Thursday-Abstracts
Thursday-Abstracts
Thursday-Abstracts
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<strong>Thursday</strong>, May 30, 2013<br />
S218 Vol. 45 No. 5 Supplement<br />
1161 Board #106 May 30, 8:00 AM - 9:30 AM<br />
Physical activity and Benign Prostatic hyperplasia / Lower<br />
urinary Tract symptoms<br />
Kathleen Y. Wolin, FACSM1 , Robert Grubb, III1 , Ratna<br />
Pakpahan1 , Lawrence Ragard2 , Jerome Mabie3 , Gerald Andriole1 ,<br />
Siobhan Sutcliffe1 . 1Washington University School of Medicine<br />
St Louis, St Louis, MO. 2Westat, Rockville, MD. 3IMS, Inc,<br />
Calverton, MD.<br />
(No relationships reported)<br />
Benign prostatic hyperplasia (BPH) and its associated lower urinary tract symptoms<br />
(LUTS) are extremely common among middle- and older-aged American men. Few<br />
studies have investigated physical activity (PA) in relation to BPH/LUTS, with<br />
inconclusive results in cross-sectional studies suggesting a protective association.<br />
However, as this association may potentially reflect the influence of BPH/LUTS on PA<br />
rather than PA on BPH/LUTS, prospective investigations are necessary.<br />
PurPOsE: To examine the association of physical activity with incident BPH/LUTS.<br />
METhOds: Using observational data from the PLCO, a large well-characterized<br />
clinical trial sample, we examined the association of self-reported vigorous PA (current<br />
and at age 40) with incident BPH/LUTS. BPH/LUTS was measured at baseline<br />
(1993-2001) and follow-up (2006-8) using self-report of physician diagnosis, BPH<br />
surgery, finasteride use, nocturia, prostate-specific antigen (PSA) elevation, and large<br />
prostate volume. We included 4,771 men in the incident analysis. Poisson regression<br />
with robust variance estimation was used to calculate multivariable relative risks<br />
(RR) adjusted for age, follow-up time, and number of PSA tests and digital rectal<br />
examinations, as appropriate.<br />
rEsuLTs: As hypothesized, associations for incident BPH/LUTS differed from<br />
previous cross-sectional findings for prevalent BPH/LUTS. PA was not associated with<br />
elevated PSA, greater prostate volume, physician diagnosis of BPH, or finasteride use,<br />
although it was still inversely associated with nocturia. Men engaging in PA 4+ h/wk<br />
were 14% (RR=0.86, 95% CI: 0.76-0.99) less likely to report nocturia ≥2 times/wk and<br />
32% (RR=0.68, 95%CI: 0.51-0.92) less likely to report nocturia ≥3 times/wk than men<br />
who were not active. PA at age 40 was not associated with incident BPH.<br />
CONCLusIONs: The association of PA with incident BPH/LUTS differs from<br />
previous findings for prevalent BPH/LUTS. PA was not associated with incident BPH/<br />
LUTS except when defined as nocturia. Previous studies have suggested that PA may<br />
increase sleep quality, which may explain why PA was only associated with nocturia<br />
and not other dimensions of BPH/LUTS.<br />
1162 Board #107 May 30, 8:00 AM - 9:30 AM<br />
Moderate-to-vigorous Physical activity Thresholds<br />
associated with Metabolic syndrome risk Factors<br />
Tiago V. Barreira, John M. Schuna, Catrine Tudor-Locke,<br />
FACSM, Peter T. Katzmarzyk, FACSM. Pennington Biomedical<br />
Research Center, Baton Rouge, LA.<br />
(No relationships reported)<br />
Current physical activity (PA) guidelines were primarily developed from<br />
epidemiological evidence linking self-reported PA levels with chronic disease<br />
outcomes. Recently, accelerometer PA data from the National Health and Nutrition<br />
