Actigraph-defined moderate-to-vigorous physical activity cut-off points among children: statistical and biobehavioural relevance

Calibration and validation of physical behaviour cut-points using wrist-worn ActiGraphs for children and adolescents: A systematic review

OBJECTIVES

To review cut-points calibrated and independently validated from wrist-worn ActiGraph accelerometers to measure moderate to vigorous physical activity (MVPA) and time spent sedentary (SED) in children and adolescents.

DESIGN

Systematic literature review.

METHODS

Five databases were searched for relevant cut-point calibration and independent validation studies relating to wrist worn ActiGraphs in children and adolescents from inception through 30 April 2022. Extracted data included: country of publication; study name; population; device model; wear location; sampling frequency; epoch length; activity protocol; criterion method and definitions used to classify PA intensity; statistical methods for calibration; statistical methods for validation/cross-validation; and MVPA and SED outcome.

RESULTS

Fourteen calibration studies and seven independent validation studies were identified. Calibrated cut-points for MVPA vector magnitude counts ranged from 7065 to 9204 counts per minute (cpm) and 63.5 to 201 milli-gravitational units (mg). For SED, calibrated cut-points ranged from <2556 cpm to 4350 cpm and 30.8 to 48.1 mg. Classification accuracy values determined by independent validation studies varied, with kappa values ranging from 0.31 to 0.60 and area under the curve statistics ranging from 0.51 to 0.84 for MVPA and kappa values ranging from 0.31 to 0.44 and area under the curve statistics ranging from 0.70 to 0.85 for SED.

CONCLUSIONS

The results of this systematic literature review support the use of the Crouter and colleagues cut-points for the measurement of MVPA and SED for children and adolescents aged 6-12 years. Further work is required to independently validate cut-points developed in younger children and older adolescents.

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.

Using hidden markov models to improve quantifying physical activity in accelerometer data - a simulation study

Introduction

The use of accelerometers to objectively measure physical activity (PA) has become the most preferred method of choice in recent years. Traditionally, cutpoints are used to assign impulse counts recorded by the devices to sedentary and activity ranges. Here, hidden Markov models (HMM) are used to improve the cutpoint method to achieve a more accurate identification of the sequence of modes of PA.

Methods

1,000 days of labeled accelerometer data have been simulated. For the simulated data the actual sedentary behavior and activity range of each count is known. The cutpoint method is compared with HMMs based on the Poisson distribution (HMM[Pois]), the generalized Poisson distribution (HMM[GenPois]) and the Gaussian distribution (HMM[Gauss]) with regard to misclassification rate (MCR), bout detection, detection of the number of activities performed during the day and runtime.

Results

The cutpoint method had a misclassification rate (MCR) of 11% followed by HMM[Pois] with 8%, HMM[GenPois] with 3% and HMM[Gauss] having the best MCR with less than 2%. HMM[Gauss] detected the correct number of bouts in 12.8% of the days, HMM[GenPois] in 16.1%, HMM[Pois] and the cutpoint method in none. HMM[GenPois] identified the correct number of activities in 61.3% of the days, whereas HMM[Gauss] only in 26.8%. HMM[Pois] did not identify the correct number at all and seemed to overestimate the number of activities. Runtime varied between 0.01 seconds (cutpoint), 2.0 minutes (HMM[Gauss]) and 14.2 minutes (HMM[GenPois]).

Conclusions

Using simulated data, HMM-based methods were superior in activity classification when compared to the traditional cutpoint method and seem to be appropriate to model accelerometer data. Of the HMM-based methods, HMM[Gauss] seemed to be the most appropriate choice to assess real-life accelerometer data.

Does biological maturity actually confound gender-related differences in physical activity in preadolescence?

AIM

To examine: (i) if maturity-related gender differences in moderate-to-vigorous physical activity (MVPA) depend on how maturity status is defined and measured; and (ii) the influence of maturity level on compliance with PA recommendations.

METHODS

The study involved 253 children (139 boys) aged 9.9 ± 0.9 years, with mean stature and weight of 1.39 ± 0.08 m and 35.8 ± 8.8 kg respectively. Their PA was evaluated using an Actigraph accelerometer (Model 7164). Maturity was assessed using the estimated age at peak height velocity (APHV) and a standardized APHV by gender (i.e. centred APHV).

RESULTS

Boys engaged in significantly more MVPA than girls (P < 0.0001). There was a significant correlation between the centred APHV and MVPA in boys (r = 0.20; P = 0.016), but not in girls (r = 0.13; P = 0.155). An ancova controlling for the estimated APHV showed no significant interactions between gender and APHV, and the main effect of gender on MVPA was negated. Conversely, there was a significant main effect of APHV on MVPA (F 1,249 = 6.12; P = 0.014; η p (2) = 0.024). Only 9.1% of children met the PA recommendations, including 14.4% of boys and 2.6% of girls (P < 0.01). This observation also applies in both pre-APHV (12.7% of boys vs. 2.4% of girls, P < 0.001) and post-APHV children (23.8% of boys vs. 3.4% of girls, P < 0.0001). No differences in PA guidelines were observed between pre-APHV and post-APHV children.

