32 research outputs found

    Physical Activity and Screen Time Sedentary Behaviors in College Students

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    It is well established that Americans are not meeting physical activity (PA) guidelines and college students are no exception. Given the lack of regular PA, many health promotion professionals seek to discover what barriers to PA may exist. A common explanation is screen time (ST), which is comprised primarily of television viewing, computer use, and the playing of video games. The purpose of this study was to present descriptive data on college students’ PA and sedentary behavior and to assess if any evidence exists to suggest displacement between sedentary behaviors and PA in college students. Students completed an online health survey specific to time spent in PA and sedentary behavior. Students were categorized into one of three PA groups based on their activity level. Males were significantly more physically active than females in terms of days per week engaged in aerobic exercise (p=.022) and strength training (p\u3c.001). When categorized by activity level, a greater percentage of male students met recommended PA levels than did females (p\u3c.001). Males reported significantly higher levels of overall ST (p=.004) and television viewing (p\u3c.001), whereas females reported significantly higher levels of time spent engaged in homework (p\u3c.001). When categorized by activity level, physically active students reported significantly fewer minutes of total ST than inactive students (p=.047). Implications of this study suggest that within a college population, television and PA are not competing behaviors in either gender

    Evaluation of a Circumference-based Prediction Equation to Assess Body Composition Changes in Men

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    International Journal of Exercise Science 6(3) : 188-198, 2013. This study evaluated the validity of the current U.S. Department of Defense (DOD) circumference-based prediction equation for males to detect body composition changes in comparison to air-displacement plethysmography (ADP). Body composition was assessed using ADP and the DOD equation at the beginning and end of an academic school year among 21 male (18-29 years-old) Army ROTC cadets. Body mass significantly increased (+1.8 Kg) after 9 months. Significant method by time interactions for percent body fat (percent body fat), fat mass (FM), and fat-free mass were found (p = 0.022, p = 0.023, p = 0.023, respectively) as body composition changes were not tracked equally by the two methods. Regression and Bland-Altman analyses indicated a lack of agreement between methods as the DOD equation underestimated percent body fat and FM changes in comparison to ADP. Results suggest the DOD equation for males cannot adequately detect body composition changes following a small body mass gain

    Validation of an integrated pedal desk and electronic behavior tracking platform

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    Background This study tested the validity of revolutions per minute (RPM) measurements from the Pennington Pedal Desk™. Forty-four participants (73 % female; 39 ± 11.4 years-old; BMI 25.8 ± 5.5 kg/m2 [mean ± SD]) completed a standardized trial consisting of guided computer tasks while using a pedal desk for approximately 20 min. Measures of RPM were concurrently collected by the pedal desk and the Garmin Vector power meter. After establishing the validity of RPM measurements with the Garmin Vector, we performed equivalence tests, quantified mean absolute percent error (MAPE), and constructed Bland–Altman plots to assess agreement between RPM measures from the pedal desk and the Garmin Vector (criterion) at the minute-by-minute and trial level (i.e., over the approximate 20 min trial period). Results The average (mean ± SD) duration of the pedal desk trial was 20.5 ± 2.5 min. Measures of RPM (mean ± SE) at the minute-by-minute (Garmin Vector: 54.8 ± 0.4 RPM; pedal desk: 55.8 ± 0.4 RPM) and trial level (Garmin Vector: 55.0 ± 1.7 RPM; pedal desk: 56.0 ± 1.7 RPM) were deemed equivalent. MAPE values for RPM measured by the pedal desk were small (minute-by-minute: 2.1 ± 0.1 %; trial: 1.8 ± 0.1 %) and no systematic relationships in error variance were evident by Bland–Altman plots. Conclusion The Pennington Pedal Desk™ provides a valid count of RPM, providing an accurate metric to promote usage

    How fast is fast enough? Walking cadence (steps/min) as a practical estimate of intensity in adults: A narrative review

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    Background: Cadence (steps/min) may be a reasonable proxy-indicator of ambulatory intensity. A summary of current evidence is needed for cadence-based metrics supporting benchmark (standard or point of reference) and threshold (minimums associated with desired outcomes) values that are informed by a systematic process.Objective: To review how fast, in terms of cadence, is enough, with reference to crafting public health recommendations in adults.Methods: A comprehensive search strategy was conducted to identify relevant studies focused on walking cadence and intensity for adults. Identified studies (n=38) included controlled (n=11), free-living observational (n=18) and intervention (n=9) designs.Results: There was a strong relationship between cadence (as measured by direct observation and objective assessments) and intensity (indirect calorimetry). Despite acknowledged interindividual variability, =100 steps/min is a consistent heuristic (e.g., evidence-based, rounded) value associated with absolutely defined moderate intensity (3 metabolic equivalents (METs)). Epidemiological studies report notably low mean daily cadences (ie, 7.7 steps/min), shaped primarily by the very large proportion of time (13.5 hours/day) spent between zero and purposeful cadences (100 and >70 steps/min, respectively. Peak cadence indicators are negatively associated with increased age and body mass index. Identified intervention studies used cadence to either prescribe and/or quantify ambulatory intensity but the evidence is best described as preliminary.Conclusions: A cadence value of =100 steps/min in adults appears to be a consistent and reasonable heuristic answer to 'How fast is fast enough?' during sustained and rhythmic ambulatory behaviour.Peer reviewedCommunity Health Sciences, Counseling and Counseling Psycholog

    Older Adult Compendium of Physical Activities: Energy Costs of Human Activities in Adults Aged 60 and Older

