Estimates Of Moderate-to-vigorous Physical Activity Research Articles

Evaluation of indoor activities for moderate-to-vigorous physical activity in preschoolers

ABSTRACT The study objectives were 1) to determine the feasibility and acceptability of indoor activities to achieve moderate-to-vigorous physical activity (MVPA) in preschoolers, and 2) compare MVPA estimates between direct observation (DO) and various accelerometry placements. In this cross-sectional study, 35 preschoolers (51% female, 54% 3-year-olds) performed six, 6-minute activities (dancing to video, balloon/bubbles, stationary exergame cycling, circuits, running-in-place, and cleaning up) in sequential order, facilitated by a trained staff member. Triaxial accelerometers (Actigraph Gt3×BT) at the ankle, waist, and wrist measured MVPA using age-specific cut-points. Total activity and MVPA time were quantified via DO of video recordings. Feasibility and acceptability were assessed via parent and child report. Preschoolers contributed 4339, 15-second epochs of accelerometry and DO data (~31.0 minutes/preschooler). Preschoolers achieved MVPA ≥ 50% of the time while engaging in balloon/bubbles, cycling, and circuits; but not while dancing to video (15%), running-in-place (48.5%), or cleaning up (8%). There were no differences in MVPA by age, sex, or between screen and non-screen activities. Parents and preschoolers reported most activities were feasible (≥4.0/5.0). Waist and ankle accelerometry had strong agreement with DO (ICCs range: 0.70–0.84) while wrist had fair to low agreement (ICCs: 0.22–0.58). Multiple indoor activities show promise to increase preschoolers’ MVPA.

Influence of Accelerometer Calibration on the Estimation of Objectively Measured Physical Activity: The Tromsø Study

Accelerometers are increasingly used to observe human behavior such as physical activity under free-living conditions. An important prerequisite to obtain reliable results is the correct calibration of the sensors. However, accurate calibration is often neglected, leading to potentially biased results. Here, we demonstrate and quantify the effect of accelerometer miscalibration on the estimation of objectively measured physical activity under free-living conditions. The total volume of moderate to vigorous physical activity (MVPA) was significantly reduced after post hoc auto-calibration for uniaxial and triaxial count data, as well as for Euclidean Norm Minus One and mean amplitude deviation raw data. Weekly estimates of MVPA were reduced on average by 5.5, 9.2, 45.8, and 4.8 min, respectively, when compared to the original uncalibrated estimates. Our results indicate a general trend of overestimating physical activity when using factory-calibrated sensors. In particular, the accuracy of estimates derived from the Euclidean Norm Minus One feature suffered from uncalibrated sensors. For all modalities, the more uncalibrated the sensor was, the more MVPA was overestimated. This might especially affect studies with lower sample sizes.

Convergent Validity Between Epoch-Based activPAL and ActiGraph Methods for Measuring Moderate to Vigorous Physical Activity in Youth and Adults

Purpose: We investigated convergent validity of commonly used ActiGraph scoring methods with various activPAL scoring methods in youth and adults. Methods: Youth and adults wore an ActiGraph and activPAL simultaneously for 1–3 days. We compared moderate to vigorous physical activity (MVPA) estimates from the ActiGraph Evenson 15-s (youth) and Freedson 60-s (adult) cut-point scoring methods and four activPAL scoring methods based on metabolic equivalents (METs), step counts, vertical axis counts, and vector magnitude counts. All activPAL methods were applied to 15-s epochs for youth and 60-s epochs for adults, and the METs method was also applied to 1-s epochs. Epoch-level agreement was examined with classification tests (sensitivity, positive predictive value, and F1) using the ActiGraph methods as the referent. Day-level agreement was examined using tests of mean error, mean absolute error, and Spearman correlations. Results: Relative to ActiGraph methods, which indicated a mean MVPA of 41 min/day for youth and 24 min/day for adults, the activPAL METs method applied to 15-s epochs in youth and 60-s epochs in adults yielded the most comparable estimates of MVPA. Daily MVPA estimated from all other activPAL scoring methods generally had poor agreement with ActiGraph methods in youth and adults. Conclusion: When using the same epoch lengths between monitors, MVPA estimation via the activPAL METs scoring method appears to have good comparability to ActiGraph cut points at the group-level and moderate comparability at the individual-level in youth and adults. When using this scoring method, the activPAL appears to be appropriate for measuring daily minutes of MVPA in youth and adults.

