Validation of a web-based, time-use application to assess children’s movement behaviours: My E-Diary for Activities and Lifestyle (MEDAL) (Preprint)

BACKGROUND Existing modes of collecting self-reported 24-hour movement information from children, including digital assessments, have not been demonstrated to be of acceptable validity when compared to objective measurements. My E-Diary for Activities and Lifestyle (MEDAL) is an interactive web-based diary developed to collect time-use information from children aged 10 years and older. OBJECTIVE This study compared self-reported and accelerometer-measured time spent in movement behaviour among children in Singapore aged 10–11 years. METHODS Participants recorded their daily activities using MEDAL over two specified weekdays and two weekend days, and wore an Actigraph accelerometer on their non-dominant wrist throughout the study to objectively assess movement behaviours. Spearman correlation coefficient and intraclass correlation coefficient were used to compare the accelerometer measurements and self-reports for each movement behaviour. Bland-Altman plots were generated to investigate trends of bias in the self-reports. RESULTS Among the participants aged 10-11 years (n=49, 59% boys), we observed that children reported lower light physical activity (LPA), and higher moderate-to-vigorous physical activity (MVPA), inactivity and night sleep than accelerometer-measured. There was moderate to strong correlation between self-reported and accelerometer-measured MVPA (r=0.37, 95% CI 0.20–0.54), inactivity (r=0.36, 95% CI 0.18–0.54) and night sleep (r=0.58, 95% CI 0.43–0.74); the correlation for LPA was poor (r=0.19, 95% CI 0.02–0.36). Agreement was poor for all behaviours (MVPA ICC 0.24, 95% CI 0.07–0.40; LPA ICC=0.19, 95% CI 0.01–0.36; inactivity ICC=0.29, 95% CI 0.11–0.44; night sleep ICC=0.45, 95% CI 0.29–0.58). There was stronger correlation and agreement on weekdays for inactivity and night sleep; conversely, there was stronger correlation and agreement for MVPA and LPA on weekend days. Finally, we observed that with increasing MVPA, children tended to report higher MVPA than accelerometer measurements. There were no clear trends for the other behaviours. CONCLUSIONS MEDAL may be used to assess movement behaviours of children. Based on self-reports, the children are able to estimate their time spent in MVPA, inactivity and night sleep, although actual time spent in these behaviours may differ from accelerometer-derived estimates; self-reported LPA warrant cautious interpretation. Observable differences in reporting accuracy exist between weekdays and weekend days.

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

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17249323 ◽

2020 ◽

Vol 17 (24) ◽

pp. 9323

Author(s):

Alyse Davies ◽

Margaret Allman-Farinelli ◽

Katherine Owen ◽

Louise Signal ◽

Cameron Hosking ◽

...

Keyword(s):

Physical Activity ◽

Sedentary Behavior ◽

Correlation Coefficient ◽

Image Coding ◽

Large Scale ◽

Vigorous Physical Activity ◽

Intraclass Correlation ◽

Small Scale ◽

Wearable Camera ◽

Wearable Cameras

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.

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Validity and Interinstrument Reliability of a Medical Grade Physical Activity Monitor in Older Adults

Journal for the Measurement of Physical Behaviour ◽

10.1123/jmpb.2019-0074 ◽

2021 ◽

Vol 4 (1) ◽

pp. 31-38

Author(s):

Myles W. O’Brien ◽

William R. Wojcik ◽

Jonathon R. Fowles

Keyword(s):

Physical Activity ◽

Older Adults ◽

Correlation Coefficient ◽

Intraclass Correlation Coefficient ◽

Vigorous Physical Activity ◽

Intraclass Correlation ◽

Activity Monitor ◽

Moderate Physical Activity ◽

Step Rate ◽

Medical Grade

Wearable physical activity monitors are associated with an increase in user’s habitual physical activity levels. Most of the older adult population do not meet the national moderate- to vigorous-intensity physical activity (MVPA) recommendations and may benefit from being prescribed a physical activity monitor. The PiezoRx is a class one medical grade device that uses step rate thresholds to measure MVPA. The validity and reliability of the PiezoRx in measuring MVPA has yet to be determined in older persons. We assessed the validity and interinstrument reliability of the PiezoRx to measure steps and MVPA in older adults. Participants (n = 19; 68.8 ± 2.3 years) wore an Omron HJ-320 pedometer, ActiGraph GT3X accelerometer, and four PiezoRx monitors during a five-stage treadmill walking protocol. The PiezoRx devices were set at moderate physical activity and vigorous physical activity step rate thresholds (steps per minute) of 100/120, 110/130, adjusted for height and adjusted for height + fitness. The PiezoRx exhibited a stronger correlation (intraclass correlation coefficient = .82) with manually counted steps than the ActiGraph (intraclass correlation coefficient = .53) and Omron (intraclass correlation coefficient = .54) and had a low absolute percentage error (3 ± 6%). The PiezoRx with moderate physical activity/vigorous physical activity step thresholds adjusted to 110/130 was strongly correlated to indirect calorimetry (0.84, p < .001) and best distinguished each walking stage as MVPA or not (sensitivity: 88%; specificity: 95%). The PiezoRx monitor is a valid and reliable measure of step count and MVPA among older adults. The device’s ability to measure MVPA in absolute terms was improved when step rate thresholds for moderate physical activity/vigorous physical activity were increased to 110/130 steps per minute in this population.

