Equating accelerometer estimates among youth: The Rosetta Stone 2

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

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.

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

BACKGROUND

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 30 minutes of moderate to vigorous physical activity (MVPA). This systematic review and meta-analysis estimated temporal trends in children's school day MVPA.

METHODS

Three online databases were searched to identify studies with objectively measured MVPA, during school hours, in school aged children (5-18 y). Multilevel random-effects meta-analyses estimated MVPA by year, and meta-regression analyses estimated temporal trends in school day MVPA.

RESULTS

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 15 min decline), plateaued from 2010 to 2015 (approximately 1 min decrease), and increased from 2015 to 2019 (approximately 5 min increase).

CONCLUSIONS

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.

Children's moderate-to-vigorous physical activity on weekdays versus weekend days: a multi-country analysis

Purpose

The Structured Days Hypothesis (SDH) posits that children’s behaviors associated with obesity – such as physical activity – are more favorable on days that contain more ‘structure’ (i.e., a pre-planned, segmented, and adult-supervised environment) such as school weekdays, compared to days with less structure, such as weekend days. The purpose of this study was to compare children’s moderate-to-vigorous physical activity (MVPA) levels on weekdays versus weekend days using a large, multi-country, accelerometer-measured physical activity dataset.

Methods

Data were received from the International Children’s Accelerometer Database (ICAD) July 2019. The ICAD inclusion criteria for a valid day of wear, only non-intervention data (e.g., baseline intervention data), children with at least 1 weekday and 1 weekend day, and ICAD studies with data collected exclusively during school months, were included for analyses. Mixed effects models accounting for the nested nature of the data (i.e., days within children) assessed MVPA minutes per day (min/day MVPA) differences between weekdays and weekend days by region/country, adjusted for age, sex, and total wear time. Separate meta-analytical models explored differences by age and country/region for sex and child weight-status.

Results/findings

Valid data from 15 studies representing 5794 children (61% female, 10.7 ± 2.1 yrs., 24% with overweight/obesity) and 35,263 days of valid accelerometer data from 5 distinct countries/regions were used. Boys and girls accumulated 12.6 min/day (95% CI: 9.0, 16.2) and 9.4 min/day (95% CI: 7.2, 11.6) more MVPA on weekdays versus weekend days, respectively. Children from mainland Europe had the largest differences (17.1 min/day more MVPA on weekdays versus weekend days, 95% CI: 15.3, 19.0) compared to the other countries/regions. Children who were classified as overweight/obese or normal weight/underweight accumulated 9.5 min/day (95% CI: 6.9, 12.2) and 10.9 min/day (95% CI: 8.3, 13.5) of additional MVPA on weekdays versus weekend days, respectively.

Conclusions

Children from multiple countries/regions accumulated significantly more MVPA on weekdays versus weekend days during school months. This finding aligns with the SDH and warrants future intervention studies to prioritize less-structured days, such as weekend days, and to consider providing opportunities for all children to access additional opportunities to be active.

Comparing 24 h physical activity profiles: Office workers, women with a history of gestational diabetes and people with chronic disease condition(s)

This study demonstrates a novel data-driven method of summarising accelerometer data to profile physical activity in three diverse groups, compared with cut-point determined moderate-to-vigorous physical activity (MVPA). GGIR was used to generate average daily acceleration, intensity gradient, time in MVPA and MX metrics (acceleration above which the most active X-minutes accumulate) from wrist-worn accelerometer data from three datasets: office-workers (OW, N = 697), women with a history of post-gestational diabetes (PGD, N = 267) and adults with ≥1 chronic disease (CD, N = 1,325). Average acceleration and MVPA were lower in CD, but not PGD, relative to OW (-5.2 mg and -30.7 minutes, respectively, P < 0.001). Both PGD and CD had poorer intensity distributions than OW (P < 0.001). Application of a cut-point to the M30 showed 7%, 17% and 28%, of OW, PGD and CD, respectively, accumulated 30 minutes of brisk walking per day. Radar plots showed OW had higher overall activity than CD. The relatively poor intensity distribution of PGD, despite similar overall activity to OW, was due to accumulation of more light and less higher intensity activity. These data-driven methods identify aspects of activity that differ between groups, which may be missed by cut-point methods alone. Abbreviations: CD: Adults with ≥1 chronic disease; mg: Milli-gravitational unit; MVPA: Moderate-to-vigorous physical activity; OW: Office workers; PGD: Women with a history of post-gestational diabetes; VPA: Vigorous physical activity.

