scholarly journals Robust Compositional Analysis of Physical Activity and Sedentary Behaviour Data

2018 ◽  
Vol 15 (10) ◽  
pp. 2248 ◽  
Author(s):  
Nikola Štefelová ◽  
Jan Dygrýn ◽  
Karel Hron ◽  
Aleš Gába ◽  
Lukáš Rubín ◽  
...  
Keyword(s):  
Physical Activity ◽  
Light Intensity ◽  
Robust Statistics ◽  
Compositional Data ◽  
Compositional Analysis ◽  
Public Health Research ◽  
Movement Behavior ◽  
Moderate Intensity ◽  
Compositional Data Analysis ◽  
Aberrant Observations

Although there is an increasing awareness of the suitability of using compositional data methodology in public health research, classical methods of statistical analysis have been primarily used so far. The present study aims to illustrate the potential of robust statistics to model movement behaviour using Czech adolescent data. We investigated: (1) the inter-relationship between various physical activity (PA) intensities, extended to model relationships by age; and (2) the associations between adolescents’ PA and sedentary behavior (SB) structure and obesity. These research questions were addressed using three different types of compositional regression analysis—compositional covariates, compositional response, and regression between compositional parts. Robust counterparts of classical regression methods were used to lessen the influence of possible outliers. We outlined the differences in both classical and robust methods of compositional data analysis. There was a pattern in Czech adolescents’ movement/non-movement behavior—extensive SB was related to higher amounts of light-intensity PA, and vigorous PA ratios formed the main source of potential aberrant observations; aging is associated with more SB and vigorous PA at the expense of light-intensity PA and moderate-intensity PA. The robust counterparts indicated that they might provide more stable estimates in the presence of outlying observations. The findings suggested that replacing time spent in SB with vigorous PA may be a powerful tool against adolescents’ obesity.

scholarly journals Effects of Two Randomized and Controlled Multi-Component Interventions Focusing On 24-Hour Movement Behavior among Office Workers: A Compositional Data Analysis

2021 ◽  
Vol 18 (8) ◽  
pp. 4191
Author(s):  
Lisa-Marie Larisch ◽  
Emil Bojsen-Møller ◽  
Carla F. J. Nooijen ◽  
Victoria Blom ◽  
Maria Ekblom ◽  
...  
Keyword(s):  
Physical Activity ◽  
Data Analysis ◽  
Cardiorespiratory Fitness ◽  
Leisure Time ◽  
Compositional Data ◽  
Office Workers ◽  
Movement Behavior ◽  
Compositional Data Analysis ◽  
Intervention Effects ◽  
Time In Bed

Intervention studies aiming at changing movement behavior have usually not accounted for the compositional nature of time-use data. Compositional data analysis (CoDA) has been suggested as a useful strategy for analyzing such data. The aim of this study was to examine the effects of two multi-component interventions on 24-h movement behavior (using CoDA) and on cardiorespiratory fitness among office workers; one focusing on reducing sedentariness and the other on increasing physical activity. Office workers (n = 263) were cluster randomized into one of two 6-month intervention groups, or a control group. Time spent in sedentary behavior, light-intensity, moderate and vigorous physical activity, and time in bed were assessed using accelerometers and diaries, both for 24 h in total, and for work and leisure time separately. Cardiorespiratory fitness was estimated using a sub-maximal cycle ergometer test. Intervention effects were analyzed using linear mixed models. No intervention effects were found, either for 24-h behaviors in total, or for work and leisure time behaviors separately. Cardiorespiratory fitness did not change significantly. Despite a thorough analysis of 24-h behaviors using CoDA, no intervention effects were found, neither for behaviors in total, nor for work and leisure time behaviors separately. Cardiorespiratory fitness did not change significantly. Although the design of the multi-component interventions was based on theoretical frameworks, and included cognitive behavioral therapy counselling, which has been proven effective in other populations, issues related to implementation of and compliance with some intervention components may have led to the observed lack of intervention effect.