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Association of daily composition of physical activity and sedentary behaviour with incidence of cardiovascular disease in older adults

International Journal of Behavioral Nutrition and Physical Activity ◽

10.1186/s12966-021-01157-0 ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Manasa S. Yerramalla ◽

Duncan E. McGregor ◽

Vincent T. van Hees ◽

Aurore Fayosse ◽

Aline Dugravot ◽

...

Keyword(s):

Physical Activity ◽

Older Adults ◽

Sedentary Behaviour ◽

Cox Regression ◽

Vigorous Physical Activity ◽

Movement Behaviour ◽

Cvd Risk ◽

Daily Movement ◽

Intensity Physical Activity ◽

Current Duration

Abstract Background Moderate-to-vigorous physical activity (MVPA) is proposed as key for cardiovascular diseases (CVD) prevention. At older ages, the role of sedentary behaviour (SB) and light intensity physical activity (LIPA) remains unclear. Evidence so far is based on studies examining movement behaviours as independent entities ignoring their co-dependency. This study examines the association between daily composition of objectively-assessed movement behaviours (MVPA, LIPA, SB) and incident CVD in older adults. Methods Whitehall II accelerometer sub-study participants free of CVD at baseline (N = 3319, 26.7% women, mean age = 68.9 years in 2012–2013) wore a wrist-accelerometer from which times in SB, LIPA, and MVPA during waking period were extracted over 7 days. Compositional Cox regression was used to estimate the hazard ratio (HR) for incident CVD for daily compositions of movement behaviours characterized by 10 (20 or 30) minutes greater duration in one movement behaviour accompanied by decrease in another behaviour, while keeping the third behaviour constant, compared to reference composition. Analyses were adjusted for sociodemographic, lifestyle, cardiometabolic risk factors and multimorbidity index. Results Of the 3319 participants, 299 had an incident CVD over a mean (SD) follow-up of 6.2 (1.3) years. Compared to daily movement behaviour composition with MVPA at recommended 21 min per day (150 min/week), composition with additional 10 min of MVPA and 10 min less SB was associated with smaller risk reduction – 8% (HR, 0.92; 95% CI, 0.87–0.99) – than the 14% increase in risk associated with a composition of similarly reduced time in MVPA and more time in SB (HR, 1.14; 95% CI, 1.02–1.27). For a given MVPA duration, the CVD risk did not differ as a function of LIPA and SB durations. Conclusions Among older adults, an increase in MVPA duration at the expense of time in either SB or LIPA was found associated with lower incidence of CVD. This study lends support to public health guidelines encouraging increase in MVPA or at least maintain MVPA at current duration.

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Do differences in compositional time use explain ethnic variation in the prevalence of obesity in children? Analyses using 24-hour accelerometry

10.26686/wgtn.12830837.v1 ◽

2020 ◽

Cited By ~ 1

Author(s):

RW Taylor ◽

JJ Haszard ◽

VL Farmer ◽

R Richards ◽

Lisa Te Morenga ◽

...

Keyword(s):

