Cargando…
Optimal Obesity- and Lipid-Related Indices for Predicting Metabolic Syndrome in Chronic Kidney Disease Patients with and without Type 2 Diabetes Mellitus in China
Existing obesity- and lipid-related indices are inconsistent with metabolic syndrome (MetS) in chronic kidney disease (CKD) patients. We compared seven indicators, including waist circumference (WC), body mass index (BMI), visceral fat area (VFA), subcutaneous fat area (SFA), visceral adiposity inde...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002364/ https://www.ncbi.nlm.nih.gov/pubmed/35405947 http://dx.doi.org/10.3390/nu14071334 |
_version_ | 1784685871390261248 |
---|---|
author | Li, Hangtian Wang, Qian Ke, Jianghua Lin, Wenwen Luo, Yayong Yao, Jin Zhang, Weiguang Zhang, Li Duan, Shuwei Dong, Zheyi Chen, Xiangmei |
author_facet | Li, Hangtian Wang, Qian Ke, Jianghua Lin, Wenwen Luo, Yayong Yao, Jin Zhang, Weiguang Zhang, Li Duan, Shuwei Dong, Zheyi Chen, Xiangmei |
author_sort | Li, Hangtian |
collection | PubMed |
description | Existing obesity- and lipid-related indices are inconsistent with metabolic syndrome (MetS) in chronic kidney disease (CKD) patients. We compared seven indicators, including waist circumference (WC), body mass index (BMI), visceral fat area (VFA), subcutaneous fat area (SFA), visceral adiposity index (VAI), Chinese VAI and lipid accumulation product (LAP), to evaluate their ability to predict MetS in CKD patients with and without Type 2 diabetes mellitus (T2DM) under various criteria. Multivariate logistic regression analysis was used to investigate the independent associations between the indices and metabolic syndrome among 547 non-dialysis CKD patients, aged ≥18 years. The predictive power of these indices was assessed using receiver operating characteristic (ROC) curve analysis. After adjusting for potential confounders, the correlation between VAI and MetS was strongest based on the optimal cut-off value of 1.51 (sensitivity 86.84%, specificity 91.18%) and 2.35 (sensitivity 83.54%, specificity 86.08%), with OR values of 40.585 (8.683–189.695) and 5.076 (1.247–20.657) for males and females with CKD and T2DM. In CKD patients without T2DM, based on the optimal cut-off values of 1.806 (sensitivity 98.11%, specificity 72.73%) and 3.11 (sensitivity 84.62%, specificity 83.82%), the OR values were 7.514 (3.757–15.027) and 3.008 (1.789–5.056) for males and females, respectively. The area under ROC curve (AUC) and Youden index of VAI were the highest among the seven indexes, indicating its superiority in predicting MetS in both male and female CKD patients, especially those with T2DM. |
format | Online Article Text |
id | pubmed-9002364 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90023642022-04-13 Optimal Obesity- and Lipid-Related Indices for Predicting Metabolic Syndrome in Chronic Kidney Disease Patients with and without Type 2 Diabetes Mellitus in China Li, Hangtian Wang, Qian Ke, Jianghua Lin, Wenwen Luo, Yayong Yao, Jin Zhang, Weiguang Zhang, Li Duan, Shuwei Dong, Zheyi Chen, Xiangmei Nutrients Article Existing obesity- and lipid-related indices are inconsistent with metabolic syndrome (MetS) in chronic kidney disease (CKD) patients. We compared seven indicators, including waist circumference (WC), body mass index (BMI), visceral fat area (VFA), subcutaneous fat area (SFA), visceral adiposity index (VAI), Chinese VAI and lipid accumulation product (LAP), to evaluate their ability to predict MetS in CKD patients with and without Type 2 diabetes mellitus (T2DM) under various criteria. Multivariate logistic regression analysis was used to investigate the independent associations between the indices and metabolic syndrome among 547 non-dialysis CKD patients, aged ≥18 years. The predictive power of these indices was assessed using receiver operating characteristic (ROC) curve analysis. After adjusting for potential confounders, the correlation between VAI and MetS was strongest based on the optimal cut-off value of 1.51 (sensitivity 86.84%, specificity 