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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&lt;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 &lt; 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 &lt; 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

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