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Enhanced Predictive Value of Lipid Accumulation Product for Identifying Metabolic Syndrome in the General Population of China
The purpose of this research was to evaluate the lipid accumulation product (LAP)’s accuracy and predictive value for identifying metabolic syndrome (MS) in the general Chinese population compared with other obesity indicators. Baseline survey information from a population-based cohort study carried...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10383986/ https://www.ncbi.nlm.nih.gov/pubmed/37513586 http://dx.doi.org/10.3390/nu15143168 |
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author | Shao, Qi Li, Jing Wu, Yiling Liu, Xing Wang, Na Jiang, Yonggen Zhao, Qi Zhao, Genming |
author_facet | Shao, Qi Li, Jing Wu, Yiling Liu, Xing Wang, Na Jiang, Yonggen Zhao, Qi Zhao, Genming |
author_sort | Shao, Qi |
collection | PubMed |
description | The purpose of this research was to evaluate the lipid accumulation product (LAP)’s accuracy and predictive value for identifying metabolic syndrome (MS) in the general Chinese population compared with other obesity indicators. Baseline survey information from a population-based cohort study carried out in Shanghai’s Songjiang District was used in this research. Odds ratios (OR) and a 95% confidence interval (CI) were obtained by logistic regression. The ability of each variable to detect MS was assessed using the receiver operating characteristic curve (ROC). The optimum cut-off point for each indicator was selected using Youden’s index. The survey involved 35,446 participants in total. In both genders, the prevalence of MS rose as the LAP increased (p < 0.001). The LAP’s AUC was 0.901 (95%CI: 0.895–0.906) in males and 0.898 (95%CI: 0.893–0.902) in females, making it substantially more predictive of MS than other variables (BMI, WC, WHR, WHtR). The optimal cutoff point of the LAP for men and women was 36.04 (Se: 81.91%, Sp: 81.06%) and 34.95 (Se: 80.93%, Sp: 83.04%). The Youden index of the LAP was 0.64 for both sexes. Our findings imply that the LAP, compared to other obesity markers in China, is a more accurate predictor of MS. |
format | Online Article Text |
id | pubmed-10383986 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103839862023-07-30 Enhanced Predictive Value of Lipid Accumulation Product for Identifying Metabolic Syndrome in the General Population of China Shao, Qi Li, Jing Wu, Yiling Liu, Xing Wang, Na Jiang, Yonggen Zhao, Qi Zhao, Genming Nutrients Article The purpose of this research was to evaluate the lipid accumulation product (LAP)’s accuracy and predictive value for identifying metabolic syndrome (MS) in the general Chinese population compared with other obesity indicators. Baseline survey information from a population-based cohort study carried out in Shanghai’s Songjiang District was used in this research. Odds ratios (OR) and a 95% confidence interval (CI) were obtained by logistic regression. The ability of each variable to detect MS was assessed using the receiver operating characteristic curve (ROC). The optimum cut-off point for each indicator was selected using Youden’s index. The survey involved 35,446 participants in total. In both genders, the prevalence of MS rose as the LAP increased (p < 0.001). The LAP’s AUC was 0.901 (95%CI: 0.895–0.906) in males and 0.898 (95%CI: 0.893–0.902) in females, making it substantially more predictive of MS than other variables (BMI, WC, WHR, WHtR). The optimal cutoff point of the LAP for men and women was 36.04 (Se: 81.91%, Sp: 81.06%) and 34.95 (Se: 80.93%, Sp: 83.04%). The Youden index of the LAP was 0.64 for both sexes. Our findings imply that the LAP, compared to other obesity markers in China, is a more accurate predictor of MS. MDPI 2023-07-17 /pmc/articles/PMC10383986/ /pubmed/37513586 http://dx.doi.org/10.3390/nu15143168 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Shao, Qi Li, Jing Wu, Yiling Liu, Xing Wang, Na Jiang, Yonggen Zhao, Qi Zhao, Genming Enhanced Predictive Value of Lipid Accumulation Product for Identifying Metabolic Syndrome in the General Population of China |
title | Enhanced Predictive Value of Lipid Accumulation Product for Identifying Metabolic Syndrome in the General Population of China |
title_full | Enhanced Predictive Value of Lipid Accumulation Product for Identifying Metabolic Syndrome in the General Population of China |
title_fullStr | Enhanced Predictive Value of Lipid Accumulation Product for Identifying Metabolic Syndrome in the General Population of China |
title_full_unstemmed | Enhanced Predictive Value of Lipid Accumulation Product for Identifying Metabolic Syndrome in the General Population of China |
title_short | Enhanced Predictive Value of Lipid Accumulation Product for Identifying Metabolic Syndrome in the General Population of China |
title_sort | enhanced predictive value of lipid accumulation product for identifying metabolic syndrome in the general population of china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10383986/ https://www.ncbi.nlm.nih.gov/pubmed/37513586 http://dx.doi.org/10.3390/nu15143168 |
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