Anthropometric parameter that best predict metabolic syndrome in South west Nigeria
This study compared the ability of anthropometric parameters to predict Metabolic Syndrome (MetS). Eleven anthropometric parameters: waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), visceral adiposity index (VAI), a...
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Veröffentlicht in: | Diabetes & metabolic syndrome clinical research & reviews 2019-01, Vol.13 (1), p.48-54 |
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creator | Adejumo, Esther Ngozi Adejumo, Adedeji Olusola Azenabor, Alfred Ekun, Ayodele Oloruntoba Enitan, Seyi Samson Adebola, Olayimika Kehinde Ogundahunsi, Omobolanle Abioye |
description | This study compared the ability of anthropometric parameters to predict Metabolic Syndrome (MetS).
Eleven anthropometric parameters: waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), visceral adiposity index (VAI), abdominal volume index (AVI), Conicity Index (CI), body adiposity index (BAI), lipid accumulation product (LAP) and waist circumference-triglyceride index (WTI) were measured and calculated in apparently healthy subjects with and without MetS. A receiver operating characteristic (ROC) curve was applied to assess their ability to predict MetS.
Of the 535 subjects recruited 23% had MetS. WC had the largest area under the curve (AUC) in both men (0.814 95% CI 0.721–0.907) and women (0.819 95%CI 0.771–0.867). This did not differ from the AUC of BMI, WHtR, BRI, CI, BAI, LAP in men and BMI, WHtR, BAI, LAP, VAI and WTI in women (P > 0.05). The cutoff point for WC was 89.5 cm and 91.8 cm in men and women respectively. The AUC of WC was the largest in the 40–49 and 60 years and above age groups while the AUC of LAP was the largest for age groups 30–39 and 50–59 years.
Of the 11 anthropometric parameters assessed, the WC was the best at predicting MetS in both men and women. There is need to ascertain the cutoff point and establish landmark for measuring WC especially for the sub Saharan region. |
doi_str_mv | 10.1016/j.dsx.2018.08.009 |
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Eleven anthropometric parameters: waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), visceral adiposity index (VAI), abdominal volume index (AVI), Conicity Index (CI), body adiposity index (BAI), lipid accumulation product (LAP) and waist circumference-triglyceride index (WTI) were measured and calculated in apparently healthy subjects with and without MetS. A receiver operating characteristic (ROC) curve was applied to assess their ability to predict MetS.
Of the 535 subjects recruited 23% had MetS. WC had the largest area under the curve (AUC) in both men (0.814 95% CI 0.721–0.907) and women (0.819 95%CI 0.771–0.867). This did not differ from the AUC of BMI, WHtR, BRI, CI, BAI, LAP in men and BMI, WHtR, BAI, LAP, VAI and WTI in women (P > 0.05). The cutoff point for WC was 89.5 cm and 91.8 cm in men and women respectively. The AUC of WC was the largest in the 40–49 and 60 years and above age groups while the AUC of LAP was the largest for age groups 30–39 and 50–59 years.
