Using Cluster Analysis to Identify Metabolic Syndrome Components and Physical Fitness in Patients with Metabolic Syndrome.

IF 1.3 4区 医学 Q4 MEDICINE, RESEARCH & EXPERIMENTAL Metabolic syndrome and related disorders Pub Date : 2024-09-01 Epub Date: 2024-05-09 DOI:10.1089/met.2024.0041
Şafak Yiğit, Buket Akıncı, Büşra Ülker Ekşi, Damla Korkmaz Dayıcan, Fulya Çalıkoğlu, Yusuf Çelik, İpek Yeldan, İlhan Satman
{"title":"Using Cluster Analysis to Identify Metabolic Syndrome Components and Physical Fitness in Patients with Metabolic Syndrome.","authors":"Şafak Yiğit, Buket Akıncı, Büşra Ülker Ekşi, Damla Korkmaz Dayıcan, Fulya Çalıkoğlu, Yusuf Çelik, İpek Yeldan, İlhan Satman","doi":"10.1089/met.2024.0041","DOIUrl":null,"url":null,"abstract":"<p><p><b><i>Background:</i></b> Metabolic syndrome (MetS) comprises a cluster of cardiovascular risk factors. Physical inactivity and reduced physical fitness are associated with one or more components of MetS. However, MetS has many components, and the unclear relationship between the components and physical fitness parameters can provide a plain and straightforward understanding of the clustering method. <b><i>Aim:</i></b> To identify the relationship between physical fitness parameters, physical activity levels, and components of MetS using hierarchical cluster analysis. <b><i>Methods:</i></b> One hundred twenty-one patients (mean age = 51.4 ± 7.1/years, F:90, M:31) who were diagnosed as having MetS according to the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) criteria were included in the study. Fasting plasma glucose (FPG), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) were analyzed. Systolic and diastolic blood pressures, (SBP and DBP), were evaluated. Body composition (waist and hip circumference, (WC and HC), waist-to-hip ratio (WHR), body mass index (BMI), percent body fat, and visceral fat), upper and lower extremity muscle strength (dynamometer), and functional exercise capacity [6-minute walk test (6MWT)] were assessed as physical fitness parameters. Physical activity levels were assessed using a pedometer and number of steps (NS) was determined. <b><i>Results:</i></b> Of the patients, 45.5% were diagnosed as having MetS based on four components. The dendrogram consisted of two main clusters and four subclusters. The main cluster I composed of BMI, HC, WC, visceral fat, HDL-C, percent fat, SBP, DBP, and percent quadriceps. The main cluster II comprised FPG, TG, WHR, handgrip strength, 6MWT, and NS. <b><i>Conclusion:</i></b> MetS components clustered with different physical fitness parameters. The clusters in the dendrogram can provide substantial implications for heterogeneous MetS components and physical fitness parameters. Future studies are needed to elucidate the effectiveness of dendrogram-derived exercise programs in MetS.</p>","PeriodicalId":18405,"journal":{"name":"Metabolic syndrome and related disorders","volume":" ","pages":"558-565"},"PeriodicalIF":1.3000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metabolic syndrome and related disorders","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1089/met.2024.0041","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/9 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Metabolic syndrome (MetS) comprises a cluster of cardiovascular risk factors. Physical inactivity and reduced physical fitness are associated with one or more components of MetS. However, MetS has many components, and the unclear relationship between the components and physical fitness parameters can provide a plain and straightforward understanding of the clustering method. Aim: To identify the relationship between physical fitness parameters, physical activity levels, and components of MetS using hierarchical cluster analysis. Methods: One hundred twenty-one patients (mean age = 51.4 ± 7.1/years, F:90, M:31) who were diagnosed as