A consensus method for estimating physical activity levels in adults using accelerometry

ABSTRACT Identifying the best analytical approach for capturing moderate-to-vigorous physical activity (MVPA) using accelerometry is complex but inconsistent approaches employed in research and surveillance limits comparability. We illustrate the use of a consensus method that pools estimates from multiple approaches for characterising MVPA using accelerometry. Participants (n = 30) wore an accelerometer on their right hip during two laboratory visits. Ten individual classification methods estimated minutes of MVPA, including cut-point, two-regression, and machine learning approaches, using open-source count and raw inputs and several epoch lengths. Results were averaged to derive the consensus estimate. Mean MVPA ranged from 33.9–50.4 min across individual methods, but only one (38.9 min) was statistically equivalent to the criterion of direct observation (38.2 min). The consensus estimate (39.2 min) was equivalent to the criterion (even after removal of the one individual method that was equivalent to the criterion), had a smaller mean absolute error (4.2 min) compared to individual methods (4.9–12.3 min), and enabled the estimation of participant-level variance (mean standard deviation: 7.7 min). The consensus method allows for addition/removal of methods depending on data availability or field progression and may improve accuracy and comparability of device-based MVPA estimates while limiting variability due to convergence between estimates.

Accelerometer-Based Physical Activity Assessment During Intermittent Conditions: Effect of Epoch Length on Energy Expenditure Estimate

ABSTRACT Purpose: This study analyzed the effect of epoch length on energy expenditure (EE) estimates and on the moderate-to-vigorous physical activity (MVPA) measure obtained from EE estimates during accelerometer-based assessment. Methods: Ten active students exercised on a treadmill for four 5-min bouts, using two effort intensities (running and walking) and two physical activity (PA) patterns (continuous or intermittent) wearing an accelerometer. The criterion measure of EE was achieved using indirect calorimetry. Data obtained from the accelerometer were reintegrated into 1-sec, 10-sec, 30-sec and 60-sec epochs. Results: During the running intermittent condition, EE and MVPA estimates from the accelerometer were no different from the criterion measure with 30- and 60-sec epoch lengths but they were different with shorter epoch lengths. During the walking intermittent condition, no difference was observed between EE estimates and the criterion measure, regardless of the epoch length. During the running continuous condition, EE estimated from the accelerometer was significantly lower than the EE obtained with the criterion measure, regardless of the epoch length. During the walking continuous condition, no difference was observed. Conclusion: During the intermittent running condition, longer epoch lengths gave the best EE and MVPA estimates. This conclusion is contrary to the current general view that shorter epochs are the most accurate for PA assessment. However, PA estimates are closer to an external load estimates whereas EE estimates are closer to the internal load estimate. Depending on the objective of their study, researchers should be aware of these findings.

Temporal Trends in Children's School Day Moderate to Vigorous Physical Activity: A Systematic Review and Meta-Regression Analysis.

Evidence from a limited sample of countries indicates that time for physical education and recess during school have declined. Schools are called to provide children with 30minutes of moderate to vigorous physical activity (MVPA). This systematic review and meta-analysis estimated temporal trends in children's school day MVPA. Three online databases were searched to identify studies with objectively measured MVPA, during school hours, in school aged children (5-18y). Multilevel random-effects meta-analyses estimated MVPA by year, and meta-regression analyses estimated temporal trends in school day MVPA. Studies (N = 65) providing 171 MVPA estimates, representing 60,779 unique children, from 32 countries, and spanning 2003-2019 were identified. Most studies were conducted in North America (n = 33) or Europe (n = 21). School day MVPA ranged from 18.1 (95% confidence interval,15.1-21.1) to 47.1 (95% confidence interval,39.4-54.8) minutes per day in any given year. Meta-regression analyses indicated that MVPA declined from 2003 to 2010 (approximately 15min decline), plateaued from 2010 to 2015 (approximately 1min decrease), and increased from 2015 to 2019 (approximately 5min increase). School day MVPA decreased from 2003 to 2010 and has recently begun to increase. However, the majority of the evidence is from North America and Europe with some evidence from Oceania and very little evidence from Asia to South America.

