A Validation Study of Assessing Physical Activity and Sedentary Behavior in Children Aged 3 to 5 Years

2010 ◽  
Vol 22 (3) ◽  
pp. 408-420 ◽  
Author(s):  
Li Ming Wen ◽  
Hidde P. van der Ploeg ◽  
James Kite ◽  
Aaron Cashmore ◽  
Chris Rissel
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Correlation Coefficients ◽  
Future Research ◽  
Accelerometer Data ◽  
Sedentary Behaviors ◽  
Childcare Centers ◽  
Reference Measure ◽  
Activity Preferences ◽  
Activity Diary

Assessing young children’s physical activity and sedentary behavior can be challenging and costly. This study aimed to assess the validity of a brief survey about activity preferences as a proxy of physical activity and of a 7-day activity diary, both completed by the parents and using accelerometers as a reference measure. Thirty-four parents and their children (aged 3–5 years) who attended childcare centers in Sydney (Australia) were recruited for the study. Parents were asked to complete a 9-item brief survey about activity preferences of their child and a 7-day diary recording the child’s physical activity and sedentary behaviors. Both measures were compared with accelerometer data collected from the child over the same period as the diary survey. The findings suggest that parent completed diaries have acceptable correlation coefficients with accelerometer measures and could be considered in future research assessing physical activity and sedentary behavior of children aged 3–5 years.

Measuring Physical Activity in Juvenile Idiopathic Arthritis: Activity Diary Versus Accelerometer

2017 ◽  
Vol 44 (8) ◽  
pp. 1249-1256 ◽  
Author(s):  
Wineke Armbrust ◽  
G.J.F. Joyce Bos ◽  
Jan H.B. Geertzen ◽  
Pieter J.J. Sauer ◽  
Pieter U. Dijkstra ◽  
...  
Keyword(s):  
Physical Activity ◽  
Juvenile Idiopathic Arthritis ◽  
Effect Size ◽  
Convergent Validity ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Accelerometer Data ◽  
Individual Level ◽  
Intraclass Correlation Coefficients ◽  
Activity Diary

Objective.(1) To determine convergent validity of an activity diary (AD) and accelerometer (Actical brand/Phillips-Respironics) in measuring physical activity (PA) in children with juvenile idiopathic arthritis (JIA). (2) To determine how many days give reliable results. (3) To analyze effects of correcting accelerometer data for non-wear.Methods.Patients with JIA (8–13 yrs) were recruited from 3 Dutch pediatric rheumatology centers. PA was assessed for 7 days with an AD and accelerometer, and was expressed as mean min/day of rest, light PA (LPA), moderate to vigorous PA (MVPA), and PA level (PAL). To analyze convergent validity, intraclass correlation coefficients (ICC) were calculated and paired sample Student t tests were performed. The required number of days to achieve reliable results was calculated using the Spearman-Brown prophecy formula.Results.Convergent validity between AD and accelerometer was moderate for rest and PAL (ICC 0.41). ICC for LPA and MVPA were < 0.24. AD overestimated PAL and MVPA compared with the accelerometer. Wearing the accelerometer 7–19 days gave reliable PA estimates on group and individual levels. For the AD, 13–36 days were needed. Adjusting accelerometer data for non-wear resulted in a clinically relevant higher mean number of min/day spent in LPA (effect size 1.12), but not in MVPA (effect size 0.44).Conclusion.Convergent validity between AD and accelerometer is moderate to poor. In children with JIA, 1-week assessment with an accelerometer is sufficient to measure PA (all levels) reliably. On an individual level and for clinical use, 3 weeks are required. Additional use of AD enables correction for non-wear of accelerometer data.

scholarly journals Moving in Sync: Hourly Physical Activity and Sedentary Behavior are Synchronized in Couples

2019 ◽  
Vol 54 (1) ◽  
pp. 10-21 ◽  
Author(s):  
Theresa Pauly ◽  
Jan Keller ◽  
Nina Knoll ◽  
Victoria I Michalowski ◽  
Diana Hilda Hohl ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Physical Activity Promotion ◽  
Accelerometer Data ◽  
Sedentary Behaviors ◽  
Daily Lives ◽  
Individual Level ◽  
Physical Activity Interventions ◽  
Activity Promotion ◽  
Intensity Physical Activity

