Objectively Measured Sedentary Behavior in Preschool Children: Comparison Between Montessori and Traditional Preschools

Background: This study aimed to compare the levels of objectively-measured sedentary behavior in children attending Montessori preschools with those attending traditional preschools. Methods: The participants in this study were preschool children aged 4 years old who were enrolled in Montessori and traditional preschools. The preschool children wore ActiGraph accelerometers. Accelerometers were initialized using 15-second intervals and sedentary behavior was defined as/15-second. The accelerometry data were summarized into the average minutes per hour spent in sedentary behavior during the in-school, the afterschool, and the total-day period. Mixed linear regression models were used to determine differences in the average time spent in sedentary behavior between children attending traditional and Montessori preschools, after adjusting for selected potential correlates of preschoolers’ sedentary behavior. Results: Children attending Montessori preschools spent less time in sedentary behavior than those attending traditional preschools during the in-school (44.4. min/hr vs. 47.1 min/hr, P=0.03), after-school (42.8. min/hr vs. 44.7 min/hr, P=0.04), and total-day (43.7 min/hr vs. 45.5 min/hr, P = 0. 009) periods. School type (Montessori or traditional), preschool setting (private or public), socio-demographic factors (age, gender, and socioeconomic status) were found to be significant predictors of preschoolers’ sedentary behavior. Conclusions: Levels of objectively-measured sedentary behavior were significantly lower among children attending Montessori preschools compared to children attending traditional preschools. Future research should examine the specific characteristics of Montessori preschools that predict the lower levels of sedentary behavior among children attending these preschools compared to children attending traditional preschools

Comparison of Wearable Trackers’ Ability to Estimate Sleep

Tracking physical activity and sleep patterns using wearable trackers has become a current trend. However, little information exists about the comparability of wearable trackers measuring sleep. This study examined the comparability of wearable trackers for estimating sleep measurement with a sleep diary (SD) for three full nights. A convenience sample of 78 adults were recruited in this research with a mean age of 27.6... 11.0 years. Comparisons between wearable trackers and sleep outcomes were analyzed using the mean absolute percentage errors, Pearson correlations, Bland–Altman Plots, and equivalent testing. Trackers that showed the greatest equivalence with the SD for total sleep time were the Jawbone UP3 and Fitbit Charge Heart Rate (effect size = 0.09 and 0.23, respectively). The greatest equivalence with the SD for time in bed was seen with the SenseWear Armband, Garmin Vivosmart, and Jawbone UP3 (effect size = 0.09, 0.16, and 0.07, respectively). Some of the wearable trackers resulted in closer approximations to self-reported sleep outcomes than a previously sleep research-grade device, these trackers offer a lower-cost alternative to tracking sleep in healthy populations

Associations Between Screen-Based Sedentary Behavior and Cardiovascular Disease Risk Factors in Korean Youth

The purposes of this study were to: 1) describe the patterns of screen-based sedentary behaviors, and 2) examine the association between screen-based sedentary behavior and cardiovascular disease (CVD) risk factors in representative Korean children and adolescents, aged 12 to 18 yr, in the Korean National Health and Nutrition Examination Survey. Screen-based sedentary behavior was measured using self-report questionnaires that included items for time spent watching TV and playing PC/video games. Physical activity was measured using items for frequency and duration of moderate-to-vigorous physical activity (MVPA). CVD risk factors such as body mass index (BMI), waist circumference, LDL cholesterol, HDL cholesterol, total cholesterol, triglycerides, glucose, systolic blood pressure, and diastolic blood pressure were measured. Boys spent more time playing PC/video games, and girls spent more time watching TV. After adjusting for age, gender, annual household income, and MVPA, an additional hour of watching TV was significantly associated with the risk of overweight (OR 1.17 [95% CI 1.03-1.33]), high abdominal adiposity (OR 1.27 [1.06-1.51]), and low HDL cholesterol (OR 1.27 [1.10-1.47]). An additional hour spent playing PC/video games also increased the risk of high abdominal adiposity (OR 1.20 [1.03-1.40]). Prospective observations and interventions are needed to determine causal relationships between screen-based sedentary behavior and CVD risk profiles in Korean youth

Sedentary Behavior in Preschoolers: How Many Days of Accelerometer Monitoring Is Needed?

