Lipid accumulation product and visceral adiposity index are effective markers for identifying the metabolically obese normal-weight phenotype
Aim Studies have identified the metabolically obese normal-weight (MONW) phenotype, which carries increased risk of diabetes and cardiovascular disease. We aimed to investigate the ability of lipid accumulation product (LAP) and visceral adiposity index (VAI), two markers of visceral obesity, to ide...
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description | Aim
Studies have identified the metabolically obese normal-weight (MONW) phenotype, which carries increased risk of diabetes and cardiovascular disease. We aimed to investigate the ability of lipid accumulation product (LAP) and visceral adiposity index (VAI), two markers of visceral obesity, to identify the MONW phenotype.
Methods
Normal-weight participants [body mass index (BMI) being of 18.5–23 kg/m
2
] (
n
= 3,552; 46.9 % men) in the 2009 nationwide China Health and Nutrition Survey were included in our analysis. Four different criteria that have been published were used to define the MONW phenotype. LAP and VAI were calculated according to published formula.
Results
Receiver operating characteristic (ROC) curve analysis revealed that, regardless of the definition used to define MONW phenotype, both LAP [area under the ROC curve (AUC) ranging from 0.606 to 0.807 depending on the criteria used for MONW phenotype] and VAI (AUC ranging from 0.611 to 0.835 depending on the criteria used for MONW phenotype) outperformed anthropometric parameters including BMI, waist circumference, waist-to-hip ratio, and waist-to-height ratio for identifying MONW phenotype. Both LAP and VAI were strongly related to the MONW phenotype, irrespective of the criteria used to define the MONW phenotype. The associations between the 4th quartile of LAP and the MONW phenotype or between the 4th quartile of VAI and the MONW phenotype were consistently seen in various subgroups.
Conclusion
Our study demonstrates that both LAP and VAI are effective markers for identifying the Chinese adults with MONW phenotype. |
doi_str_mv | 10.1007/s00592-015-0715-2 |
format | Article |
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Studies have identified the metabolically obese normal-weight (MONW) phenotype, which carries increased risk of diabetes and cardiovascular disease. We aimed to investigate the ability of lipid accumulation product (LAP) and visceral adiposity index (VAI), two markers of visceral obesity, to identify the MONW phenotype.
Methods
Normal-weight participants [body mass index (BMI) being of 18.5–23 kg/m
2
] (
n
= 3,552; 46.9 % men) in the 2009 nationwide China Health and Nutrition Survey were included in our analysis. Four different criteria that have been published were used to define the MONW phenotype. LAP and VAI were calculated according to published formula.
Results
Receiver operating characteristic (ROC) curve analysis revealed that, regardless of the definition used to define MONW phenotype, both LAP [area under the ROC curve (AUC) ranging from 0.606 to 0.807 depending on the criteria used for MONW phenotype] and VAI (AUC ranging from 0.611 to 0.835 depending on the criteria used for MONW phenotype) outperformed anthropometric parameters including BMI, waist circumference, waist-to-hip ratio, and waist-to-height ratio for identifying MONW phenotype. Both LAP and VAI were strongly related to the MONW phenotype, irrespective of the criteria used to define the MONW phenotype. The associations between the 4th quartile of LAP and the MONW phenotype or between the 4th quartile of VAI and the MONW phenotype were consistently seen in various subgroups.
Conclusion
Our study demonstrates that both LAP and VAI are effective markers for identifying the Chinese adults with MONW phenotype.</description><identifier>ISSN: 0940-5429</identifier><identifier>EISSN: 1432-5233</identifier><identifier>DOI: 10.1007/s00592-015-0715-2</identifier><identifier>PMID: 25690647</identifier><identifier>CODEN: ACDAEZ</identifier><language>eng</language><publisher>Milan: Springer Milan</publisher><subject>Adiposity ; Adult ; Biomarkers ; Body Mass Index ; Body Weight ; Cardiovascular disease ; Cardiovascular Diseases ; China ; Diabetes ; Female ; Genotype & phenotype ; Humans ; Internal Medicine ; Intra-Abdominal Fat - physiopathology ; Lipid Accumulation Product ; Lipids ; Male ; Medicine ; Medicine & Public Health ; Metabolic Diseases ; Metabolism ; Middle Aged ; Nutrition Surveys ; Obesity ; Obesity, Abdominal ; Original Article ; Phenotype ; Risk factors ; ROC Curve ; Waist Circumference ; Weight</subject><ispartof>Acta diabetologica, 2015-10, Vol.52 (5), p.855-863</ispartof><rights>Springer-Verlag Italia 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c471t-b408fcfac5b4de0383256f1c12f95f373cb83f9d95414ae0c220936a397b13ae3</citedby><cites>FETCH-LOGICAL-c471t-b408fcfac5b4de0383256f1c12f95f373cb83f9d95414ae0c220936a397b13ae3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00592-015-0715-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00592-015-0715-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>315,782,786,27931,27932,41495,42564,51326</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25690647$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Du, Tingting</creatorcontrib><creatorcontrib>Yu, Xuefeng</creatorcontrib><creatorcontrib>Zhang, Jianhua</creatorcontrib><creatorcontrib>Sun, Xingxing</creatorcontrib><title>Lipid accumulation product and visceral adiposity index are effective markers for identifying the metabolically obese normal-weight phenotype</title><title>Acta diabetologica</title><addtitle>Acta Diabetol</addtitle><addtitle>Acta Diabetol</addtitle><description>Aim
Studies have identified the metabolically obese normal-weight (MONW) phenotype, which carries increased risk of diabetes and cardiovascular disease. We aimed to investigate the ability of lipid accumulation product (LAP) and visceral adiposity index (VAI), two markers of visceral obesity, to identify the MONW phenotype.