Abstract Background Overall time spent in moderate-to-vigorous intensity physical activity (MVPA) and sedentary behavior are both correlated in couples. Knowledge about the nature and psychosocial correlates of such dyadic covariation could inform important avenues for physical activity promotion. Purpose The present study investigates hour-by-hour covariation between partners (i.e., synchrony) in MVPA and sedentary behavior as partners engage in their daily lives and links it with person-level MVPA/sedentary behavior, temporal characteristics, and relationship variables. Methods We used 7-day accelerometer data from two couple studies (Study 1, n = 306 couples, aged 18–80 years; Study 2, n = 108 couples, aged 60–87 years) to estimate dyadic covariation in hourly MVPA and sedentary behavior between partners. Data were analyzed using coordinated multilevel modeling. Results In both studies, hourly MVPA and sedentary behavior exhibited similarly sized dyadic covariation between partners in the low-to-medium range of effects. Higher MVPA synchrony between partners was linked with higher individual weekly MVPA and higher individual weekly sedentary levels, whereas higher sedentary synchrony between partners was associated with higher individual weekly MVPA but lower individual weekly sedentary levels. MVPA and sedentary synchrony were higher in the morning and evening, more pronounced on weekends, and associated with more time spent together, longer relationship duration, and time-varying perceptions of higher partner closeness. Conclusions This study demonstrates that MVPA and sedentary behaviors do not occur in a social vacuum. Instead, they are linked with close others such as partners. Thus, capitalizing on social partners may increase the effectiveness of individual-level physical activity interventions.

scholarly journals mHealth Interventions to Address Physical Activity and Sedentary Behavior in Cancer Survivors: A Systematic Review

2021 ◽  
Vol 18 (11) ◽  
pp. 5798
Author(s):  
Selina Khoo ◽  
Najihah Mohbin ◽  
Payam Ansari ◽  
Mahfoodha Al-Kitani ◽  
Andre Matthias Müller
Keyword(s):  
Physical Activity ◽  
Cancer Survivors ◽  
Sedentary Behavior ◽  
Total Activity ◽  
Personal Contact ◽  
Future Research ◽  
Controlled Trials ◽  
Cancer Types ◽  
Study Participants ◽  
Multicomponent Interventions

This review aimed to identify, evaluate, and synthesize the scientific literature on mobile health (mHealth) interventions to promote physical activity (PA) or reduce sedentary behavior (SB) in cancer survivors. We searched six databases from 2000 to 13 April 2020 for controlled and non-controlled trials published in any language. We conducted best evidence syntheses on controlled trials to assess the strength of the evidence. All 31 interventions included in this review measured PA outcomes, with 10 of them also evaluating SB outcomes. Most study participants were adults/older adults with various cancer types. The majority (n = 25) of studies implemented multicomponent interventions, with activity trackers being the most commonly used mHealth technology. There is strong evidence for mHealth interventions, including personal contact components, in increasing moderate-to-vigorous intensity PA among cancer survivors. However, there is inconclusive evidence to support mHealth interventions in increasing total activity and step counts. There is inconclusive evidence on SB potentially due to the limited number of studies. mHealth interventions that include personal contact components are likely more effective in increasing PA than mHealth interventions without such components. Future research should address social factors in mHealth interventions for PA and SB in cancer survivors.

Prevalence of Physical Activity and Sedentary Behaviors in US High School Students by Metropolitan Status and Geographic Region

2006 ◽  
Vol 3 (4) ◽  
pp. 365-380 ◽  
Author(s):  
Andrew E. Springer ◽  
Deanna M. Hoelscher ◽  
Steven H. Kelder
Keyword(s):  
Physical Activity ◽  
High School Students ◽  
Sedentary Behavior ◽  
Geographic Region ◽  
Sedentary Behaviors ◽  
The South ◽  
School Students ◽  
Cross Sectional ◽  
Nationally Representative ◽  
Tv Watching

