Variability of Objectively Measured Sedentary Behavior

The primary purpose of this study was to evaluate variability of sedentary behavior (SB) throughout a 7-d measurement period and to determine if G7 d of SB measurement would be comparable with the typical 7-d measurement period. Methods: Retrospective data from Ball State University_s Clinical Exercise Physiology Laboratory on 293 participants (99 men, 55 T 14 yr, body mass index = 29 T 5 kgImj2; 194 women, 51 T 12 yr, body mass index = 27 T 7 kgImj2) with seven consecutive days of data collected with ActiGraph accelerometers were analyzed (ActiGraph, Fort Walton Beach, FL). Time spent in SB (either G100 counts per minute or G150 counts per minute) and breaks in SB were compared between days and by sex using a two-way repeated-measures ANOVA. Stepwise regression was performed to determine if G7 d of SB measurement were comparable with the 7-d method, using an adjusted R2 of Q0.9 as a criterion for equivalence. Results: There were no differences in daily time spent in SB between the 7 d for all participants. However, there was a significant interaction between sex and days, with women spending less time in SB on both Saturdays and Sundays than men when using the 100 counts per minute cut-point. Stepwise regression showed using any 4 d would be comparable with a 7-d measurement (R2 9 0.90). Conclusions: When assessed over a 7-d measurement period, SB appears to be very stable from day to day, although there may be some small differences in time spent in SB and breaks in SB between men and women, particularly on weekend days. The stepwise regression analysis suggests that a measurement period as short as 4 d could provide comparable data (91% of variance) with a 1-wk assessment. Shorter assessment periods would reduce both researcher and subject burden in data collection

Living a Long Life is a Multi-Step Process

There is a strong link between physical activity and health. Historically, large-scale epidemiological studies have used self-report surveys to capture physical activity measures (eg, type and intensity). In the past 20–30 years, large cohort studies have increasingly adopted devices, such as pedometers, accelerometers, and consumer-marketed activity trackers, to measure physical activity. Device-based physical activity measures alleviate some limitations of self-reporting by increasing measurement objectivity and accuracy. Additionally, device-based measures often show stronger associations with health outcomes than do self-reported measures, showcasing their value in understanding how physical activity affects health. Unlike self-report, device-based measures can capture steps, which are easily understandable and can be effective for goal setting and motivation to increase physical activity levels. Moreover, steps can be used to assess both physical activity volume (eg, steps per day) and intensity (eg, steps per min)

Raw and Count Data Comparability of Hip-Worn ActiGraph GT3X+ and Link Accelerometers

To enable inter- and intrastudy comparisons it is important to ascertain comparability among accelerometer models. Purpose: The purpose of this study was to compare raw and count data between hip-worn ActiGraph GT3X+ and GT9X Link accelerometers. Methods: Adults (n = 26 (n = 15 women); age, 49.1 T 20.0 yr) wore GT3X+ and Link accelerometers over the right hip for an 80-min protocol involving 12–21 sedentary, household, and ambulatory/exercise activities lasting 2–15 min each. For each accelerometer, mean and variance of the raw (60 Hz) data for each axis and vector magnitude (VM) were extracted in 30-s epochs. A machine learning model (Montoye 2015) was used to predict energy expenditure in METs from the raw data. Raw data were also processed into activity counts in 30-s epochs for each axis and VM, with Freedson 1998 and 2011 count-based regression models used to predictMETs. Time spent in sedentary, light, moderate, and vigorous intensities was derived from predicted METs from each model. Correlations were calculated to compare raw and count data between accelerometers, and percent agreement was used to compare epoch-by-epoch activity intensity. Results: For raw data, correlations for mean acceleration were 0.96 T 0.05, 0.89 T 0.16, 0.71 T 0.33, and 0.80 T 0.28, and those for variance were 0.98 T 0.02, 0.98 T 0.03, 0.91 T 0.06, and 1.00 T 0.00 in the X, Y, and Z axes and VM, respectively. For count data, corresponding correlations were 1.00 T 0.01, 0.98 T 0.02, 0.96 T 0.04, and 1.00 T 0.00, respectively. Freedson 1998 and 2011 count-based models had significantly higher percent agreement for activity intensity (95.1% T 5.6% and 95.5% T 4.0%) compared with theMontoye 2015 raw data model (61.5% T 27.6%; P G 0.001). Conclusions: Count data were more highly comparable than raw data between accelerometers. Data filtering and/or more robust raw data models are needed to improve raw data comparability between ActiGraph GT3X+ and Link accelerometers

Reference Standards for Body Fat Measure Using GE Dual Energy X-Ray Absorptiometry in Caucasian Adults