Methods
Normal-weight participants [body mass index (BMI) being of 18.5–23 kg/m
2
] (
n
= 3,552; 46.9 % men) in the 2009 nationwide China Health and Nutrition Survey were included in our analysis. Four different criteria that have been published were used to define the MONW phenotype. LAP and VAI were calculated according to published formula.
Results
Receiver operating characteristic (ROC) curve analysis revealed that, regardless of the definition used to define MONW phenotype, both LAP [area under the ROC curve (AUC) ranging from 0.606 to 0.807 depending on the criteria used for MONW phenotype] and VAI (AUC ranging from 0.611 to 0.835 depending on the criteria used for MONW phenotype) outperformed anthropometric parameters including BMI, waist circumference, waist-to-hip ratio, and waist-to-height ratio for identifying MONW phenotype. Both LAP and VAI were strongly related to the MONW phenotype, irrespective of the criteria used to define the MONW phenotype. The associations between the 4th quartile of LAP and the MONW phenotype or between the 4th quartile of VAI and the MONW phenotype were consistently seen in various subgroups.
Conclusion
Our study demonstrates that both LAP and VAI are effective markers for identifying the Chinese adults with MONW phenotype.</description><subject>Adiposity</subject><subject>Adult</subject><subject>Biomarkers</subject><subject>Body Mass Index</subject><subject>Body Weight</subject><subject>Cardiovascular disease</subject><subject>Cardiovascular Diseases</subject><subject>China</subject><subject>Diabetes</subject><subject>Female</subject><subject>Genotype & phenotype</subject><subject>Humans</subject><subject>Internal Medicine</subject><subject>Intra-Abdominal Fat - physiopathology</subject><subject>Lipid Accumulation Product</subject><subject>Lipids</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Metabolic Diseases</subject><subject>Metabolism</subject><subject>Middle Aged</subject><subject>Nutrition Surveys</subject><subject>Obesity</subject><subject>Obesity, Abdominal</subject><subject>Original Article</subject><subject>Phenotype</subject><subject>Risk factors</subject><subject>ROC Curve</subject><subject>Waist Circumference</subject><subject>Weight</subject><issn>0940-5429</issn><issn>1432-5233</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqNkc2KFDEURoMoTtv6AG4k4MZNaX67KksZdBQa3Oi6SKVuujOmkjJJzVgP4Tubnh5FBMFNsrjnfuHLQeg5Ja8pIe2bTIhUrCFUNqStB3uANlRw1kjG-UO0IUqQRgqmLtCTnK8Joazl3WN0weROkZ1oN-jH3s1uxNqYZVq8Li4GPKc4LqZgHUZ847KBpD3Wo5tjdmXFLozwHesEGKwFU9wN4Emnr5AytjFhN0Iozq4uHHA51hkUPUTvjPZ-xXGADDjENGnf3II7HAuejxBiWWd4ih5Z7TM8u7-36Mv7d58vPzT7T1cfL9_uGyNaWppBkM4aq40cxAiEd7wWstRQZpW0vOVm6LhVo5KCCg3EMEYU32mu2oFyDXyLXp1za9VvC-TST6ee3usAcck9bTvJmOJ89x8opVLI6qOiL_9Cr-OSQi1yR9GOt9XOFtEzZVLMOYHt5-Tq_609Jf1Ja3_W2let_Ulrz-rOi_vkZZhg_L3xy2MF2BnIdRQOkP54-p-pPwGmrK9h</recordid><startdate>20151001</startdate><enddate>20151001</enddate><creator>Du, Tingting</creator><creator>Yu, Xuefeng</creator><creator>Zhang, Jianhua</creator><creator>Sun, Xingxing</creator><general>Springer Milan</general><general>Springer Nature B.V</general><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>3V.</scope><scope>7T5</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>20151001</creationdate><title>Lipid accumulation product and visceral adiposity index are effective markers for identifying the metabolically obese normal-weight phenotype</title><author>Du, Tingting ; Yu, Xuefeng ; Zhang, Jianhua ; Sun, Xingxing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c471t-b408fcfac5b4de0383256f1c12f95f373cb83f9d95414ae0c220936a397b13ae3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Adiposity</topic><topic>Adult</topic><topic>Biomarkers</topic><topic>Body Mass Index</topic><topic>Body Weight</topic><topic>Cardiovascular disease</topic><topic>Cardiovascular Diseases</topic><topic>China</topic><topic>Diabetes</topic><topic>Female</topic><topic>Genotype & phenotype</topic><topic>Humans</topic><topic>Internal