CONCLUSIONS

Among prepubescent children, the influence of biological maturity on gender differences in PA may be a function of how maturity status is determined. The most physically active prepubescent children were those who were on time according to APHV.

School day segmented physical activity patterns of high and low active children

Background

Variability exists in children’s activity patterns due to the association with environmental, social, demographic, and inter-individual factors. This study described accelerometer assessed physical activity patterns of high and low active children during segmented school week days whilst controlling for potential correlates.

Methods

Two hundred and twenty-three children (mean age: 10.7 ± 0.3 yrs, 55.6% girls, 18.9% overweight/obese) from 8 north-west England primary schools wore ActiGraph GT1M accelerometers for 7 consecutive days during autumn of 2009. ActiGraph counts were converted to minutes of moderate (MPA), vigorous (VPA) and moderate-to-vigorous (MVPA) physical activity. Children were classified as high active (HIGH) or low active (LOW) depending on the percentage of week days they accumulated at least 60 minutes of MVPA. Minutes spent in MPA and VPA were calculated for school time and non-school time and for five discrete school day segments (before-school, class time, recess, lunchtime, and after-school). Data were analysed using multi-level modelling.

Results

The HIGH group spent significantly longer in MPA and/or VPA before-school, during class time, lunchtime, and after-school (P < .05), independent of child and school level factors. The greatest differences occurred after-school (MPA = 5.5 minutes, VPA = 3.8 minutes, P < 0.001). MPA and VPA were also associated with gender, BMI z-score, number of enrolled children, playground area per student, and temperature, depending on the segment analysed.

The additive effect of the segment differences was that the HIGH group accumulated 12.5 minutes per day more MVPA than the LOW group.

Conclusions

HIGH active children achieved significantly more MPA and VPA than LOW active during four of the five segments of the school day when analyses were adjusted for potential correlates. Physical activity promotion strategies targeting low active children during discretionary physical activity segments of the day, and particularly via structured afterschool physical activity programs may be beneficial.

A calibration protocol for population-specific accelerometer cut-points in children

PURPOSE

To test a field-based protocol using intermittent activities representative of children's physical activity behaviours, to generate behaviourally valid, population-specific accelerometer cut-points for sedentary behaviour, moderate, and vigorous physical activity.

METHODS

Twenty-eight children (46% boys) aged 10-11 years wore a hip-mounted uniaxial GT1M ActiGraph and engaged in 6 activities representative of children's play. A validated direct observation protocol was used as the criterion measure of physical activity. Receiver Operating Characteristics (ROC) curve analyses were conducted with four semi-structured activities to determine the accelerometer cut-points. To examine classification differences, cut-points were cross-validated with free-play and DVD viewing activities.

RESULTS

Cut-points of ≤ 372, >2160 and >4806 counts • min(-1) representing sedentary, moderate and vigorous intensity thresholds, respectively, provided the optimal balance between the related needs for sensitivity (accurately detecting activity) and specificity (limiting misclassification of the activity). Cross-validation data demonstrated that these values yielded the best overall kappa scores (0.97; 0.71; 0.62), and a high classification agreement (98.6%; 89.0%; 87.2%), respectively. Specificity values of 96-97% showed that the developed cut-points accurately detected physical activity, and sensitivity values (89-99%) indicated that minutes of activity were seldom incorrectly classified as inactivity.

CONCLUSION

The development of an inexpensive and replicable field-based protocol to generate behaviourally valid and population-specific accelerometer cut-points may improve the classification of physical activity levels in children, which could enhance subsequent intervention and observational studies.

Maturity negates the gender-related difference in physical activity among youth. Is this equally justified whatever the accelerometer cut-off point used?

OBJECTIVES

To examine the consistency in findings about the influence of maturity on the gender-difference in moderate-to-vigorous physical activity (MVPA) of children using different cut-off points for MVPA.

DESIGN

Cross-sectional observation study.

METHODS

The sample involved 253 children (139 boys) of 9.9±0.9 years. Their physical activity was evaluated using an Actigraph accelerometer. The biological age of children was determined with their estimated age at the peak height velocity, and maturity categories were gender-specific defined.

