Does the metabolic syndrome predict subclinical atherosclerotic damage in an asymptomatic population at intermediate cardiovascular risk?
Abstract Background and Aims It is not clear whether the metabolic syndrome (MetS) is a distinct entity or a combination of risk factors. Several studies showed the association between MetS and cardiovascular disease (CVD). Subclinical target organ damage (TOD) is a recognized marker of atherosclero...
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Veröffentlicht in: | Nutrition, metabolism, and cardiovascular diseases metabolism, and cardiovascular diseases, 2013-09, Vol.23 (9), p.864-870 |
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description | Abstract Background and Aims It is not clear whether the metabolic syndrome (MetS) is a distinct entity or a combination of risk factors. Several studies showed the association between MetS and cardiovascular disease (CVD). Subclinical target organ damage (TOD) is a recognized marker of atherosclerosis and predictor of cardiovascular events. Increased burden of subclinical atherosclerosis was detected in individuals with MetS. We thus aimed to examine the association between MetS and cumulative or specific TOD and to assess whether MetS predicts TOD better than the risk factors included in current definitions. Methods and Results We recorded TOD in 979 patients at intermediate cardiovascular risk with and without MetS according to IDF and NCEP criteria. We measured common carotid intima-media thickness, left ventricular mass index (LVMI), urine albumin to creatinine ratio (UACR), and ankle-brachial index. We found no correlation between having at least one TOD and being positive for MetS. A high UACR was associated with MetS using both IDF and NCEP criteria, while only NCEP identified individuals with increased LVMI. Using a multivariate logistic regression model including MetS, age, sex, waist circumference, triglycerides, HDL cholesterol, blood pressure and blood glucose levels we found no correlations between the presence of MetS and at least one TOD. The associations with high UACR and LVMI disappeared when age, blood pressure and glycemia were counted in. Conclusion Although MetS showed some relation with subclinical renal and cardiac damage, it does not predict TOD any better than the risk factors specified in the definitions. |
doi_str_mv | 10.1016/j.numecd.2012.06.003 |
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Several studies showed the association between MetS and cardiovascular disease (CVD). Subclinical target organ damage (TOD) is a recognized marker of atherosclerosis and predictor of cardiovascular events. Increased burden of subclinical atherosclerosis was detected in individuals with MetS. We thus aimed to examine the association between MetS and cumulative or specific TOD and to assess whether MetS predicts TOD better than the risk factors included in current definitions. Methods and Results We recorded TOD in 979 patients at intermediate cardiovascular risk with and without MetS according to IDF and NCEP criteria. We measured common carotid intima-media thickness, left ventricular mass index (LVMI), urine albumin to creatinine ratio (UACR), and ankle-brachial index. We found no correlation between having at least one TOD and being positive for MetS. A high UACR was associated with MetS using both IDF and NCEP criteria, while only NCEP identified individuals with increased LVMI. Using a multivariate logistic regression model including MetS, age, sex, waist circumference, triglycerides, HDL cholesterol, blood pressure and blood glucose levels we found no correlations between the presence of MetS and at least one TOD. The associations with high UACR and LVMI disappeared when age, blood pressure and glycemia were counted in. Conclusion Although MetS showed some relation with subclinical renal and cardiac damage, it does not predict TOD any better than the risk factors specified in the definitions.