Physical Activity ◽

Ethnic Differences ◽

Time Use ◽

Vigorous Physical Activity ◽

Obesity Prevalence ◽

Z Score ◽

Movement Data ◽

Increased Risk ◽

Prevalence Of Obesity ◽

Log Ratio

© 2019, Springer Nature Limited. Background/Objectives: Whether variation in sleep and physical activity explain marked ethnic and socioeconomic disparities in childhood obesity is unclear. As time spent in one behaviour influences time spent in other behaviours across the 24-hour day, compositional analyses are essential. The aims of this study were to determine how ethnicity and socioeconomic status influence compositional time use in children, and whether differences in compositional time use explain variation in body mass index (BMI) z-score and obesity prevalence across ethnic groups. Methods: In all, 690 children (58% European, 20% Māori, 13% Pacific, 9% Asian; 66% low-medium deprivation and 34% high deprivation) aged 6–10 years wore an ActiGraph accelerometer 24-hours a day for 5 days yielding data on sedentary time, sleep, light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA). Height and weight were measured using standard techniques and BMI z-scores calculated. Twenty-four hour movement data were transformed into isometric log-ratio co-ordinates for multivariable regression analysis and effect sizes were back-transformed. Results: European children spent more time asleep (predicted difference in minutes, 95% CI: 16.1, 7.4–24.9) and in MVPA (6.6 min, 2.4–10.4), and less time sedentary (−10.2 min, −19.8 to −0.6) and in LPA (−12.2 min, −21.0 to −3.5) than non-European children. Overall, 10% more sleep was associated with a larger difference in BMI z-score (adjusted difference, 95% CI: −0.13, −0.25 to −0.01) than 10% more MVPA (−0.06, −0.09 to −0.03). Compositional time use explained 35% of the increased risk of obesity in Pacific compared with European children after adjustment for age, sex, deprivation and diet, but only 9% in Māori and 24% in Asian children. Conclusions: Ethnic differences in compositional time use explain a relatively small proportion of the ethnic differences in obesity prevalence that exist in children.

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Validation of self-reported physical activity by accelerometry among primary school children in Kilimanjaro, Tanzania: a pilot study

AAS Open Research ◽

10.12688/aasopenres.13118.1 ◽

2020 ◽

Vol 3 ◽

pp. 40

Author(s):

Mary Vincent Mosha ◽

Elizabeth Kasagama ◽

Philip Ayieko ◽

Jim Todd ◽

Sia E. Msuya ◽

...

Keyword(s):

Physical Activity ◽

Primary School ◽

School Children ◽

Primary Schools ◽

Vigorous Physical Activity ◽

Primary School Children ◽

Positive Correlation ◽

Self Reports ◽

Study Participants ◽

Moderate Positive Correlation

Background: Self-reports are commonly used to assess physical activity in children. Existing self-reports for physical activity have not been validated for use among primary school children in Kilimanjaro, Tanzania. In order to understand if primary school children can accurately report their physical activity, we examined the validity of self-reported physical activity against accelerometer measured physical activity. Methods: A community based cross-sectional study was conducted from May to July, 2018 among four primary schools in Moshi municipal and Moshi rural districts, Kilimanjaro, Tanzania. A total of 51 primary school children aged 9–11 years were enrolled using a simple random sampling technique. A self-reported questionnaire was used to collect physical activity related variables. In addition, children wore accelerometers for seven consecutive days to capture physical activity movements. Spearman’s rank test and Bland Altman plots were used for assessing validity and agreement between self-reports and accelerometer moderate to vigorous physical activity (MVPA). Results: The mean age of the study participants was 10 (SD=0.8) years. Majority of the study participants were female 32 (63%). A moderate, positive correlation was found between self-reports and accelerometer MVPA (rho=0.36, p=0.009). Accelerometer had higher MVPA compared to self-reports. Children who reported walking to school had higher MVPA for both accelerometer and self- reports compared to children who use other means of transport to school, e.g. school buses (p < 0.001). Conclusions: This study found the moderate positive correlation between self-reports and accelerometers. Self-reports are prone to errors due to recall bias, and this interferes their validity. More research is needed to develop better self-reported measures with specific activities which can easily be recalled by children. Also, researchers have to be aware of self-reports validity limitation.

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Active Transport, Not Device Use, Associates with Self-Reported School Week Physical Activity in Adolescents

Behavioral Sciences ◽

10.3390/bs9030032 ◽

2019 ◽

Vol 9 (3) ◽

pp. 32 ◽

Cited By ~ 1

Author(s):

Ryan Burns ◽

Christopher Pfledderer ◽

Timothy Brusseau

Keyword(s):

Physical Activity ◽

Active Transport ◽

Electronic Device ◽

Vigorous Physical Activity ◽

Outcome Variable ◽

Linear Regression Models ◽

Web Based ◽

School Week ◽

Device Use ◽

Youth Activity

The purpose of this study was to examine the relationships among active transport, electronic device-use, and self-reported school week moderate-to-vigorous physical activity (MVPA) in a sample of adolescents. The sample consisted of 1445 adolescents enrolled in the Family Life, Activity, Sun, Health, and Eating study. A panel research organization invited panel members balanced to the US population on sex, census division, household income and size, and race/ethnicity. Web-based surveys were administered to each selected adolescent. Adolescents answered questions pertaining to out-of-school electronic device-use and active transport to and from school. Predicted weekly minutes of MVPA were calculated from the Youth Activity Profile. The outcome variable was predicted school week MVPA (in minutes). The predictive utility of device-use and active transport variables on self-reported school week MVPA were examined using weighted multiple linear regression models. After adjusting for age, sex, and BMI, active transport to school (b = 12.32, 95% CI [9.72–14.93], p < 0.001) and from school (b = 7.18, 95% CI [4.79–5.57], p < 0.001) were significantly associated with self-reported school week MVPA. No device-use variables were significantly associated with school week MVPA. Active transport to and from school may have an impact on school week MVPA in adolescents.