A Clinical Trial to Increase Self-Monitoring of Physical Activity and Eating Behaviors Among Adolescents: Protocol for the ImPACT Feasibility Study

Background

Severe obesity among youths (BMI for age≥120th percentile) has been steadily increasing. The home environment and parental behavioral modeling are two of the strongest predictors of child weight loss during weight loss interventions, which highlights that a family-based treatment approach is warranted. This strategy has been successful in our existing evidence-based pediatric weight management program, Brenner Families in Training (Brenner FIT). However, this program relies on face-to-face encounters, which are limited by the time constraints of the families enrolled in treatment.

Objective

This study aims to refine and test a tailored suite of mobile health (mHealth) components to augment an existing evidence-based pediatric weight management program.

Methods

Study outcomes will include acceptability from a patient and clinical staff perspective, feasibility, and economic costs relative to the established weight management protocol alone (ie, Brenner FIT vs Brenner FIT + mHealth [Brenner mFIT]). The Brenner mFIT intervention will consist of 6 mHealth components designed to increase patient and caregiver exposure to Brenner FIT programmatic content including the following: (1) a mobile-enabled website, (2) dietary and physical activity tracking, (3) caregiver podcasts (n=12), (4) animated videos (n=6) for adolescent patients, (5) interactive messaging, and (6) in-person tailored clinical feedback provided based on a web-based dashboard. For the study, 80 youths with obesity (aged 13-18 years) and caregiver dyads will be randomized to Brenner FIT or Brenner mFIT. All participants will complete baseline measures before randomization and at 3- and 6-month follow-up points.

Results

This study was approved by the Institutional Review Board in July 2019, funded in August 2019, and will commence enrollment in April 2020. The results of the study are expected to be published in the fall/winter of 2021.

Conclusions

The results of this study will be used to inform a large-scale implementation-effectiveness clinical trial.

International Registered Report Identifier (IRRID)

PRR1-10.2196/18098

Standardizing Analytic Methods and Reporting in Activity Monitor Validation Studies

INTRODUCTION

A lack of standardization with accelerometry-based monitors has made it hard to advance applications for both research and practice. Resolving these challenges is essential for developing methods for consistent, agnostic reporting of physical activity outcomes from wearable monitors in clinical applications.

METHODS

This article reviewed the literature on the methods used to evaluate the validity of contemporary consumer activity monitors. A rationale for focusing on energy expenditure as a key outcome measure in validation studies was provided followed by a summary of the strengths and limitations of different analytical methods. The primary review included 23 recent validation studies that collectively reported energy expenditure estimates from 58 monitors relative to values from appropriate criterion measures.

RESULTS

The majority of studies reported weak indicators such as correlation coefficients (87%), but only half (52%) reported the recommended summary statistic of mean absolute percent error needed to evaluate actual individual error. Fewer used appropriate tests of agreement such as equivalence testing (22%).

CONCLUSIONS

The use of inappropriate analytic methods and incomplete reporting of outcomes is a major limitation for systematically advancing research with both research grade and consumer-grade activity monitors. Guidelines are provided to standardize analytic methods and reporting in these types of studies to enhance the utility of the devices for clinical mHealth applications.

Isotemporal substitution of inactive time with physical activity and time in bed: cross-sectional associations with cardiometabolic health in the PREDIMED-Plus study

BACKGROUND

This study explored the association between inactive time and measures of adiposity, clinical parameters, obesity, type 2 diabetes and metabolic syndrome components. It further examined the impact of reallocating inactive time to time in bed, light physical activity (LPA) or moderate-to-vigorous physical activity (MVPA) on cardio-metabolic risk factors, including measures of adiposity and body composition, biochemical parameters and blood pressure in older adults.

METHODS

This is a cross-sectional analysis of baseline data from 2189 Caucasian men and women (age 55-75 years, BMI 27-40 Kg/m2) from the PREDIMED-Plus study (http://www.predimedplus.com/). All participants had ≥3 components of the metabolic syndrome. Inactive time, physical activity and time in bed were objectively determined using triaxial accelerometers GENEActiv during 7 days (ActivInsights Ltd., Kimbolton, United Kingdom). Multiple adjusted linear and logistic regression models were used. Isotemporal substitution regression modelling was performed to assess the relationship of replacing the amount of time spent in one activity for another, on each outcome, including measures of adiposity and body composition, biochemical parameters and blood pressure in older adults.

RESULTS

Inactive time was associated with indicators of obesity and the metabolic syndrome. Reallocating 30 min per day of inactive time to 30 min per day of time in bed was associated with lower BMI, waist circumference and glycated hemoglobin (HbA1c) (all p-values < 0.05). Reallocating 30 min per day of inactive time with 30 min per day of LPA or MVPA was associated with lower BMI, waist circumference, total fat, visceral adipose tissue, HbA1c, glucose, triglycerides, and higher body muscle mass and HDL cholesterol (all p-values < 0.05).

CONCLUSIONS

Inactive time was associated with a poor cardio-metabolic profile. Isotemporal substitution of inactive time with MVPA and LPA or time in bed could have beneficial impact on cardio-metabolic health.

