Kieran P. Dowd

Criterion and Concurrent Validity of the activPAL™ Professional Physical Activity Monitor in Adolescent Females

Background The activPAL has been identified as an accurate and reliable measure of sedentary behaviour. However, only limited information is available on the accuracy of the activPAL activity count function as a measure of physical activity, while no unit calibration of the activPAL has been completed to date. This study aimed to investigate the criterion validity of the activPAL, examine the concurrent validity of the activPAL, and perform and validate a value calibration of the activPAL in an adolescent female population. The performance of the activPAL in estimating posture was also compared with sedentary thresholds used with the ActiGraph accelerometer. Methodologies Thirty adolescent females (15 developmental; 15 cross-validation) aged 15–18 years performed 5 activities while wearing the activPAL, ActiGraph GT3X, and the Cosmed K4B2. A random coefficient statistics model examined the relationship between metabolic equivalent (MET) values and activPAL counts. Receiver operating characteristic analysis was used to determine activity thresholds and for cross-validation. The random coefficient statistics model showed a concordance correlation coefficient of 0.93 (standard error of the estimate = 1.13). An optimal moderate threshold of 2997 was determined using mixed regression, while an optimal vigorous threshold of 8229 was determined using receiver operating statistics. The activPAL count function demonstrated very high concurrent validity (r = 0.96, p<0.01) with the ActiGraph count function. Levels of agreement for sitting, standing, and stepping between direct observation and the activPAL and ActiGraph were 100%, 98.1%, 99.2% and 100%, 0%, 100%, respectively. Conclusions These findings suggest that the activPAL is a valid, objective measurement tool that can be used for both the measurement of physical activity and sedentary behaviours in an adolescent female population.

Cross-Sectional analysis of levels and patterns of objectively measured sedentary time in adolescent females

BackgroundAdolescent females have been highlighted as a particularly sedentary population and the possible negative effects of a sedentary lifestyle are being uncovered. However, much of the past sedentary research is based on self-report or uses indirect methods to quantity sedentary time. Total time spent sedentary and the possible intricate sedentary patterns of adolescent females have not been described using objective and direct measure of body inclination. The objectives of this article are to examine the sedentary levels and patterns of a group of adolescent females using the ActivPAL™ and to highlight possible differences in sedentary levels and patterns across the week and within the school day. A full methodological description of how the data was analyzed is also presented.MethodsOne hundred and eleven adolescent females, age 15-18 yrs, were recruited from urban and rural areas in the Republic of Ireland. Participants wore an ActivPAL physical activity monitor for a 7.5 day period. The ActivPAL directly reports total time spent sitting/lying every 15 seconds and accumulation (frequency and duration) of sedentary activity was examined using a customized MATLAB® computer software programme.ResultsWhile no significant difference was found in the total time spent sitting/lying over the full 24 hour day between weekday and weekend day (18.8 vs. 18.9 hours; p = .911), significantly more sedentary bouts of 1 to 5 minutes and 21 to 40 minutes in duration were accumulated on weekdays compared to weekend days (p < .001). The mean length of each sedentary bout was also longer (9.8 vs. 8.8 minutes; p < .001). When school hours (9 am-3 pm) and after school hours (4 pm-10 pm) were compared, there was no difference in total time spent sedentary (3.9 hours; p = .796) but the pattern of accumulation of the sedentary time differed. There were a greater number of bouts of > 20 minutes duration during school hours than after school hours (4.7 vs. 3.5 bouts; p < .001) while after school time consisted of shorter bouts < 20 minutes.ConclusionsSchool is highlighted as a particularly sedentary setting for adolescent females. Interventions to decrease sedentary time at school and the use of wearable devices which distinguish posture should be encouraged when examining sedentary patterns and behaviors in this population.

The measurement of sedentary patterns and behaviors using the activPAL™ Professional physical activity monitor

Epidemiological studies have associated the negative effects of sedentary time and sedentary patterns on health indices. However, these studies have used methodologies that do not directly measure the sedentary state. Recent technological developments in the area of motion sensors have incorporated inclinometers, which can measure the inclination of the body directly, without relying on self-report or count thresholds. This paper aims to provide a detailed description of methodologies used to examine a range of relevant variables, including sedentary levels and patterns from an inclinometer-based motion sensor. The activPAL Professional physical activity logger provides an output which can be interpreted and used without the need for further processing and additional variables were derived using a custom designed MATLAB® computer program. The methodologies described have been implemented on a sample of 44 adolescent females, and the results of a range of daily physical activity and sedentary variables are described and presented. The results provide a range of objectively measured and objectively processed variables, including total time spent sitting/lying, standing and stepping, number and duration of daily sedentary bouts and both bed hours and non-bed hours, which may be of interest when making association between physical activity, sedentary behaviors and health indices.

Light-intensity physical activity is associated with adiposity in adolescent females.