The reliability of accelerometry for measuring sedentary behavior in preschoolers has not been determined, thus we determined how many days of accelerometry monitoring are necessary to reliably estimate daily time spent in sedentary behavior in preschoolers. In total, 191 and 150 preschoolers (three to five years) wore ActiGraph accelerometers (15-s epoch) during the in-school (≥4 days) and the total-day (≥6 days) period respectively. Accelerometry data were summarized as time spent in sedentary behavior (min/h) using three different cutpoints developed for preschool-age children

The Association of Virtual Exercise Classes and Well-Being During COVID-19 Among University Employees

This cross-sectional study sought to examine the association of virtual exercise with physical activity (PA), general, and mental health during COVID-19 among university employees. Individuals completed an online survey with questions about demographic, sleep, substance use, and virtual exercise participation. The International Physical Activity Questionnaire and 36-Item Short Form Health Survey assessed PA, general, and mental health. Data were analyzed for descriptive, correlation, and multiple regression models. Complete data were collected from 122 participants with a mean age of 45.6±13.1 years. Participation in virtual exercise were highest for twice a week (24.6%) followed by once a month (17.2%) and never (17.2%). Over a quarter of participants reported an increase (29.1%) in alcohol use. No significant differences were found in total MET-min between before (1952 ± 1373) and during-COVID (1973 ± 1692) (p \u3e .05); however, virtual exercise participation significantly associated with an increase in PA (β = 609.08, p=.01). Statistically significant positive relationships were also found between higher PA and better general health (β = .005, p \u3c 0.01), and emotional well-being (β = .004, p \u3c .05). Self-reported COVID disruptiveness was negatively associated with emotional well-being (β = -3.28, p \u3c 0.001). This data suggested that virtual exercise courses were associated with maintaining PA which may indirectly regulate general and mental well-being during the pandemic for university employees

Validation of the Apple Watch for Estimating Moderate-to-Vigorous Physical Activity and Activity Energy Expenditure in School-Aged Children.

The Apple Watch is one of the most popular wearable devices designed to monitor physical activity (PA). However, it is currently unknown whether the Apple Watch accurately estimates children's free-living PA. Therefore, this study assessed the concurrent validity of the Apple Watch 3 in estimating moderate-to-vigorous physical activity (MVPA) time and active energy expenditure (AEE) for school-aged children under a simulated and a free-living condition. Twenty elementary school students (Girls: 45%, age: 9.7 ± 2.0 years) wore an Apple Watch 3 device on their wrist and performed prescribed free-living activities in a lab setting. A subgroup of participants (N = 5) wore the Apple Watch for seven consecutive days in order to assess the validity in free-living condition. The K5 indirect calorimetry (K5) and GT3X+ were used as the criterion measure under simulated free-living and free-living conditions, respectively. Mean absolute percent errors (MAPE) and Bland-Altman (BA) plots were conducted to assess the validity of the Apple Watch 3 compared to those from the criterion measures. Equivalence testing determined the statistical equivalence between the Apple Watch and K5 for MVPA time and AEE. The Apple Watch provided comparable estimates for MVPA time (mean bias: 0.3 min, p = 0.91, MAPE: 1%) and for AEE (mean bias: 3.8 kcal min, p = 0.75, MAPE: 4%) during the simulated free-living condition. The BA plots indicated no systematic bias for the agreement in MVPA and AEE estimates between the K5 and Apple Watch 3. However, the Apple Watch had a relatively large variability in estimating AEE in children. The Apple Watch was statistically equivalent to the K5 within ±17.7% and ±20.8% for MVPA time and AEE estimates, respectively. Our findings suggest that the Apple Watch 3 has the potential to be used as a PA assessment tool to estimate MVPA in school-aged children

Inter-Device Agreement between Fitbit Flex 1 and 2 for Assessing Sedentary Behavior and Physical Activity.

This study examined the inter-model agreement between the Fitbit Flex (FF) and FF2 in estimating sedentary behavior (SED) and physical activity (PA) during a free-living condition. 33 healthy adults wore the FF and FF2 on non-dominant wrist for 14 consecutive days. After excluding sleep and non-wear time, data from the FF and FF2 was converted to the time spent (min/day) in SED and PA using a proprietary algorithm. Pearson's correlation was used to evaluate the association between the estimates from FF and FF2. Mean absolute percent errors (MAPE) were used to examine differences and measurement agreement in SED and PA estimates between FF and FF2. Bland-Altman (BA) plots were used to examine systematic bias between two devices. Equivalence testing was conducted to examine the equivalence between the FF and FF2. The FF2 had strong correlations with the FF in estimating SED and PA times. Compared to the FF, the FF2 yielded similar SED and PA estimates along with relatively low measurement discords and did not have significant systematic biases for SED and Moderate-to-vigorous PA estimates. Our findings suggest that researchers may choose FF2 as a measurement of SED and PA when FF is not available in the market during the longitudinal PA research

Equating Accelerometer Estimates of Moderate-to-Vigorous Physical Activity: In Search of the Rosetta Stone