TRIAL REGISTRATION

The trial was registered at the International Standard Randomized Controlled Trial (ISRCTN: http://www.isrctn.com/ISRCTN89898870) with number 89898870 and registration date of 24 July 2014, retrospectively registered.

Enhancing the value of accelerometer-assessed physical activity: meaningful visual comparisons of data-driven translational accelerometer metrics

The lack of consensus on meaningful and interpretable physical activity outcomes from accelerometer data hampers comparison across studies. Cut-point analyses are simple to apply and easy to interpret but can lead to results that are not comparable. We propose that the optimal accelerometer metrics for data analysis are not the same as the optimal metrics for translation. Ideally, analytical metrics are precise continuous variables that cover the intensity spectrum, while translational metrics facilitate meaningful, public-health messages and can be described in terms of activities (e.g. brisk walking) or intensity (e.g. moderate-to-vigorous physical activity). Two analytical metrics that capture the volume and intensity of the 24-h activity profile are average acceleration (volume) and intensity gradient (intensity distribution). These allow investigation of independent, additive and interactive associations of volume and intensity of activity with health; however, they are not immediately interpretable. The MX metrics, the acceleration above which the most active X minutes are accumulated, are translational metrics that can be interpreted in terms of indicative activities. Using a range of MX metrics illustrates the intensity gradient and average acceleration (i.e. 24-h activity profile). The M120, M60, M30, M15 and M5 illustrate the most active accumulated minutes of the day, the M1/3DAY the most active accumulated 8 h of the day. We demonstrate how radar plots of MX metrics can be used to interpret and translate results from between- and within-group comparisons, provide information on meeting guidelines, assess individual activity profiles relative to percentiles and compare activity profiles between domains and/or time periods.

Comparison of Indirect Calorimetry- and Accelerometry-Based Energy Expenditure During Children's Discrete Skill Performance

Purpose: To compare children's energy expenditure (EE) levels during object projection skill performance (OPSP; e.g., kicking, throwing, striking) as assessed by hip- and wrist-worn accelerometers. Method: Forty-two children (female n = 20, Mage = 8.1 ± 0.8 years) performed three, nine-minute sessions of kicking, over-arm throwing, and striking at performance intervals of 6, 12, and 30 seconds. EE was estimated using indirect calorimetry (COSMED k4b2) and accelerometers (ActiGraph GT3X+) worn on three different locations (hip, dominant-wrist, and non-dominant-wrist) using four commonly used cut-points. Bland-Altman plots were used to analyze the agreement in EE estimations between accelerometry and indirect calorimetry (METS). Chi-square goodness of fit tests were used to examine the agreement between accelerometry and indirect calorimetry. Results: Hip- and wrist-worn accelerometers underestimated EE, compared to indirect calorimetry, during all performance conditions. Skill practice at a rate of two trials per minute resulted in the equivalent of moderate PA and five trials per minute resulted in vigorous PA (as measured by indirect calorimetry), yet was only categorized as light and/or moderate activity by all measured forms of accelerometry. Conclusion: This is one of the first studies to evaluate the ability of hip- and wrist-worn accelerometers to predict PA intensity levels during OPSP in children. These data may significantly impact PA intervention measurement strategies by revealing the lack of validity in accelerometers to accurately predict PA levels during OPSP in children.

A data-driven, meaningful, easy to interpret, standardised accelerometer outcome variable for global surveillance

OBJECTIVES

Our aim is to demonstrate how a data-driven accelerometer metric, the acceleration above which a person's most active minutes are accumulated, can (a) quantify the prevalence of meeting current physical activity guidelines for global surveillance and (b) moving forward, could inform accelerometer-driven physical activity guidelines. Unlike cut-point methods, the metric is population-independent (e.g. age) and potentially comparable across datasets.

DESIGN

Cross-sectional, secondary data analysis.

METHODS

Analyses were carried out on five datasets using wrist-worn accelerometers: children (N=145), adolescent girls (N=1669), office workers (N=114), pre- (N=1218) and post- (N=1316) menopausal women, and adults with type 2 diabetes (N=475). Open-source software (GGIR) was used to generate the magnitude of acceleration above which a person's most active 60, 30 and 2min are accumulated: M60_ACC; M30_ACC and M2_ACC, respectively.

RESULTS

The proportion of participants with M60_ACC (children) and M30_ACC (adults) values higher than accelerations representative of brisk walking (i.e., moderate-to-vigorous physical activity) ranged from 17 to 68% in children and 15 to 81% in adults, tending to decline with age. The proportion of pre-and post-menopausal women with M2_ACC values meeting thresholds for bone health ranged from 6 to 13%.