Background:Geographic differences in the prevalence of physical activity (PA) have been found among adults in the US; similar studies have not been conducted among adolescents.Methods:Using nationally representative cross-sectional data from the CDC’s 2003 Youth Risk Behavior Survey, we estimated the prevalence of PA and sedentary behaviors by metropolitan status and geographic region.Results:The prevalence of PA was lowest and prevalence of sedentary behavior highest for urban students. Students from the South reported the lowest prevalence of PA and the highest prevalence of TV watching, while students from the West generally reported the highest PA prevalence and lowest sedentary behavior prevalence. Prevalence differences ranged from < 1.0% to > 15%, with most differences falling between 5% and 10%.Conclusions:Findings mirror regional variations previously observed in adult PA. We need to understand factors that contribute to lower PA in youth living in the South and in urban settings.

scholarly journals Capturing the Pattern of Physical Activity and Sedentary Behavior: Exposure Variation Analysis of Accelerometer Data

2014 ◽  
Vol 11 (3) ◽  
pp. 614-625 ◽  
Author(s):  
Leon Straker ◽  
Amity Campbell ◽  
Svend Erik Mathiassen ◽  
Rebecca Anne Abbott ◽  
Sharon Parry ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Public Health Research ◽  
Office Workers ◽  
Accelerometer Data ◽  
Variation Analysis ◽  
Occupational Groups ◽  
Time Pattern ◽  
Exposure Variation Analysis ◽  
First Time

Background:Capturing the complex time pattern of physical activity (PA) and sedentary behavior (SB) using accelerometry remains a challenge. Research from occupational health suggests exposure variation analysis (EVA) could provide a meaningful tool. This paper (1) explains the application of EVA to accelerometer data, (2) demonstrates how EVA thresholds and derivatives could be chosen and used to examine adherence to PA and SB guidelines, and (3) explores the validity of EVA outputs.Methods:EVA outputs are compared with accelerometer data from 4 individuals (Study 1a and1b) and 3 occupational groups (Study 2): seated workstation office workers (n = 8), standing workstation office workers (n = 8), and teachers (n = 8).Results:Line graphs and related EVA graphs highlight the use of EVA derivatives for examining compliance with guidelines. EVA derivatives of occupational groups confirm no difference in bouts of activity but clear differences as expected in extended bouts of SB and brief bursts of activity, thus providing evidence of construct validity.Conclusions:EVA offers a unique and comprehensive generic method that is able, for the first time, to capture the time pattern (both frequency and intensity) of PA and SB, which can be tailored for both occupational and public health research.

Abstract MP92: Sedentary Behavior: Do Television-viewing and Total Time Sitting Measure the Same Component?

Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Heather A McGrane Minton ◽  
Kelly Thevenet-Morrison ◽  
I. Diana Fernandez
Keyword(s):  
Physical Activity ◽  
Health Outcomes ◽  
Sedentary Behavior ◽  
Television Viewing ◽  
Weighted Kappa ◽  
Sitting Time ◽  
Viewing Time ◽  
Kappa Statistics ◽  
Sedentary Behaviors ◽  
Tv Viewing

Background: Sedentary behaviors (SB) are activities associated with prolonged time periods of sitting, reclining, or laying down during waking hours. While the relation between SB and physical activity is complex, the common consensus is that SB is not the absence of physical activity and consists of its own determinants posing distinct health outcomes. These behaviors are of significant public health importance as the majority of Americans spend much of their days in SB and due to the increased risks of morbidity and mortality associated with SB. Adverse health outcomes associated with SB include cardiovascular disease, obesity, metabolic syndrome, hypertension and mortality. Television-viewing time and total sitting time have both been used widely to assess time spent in SB and therefore we hypothesize that TV-viewing time and total hours sitting will have high concordance and can be used interchangeably to represent sedentary behaviors. Methods: Using a sample (n = 2858) from the Images of a Healthy Worksite study, a group-randomized control trial involving nutrition and physical activity, the current study assessed how two different tools measured time spent in SB. Tertiles were created based upon the distribution of hours sitting and hours spent TV-vewing. Weighted Kappa statistics were used to measure concordance between hours of TV-viewing and total hours of time spent sitting for the entire sample and for subgroup analyses. Results: Weighted Kappa statistics for tertiles of hours sitting and tv hours were 0.0046, indicating little agreement on the television and the sitting items. Kappa w statistics for BMI categories also showed poor agreement (obese Kappa w = 0.02, overweight Kappa w = 0.002, and healthy subjects Kappa w = 0.006. The Kappa w statistics for males and females were -0.006 and 0.02, respectively. Kappa w statistics for the intervention group (Kappa w = 0.007) and for the control group (Kappa w = 0.0005) also showed little agreement. Conclusions: These results suggest that although commonly used, using television viewing time and total time spent sitting as interchangeable markers of SB, is not a valid assumption. We propose that total time spent sitting and hours spent television-viewing represent different domains within the construct of sedentary behavior. It is important for future researchers to use measures of sedentary behavior that capture the numerous domains involved in measuring SB to allow for the most sensitive measurement of this high-risk behavior.