Purpose - No universally accepted ActiGraph accelerometer cutpoints for quantifying moderate-to-vigorous physical activity (MVPA) exist. Estimates of MVPA from one set of cutpoints cannot be directly compared to MVPA estimates using different cutpoints, even when the same outcome units are reported (MVPA min•d-1). The purpose of this study was to illustrate the utility of an equating system that translates reported MVPA estimates from one set of cutpoints into another, to better inform public health policy. Design - Secondary data analysis. Methods - ActiGraph data from a large preschool project (N=419, 3-6yr-olds, CHAMPS) was used to conduct the analyses. Conversions were made among five different published MVPA cutpoints for children: Pate (PT), Sirard (SR), Puyau (PY), Van Cauwengerghe (VC), and Freedson Equation (FR). A 10 fold cross-validation procedure was used to develop prediction equations using MVPA estimated from each of the five sets of cutpoints as the dependent variable, with estimated MVPA from one of the other four sets of cutpoints (e.g., PT MVPA predicted from FR MVPA). Results - The mean levels of MVPA for the total sample ranged from 22.5 (PY) to 269.0 (FR) min•d-1. Across the prediction models (5 total), the median proportion of variance explained (R2) was 0.76 (range 0.48-0.97). The median absolute percent error was 17.2% (range 6.3%-38.4%). Conclusion - The prediction equations developed here allow for direct comparisons between studies employing different ActiGraph cutpoints in preschool-age children. These prediction equations give public health researchers and policy makers a more concise picture of physical activity levels of preschool-aged children

The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings.

MotionSense HRV is a wrist-worn accelerometery-based sensor that is paired with a smartphone and is thus capable of measuring the intensity, duration, and frequency of physical activity (PA). However, little information is available on the validity of the MotionSense HRV. Therefore, the purpose of this study was to assess the concurrent validity of the MotionSense HRV in estimating sedentary behavior (SED) and PA. A total of 20 healthy adults (age: 32.5 ± 15.1 years) wore the MotionSense HRV and ActiGraph GT9X accelerometer (GT9X) on their non-dominant wrist for seven consecutive days during free-living conditions. Raw acceleration data from the devices were summarized into average time (min/day) spent in SED and moderate-to-vigorous PA (MVPA). Additionally, using the Cosemed K5 indirect calorimetry system (K5) as a criterion measure, the validity of the MotionSense HRV was examined in simulated free-living conditions. Pearson correlations, mean absolute percent errors (MAPE), Bland-Altman (BA) plots, and equivalence tests were used to examine the validity of the MotionSense HRV against criterion measures. The correlations between the MotionSense HRV and GT9X were high and the MAPE were low for both the SED (r = 0.99, MAPE = 2.4%) and MVPA (r = 0.97, MAPE = 9.1%) estimates under free-living conditions. BA plots illustrated that there was no systematic bias between the MotionSense HRV and criterion measures. The estimates of SED and MVPA from the MotionSense HRV were significantly equivalent to those from the GT9X; the equivalence zones were set at 16.5% for SED and 29% for MVPA. The estimates of SED and PA from the MotionSense HRV were less comparable when compared with those from the K5. The MotionSense HRV yielded comparable estimates for SED and PA when compared with the GT9X accelerometer under free-living conditions. We confirmed the promising application of the MotionSense HRV for monitoring PA patterns for practical and research purposes

Cardiorespiratory fitness and risk of prostate cancer: Findings from the Aerobics Center Longitudinal Study

Objective - To examine the association between cardiorespiratory (CRF) and risk of incident prostate cancer (PrCA). Methods - Participants were 19,042 male subjects in the Aerobics Center Longitudinal Study (ACLS), ages 20 to 82 years, who received a baseline medical examination including a maximal treadmill exercise test between 1976 and 2003. CRF levels were defined as low (lowest 20%), moderate (middle 40%), and high (upper 40%) according to age-specific distribution of treadmill duration from the overall ACLS population. PrCA was assessed from responses to mail-back health surveys during 1982 to 2004. Cox proportional hazards regression models, adjusted for potential confounders, were used to compute hazard ratios (HRs), 95% confidence intervals (95% CIs), and incidence rates (per 10,000 person-years of follow-up). Results - A total of 634 men reported a diagnosis of incident PrCA during an average of 9.3 ± 7.1 years of follow-up. Adjusted HRs (95% CIs) in men with moderate and high CRF relative to low CRF were, 1.68 (1.13-2.48) and 1.74 (1.15-.2.62), respectively. The positive association between CRF and PrCA was observed only in the strata of men who were not obese, had ≥ 1 follow-up examination, or who were diagnosed ≤ 1995. Conclusions - Rather than revealing a causal relationship, the unexpected positive association observed between CRF and incident PrCA is most likely due to a screening/detection bias in more fit men who also are more health conscious. Results have important implications for understanding the health-related factors that predispose men to receive PrCA screening that may lead to over-detection of indolent disease