CONCLUSIONS

These metrics can be used for global surveillance of physical activity, including assessing prevalence of meeting current physical activity guidelines. As accelerometer and corresponding health data accumulate it will be possible to interpret the metrics relative to age- and sex- specific norms and derive evidence-based physical activity guidelines directly from accelerometer data for use in future global surveillance. This is where the potential advantages of these metrics lie.

Accelerometer-derived physical activity estimation in preschoolers - comparison of cut-point sets incorporating the vector magnitude vs the vertical axis

Background

ActiGraph accelerometers are a widely used tool to objectively measure physical activity (PA) behavior in young children and several validated cut-point sets exist to estimate time spent in different PA intensities (sedentary time, light PA, moderate-to-vigorous PA). Applying different cut-point sets leads to large and meaningful differences in results. So far, only cut-point sets validated for the vertical axis have been compared and only the influence on time spent in moderate-to-vigorous PA has been analyzed.

Methods

A range of validated cut-point sets with their respective epoch length was applied to analyze cross-sectional data of the Swiss Preschoolers’ Health Study (SPLASHY): 1) Vertical axis in combination with an epoch length of 15 s (VA-15), 2) Vertical axis in combination with an epoch length of 60 s (VA-60) and 3) Vector magnitude in combination with an epoch length of 60 s (VM-60). PA was measured for eight consecutive days using ActiGraph accelerometers (wGT3X-BT). Three days were required to be included in the analysis (minimum two weekdays and one weekend-day with at least ten hours recording per day).

Results

Four hundred forty-five preschoolers (mean age 3.9 ± 0.5 years; 46% girls) had valid accelerometer measurements. A longer epoch (VA-60 vs VA-15) resulted in 2% less sedentary time (ST), 18% more light PA (LPA) and 51% less moderate-to-vigorous PA (MVPA); using the vector magnitude compared to the vertical axis (VM-60 vs VA-60) resulted in 34% less ST, 27% more LPA and 63% more MVPA (all p ≤ 0.001). Comparing all three sets of cut-points, ST ranged from 4.0 to 6.2 h, LPA from 5.1 to 7.6 h and MVPA from 0.8 to 1.6 h.

Conclusions

Estimated time spent in different PA intensities was strongly influenced by the choice of cut-point sets. Both, axis selection and epoch length need to be considered when comparing different studies especially when they relate PA behavior to health. The differences in the prevalence of children fulfilling PA guidelines highlight the relevance of these findings.

Trial registration

Current Controlled Trials ISRCTN41045021 (date of registration: 21.03.2014).

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6837-7) contains supplementary material, which is available to authorized users.

Expert's Choice: 2018's Most Exciting Research in the Field of Pediatric Exercise Science

This commentary highlights 23 noteworthy publications from 2018, selected by leading scientists in pediatric exercise science. These publications have been deemed as significant or exciting in the field as they (a) reveal a new mechanism, (b) highlight a new measurement tool, (c) discuss a new concept or interpretation/application of an existing concept, or (d) describe a new therapeutic approach or clinical tool in youth. In some cases, findings in adults are highlighted, as they may have important implications in youth. The selected publications span the field of pediatric exercise science, specifically focusing on: aerobic exercise and training; neuromuscular physiology, exercise, and training; endocrinology and exercise; resistance training; physical activity and bone strength; growth, maturation, and exercise; physical activity and cognition; childhood obesity, physical activity, and exercise; pulmonary physiology or diseases, exercise, and training; immunology and exercise; cardiovascular physiology and disease; and physical activity, inactivity, and health.

A Primer on the Use of Equivalence Testing for Evaluating Measurement Agreement

PURPOSE

Statistical equivalence testing is more appropriate than conventional tests of difference to assess the validity of physical activity (PA) measures. This article presents the underlying principles of equivalence testing and gives three examples from PA and fitness assessment research.

METHODS

The three examples illustrate different uses of equivalence tests. Example 1 uses PA data to evaluate an activity monitor's equivalence to a known criterion. Example 2 illustrates the equivalence of two field-based measures of physical fitness with no known reference method. Example 3 uses regression to evaluate an activity monitor's equivalence across a suite of 23 activities.

RESULTS

The examples illustrate the appropriate reporting and interpretation of results from equivalence tests. In the first example, the mean criterion measure is significantly within ±15% of the mean PA monitor. The mean difference is 0.18 METs and the 90% confidence interval of -0.15 to 0.52 is inside the equivalence region of -0.65 to 0.65. In the second example, we chose to define equivalence for these two measures as a ratio of mean values between 0.98 and 1.02. The estimated ratio of mean V˙O2 values is 0.99, which is significantly (P = 0.007) inside the equivalence region. In the third example, the PA monitor is not equivalent to the criterion across the suite of activities. The estimated regression intercept and slope are -1.23 and 1.06. Neither confidence interval is within the suggested regression equivalence regions.