Medicine</topic><topic>Intra-Abdominal Fat - physiopathology</topic><topic>Lipid Accumulation Product</topic><topic>Lipids</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Metabolic Diseases</topic><topic>Metabolism</topic><topic>Middle Aged</topic><topic>Nutrition Surveys</topic><topic>Obesity</topic><topic>Obesity, Abdominal</topic><topic>Original Article</topic><topic>Phenotype</topic><topic>Risk factors</topic><topic>ROC Curve</topic><topic>Waist Circumference</topic><topic>Weight</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Du, Tingting</creatorcontrib><creatorcontrib>Yu, Xuefeng</creatorcontrib><creatorcontrib>Zhang, Jianhua</creatorcontrib><creatorcontrib>Sun, Xingxing</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Immunology Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Acta diabetologica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Du, Tingting</au><au>Yu, Xuefeng</au><au>Zhang, Jianhua</au><au>Sun, Xingxing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Lipid accumulation product and visceral adiposity index are effective markers for identifying the metabolically obese normal-weight phenotype</atitle><jtitle>Acta diabetologica</jtitle><stitle>Acta Diabetol</stitle><addtitle>Acta Diabetol</addtitle><date>2015-10-01</date><risdate>2015</risdate><volume>52</volume><issue>5</issue><spage>855</spage><epage>863</epage><pages>855-863</pages><issn>0940-5429</issn><eissn>1432-5233</eissn><coden>ACDAEZ</coden><abstract>Aim
Studies have identified the metabolically obese normal-weight (MONW) phenotype, which carries increased risk of diabetes and cardiovascular disease. We aimed to investigate the ability of lipid accumulation product (LAP) and visceral adiposity index (VAI), two markers of visceral obesity, to identify the MONW phenotype.
Methods
Normal-weight participants [body mass index (BMI) being of 18.5–23 kg/m
2
] (
n
= 3,552; 46.9 % men) in the 2009 nationwide China Health and Nutrition Survey were included in our analysis. Four different criteria that have been published were used to define the MONW phenotype. LAP and VAI were calculated according to published formula.
Results
Receiver operating characteristic (ROC) curve analysis revealed that, regardless of the definition used to define MONW phenotype, both LAP [area under the ROC curve (AUC) ranging from 0.606 to 0.807 depending on the criteria used for MONW phenotype] and VAI (AUC ranging from 0.611 to 0.835 depending on the criteria used for MONW phenotype) outperformed anthropometric parameters including BMI, waist circumference, waist-to-hip ratio, and waist-to-height ratio for identifying MONW phenotype. Both LAP and VAI were strongly related to the MONW phenotype, irrespective of the criteria used to define the MONW phenotype. The associations between the 4th quartile of LAP and the MONW phenotype or between the 4th quartile of VAI and the MONW phenotype were consistently seen in various subgroups.
Conclusion
Our study demonstrates that both LAP and VAI are effective markers for identifying the Chinese adults with MONW phenotype.</abstract><cop>Milan</cop><pub>Springer Milan</pub><pmid>25690647</pmid><doi>10.1007/s00592-015-0715-2</doi><tpages>9</tpages></addata></record> |
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subjects | Adiposity Adult Biomarkers Body Mass Index Body Weight Cardiovascular disease Cardiovascular Diseases China Diabetes Female Genotype & phenotype Humans Internal Medicine Intra-Abdominal Fat - physiopathology Lipid Accumulation Product Lipids Male Medicine Medicine & Public Health Metabolic Diseases Metabolism Middle Aged Nutrition Surveys Obesity Obesity, Abdominal Original Article Phenotype Risk factors ROC Curve Waist Circumference Weight |
title | Lipid accumulation product and visceral adiposity index are effective markers for identifying the metabolically obese normal-weight phenotype |
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