Background Dual energy x-ray absorptiometry (DXA) is an established technique for the measurement of body composition. Reference values for these variables, particularly those related to fat mass, are necessary for interpretation and accurate classification of those at risk for obesityrelated health complications and in need of lifestyle modifications (diet, physical activity, etc.). Currently, there are no reference values available for GE-Healthcare DXA systems and it is known that whole-body and regional fat mass measures differ by DXA manufacturer. Objective To develop reference values by age and sex for DXA-derived fat mass measurements with GE-Healthcare systems. Methods A de-identified sample of 3,327 participants (2,076 women, 1,251 men) was obtained from Ball State University\u27s Clinical Exercise Physiology Laboratory and University of Wisconsin- Milwaukee\u27s Physical Activity & Health Research Laboratory. All scans were completed using a GE Lunar Prodigy or iDXA and data reported included percent body fat (%BF), fat mass index (FMI), and ratios of android-to-gynoid (A/G), trunk/limb, and trunk/leg fat measurements. Percentiles were calculated and a factorial ANOVA was used to determine differences in the mean values for each variable between age and sex. Results Normative reference values for fat mass variables from DXA measurements obtained from GE-Healthcare DXA systems are presented as percentiles for both women and men in 10- year age groups. Women had higher (p\u3c0.01) mean %BF and FMI than men, whereas men had higher (p\u3c0.01) mean ratios of A/G, trunk/limb, and trunk/leg fat measurements than women

Comparison of Four Fitbit and Jawbone Activity Monitors with a Research-Grade ActiGraph Accelerometer for Estimating Physical Activity and Energy Expenditure

Background/aim Consumer-based physical activity (PA) monitors have become popular tools to track PA behaviours. Currently, little is known about the validity of the measurements provided by consumer monitors. We aimed to compare measures of steps, energy expenditure (EE) and active minutes of four consumer monitors with one research-grade accelerometer within a semistructured protocol. Methods Thirty men and women (18–80 years old) wore Fitbit One (worn at the waist), Fitbit Zip (waist), Fitbit Flex (wrist), Jawbone UP24 (wrist) and one waist-worn research-grade accelerometer (ActiGraph) while participating in an 80 min protocol. A validated EE prediction equation and active minute cut-points were applied to ActiGraph data. Criterion measures were assessed using direct observation (step count) and portable metabolic analyser (EE, active minutes). A repeated measures analysis of variance (ANOVA) was used to compare differences between consumer monitors, ActiGraph, and criterion measures. Similarly, a repeated measures ANOVA was applied to a subgroup of subjects who didn’t cycle. Results Participants took 3321±571 steps, had 28±6 active min and expended 294±56 kcal based on criterion measures. Comparatively, all monitors underestimated steps and EE by 13%–32% (p\u3c0.01); additionally the Fitbit Flex, UP24, and ActiGraph underestimated active minutes by 35%–65% (p\u3c0.05). Underestimations of PA and EE variables were found to be similar in the subgroup analysis. Conclusion Consumer monitors had similar accuracy for PA assessment as the ActiGraph, which suggests that consumer monitors may serve to track personal PA behaviours and EE. However, due to discrepancies among monitors, individuals should be cautious when comparing relative and absolute differences in PA values obtained using different monitors

A Pilot, Virtual Exercise Intervention Improves Health and Fitness during the COVID-19 Pandemic

International Journal of Exercise Science 15(7): 1395-1417, 2022. Physical activity levels are low in individuals with chronic disease (e.g., obesity) and have worsened during the COVID-19 pandemic. Purpose: Our pilot study tested a virtual exercise intervention for rural-dwelling adults with chronic disease from January-April 2021 for changes in mental health, physical fitness, and physical activity and for intervention fidelity. Methods: Participants (n = 8 [7 female]; age = 57.5 ± 13.8 years, body mass index = 38.2 ± 8.0 kg/m2) completed an exercise intervention led virtually by collegiate health science majors. Participants attended two 60-minute sessions/week for 12 weeks, completing individually-tailored and progressed aerobic and muscle-strengthening training. A non-randomized control group matched on gender and age continued normal activity during the 12 weeks. Changes in mental health, physical fitness, and physical activity measures were evaluated using a 2x2 (group x time) analysis of covariance. Results: Both groups improved mental health, but only intervention participants lost weight (3.1 ± 1.0 kg; no change in controls). Step test, arm curls, and chair stands improved by 16.1-20.6% in the intervention and 7.8-12.1% in the control groups. Intervention participants did not increase overall physical activity during or after the intervention. Intervention fidelity was high; participants attended ~73% of sessions and rated the sessions 4.7 ± 0.6 (out of 5). Researcher observations rated exercise sessions as meeting 12.7 ± 0.6 of 16 goals. Conclusions: Our virtual exercise program was associated with positive mental health and physical fitness changes. Such programs may provide a method, even beyond the pandemic, to improve fitness in adults with chronic disease