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.

Changes in Device-Measured Physical Activity Patterns in U.K. Adults Related to the First COVID-19 Lockdown

The response to COVID-19 resulted in behavioral restrictions to tackle the spread of infection. Initial data indicates that step counts were impacted by lockdown restrictions; however, there is little evidence regarding changes of light and moderate to vigorous physical activity (MVPA) behavioral intensities. In this study, participants were asked to provide longitudinal wearable data from Fitbit devices over a period of 30 weeks, from December 2019 to June 2020. Self-assessed key worker status was captured, along with wearable estimates of steps, light activity, and MVPA. Bayesian change point analyses of data from 97 individuals found that there was a sharp decrease of 1,473 steps (95% credible interval [CI] [−2,218, −709]) and light activity minutes (41.9; 95% CI [−54.3, −29.3]), but an increase in MVPA minutes (11.7; 95% CI [2.9, 19.4]) in the mean weekly totals for nonkey workers. For the key workers, the total number of steps (207; 95% CI [−788, 1,456]) and MVPA minutes increased (20.5; 95% CI [12.6, 28.3]) but light activity decreased by an average of 46.9 min (95% CI [−61.2, −31.8]). Interestingly, the change in steps was commensurate with that observed during Christmas (1,458; 95% CI [−2,286, −554]) for nonkey workers and behavioral changes occurred at different time points and rates depending on key worker status. Results indicate that there were clear behavioral modifications before and during the initial COVID-19 lockdown period, and future research should assess whether any behavioral modifications were sustained over time.

A Multi-Level Analysis of the Effects of Epoch Length on the Estimates of Children’s Moderate to Vigorous Physical Activity

Using an ActiGraph GT3X+ accelerometer, the study examined the effects of different epoch lengths on children’s moderate to vigorous physical activity (MVPA). The study also tested how different MVPA levels influence the relationship between epoch length and MVPA. The participants included third (n = 28) and fourth grade (n = 35) students. The third graders participated in a physical education class while the fourth graders were engaged in an active video game (AVG) class. Data were downloaded using six different epoch lengths. MVPA estimates were determined by five different cut points. Multi-level analyses were used to analyze the data. Results showed that when lower cut points were used, MVPA was positively related to epoch lengths, and this relationship was stronger when the MVPA level was higher. When higher cut points were used, epoch length was negatively related to MVPA, and this relationship was stronger when the MVPA level was lower. This study revealed that different epoch lengths generate various estimates of MVPA, and the relationship between epoch length and MVPA is affected by MVPA levels.

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.

Feasibility Study Comparing Physical Activity Classifications from Accelerometers with Wearable Camera Data.

Device-based assessments are frequently used to measure physical activity (PA) but contextual measures are often lacking. There is a need for new methods, and one under-explored option is the use of wearable cameras. This study tested the use of wearable cameras in PA measurement by comparing intensity classifications from accelerometers with wearable camera data. Seventy-eight 18–30-year-olds wore an Actigraph GT9X link accelerometer and Autographer wearable camera for three consecutive days. An image coding schedule was designed to assess activity categories and activity sub-categories defined by the 2011 Compendium of Physical Activities (Compendium). Accelerometer hourly detailed files processed using the Montoye (2020) cut-points were linked to camera data using date and time stamps. Agreement was examined using equivalence testing, intraclass correlation coefficient (ICC) and Spearman’s correlation coefficient (rho). Fifty-three participants contributing 636 person-hours were included. Reliability was moderate to good for sedentary behavior (rho = 0.77), light intensity activities (rho = 0.59) and moderate-to-vigorous physical activity (MVPA) (rho = 0.51). The estimates of sedentary behavior, light activity and MVPA from the two methods were similar, but not equivalent. Wearable cameras are a potential complementary tool for PA measurement, but practical challenges and limitations exist. While wearable cameras may not be feasible for use in large scale studies, they may be feasible in small scale studies where context is important.

