Itamar S Santos1, Airlane P Alencar2, Tatjana Rundek2, Alessandra C Goulart2, Sandhi M Barreto2, Alexandre C Pereira2, Isabela M Benseñor2, Paulo A Lotufo2. 1. From the Centro de Pesquisa Clínica e Epidemiológica do Hospital Universitário (I.S.S., A.C.G., I.M.B., P.A.L.), Instituto de Matemática e Estatística (A.P.A.), and Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina (A.C.P.), Universidade de São Paulo, São Paulo, Brazil; Department of Neurology, University of Miami Miller School of Medicine, FL (T.R.); and Faculdade de Medicina da Universidade Federal de Minas Gerais, Belo Horizonte, Brazil (S.M.B.). itamarss@usp.br. 2. From the Centro de Pesquisa Clínica e Epidemiológica do Hospital Universitário (I.S.S., A.C.G., I.M.B., P.A.L.), Instituto de Matemática e Estatística (A.P.A.), and Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina (A.C.P.), Universidade de São Paulo, São Paulo, Brazil; Department of Neurology, University of Miami Miller School of Medicine, FL (T.R.); and Faculdade de Medicina da Universidade Federal de Minas Gerais, Belo Horizonte, Brazil (S.M.B.).
Abstract
OBJECTIVE: There is little information about how much traditional cardiovascular risk factors explain common carotid artery intima-media thickness (CCA-IMT) variance. We aimed to study to which extent CCA-IMT values are determined by traditional risk factors and which commonly used measurements of blood pressure, glucose metabolism, lipid profile, and adiposity contribute the most to this determination in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) cohort baseline. APPROACH AND RESULTS: We analyzed 9792 individuals with complete data and CCA-IMT measurements. We built multiple linear regression models using mean left and right CCA-IMT as the dependent variable. All models were stratified by sex. We also analyzed individuals stratified by 10-year coronary heart disease risk and, in separate, those with no traditional risk factors. Main models' R(2) varied between 0.141 and 0.373. The major part of the explained variance in CCA-IMT was because of age and race. Indicators of blood pressure, lipid profile, and adiposity that most frequently composed the best models were pulse pressure, low-density lipoprotein/high-density lipoprotein ratio, and neck circumference. The association between neck circumference and CCA-IMT persisted significant even after further adjustment for vessel sizes and body mass index. Indicators of glucose metabolism had smaller contribution. CONCLUSIONS: We found that >60% of CCA-IMT were not explained by demographic and traditional cardiovascular risk factors, which highlights the need to study novel risk factors. Pulse pressure, low-density lipoprotein/high-density lipoprotein ratio, and neck circumference were the most consistent contributors.
OBJECTIVE: There is little information about how much traditional cardiovascular risk factors explain common carotid artery intima-media thickness (CCA-IMT) variance. We aimed to study to which extent CCA-IMT values are determined by traditional risk factors and which commonly used measurements of blood pressure, glucose metabolism, lipid profile, and adiposity contribute the most to this determination in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) cohort baseline. APPROACH AND RESULTS: We analyzed 9792 individuals with complete data and CCA-IMT measurements. We built multiple linear regression models using mean left and right CCA-IMT as the dependent variable. All models were stratified by sex. We also analyzed individuals stratified by 10-year coronary heart disease risk and, in separate, those with no traditional risk factors. Main models' R(2) varied between 0.141 and 0.373. The major part of the explained variance in CCA-IMT was because of age and race. Indicators of blood pressure, lipid profile, and adiposity that most frequently composed the best models were pulse pressure, low-density lipoprotein/high-density lipoprotein ratio, and neck circumference. The association between neck circumference and CCA-IMT persisted significant even after further adjustment for vessel sizes and body mass index. Indicators of glucose metabolism had smaller contribution. CONCLUSIONS: We found that >60% of CCA-IMT were not explained by demographic and traditional cardiovascular risk factors, which highlights the need to study novel risk factors. Pulse pressure, low-density lipoprotein/high-density lipoprotein ratio, and neck circumference were the most consistent contributors.
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