Exploring Potential Mediation Pathways on the Relationship Between Acculturation and Body Mass Index (BMI) Among Latino Adolescents

2021 ◽  
pp. 154041532110298
Author(s):  
Christopher Johansen ◽  
Kim D. Reynolds ◽  
Bin Xie ◽  
Paula Palmer
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Sedentary Behavior ◽  
Body Mass ◽  
Self Report ◽  
Latino Adolescents ◽  
Future Research ◽  
Public High Schools ◽  
Multiple Mediation ◽  
The Relationship

Background: Positive associations have been observed between acculturation and body mass index (BMI), but the mediators of this relationship are not well established. Acculturation researchers have called for investigating the influence of socio-contextual variables as mediators. The objective of this study was to test the mediating effects of salty snacks, sweet snacks, physical activity, and sedentary behavior on the relationship between acculturation and BMI among Latino adolescents. Methods: Adolescents who self-identified as Latino ( n = 431) at public high schools in Southern California were recruited and completed a self-report survey. A bootstrapped multiple mediation model was used to test mediation pathways. Results: Acculturation was positively associated with physical activity ( B = 0.09, p < .05). The indirect effects of salty snacks, sweet snacks, physical activity, and sedentary behavior were not associated with BMI, suggesting no mediation. Conclusions: Future research should examine additional mediating variables on the relationship between acculturation and BMI.

scholarly journals The FLASHE Study: A Publicly Available Data Resource

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1337-1337
Author(s):  
Linda Nebeling ◽  
Laura Dwyer ◽  
April Oh
Keyword(s):  
Physical Activity ◽  
Health Behaviors ◽  
The United States ◽  
National Sample ◽  
Study Data ◽  
Accelerometer Data ◽  
Sedentary Behaviors ◽  
Data Resource ◽  
Neighborhood Socioeconomic Status ◽  
Funding Sources

Abstract Objectives The Family Life, Activity, Sun, Health and Eating (FLASHE) survey was conducted in 2014 to collect information on eating, physical activity, sedentary behaviors, and behavioral correlates from a national sample of parent-adolescent dyads in the United States. It is a publicly available data resource which can be used to research questions about psychosocial, generational, household and neighborhood correlates of health behaviors. Methods Data were collected from dyads of caregivers and their adolescent children (ages 12–17) (n = 1072 completed dyads) between April – October 2014. Two surveys for each respondent: one on diet-related behaviors and one on physical activity-related behaviors were collected. An additional 407 dyads wore an accelerometer for seven days and completed an activity log. A ‘geoFLASHE’ dataset used parent-provided address information for home and school to geocode these locations and compute a set of variables applied to several different neighborhood definitions, including both circular and street-network buggers with distances ranging from 400 – 1200 meters. Accelerometer variables were computed for a subset of adolescents who wore an Actigraph Gt3x+ for seven days and includes estimates from raw and activity counts data. Training webinars on dyadic analytical methods, models and applications were provided. Results The geoFLASHE dataset includes variables for neighborhood, socioeconomic status factor, factor scores for built environment characteristics (high density, older neighborhood, and short commutes), and other variables for each buffer configuration. The adolescent accelerometer dataset offers summary variables of accelerometer data and minute-level estimates of light, moderate, and vigorous activity using Crouter, Chandler, and GGIR processing methods. Additionally, training webinar, questionnaires, survey data files and codebooks are available. Conclusions The FLASHE study data resources can be used to understand cancer-related health behaviors in family dyads. Funding Sources FLASHE study was funded by the National Cancer Institute under contract number HHSN2612012000391 issued to Westat, Inc.