CONCLUSIONS

When the study goal is to show similarity between methods, equivalence testing is more appropriate than traditional statistical tests of differences (e.g., ANOVA and t-tests).

Predictors of Physical Activity for Preschool Children With and Without Disabilities From Socioeconomically Disadvantaged Settings

The purpose of this study was to examine differences in motor competence, perceived motor competence (PMC), body mass index, and physical activity (PA) and to assess factors that predict PA behaviors of preschool children with and without disabilities. A total of 59 children with (n = 28) and without (n = 31) disabilities participated in the study. Results revealed that children with disabilities had significantly greater amounts of PA than peers without disabilities. There were no significant differences for motor competence, PMC, and body mass index for children with or without a disability. Although age and body mass index were controlled, both disability and PMC significantly predicted PA. Future intervention studies should consider maintaining high levels of PMC, as it is a significant predictor of PA.

Comparing physical activity estimates in children from hip-worn Actigraph GT3X+ accelerometers using raw and counts based processing methods

This study examined differences in physical activity (PA) estimates provided from raw and counts processing methods. One hundred and sixty-five children (87 girls) wore a hip-mounted ActiGraph GT3X+ accelerometer for 7 days. Data were available for 129 participants. Time in moderate PA (MPA), vigorous PA (VPA) and moderate-vigorous PA (MVPA) were calculated using R-package GGIR and ActiLife. Participants meeting the wear time criteria for both processing methods were included in the analysis. Time spent in MPA (-21.4 min.d^-1, 95%CI -21 to -20) and VPA (-36 min.d^-1, 95%CI -40 to -33) from count data were higher (P < 0.001) than raw data. Time spent in MVPA between the two processing methods revealed significant differences (All P < 0.001). Bland-Altman plots suggest that the mean bias for time spent in MPA, VPA and MVPA were large when comparing raw and count methods. Equivalence tests showed that estimates from raw and count processing methods across all activity intensities lacked equivalence. Lack of equivalence and poor agreement between raw and count processing methods suggest the two approaches to estimate PA are not comparable. Further work to facilitate the comparison of findings between studies that process and report raw and count physical activity data may be necessary.

Advances and Controversies in Diet and Physical Activity Measurement in Youth

Technological advancements in the past decades have improved dietary intake and physical activity measurements. This report reviews current developments in dietary intake and physical activity assessment in youth. Dietary intake assessment has relied predominantly on self-report or image-based methods to measure key aspects of dietary intake (e.g., food types, portion size, eating occasion), which are prone to notable methodologic (e.g., recall bias) and logistic (e.g., participant and researcher burden) challenges. Although there have been improvements in automatic eating detection, artificial intelligence, and sensor-based technologies, participant input is often needed to verify food categories and portions. Current physical activity assessment methods, including self-report, direct observation, and wearable devices, provide researchers with reliable estimations for energy expenditure and bodily movement. Recent developments in algorithms that incorporate signals from multiple sensors and technology-augmented self-reporting methods have shown preliminary efficacy in measuring specific types of activity patterns and relevant contextual information. However, challenges in detecting resistance (e.g., in resistance training, weight lifting), prolonged physical activity monitoring, and algorithm (non)equivalence remain to be addressed. In summary, although dietary intake assessment methods have yet to achieve the same validity and reliability as physical activity measurement, recent developments in wearable technologies in both arenas have the potential to improve current assessment methods.

THEME INFORMATION

This article is part of a theme issue entitled Innovative Tools for Assessing Diet and Physical Activity for Health Promotion, which is sponsored by the North American branch of the International Life Sciences Institute.

Objectively assessed moderate-to-vigorous physical activity levels among primary school children in Norway: The Health Oriented Pedagogical Project (HOPP)

AIMS

The objective was to investigate moderate-to-vigorous physical activity levels (MVPA) of primary school children at baseline of the Health Oriented Pedagogical Project (HOPP), Norway.

METHODS

Data on 2123 children aged 6-12 years were included for analysis (75% participation rate). Average minutes per day in MVPA was objectively measured using accelerometry based on seven-day averages. The sample was analysed for age-, sex-, socioeconomic-, and season-related patterns. A linear regression investigated the moderating effect of these factors as well as body mass index and waist circumference.

RESULTS

Some 86.5% of the sample had at least 60 min/day MVPA, averaging 90.7 min/day. The main differences in daily averages were between age groups 6½-9 and 10-12 ( p < .05). Boys (95.8 min/day, 95% CI: 94.1-97.5) were more active than girls (85.6 min/day, 95% CI: 83.9-87.2) in all age groups ( p < .0001). MVPA was lower by 3.5 min ( p < .0001) per additional year of age in the linear regression (R² = 0.176) and was reduced by 20 min less per day in MVPA in the winter months compared with the summer months ( p < .0001).

