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Meena D, Huang J, Dib M, Chirinos J, Jia M, Chauhan G, Gill D, Elliott P, Dehghan A, Tzoulaki I. Body Mass Index and Hypertension as Mediators of the Association Between Age at Menarche and Subclinical Atherosclerosis: A Sex-Specific Mendelian Randomization Analysis. J Am Heart Assoc 2024; 13:e032192. [PMID: 38979809 PMCID: PMC11292777 DOI: 10.1161/jaha.123.032192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 05/22/2024] [Indexed: 07/10/2024]
Abstract
BACKGROUND Early age at menarche (AAM) has been associated with a higher risk of carotid artery intima-media thickness (cIMT), an indicator of subclinical vascular disease, albeit the mechanisms underlying this association remain elusive. A better understanding of the relationship between AAM, modifiable cardiometabolic risk factors, and subclinical atherosclerosis may contribute to improved primary prevention and cardiovascular disease treatment. We aimed to investigate the putative causal role of AAM on cIMT, and to identify and quantify the potentially mediatory effects of cardiometabolic risk factors underlying this relationship. METHODS AND RESULTS We conducted linkage disequilibrium score regression analyses between our exposure of interest, AAM, our outcome of interest, cIMT and potential mediators of the AAM-cIMT association to gauge cross-trait genetic overlap. We considered as mediators the modifiable anthropometric risk factors body mass index (BMI), systolic blood pressure (SBP), lipid traits (total cholesterol, triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol), and glycemic traits (fasting glucose). We then leveraged the paradigm of Mendelian randomization to infer causality between AAM and cIMT, and to identify whether cardiometabolic risk factors served as potential mediators of this effect. Our analyses showed that genetically predicted AAM was inversely associated with cIMT, BMI, SBP, and triglycerides, and positively associated with high-density lipoprotein, low-density lipoprotein, and total cholesterol. We showed that the effect of genetically predicted AAM on cIMT may be partially mediated through BMI (20.1% [95% CI, 1.4% to 38.9%]) and SBP (13.5% [95% CI, 0.5%-26.6%]). Our cluster-specific Mendelian randomization revealed heterogeneous causal effect estimates of age at menarche on BMI and SBP. CONCLUSIONS We highlight supporting evidence for a potential causal association between earlier AAM and cIMT, and almost one third of the effect of AAM on cIMT may be mediated by BMI and SBP. Early intervention aimed at lowering BMI and hypertension may be beneficial in reducing the risk of developing subclinical atherosclerosis due to earlier age at menarche.
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Affiliation(s)
- Devendra Meena
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
| | - Jian Huang
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR)Singapore
- Bioinformatics Institute (BII)Agency for Science, Technology and Research (A*STAR)SingaporeSingapore
| | - Marie‐Joe Dib
- Division of Cardiovascular MedicineHospital of the University of PennsylvaniaPhiladelphiaPAUSA
| | - Julio Chirinos
- Division of Cardiovascular MedicineHospital of the University of PennsylvaniaPhiladelphiaPAUSA
| | - Manyi Jia
- Department of Metabolism Digestion and Reproduction, Section of Computational and Systems MedicineImperial College LondonLondonUnited Kingdom
| | - Ganesh Chauhan
- Department of Genetics & GenomicsRajendra Institute of Medical Sciences (RIMS)RanchiIndia
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
- British Heart Foundation Centre of Excellence, Imperial College LondonLondonUnited Kingdom
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
- British Heart Foundation Centre of Excellence, Imperial College LondonLondonUnited Kingdom
- Dementia Research Institute, Imperial College LondonLondonUnited Kingdom
- MRC Centre for Environment and Health, School of Public Health, Imperial College LondonLondonUnited Kingdom
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
- Dementia Research Institute, Imperial College LondonLondonUnited Kingdom
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, School of Public HealthImperial College LondonLondonUnited Kingdom