scholarly journals Standardising the measurement of physical activity in people receiving haemodialysis: considerations for research and practice

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Hannah M. L. Young ◽  
Mark W. Orme ◽  
Yan Song ◽  
Maurice Dungey ◽  
James O. Burton ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sample Size ◽  
Repeated Measures ◽  
A Priori ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Future Research ◽  
Wear Time ◽  
Minimum Number ◽  
The Uk

Abstract Background Physical activity (PA) is exceptionally low amongst the haemodialysis (HD) population, and physical inactivity is a powerful predictor of mortality, making it a prime focus for intervention. Objective measurement of PA using accelerometers is increasing, but standard reporting guidelines essential to effectively evaluate, compare and synthesise the effects of PA interventions are lacking. This study aims to (i) determine the measurement and processing guidance required to ensure representative PA data amongst a diverse HD population, and; (ii) to assess adherence to PA monitor wear amongst HD patients. Methods Clinically stable HD patients from the UK and China wore a SenseWear Armband accelerometer for 7 days. Step count between days (HD, Weekday, Weekend) were compared using repeated measures ANCOVA. Intraclass correlation coefficients (ICCs) determined reliability (≥0.80 acceptable). Spearman-Brown prophecy formula, in conjunction with a priori ≥  80% sample size retention, identified the minimum number of days required for representative PA data. Results Seventy-seven patients (64% men, mean ± SD age 56 ± 14 years, median (interquartile range) time on HD 40 (19–72) months, 40% Chinese, 60% British) participated. Participants took fewer steps on HD days compared with non-HD weekdays and weekend days (3402 [95% CI 2665–4140], 4914 [95% CI 3940–5887], 4633 [95% CI 3558–5707] steps/day, respectively, p < 0.001). PA on HD days were less variable than non-HD days, (ICC 0.723–0.839 versus 0.559–0.611) with ≥ 1 HD day and ≥  3 non-HD days required to provide representative data. Using these criteria, the most stringent wear-time retaining ≥ 80% of the sample was ≥7 h. Conclusions At group level, a wear-time of ≥7 h on ≥1HD day and ≥ 3 non-HD days is required to provide reliable PA data whilst retaining an acceptable sample size. PA is low across both HD and non- HD days and future research should focus on interventions designed to increase physical activity in both the intra and interdialytic period.

scholarly journals Sedentary Behavior and Quality of Life in Individuals With Parkinson’s Disease

2019 ◽  
Vol 33 (8) ◽  
pp. 595-601 ◽  
Author(s):  
Laura D. Ellingson ◽  
Andrew Zaman ◽  
Elizabeth L. Stegemöller
Keyword(s):  
Quality Of Life ◽  
Physical Activity ◽  
Sedentary Behavior ◽  
Cognitive Processing ◽  
Sedentary Time ◽  
Health Concern ◽  
Sedentary Behaviors ◽  
Secondary Purpose ◽  
Sedentary Activities

Background. Sedentary behavior is a growing public health concern and may have particular relevance for the Parkinson disease (PD) population. However, the influence of sedentary time on factors associated with quality of life (QOL) in PD is unknown. The primary purpose of this study was to examine relationships between sedentary behaviors and markers of PD-specific QOL. A secondary purpose was to examine relationships between physical activity behaviors and QOL. Methods. We assessed sedentary and active behaviors using objective and interview measures and examined relationships between these behaviors and a measure of PD-specific QOL in individuals with PD. Results. Results demonstrated that sedentary time was significantly related to several aspects of QOL, including perceived deficits in the domains of mobility, cognitive processing, and communication. Additionally, results showed that time spent watching television was more strongly associated with lower levels of QOL than other more engaging sedentary activities. For physical activity, relationships between objective measures and QOL were weaker and only significantly associated with mobility. Time spent doing housework was associated with lower levels of QOL, whereas time spent in recreational activity was associated with lower levels of discomfort. Discussion. These results suggest that targeting decreases in sedentary behaviors (eg, reducing time spent watching television, breaking up prolonged bouts of sedentary time) may be effective for improving QOL in individuals with PD.

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