Of the 11 anthropometric parameters assessed, the WC was the best at predicting MetS in both men and women. There is need to ascertain the cutoff point and establish landmark for measuring WC especially for the sub Saharan region.</description><identifier>ISSN: 1871-4021</identifier><identifier>EISSN: 1878-0334</identifier><identifier>DOI: 10.1016/j.dsx.2018.08.009</identifier><identifier>PMID: 30641748</identifier><language>eng</language><publisher>Netherlands: Elsevier Ltd</publisher><subject>Anthropometric parameters ; Lagos ; Metabolic syndrome ; Nigeria ; Predictors</subject><ispartof>Diabetes & metabolic syndrome clinical research & reviews, 2019-01, Vol.13 (1), p.48-54</ispartof><rights>2018 Diabetes India</rights><rights>Copyright © 2018 Diabetes India. Published by Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c353t-c3937cc88e1f50cc6afcce8b8de5a26e533d3d46438c78ea2560e0076b0a7dc13</citedby><cites>FETCH-LOGICAL-c353t-c3937cc88e1f50cc6afcce8b8de5a26e533d3d46438c78ea2560e0076b0a7dc13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.dsx.2018.08.009$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30641748$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Adejumo, Esther Ngozi</creatorcontrib><creatorcontrib>Adejumo, Adedeji Olusola</creatorcontrib><creatorcontrib>Azenabor, Alfred</creatorcontrib><creatorcontrib>Ekun, Ayodele Oloruntoba</creatorcontrib><creatorcontrib>Enitan, Seyi Samson</creatorcontrib><creatorcontrib>Adebola, Olayimika Kehinde</creatorcontrib><creatorcontrib>Ogundahunsi, Omobolanle Abioye</creatorcontrib><title>Anthropometric parameter that best predict metabolic syndrome in South west Nigeria</title><title>Diabetes & metabolic syndrome clinical research & reviews</title><addtitle>Diabetes Metab Syndr</addtitle><description>This study compared the ability of anthropometric parameters to predict Metabolic Syndrome (MetS).
Eleven anthropometric parameters: waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), visceral adiposity index (VAI), abdominal volume index (AVI), Conicity Index (CI), body adiposity index (BAI), lipid accumulation product (LAP) and waist circumference-triglyceride index (WTI) were measured and calculated in apparently healthy subjects with and without MetS. A receiver operating characteristic (ROC) curve was applied to assess their ability to predict MetS.
Of the 535 subjects recruited 23% had MetS. WC had the largest area under the curve (AUC) in both men (0.814 95% CI 0.721–0.907) and women (0.819 95%CI 0.771–0.867). This did not differ from the AUC of BMI, WHtR, BRI, CI, BAI, LAP in men and BMI, WHtR, BAI, LAP, VAI and WTI in women (P > 0.05). The cutoff point for WC was 89.5 cm and 91.8 cm in men and women respectively. The AUC of WC was the largest in the 40–49 and 60 years and above age groups while the AUC of LAP was the largest for age groups 30–39 and 50–59 years.
Of the 11 anthropometric parameters assessed, the WC was the best at predicting MetS in both men and women. There is need to ascertain the cutoff point and establish landmark for measuring WC especially for the sub Saharan region.</description><subject>Anthropometric parameters</subject><subject>Lagos</subject><subject>Metabolic syndrome</subject><subject>Nigeria</subject><subject>Predictors</subject><issn>1871-4021</issn><issn>1878-0334</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LAzEQhoMotlZ_gBfZo5fWyWY3m8VTKX5B0UP1HLLJ1Kbsl0mq9t-bWvUoDMkwPO_LzEvIOYUJBcqv1hPjPycpUDGBWFAekCEVhRgDY9nhd0_HGaR0QE68XwPkeZmWx2TAgGe0yMSQLKZtWLmu7xoMzuqkV07FFl0SViokFfqQ9A6N1SGJc1V1daT8tjUuShLbJotuE1bJxw58tK_orDolR0tVezz7-Ufk5fbmeXY_nj_dPcym87FmOQvxLVmhtRBIlzlozdVSaxSVMJirlGPOmGEm4xkTuhCo0pwDAhS8AlUYTdmIXO59e9e9beICsrFeY12rFruNlyktSsbLMhcRpXtUu857h0vZO9sot5UU5C5LuZYxS7nLUkIsKKPm4sd-UzVo_hS_4UXgeg9gPPLdopNeW2x1TMuhDtJ09h_7LyRbhgY</recordid><startdate>201901</startdate><enddate>201901</enddate><creator>Adejumo, Esther Ngozi</creator><creator>Adejumo, Adedeji