INTRODUCTION Sedentary behavior (SB) research has relied on accelerometer thresholds to distinguish between sitting/lying time (SLT) and light-intensity physical activity (LIPA). Such methods may misclassify SLT, standing time (StT), and LIPA. This study examines the association between directly measured SB, physical activity (PA), and adiposity in an adolescent female sample. METHODS Female adolescents (n = 195; mean age, 15.7 yr (SD, 0.9)) had body mass index (BMI) (median, 21.7 kg·m (interquartile range, 5.2 kg·m)) and four-site sum of skinfolds (median, 62.0 mm; interquartile range, 37.1 mm) measured and wore an activPAL™ activity monitor for 7 d. SLT, StT, breaks in SLT, and bouts of SLT <30 and ≥30 min were determined from activPAL outputs. A threshold of 2997 counts per 15 s determined moderate-to-vigorous PA. All remaining time was quantified as LIPA. Mixed linear regression models examined associations between PA variables, SB variables, and adiposity. RESULTS Participants spent a mean of 65.3% (SD, 7.1) of the waking day in SLT, 23.0% (SD, 5.3) in StT, 5.6% (SD, 1.5) in LIPA, and 6.1% (SD, 2.4) in moderate-to-vigorous PA. Significant effects for the percentage of LIPA (which excluded StT) with both BMI (β = -4.38, P = 0.0006) and sum of skinfolds (β = -4.05, P = 0.006) were identified. Significant effects for breaks in SLT with BMI (β = -0.30, P = 0.04) were also observed. No additional significant associations were found between activity measures and adiposity. CONCLUSIONS Increased LIPA (excluding StT) and breaks in SLT were negatively associated with adiposity in this sample, independent of age. Interventional work should examine whether reducing SLT through breaks and increasing LIPA may prevent increases in adiposity in adolescent females.

Results From Ireland's 2014 Report Card on Physical Activity in Children and Youth

BACKGROUND Physical activity (PA) levels are a key performance indicator for policy documents in Ireland. The first Ireland Report Card on Physical Activity in Children and Youth aims to set a robust baseline for future surveillance of indicators related to PA in children and youth. METHODS Data collected between 2003-2010 on more than 35,000 7- to 18-year-old children and youth were used and graded using a standardized grading system for 10 indicators. RESULTS Grades assigned for the indicators were as follows: overall physical activity levels, D-; sedentary behavior (TV viewing), C-; organized sport participation, C-: physical education, D-; active play, inconclusive (INC); active transportation, D; school, C-, community and the built environment, B; family, INC; and government, INC. CONCLUSIONS PA recommendations exist in Ireland but this Report Card has shown that participation is still low. A number of promising policies, programs and services are in place but these require thorough evaluation and adequate resourcing. Agreement and implementation of a common framework for the systematic surveillance of indictors related to PA of children and youth is necessary to monitor change over time and ensure the impact of promising work is captured.

Simultaneous validation of five activity monitors for use in adult populations

Numerous cut‐points exist to measure physical activity by accelerometry. The ability to compare accelerometer findings from different devices from different locations may be advantageous to researchers. This study aimed to develop and validate cut‐points for 1.5, 3, and 6 METs in five activity monitors simultaneously. Fifty‐six participants (mean age=39.9 [±11.5] years) performed six activities while wearing a CosMED K4b2 and five activity monitors: activPAL3 Micro, activPAL, ActiGraph GT1M, ActiGraph wGT3X‐BT, and GENEActiv. Receiver operating characteristic curves and analysis were used to develop and validate cut‐points for the vertical axis counts (all activity monitors) and sum of the vector magnitude (ActiGraph wGT3X‐BT and GENEActiv) for 15 second (all devices) and 60 second (ActiGraph devices) epochs. A random coefficients statistical model was used to derive MET predictive equations for all activity monitors. Bland‐Altman plots examined the variability in device error. No 1.5 MET cut‐points were developed for the activPAL devices. All developed cut‐points had high levels of sensitivity and specificity. When cross‐validated in an independent group, high levels of sensitivity and specificity remained (≥77.4%, monitor and intensity dependent). The mean bias based on the Bland‐Altman plots ranged from −0.03 METs to 0.35 METs (monitor dependent). This is the first study to develop and validate cut‐points for five activity monitors simultaneously with high levels of sensitivity and specificity (≥77.4%). This is potentially a step toward cross‐comparison/harmonization of data; however, further validation in a free‐living environment is warranted.