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Dynamics of sleep, sedentary behavior, and moderate-to-vigorous physical activity on school versus nonschool days

SLEEP ◽

10.1093/sleep/zsaa174 ◽

2020 ◽

Author(s):

Bridget Armstrong ◽

Michael W Beets ◽

Angela Starrett ◽

Keith Brazendale ◽

Gabrielle Turner-McGrievy ◽

...

Keyword(s):

Physical Activity ◽

Sedentary Behavior ◽

Time Use ◽

Structural Equation ◽

Time Series Data ◽

Vigorous Physical Activity ◽

Series Data ◽

Equation Modeling ◽

Specific Behavior ◽

School Day

Abstract Study Objectives Studies examining time-use activity behaviors (sleep, sedentary behavior, and physical activity) on school days compared with nonschool days have examined these behaviors independently, ignoring their interrelated nature, limiting our ability to optimize the health benefits of these behaviors. This study examines the associations of school-day (vs. nonschool day) with time-use activity behaviors. Methods Time series data (6,642 days) from Fitbits (Charge-2) were collected (n = 196, 53% female, 5–10 years). We used a variable-centered dynamic structural equation modeling approach to estimate day-to-day associations of time-use activity behaviors on school days for each child. We then used person-centered cluster analyses to group individuals based on these estimates. Results Within-participant analysis showed that on school days (vs. nonschool days), children (1) slept less (β = −0.17, 95% CI = −0.21, −0.13), (2) were less sedentary (β = −0.05, 95% CI = −0.09, −0.02), and (3) had comparable moderate-to-vigorous physical activity (MVPA; β = −0.05, 95% CI = −0.11, 0.00). Between-participant analysis showed that, on school days, children with higher sleep carryover experienced greater decreases in sleep (β = 0.44, 95% CI = 0.08, 0.71), children with higher body mass index z-score decreased sedentary behavior more (β = −0.41, 95% CI = −0.64, −0.13), and children with lower MVPA increased MVPA more (β = −0.41, 95% CI −0.64, −0.13). Cluster analysis demonstrated four distinct patterns of connections between time-use activity behaviors and school (High Activity, Sleep Resilient, High Sedentary, and Dysregulated Sleep). Conclusions Using a combination of person-centered and more traditional variable-centered approaches, we identified patterns of interrelated behaviors that differed on school, and nonschool days. Findings can inform targeted intervention strategies tailored to children’s specific behavior patterns.

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Variables Associated With Active and Inactive Behavior During the After-School Period

Pediatric Exercise Science ◽

10.1123/pes.25.2.288 ◽

2013 ◽

Vol 25 (2) ◽

pp. 288-299 ◽

Cited By ~ 4

Author(s):

Eric Wickel

Keyword(s):

Physical Activity ◽

Time Use ◽

Screen Time ◽

Vigorous Physical Activity ◽

Peer Groups ◽

Fourth Grade ◽

After School ◽

Light Physical Activity ◽

Children's Behavior ◽

School Period

This study analyzed time-use interviews to report levels of active and inactive behavior during the after-school period (3–6 pm). Interviews were conducted on random days from three separate seasons during third and fourth grade. Youth with at least two interviews during third (356 completed 2 interviews; 506 completed 3 interviews [9 yrs; 50% boys]) and fourth (186 completed 2 interviews; 768 completed 3 interviews [10 yrs; 50% boys]) grade were included to report levels of moderate-to-vigorous physical activity (MVPA), light physical activity, inactive screen time, inactive nonscreen time, and travel by location and who the activity was undertaken with. Reporting time outside the home and with peers (single or group) was related to higher levels of MVPA. While inside the home, screen and nonscreen proportions were comparable (38% and 40%, respectively), despite unique patterns (screen: boys > girls; nonscreen: girls > boys). Reporting time with both parents was associated with more nonscreen time; whereas reporting time with peer groups was associated with lower screen time. Understanding active and inactive patterns of children’s behavior outside of school hours can be very important in contributing toward the development of innovative interventions for increasing physical activity.