Accelerometer output and its association with energy expenditure in persons with mild-to-moderate Parkinson's disease.

ObjectiveThis study examined the association between ActiGraph accelerometer output and energy expenditure across different speeds of walking in persons with Parkinson’s disease (PD), and further generated cut-points that represent a metric for quantifying time spent in moderate-to-vigorous physical activity (MVPA) among persons with PD.MethodsThe sample included 30 persons with mild-to-moderate PD (Hoehn and Yahr stages 2–3) and 30 adults without PD matched by sex and age. All participants completed 5 minutes of quiet, seated rest and then underwent three, 6-minute bouts of walking on a treadmill at three different speeds relative to the individual’s self-selected pace. Activity counts were measured using an ActiGraph accelerometer worn at the waist level on the least affected side for persons with PD and the dominant side for controls. The rate of oxygen consumption, or energy expenditure, was measured using a portable, open-circuit spirometry system.ResultsOur results indicated a strong association between activity counts and energy expenditure for persons with PD (R2 = 0.87) and controls (R2 = 0.89). However, the significant difference in slopes resulted in a lower cut-point of 1,354 counts·min-1 for persons with PD than the cut-point of 2,010 counts·min-1 for controls.ConclusionOur results support the application of the disease-specific cut-point for quantifying the amount of time spent in MVPA using ActiGraph accelerometers among persons with mild-to-moderate PD. Such an application may provide accurate estimates of MVPA in this population, and better inform future research examining the possible determinants and consequences of physical activity as well as testing of interventions for changing MVPA in PD.

Accelerometer-derived Physical Activity Estimates And Daily Wear Time In Children

Most of the studies applying the accelerometers to quantify physical activity (PA) and sedentary time (ST) require participants to wear the devices during waking hours only. There is no consensus on how many wearing hours are enough to reflect daily activity behavior in free-living conditions. Whether wear time has substantial impact on accelerometer-based estimates remains unclear. PURPOSE: To examine whether accelerometer-derived metrics were dependent on daily wear time. METHODS: Baseline data from 120 children (24.2% boys) aged 8 to 11 years who participated in the longitudinal study on active travel were analyzed. They were instructed to wear an ActiGraph wGT3x accelerometry on the waist for 7 to 10 consecutive days, only removing it while swimming and bathing. Accelerometer-derived metrics included daily wear time, total activity counts (TAC), ST, light-intensity PA (LPA), moderate-intensity PA (MPA), vigorous-intensity PA (VPA), moderate-to-vigorous PA (MVPA), moderate-to-vigorous PA (MVPA) bouts ≥ 10 minutes (MVPA-10), and proportion of VPA within MVPA (%VPA). Linear mixed models were performed to examine the relationships of these metrics with daily wear time which was categorized into quarters. RESULTS: Majority of the children (96%) provided at least 3 valid accelerometer wear days (defined as ≥ 480 minutes of valid wear time per day), with a total of 797 valid wear days included in analyses. After adjustment for age, sex, and body mass index, none of the PA metrics was completely independent on wear time. A linear relationship was found between wear time and four PA metrics including TAC, MPA, LPA, and ST. However, MVPA estimates were comparable between the first (8 to 11 hours per day) and second quarters (11 to 13 hours per day) of wear time (mean ± standard error: 31.4 ± 1.8 vs 35.7 ± 1.8 minutes, NS). Similar results were found for MVPA-10, VPA, and %VPA. CONCLUSIONS: Accelerometer-derived PA metrics were largely dependent on wear time. MVPA minutes seem to be comparable across wear time of 13 hours per day or less. Comparisons of accelerometer-derived PA estimates between studies need to be cautious and taken into account of differences in wear duration.

