1" align="center" valign="top">2.3 (1.2–3.2)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> Any NNRTI</td><td colspan="1" rowspan="1" align="center" valign="top">7,652 (33.0)</td><td colspan="1" rowspan="1" align="center" valign="top">366 (35.7)</td><td colspan="1" rowspan="1" align="center" valign="top">7,286 (32.9)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> Total exposure (years)</td><td colspan="1" rowspan="1" align="center" valign="top">0.9 (0.4–1.6)</td><td colspan="1" rowspan="1" align="center" valign="top">1.0 (0.5–1.7)</td><td colspan="1" rowspan="1" align="center" valign="top">0.9 (0.4–1.6)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">MS components present at enrollment in D:A:D<xref ref-type="table-fn" rid="t1fn1">*</xref></td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> High TRIG</td><td colspan="1" rowspan="1" align="center" valign="top">8,923 (38.5)</td><td colspan="1" rowspan="1" align="center" valign="top">979 (95.5)</td><td colspan="1" rowspan="1" align="center" valign="top">7,944 (35.8)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> Low HDL</td><td colspan="1" rowspan="1" align="center" valign="top">4,934 (21.3)</td><td colspan="1" rowspan="1" align="center" valign="top">872 (85.1)</td><td colspan="1" rowspan="1" align="center" valign="top">4,062 (18.3)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> High BP</td><td colspan="1" rowspan="1" align="center" valign="top">3,278 (14.1)</td><td colspan="1" rowspan="1" align="center" valign="top">838 (81.8)</td><td colspan="1" rowspan="1" align="center" valign="top">2,440 (11.0)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> High BMI</td><td colspan="1" rowspan="1" align="center" valign="top">1,019 (4.4)</td><td colspan="1" rowspan="1" align="center" valign="top">301 (29.4)</td><td colspan="1" rowspan="1" align="center" valign="top">718 (3.2)</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> Diabetes</td><td colspan="1" rowspan="1" align="center" valign="top">651 (2.8)</td><td colspan="1" rowspan="1" align="center" valign="top">238 (23.2)</td><td colspan="1" rowspan="1" align="center" valign="top">413 (1.9)</td></tr></tbody></table><table-wrap-foot><fn><p>Data are <italic>n</italic> (%) or median (interquartile range).</p></fn><fn id="t1fn1"><label>*</label><p>High triglycerides (TRIG): ≥1.7 mmol/l; low HDL cholesterol: ≤1.0 mmol/l (men) or ≤1.3 mmol/l (women); high blood pressure (BP): systolic BP >130 mmHg or diastolic BP >85 mmHg; high BMI: >30 kg/m<sup>2</sup>; diabetes: an established diagnosis of diabetes.</p></fn></table-wrap-foot></table-wrap><table-wrap position="float" id="t2"><label>Table 2</label><caption><p>CVD incidence rates stratified by each metabolic syndrome component “pair”</p></caption><table frame="hsides" rules="groups"><thead><tr><th colspan="1" rowspan="2" align="center" valign="bottom">Criterion 1<xref ref-type="table-fn" rid="t2fn1">*</xref></th><th colspan="1" rowspan="2" align="center" valign="bottom">Criterion 2<xref ref-type="table-fn" rid="t2fn1">*</xref></th><th colspan="2" rowspan="1" align="center" valign="bottom">At baseline (fixed)
<hr></hr></th><th colspan="2" rowspan="1" align="center" valign="bottom">Over follow-up (time-updated)
<hr></hr></th></tr><tr><th colspan="1" rowspan="1" align="center" valign="bottom">Rate/1,000 person-years (95% CI)</th><th colspan="1" rowspan="1" align="center" valign="bottom">Interaction <italic>P</italic> value<xref ref-type="table-fn" rid="t2fn2">†</xref></th><th colspan="1" rowspan="1" align="center" valign="bottom">Rate/1,000 person-years (95% CI)</th><th colspan="1" rowspan="1" align="center" valign="bottom">Interaction <italic>P</italic> value<xref ref-type="table-fn" rid="t2fn2">†</xref></th></tr></thead><tbody><tr><td colspan="1" rowspan="1" align="left" valign="top">Low TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">High HDL</td><td colspan="1" rowspan="1" align="char" char="." valign="top">4.0 (3.4–4.5)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">2.8 (2.2–3.5)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Low TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">Low HDL</td><td colspan="1" rowspan="1" align="char" char="." valign="top">5.9 (4.5–7.2)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.2 (0.8–1.6)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">High HDL</td><td colspan="1" rowspan="1" align="char" char="." valign="top">7.5 (6.5–8.6)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">5.1 (4.3–6.0)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">Low HDL</td><td colspan="1" rowspan="1" align="char" char="." valign="top">10.1 (8.7–11.6)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.78</td><td colspan="1" rowspan="1" align="char" char="." valign="top">8.6 (7.8–9.4)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.30</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Low TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">No high BP</td><td colspan="1" rowspan="1" align="char" char="." valign="top">3.7 (3.2–4.2)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">2.4 (1.8–2.9)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Low TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">High BP</td><td colspan="1" rowspan="1" align="char" char="." valign="top">9.1 (6.9–11.3)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">5.5 (3.8–7.1)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">No high BP</td><td colspan="1" rowspan="1" align="char" char="." valign="top">8.1 (7.2–9.0)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">5.9 (5.2–6.6)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">High BP</td><td colspan="1" rowspan="1" align="char" char="." valign="top">11.1 (8.8–13.4)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.06<xref ref-type="table-fn" rid="t2fn3">‡</xref></td><td colspan="1" rowspan="1" align="char" char="." valign="top">9.3 (8.3–10.4)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.07</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Low TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">No diabetes</td><td colspan="1" rowspan="1" align="char" char="." valign="top">4.0 (3.5–4.5)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">2.9 (2.3–3.4)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Low TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">Diabetes</td><td colspan="1" rowspan="1" align="char" char="." valign="top">19.2 (11.7–2.7)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">11.0 (4.8–2.2)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">No diabetes</td><td colspan="1" rowspan="1" align="char" char="." valign="top">7.5 (6.7–8.3)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">6.4 (5.9–7.0)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">Diabetes</td><td colspan="1" rowspan="1" align="char" char="." valign="top">39.2 (29.5–48.8)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.19</td><td colspan="1" rowspan="1" align="char" char="." valign="top">25.9 (20.8–31.1)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.23</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Low TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">Low BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">4.3 (3.8–4.8)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">2.9 (2.3–3.5)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Low TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">High BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">4.8 (2.6–8.2)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">5.2 (2.7–9.0)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">Low BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">8.3 (7.5–9.2)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">7.2 (6.5–7.8)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High TRIG</td><td colspan="1" rowspan="1" align="left" valign="top">High BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">15.1 (9.7–20.5)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.38</td><td colspan="1" rowspan="1" align="char" char="." valign="top">10.1 (7.5. 12.8)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.14</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High HDL</td><td colspan="1" rowspan="1" align="left" valign="top">No high BP</td><td colspan="1" rowspan="1" align="char" char="." valign="top">4.5 (4.0–5.0)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">3.2 (2.7–3.8)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High HDL</td><td colspan="1" rowspan="1" align="left" valign="top">High BP</td><td colspan="1" rowspan="1" align="char" char="." valign="top">10.1 (8.0–12.1)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">6.7 (5.2–8.2)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Low HDL</td><td colspan="1" rowspan="1" align="left" valign="top">No high BP</td><td colspan="1" rowspan="1" align="char" char="." valign="top">8.0 (6.9–9.1)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">6.3 (5.4–7.2)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Low HDL</td><td colspan="1" rowspan="1" align="left" valign="top">High BP</td><td colspan="1" rowspan="1" align="char" char="." valign="top">10.3 (7.9–12.8)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.04<xref ref-type="table-fn" rid="t2fn3">‡</xref></td><td colspan="1" rowspan="1" align="char" char="." valign="top">9.4 (8.3–10.6)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.05<xref ref-type="table-fn" rid="t2fn3">‡</xref></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High HDL</td><td colspan="1" rowspan="1" align="left" valign="top">No diabetes</td><td colspan="1" rowspan="1" align="char" char="." valign="top">4.7 (4.2–5.1)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">3.7 (3.1–4.2)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High HDL</td><td colspan="1" rowspan="1" align="left" valign="top">Diabetes</td><td colspan="1" rowspan="1" align="char" char="." valign="top">24.7 (17.5–31.9)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">17.8 (10.9–24.6)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Low HDL</td><td colspan="1" rowspan="1" align="left" valign="top">No diabetes</td><td colspan="1" rowspan="1" align="char" char="." valign="top">7.3 (6.4–8.3)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">6.8 (6.2–7.5)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Low HDL</td><td colspan="1" rowspan="1" align="left" valign="top">Diabetes</td><td colspan="1" rowspan="1" align="char" char="." valign="top">39.4 (27.6–51.2)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.80</td><td colspan="1" rowspan="1" align="char" char="." valign="top">26.3 (20.5–32.1)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.53</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High HDL</td><td colspan="1" rowspan="1" align="left" valign="top">Low BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">5.0 (4.5–5.5)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">4.0 (3.4–4.5)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High HDL</td><td colspan="1" rowspan="1" align="left" valign="top">High BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">7.3 (4.5–10.2)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">5.0 (2.8–7.1)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Low HDL</td><td colspan="1" rowspan="1" align="left" valign="top">Low BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">8.2 (7.2–9.2)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">7.5 (6.8–8.2)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Low HDL</td><td colspan="1" rowspan="1" align="left" valign="top">High BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">14.8 (8.6–23.6)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.52</td><td colspan="1" rowspan="1" align="char" char="." valign="top">12.6 (9.0–16.2)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.32</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">No high BP</td><td colspan="1" rowspan="1" align="left" valign="top">No diabetes</td><td colspan="1" rowspan="1" align="char" char="." valign="top">4.9 (4.4–5.3)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">4.1 (3.6–4.6)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">No high BP</td><td colspan="1" rowspan="1" align="left" valign="top">Diabetes</td><td colspan="1" rowspan="1" align="char" char="." valign="top">27.9 (20.8–35.0)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">20.7 (14.2–27.2)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High BP</td><td colspan="1" rowspan="1" align="left" valign="top">No diabetes</td><td colspan="1" rowspan="1" align="char" char="." valign="top">8.8 (7.3–10.3)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">7.5 (6.6–8.4)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High BP</td><td colspan="1" rowspan="1" align="left" valign="top">Diabetes</td><td colspan="1" rowspan="1" align="char" char="." valign="top">36.3 (23.1–49.6)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.55</td><td colspan="1" rowspan="1" align="char" char="." valign="top">25.5 (19.4–31.7)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.21</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">No high BP</td><td colspan="1" rowspan="1" align="left" valign="top">Low BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">5.3 (4.8–5.8)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">4.6 (4.0–5.1)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">No high BP</td><td colspan="1" rowspan="1" align="left" valign="top">High BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">8.3 (5.2–11.4)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">4.8 (2.9–7.6)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High BP</td><td colspan="1" rowspan="1" align="left" valign="top">Low BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">10.1 (8.4–11.7)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">8.2 (7.3–9.2)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">High BP</td><td colspan="1" rowspan="1" align="left" valign="top">High BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">11.4 (5.6–17.1)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.23</td><td colspan="1" rowspan="1" align="char" char="." valign="top">12.1 (8.8–15.5)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.43</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">No diabetes</td><td colspan="1" rowspan="1" align="left" valign="top">Low BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">5.4 (4.9–5.8)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">5.3 (4.8–5.7)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">No diabetes</td><td colspan="1" rowspan="1" align="left" valign="top">High BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">6.0 (3.7–8.4)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">6.1 (4.2–7.9)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Diabetes</td><td colspan="1" rowspan="1" align="left" valign="top">Low BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">28.2 (21.6–34.7)</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="char" char="." valign="top">22.2 (17.3–27.1)</td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Diabetes</td><td colspan="1" rowspan="1" align="left" valign="top">High BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">43.3 (25.2–69.3)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.12</td><td colspan="1" rowspan="1" align="char" char="." valign="top">28.7 (17.7–39.8)</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.44</td></tr></tbody></table><table-wrap-foot><fn><p>Data are CVD incidence rates per 1,000 person years (95 % CI).</p></fn><fn id="t2fn1"><label>*</label><p>High triglycerides (TRIG): ≥ 1.7 mmol/l; low HDL cholesterol: ≤1.0 mmol/l (men) or ≤1.3 mmol/l (women); high blood pressure (BP): systolic BP >130 mmHg or diastolic BP >85 mmHg; diabetes: an established diagnosis of diabetes.