Examination Survey (NHANES) has been used to estimate the proportion of US adults<br />
meeting PA guidelines. However, PA information collected via self-report and from<br />
accelerometers may not be equivalent.<br />
PurPOsE: To determine if levels of objectively monitored moderate-to-vigorous<br />
PA (MVPA) can adequately discriminate between adults with and without metabolic<br />
syndrome (MetS) risk factors.<br />
METhOds: 2103 fasted, non-pregnant participants ≥ 20 years of age who had ≥ 4<br />
days of valid accelerometer data (≥ 10 h/dy) and non-missing data for the harmonized<br />
MetS risk factors (blood pressure [BP], triglycerides [TG], fasting blood glucose<br />
[GLU], high-density lipoprotein [HDL-C], waist circumference [WC]) were included<br />
in this analysis of the 03-06 NHANES. MVPA was defined using a threshold of 2020<br />
counts/min. Participants were classified as healthy or unhealthy using the harmonized<br />
MetS risk cut-points for each risk factor. MetS was defined as the presence of ≥ 3 risk<br />
factors. Receiver operating characteristic curve analysis was used to identify optimal<br />
MVPA thresholds to discriminate between healthy and unhealthy adults.<br />
rEsuLTs: Discriminatory MVPA thresholds for all MetS risk factors in men were<br />
identified with area under the curve (AUC) values ranging from 0.55-0.65 (all p < 0.01).<br />
MVPA thresholds were 14-16 min/day for BP, TG, and GLU, 24 min/day for WC, 25<br />
min/day for HDL-C, and 14 min/day for MetS (sensitivity 51%, specificity 72%, AUC<br />
0.63). The optimal MVPA threshold for HDL-C in women was 16 min/day however the<br />
AUC (0.55) was non-significant (p = 0.09). MVPA thresholds for all other MetS risk<br />
factors were identified, with AUC values ranging from 0.65-0.72 (all p < 0.01). Optimal<br />
MVPA thresholds were 10-11 min/day for BP, TG, GLU, and WC. For MetS the MVPA<br />
threshold was 10 min/day (sensitivity 71%, specificity 61%, AUC 0.70).<br />
CONCLusIONs: Although discriminatory thresholds of MVPA in relation to MetS<br />
risk factors were identified, all AUC, sensitivity, and specificity values were fairly low.<br />
Daily MVPA thresholds were lower than the current guidelines and different between<br />
men and women.<br />
MEDICINE & SCIENCE IN SPORTS & EXERCISE ®<br />
1163 Board #108 May 30, 8:00 AM - 9:30 AM<br />
Vitality age: Calibration Of a Modifiable risk-related age<br />
algorithm, Part of an Incentivised Wellness Program<br />
Estelle V. Lambert1 , Kolbe-Alexander Tracy1 , Maroba Josiase2 ,<br />
Mweete Naglazi1 , Deepak Patel2 , Lori Serradas3 , Rhonda<br />
Roscoe3 , Jonathon Dugas3 , Adam Noach2 . 1University of<br />
Cape Town, Newlands, South Africa. 2Discovery Health,<br />
Johannesburg, South Africa. 3The Vitality Group, Chicago, IL.<br />
(No relationships reported)<br />
PurPOsE: The primary aim of this study was to compare the Vitality Risk Age (VA),<br />
based entirely on modifiable risk factors for cardio-metabolic disease (CMD), against<br />
the Framingham Heart Score (FHS) in a cross-sectional sample of persons registered<br />
for an employee-sponsored, Vitality wellness program.<br />
METhOds: The VA algorithm is comprised of modifiable risk factors including:<br />
BMI, smoking, physical activity, alcohol, blood pressure, fasting glucose, cholesterol,<br />
depression/anxiety and dietary behavior scores. A combined relative risk was<br />
calculated (CRR), to adjust actual age to risk age, based on standardized life<br />
expectancy (VA diff %). The sample included de-identified data from all members who<br />