Comparison Between Fitbit Flex And Flex 2: Measures Of Sedentary And Physical Activity In Free-living

In recent years, Fitbit has been increasingly used as a measurement or intervention tool in physical activity research. However, Fitbit’s shorter lifespan of model generation than research-based accelerometers may limit its utilization in the longitudinal study if measurement properties vary across model generations. To date, no information is available whether the estimates of sedentary behavior (SED) and physical activity (PA) differ between predecessor and newer models of Fitbit. PURPOSE: To determine the inter-model comparability between FF and FF2 in assessing SED and PA during free-living conditions. METHODS: 38 healthy adults (Female: 65.8%, Age: 23.8 ± 0.8 yrs, BMI: 25.0 ± 24.6 kg/m2) wore the FF and FF2 on non-dominant wrist for seven consecutive days. Raw data of FF and FF2 were converted to activity counts summarized into minutes of SED and moderate-to-vigorous PA (MVPA) using a proprietary algorithm. Spearman’s correlation was used to assess the relationship between the estimates from FF and FF2. Paired t-test and mean absolute percent error (MAPE) were used to examine differences between FF and FF2. Bland-Altman (BA) plots were used to examine bias for agreement and variance between two devices. RESULTS: The correlation showed a strong relationship (r = 0.81, P < 0.01) between FF and FF2 for estimating in total daily activities. FF2 yielded almost identical MVPA estimate (mean difference = 0.04 min/day, p = 0.94), but 8.8 min/day higher SED estimate (p < 0.01) when compared with FF. MAPEs were relatively lower for both SED (0.8 ± 0.8%) and MVPA (9.1 ± 9.9%). BA plots showed no apparent bias for the agreement and variance between the estimates from two devices; SED (limits of agreement: - 9.9 ~ 27.1 min/day, Pitman’s test: r = - 0.14, P = 1.51) and MVPA (- 5.7 ~ 5.8 min/day, r = -0.36, P = 1.94) estimates. CONCLUSION: Findings from this study showed that the estimates of SED and MVPA were similar between FF and FF2. Therefore, Fitbit Flex models can provide comparable estimates in SED and PA between models. Further, we suggest that researchers can choose FF2 as a measurement of PA when FF is not available in the market during the longitudinal PA research.

Modifying Accelerometer Cut-Points Affects Criterion Validity in Simulated Free-Living for Adolescents and Adults

ABSTRACT Purpose: To assess changes in criterion validity when modifying cut-points for use in different epoch lengths. Method: Simulated free-living data came from 42 adolescents (2-hr each) and 29 adults (6-hr each) wearing a hip-worn accelerometer and portable indirect calorimeter (Cosmed K4b2). K4b2 data were classified as sedentary behavior (SB), light physical activity (LPA), or moderate-to-vigorous physical activity (MVPA), and compared to estimates from accelerometer data processed with three youth and three adult cut-points in six epoch lengths (1, 5, 10, 15, 30, and 60-s). A cut-point of 100 counts per minute was used for all SB estimates. Results: For both adolescents and adults, SB estimates in all but 60-s epochs were significantly higher than the criterion, by 18.4%–78.4% (all p < .02). CPS had varied effects on youth LPA, ranging from favorable effects for one cut-point (1.9% underestimation in 1-s epochs, versus 40.2% overestimation in the originally-calibrated epoch length; p < .01 and p = .91, respectively) to unfavorable effects for another (41.8% underestimation in 1-s epochs, versus 9.8% underestimation in the originally-calibrated epoch length; p < .01 and p = .39, respectively). Adult LPA estimates in 30-s or 60-s epochs were closest to the criterion (within 5.2%–37.3%, p = .0001–0.49). Youth MVPA estimates in 60-s epochs were closest to the criterion (within 9.5%–53.2%, all p < .05), whereas adult MVPA estimates in 1-s epochs were closest to the criterion (within 6.6%–34.2%, p = .02–0.59). Conclusion: Cut-point modification is not universally beneficial, and thus it is not recommended.

Validating Fitbit for Evaluation of Physical Activity in Patients with Knee Osteoarthritis: Do Thresholds Matter?

