Literature DB >> 20211506

Latent class analysis of the metabolic syndrome.

Edward J Boyko1, Rebecca A Doheny, Marguerite J McNeely, Steven E Kahn, Donna L Leonetti, Wilfred Y Fujimoto.   

Abstract

Attempts to explain the associations among metabolic syndrome (MetS) features using factor analysis to identify unobserved potential causes have resulted in inconsistent findings. We examined whether an unobserved categorical factor explains the associations among MetS features using latent class analysis. A cross-sectional analysis of 499 non-diabetic Japanese-Americans who underwent measurements of fasting blood, waist circumference (WC) and CT-measured intra-abdominal fat (IAF) area was conducted. MetS components were defined by IDF criteria. IAF and fasting serum insulin (FI) were dichotomized at the 75(th) percentile. Latent two- and three-class models were fit that included hypertension, dyslipidemia, hyperglycemia, and either WC, IAF, or FI for a total of six models. A three-class latent model fit the data well, while a two-class model did not. In the three-class model, one latent class was strongly associated with all MetS components, while another was associated with hyperglycemia and hypertension only. IAF was associated with only one latent class. Latent class analysis supports the presence of an unobserved factor linked to the co-occurrence of MetS features. One class of this factor was associated with hypertension and hyperglycemia but not central adiposity or FI, suggesting another pathway for observed MetS features.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20211506      PMCID: PMC2893282          DOI: 10.1016/j.diabres.2010.02.013

Source DB:  PubMed          Journal:  Diabetes Res Clin Pract        ISSN: 0168-8227            Impact factor:   5.602


  23 in total

1.  Latent class model diagnosis.

Authors:  E S Garrett; S L Zeger
Journal:  Biometrics       Date:  2000-12       Impact factor: 2.571

2.  (Mis)use of factor analysis in the study of insulin resistance syndrome.

Authors:  Debbie A Lawlor; Shah Ebrahim; Margaret May; George Davey Smith
Journal:  Am J Epidemiol       Date:  2004-06-01       Impact factor: 4.897

3.  Visceral adiposity and risk of type 2 diabetes: a prospective study among Japanese Americans.

Authors:  E J Boyko; W Y Fujimoto; D L Leonetti; L Newell-Morris
Journal:  Diabetes Care       Date:  2000-04       Impact factor: 19.112

Review 4.  The deadly quartet. Upper-body obesity, glucose intolerance, hypertriglyceridemia, and hypertension.

Authors:  N M Kaplan
Journal:  Arch Intern Med       Date:  1989-07

5.  Prevalence of diabetes mellitus and impaired glucose tolerance among second-generation Japanese-American men.

Authors:  W Y Fujimoto; D L Leonetti; J L Kinyoun; L Newell-Morris; W P Shuman; W C Stolov; P W Wahl
Journal:  Diabetes       Date:  1987-06       Impact factor: 9.461

6.  How good a marker is insulin level for insulin resistance?

Authors:  M Laakso
Journal:  Am J Epidemiol       Date:  1993-05-01       Impact factor: 4.897

7.  Are metabolic risk factors one unified syndrome? Modeling the structure of the metabolic syndrome X.

Authors:  Biing-Jiun Shen; John F Todaro; Raymond Niaura; Jeanne M McCaffery; Jianping Zhang; Avron Spiro; Kenneth D Ward
Journal:  Am J Epidemiol       Date:  2003-04-15       Impact factor: 4.897

8.  Comparison of waist circumference with body mass index for predicting abdominal adipose tissue.

Authors:  Rie Oka; Katsuyuki Miura; Masaru Sakurai; Koshi Nakamura; Kunimasa Yagi; Susumu Miyamoto; Tadashi Moriuchi; Hiroshi Mabuchi; Masakazu Yamagishi; Yoshiyu Takeda; Senshu Hifumi; Akihiro Inazu; Atsushi Nohara; Masa-aki Kawashiri; Junji Kobayashi
Journal:  Diabetes Res Clin Pract       Date:  2008-11-18       Impact factor: 5.602

9.  The central roles of obesity-associated dyslipidaemia, endothelial activation and cytokines in the Metabolic Syndrome--an analysis by structural equation modelling.