The accuracy of the SenseWear Pro3 and the activPAL3 Micro devices for measurement of energy expenditure

Activity monitors such as the SenseWear Pro3 (SWP3) and the activPAL3 Micro (aP3M) are regularly used by researchers and practitioners to provide estimates of the metabolic cost (METs) of activities in free-living settings. The purpose of this study is to examine the accuracy of the MET predictions from the SWP3 and the aP3M compared to the criterion standard MET values from indirect calorimetry. Fifty-six participants (mean age: 39.9 (±11.5), 25M/31F) performed eight activities (four daily living, three ambulatory and one cycling), while simultaneously wearing a SWP3, aP3M and the Cosmed K4B2 (K4B2) mobile metabolic unit. Paired samples T-tests were used to examine differences between device predicted METs and criterion METs. Bland-Altman plots were constructed to examine the mean bias and limits of agreement for predicted METs compared to criterion METs. SWP3 predicted MET values were significantly different from the K4B2 for each activity (p  ⩽  0.004), excluding sweeping (p  =  0.122). aP3M predicted MET values were significantly different (p  <  0.001) from the K4B2 for each activity. When examining the activities collectively, both devices underestimated activity intensity (0.20 METs (SWP3), 0.95 METs (aP3M)). The greatest mean bias for the SWP3 was for cycling (-3.25 METs), with jogging (-5.16 METs) producing the greatest mean bias for the aP3M. All of the activities (excluding SWP3 sweeping) were significantly different from the criterion measure. Although the SWP3 predicted METs are more accurate than their aP3M equivalent, the predicted MET values from both devices are significantly different from the criterion measure for the majority of activities.

A Systematic Literature Review of Reviews on Techniques for Physical Activity Measurement in Adults: A DEDIPAC Study

The links between increased participation in Physical Activity (PA) and improvements in health are well established. As this body of evidence has grown, so too has the search for measures of PA with high levels of methodological effectiveness (i.e. validity, reliability and responsiveness to change). The aim of this “review of reviews” was to provide a comprehensive overview of the methodological effectiveness of currently employed measures of PA, to aid researchers in their selection of an appropriate tool. A total of 63 review articles were included in this review, and the original articles cited by these reviews were included in order to extract detailed information on methodological effectiveness.Self-report measures of PA have been most frequently examined for methodological effectiveness, with highly variable findings identified across a broad range of behaviours. The evidence-base for the methodological effectiveness of objective monitors, particularly accelerometers/activity monitors, is increasing, with lower levels of variability observed for validity and reliability when compared to subjective measures. Unfortunately, responsiveness to change across all measures and behaviours remains under-researched, with limited information available.Other criteria beyond methodological effectiveness often influence tool selection, including cost and feasibility. However, researchers must be aware of the methodological effectiveness of any measure selected for use when examining PA. Although no “perfect” tool for the examination of PA in adults exists, it is suggested that researchers aim to incorporate appropriate objective measures, specific to the behaviours of interests, when examining PA in free-living environments.

The association between maternal perceptions of own weight status and weight status of her child: results from a national cohort study

Objectives To examine the relationship between maternal self-reported and measured height and weight, maternal perceived weight status and measured body mass index (BMI), and maternal perceived child weight status and measured child BMI. Setting and design Population-representative National Longitudinal Study of Children Growing Up in Ireland. Methods Height and weight of 7655 mothers and their 9-year-old children were objectively measured using standard measurement techniques. Mothers’ perceptions of their own weight status and the weight status of their child were reported. The association between accurate perceptions of the mother for herself and her child was tested. Results Mothers overestimated their height by a mean of 0.5 cm (SD=2.9), underestimated their weight by a mean of 1.4 kg (SD=3.8), consequently underestimating their BMI by a mean of 0.6 kg/m2 (SD=1.7). The majority (60%) of obese mothers correctly categorised their own weight status. Only 17% of mothers of obese children correctly categorised the weight status of their child. Overweight/obese mothers who correctly categorised their own weight status were more likely to correctly categorise their overweight/obese child compared with those who incorrectly categorised their own weight status (44% vs 23%, 95% CI for difference 13% to 28%, p<0.001 for girls; 37% vs 27%, 95% CI 2% to 18%, p=0.02 for boys; significantly greater difference for girls compared with boys, p=0.04). Conclusions Maternal perceptions of their own weight status tend to be more accurate than maternal perceptions of their overweight or obese child. Overweight/obese mothers who correctly categorised their own weight status were more likely to correctly categorise their overweight/obese child.

ActivPAL™ determined sedentary behaviour, physical activity and academic achievement in college students

ABSTRACT The aim of this study was to examine relationships between activPAL™-determined sedentary behavior (SB) and physical activity (PA) with academic achievement. A total of 120 undergraduates (N = 57 female; 20.6 ± 2.3 years) participated in the study. Academic achievement was measured as the grade point average obtained from all completed courses. Participants wore on the right tight an activPAL™ for 7 days to determine total sedentary time, total number of sedentary breaks, sedentary bouts, standing time, light and moderate-to-vigorous physical activity (MVPA). Separate multiple linear regression models were performed to examine associations between SB variables and academic achievement. Light PA, MVPA, total sedentary time, total standing time, or total number of sedentary breaks were not related to academic achievement. Independently of PA, the amount of time spent in sedentary bouts of 10-20min during weekdays was positively related to academic achievement. Given that college students spend the majority of their workday in environments that encourage prolonged sitting, these data suggest that interruptions in prolonged periods of sitting time every 10-20min via short breaks may optimize cognitive operations associated with academic performance.