RESULTS

Boys spent more time in MVPA than girls (P<0.0001), and no maturity-related differences were obtained on the whole sample. It was only among boys that differences were found between maturity groups with cut-off points of 3000 cpm (P=0.034), 3200 cpm (P=0.024), and 3600 cpm (P=0.011). At a given maturity level, boys spent significantly more time in MVPA than girls, except with the cut-off point of 1000 cpm (P=0.07). There were higher proportions of sufficiently active boys, but significances were reached only with cut-off points above 3000 cpm. There were no maturity-related differences in the proportion of sufficiently active children as MVPA was computed using cut-off points of 1000 cpm, 2000 cpm or 3000 cpm.

CONCLUSIONS

The role of maturity in the gender-difference in MVPA seems unclear as one another cut-off point is used among children. Even if a relatively greater consistency was found with the three cut-off points above 3000 cpm, data comparison may require a conversion system until a consensus is reached about the exact value to be used among children.

Assessment of a two-year school-based physical activity intervention among 7-9-year-old children

Background

Physical activity (PA) in children has declined in recent decades, highlighting the need for effective intervention programs for school-aged children. The main objective of this study was to assess to what extent PA during and after school hours changed among children who received a progressive two-year long intervention vs. that of children who only received general curriculum-based PA.

Methods

A cluster randomized intervention study was conducted and six elementary schools randomly assigned to serve as control- or intervention schools. All children attending second grade (mean age = 7.4 years - born in 1999) were invited to participate in the fall of 2006 (N = 320, 82% participated), again in 2007 (midpoint) and 2008 (end of intervention). The intervention consisted of multi-component PA-intervention during school hours and was conducted by teachers at each intervention school. PA was assessed by means of accelerometers and subjectively at the intervention schools via teachers' PA log-books.

Results

There was no difference in PA intensity (minutes of moderate-to-vigorous physical activity - min of MVPA) between the two study groups at baseline, but children in the intervention schools were more physically active at moderate-to-vigorous intensity compared to those in control schools after one year of intervention (mean difference of MVPA_log-minutes: 0.61, 95%CI: 0.02, 1.20, p = 0.04). Moreover, the model for minutes of MVPA during school hours, showed a significant three-way interaction between time at mid-point, group and gender (mean difference of MVPA_log-minutes: 1.06, 95%CI: 0.15, 1.97, p = .02), indicating a significantly greater increase among the boys in the intervention schools compared to girls. No difference in PA was detected between the study groups at the end of the study period after two years of intervention.

Conclusions

The results suggest that the objective of increasing PA at school was met after one year of intervention, and it was more pronounced among boys. The lack of increase at the end of the study period suggested that any increase in PA during school may highly depend on both motivation and training of general teachers. Boys may respond better to PA interventions such as the one described in this study.

Equating accelerometer estimates of moderate-to-vigorous physical activity: in search of the Rosetta Stone

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 mind(-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. Secondary data analysis. ActiGraph data from a large preschool project (N=419, 3-6-yr-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). The mean levels of MVPA for the total sample ranged from 22.5 (PY) to 269.0 (FR) mind(-1). Across the prediction models (5 total), the median proportion of variance explained (R(2)) was 0.76 (range 0.48-0.97). The median absolute percent error was 17.2% (range 6.3-38.4%). 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.

Actigraph accelerometer-defined boundaries for sedentary behaviour and physical activity intensities in 7 year old children

Background

Accurate objective assessment of sedentary and physical activity behaviours during childhood is integral to the understanding of their relation to later health outcomes, as well as to documenting the frequency and distribution of physical activity within a population.

Purpose

To calibrate the Actigraph GT1M accelerometer, using energy expenditure (EE) as the criterion measure, to define thresholds for sedentary behaviour and physical activity categories suitable for use in a large scale epidemiological study in young children.

Methods

Accelerometer-based assessments of physical activity (counts per minute) were calibrated against EE measures (kcal.kg⁻¹.hr⁻¹) obtained over a range of exercise intensities using a COSMED K4b² portable metabolic unit in 53 seven-year-old children. Children performed seven activities: lying down viewing television, sitting upright playing a computer game, slow walking, brisk walking, jogging, hopscotch and basketball. Threshold count values were established to identify sedentary behaviour and light, moderate and vigorous physical activity using linear discriminant analysis (LDA) and evaluated using receiver operating characteristic (ROC) curve analysis.

Results

EE was significantly associated with counts for all non-sedentary activities with the exception of jogging. Threshold values for accelerometer counts (counts.minute⁻¹) were <100 for sedentary behaviour and ≤2240, ≤3840 and ≥3841 for light, moderate and vigorous physical activity respectively. The area under the ROC curves for discrimination of sedentary behaviour and vigorous activity were 0.98. Boundaries for light and moderate physical activity were less well defined (0.61 and 0.60 respectively). Sensitivity and specificity were higher for sedentary (99% and 97%) and vigorous (95% and 91%) than for light (60% and 83%) and moderate (61% and 76%) thresholds.