91.18%) and 2.35 (sensitivity 83.54%, specificity 86.08%), with OR values of 40.585 (8.683–189.695) and 5.076 (1.247–20.657) for males and females with CKD and T2DM. In CKD patients without T2DM, based on the optimal cut-off values of 1.806 (sensitivity 98.11%, specificity 72.73%) and 3.11 (sensitivity 84.62%, specificity 83.82%), the OR values were 7.514 (3.757–15.027) and 3.008 (1.789–5.056) for males and females, respectively. The area under ROC curve (AUC) and Youden index of VAI were the highest among the seven indexes, indicating its superiority in predicting MetS in both male and female CKD patients, especially those with T2DM. MDPI 2022-03-23 /pmc/articles/PMC9002364/ /pubmed/35405947 http://dx.doi.org/10.3390/nu14071334 Text en © 2022 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 Li, Hangtian Wang, Qian Ke, Jianghua Lin, Wenwen Luo, Yayong Yao, Jin Zhang, Weiguang Zhang, Li Duan, Shuwei Dong, Zheyi Chen, Xiangmei Optimal Obesity- and Lipid-Related Indices for Predicting Metabolic Syndrome in Chronic Kidney Disease Patients with and without Type 2 Diabetes Mellitus in China |
title | Optimal Obesity- and Lipid-Related Indices for Predicting Metabolic Syndrome in Chronic Kidney Disease Patients with and without Type 2 Diabetes Mellitus in China |
title_full | Optimal Obesity- and Lipid-Related Indices for Predicting Metabolic Syndrome in Chronic Kidney Disease Patients with and without Type 2 Diabetes Mellitus in China |
title_fullStr | Optimal Obesity- and Lipid-Related Indices for Predicting Metabolic Syndrome in Chronic Kidney Disease Patients with and without Type 2 Diabetes Mellitus in China |
title_full_unstemmed | Optimal Obesity- and Lipid-Related Indices for Predicting Metabolic Syndrome in Chronic Kidney Disease Patients with and without Type 2 Diabetes Mellitus in China |
title_short | Optimal Obesity- and Lipid-Related Indices for Predicting Metabolic Syndrome in Chronic Kidney Disease Patients with and without Type 2 Diabetes Mellitus in China |
title_sort | optimal obesity- and lipid-related indices for predicting metabolic syndrome in chronic kidney disease patients with and without type 2 diabetes mellitus in china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002364/ https://www.ncbi.nlm.nih.gov/pubmed/35405947 http://dx.doi.org/10.3390/nu14071334 |
work_keys_str_mv | AT lihangtian optimalobesityandlipidrelatedindicesforpredictingmetabolicsyndromeinchronickidneydiseasepatientswithandwithouttype2diabetesmellitusinchina AT wangqian optimalobesityandlipidrelatedindicesforpredictingmetabolicsyndromeinchronickidneydiseasepatientswithandwithouttype2diabetesmellitusinchina AT kejianghua optimalobesityandlipidrelatedindicesforpredictingmetabolicsyndromeinchronickidneydiseasepatientswithandwithouttype2diabetesmellitusinchina AT linwenwen optimalobesityandlipidrelatedindicesforpredictingmetabolicsyndromeinchronickidneydiseasepatientswithandwithouttype2diabetesmellitusinchina AT luoyayong optimalobesityandlipidrelatedindicesforpredictingmetabolicsyndromeinchronickidneydiseasepatientswithandwithouttype2diabetesmellitusinchina AT yaojin optimalobesityandlipidrelatedindicesforpredictingmetabolicsyndromeinchronickidneydiseasepatientswithandwithouttype2diabetesmellitusinchina AT zhangweiguang optimalobesityandlipidrelatedindicesforpredictingmetabolicsyndromeinchronickidneydiseasepatientswithandwithouttype2diabetesmellitusinchina AT zhangli optimalobesityandlipidrelatedindicesforpredictingmetabolicsyndromeinchronickidneydiseasepatientswithandwithouttype2diabetesmellitusinchina AT duanshuwei optimalobesityandlipidrelatedindicesforpredictingmetabolicsyndromeinchronickidneydiseasepatientswithandwithouttype2diabetesmellitusinchina AT dongzheyi optimalobesityandlipidrelatedindicesforpredictingmetabolicsyndromeinchronickidneydiseasepatientswithandwithouttype2diabetesmellitusinchina AT chenxiangmei optimalobesityandlipidrelatedindicesforpredictingmetabolicsyndromeinchronickidneydiseasepatientswithandwithouttype2diabetesmellitusinchina |