CONTEXT: Both excess visceral adipose tissue (VAT) and low cardiorespiratory fitness (CRF) levels are associated with a deteriorated cardiometabolic risk profile. OBJECTIVE: The aim of the study was to examine the respective contributions of changes in VAT accumulation vs. changes in CRF to 6-yr longitudinal changes in cardiometabolic risk markers. DESIGN, SETTINGS, AND PARTICIPANTS: We conducted a prospective, population-based study with an average follow-up of 5.9 ± 0.8 yr. We followed 132 middle-aged participants from the Quebec Family Study (mean age, 35.3 ± 13.9 yr). VAT was measured by computed tomography, whereas the level of CRF was assessed by a submaximal physical working capacity test at baseline and at follow-up. A complete cardiometabolic risk profile, including systolic and diastolic blood pressure, fasting glucose and insulin levels, C-reactive protein (n = 72), as well as a standard lipoprotein-lipid profile, was obtained at baseline and at follow-up. MAIN OUTCOME MEASURES: We measured changes in CRF, VAT, and cardiometabolic risk profile over 6 yr. RESULTS: After adjusting for age and sex, 6-yr changes in VAT were negatively correlated with changes in CRF (r = -0.38; P < 0.001). In a multivariate model that included age, sex, changes in VAT, changes in CRF, as well as baseline levels of the above cardiometabolic risk factors, 6-yr changes in VAT were the most important predictor of the change in the metabolic syndrome score (R(2) = 13.2%; P < 0.001). Adding 6-yr changes in CRF levels significantly improved the predictability of the model (R(2) = 19.7%; P = 0.002). CONCLUSIONS: Changes in both VAT and CRF levels observed over 6 yr are associated with changes in parameters of the lipoprotein-lipid profile, glucose-insulin homeostasis, and inflammatory markers. Thus, maintaining a low level of VAT and a high level of CRF are important targets for maintenance of cardiometabolic health.
CONTEXT: Both excess visceral adipose tissue (VAT) and low cardiorespiratory fitness (CRF) levels are associated with a deteriorated cardiometabolic risk profile. OBJECTIVE: The aim of the study was to examine the respective contributions of changes in VAT accumulation vs. changes in CRF to 6-yr longitudinal changes in cardiometabolic risk markers. DESIGN, SETTINGS, AND PARTICIPANTS: We conducted a prospective, population-based study with an average follow-up of 5.9 ± 0.8 yr. We followed 132 middle-aged participants from the Quebec Family Study (mean age, 35.3 ± 13.9 yr). VAT was measured by computed tomography, whereas the level of CRF was assessed by a submaximal physical working capacity test at baseline and at follow-up. A complete cardiometabolic risk profile, including systolic and diastolic blood pressure, fasting glucose and insulin levels, C-reactive protein (n = 72), as well as a standard lipoprotein-lipid profile, was obtained at baseline and at follow-up. MAIN OUTCOME MEASURES: We measured changes in CRF, VAT, and cardiometabolic risk profile over 6 yr. RESULTS: After adjusting for age and sex, 6-yr changes in VAT were negatively correlated with changes in CRF (r = -0.38; P < 0.001). In a multivariate model that included age, sex, changes in VAT, changes in CRF, as well as baseline levels of the above cardiometabolic risk factors, 6-yr changes in VAT were the most important predictor of the change in the metabolic syndrome score (R(2) = 13.2%; P < 0.001). Adding 6-yr changes in CRF levels significantly improved the predictability of the model (R(2) = 19.7%; P = 0.002). CONCLUSIONS: Changes in both VAT and CRF levels observed over 6 yr are associated with changes in parameters of the lipoprotein-lipid profile, glucose-insulin homeostasis, and inflammatory markers. Thus, maintaining a low level of VAT and a high level of CRF are important targets for maintenance of cardiometabolic health.
Authors: Ming Ding; Oana A Zeleznik; Marta Guasch-Ferre; Jie Hu; Jessica Lasky-Su; I-Min Lee; Rebecca D Jackson; Aladdin H Shadyab; Michael J LaMonte; Clary Clish; A Heather Eliassen; Frank Sacks; Walter C Willett; Frank B Hu; Kathryn M Rexrode; Peter Kraft Journal: Am J Epidemiol Date: 2019-11-01 Impact factor: 4.897
Authors: Catherine A Sullivan; Steven E Kahn; Wilfred Y Fujimoto; Tomoshige Hayashi; Donna L Leonetti; Edward J Boyko Journal: Hypertension Date: 2015-05-11 Impact factor: 10.190
Authors: Arpit Saxena; Dawn Minton; Duck-chul Lee; Xuemei Sui; Raja Fayad; Carl J Lavie; Steven N Blair Journal: Mayo Clin Proc Date: 2013-12 Impact factor: 7.616
Authors: Michael N Vranian; Tanya Keenan; Michael J Blaha; Michael G Silverman; Erin D Michos; C Michael Minder; Roger S Blumenthal; Khurram Nasir; Romeu S Meneghelo; Raul D Santos Journal: Am J Cardiol Date: 2013-01-19 Impact factor: 2.778