Conclusion

The accelerometer cut points established in this study can be used to classify sedentary behaviour and to distinguish between light, moderate and vigorous physical activity in children of this age.

MVPA is associated with lower weight gain in 8-10 year old children: a prospective study with 1 year follow-up

BACKGROUND

Studies relating physical activity (PA) to weight gain in children have produced mixed results, although there is some evidence for stronger associations with more intense physical activities. The present study tested the hypothesis that weight gain over one year in 8-10 year olds would be more strongly predicted by moderate and vigorous physical activity (MVPA) than total physical activity (total PA) or sedentary behaviour.

METHODOLOGY

Participants were 280 children taking part in the Physical Exercise and Appetite in Children Study (PEACHES). Weight status was assessed using body mass index (BMI), fat mass index (FMI), and waist circumference (WC) in school Year 4 (baseline; age 8.7 yrs) and Year 5 (follow-up; age 9.7 yrs). Physical activity was measured at baseline using the Actigraph GT1M accelerometer to assess total PA (mean accelerometers counts per minute), MVPA; ≥ 4000 counts per minute) and sedentary time (<100 counts per minute).

PRINCIPAL FINDINGS

After adjustment for baseline BMI, SES, sex and ethnicity, MVPA was significantly associated with follow-up BMI (adjusted β  = -0.07; p = 0.002). This association was independent of total PA or sedentary time. Similar results were observed for FMI; again MVPA was significantly associated with follow up FMI (β = -0.16; p = 0.001) independent of total PA or sedentary time. The pattern was similar for WC (β = -0.07), but the association between MVPA and WC did not reach significance at p = 0.06.

CONCLUSION

The results of this study strongly support promotion of MVPA in children.

Development of an ecologically valid approach to assess moderate physical activity using accelerometry in community dwelling women of color: a cross-sectional study

Background

Women of color report the lowest levels of physical activity and highest rates of overweight and obesity in the US. The purpose of this study was to develop an individualized, ecologically valid, field based method to assess physical activity over seven days for community dwelling women of color using accelerometers.

Methods

Accelerometer-measured physical activity, Borg perceived exertion, demographics, blood pressure, heart rate, and anthropometric measures were collected from African American and Hispanic or Latina women (N = 209). A threshold for increased physical activity was determined for each participant by calculating the average count per minute (plus one standard deviation) for each participant collected during a self-selected pace that corresponded to a 'recreational' walk about their neighborhood. The threshold was then used to calculate the amount of time spent doing increased intensity physical activity during a typical week.

Results

Women were middle-aged and obese (M BMI = 34.3 ± 9.3). The average individual activity counts per day ranged from 482-1368 in African American women and 470-1302 in Hispanic or Latina women. On average, African American women spent significantly more time doing what was labeled 'increased' physical activity than Hispanic and Latino women. However neither group approached recommended physical activity levels, as African American women, averaged 1.73% and Hispanic and Latino women averaged 0.83% of their day engaged in increased physical activity (p < 0.05).

Conclusions

This study presents a simple field-based method for developing accelerometer thresholds that identify personalized thresholds of moderate intensity physical activity that can be used by in community-based settings. Findings highlight a need for physical activity programs whose starting points are based upon the individual's typical baseline physical activity level, which is likely to be well below the minimum recommended published guidelines.

Calibration and comparison of accelerometer cut points in preschool children

OBJECTIVE

The present study aimed to develop accelerometer cut points to classify physical activities (PA) by intensity in preschoolers and to investigate discrepancies in PA levels when applying various accelerometer cut points.

METHODS

To calibrate the accelerometer, 18 preschoolers (5.8 ± 0.4 years) performed eleven structured activities and one free play session while wearing a GT1M ActiGraph accelerometer using 15 s epochs. The structured activities were chosen based on the direct observation system Children's Activity Rating Scale (CARS) while the criterion measure of PA intensity during free play was provided using a second-by-second observation protocol (modified CARS). Receiver Operating Characteristic (ROC) curve analyses were used to determine the accelerometer cut points. To examine the classification differences, accelerometer data of four consecutive days from 114 preschoolers (5.5 ± 0.3 years) were classified by intensity according to previously published and the newly developed accelerometer cut points. Differences in predicted PA levels were evaluated using repeated measures ANOVA and Chi Square test.

RESULTS

Cut points were identified at 373 counts/15 s for light (sensitivity: 86%; specificity: 91%; Area under ROC curve: 0.95), 585 counts/15 s for moderate (87%; 82%; 0.91) and 881 counts/15 s for vigorous PA (88%; 91%; 0.94). Further, applying various accelerometer cut points to the same data resulted in statistically and biologically significant differences in PA.

CONCLUSIONS

Accelerometer cut points were developed with good discriminatory power for differentiating between PA levels in preschoolers and the choice of accelerometer cut points can result in large discrepancies.