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Comparisons of conventional and novel anthropometric obesity indices to predict metabolic syndrome among vegetarians in Malaysia

Our study aimed to compare the ability of anthropometric obesity indices to predict MetS and to determine the sex-specific optimal cut-off values for MetS among Malaysian vegetarians. Body weight, height, waist circumference (WC), blood pressure (BP), fasting venous blood sample were collected from...

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Autores principales: Ching, Yuan Kei, Chin, Yit Siew, Appukutty, Mahenderan, Gan, Wan Ying, Chan, Yoke Mun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7705716/
https://www.ncbi.nlm.nih.gov/pubmed/33257810
http://dx.doi.org/10.1038/s41598-020-78035-5
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author Ching, Yuan Kei
Chin, Yit Siew
Appukutty, Mahenderan
Gan, Wan Ying
Chan, Yoke Mun
author_facet Ching, Yuan Kei
Chin, Yit Siew
Appukutty, Mahenderan
Gan, Wan Ying
Chan, Yoke Mun
author_sort Ching, Yuan Kei
collection PubMed
description Our study aimed to compare the ability of anthropometric obesity indices to predict MetS and to determine the sex-specific optimal cut-off values for MetS among Malaysian vegetarians. Body weight, height, waist circumference (WC), blood pressure (BP), fasting venous blood sample were collected from 273 vegetarians in Selangor and Kuala Lumpur, Malaysia. The abilities of body mass index (BMI), body fat percentage (BF%), waist to height ratio (WHtR), lipid accumulation product (LAP), visceral adiposity index (VAI), a body shape index (ABSI), and body roundness index (BRI) to identify MetS were tested using receiver operating characteristic (ROC) curve analyses. MetS was defined according to the Joint Interim Statement 2009. The ROC curve analyses show that BMI, BF%, WHtR, LAP and VAI were able to discriminate MetS in both sexes. LAP was a better predictor to predict MetS, followed by WHtR for male and female vegetarians. The suggested WHtR’s optimal cut-offs and LAP’s optimal cut-offs for MetS for male and female vegetarians were 0.541, 0.532, 41.435 and 21.743, respectively. In conclusion, LAP was a better predictor to predict MetS than other anthropometric obesity indices. However, WHtR could be an alternative obesity index in large epidemiology survey due to its convenient and cost-effective characteristics.
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spelling pubmed-77057162020-12-02 Comparisons of conventional and novel anthropometric obesity indices to predict metabolic syndrome among vegetarians in Malaysia Ching, Yuan Kei Chin, Yit Siew Appukutty, Mahenderan Gan, Wan Ying Chan, Yoke Mun Sci Rep Article Our study aimed to compare the ability of anthropometric obesity indices to predict MetS and to determine the sex-specific optimal cut-off values for MetS among Malaysian vegetarians. Body weight, height, waist circumference (WC), blood pressure (BP), fasting venous blood sample were collected from 273 vegetarians in Selangor and Kuala Lumpur, Malaysia. The abilities of body mass index (BMI), body fat percentage (BF%), waist to height ratio (WHtR), lipid accumulation product (LAP), visceral adiposity index (VAI), a body shape index (ABSI), and body roundness index (BRI) to identify MetS were tested using receiver operating characteristic (ROC) curve analyses. MetS was defined according to the Joint Interim Statement 2009. The ROC curve analyses show that BMI, BF%, WHtR, LAP and VAI were able to discriminate MetS in both sexes. LAP was a better predictor to predict MetS, followed by WHtR for male and female vegetarians. The suggested WHtR’s optimal cut-offs and LAP’s optimal cut-offs for MetS for male and female vegetarians were 0.541, 0.532, 41.435 and 21.743, respectively. In conclusion, LAP was a better predictor to predict MetS than other anthropometric obesity indices. However, WHtR could be an alternative obesity index in large epidemiology survey due to its convenient and cost-effective characteristics. Nature Publishing Group UK 2020-11-30 /pmc/articles/PMC7705716/ /pubmed/33257810 http://dx.doi.org/10.1038/s41598-020-78035-5 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Ching, Yuan Kei
Chin, Yit Siew
Appukutty, Mahenderan
Gan, Wan Ying
Chan, Yoke Mun
Comparisons of conventional and novel anthropometric obesity indices to predict metabolic syndrome among vegetarians in Malaysia
title Comparisons of conventional and novel anthropometric obesity indices to predict metabolic syndrome among vegetarians in Malaysia
title_full Comparisons of conventional and novel anthropometric obesity indices to predict metabolic syndrome among vegetarians in Malaysia
title_fullStr Comparisons of conventional and novel anthropometric obesity indices to predict metabolic syndrome among vegetarians in Malaysia
title_full_unstemmed Comparisons of conventional and novel anthropometric obesity indices to predict metabolic syndrome among vegetarians in Malaysia
title_short Comparisons of conventional and novel anthropometric obesity indices to predict metabolic syndrome among vegetarians in Malaysia
title_sort comparisons of conventional and novel anthropometric obesity indices to predict metabolic syndrome among vegetarians in malaysia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7705716/
https://www.ncbi.nlm.nih.gov/pubmed/33257810
http://dx.doi.org/10.1038/s41598-020-78035-5
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