- British Heart Foundation Centre of Excellence, Imperial College LondonLondonUnited Kingdom
- Systems Biology, Biomedical Research Foundation Academy of AthensAthensGreece
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Liu S, Yu J, Wang L, Zhang X, Wang F, Zhu Y. Weight-adjusted waist index as a practical predictor for diabetes, cardiovascular disease, and non-accidental mortality risk. Nutr Metab Cardiovasc Dis 2024:S0939-4753(24)00238-2. [PMID: 39117486 DOI: 10.1016/j.numecd.2024.06.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 06/10/2024] [Accepted: 06/13/2024] [Indexed: 08/10/2024]
Abstract
BACKGROUND AND AIM Identifying a more suitable marker among various measures of adiposity, demonstrating strong associations and predictive ability for clinical use, remains a topic of debate. Weight-adjusted waist index (WWI) has been proposed as a novel index of adiposity, yet its exploration is limited, especially in Chinese populations. This study seeks to examine the associations between body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHTR), weight-adjusted waist index (WWI), waist circumference divided by body mass to the power of 0.333 (WC/M0.333), visceral adiposity index (VAI), lipid accumulation product (LAP), and the incidence of diabetes, cardiovascular disease, and non-accidental mortality in Chinese populations. Furthermore, our goal is to compare the respective predictive values of these measures for these health outcomes. METHODS AND RESULTS This prospective cohort study included 21,750 subjects with a 9-year follow-up period. Cox proportional hazard models were used to investigate the relationship between eight anthropometric indexes and the incidence of diabetes, cardiovascular disease, and non-accidental mortality. The predictive value of these eight indexes was compared using the area under the curve metric. Significant positive associations were found between WWI and the risk of diabetes. Using the first quartile (Q1) of WWI as the reference group, hazard ratios with 95% confidence intervals for the risk of diabetes were 1.58 (0.98-2.55) for Q2, 2.18 (1.34-3.35) for Q3, and 2.27 (1.41-3.67) for Q4. Significant associations were observed with the highest quartile of WWI for the risk of cardiovascular disease [Q2: HR 1.45 (95% CI 1.06-1.98); Q3: 1.33 (0.97-1.83); Q4: 1.55 (1.13-2.14)] and risk of non-accidental mortality [Q2: 0.94 (0.80-1.11); Q3: 1.24 (1.04-1.48); Q4: 1.44 (1.16-1.79)]. Receiver operating characteristic analysis revealed that WWI exhibited superior discrimination and accuracy in predicting cardiovascular disease and non-accidental mortality compared to other adiposity indexes (BMI, WC, WHR, WHTR, WC/M0.333, VAI, and LAP). CONCLUSION WWI exhibited the most robust and consistent association with the incidence of cardiovascular disease and non-accidental mortality. Given its simplicity and widespread use, WWI emerges as a novel and practical predictor of diabetes, cardiovascular disease, and non-accidental mortality among the eight adiposity indexes investigated in this study.
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Affiliation(s)
- Sitong Liu
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China; Department of Health Hazards Surveillance, Hangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), Hangzhou, Zhejiang, China.
| | - Jiazhou Yu
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Sha Tin, Hong Kong SAR.
| | - Lu Wang
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China; Department of Health Hazards Surveillance, Hangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), Hangzhou, Zhejiang, China.
| | - Xuhui Zhang
- Department of Health Hazards Surveillance, Hangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), Hangzhou, Zhejiang, China.
| | - Fengying Wang
- Department of Jinhua Center for Disease Control and Prevention (Jinhua Health Supervision Institution), Jinhua, Zhejiang, China.
| | - Yimin Zhu
- Department of Epidemiology and Biostatistics, and Department of Respiratory Disease, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China; Cancer Center, Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, Zhejiang, China.