Reallocating Time From Sedentary Behavior to Physical Activity in Patients With Peripheral Artery Disease: Analyzing the Effects on Walking Capacity Using Compositional Data Analysis

2021 ◽  
Vol 18 (4) ◽  
pp. 426-432
Author(s):  
Antonio Henrique Germano-Soares ◽  
Rafael M. Tassitano ◽  
Breno Quintela Farah ◽  
Aluísio Andrade-Lima ◽  
Marília de Almeida Correia ◽  
...  
Keyword(s):  
Physical Activity ◽  
Data Analysis ◽  
Light Intensity ◽  
Confidence Interval ◽  
Sedentary Behavior ◽  
Compositional Data ◽  
Compositional Data Analysis ◽  
Peripheral Artery ◽  
Walking Capacity ◽  
Artery Disease

Background: To examine the associations between physical activity (PA) and sedentary behavior (SB) with walking capacity and the effects of reallocating time from SB to PA in patients with symptomatic peripheral artery disease (PAD) using compositional data analysis. Methods: This cross-sectional study included 178 patients (34% females, mean age = 66 [9] y, body mass index = 27.8 [5.0] kg/m2, and ankle-brachial index = 0.60 [0.18]). Walking capacity was assessed as the total walking distance (TWD) achieved in a 6-minute walk test, while SB, light-intensity PA, and moderate to vigorous-intensity PA (MVPA) were measured by a triaxial accelerometer and conceptualized as a time-use composition. Associations between time reallocation among wake-time behaviors and TWD were determined using compositional isotemporal substitution models. Results: A positive association of MVPA with TWD (relative to remaining behaviors) was found in men (βilr = 66.9, SE = 21.4, P = .003) and women (βilr = 56.5, SE = 19.8; P = .005). Reallocating 30 minutes per week from SB to MVPA was associated with higher TWD in men (6.7 m; 95% confidence interval, 2.6–10.9 m) and women (4.5 m; 95% confidence interval, 1.5–7.5 m). Conclusions: The findings highlight, using a compositional approach, the beneficial and independent association of MVPA with walking capacity in patients with symptomatic PAD, whereas SB and light-intensity PA were not associated.

Excellent Self-Rated Health Associated With Activities of Higher Intensities: A Compositional Data Analysis Approach

2019 ◽  
Vol 16 (11) ◽  
pp. 1007-1013 ◽  
Author(s):  
Philip von Rosen ◽  
Maria Hagströmer
Keyword(s):  
Physical Activity ◽  
Data Analysis ◽  
Light Intensity ◽  
Chronic Diseases ◽  
Compositional Data ◽  
Vigorous Physical Activity ◽  
Compositional Data Analysis ◽  
Activity Data ◽  
Self Rated Health ◽  
Intensity Physical Activity

Background: This study investigates the association between self-rated health and the time spent in sedentary behavior (SB), low light-intensity physical activity (LLPA), high light-intensity physical activity (HLPA), and moderate to vigorous physical activity (MVPA), by controlling for demographics, socioeconomic status, and chronic diseases. Methods: A total of 1665 participants (55% women) completed a questionnaire about demographics, chronic diseases, and anthropometric characteristics and provided objective physical activity data on time in SB, LLPA, HLPA, and MVPA, using an ActiGraph 7164 accelerometer. Association between self-rated health and activity data was explored in a compositional data analysis. Results: The multinomial logistic regression analysis showed a significantly lower time spent in MVPA in proportion to time in other movement behaviors (SB, LLPA, and HLPA) for participants who rated their health as alright or poor compared with excellent (P < .001). Participants with poor, compared with excellent health, spent about a third of the time in MVPA (17 vs 50 min), marginally higher time in HLPA (134 vs 125 min), more time in LLPA (324 vs 300 min), and similar time in SB (383 vs 383 min), accounting for confounders and time in other movement behaviors. Conclusions: Promoting MVPA, as opposed to time in other movement behaviors, is suggested to be beneficial for excellent self-rated health.

scholarly journals Associations between sedentary time, physical activity and bone health among older people using compositional data analysis

PLoS ONE ◽  
2018 ◽  
Vol 13 (10) ◽  
pp. e0206013 ◽  
Author(s):  
Irene Rodríguez-Gómez ◽  
Asier Mañas ◽  
José Losa-Reyna ◽  
Leocadio Rodríguez-Mañas ◽  
Sebastien F. M. Chastin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Data Analysis ◽  
Older People ◽  
Bone Health ◽  
Sedentary Time ◽  
Compositional Data ◽  
Compositional Data Analysis

scholarly journals Associations of movement behaviors and body mass index: comparison between a report-based and monitor-based method using Compositional Data Analysis