</description><identifier>ISSN: 0939-4753</identifier><identifier>EISSN: 1590-3729</identifier><identifier>DOI: 10.1016/j.numecd.2012.06.003</identifier><identifier>PMID: 22901845</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Adult ; Aged ; albumins ; Albuminuria ; Albuminuria - etiology ; Albuminuria - physiopathology ; Ankle Brachial Index ; Atherosclerosis ; blood glucose ; Blood Pressure ; Cardiovascular ; Cardiovascular diseases ; Cardiovascular Diseases - complications ; Cardiovascular Diseases - diagnostic imaging ; Cardiovascular Diseases - physiopathology ; Carotid artery diseases ; Carotid Intima-Media Thickness ; Cholesterol, HDL - blood ; creatinine ; Creatinine - urine ; Cross-Sectional Studies ; Female ; high density lipoprotein cholesterol ; Humans ; Left ventricular hypertrophy ; Logistic Models ; Male ; metabolic syndrome ; Metabolic Syndrome - complications ; Metabolic Syndrome - diagnostic imaging ; Metabolic Syndrome - physiopathology ; Metabolic syndrome X ; Middle Aged ; Multivariate Analysis ; patients ; Peripheral arterial disease ; Peripheral Arterial Disease - diagnostic imaging ; Peripheral Arterial Disease - etiology ; Peripheral Arterial Disease - physiopathology ; regression analysis ; risk ; Risk Factors ; Takotsubo Cardiomyopathy - diagnostic imaging ; Takotsubo Cardiomyopathy - physiopathology ; triacylglycerols ; Triglycerides - blood ; urine ; waist circumference</subject><ispartof>Nutrition, metabolism, and cardiovascular diseases, 2013-09, Vol.23 (9), p.864-870</ispartof><rights>Elsevier B.V.</rights><rights>2012 Elsevier B.V.</rights><rights>Copyright © 2012 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c441t-48a89c2cb3893464cb47c1091110b2558df061080b4db209eab5188025a5dec73</citedby><cites>FETCH-LOGICAL-c441t-48a89c2cb3893464cb47c1091110b2558df061080b4db209eab5188025a5dec73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.numecd.2012.06.003$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22901845$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zocchi, L</creatorcontrib><creatorcontrib>Perego, F</creatorcontrib><creatorcontrib>Casella, F</creatorcontrib><creatorcontrib>Arquati, M</creatorcontrib><creatorcontrib>Renesto, E</creatorcontrib><creatorcontrib>Casazza, G</creatorcontrib><creatorcontrib>D'Ambrosio, A</creatorcontrib><creatorcontrib>Cortellaro, M</creatorcontrib><title>Does the metabolic syndrome predict subclinical atherosclerotic damage in an asymptomatic population at intermediate cardiovascular risk?</title><title>Nutrition, metabolism, and cardiovascular diseases</title><addtitle>Nutr Metab Cardiovasc Dis</addtitle><description>Abstract Background and Aims It is not clear whether the metabolic syndrome (MetS) is a distinct entity or a combination of risk factors. Several studies showed the association between MetS and cardiovascular disease (CVD). Subclinical target organ damage (TOD) is a recognized marker of atherosclerosis and predictor of cardiovascular events. Increased burden of subclinical atherosclerosis was detected in individuals with MetS. We thus aimed to examine the association between MetS and cumulative or specific TOD and to assess whether MetS predicts TOD better than the risk factors included in current definitions. Methods and Results We recorded TOD in 979 patients at intermediate cardiovascular risk with and without MetS according to IDF and NCEP criteria. We measured common carotid intima-media thickness, left ventricular mass index (LVMI), urine albumin to creatinine ratio (UACR), and ankle-brachial index. We found no correlation between having at least one TOD and being positive for MetS. A high UACR was associated with MetS using both IDF and NCEP criteria, while only NCEP identified individuals with increased LVMI. Using a multivariate logistic regression model including MetS, age, sex, waist circumference, triglycerides, HDL cholesterol, blood pressure and blood glucose levels we found no correlations between the presence of MetS and at least one TOD. The associations with high UACR and LVMI disappeared when age, blood pressure and glycemia were counted in. Conclusion Although MetS showed some relation with subclinical renal and cardiac damage, it does not predict TOD any better than the risk factors specified in the definitions.</description><subject>Adult</subject><subject>Aged</subject><subject>albumins</subject><subject>Albuminuria</subject><subject>Albuminuria - etiology</subject><subject>Albuminuria - physiopathology</subject><subject>Ankle Brachial Index</subject><subject>Atherosclerosis</subject><subject>blood glucose</subject><subject>Blood Pressure</subject><subject>Cardiovascular</subject><subject>Cardiovascular diseases</subject><subject>Cardiovascular Diseases - complications</subject><subject>Cardiovascular Diseases - diagnostic imaging</subject><subject>Cardiovascular Diseases - physiopathology</subject><subject>Carotid artery diseases</subject><subject>Carotid Intima-Media