CONCLUSIONS

Physical activity levels are already in decline from 6-7 years old and are likely to continue to decline into adolescence. Interventions must therefore focus on primary school children.

Moving Forward with Backward Compatibility: Translating Wrist Accelerometer Data

PURPOSE

This study aimed to provide a means for calibrating raw acceleration data from wrist-worn accelerometers in relation to past estimates of children's moderate-to-vigorous physical activity (MVPA) from a range of cut points applied to hip-worn ActiGraph data.

METHODS

This is a secondary analysis of three studies with concurrent 7-d accelerometer wear at the wrist (GENEActiv) and hip (ActiGraph) in 238 children age 9-12 yr. The time spent above acceleration (ENMO) thresholds of 100, 150, 200, 250, 300, 350, and 400 mg from wrist acceleration data (≤5-s epoch) was calculated for comparison with MVPA estimated from widely used children's hip-worn ActiGraph MVPA cut points (Freedson/Trost, 1100 counts per minute; Pate, 1680 counts per minute; Evenson, 2296 counts per minute; Puyau, 3200 counts per minute) with epochs of ≤5, 15, and 60 s.

RESULTS

The optimal ENMO thresholds for alignment with MVPA estimates from ActiGraph cut points determined from 70% of the sample and cross validated with the remaining 30% were as follows: Freedson/Trost = ENMO 150+ mg, irrespective of ActiGraph epoch (intraclass correlation [ICC] ≥ 0.65); Pate = ENMO 200+ mg, irrespective of ActiGraph epoch (ICC ≥ 0.67); Evenson = ENMO 250+ mg for ≤5- and 15-s epochs (ICC ≥ 0.69) and ENMO 300+ mg for 60-s epochs (ICC = 0.73); Puyau = ENMO 300+ mg for ≤5-s epochs (ICC = 0.73), ENMO 350+ mg for 15-s epochs (ICC = 0.73), and ENMO 400+ mg for 60-s epochs (ICC = 0.65). Agreement was robust with cross-validation ICC = 0.62-0.71 and means within ∣7.8∣% ± 4.9% of MVPA estimates from ActiGraph cut points, except Puyau 60-s epochs (ICC = 0.42).

CONCLUSION

Incremental ENMO thresholds enable children's acceleration data measured at the wrist to be simply and directly compared, at a group level, with past estimates of MVPA from hip-worn ActiGraphs across a range of cut points.

Associations of Vigorous-Intensity Physical Activity with Biomarkers in Youth

INTRODUCTION

Physical activity (PA) conveys known cardiometabolic benefits to youth, but the contribution of vigorous-intensity PA (VPA) to these benefits is unknown. Therefore, we sought to determine (a) the associations between VPA and cardiometabolic biomarkers independent of moderate-intensity PA (MPA) and time sedentary and (b) the accelerometer cut point that best represents the threshold for health-promoting VPA in youth.

METHODS

Data from the International Children's Accelerometry Database (ICAD) were analyzed in 2015. The relationship between cardiometabolic biomarkers and four categories of VPA estimated via three sets of cut points were examined using isotemporal substitution quantile regression modeling at the 10th, 25th, 50th, 75th, and 90th percentile of the distribution of each biomarker, separately. Age, sex, accelerometer wear time, sedentary time, and MPA were controlled for while allowing substitution for light-intensity PA. Data from 11,588 youth (4-18 yr) from 11 ICAD studies (collected 1998-2009) were analyzed.

RESULTS

Only 32 of 360 significant associations were observed. Significant, negative relationships were observed for VPA with waist circumference and insulin. Replacing light-intensity PA with VPA (corresponding to at the 25th to 90th percentiles of VPA) was associated with 0.67 (-1.33 to -0.01; P = 0.048) to 7.30 cm (-11.01 to -3.58; P < 0.001) lower waist circumference using Evenson and ICAD cut points (i.e., higher counts per minute). VPA levels were associated with 12.60 (-21.28 to -3.92; P = 0.004) to 27.03 pmol·L (-45.03 to -9.03; P = 0.003) lower insulin levels at the 75th to 90th percentiles using Evenson and ICAD cut points when substituted for light PA.

CONCLUSIONS

Substituting light PA with VPA was inversely associated with waist circumference and insulin. However, VPA was inconsistently related to the remaining biomarkers after controlling for time sedentary and MPA.

Calibration and Validation of the Youth Activity Profile: The FLASHE Study

INTRODUCTION

This study describes the calibration and validity of the Youth Activity Profile (YAP) for use in the National Cancer Institute's Family Life, Activity, Sun, Health, and Eating (FLASHE) study. The calibrated YAP was designed to estimate minutes of moderate to vigorous physical activity (MVPA) and sedentary behavior (SB).