2020 ◽  
Vol 45 (1) ◽  
pp. 266-275 ◽  
Author(s):  
Youngwon Kim ◽  
Ryan D. Burns ◽  
Duck-chul Lee ◽  
Gregory J. Welk
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Data Analysis ◽  
Body Mass ◽  
Compositional Data ◽  
Activity Measurement ◽  
Compositional Data Analysis ◽  
Lifestyle Behaviors ◽  
Linear Regression Models ◽  
Index Comparison

Abstract Background/objectives Evidence on the associations between lifestyle movement behaviors and obesity has been established without taking into account the time-constrained nature of categorized, time-based lifestyle behaviors. We examined the associations of sleep, sedentary behavior (SED), light-intensity physical activity (LPA), and moderate-to-vigorous PA (MVPA) with body mass index (BMI) using Compositional Data Analysis (CoDA), and compared the associations between a report-based method (24-h Physical Activity Recall; 24PAR) and a monitor-based method (SenseWear Armband; SWA). Subjects/methods Replicate data from a representative sample of 1247 adults from the Physical Activity Measurement Survey (PAMS) were used in the study. Participants completed activity monitoring on two randomly selected days, each of which required wearing a SWA for a full day, and then completing a telephone-administered 24PAR the following day. Relationships among behavioral compositional parts and BMI were analyzed using CoDA via multiple linear regression models with both 24PAR and SWA data. Results Using 24PAR, time spent in sleep (γ = −3.58, p = 0.011), SED (γ = 3.70, p = 0.002), and MVPA (γ = −0.53, p = 0.018) was associated with BMI. Using SWA, time spent in sleep (γ = −5.10, p < 0.001), SED (γ = 8.93, p < 0.001), LPA (γ = −3.12, p < 0.001), and MVPA (γ = −1.43, p < 0.001) was associated with BMI. The SWA models explained more variance in BMI (R2 = 0.28) compared with the 24PAR models (R2 = 0.07). The compositional isotemporal substitution models revealed reductions in BMI when replacing SED by MVPA, LPA (not with 24PAR) or sleep for both 24PAR and SWA, but the effect estimates were larger with SWA. Conclusions Favorable levels of relative time spent in lifestyle movement behaviors were, in general, associated with decreased BMI. The observed associations were stronger using the monitor-based SWA method compared with the report-based 24PAR method.

scholarly journals Associations of Physical Behaviours and Behavioural Reallocations with Markers of Metabolic Health: A Compositional Data Analysis

2018 ◽  
Vol 15 (10) ◽  
pp. 2280 ◽  
Author(s):  
Gregory Biddle ◽  
Charlotte Edwardson ◽  
Joseph Henson ◽  
Melanie Davies ◽  
Kamlesh Khunti ◽  
...  
Keyword(s):  
Insulin Sensitivity ◽  
Compositional Data ◽  
Compositional Analysis ◽  
Statistical Modelling ◽  
Metabolic Health ◽  
Sitting Time ◽  
Compositional Data Analysis ◽  
Sensitivity Index ◽  
Model Assessment ◽  
Physical Behaviour

Standard statistical modelling has shown that the reallocation of sitting time to either standing or stepping may be beneficial for metabolic health. However, this overlooks the inherent dependency of time spent in all behaviours. The aim is to examine the associations between physical behaviours and markers of metabolic health (fasting glucose, fasting insulin, 2-h glucose, 2-h insulin, Homeostasis Model Assessment of Insulin Sensitivity (HOMA-IS), Matsuda Insulin Sensitivity Index (Matsuda-ISI) while quantifying the associations of reallocating time from one physical behaviour to another using compositional analysis. Objectively measured physical behaviour data were analysed (n = 435) using compositional analysis and compositional isotemporal substitutions to estimate the association of reallocating time from one behaviour to another in a population at high risk of type 2 diabetes mellitus (T2DM). Stepping time was associated with all markers of metabolic health relative to all other behaviours. Reallocating 30 min from sleep, sitting, or standing to stepping was associated with 5–6 fold lower 2-h glucose, 15–17 fold lower 2-h insulin, and higher insulin sensitivity (10–11 fold via HOMA-IS, 12–15 fold via Matsuda-ISI). Associations of reallocating time from any behaviour to stepping were maintained for 2-h glucose, 2-h insulin, and Matsuda-ISI after further adjusting for body mass index (BMI). Relocating time from stepping into sleep, sitting, or standing was associated with lower insulin sensitivity. Stepping time may be the most important behavioural composition when promoting improved metabolic health in adults at risk of T2DM.