The Effect of Compression Socks on Maximal Exercise Performance and Recovery in Insufficiently Active Adults

International Journal of Exercise Science 14(7): 1036-1051, 2021. In athletic populations, compression socks (CS) may improve exercise performance recovery. However, their potential to improve performance and/or recovery following exercise in non-athletic populations is unknown. Our study evaluated the effects of CS on exercise performance and recovery from a graded maximal treadmill test. Insufficiently active adults (n = 10, 60% female, average physical activity ~60 minutes/week) performed two graded maximal exercise tests; one while wearing below-knee CS, and the other trial with regular socks (CON). Order of trials was randomized. For both trials, heart rate, lactate, and rating of perceived exertion were measured at each stage and at one, five, and ten- minutes post-exercise. Additionally, recovery variables (soreness, tightness, annoyingness, tenderness, pulling) were measured at 24 and 48 hours post-exercise using a visual analog scale. Paired-samples t-tests were used to compare exercise and recovery variables between CS and CON trials. Heart rate, lactate, and rating of perceived exertion were not different between trials for any stage during the exercise test or immediate recovery. Most 24- and 48-hour recovery variables were significantly improved after the CS trial, with values 34.6 - 42.3% lower at 24 hours and 40.3 - 61.4% lower at 48 hours compared to CON. Compression socks provided a significant and meaningful improvement in recovery variables 24-48 hours following maximal exercise. Therefore, CS may remove a common barrier to exercise adherence and facilitate more effective training recovery for insufficiently active adults

Glucose tolerance and physical fitness: An epidemiologic study in an entire community

A modification of the Harvard Step Test was administered to approximately 4700 males and females, age 10–69 in Tecumseh, Michigan. Heart rate response to this standardized exercise test is an estimate of capacity for muscular work. A blood sample was drawn 1 h after a glucose challenge on the same day the exercise test was given. Four skinfolds were measured as an index of body fatness. It was the purpose of this analysis to study the relationship of glucose tolerance to heart rate response to exercise.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47419/1/421_2004_Article_BF00421779.pd

Development of Cut-points for Determining Activity Intensity From a Wrist-worn ActiGraph Accelerometer in Free-living Adults

Despite recent popularity of wrist-worn accelerometers for assessing free-living physical behaviours, there is a lack of user-friendly methods to characterize physical activity from a wrist-worn ActiGraph accelerometer. Participants in this study completed a laboratory protocol and/or 3–8 hours of directly observed free-living (criterion measure of activity intensity) while wearing ActiGraph GT9X Link accel- erometers on the right hip and non-dominant wrist. All laboratory data (n = 36) and 11 participants’ free- living data were used to develop vector magnitude count cut-points (counts/min) for activity intensity for the wrist-worn accelerometer, and 12 participants’ free-living data were used to cross-validate cut-point accuracy. The cut-points were: \u3c2,860 counts/min (sedentary); 2,860–3,940 counts/min (light); and ≥3,941counts/min (moderate-to-vigorous (MVPA)). These cut-points had an accuracy of 70.8% for asses- sing free-living activity intensity, whereas Sasaki/Freedson cut-points for the hip accelerometer had an accuracy of 77.1%, and Hildebrand Euclidean Norm Minus One (ENMO) cut-points for the wrist accel- erometer had an accuracy of 75.2%. While accuracy was higher for a hip-worn accelerometer and for ENMO wrist cut-points, the high wear compliance of wrist accelerometers shown in past work and the ease of use of count-based analysis methods may justify use of these developed cut-points until more accurate, equally usable methods can be developed

Walking for Health During Pregnancy: A Literature Review and Considerations for Future Research

Walking is the most commonly chosen type of physical activity (PA) during pregnancy and provides several health benefits to both mother and child. National initiatives have promoted the importance of walking in general, but little emphasis is directed toward pregnant women, the majority of whom are insufficiently active. Pregnant women face a variety of dynamic barriers to a physically active lifestyle, some of which are more commonly experienced during specific times throughout the pregnancy experience. Walking is unique in that it appears resistant to a number of these barriers that limit other types of PA participation, and it can be meaningfully integrated into some transportation and occupational activities when leisure-time options are unavailable. Preliminary intervention work suggests that walking programs can be effectively adopted into a typical pregnancy lifestyle. However, a great deal of work remains to administer successful pregnancy walking interventions, including developing and using validated methods of PA and walking assessment. This narrative review discusses the unique advantages of walking during pregnancy, provides recommendations for future intervention work, and outlines the need for pregnancy-focused community walking initiatives.Standard search procedures were followed to determine sources from the literature specific to walking during pregnancy for use in each section of this review