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Zhang X, Wang Y, Li Y, Gui J, Mei Y, Yang X, Liu H, Guo LL, Li J, Lei Y, Li X, Sun L, Yang L, Yuan T, Wang C, Zhang D, Li J, Liu M, Hua Y, Zhang L. Optimal obesity- and lipid-related indices for predicting type 2 diabetes in middle-aged and elderly Chinese. Sci Rep 2024; 14:10901. [PMID: 38740846 DOI: 10.1038/s41598-024-61592-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 05/07/2024] [Indexed: 05/16/2024] Open
Abstract
To investigate the screening and predicting functions of obesity- and lipid-related indices for type 2 diabetes (T2D) in middle-aged and elderly Chinese, as well as the ideal predicted cut-off value. This study's data comes from the 2011 China Health and Retirement Longitudinal Study (CHARLS). A cross-sectional study design was used to investigate the relationship of T2D and 13 obesity- and lipid-related indices, including body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI), body roundness index (BRI), lipid accumulation product (LAP), conicity index (CI), Chinese visceral adiposity index (CVAI), triglyceride- glucose index (TyG index) and its correlation index (TyG-BMI, TyG-WC, TyG-WHtR). The unadjusted and adjusted correlations between 13 indices and T2D were assessed using binary logistic regression analysis. The receiver operating characteristic curve (ROC) was used to determine the usefulness of anthropometric indices for screening for T2D and determining their cut‑off value, sensitivity, specificity, and area under the curve (AUC). The study comprised 9488 people aged 45 years or above in total, of whom 4354 (45.89%) were males and 5134 (54.11%) were females. Among them were 716 male cases of T2D (16.44%) and 870 female cases of T2D (16.95%). A total of 13 obesity- and lipid-related indices were independently associated with T2D risk after adjusted for confounding factors (P < 0.05). According to ROC analysis, the TyG index was the best predictor of T2D among males (AUC = 0.780, 95% CI 0.761, 0.799) and females (AUC = 0.782, 95% CI 0.764, 0.799). The AUC values of the 13 indicators were higher than 0.5, indicating that they have predictive values for T2D in middle-aged and elderly Chinese. The 13 obesity- and lipid-related indices can predict the risk of T2D in middle‑aged and elderly Chinese. Among 13 indicators, the TyG index is the best predictor of T2D in both males and females. TyG-WC, TyG-BMI, TyG-WHtR, LAP, and CVAI all outperformed BMI, WC, and WHtR in predicting T2D.
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Affiliation(s)
- Xiaoyun Zhang
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Ying Wang
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Yuqing Li
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Jiaofeng Gui
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Yujin Mei
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Xue Yang
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Haiyang Liu
- Student Health Center, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Lei-Lei Guo
- Department of Surgical Nursing, School of Nursing, Jinzhou Medical University, No. 40, Section 3, Songpo Road, Linghe District, Jinzhou City, Liaoning Province, People's Republic of China
| | - Jinlong Li
- Department of Occupational and Environmental Health, Key Laboratory of Occupational Health and Safety for Coal Industry in Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, People's Republic of China
| | - Yunxiao Lei
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Xiaoping Li
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Lu Sun
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Liu Yang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Ting Yuan
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Congzhi Wang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Dongmei Zhang
- Department of Pediatric Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Jing Li
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Mingming Liu
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Ying Hua
- Rehabilitation Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Lin Zhang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China.
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Zhang X, Wang Y, Yang X, Li Y, Gui J, Mei Y, Liu H, Guo LL, Li J, Lei Y, Li X, Sun L, Yang L, Yuan T, Wang C, Zhang D, Li J, Liu M, Hua Y, Zhang L. Obesity and lipid indices as predictors of depressive symptoms in middle-aged and elderly Chinese: insights from a nationwide cohort study. BMC Psychiatry 2024; 24:351. [PMID: 38730360 PMCID: PMC11088055 DOI: 10.1186/s12888-024-05806-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 05/02/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Depressive symptoms are one of the most common psychiatric disorders, with a high lifetime prevalence rate among middle-aged and elderly Chinese. Obesity may be one of the risk factors for depressive symptoms, but there is currently no consensus on this view. Therefore, we investigate the relationship and predictive ability of 13 obesity- and lipid-related indices with depressive symptoms among middle-aged and elderly Chinese. METHODS The data were obtained from The China Health and Retirement Longitudinal Study (CHARLS). Our analysis includes individuals who did not have depressive symptoms at the baseline of the CHARLS Wave 2011 study and were successfully follow-up in 2013 and 2015. Finally, 3790 participants were included in the short-term (from 2011 to 2013), and 3660 participants were included in the long-term (from 2011 to 2015). The average age of participants in short-term and long-term was 58.47 years and 57.88 years. The anthropometric indicators used in this analysis included non-invasive [e.g. waist circumference (WC), body mass index (BMI), and a body mass index (ABSI)], and invasive anthropometric indicators [e.g. lipid accumulation product (LAP), triglyceride glucose index (TyG index), and its-related indices (e.g. TyG-BMI, and TyG-WC)]. Receiver operating characteristic (ROC) analysis was used to examine the predictive ability of various indicators for depressive symptoms. The association of depressive symptoms with various indicators was calculated using binary logistic regression. RESULTS The overall incidence of depressive symptoms was 20.79% in the short-term and 27.43% in the long-term. In males, WC [AUC = 0.452], LAP [AUC = 0.450], and TyG-WC [AUC = 0.451] were weak predictors of depressive symptoms during the short-term (P < 0.05). In females, BMI [AUC = 0.468], LAP [AUC = 0.468], and TyG index [AUC = 0.466] were weak predictors of depressive symptoms during the long-term (P < 0.05). However, ABSI cannot predict depressive symptoms in males and females during both periods (P > 0.05). CONCLUSION The research indicates that in the middle-aged and elderly Chinese, most obesity- and lipid-related indices have statistical significance in predicting depressive symptoms, but the accuracy of these indicators in prediction is relatively low and may not be practical predictors.
