Presentation Abstract

Session: A-31-Vascular Function
Wednesday, Jun 02, 2010, 7:30 AM -12:30 PM
Presentation: 1547 - Low Levels Of Physical Activity Is Associated With Arterial Stiffness In Adolescents
Location: Hall C, Poster Board: 203
Pres. Time: Wednesday, Jun 02, 2010, 11:00 AM -12:30 PM
Category: +203 vascular function
Keywords: physical activity; arterial stiffness; adolescents
Author(s): Randal P. Claytor1, Philip R. Khoury2, Elaine M. Urbina2, Thomas R. Kimball2, Stephen R. Daniels3. 1Maimi University and CCHMC, Oxford, OH. 2CCHMC, Cincinnati, OH. 3Colorado Health Sciences Center, Aurora, CO. (Sponsor: Jeffrey Potteiger, FACSM)
Abstract: PURPOSE: Physical inactivity is associated with adverse cardiovascular (CV) outcomes in adults. Arterial stiffness is considered to be a precursor of CV disease development and has been shown to be associated with traditional CV risk factors in youth. We examined the relationship between arterial stiffness and physical activity (PA) in 593 youth age 10-24 yrs. (M=18.1 + 3.4 yrs, 35 % male, 63 % non-Caucasian); 218 Ss were categorized as normal weight controls (N); 199 were categorized as obese (O); and 176 were categorized as obese w/ T2D (T). METHODS: Anthropometry and body composition (DXA) was assessed and Ss were instructed to wear an Actical accelerometer on the right hip for 7 consecutive days to assess PA. Average Counts per minute (CPM), time and proportion of total activity spent in moderate to vigorous activity (TMVA, PTMVA), and vigorous (TVA, PTVA) activity was calculated. Echocardiographic and vascular function measures were taken: left ventricular mass was indexed to height (LVMI), Augmentation Index (AIx), Pulse Wave Velocity-femoral (PWVf) and brachial artery distensibility (BrachD) was determined. RESULTS: Actical wear time (AWT) was 801+/-86 min; days with <600 min. were excluded from analyses. ANOVA revealed significant group differences in anthropometric (BMI, % fat and agratio - T>O>N) and PA measures (TMVA, PTMVA, TVA, PTMVA - N>O>T). Stepwise Linear regression modeling indicated that age (+, p< 0.001), BMI (+, p < 0.001), BMIz (+, p < 0.02) and CPM (+, p < 0.01) were independent predictors of LVMI. Age (p < 0.001), and PTVA (-, p < 0.02) were independent predictors of PWVf. Android to gynoid fat ratio (agratio) (+, p<.001), TMVA and PTVA (- both P<.01) were independent predictors of AIx . Wt (-, p<.001), age (+, p<.001), and TVA (+, P<.01) were independent predictors of BrachD. Within each group (N, O, T) LVMI and PWVf were significantly related to BMI, AGE, TMVA, and TVA. CONCLUSIONS: In a large sample of young people higher levels of PA, increased BMI and AGE is associated with an increased LVMI. A lower level of PA and higher AGE is associated with increased PWVf. Within each group the same patterns were evident; less PA and greater levels of obesity were associated with increased PWVf. Clearly, lack of PA, especially vigorous PA, plays a significant role in the development and progression of CVD risk in youth.
Disclosures:  R.P. Claytor, None.