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Novel and traditional anthropometric indices for identifying metabolic syndrome in non-overweight/obese adults

BACKGROUND: Metabolic syndrome (MetS) in non-overweight/obese people is insidiously associated with cardiovascular disease. Novel anthropometric indices can reflect central obesity better than the traditional anthropometric indices. Therefore, we hypothesize that these newly developed anthropometric...

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Autores principales: Wu, Lihong, Zhu, Wenhua, Qiao, Qiaohua, Huang, Lijuan, Li, Yiqi, Chen, Liying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788902/
https://www.ncbi.nlm.nih.gov/pubmed/33407674
http://dx.doi.org/10.1186/s12986-020-00536-x
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author Wu, Lihong
Zhu, Wenhua
Qiao, Qiaohua
Huang, Lijuan
Li, Yiqi
Chen, Liying
author_facet Wu, Lihong
Zhu, Wenhua
Qiao, Qiaohua
Huang, Lijuan
Li, Yiqi
Chen, Liying
author_sort Wu, Lihong
collection PubMed
description BACKGROUND: Metabolic syndrome (MetS) in non-overweight/obese people is insidiously associated with cardiovascular disease. Novel anthropometric indices can reflect central obesity better than the traditional anthropometric indices. Therefore, we hypothesize that these newly developed anthropometric indices can better identify MetS in non-overweight/obese people than conventional indices. METHODS: Cross-sectional data of sociodemographic, biochemical and anthropometric indices were collected from 2916 non-overweight/obese Chinese people. A body shape index (ABSI), body roundness index (BRI), waist-to-height ratio (WHtR), weight-adjusted-waist index (WWI) and abdominal volume index (AVI) were calculated. Partial correlation analysis was used to clarify the correlation between anthropometric indices and MetS variables. Binary logistic regression analysis was applied to assess the association between anthropometric indices and MetS and its components. Receiver-operating characteristic curve was used to identify the diagnostic ability of anthropometric indices for MetS and its components. The area under curve (AUC) difference between WHtR and each new anthropometric index was compared in pairs. RESULTS: After adjusting for covariates, AVI had the optimal ability of identifying MetS (AUC: 0.743 for male, 0.819 for female) and the strongest correlation with high-density lipoprotein cholesterol (HDL-C) (coe: − 0.227 for male, − 0.207 for female) and the highest odds rations (OR) with low HDL-C group (male: OR = 1.37, female: OR = 1.55). The WHtR was comparable to BRI in assessing MetS (AUC: 0.739 for male, 0.817 for female). WHtR or BRI could also well identify hypertension (AUC: 0.602 for male, 0.688 for female) and dysglycemia (AUC: 0.669 for male, 0.713 for female) and female’s high triglyceride level (AUC 0.712). The recognition ability of the two was equivalent. The ability of ABSI and WWI to identify MetS was weak. CONCLUSIONS: AVI is the optimal anthropometric indices to identify MetS in non-overweight/obese Chinese adults. BRI and WHtR can also be considered as discriminators, while ABSI and WWI are weak discriminators. WHtR is easy to measure. So, it is recommended as an early preliminary screening method for the MetS in non-overweight/obese people.
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spelling pubmed-77889022021-01-07 Novel and traditional anthropometric indices for identifying metabolic syndrome in non-overweight/obese adults Wu, Lihong Zhu, Wenhua Qiao, Qiaohua Huang, Lijuan Li, Yiqi Chen, Liying Nutr Metab (Lond) Research BACKGROUND: Metabolic syndrome (MetS) in non-overweight/obese people is insidiously associated with cardiovascular disease. Novel anthropometric indices can reflect central obesity better than the traditional anthropometric indices. Therefore, we hypothesize that these newly developed anthropometric indices can better identify MetS in non-overweight/obese people than conventional indices. METHODS: Cross-sectional data of sociodemographic, biochemical and anthropometric indices were collected from 2916 non-overweight/obese Chinese people. A body shape index (ABSI), body roundness index (BRI), waist-to-height ratio (WHtR), weight-adjusted-waist index (WWI) and abdominal volume index (AVI) were calculated. Partial correlation analysis was used to clarify the correlation between anthropometric indices and MetS variables. Binary logistic regression analysis was applied to assess the association between anthropometric indices and MetS and its components. Receiver-operating characteristic curve was used to identify the diagnostic ability of anthropometric indices for MetS and its components. The area under curve (AUC) difference between WHtR and each new anthropometric index was compared in pairs. RESULTS: After adjusting for covariates, AVI had the optimal ability of identifying MetS (AUC: 0.743 for male, 0.819 for female) and the strongest correlation with high-density lipoprotein cholesterol (HDL-C) (coe: − 0.227 for male, − 0.207 for female) and the highest odds rations (OR) with low HDL-C group (male: OR = 1.37, female: OR = 1.55). The WHtR was comparable to BRI in assessing MetS (AUC: 0.739 for male, 0.817 for female). WHtR or BRI could also well identify hypertension (AUC: 0.602 for male, 0.688 for female) and dysglycemia (AUC: 0.669 for male, 0.713 for female) and female’s high triglyceride level (AUC 0.712). The recognition ability of the two was equivalent. The ability of ABSI and WWI to identify MetS was weak. CONCLUSIONS: AVI is the optimal anthropometric indices to identify MetS in non-overweight/obese Chinese adults. BRI and WHtR can also be considered as discriminators, while ABSI and WWI are weak discriminators. WHtR is easy to measure. So, it is recommended as an early preliminary screening method for the MetS in non-overweight/obese people. BioMed Central 2021-01-06 /pmc/articles/PMC7788902/ /pubmed/33407674 http://dx.doi.org/10.1186/s12986-020-00536-x Text en © The Author(s) 2021 Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Wu, Lihong
Zhu, Wenhua
Qiao, Qiaohua
Huang, Lijuan
Li, Yiqi
Chen, Liying
Novel and traditional anthropometric indices for identifying metabolic syndrome in non-overweight/obese adults
title Novel and traditional anthropometric indices for identifying metabolic syndrome in non-overweight/obese adults
title_full Novel and traditional anthropometric indices for identifying metabolic syndrome in non-overweight/obese adults
title_fullStr Novel and traditional anthropometric indices for identifying metabolic syndrome in non-overweight/obese adults
title_full_unstemmed Novel and traditional anthropometric indices for identifying metabolic syndrome in non-overweight/obese adults
title_short Novel and traditional anthropometric indices for identifying metabolic syndrome in non-overweight/obese adults
title_sort novel and traditional anthropometric indices for identifying metabolic syndrome in non-overweight/obese adults
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788902/
https://www.ncbi.nlm.nih.gov/pubmed/33407674
http://dx.doi.org/10.1186/s12986-020-00536-x
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