METHODS

The YAP was calibrated/validated in adolescents (aged 12-17 years) using cross-sectional data from the FLASHE study. Participants wore a GT3X+ ActiGraph on the dominant wrist for 7 days and then completed the YAP. Calibration was conducted for school (n=118); out of school (n=119); weekend (n=61); and SB (n=116) subsections of the YAP and by regressing percentage time in MVPA/SB (%MVPA/%SB) on each respective YAP subsection score, age, and the interaction between these two. The final algorithms were applied to independent samples (n=39-51) to examine validity (median absolute percentage error, equivalence testing).

RESULTS

The final algorithms explained 15% (school); 16% (out of school); and 12% (weekend) of the variability in GT3X+ %MVPA and 7% of the variability in GT3X+ %SB. The calibrated algorithms were applied to independent samples and predicted GT3X+ minutes of MVPA/SB, with median absolute percentage error values ranging from 12.5% (SB section) to 32.5% (weekend section). Predicted values obtained from the YAP were within 10%-20% of those produced by the GT3X+.

CONCLUSIONS

The YAP-predicted minutes of MVPA/SB resulted in similar group estimates obtained from an objective measure. The YAP offers good utility for large-scale research projects to characterize PA/SB levels among groups of youth.

Application of the Rosetta Stone to understand how much MVPA preschoolers accumulate: A systematic review

OBJECTIVES

This study illustrates the utility of the Rosetta Stone equations for comparing estimates of preschool-age children's moderate-to-vigorous physical activity (MVPA) across studies utilizing different cutpoints.

DESIGN

Systematic review.

METHODS

A search of online databases was conducted to identify studies that reported daily minutes of MVPA in preschoolers using the cutpoints from which Rosetta Stone equations have been developed. Mean MVPA minday^-1 from each study and the transformed estimate using the Rosetta Stone equations were compared across 7 sets of cutpoints. The weighted mean was used to calculate absolute differences between the MVPA estimates of studies using the same cutpoints (e.g all studies that have used Pate cutpoint), and from all of the remaining studies using different cutpoints (e.g., all remaining studies that have not used Pate cutpoint), before and after the Rosetta Stone transformation.

RESULTS

A total of 33 manuscripts met the eligibility criteria and reported MVPA for 12,178 preschoolers (50% girls). The mean MVPA for the total sample ranged from 21.1 (Puyau cutpoint) to 288.6 (Freedson cutpoints) minday^-1. The difference between studies using the same cutpoint and estimates from remaining studies using different cutpoints was 82.4 and 80.0minday^-1 for boys and girls, respectively. These differences were reduced to approximately 14minday^-1 for boys and girls, after Rosetta Stone transformations.

CONCLUSIONS

The Rosetta Stone equations substantially reduced the differences across studies that utilize different cutpoints and improved the ability to interpret findings across studies. Future equations should be developed for sedentary and total physical activity, as well as, comparisons across different devices and placements.

Effect of Accelerometer Cut-Off Points on the Recommended Level of Physical Activity for Obesity Prevention in Children

There is no general consensus regarding which accelerometer cut-off point (CoP) is most acceptable to estimate the time spent in moderate-to-vigorous physical activity (MVPA) in children and choice of an appropriate CoP primarily remains a subjective decision. Therefore, this study aimed to analyze the influence of CoP selection on the mean MVPA and to define the optimal thresholds of MVPA derived from different accelerometer CoPs to avoid overweight/obesity and adiposity in children aged 7 to 12 years. Three hundred six children participated. Physical activity (PA) was monitored for seven consecutive days using an ActiGraph accelerometer (model GT3X) and the intensity of PA was estimated using the five most frequently published CoPs. Body adiposity was assessed using a multi-frequency bioelectrical impedance analysis. There was found a wide range of mean levels of MVPA that ranged from 27 (Puyau CoP) to 231 min∙d-1 (Freedson 2005 CoP). A receiver operating characteristic curve analysis indicated that the optimal thresholds for counts per minute (cpm) and MVPA derived from the Puyau CoP was the most useful in classifying children according to their body mass index (BMI) and fat mass percentage (FM%). In the total sample, the optimal thresholds of the MVPA derived from the Puyau CoP were 22 and 23 min∙d-1 when the categories based on BMI and FM%, respectively, were used. The children who did not meet these optimal thresholds had a significantly increased risk of being overweight/obese (OR = 2.88, P < 0.01) and risk of having excess fat mass (OR = 2.41, P < 0.01). In conclusion, the decision of selecting among various CoPs significantly influences the optimal levels of MVPA. The Puyau CoP of 3 200 cmp seems to be the most useful for defining the optimal level of PA for pediatric obesity prevention.