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Affiliation(s)
- Xiaoyun Zhang
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Ying Wang
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Xue Yang
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Yuqing Li
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Jiaofeng Gui
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Yujin Mei
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Haiyang Liu
- Student Health Center, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Lei-Lei Guo
- Department of Surgical Nursing, School of Nursing, Jinzhou Medical University, No.40, Section 3, Songpo Road, Linghe District, Jinzhou City, Liaoning Province, People's Republic of China
| | - Jinlong Li
- Department of Occupational and Environmental Health, Key Laboratory of Occupational Health and Safety for Coal Industry in Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, People's Republic of China
| | - Yunxiao Lei
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Xiaoping Li
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Lu Sun
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Liu Yang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Ting Yuan
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Congzhi Wang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Dongmei Zhang
- Department of Pediatric Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Jing Li
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Mingming Liu
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Ying Hua
- Rehabilitation Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Lin Zhang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China.
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Zhang X, Wang Y, Li Y, Gui J, Mei Y, Yang X, Liu H, Guo LL, Li J, Lei Y, Li X, Sun L, Yang L, Yuan T, Wang C, Zhang D, Li J, Liu M, Hua Y, Zhang L. Four-years change of BMI and waist circumference are associated with metabolic syndrome in middle-aged and elderly Chinese. Sci Rep 2024; 14:10220. [PMID: 38702424 PMCID: PMC11068757 DOI: 10.1038/s41598-024-60172-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 04/19/2024] [Indexed: 05/06/2024] Open
Abstract
The purpose of the study was to determine whether changes in body mass index (BMI) and waist circumference (WC) in middle-aged and elderly Chinese are associated with metabolic syndrome. In this cohort investigation, 3697 middle-aged and elderly people aged 45 or over were recruited from the China Health and Retirement Longitudinal Study (CHARLS). The National Cholesterol Education Program Adult Treatment Panel III (2005) defined metabolic syndrome (MetS). With Cox regression analysis, we calculated hazard ratio (HR) and 95% confidence intervals (CIs) for MetS based on BMI-WC change categories. To assess the prevalence of MetS, the changes in BMI and WC levels were classified into four quartiles based on their relative and absolute changes. In subjects whose BMI and WC decreased (HR = 0.338; 95% CIs 0.264, 0.433) as well as those whose BMI increased and their WC decreased (HR = 0.375; 95% CIs 0.228, 0.499), metabolic syndrome risk was significantly lower compared with those with increases in both BMI and WC. Regarding the absolute changes in BMI, the lowest percentile of BMI was significantly lower in both males (HR = 0.302; 95% CIs 0.204, 0.448) and females (HR = 0.486; 95% CIs 0.354, 0.667) for the risk of metabolic syndrome. Similar results were observed in the absolute changes in WC, with the lowest quantile of WC having a significant impact on MetS risk in males (HR = 0.170; 95% CIs 0.107, 0.270) and females (HR = 0.303; 95% CIs 0.217, 0.424). The risk of metabolic syndrome was significantly associated with changes in BMI and WC in middle-aged and elderly Chinese. A reduced BMI and WC are associated with lower metabolic syndrome risks in middle-aged and elderly people.