ObjectiveWe sought to evaluate the performance of Fitbit in estimating ActiGraph‐derived moderate‐to‐vigorous physical activity (MVPA) and sedentary time in the knee osteoarthritis (OA) population.MethodsWe used data from two weeks of Fitbit and ActiGraph wear among knee OA subjects. In primary analyses, we used literature‐based ActiGraph thresholds of 200 and 1924 counts/min (triaxial vector magnitude) for sedentary and MVPA time as the gold standard to which we compared three sets of Fitbit thresholds informed by literature and data (Youden index). We also considered personalized, stride length–based Fitbit thresholds. In sensitivity analyses, we used uniaxial, vertical axis–based as well as personalized, BMI‐based ActiGraph thresholds. We calculated agreement, sensitivity, and specificity of Fitbit in classifying sedentary and MVPA time.ResultsIn the primary analysis (vector magnitude thresholds), maximum agreement for sedentary and MVPA time was 67.0% from the Youden index–based and 91.1% from the stride length–based Fitbit thresholds. For sedentary time, the 20 strides/min threshold had the highest sensitivity (97.6%), and Youden‐derived 1 stride/min had the highest specificity (51.6%). For MVPA, Youden‐derived 14 strides/min yielded 72.8% sensitivity, and using stride length yielded 98.6% specificity. MVPA time ranged from 49‐323 min/d, depending on threshold used, with literature‐based and personalized thresholds leading to more conservative estimates of MVPA than Youden‐derived thresholds.ConclusionUsing Fitbit for MVPA and sedentary time assessment may lead to inaccurate estimates of both. Fitbit MVPA estimates were generally more conservative than ActiGraph estimates. Incorporating individuals’ characteristics did not meaningfully improve Fitbit performance. Caution should be exercised when measuring activity using Fitbit.

Calibration and Validation of the Youth Activity Profile as a Physical Activity and Sedentary Behaviour Surveillance Tool for English Youth.

Self-reported youth physical activity (PA) is typically overestimated. We aimed to calibrate and validate a self-report tool among English youth. Four-hundred-and-two participants (aged 9–16 years; 212 boys) wore SenseWear Armband Mini devices (SWA) for eight days and completed the self-report Youth Activity Profile (YAP) on the eighth day. Calibration algorithms for temporally matched segments were generated from the YAP data using quantile regression. The algorithms were applied in an independent cross-validation sample, and student- and school-level agreement were assessed. The utility of the YAP algorithms to assess compliance to PA guidelines was also examined. The school-level bias for the YAP estimates of in-school, out-of-school, and weekend moderate-to-vigorous PA (MVPA) were 17.2 (34.4), 31.6 (14.0), and −4.9 (3.6) min·week−1, respectively. Out-of-school sedentary behaviour (SB) was over-predicted by 109.2 (11.8) min·week−1. Predicted YAP values were within 15%–20% equivalence of the SWA estimates. The classification accuracy of the YAP MVPA estimates for compliance to 60 min·day−1 and 30 min·school-day−1 MVPA recommendations were 91%/37% and 89%/57% sensitivity/specificity, respectively. The YAP generated robust school-level estimates of MVPA and SB and has potential for surveillance to monitor compliance with PA guidelines. The accuracy of the YAP may be further improved through research with more representative UK samples to enhance the calibration process and to refine the resultant algorithms.

Concurrent validity of the Fitbit for assessing sedentary behavior and moderate-to-vigorous physical activity

BackgroundRecent advances in sensor technologies have promoted the use of consumer-based accelerometers such as Fitbit Flex in epidemiological and clinical research; however, the validity of the Fitbit Flex in measuring sedentary behavior (SED) and physical activity (PA) has not been fully determined against previously validated research-grade accelerometers such as ActiGraph GT3X+. Therefore, the purpose of this study was to examine the concurrent validity of the Fitbit Flex against ActiGraph GT3X+ in a free-living condition.MethodsA total of 65 participants (age: M = 42, SD = 14 years, female: 72%) each wore a Fitbit Flex and GT3X+ for seven consecutive days. After excluding sleep and non-wear time, time spent (min/day) in SED and moderate-to-vigorous PA (MVPA) were estimated using various cut-points for GT3X+ and brand-specific algorithms for Fitbit, respectively. Repeated measures one-way ANOVA and mean absolute percent errors (MAPE) served to examine differences and measurement errors in SED and MVPA estimates between Fitbit Flex and GT3X+, respectively. Pearson and Spearman correlations and Bland-Altman (BA) plots were used to evaluate the association and potential systematic bias between Fitbit Flex and GT3X+. PROC MIXED procedure in SAS was used to examine the equivalence (i.e., the 90% confidence interval with ±10% equivalence zone) between the devices.ResultsFitbit Flex produced similar SED and low MAPE (mean difference [MD] = 37 min/day, P = .21, MAPE = 6.8%), but significantly higher MVPA and relatively large MAPE (MD = 59–77 min/day, P < .0001, MAPE = 56.6–74.3%) compared with the estimates from GT3X+ using three different cut-points. The correlations between Fitbit Flex and GT3X+ were consistently higher for SED (r = 0.90, ρ = 0.86, P < .01), but weaker for MVPA (r = 0.65–0.76, ρ = 0.69–0.79, P < .01). BA plots revealed that there is no apparent bias in estimating SED.ConclusionIn comparison with the GT3X+ accelerometer, the Fitbit Flex provided comparatively accurate estimates of SED, but the Fitbit Flex overestimated MVPA under free-living conditions. Future investigations using the Fitbit Flex should be aware of present findings.

