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Factor analysis for the clustering of cardiometabolic risk factors and sedentary behavior, a cross-sectional study

BACKGROUND: Few studies have reported on the clustering pattern of CVD risk factors, including sedentary behavior, systemic inflammation, and cadiometabolic components in the general population. OBJECTIVE: We aimed to explore the clustering pattern of CVD risk factors using exploratory factor analys...

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Autores principales: Tsai, Tsung-Ying, Hsu, Pai-Feng, Lin, Chung-Chi, Wang, Yuan-Jen, Ding, Yaw-Zon, Liou, Teh-Ling, Wang, Ying-Wen, Huang, Shao-Sung, Chan, Wan-Leong, Lin, Shing-Jong, Chen, Jaw-Wen, Leu, Hsin-Bang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668610/
https://www.ncbi.nlm.nih.gov/pubmed/33196674
http://dx.doi.org/10.1371/journal.pone.0242365
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author Tsai, Tsung-Ying
Hsu, Pai-Feng
Lin, Chung-Chi
Wang, Yuan-Jen
Ding, Yaw-Zon
Liou, Teh-Ling
Wang, Ying-Wen
Huang, Shao-Sung
Chan, Wan-Leong
Lin, Shing-Jong
Chen, Jaw-Wen
Leu, Hsin-Bang
author_facet Tsai, Tsung-Ying
Hsu, Pai-Feng
Lin, Chung-Chi
Wang, Yuan-Jen
Ding, Yaw-Zon
Liou, Teh-Ling
Wang, Ying-Wen
Huang, Shao-Sung
Chan, Wan-Leong
Lin, Shing-Jong
Chen, Jaw-Wen
Leu, Hsin-Bang
author_sort Tsai, Tsung-Ying
collection PubMed
description BACKGROUND: Few studies have reported on the clustering pattern of CVD risk factors, including sedentary behavior, systemic inflammation, and cadiometabolic components in the general population. OBJECTIVE: We aimed to explore the clustering pattern of CVD risk factors using exploratory factor analysis to investigate the underlying relationships between various CVD risk factors. METHODS: A total of 5606 subjects (3157 male, 51.5±11.7 y/o) were enrolled, and 14 cardiovascular risk factors were analyzed in an exploratory group (n = 3926) and a validation group (n = 1676), including sedentary behaviors. RESULTS: Five factor clusters were identified to explain 69.4% of the total variance, including adiposity (BMI, TG, HDL, UA, and HsCRP; 21.3%), lipids (total cholesterol and LDL-cholesterol; 14.0%), blood pressure (SBP and DBP; 13.3%), glucose (HbA1C, fasting glucose; 12.9%), and sedentary behavior (MET and sitting time; 8.0%). The inflammation biomarker HsCRP was clustered with only adiposity factors and not with other cardiometabolic risk factors, and the clustering pattern was verified in the validation group. CONCLUSION: This study confirmed the clustering structure of cardiometabolic risk factors in the general population, including sedentary behavior. HsCRP was clustered with adiposity factors, while physical inactivity and sedentary behavior were clustered with each other.
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spelling pubmed-76686102020-11-19 Factor analysis for the clustering of cardiometabolic risk factors and sedentary behavior, a cross-sectional study Tsai, Tsung-Ying Hsu, Pai-Feng Lin, Chung-Chi Wang, Yuan-Jen Ding, Yaw-Zon Liou, Teh-Ling Wang, Ying-Wen Huang, Shao-Sung Chan, Wan-Leong Lin, Shing-Jong Chen, Jaw-Wen Leu, Hsin-Bang PLoS One Research Article BACKGROUND: Few studies have reported on the clustering pattern of CVD risk factors, including sedentary behavior, systemic inflammation, and cadiometabolic components in the general population. OBJECTIVE: We aimed to explore the clustering pattern of CVD risk factors using exploratory factor analysis to investigate the underlying relationships between various CVD risk factors. METHODS: A total of 5606 subjects (3157 male, 51.5±11.7 y/o) were enrolled, and 14 cardiovascular risk factors were analyzed in an exploratory group (n = 3926) and a validation group (n = 1676), including sedentary behaviors. RESULTS: Five factor clusters were identified to explain 69.4% of the total variance, including adiposity (BMI, TG, HDL, UA, and HsCRP; 21.3%), lipids (total cholesterol and LDL-cholesterol; 14.0%), blood pressure (SBP and DBP; 13.3%), glucose (HbA1C, fasting glucose; 12.9%), and sedentary behavior (MET and sitting time; 8.0%). The inflammation biomarker HsCRP was clustered with only adiposity factors and not with other cardiometabolic risk factors, and the clustering pattern was verified in the validation group. CONCLUSION: This study confirmed the clustering structure of cardiometabolic risk factors in the general population, including sedentary behavior. HsCRP was clustered with adiposity factors, while physical inactivity and sedentary behavior were clustered with each other. Public Library of Science 2020-11-16 /pmc/articles/PMC7668610/ /pubmed/33196674 http://dx.doi.org/10.1371/journal.pone.0242365 Text en © 2020 Tsai et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Tsai, Tsung-Ying
Hsu, Pai-Feng
Lin, Chung-Chi
Wang, Yuan-Jen
Ding, Yaw-Zon
Liou, Teh-Ling
Wang, Ying-Wen
Huang, Shao-Sung
Chan, Wan-Leong
Lin, Shing-Jong
Chen, Jaw-Wen
Leu, Hsin-Bang
Factor analysis for the clustering of cardiometabolic risk factors and sedentary behavior, a cross-sectional study
title Factor analysis for the clustering of cardiometabolic risk factors and sedentary behavior, a cross-sectional study
title_full Factor analysis for the clustering of cardiometabolic risk factors and sedentary behavior, a cross-sectional study
title_fullStr Factor analysis for the clustering of cardiometabolic risk factors and sedentary behavior, a cross-sectional study
title_full_unstemmed Factor analysis for the clustering of cardiometabolic risk factors and sedentary behavior, a cross-sectional study
title_short Factor analysis for the clustering of cardiometabolic risk factors and sedentary behavior, a cross-sectional study
title_sort factor analysis for the clustering of cardiometabolic risk factors and sedentary behavior, a cross-sectional study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7668610/
https://www.ncbi.nlm.nih.gov/pubmed/33196674
http://dx.doi.org/10.1371/journal.pone.0242365
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