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Affiliation(s)
- Xiaoyun Zhang
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Ying Wang
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Yuqing Li
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Jiaofeng Gui
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Yujin Mei
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Xue Yang
- Department of Graduate School, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Haiyang Liu
- Student Health Center, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Lei-Lei Guo
- Department of Surgical Nursing, School of Nursing, Jinzhou Medical University, No.40, Section 3, Songpo Road, Linghe District, Jinzhou City, Liaoning Province, People's Republic of China
| | - Jinlong Li
- Department of Occupational and Environmental Health, Key Laboratory of Occupational Health and Safety for Coal Industry in Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan, Hebei Province, People's Republic of China
| | - Yunxiao Lei
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Xiaoping Li
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Lu Sun
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Liu Yang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Ting Yuan
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Congzhi Wang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Dongmei Zhang
- Department of Pediatric Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Jing Li
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Mingming Liu
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Ying Hua
- Rehabilitation Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Lin Zhang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China.
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Gui J, Li Y, Liu H, Guo LL, Li J, Lei Y, Li X, Sun L, Yang L, Yuan T, Wang C, Zhang D, Li J, Liu M, Hua Y, Zhang L. Obesity-and lipid-related indices as a risk factor of hypertension in mid-aged and elderly Chinese: a cross-sectional study. BMC Geriatr 2024; 24:77. [PMID: 38245677 PMCID: PMC10800050 DOI: 10.1186/s12877-023-04650-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Accepted: 12/30/2023] [Indexed: 01/22/2024] Open
Abstract
OBJECTIVE Hypertension refers to the persistent elevation of blood pressure above the established normal range, resulting in increased pressure exerted by blood on the walls of blood vessels during its circulation. Recent studies have identified significant associations between obesity and lipid-related indices, as well as hypertension. Nevertheless, these studies have yet to comprehensively examine the correlation between the two variables. Our objective is to identify the fat and lipid-related indices that have the strongest correlation with hypertension. METHOD There was a total of 9488 elderly and middle-aged Chinese citizens who participated in this investigation. The participants in this research were separated into distinct gender cohorts. The participants were classified into normal and hypertensive categories according to their gender, with hypertension defined as a blood pressure level of 140/90 mmHg or higher, or a history of hypertension. Through the utilization of binary logistic regression analyses and the receiver operator curve (ROC), the optimal among fourteen indicators associated with obesity and lipids were identified. RESULTS After adjusting for variables, statistical analysis showed that all 14 measures of obesity and lipid were risk factors for hypertension. The receiver operating characteristic (ROC) curve analysis reveals that the Chinese visceral adiposity index (CVAI) has the highest degree of relationship to hypertension. Simultaneously, a statistically significant association between hypertension and these 14 variables was observed in both males and females. CONCLUSION There was a significant independent association between various parameters related to obesity and lipid-related index and the presence of hypertension, indicating that these factors can be considered risk factors for hypertension. CVAI and WHtR (waist height ratio) can be used to screen the high-risk groups of hypertensions in middle-aged and elderly people in China, and then take individualized health care measures to reduce the harm of hypertension.
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Affiliation(s)
- Jiaofeng Gui
- Department of Graduate School, Wannan Medical College, Wuhu, Anhui, China
| | - Yuqing Li
- Department of Graduate School, Wannan Medical College, Wuhu, Anhui, China
| | - Haiyang Liu
- Student Health Center, Wannan Medical College, Wuhu, Anhui, China
| | - Lei-Lei Guo
- Department of Surgical Nursing, School of Nursing, Jinzhou Medical University, Jinzhou, Liaoning, China
| | - Jinlong Li
- Department of Occupational and Environmental Health, Key Laboratory of Occupational Health and Safety for Coal Industry in Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan, Hebei, China
| | - Yunxiao Lei
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Xiaoping Li
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Lu Sun
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Liu Yang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Ting Yuan
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Congzhi Wang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Dongmei Zhang
- Department of Pediatric Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Jing Li
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Mingming Liu
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Ying Hua
- Rehabilitation Nursing, School of Nursing, Wanna Medical College, Wuhu, Anhui, China
| | - Lin Zhang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China.
