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Predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly Chinese: a population-based cross-sectional study

OBJECTIVE: To predict the optimal cut-off values for screening and predicting metabolic syndrome(MetS) in a middle-aged and elderly Chinese population using 13 obesity and lipid-related indicators, and to identify the most suitable predictors. METHODS: The data for this cross-sectional investigation...

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Autores principales: Li, Yuqing, Gui, Jiaofeng, Liu, Haiyang, Guo, Lei-lei, Li, Jinlong, Lei, Yunxiao, Li, Xiaoping, Sun, Lu, Yang, Liu, Yuan, Ting, Wang, Congzhi, Zhang, Dongmei, Wei, Huanhuan, Li, Jing, Liu, Mingming, Hua, Ying, Zhang, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10419183/
https://www.ncbi.nlm.nih.gov/pubmed/37576971
http://dx.doi.org/10.3389/fendo.2023.1201132
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author Li, Yuqing
Gui, Jiaofeng
Liu, Haiyang
Guo, Lei-lei
Li, Jinlong
Lei, Yunxiao
Li, Xiaoping
Sun, Lu
Yang, Liu
Yuan, Ting
Wang, Congzhi
Zhang, Dongmei
Wei, Huanhuan
Li, Jing
Liu, Mingming
Hua, Ying
Zhang, Lin
author_facet Li, Yuqing
Gui, Jiaofeng
Liu, Haiyang
Guo, Lei-lei
Li, Jinlong
Lei, Yunxiao
Li, Xiaoping
Sun, Lu
Yang, Liu
Yuan, Ting
Wang, Congzhi
Zhang, Dongmei
Wei, Huanhuan
Li, Jing
Liu, Mingming
Hua, Ying
Zhang, Lin
author_sort Li, Yuqing
collection PubMed
description OBJECTIVE: To predict the optimal cut-off values for screening and predicting metabolic syndrome(MetS) in a middle-aged and elderly Chinese population using 13 obesity and lipid-related indicators, and to identify the most suitable predictors. METHODS: The data for this cross-sectional investigation came from the China Health and Retirement Longitudinal Study (CHARLS), including 9457 middle-aged and elderly people aged 45-98 years old. We examined 13 indicators, including waist circumference (WC), body mass index (BMI), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product index (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride-glucose index (TyG-index) and their combined indices (TyG-BMI, TyG-WC, TyG-WHtR). The receiver operating characteristic curve (ROC) was used to determine the usefulness of indicators for screening for MetS in the elderly and to determine their cut-off values, sensitivity, specificity, and area under the curve (AUC). Association analysis of 13 obesity-related indicators with MetS was performed using binary logistic regression analysis. RESULTS: A total of 9457 middle-aged and elderly Chinese were included in this study, and the overall prevalence of the study population was 41.87% according to the diagnostic criteria of NCEP ATP III. According to age and gender, the percentage of males diagnosed with MetS was 30.67% (45-54 years old: 30.95%, 55-64 years old: 41.02%, 65-74 years old: 21.19%, ≥ 75 years old: 6.84%). The percentage of females diagnosed with MetS was 51.38% (45-54 years old: 31.95%, 55-64 years old: 39.52%, 65-74 years old: 20.43%, ≥ 75 years old: 8.10%). The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS. ABSI had a poor prediction ability. CONCLUSIONS: Among the middle-aged and elderly population in China, after adjusting for confounding factors, all the indicators except ABSI had good predictive power. The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS.
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spelling pubmed-104191832023-08-12 Predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly Chinese: a population-based cross-sectional study Li, Yuqing Gui, Jiaofeng Liu, Haiyang Guo, Lei-lei Li, Jinlong Lei, Yunxiao Li, Xiaoping Sun, Lu Yang, Liu Yuan, Ting Wang, Congzhi Zhang, Dongmei Wei, Huanhuan Li, Jing Liu, Mingming Hua, Ying Zhang, Lin Front Endocrinol (Lausanne) Endocrinology OBJECTIVE: To predict the optimal cut-off values for screening and predicting metabolic syndrome(MetS) in a middle-aged and elderly Chinese population using 13 obesity and lipid-related indicators, and to identify the most suitable predictors. METHODS: The data for this cross-sectional investigation came from the China Health and Retirement Longitudinal Study (CHARLS), including 9457 middle-aged and elderly people aged 45-98 years old. We examined 13 indicators, including waist circumference (WC), body mass index (BMI), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product index (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride-glucose index (TyG-index) and their combined indices (TyG-BMI, TyG-WC, TyG-WHtR). The receiver operating characteristic curve (ROC) was used to determine the usefulness of indicators for screening for MetS in the elderly and to determine their cut-off values, sensitivity, specificity, and area under the curve (AUC). Association analysis of 13 obesity-related indicators with MetS was performed using binary logistic regression analysis. RESULTS: A total of 9457 middle-aged and elderly Chinese were included in this study, and the overall prevalence of the study population was 41.87% according to the diagnostic criteria of NCEP ATP III. According to age and gender, the percentage of males diagnosed with MetS was 30.67% (45-54 years old: 30.95%, 55-64 years old: 41.02%, 65-74 years old: 21.19%, ≥ 75 years old: 6.84%). The percentage of females diagnosed with MetS was 51.38% (45-54 years old: 31.95%, 55-64 years old: 39.52%, 65-74 years old: 20.43%, ≥ 75 years old: 8.10%). The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS. ABSI had a poor prediction ability. CONCLUSIONS: Among the middle-aged and elderly population in China, after adjusting for confounding factors, all the indicators except ABSI had good predictive power. The predictive power of Tyg-related parameters was more prominent in both sexes. In addition, LAP and CVAI are also good at predicting MetS. Frontiers Media S.A. 2023-07-28 /pmc/articles/PMC10419183/ /pubmed/37576971 http://dx.doi.org/10.3389/fendo.2023.1201132 Text en Copyright © 2023 Li, Gui, Liu, Guo, Li, Lei, Li, Sun, Yang, Yuan, Wang, Zhang, Wei, Li, Liu, Hua and Zhang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Endocrinology
Li, Yuqing
Gui, Jiaofeng
Liu, Haiyang
Guo, Lei-lei
Li, Jinlong
Lei, Yunxiao
Li, Xiaoping
Sun, Lu
Yang, Liu
Yuan, Ting
Wang, Congzhi
Zhang, Dongmei
Wei, Huanhuan
Li, Jing
Liu, Mingming
Hua, Ying
Zhang, Lin
Predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly Chinese: a population-based cross-sectional study
title Predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly Chinese: a population-based cross-sectional study
title_full Predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly Chinese: a population-based cross-sectional study
title_fullStr Predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly Chinese: a population-based cross-sectional study
title_full_unstemmed Predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly Chinese: a population-based cross-sectional study
title_short Predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly Chinese: a population-based cross-sectional study
title_sort predicting metabolic syndrome by obesity- and lipid-related indices in mid-aged and elderly chinese: a population-based cross-sectional study
topic Endocrinology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10419183/
https://www.ncbi.nlm.nih.gov/pubmed/37576971
http://dx.doi.org/10.3389/fendo.2023.1201132
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