Thickness</subject><subject>Cholesterol, HDL - blood</subject><subject>creatinine</subject><subject>Creatinine - urine</subject><subject>Cross-Sectional Studies</subject><subject>Female</subject><subject>high density lipoprotein cholesterol</subject><subject>Humans</subject><subject>Left ventricular hypertrophy</subject><subject>Logistic Models</subject><subject>Male</subject><subject>metabolic syndrome</subject><subject>Metabolic Syndrome - complications</subject><subject>Metabolic Syndrome - diagnostic imaging</subject><subject>Metabolic Syndrome - physiopathology</subject><subject>Metabolic syndrome X</subject><subject>Middle Aged</subject><subject>Multivariate Analysis</subject><subject>patients</subject><subject>Peripheral arterial disease</subject><subject>Peripheral Arterial Disease - diagnostic imaging</subject><subject>Peripheral Arterial Disease - etiology</subject><subject>Peripheral Arterial Disease - physiopathology</subject><subject>regression analysis</subject><subject>risk</subject><subject>Risk Factors</subject><subject>Takotsubo Cardiomyopathy - diagnostic imaging</subject><subject>Takotsubo Cardiomyopathy - physiopathology</subject><subject>triacylglycerols</subject><subject>Triglycerides - blood</subject><subject>urine</subject><subject>waist circumference</subject><issn>0939-4753</issn><issn>1590-3729</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkstu1TAQhiMEoofCGyDIkk0O40sSewNC5SpVYlG6thxnTvFpEgfbqXQegbdmorQs2CBZtmV_83vmHxfFSwZ7Bqx5e9xPy4iu33NgfA_NHkA8Knas1lCJluvHxQ600JVsa3FWPEvpSEALQj4tzjjXwJSsd8XvjwFTmX9iOWK2XRi8K9Np6mMYsZwj9t7lMi2dG_zknR1KS2wMyQ00Z4J7O9obLP1UWhrpNM45jHa9mcO8DLQLdJ4JyBhH0rMZS2dj78OdTY6IWEafbt8_L54c7JDwxf16Xlx__vTj4mt1-f3Lt4sPl5WTkuVKKqu0464TSgvZSNfJ1jHQjDHoeF2r_gANAwWd7DsOGm1XM6WA17bu0bXivHiz6c4x_FowZTP65HAY7IRhSYZJIXijFUhC5YY6qjhFPJg5-tHGk2Fg1iaYo9maYNYmGGgMeUxhr-5fWDqq-G_Qg-sEvN6Agw3G3lD55vqKFGoAUEy1q8S7jUBy4s5jNMl5nBz5F9Fl0wf_vxz-FXjo4C2eMB3DEidy2TCTKMZcrV9l_SmMA-UhlfgDGEy60A</recordid><startdate>20130901</startdate><enddate>20130901</enddate><creator>Zocchi, L</creator><creator>Perego, F</creator><creator>Casella, F</creator><creator>Arquati, M</creator><creator>Renesto, E</creator><creator>Casazza, G</creator><creator>D'Ambrosio, A</creator><creator>Cortellaro, M</creator><general>Elsevier B.V</general><scope>FBQ</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20130901</creationdate><title>Does the metabolic syndrome predict subclinical atherosclerotic damage in an asymptomatic population at intermediate cardiovascular risk?</title><author>Zocchi, L ; Perego, F ; Casella, F ; Arquati, M ; Renesto, E ; Casazza, G ; D'Ambrosio, A ; Cortellaro, M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c441t-48a89c2cb3893464cb47c1091110b2558df061080b4db209eab5188025a5dec73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Adult</topic><topic>Aged</topic><topic>albumins</topic><topic>Albuminuria</topic><topic>Albuminuria - etiology</topic><topic>Albuminuria - physiopathology</topic><topic>Ankle Brachial Index</topic><topic>Atherosclerosis</topic><topic>blood glucose</topic><topic>Blood Pressure</topic><topic>Cardiovascular</topic><topic>Cardiovascular diseases</topic><topic>Cardiovascular Diseases - complications</topic><topic>Cardiovascular Diseases - diagnostic imaging</topic><topic>Cardiovascular Diseases - physiopathology</topic><topic>Carotid artery diseases</topic><topic>Carotid Intima-Media Thickness</topic><topic>Cholesterol, HDL - blood</topic><topic>creatinine</topic><topic>Creatinine - urine</topic><topic>Cross-Sectional Studies</topic><topic>Female</topic><topic>high density lipoprotein cholesterol</topic><topic>Humans</topic><topic>Left ventricular hypertrophy</topic><topic>Logistic Models</topic><topic>Male</topic><topic>metabolic syndrome</topic><topic>Metabolic Syndrome - complications</topic><topic>Metabolic Syndrome - diagnostic imaging</topic><topic>Metabolic Syndrome - physiopathology</topic><topic>Metabolic syndrome X</topic><topic>Middle Aged</topic><topic>Multivariate Analysis</topic><topic>patients</topic><topic>Peripheral arterial disease</topic><topic>Peripheral Arterial Disease - diagnostic imaging</topic><topic>Peripheral Arterial Disease - etiology</topic><topic>Peripheral Arterial Disease - physiopathology</topic><topic>regression analysis</topic><topic>risk</topic><topic>Risk Factors</topic><topic>Takotsubo Cardiomyopathy - diagnostic imaging</topic><topic>Takotsubo Cardiomyopathy - physiopathology</topic><topic>triacylglycerols</topic><topic>Triglycerides - blood</topic><topic>urine</topic><topic>waist circumference</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zocchi, L</creatorcontrib><creatorcontrib>Perego, F</creatorcontrib><creatorcontrib>Casella, F</creatorcontrib><creatorcontrib>Arquati, M</creatorcontrib><creatorcontrib>Renesto, E</creatorcontrib><creatorcontrib>Casazza, G</creatorcontrib><creatorcontrib>D'Ambrosio, A</creatorcontrib><creatorcontrib>Cortellaro, M</creatorcontrib><collection>AGRIS</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Nutrition, metabolism, and cardiovascular diseases</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zocchi, L</au><au>Perego, F</au><au>Casella, F</au><au>Arquati, M</au><au>Renesto, E</au><au>Casazza, G</au><au>D'Ambrosio, A</au><au>Cortellaro, M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Does the metabolic syndrome predict subclinical atherosclerotic damage in an asymptomatic population at intermediate cardiovascular risk?</atitle><jtitle>Nutrition, metabolism, and cardiovascular diseases</jtitle><addtitle>Nutr Metab Cardiovasc Dis</addtitle><date>2013-09-01</date><risdate>2013</risdate><volume>23</volume><issue>9</issue><spage>864</spage><epage>870</epage><pages>864-870</pages><issn>0939-4753</issn><eissn>1590-3729</eissn><abstract>Abstract Background and Aims It is not clear whether the metabolic syndrome (MetS) is a distinct entity or a combination of risk factors. Several studies showed the association between MetS and cardiovascular disease (CVD). Subclinical target organ damage (TOD) is a recognized marker of atherosclerosis and predictor of cardiovascular events. Increased burden of subclinical atherosclerosis was detected in individuals with MetS. We thus aimed to examine the association between MetS and cumulative or specific TOD and to assess whether MetS predicts TOD better than the risk factors included in current definitions. Methods and Results We recorded TOD in 979 patients at intermediate cardiovascular risk with and without MetS according to IDF and NCEP criteria. We measured common carotid intima-media thickness, left ventricular mass index (LVMI), urine albumin to creatinine ratio (UACR), and ankle-brachial index. We found no correlation between having at least one TOD and being positive for MetS. A high UACR was associated with MetS using both IDF and NCEP criteria, while only NCEP identified individuals with increased LVMI. Using a multivariate logistic regression model including MetS, age, sex, waist circumference, triglycerides, HDL cholesterol, blood pressure and blood glucose levels we found no correlations between the presence of MetS and at least one TOD. The associations with high UACR and LVMI disappeared when age, blood pressure and glycemia were counted in. Conclusion Although MetS showed some relation with subclinical renal and cardiac damage, it does not predict TOD any better than the risk factors specified in the definitions.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>22901845</pmid><doi>10.1016/j.numecd.2012.06.003</doi><tpages>7</tpages></addata></record> |
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subjects | Adult Aged albumins Albuminuria Albuminuria - etiology Albuminuria - physiopathology Ankle Brachial Index Atherosclerosis blood glucose Blood Pressure Cardiovascular Cardiovascular diseases Cardiovascular Diseases - complications Cardiovascular Diseases - diagnostic imaging Cardiovascular Diseases - physiopathology Carotid artery diseases Carotid Intima-Media Thickness Cholesterol, HDL - blood creatinine Creatinine - urine Cross-Sectional Studies Female high density lipoprotein cholesterol Humans Left ventricular hypertrophy Logistic Models Male metabolic syndrome Metabolic Syndrome - complications Metabolic Syndrome - diagnostic imaging Metabolic Syndrome - physiopathology Metabolic syndrome X Middle Aged Multivariate Analysis patients Peripheral arterial disease Peripheral Arterial Disease - diagnostic imaging Peripheral Arterial Disease - etiology Peripheral Arterial Disease - physiopathology regression analysis risk Risk Factors Takotsubo Cardiomyopathy - diagnostic imaging Takotsubo Cardiomyopathy - physiopathology triacylglycerols Triglycerides - blood urine waist circumference |
title | Does the metabolic syndrome predict subclinical atherosclerotic damage in an asymptomatic population at intermediate cardiovascular risk? |
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