Olusola</creator><creator>Azenabor, Alfred</creator><creator>Ekun, Ayodele Oloruntoba</creator><creator>Enitan, Seyi Samson</creator><creator>Adebola, Olayimika Kehinde</creator><creator>Ogundahunsi, Omobolanle Abioye</creator><general>Elsevier Ltd</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>201901</creationdate><title>Anthropometric parameter that best predict metabolic syndrome in South west Nigeria</title><author>Adejumo, Esther Ngozi ; Adejumo, Adedeji Olusola ; Azenabor, Alfred ; Ekun, Ayodele Oloruntoba ; Enitan, Seyi Samson ; Adebola, Olayimika Kehinde ; Ogundahunsi, Omobolanle Abioye</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c353t-c3937cc88e1f50cc6afcce8b8de5a26e533d3d46438c78ea2560e0076b0a7dc13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Anthropometric parameters</topic><topic>Lagos</topic><topic>Metabolic syndrome</topic><topic>Nigeria</topic><topic>Predictors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Adejumo, Esther Ngozi</creatorcontrib><creatorcontrib>Adejumo, Adedeji Olusola</creatorcontrib><creatorcontrib>Azenabor, Alfred</creatorcontrib><creatorcontrib>Ekun, Ayodele Oloruntoba</creatorcontrib><creatorcontrib>Enitan, Seyi Samson</creatorcontrib><creatorcontrib>Adebola, Olayimika Kehinde</creatorcontrib><creatorcontrib>Ogundahunsi, Omobolanle Abioye</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Diabetes & metabolic syndrome clinical research & reviews</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Adejumo, Esther Ngozi</au><au>Adejumo, Adedeji Olusola</au><au>Azenabor, Alfred</au><au>Ekun, Ayodele Oloruntoba</au><au>Enitan, Seyi Samson</au><au>Adebola, Olayimika Kehinde</au><au>Ogundahunsi, Omobolanle Abioye</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Anthropometric parameter that best predict metabolic syndrome in South west Nigeria</atitle><jtitle>Diabetes & metabolic syndrome clinical research & reviews</jtitle><addtitle>Diabetes Metab Syndr</addtitle><date>2019-01</date><risdate>2019</risdate><volume>13</volume><issue>1</issue><spage>48</spage><epage>54</epage><pages>48-54</pages><issn>1871-4021</issn><eissn>1878-0334</eissn><abstract>This study compared the ability of anthropometric parameters to predict Metabolic Syndrome (MetS).
Eleven anthropometric parameters: waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), visceral adiposity index (VAI), abdominal volume index (AVI), Conicity Index (CI), body adiposity index (BAI), lipid accumulation product (LAP) and waist circumference-triglyceride index (WTI) were measured and calculated in apparently healthy subjects with and without MetS. A receiver operating characteristic (ROC) curve was applied to assess their ability to predict MetS.
Of the 535 subjects recruited 23% had MetS. WC had the largest area under the curve (AUC) in both men (0.814 95% CI 0.721–0.907) and women (0.819 95%CI 0.771–0.867). This did not differ from the AUC of BMI, WHtR, BRI, CI, BAI, LAP in men and BMI, WHtR, BAI, LAP, VAI and WTI in women (P > 0.05). The cutoff point for WC was 89.5 cm and 91.8 cm in men and women respectively. The AUC of WC was the largest in the 40–49 and 60 years and above age groups while the AUC of LAP was the largest for age groups 30–39 and 50–59 years.
Of the 11 anthropometric parameters assessed, the WC was the best at predicting MetS in both men and women. There is need to ascertain the cutoff point and establish landmark for measuring WC especially for the sub Saharan region.</abstract><cop>Netherlands</cop><pub>Elsevier Ltd</pub><pmid>30641748</pmid><doi>10.1016/j.dsx.2018.08.009</doi><tpages>7</tpages></addata></record> |
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subjects | Anthropometric parameters Lagos Metabolic syndrome Nigeria Predictors |
title | Anthropometric parameter that best predict metabolic syndrome in South west Nigeria |
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