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Yu Y, Wang Y, Xu L, Li W, Wang Y. Combined obesity- and lipid-related indices are associated with hypogonadism in Chinese male patients with type 2 diabetes: a cross-sectional study. Front Endocrinol (Lausanne) 2024; 14:1319582. [PMID: 38260153 PMCID: PMC10801025 DOI: 10.3389/fendo.2023.1319582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 12/15/2023] [Indexed: 01/24/2024] Open
Abstract
Background There is insufficient attention to hypogonadism in Chinese males with type 2 diabetes mellitus (T2DM). We evaluated the relationship between Combined obesity- and lipid-related indices [Visceral Adiposity Index (VAI), Chinese Visceral Adiposity Index (CVAI), Triglyceride Glucose Index (TyG) and Lipid Accumulation Product (LAP)] with total testosterone (TT) and analyzed the predictive capability of the respective cut-off values. Methods We recruited 958 hospitalized male patients with T2DM at the Affiliated Hospital of Qingdao University, collected baseline data and four calculated indices, and obtained their dominance ratio (OR) and corresponding 95% confidence intervals (CI) with TT by multivariate logistic regression. Receiver operating characteristic (ROC) curves were then used to determine cutoff values in predicting hypogonadism (TT< 12 nmol/L), and we also analyzed the combinations between the different indices. Results VAI, CVAI, TyG, and LAP all have satisfactory predictive capabilities. The test capability (sensitivity and specificity) of all four indices was better or not worse than that of body mass index (BMI), homeostasis model assessment of insulin resistance (HOMA-IR) and waist circumference (WC). All four indices were effective predictors of hypogonadism at their respective cutoff values (VAI ≥ 2.284, CVAI ≥ 145.779, TyG ≥ 4.308, and LAP ≥ 59.850). Of these, LAP had the largest area under the curve (AUC, AUC = 0.852, Std. Error = 0.014, 95% CI = 0.818-0.873). However, the predictive capability of the combined indices was not significantly improved over the individual indices. Conclusions VAI, CVAI, TyG, and LAP are sensitive indices for predicting hypogonadism in Chinese male patients with T2DM. Considering the need for concise and accurate indices in clinical practice, we suggest LAP as a commonly used index.
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Affiliation(s)
| | | | | | | | - Yangang Wang
- Department of Endocrinology, the Affiliated Hospital of Qingdao University, Qingdao, China
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Li K, Yin J, Qin Z, Ma B, He R, Zhuoma D, Wang Z, Liu Q, Zhao X. Age at menarche and metabolic dysfunction-associated fatty liver disease: Evidence from a large population-based epidemiological study in Southwest China. Prev Med 2023; 177:107776. [PMID: 37951543 DOI: 10.1016/j.ypmed.2023.107776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 10/29/2023] [Accepted: 11/08/2023] [Indexed: 11/14/2023]
Abstract
BACKGROUND The relationship between age at menarche and metabolic dysfunction-associated fatty liver disease remains largely not clear. The objective of this study was to examine the association between age at menarche (AAM) and metabolic dysfunction-associated fatty liver disease (MAFLD) in Chinese women and whether any observed associations were mediated by early adulthood adiposity. METHODS The cross-sectional study included 46,873 Chinese women, aged 30-79 from baseline data of the China Multi-Ethnic Cohort study. Logistic regression models were used to evaluate the association between AAM and MAFLD. Mediation analysis was adopted to examine whether early adulthood adiposity (around 25 years) mediated the association between AAM and MAFLD. RESULTS AAM was linearly and inversely associated with the risk of MAFLD (P for nonlinearity =0.743). In a multivariable-adjusted model, the odds ratios and 95% confidence interval (ORs (95% CI)) for MAFLD comparing menarche at <12, 12, 13, 15, 16, 17, ≥18 years to menarche at 14 years were 1.290 (1.082-1.537), 1.172 (1.068-1.285), 1.042 (0.960-1.131), 0.937 (0.861-1.020), 0.911(0.835-0.994), 0.868 (0.786-0.959), and 0.738 (0.670-0.814), respectively (P for trend <0.001). The 6.4% increased MAFLD risk was associated with each preceding year in AAM. The association between AAM and MAFLD was modified by age, ethnicity, and menopause. Early adulthood adiposity partially mediated this association. CONCLUSION The findings of this study suggest that obesity prevention strategies are needed from young adulthood in women who undergo early menarche to reduce the risk of MAFLD.