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    Purpose: To describe the development of a Compendium for estimating the energy costs of activities in adults ≥60 years (OA Compendium). Methods: Physical activities (PAs) and their metabolic equivalent of task (MET) values were obtained from a systematic search of studies published in 4 sport and exercise databases (PubMed, Embase, SPORTDiscus (EBSCOhost), and Scopus) and a review of articles included in the 2011 Adult Compendium that measured PA in older adults. MET values were computed as the oxygen cost (VO2, mL/kg/min) during PA divided by 2.7 mL/kg/min (MET60+) to account for the lower resting metabolic rate in older adults. Results: We identified 68 articles and extracted energy expenditure data on 427 PAs. From these, we derived 99 unique Specific Activity codes with corresponding MET60+ values for older adults. We developed a website to present the OA Compendium MET60+ values: https://pacompendium.com. Conclusion: The OA Compendium uses data collected from adults ≥60 years for more accurate estimation of the energy cost of PAs in older adults. It is an accessible resource that will allow researchers, educators, and practitioners to find MET60+ values for older adults for use in PA research and practice

    Step-based physical activity metrics and cardiometabolic risk: NHANES 2005-2006

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    Purpose: This study aimed to catalog the relationships between step-based accelerometer metrics indicative of physical activity volume (steps per day, adjusted to a pedometer scale), intensity (mean steps per minute from the highest, not necessarily consecutive, minutes in a day; peak 30-min cadence), and sedentary behavior (percent time at zero cadence relative to wear time; %TZC) and cardiometabolic risk factors. Methods: We analyzed data from 3388 participants, 20+ yr old, in the 2005-2006 National Health and Nutrition Examination Survey with >/=1 valid day of accelerometer data and at least some data on weight, body mass index, waist circumference, systolic and diastolic blood pressure, glucose, insulin, HDL cholesterol, triglycerides, and/or glycohemoglobin. Linear trends were evaluated for cardiometabolic variables, adjusted for age and race, across quintiles of steps per day, peak 30-min cadence, and %TZC. Results: Median steps per day ranged from 2247 to 12,334 steps per day for men and from 1755 to 9824 steps per day for women, and median peak 30-min cadence ranged from 48.1 to 96.0 steps per minute for men and from 40.8 to 96.2 steps per minute for women for the first and fifth quintiles, respectively. Linear trends were statistically significant (all P < 0.001), with increasing quintiles of steps per day and peak 30-min cadence inversely associated with waist circumference, weight, body mass index, and insulin for both men and women. Median %TZC ranged from 17.6% to 51.0% for men and from 19.9% to 47.6% for women for the first and fifth quintiles, respectively. Linear trends were statistically significant (all P < 0.05), with increasing quintiles of %TZC associated with increased waist circumference, weight and insulin for men, and insulin for women. Conclusions: This analysis identified strong linear relationships between step-based movement/nonmovement dimensions and cardiometabolic risk factors. These data offer a set of quantified access points for studying the potential dose-response effects of each of these dimensions separately or collectively in longitudinal observational or intervention study designs.Peer reviewedCommunity Health Sciences, Counseling and Counseling Psycholog

    Cadence (steps/min) and intensity during ambulation in 6-20 year olds: The CADENCE-kids study

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    Background: Steps/day is widely utilized to estimate the total volume of ambulatory activity, but it does not directly reflect intensity, a central tenet of public health guidelines. Cadence (steps/min) represents an overlooked opportunity to describe the intensity of ambulatory activity. We sought to establish thresholds linking directly observed cadence with objectively measured intensity in 6-20 year olds.Methods: One hundred twenty participants completed multiple 5-min bouts on a treadmill, from 13.4 m/min (0.80 km/h) to 134.0 m/min (8.04 km/h). The protocol was terminated when participants naturally transitioned to running, or if they chose to not continue. Steps were visually counted and intensity was objectively measured using a portable metabolic system. Youth metabolic equivalents (METy) were calculated for 6-17 year olds, with moderate intensity defined as >/=4 and /=6 METy. Traditional METs were calculated for 18-20 year olds, with moderate intensity defined as >/=3 and /=6 METs. Optimal cadence thresholds for moderate and vigorous intensity were identified using segmented random coefficients models and receiver operating characteristic (ROC) curves.Result: Participants were on average (+/- SD) aged 13.1 +/- 4.3 years, weighed 55.8 +/- 22.3 kg, and had a BMI z-score of 0.58 +/- 1.21. Moderate intensity thresholds (from regression and ROC analyses) ranged from 128.4 steps/min among 6-8 year olds to 87.3 steps/min among 18-20 year olds. Comparable values for vigorous intensity ranged from 157.7 steps/min among 6-8 year olds to 119.3 steps/min among 18-20 year olds. Considering both regression and ROC approaches, heuristic cadence thresholds (i.e., evidence-based, practical, rounded) ranged from 125 to 90 steps/min for moderate intensity, and 155 to 125 steps/min for vigorous intensity, with higher cadences for younger age groups. Sensitivities and specificities for these heuristic thresholds ranged from 77.8 to 99.0%, indicating fair to excellent classification accuracy.Conclusions: These heuristic cadence thresholds may be used to prescribe physical activity intensity in public health recommendations. In the research and clinical context, these heuristic cadence thresholds have apparent value for accelerometer-based analytical approaches to determine the intensity of ambulatory activity.Peer reviewedCommunity Health Sciences, Counseling and Counseling Psycholog
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