completed the health risk assessment (HRA) from Jan-Sept 2011 (Total N=41067, of<br />
whom, 4049 reported cardio-metabolic disease, CMD). We calculated the odds ratios<br />
for CMD, for each risk factor that contributed to the algorithm, adjusting for gender,<br />
and generated receiver operator characteristic curves (ROC) for risk scores predicting<br />
CMD, separately for men and women.<br />
rEsuLTs: The VA difference for the entire sample was 3.8+4.6 yrs (9% older<br />
by risk). The VA diff (yrs and %) were significantly correlated to the FHS scores<br />
(r=0.50,r=0.49, respectively, P<0.001). Persons meeting physical activity (PA)<br />
guidelines had significantly lower odds ratios for CMD (OR=0.65, 95%CI: 0.60-0.70,<br />
P < 0.001). For every 1mmHg increase in systolic blood pressure, there was an<br />
2% increase in the odds of CMD, and for each kg/m2 BMI and cm change in waist<br />
circumference, there was a 10% and 4% increase in the odds of CMD, respectively.<br />
The c-statistic for the ROC curves for CRR were 0.60 and 0.71, , compared to 0.49 and<br />
0.68 for the FHS, for men and women, respectively. The odds of CMD increased by<br />
1% for each 1% diff in VA diff (%), (P < 0.001).<br />
CONCLusIONs: Risk algorithms based on modifiable behaviors, such as physical<br />
activity, compare favorably to established risk scores for predicting CMD and provide<br />
useful tools to convey behavior change recommendations.<br />
1164 Board #109 May 30, 8:00 AM - 9:30 AM<br />
differential sex Effects on Lean Body Mass in response to<br />
Concurrent high Intensity Exercise Training<br />
Joshua A. Cotter 1 , Tomasz Owerkowicz 2 , Alvin M. Yu 1 ,<br />
Marinelle L. Camilon 1 , Theresa Hoang 1 , Per A. Tesch 3 , Vincent<br />
J. Caiozzo, FACSM 1 , Gregory R. Adams, FACSM 1 . 1 University<br />
of California, Irvine, CA. 2 California State University, San<br />
Bernardino, CA. 3 Karolinska Institute, Stockholm, Sweden.<br />
(Sponsor: Vincent J. Caiozzo, FACSM)<br />
(No relationships reported)<br />
General health, sporting requirements, and environments, e.g. space flight, that warrant<br />
the need for cardiovascular and musculoskeletal maintenance often incorporate both<br />
aerobic (AE) and resistance exercise (RE) training. Concurrent training has shown<br />
potential interference effects and therefore it is important to examine whether there<br />
are sex differences on lean body mass (LBM) responses to concurrent high intensity<br />
training.<br />
PurPOsE: To determine if concurrent training utilizing high-intensity interval<br />
rowing and maximal concentric/eccentric exercise on the Multi-Mode Exercise<br />
Device (M-MED), a gravity-independent flywheel exercise device, will exhibit similar<br />
changes in LBM regardless of sex.<br />
METhOds: Twelve healthy, sedentary males (n=6 , 23.0 ±4.6 yrs, 69.0 ±6.1 kg) and<br />
females (n=6, 23.8 ±2.4 yrs, 68.8 ±15.5 kg) completed 5 weeks of concurrent exercise<br />
training on the M-MED with alternating days of AE and RE training sessions. AE<br />
consisted of high-intensity interval rowing alternating 4 minutes of high intensity (HR<br />
at ≥90% VO2max) and 4 minutes of low intensity (HR at 50% VO2max) exercise. RE<br />
included maximal intensity horizontal squats, hamstring curls, and heel raises. LBM<br />
was assessed using dual energy X-ray absorptiometry (DXA) and whole muscle cross<br />
sectional area (CSA) by magnetic resonance imaging (MRI). Training and gender<br />
comparisons were made using a two-way ANOVA with repeated measures.<br />
rEsuLTs: LBM (3.3%, p