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Affiliation(s)
- Kehan Li
- Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jianzhong Yin
- Department of Nutrition and Food Hygiene, School of Public Health, Kunming Medical University, Kunming, Yunan, China; Baoshan College of Traditional Chinese Medicine, Baoshan, Yunan, China
| | - Zixiu Qin
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou, China
| | - Bangjing Ma
- Qingbaijiang District Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Ruifeng He
- Tibet Center for Disease Control and Prevention, Lhasa, Tibet, China
| | - Duoji Zhuoma
- School of Medicine, Tibet University, Lhasa, Tibet, China
| | - Zihao Wang
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Qiaolan Liu
- Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Xing Zhao
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
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Wang C, Wang J, Wan R, Yuan T, Yang L, Zhang D, Li X, Liu H, Zhang L. Separate and combined effects of famine exposure and menarche age on metabolic syndrome among the elderly: a cross-sectional study in China. BMC Womens Health 2023; 23:600. [PMID: 37964223 PMCID: PMC10648701 DOI: 10.1186/s12905-023-02737-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 10/27/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND Epidemiological studies have revealed multiple risk factors for metabolic syndrome. However, there are no consistent findings on the association between famine exposure, age at menarche, and the prevalence of metabolic syndrome. This cross-sectional study aimed to reveal the individual and combined effects of famine exposure and age at menarche on the prevalence of metabolic syndrome among elderly women. METHODS Four thousand seven hundred seventy participants between 60 and 93 years of age were selected from the China Health and Retirement Longitudinal Study. Statistical differences between the baseline characteristics of famine exposure, age at menarche, and metabolic syndrome were evaluated using the t-test, F-test, and Chi-square test. Three multivariable-adjusted logistic regression models were used to test the association between famine exposure, age of menarche, and the odds ratio of metabolic syndrome. RESULTS Two thousand one hundred ninety-eight (46.08%) participants had metabolic syndrome, while 2572 (53.92%) participants did not. Furthermore, 3068 (64.32%) women reported onset of menarche under 15 years of age, while 1702 (35.68%) women reported onset of menarche above 16 years of age. Regarding the separate association of famine exposure and age of menarche with metabolic syndrome, in model three, the adolescence/adulthood famine exposure group vs. no famine exposure group odds ratio was 2.45 (95% CI 2.02, 2.97), and the older than 16 years vs. younger than 15 years group odds ratio was 1.23 (95% CI 1.09, 1.39), which was the highest odds ratio among the three models. Regarding the combined association of famine exposure and age of menarche with metabolic syndrome, in model three, among the age of menarche ≤ 15 years group, the adolescence/adulthood famine exposure vs. no famine exposure group odds ratio was 2.45 (95% CI: 1.91, 3.14); among the menarche age ≥ 16 years group, the adolescence/adulthood famine exposure stages vs. exposed group odds ratio was 3.27 (95% CI: 2.44, 4.38), which was the highest odds ratio among the three models. CONCLUSION These findings suggested that famine exposure and age at menarche, either separately or in combination, were positively associated with the prevalence of metabolic syndrome among older women.
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Affiliation(s)
- Congzhi Wang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, An Hui Province, Wuhu City, 241000, P.R, China
| | - Jiazhi Wang
- Sports Institute, Chi Zhou College, Education Park, Chi Zhou City, An Hui Province, People's Republic of China
| | - Rui Wan
- Business School, Yunnan University of Finance and Economics, 237 Longquan Road, Kunming City, Yun Nan Province, People's Republic of China
| | - Ting Yuan
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Liu Yang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, An Hui Province, Wuhu City, 241000, P.R, China
| | - Dongmei Zhang
- Department of Pediatric Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Xiaoping Li
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, 22 Wenchang West Road, Higher Education Park, Wuhu City, An Hui Province, People's Republic of China
| | - Haiyang Liu
- Student Health Center, Wannan Medical College, 22 Wenchang West Road, Higher Education ParkAn Hui Province, Wuhu City, People's Republic of China
| | - Lin Zhang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, An Hui Province, Wuhu City, 241000, P.R, China.