</p></fn><fn id="t2fn2"><label>†</label><p><italic>P</italic> values for the interaction between each component pair were obtained from a multivariable Poisson regression model that included all main effects and all pairwise interactions, as well as adjustment for other potential confounders (see <sc>research design and methods</sc>).</p></fn><fn id="t2fn3"><label>‡</label><p>ARRs were all <1, suggesting an antagonistic rather than synergistic effect of each combination of components.</p></fn></table-wrap-foot></table-wrap><table-wrap position="float" id="t3"><label>Table 3</label><caption><p>Association between the metabolic syndrome (time-updated analyses), its components, and CVD from main and sensitivity analyses</p></caption><table frame="hsides" rules="groups"><thead><tr><th colspan="1" rowspan="1" align="center" valign="bottom">Factor<xref ref-type="table-fn" rid="t3fn1">*</xref></th><th colspan="1" rowspan="1" align="center" valign="bottom">Main analysis: training set (671 events, 110,652 person-years)</th><th colspan="1" rowspan="1" align="center" valign="bottom">Main analysis: validation set (303 events, 48,741 person-years)</th><th colspan="1" rowspan="1" align="center" valign="bottom">Metabolic syndrome components reversible (671 events, 110,652 person-years)</th><th colspan="1" rowspan="1" align="center" valign="bottom">No missing data on metabolic syndrome components (377 events, 57,536 person-years)</th></tr></thead><tbody><tr><td colspan="1" rowspan="1" align="left" valign="top">Unadjusted</td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> MS</td><td colspan="1" rowspan="1" align="char" char="." valign="top">2.40 (2.06–2.79); 0.0001</td><td colspan="1" rowspan="1" align="char" char="." valign="top">2.71 (2.16–3.40); 0.0001</td><td colspan="1" rowspan="1" align="char" char="." valign="top">3.02 (2.54–3.59); 0.0001</td><td colspan="1" rowspan="1" align="char" char="." valign="top">3.34 (2.36–4.74); 0.0001</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top">Adjusted<xref ref-type="table-fn" rid="t3fn2">†</xref></td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="center" valign="top"></td><td colspan="1" rowspan="1" align="center" valign="top"></td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> MS</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.94 (0.69–1.27); 0.67</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.00 (0.64–1.57); 0.99</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.03 (0.77–1.39); 0.83</td><td colspan="1" rowspan="1" align="char" char="." valign="top">0.88 (0.52–1.49); 0.63</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> High TRIG</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.50 (1.18–1.91); 0.001</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.26 (0.88–1.79); 0.20</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.47 (1.23–1.76); 0.0001</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.39 (1.10–1.76); 0.006</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> Low HDL</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.41 (1.12–1.76); 0.003</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.61 (1.12–2.30); 0.009</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.25 (1.03–1.51); 0.02</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.44 (1.12–1.86); 0.005</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> High BP</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.26 (0.98–1.62); 0.07</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.40 (0.95–2.05); 0.09</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.14 (0.92–1.41); 0.23</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.23 (0.98–1.53); 0.07</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> Diabetes</td><td colspan="1" rowspan="1" align="char" char="." valign="top">2.31 (1.83–2.92); 0.0001</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.96 (1.39–2.77); 0.0001</td><td colspan="1" rowspan="1" align="char" char="." valign="top">2.27 (1.77–2.92); 0.0001</td><td colspan="1" rowspan="1" align="char" char="." valign="top">2.07 (1.43–2.99); 0.0001</td></tr><tr><td colspan="1" rowspan="1" align="left" valign="top"> High BMI</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.33 (1.01–1.74); 0.04</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.38 (0.94–2.03); 0.10</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.13 (0.79–1.60); 0.51</td><td colspan="1" rowspan="1" align="char" char="." valign="top">1.09 (0.67–1.79); 0.72</td></tr></tbody></table><table-wrap-foot><fn><p>Data are ARRs (95% CI); <italic>P</italic> values.</p></fn><fn id="t3fn1"><label>*</label><p>High triglycerides (TRIG): ≥1.7 mmol/l; low HDL cholesterol: ≤1.0 mmol/l (men) or ≤1.3 mmol/l (women); high blood pressure (BP): systolic BP >130 mmHg or diastolic BP >85 mmHg; diabetes: an established diagnosis of diabetes; high BMI: >30 kg/m<sup>2</sup>.</p></fn><fn id="t3fn2"><label>†</label><p>Adjusted estimates obtained from a multivariable Poisson regression model that also includes adjustment for other potential confounders as sex, age, family history of CVD, smoking status, calendar year, cohort, HIV risk group, ethnic group, and exposure to the protease inhibitor, NRTI, and NNRTI classes of drugs.</p></fn></table-wrap-foot></table-wrap></floats-wrap></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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