having MetS according to the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) criteria were included in the study. Fasting plasma glucose (FPG), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) were analyzed. Systolic and diastolic blood pressures, (SBP and DBP), were evaluated. Body composition (waist and hip circumference, (WC and HC), waist-to-hip ratio (WHR), body mass index (BMI), percent body fat, and visceral fat), upper and lower extremity muscle strength (dynamometer), and functional exercise capacity [6-minute walk test (6MWT)] were assessed as physical fitness parameters. Physical activity levels were assessed using a pedometer and number of steps (NS) was determined. Results: Of the patients, 45.5% were diagnosed as having MetS based on four components. The dendrogram consisted of two main clusters and four subclusters. The main cluster I composed of BMI, HC, WC, visceral fat, HDL-C, percent fat, SBP, DBP, and percent quadriceps. The main cluster II comprised FPG, TG, WHR, handgrip strength, 6MWT, and NS. Conclusion: MetS components clustered with different physical fitness parameters. The clusters in the dendrogram can provide substantial implications for heterogeneous MetS components and physical fitness parameters. Future studies are needed to elucidate the effectiveness of dendrogram-derived exercise programs in MetS.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用聚类分析确定代谢综合征患者的代谢综合征成分和体能。
背景:代谢综合征(MetS代谢综合征(MetS)由一组心血管风险因素组成。缺乏运动和体能下降与 MetS 的一个或多个组成部分有关。然而,MetS 有许多组成部分,而这些组成部分与体能参数之间的关系并不明确,因此可以对聚类方法进行简单明了的理解。目的:采用分层聚类分析确定体能参数、体力活动水平和 MetS 组成部分之间的关系。方法:对 121 名患者(平均年龄为 45 岁)进行分组:研究纳入了 121 名根据美国国家胆固醇教育计划-成人治疗小组 III(NCEP-ATP III)标准被诊断为 MetS 的患者(平均年龄 = 51.4 ± 7.1/岁,女:90,男:31)。对空腹血浆葡萄糖(FPG)、高密度脂蛋白胆固醇(HDL-C)和甘油三酯(TG)进行了分析。评估了收缩压和舒张压(SBP 和 DBP)。身体成分(腰围和臀围(WC 和 HC)、腰臀比(WHR)、体重指数(BMI)、体脂百分比和内脏脂肪)、上下肢肌力(测力计)和功能锻炼能力[6 分钟步行测试(6MWT)]作为体能参数进行了评估。使用计步器评估身体活动水平,并确定步数(NS)。结果显示根据四个组成部分,45.5% 的患者被诊断为 MetS 患者。树枝图由两个主簇和四个子簇组成。主簇 I 由体重指数(BMI)、心率(HC)、腹围(WC)、内脏脂肪、高密度脂蛋白胆固醇(HDL-C)、脂肪百分比、SBP、DBP 和股四头肌百分比组成。主群 II 由 FPG、TG、WHR、手握力、6MWT 和 NS 组成。结论是MetS成分与不同的体能参数聚类。树枝图中的聚类可为异质性 MetS 成分和体能参数提供实质性意义。今后还需要进行研究,以阐明树枝图衍生的锻炼计划对 MetS 的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Metabolic syndrome and related disorders
Metabolic syndrome and related disorders MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
3.40
自引率
0.00%
发文量
74
审稿时长
6-12 weeks
期刊介绍: Metabolic Syndrome and Related Disorders is the only peer-reviewed journal focusing solely on the pathophysiology, recognition, and treatment of this major health condition. The Journal meets the imperative for comprehensive research, data, and commentary on metabolic disorder as a suspected precursor to a wide range of diseases, including type 2 diabetes, cardiovascular disease, stroke, cancer, polycystic ovary syndrome, gout, and asthma. Metabolic Syndrome and Related Disorders coverage includes: -Insulin resistance- Central obesity- Glucose intolerance- Dyslipidemia with elevated triglycerides- Low HDL-cholesterol- Microalbuminuria- Predominance of small dense LDL-cholesterol particles- Hypertension- Endothelial dysfunction- Oxidative stress- Inflammation- Related disorders of polycystic ovarian syndrome, fatty liver disease (NASH), and gout
期刊最新文献
Metabolic Syndrome and the Risk of Alzheimer's Disease: A Meta-Analysis. The Magnetic Resonance Image-Arterial Spin Labeling Characteristic of Nonketotic Hyperglycemic Hemichorea in an Elderly Type 2 Diabetic Female Patient. Truncated Albumins as Novel Surrogate Biomarkers in Diabetes Therapy: Epiphenomena and Potential Clinical Applications. A Novel Insight into Postmenopausal Hypercholesterolemia: Carnitine as a Key Player. Methylation Patterns of Diabetes and Obesity Susceptibility Genes in Gestational Diabetes Mellitus: A Cross-Sectional Analysis from Karachi, Pakistan.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1