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The Inventory of Physical Activity Barriers for Adults 50 Years and Older: Refinement and Validation

Innovation in Aging ◽

10.1093/geroni/igab046.2889 ◽

2021 ◽

Vol 5 (Supplement_1) ◽

pp. 789-789

Author(s):

Mariana Wingood ◽

Salene Jones ◽

Nancy Gell ◽

Denise Peters ◽

Jennifer Brach

Keyword(s):

Physical Activity ◽

Factor Analysis ◽

Correlation Coefficient ◽

Intraclass Correlation Coefficient ◽

Assessment Tool ◽

Intraclass Correlation ◽

Community Dwelling ◽

Cross Sectional ◽

Retest Reliability ◽

Test Retest Reliability

Abstract Addressing physical activity (PA) barriers is an essential component of increasing PA among the 56-73% of community-dwelling adults 50 years and older who are not performing the recommended 150 minutes of moderate-to-vigorous PA. As there is no feasible, multi-factorial tool to assess PA barriers among this population, we developed and validated a PA barrier assessment tool called the Inventory of Physical Activity Barriers (IPAB). We collected cross-sectional data on 503 adults (mean age 70.1), with 79 participants completing the scale twice for test-retest reliability and 64 completing a cross-over design examining the ability to use two administration formats interchangeably. Our analyses consisted of exploratory and confirmatory factor analysis, Cronbach alpha, intraclass correlation coefficient, Bland-Altman Plot, and t-tests. Using factor analysis, we identified and confirmed an eight-factor solution consisting of 27 items. The 27-item IPAB is internally consistent (alpha= 0.91), has a high test-retest reliability (intraclass correlation coefficient=0.99), and can differentiate between individuals who meet the recommended levels of PA and those who do not (p < 0.001). The IPAB scores ranged between 1.00-3.11 for the paper format (mean=1.78) and 1.07-3.48 for the electronic format (mean=1.78), with no statistical difference between the paper and electronic administration formats (p=0.94), resulting in the conclusion that the two administration formats can be used interchangeably. Participant feedback illustrates that the IPAB is easy to use, has clear instruction, and is an appropriate length. The newly validated IPAB scale can be used to develop individualized PA interventions that address PA barriers among patients 50 years and older.

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Compositional analysis of the association between mortality and 24-hour movement behaviour from NHANES

European Journal of Preventive Cardiology ◽

10.1177/2047487319867783 ◽

2019 ◽

pp. 204748731986778 ◽

Cited By ~ 12

Author(s):

Duncan E McGregor ◽

Javier Palarea-Albaladejo ◽

Philippa M Dall ◽

Borja del Pozo Cruz ◽

Sebastien FM Chastin

Keyword(s):

Physical Activity ◽

Sedentary Behaviour ◽

Time Use ◽

Compositional Data ◽

Cox Regression ◽

Vigorous Physical Activity ◽

Lifestyle Factors ◽

Accelerometer Data ◽

Cox Regression Analysis ◽

Daily Time

Aims Previous prospective studies of the association between mortality and physical activity have generally not fully accounted for the interplay between movement behaviours. A compositional data modelling approach accounts for relative scale and co-dependency in time-use data across physical activity behaviours of the 24-hour day. Methods A prospective analysis of the National Health and Nutrition Examination Survey 2005–2006 on N = 1468 adults ( d = 135 deaths) in ages 50–79 years was undertaken using compositional Cox regression analysis. Daily time spent in sedentary behaviour, light intensity (LIPA) and moderate-to-vigorous physical activity (MVPA) was determined from waist-mounted accelerometer data (Actigraph 7164) and supplemented with self-reported sleep data to determine the daily time-use composition. Results The composition of time spent in sedentary behaviour, LIPA, MVPA and sleep was associated with mortality rate after allowing for age and sex effects ( p < 0.001), and remained significant when other lifestyle factors were added ( p < 0.001). This was driven primarily by the preponderance of MVPA; however, significant changes are attributable to LIPA relative to sedentary behaviour and sleep, and sedentary behaviour relative to sleep. The final ratio ceased to be statistically significant after incorporating lifestyle factors. The preponderance of MVPA ceased to be statistically significant after incorporating health at outset and physical limitations on movement. Conclusions An association is inferred between survival rate and the physical activity composition of the day. The MVPA time share is important, but time spent in LIPA relative to sedentary behaviour and sleep is also a significant factor. Increased preponderance of MVPA may have detrimental associations at higher levels of MVPA.

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