Challenges and Opportunities for Harmonizing Research Methodology: Raw Accelerometry

OBJECTIVES

Raw accelerometry is increasingly being used in physical activity research, but diversity in sensor design, attachment and signal processing challenges the comparability of research results. Therefore, efforts are needed to harmonize the methodology. In this article we reflect on how increased methodological harmonization may be achieved.

METHODS

The authors of this work convened for a two-day workshop (March 2014) themed on methodological harmonization of raw accelerometry. The discussions at the workshop were used as a basis for this review.

RESULTS

Key stakeholders were identified as manufacturers, method developers, method users (application), publishers, and funders. To facilitate methodological harmonization in raw accelerometry the following action points were proposed: i) Manufacturers are encouraged to provide a detailed specification of their sensors, ii) Each fundamental step of algorithms for processing raw accelerometer data should be documented, and ideally also motivated, to facilitate interpretation and discussion, iii) Algorithm developers and method users should be open about uncertainties in the description of data and the uncertainty of the inference itself, iv) All new algorithms which are pitched as "ready for implementation" should be shared with the community to facilitate replication and ongoing evaluation by independent groups, and v) A dynamic interaction between method stakeholders should be encouraged to facilitate a well-informed harmonization process.

CONCLUSIONS

The workshop led to the identification of a number of opportunities for harmonizing methodological practice. The discussion as well as the practical checklists proposed in this review should provide guidance for stakeholders on how to contribute to increased harmonization.

Time trends: a ten-year comparison (2005-2015) of pedometer-determined physical activity and obesity in Czech preschool children

BACKGROUND

To explore the time trends (2005-2015) of pedometer-determined weekday and weekend physical activity (PA) and obesity prevalence in 4-7-year-old Czech preschool children and changes in proportion of kindergarten vs. leisure-time PA.

METHODS

The study compared data of two cross-sectional cohorts of preschool children (2005: 92 boys and 84 girls; 2015: 105 boys and 87 girls) in the Czech Republic, using the same measurements and procedures in both cases. PA was monitored by the Yamax Digiwalker SW-200 pedometer for at least eight continuous hours a day over seven consecutive days. Body weight and height were measured using calibrated Tanita scales and anthropometry. The analysis of variance was conducted to examine the gender and cohort effect on step counts. The t-test was used to examine the difference in step counts in kindergarten (or leisure-time) between non-obese and obese children, and the chi-square test compared the prevalence of obesity between 2005 and 2015.

RESULTS

The steps/day (mean ± standard deviation) of preschoolers was significantly higher (p < 0.05) in 2015 (11,739 ± 4,229 steps/day) than in 2005 (10,922 ± 3,181 steps/day); and (p < 0.001) in boys (11,939 ± 3,855 steps/day) than in girls (10,668 ± 3,587 steps/day). In 2015, girls, but not boys, had a significantly (p < 0.01) greater step count on weekdays than in 2005, but not at weekends. A decline of leisure-time step counts on weekdays between 2005 and 2015 in girls (6,8652005 vs. 6,0592015, p < 0.01) and boys (7,8612005 vs. 6,4362015, p < 0.001) is compensated for by the increase of step counts in kindergarten (girls: 3,0582005 vs. 5,3302015, and boys: 4,0032005 vs. 5,9992015, p < 0.001). The prevalence of obesity was not significantly different either in 2005 or 2015 among preschool girls (7.14 % 2005 vs. 9.20 % 2015) or boys (6.52 % 2005 vs. 9.52 % 2015).

CONCLUSION

The steps/day of preschoolers was higher in 2015 than in 2005; this higher level of PA was the result of increased PA in kindergartens over the last ten years, particularly among girls. Thus, the current PA program in kindergartens effectively compensates for the decline in PA in leisure-time of weekdays of non-obese and obese preschoolers compared to 2005 and 2015. Prevalence of obesity among Czech preschool children remains relatively stable between 2005 and 2015.

Evaluation of four sensor locations for physical activity assessment

Direct measurements of physical activity (PA) obtained with inertial measurement units (IMUs) secured to the upper arms and trunk of 36 registered nurses working a full shift were compared to measurements obtained with a commercially-available PA monitor (ActiGraph wGT3X-BT) worn at the waist. Raw accelerations from each device were summarized into PA counts/min and metabolic equivalent (METs) categories using standard definitions. Differences between measurements were examined using repeated measures one-way analyses of variance (ANOVA) and agreement was assessed using Bland-Altman plots. Statistically significant differences were observed between all sensor locations for all PA summary metrics except for between the left and right arm for percentages of work time in the light and moderate counts/min categories. Bland-Altman plots suggested limited agreement between measurements obtained with the IMUs and measurements obtained with the wGT3X-BT waist-worn PA monitor. Results indicate that PA measurements vary substantially based on sensor location.