scholarly journals Accelerometer and GPS Analysis of Trail Use and Associations With Physical Activity

2018 ◽  
Vol 15 (7) ◽  
pp. 523-530 ◽  
Author(s):  
Kosuke Tamura ◽  
Jeffrey S. Wilson ◽  
Robin C. Puett ◽  
David B. Klenosky ◽  
William A. Harper ◽  
...  
Keyword(s):  
Physical Activity ◽  
Light Intensity ◽  
Global Positioning System ◽  
Moderate Intensity ◽  
Gps Data ◽  
Accelerometer Data ◽  
Trail Use ◽  
Concurrent Use ◽  
Global Positioning ◽  
Vigorous Intensity

Background: Concurrent use of accelerometers and global positioning system (GPS) data can be used to quantify physical activity (PA) occurring on trails. This study examined associations of trail use with PA and sedentary behavior (SB) and quantified on trail PA using a combination of accelerometer and GPS data. Methods: Adults (N = 142) wore accelerometer and GPS units for 1–4 days. Trail use was defined as a minimum of 2 consecutive minutes occurring on a trail, based on GPS data. We examined associations between trail use and PA and SB. On trail minutes of light-intensity, moderate-intensity, and vigorous-intensity PA, and SB were quantified in 2 ways, using accelerometer counts only and with a combination of GPS speed and accelerometer data. Results: Trail use was positively associated with total PA, moderate-intensity PA, and light-intensity PA (P < .05). On trail vigorous-intensity PA minutes were 346% higher when classified with the combination versus accelerometer only. Light-intensity PA, moderate-intensity PA, and SB minutes were 15%, 91%, and 85% lower with the combination, respectively. Conclusions: Adult trail users accumulated more PA on trail use days than on nontrail use days, indicating the importance of these facilities for supporting regular PA. The combination of GPS and accelerometer data for quantifying on trail activity may be more accurate than accelerometer data alone and is useful for classifying intensity of activities such as bicycling.

scholarly journals Children’s Cortisol and Cell-Free DNA Trajectories in Relation to Sedentary Behavior and Physical Activity in School: A Longitudinal Analysis

2018 ◽  
Author(s):  
Christoph Becker ◽  
Sebastian Schmidt ◽  
Elmo Neuberger ◽  
Peter Kirsch ◽  
Perikles Simon ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Linear Models ◽  
Compositional Data ◽  
Intervention Group ◽  
Control Group ◽  
Compositional Data Analysis ◽  
Sampled Data ◽  
Bayesian Hierarchical ◽  
Biological Stress

Education outside the classroom (EOtC) can be beneficial for students. The relationship between biological stress markers and sedentary behavior (SB) plus physical activity (PA) is insufficiently evaluated in school settings. This exploratory study aims to evaluate the association between students&rsquo; cortisol, plus circulating cell-free deoxyribonucleic acid (cfDNA) levels, and their SB, light PA (LPA) and moderate-to-vigorous PA (MVPA) during outdoor and indoor classes in different seasons. We assessed data from an education outside the classroom (EOtC) program (n = 48; intervention group [IG], n = 37; control group [CG], n = 11). We sampled data on 3 school-days in three seasons (fall, spring, and summer) in normal teaching indoors (CG) and outdoor lessons (IG) in the forest. SB and PA were evaluated by accelerometry, and cortisol and cfDNA levels by saliva samples. The compositional data analysis approach analyzed SB and PA. Fitted Bayesian hierarchical linear models evaluated the association between cortisol and cfDNA, and SB/LPA/MVPA. A steady decline of cortisol in the outdoor setting is associated with relatively high levels of LPA. SB and MVPA tended to exhibit a similar effect in the indoor setting. CfDNA is positively associated with a relatively high amount of SB in the IG, the same association is likely for LPA and MVPA in both groups. LPA seems to support a healthy cortisol decrease in children during outdoor lessons. The relevance of SB/PA as a composition in relation to students stress response in school should be emphasized. This study facilitates the formulation of straightforward and directed hypotheses for further research.

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