Methods for Activity Monitor Validation Studies: An Example With the Fitbit Charge

Purpose: To advance research practices with consumer monitors, standard validation methods are needed. This study provides an example of best practices through systematically evaluating the validity of the Fitbit Charge (FBC) under free-living conditions using a strong reference measure and robust measurement agreement methods. Methods: 94 healthy participants (Mage 41.8 ±9.3 yrs) wore a FBC and two research grade accelerometers (Actigraph GT3X and activPAL) as they went about normal activities for a week. Estimated daily minutes of moderate to vigorous physical activity (MVPA) from the FBC were compared against reference estimates obtained from the Sojourns Including Posture (SIP) methodology, while daily step counts were compared against the activPAL. Results: Correlations with reference indicators were high for average daily MVPA (r = 0.8; p &lt; .0001) and steps (r = 0.76; p &lt; .0001), but the FBC overestimated time spent in MVPA by 56% and steps by 15%. The mean absolute percent errors of MVPA and steps estimated by FBC were 71.5% and 30.0%, respectively. Neither of the MVPA and step estimates from the FBC fell into the ±10% equivalence zone set by the criterion. The Kappa statistics of the classification agreement between the two MVPA assessment methods was 0.32 with a low sensitivity of 30.1% but a high specificity of 96.7%. Conclusion: The FBC overestimated minutes of MVPA and steps when compared to both reference assessments in free-living conditions. Standardized reporting in future studies will facilitate comparisons with other monitors and with future versions of the FBC.

Adiposity, fitness, health-related quality of life and the reallocation of time between children's school day activity behaviours: A compositional data analysis

Sedentary time (ST), light (LPA), and moderate-to-vigorous physical activity (MVPA) constitute the range of school day activity behaviours. This study investigated whether the composition of school activity behaviours was associated with health indicators, and the predicted changes in health when time was reallocated between activity behaviours. Accelerometers were worn for 7-days between October and December 2010 by 318 UK children aged 10–11, to provide estimates of school day ST, LPA, and MVPA. BMI z-scores and percent waist-to-height ratio were calculated as indicators of adiposity. Cardiorespiratory fitness (CRF) was assessed using the 20-m shuttle run test. The PedsQL™ questionnaire was completed to assess psychosocial and physical health-related quality of life (HRQL). Log-ratio multiple linear regression models predicted health indicators for the mean school day activity composition, and for new compositions where fixed durations of time were reallocated from one activity behaviour to another, while the remaining behaviours were unchanged. The school day activity composition significantly predicted adiposity and CRF (p = 0.04–0.002), but not HRQL. Replacing MVPA with ST or LPA around the mean activity composition predicted higher adiposity and lower CRF. When ST or LPA were substituted with MVPA, the relationships with adiposity and CRF were asymmetrical with favourable, but smaller predicted changes in adiposity and CRF than when MVPA was replaced. Predicted changes in HRQL were negligible. The school day activity composition significantly predicted adiposity and CRF but not HRQL. Reallocating time from ST and LPA to MVPA is advocated through comprehensive school physical activity promotion approaches. Trial registrationISRCTN03863885.