Authors:  J C N Chan; J C K Cheung; C D A Stehouwer; J J Emeis; P C Y Tong; G T C Ko; J S Yudkin
Journal:  Int J Obes Relat Metab Disord       Date:  2002-07

10.  Abnormal body fat distribution detected by computed tomography in diabetic men.

Authors:  W P Shuman; L L Morris; D L Leonetti; P W Wahl; V M Moceri; A A Moss; W Y Fujimoto
Journal:  Invest Radiol       Date:  1986-06       Impact factor: 6.016

View more
  9 in total

Review 1.  Genetic determinants of cardiometabolic risk: a proposed model for phenotype association and interaction.

Authors:  Piers R Blackett; Dharambir K Sanghera
Journal:  J Clin Lipidol       Date:  2012-04-22       Impact factor: 4.766

2.  Depression, Metabolic Syndrome, and Locus of Control in Arab Americans Living in the DC Metropolitan Area: A Structural Equation Model.

Authors:  Nawar M Shara; Alexander Zeymo; Zeid Abudiab; Jason G Umans; Soleman Abu-Bader; Asqual Getaneh; Barbara V Howard
Journal:  J Immigr Minor Health       Date:  2018-08

3.  Clustering and combining pattern of metabolic syndrome components among Iranian population with latent class analysis.

Authors:  Abbas Abbasi-Ghahramanloo; Sepideh Soltani; Ali Gholami; Mohammadreza Erfani; Somayeh Yosaee
Journal:  Med J Islam Repub Iran       Date:  2016-11-22

4.  Apolipoprotein B Levels Predict Future Development of Hypertension Independent of Visceral Adiposity and Insulin Sensitivity.

Authors:  Seung Jin Han; Wilfred Y Fujimoto; Steven E Kahn; Donna L Leonetti; Edward J Boyko
Journal:  Endocrinol Metab (Seoul)       Date:  2020-06-24

5.  Application of Latent Class Analysis to Identify Metabolic Syndrome Components Patterns in adults: Tehran Lipid and Glucose study.

Authors:  Noushin Sadat Ahanchi; Farzad Hadaegh; Abbas Alipour; Arash Ghanbarian; Fereidoun Azizi; Davood Khalili
Journal:  Sci Rep       Date:  2019-02-07       Impact factor: 4.379

6.  Subgrouping of Iranian children and adolescents based on cardiometabolic risk factors using latent class analysis: The CASPIAN-V study.

Authors:  Abbas Abbasi-Ghahramanloo; Ramin Heshmat; Amir-Masood Rafiemanzelat; Kimia Ghaderi; Mohammad Esmaeil Motlagh; Zeinab Ahadi; Gita Shafiee; Armita Mahdavi-Gorabi; Mostafa Qorbani; Roya Kelishadi
Journal:  Caspian J Intern Med       Date:  2020

7.  The neighbourhood environment and profiles of the metabolic syndrome.

Authors:  Anthony Barnett; Ester Cerin; Erika Martino; Luke D Knibbs; Jonathan E Shaw; David W Dunstan; Dianna J Magliano; David Donaire-Gonzalez
Journal:  Environ Health       Date:  2022-09-03       Impact factor: 7.123

8.  Multigroup latent class model of musculoskeletal pain combinations in children/adolescents: identifying high-risk groups by gender and age.

Authors:  Iman Dianat; Arezou Alipour; Mohammad Asghari Jafarabadi
Journal:  J Headache Pain       Date:  2018-07-13       Impact factor: 7.277

9.  Comparison of the accuracy of three diagnostic criteria and estimating the prevalence of metabolic syndrome: A latent class analysis.

Authors:  Hossein Ebrahimi; Mohammad Hassan Emamian; Ahmad Khosravi; Hassan Hashemi; Akbar Fotouhi
Journal:  J Res Med Sci       Date:  2019-12-23       Impact factor: 1.852

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.