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Gui J, Li Y, Liu H, Guo LL, Li J, Lei Y, Li X, Sun L, Yang L, Yuan T, Wang C, Zhang D, Wei H, Li J, Liu M, Hua Y, Zhang L. Obesity- and lipid-related indices as a predictor of obesity metabolic syndrome in a national cohort study. Front Public Health 2023; 11:1073824. [PMID: 36875382 PMCID: PMC9980350 DOI: 10.3389/fpubh.2023.1073824] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 01/16/2023] [Indexed: 02/18/2023] Open
Abstract
Objective Metabolic syndrome is a common condition among middle-aged and elderly people. Recent studies have reported the association between obesity- and lipid-related indices and metabolic syndrome, but whether those conditions could predict metabolic syndrome is still inconsistent in a few longitudinal studies. In our study, we aimed to predict metabolic syndrome by obesity- and lipid-related indices in middle-aged and elderly Chinese adults. Method A national cohort study that consisted of 3,640 adults (≥45 years) was conducted. A total of 13 obesity- and lipid-related indices, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), conicity index (CI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), and triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-WC, and TyG-WHtR), were recorded. Metabolic syndrome (MetS) was defined based on the criteria of the National Cholesterol Education Program Adult Treatment Panel III (2005). Participants were categorized into two groups according to the different sex. Binary logistic regression analyses were used to evaluate the associations between the 13 obesity- and lipid-related indices and MetS. Receiver operating characteristic (ROC) curve studies were used to identify the best predictor of MetS. Results A total of 13 obesity- and lipid-related indices were independently associated with MetS risk, even after adjustment for age, sex, educational status, marital status, current residence, history of drinking, history of smoking, taking activities, having regular exercises, and chronic diseases. The ROC analysis revealed that the 12 obesity- and lipid-related indices included in the study were able to discriminate MetS [area under the ROC curves (AUC > 0.6, P < 0.05)] and ABSI was not able to discriminate MetS [area under the ROC curves (AUC < 0.6, P > 0.05)]. The AUC of TyG-BMI was the highest in men, and that of CVAI was the highest in women. The cutoff values for men and women were 187.919 and 86.785, respectively. The AUCs of TyG-BMI, CVAI, TyG-WC, LAP, TyG-WHtR, BMI, WC, WHtR, BRI, VAI, TyG index, CI, and ABSI were 0.755, 0.752, 0.749, 0.745, 0.735, 0.732, 0.730, 0.710, 0.710, 0.674, 0.646, 0.622, and 0.537 for men, respectively. The AUCs of CVAI, LAP, TyG-WC, TyG-WHtR, TyG-BMI, WC, WHtR, BRI, BMI, VAI, TyG-index, CI, and ABSI were 0.687, 0.674, 0.674, 0.663, 0.656, 0.654, 0.645, 0.645, 0.638, 0.632, 0.607, 0.596, and 0.543 for women, respectively. The AUC value for WHtR was equal to that for BRI in predicting MetS. The AUC value for LAP was equal to that for TyG-WC in predicting MetS for women. Conclusion Among middle-aged and older adults, all obesity- and lipid-related indices, except ABSI, were able to predict MetS. In addition, in men, TyG-BMI is the best indicator to indicate MetS, and in women, CVAI is considered the best hand to indicate MetS. At the same time, TyG-BMI, TyG-WC, and TyG-WHtR performed better than BMI, WC, and WHtR in predicting MetS in both men and women. Therefore, the lipid-related index outperforms the obesity-related index in predicting MetS. In addition to CVAI, LAP showed a good predictive correlation, even more closely than lipid-related factors in predicting MetS in women. It is worth noting that ABSI performed poorly, was not statistically significant in either men or women, and was not predictive of MetS.
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Affiliation(s)
- Jiaofeng Gui
- Department of Graduate School, Wannan Medical College, Wuhu, Anhui, China
| | - Yuqing Li
- Department of Graduate School, Wannan Medical College, Wuhu, Anhui, China
| | - Haiyang Liu
- Student Health Center, Wannan Medical College, Wuhu, Anhui, China
| | - Lei-lei Guo
- Department of Surgical Nursing, School of Nursing, Jinzhou Medical University, Jinzhou, Liaoning, China
| | - Jinlong Li
- Department of Occupational and Environmental Health, Key Laboratory of Occupational Health and Safety for Coal Industry in Hebei Province, School of Public Health, North China University of Science and Technology, Tangshan, Hebei, China
| | - Yunxiao Lei
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Xiaoping Li
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Lu Sun
- Department of Emergency and Critical Care Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Liu Yang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Ting Yuan
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Congzhi Wang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Dongmei Zhang
- Department of Pediatric Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Huanhuan Wei
- Obstetrics and Gynecology Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Jing Li
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Mingming Liu
- Department of Surgical Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
| | - Ying Hua
- Rehabilitation Nursing, School of Nursing, Wanna Medical College, Wuhu, Anhui, China
| | - Lin Zhang
- Department of Internal Medicine Nursing, School of Nursing, Wannan Medical College, Wuhu, Anhui, China
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