TY - JOUR
T1 - Arterial Stiffness and Cardiometabolic-Based Chronic Disease
T2 - The Kardiovize Study
AU - Pavlovska, Iuliia
AU - Mechanick, Jeffrey I.
AU - Maranhao Neto, Geraldo A.
AU - Infante-Garcia, Maria M.
AU - Nieto-Martinez, Ramfis
AU - Kunzova, Sarka
AU - Polcrova, Anna
AU - Vysoky, Robert
AU - Medina-Inojosa, Jose R.
AU - Lopez-Jimenez, Francisco
AU - Stokin, Gorazd B.
AU - González-Rivas, Juan P.
N1 - Funding Information:
The authors are grateful to all participants of the study and the following team members: Jana Jaresova, who contributed with coordination of the study, and Hana Pernicova Kristofova, Jana Hruskova, Juraj Jakubik, Alena Zajickova, Maria Skladana, and Anna Pospisilova, who contributed with the data collection. The Kardiovize Brno 2030 study was supported by the European Regional Development Fund – Project FNUSA-ICRC (no. CZ.1.05/1.1.00/02.0123), project no. LQ1605 from the National Program of Sustainability II (MEYS CR), project ENOCH (no. CZ.02.1.01/0.0/0.0/16_019/0000868), and a grant by the Ministry of Health of the Czech Republic (NT13434-4/2012). Dr Jeffrey Mechanick has received speaker and program development honoraria from Abbott Nutrition (Abbott Laboratories). All other authors have no multiplicity of interest to disclose.
Funding Information:
The Kardiovize Brno 2030 study was supported by the European Regional Development Fund – Project FNUSA-ICRC (no. CZ.1.05/1.1.00/02.0123 ), project no. LQ1605 from the National Program of Sustainability II (MEYS CR), project ENOCH (no. CZ.02.1.01/0.0/0.0/16_019/0000868 ), and a grant by the Ministry of Health of the Czech Republic ( NT13434-4/2012 ).
Publisher Copyright:
© 2021 AACE
PY - 2021/6
Y1 - 2021/6
N2 - Objective: Arterial stiffness (ArSt) describes a loss of arterial wall elasticity and is an independent predictor of cardiovascular events. A cardiometabolic-based chronic disease model integrates concepts of adiposity-based chronic disease (ABCD), dysglycemia-based chronic disease (DBCD), and cardiovascular disease. We assessed if ABCD and DBCD models detect more people with high ArSt compared with traditional adiposity and dysglycemia classifiers using the cardio-ankle vascular index (CAVI). Methods: We evaluated 2070 subjects aged 25 to 64 years from a random population-based sample. Those with type 1 diabetes were excluded. ABCD and DBCD were defined, and ArSt risk was stratified based on the American Association of Clinical Endocrinologists criteria. Results: The highest prevalence of a high CAVI was in stage 2 ABCD (18.5%) and stage 4 DBCD (31.8%), and the lowest prevalence was in stage 0 ABCD (2.2%). In univariate analysis, stage 2 ABCD and all DBCD stages increased the risk of having a high CAVI compared with traditional classifiers. After adjusting for age and gender, only an inverse association between obesity (body mass index ≥30 kg/m2) and CAVI remained significant. Nevertheless, body mass index was responsible for only 0.3% of CAVI variability. Conclusion: The ABCD and DBCD models showed better performance than traditional classifiers to detect subjects with ArSt; however, the variables were not independently associated with age and gender, which might be explained by the complexity and multifactoriality of the relationship of CAVI with the ABCD and DBCD models, mediated by insulin resistance.
AB - Objective: Arterial stiffness (ArSt) describes a loss of arterial wall elasticity and is an independent predictor of cardiovascular events. A cardiometabolic-based chronic disease model integrates concepts of adiposity-based chronic disease (ABCD), dysglycemia-based chronic disease (DBCD), and cardiovascular disease. We assessed if ABCD and DBCD models detect more people with high ArSt compared with traditional adiposity and dysglycemia classifiers using the cardio-ankle vascular index (CAVI). Methods: We evaluated 2070 subjects aged 25 to 64 years from a random population-based sample. Those with type 1 diabetes were excluded. ABCD and DBCD were defined, and ArSt risk was stratified based on the American Association of Clinical Endocrinologists criteria. Results: The highest prevalence of a high CAVI was in stage 2 ABCD (18.5%) and stage 4 DBCD (31.8%), and the lowest prevalence was in stage 0 ABCD (2.2%). In univariate analysis, stage 2 ABCD and all DBCD stages increased the risk of having a high CAVI compared with traditional classifiers. After adjusting for age and gender, only an inverse association between obesity (body mass index ≥30 kg/m2) and CAVI remained significant. Nevertheless, body mass index was responsible for only 0.3% of CAVI variability. Conclusion: The ABCD and DBCD models showed better performance than traditional classifiers to detect subjects with ArSt; however, the variables were not independently associated with age and gender, which might be explained by the complexity and multifactoriality of the relationship of CAVI with the ABCD and DBCD models, mediated by insulin resistance.
KW - adiposity
KW - atherosclerosis
KW - cardio-ankle vascular index
KW - diabetes
KW - obesity
KW - type 2 diabetes
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U2 - 10.1016/j.eprac.2021.03.004
DO - 10.1016/j.eprac.2021.03.004
M3 - Article
C2 - 33722731
AN - SCOPUS:85108303636
SN - 1530-891X
VL - 27
SP - 571
EP - 578
JO - Endocrine Practice
JF - Endocrine Practice
IS - 6
ER -