scholarly journals Changes in sedentary behavior patterns during the transition from childhood to adolescence and their association with adiposity: a prospective study based on compositional data analysis

2022 ◽  
Vol 80 (1) ◽  
Author(s):  
Lukáš Rubín ◽  
Aleš Gába ◽  
Jana Pelclová ◽  
Nikola Štefelová ◽  
Lukáš Jakubec ◽  
...  
Keyword(s):  
Data Analysis ◽  
Sedentary Behavior ◽  
Fat Mass ◽  
Compositional Data ◽  
Longitudinal Design ◽  
Pediatric Population ◽  
Compositional Data Analysis ◽  
Compositional Approach ◽  
Sedentary Bouts

Abstract Background To date, no longitudinal study using a compositional approach has examined sedentary behavior (SB) patterns in relation to adiposity in the pediatric population. Therefore, our aims were to (1) investigate the changes in SB patterns and adiposity from childhood to adolescence, (2) analyze the prospective compositional associations between changes in SB patterns and adiposity, and (3) estimate the changes in adiposity associated with substituting SB with physical activity (PA) of different intensities. Methods The study presents a longitudinal design with a 5-year follow-up. A total of 88 participants (61% girls) were included in the analysis. PA and SB were monitored for seven consecutive days using a hip-worn accelerometer. Adiposity markers (fat mass percentage [FM%], fat mass index [FMI], and visceral adiposity tissue [VAT]) were assessed using the multi-frequency bioimpedance analysis. The prospective associations were examined using compositional data analysis. Results Over the follow-up period, the proportion of time spent in total SB increased by 154.8 min/day (p < 0.001). The increase in total SB was caused mainly by an increase in middle and long sedentary bouts, as these SB periods increased by 79.8 min/day and 62.0 min/day (p < 0.001 for both), respectively. FM%, FMI, and VAT increased by 2.4% points, 1.0 kg/m2, and 31.5 cm2 (p < 0.001 for all), respectively. Relative to the remaining movement behaviors, the increase in time spent in middle sedentary bouts was significantly associated with higher FM% (βilr1 = 0.27, 95% confidence interval [CI]: 0.02 to 0.53) at follow-up. Lower VAT by 3.3% (95% CI: 0.8 to 5.7), 3.8% (95% CI: 0.03 to 7.4), 3.9% (95% CI: 0.8 to 6.9), and 3.8% (95% CI: 0.7 to 6.9) was associated with substituting 15 min/week spent in total SB and in short, middle, and long sedentary bouts, respectively, with an equivalent amount of time spent in vigorous PA. Conclusions This study showed unfavorable changes in SB patterns and adiposity status in the transition from childhood to adolescence. Incorporating high-intensity PA at the expense of SB appears to be an appropriate approach to reduce the risk of excess adiposity in the pediatric population.

scholarly journals Changes in Sedentary Behavior Patterns During the Transition from Childhood to Adolescence and Their Association with Adiposity: A Prospective Study Based on Compositional Data Analysis

2021 ◽  
Author(s):  
Lukáš Rubín ◽  
Aleš Gába ◽  
Jana Pelclová ◽  
Nikola Štefelová ◽  
Lukáš Jakubec ◽  
...  
Keyword(s):  
Data Analysis ◽  
Sedentary Behavior ◽  
Fat Mass ◽  
Compositional Data ◽  
Longitudinal Design ◽  
Pediatric Population ◽  
Compositional Data Analysis ◽  
Compositional Approach ◽  
Sedentary Bouts

Abstract Background: To date, no longitudinal study using a compositional approach has examined sedentary behavior (SB) patterns in relation to adiposity in the pediatric population. Therefore, our aims were to (1) investigate the changes in SB patterns and adiposity from childhood to adolescence, (2) analyze the prospective compositional associations between changes in SB patterns and adiposity, and (3) estimate the changes in adiposity associated with substituting SB with physical activity (PA) of different intensities.Methods: The study presents a longitudinal design with a 5-year follow-up. A total of 88 participants (61% girls) were included in the analysis. PA and SB were monitored for seven consecutive days using a hip-worn accelerometer. Adiposity markers (fat mass percentage [FM%], fat mass index [FMI], and visceral adiposity tissue [VAT]) were assessed using the multi-frequency bioimpedance analysis. The prospective associations were examined using compositional data analysis. Results: Over the follow-up period, the proportion of time spent in total SB increased by 154.8 min/day (p < 0.001). The increase in total SB was caused mainly by an increase in middle and long sedentary bouts, as these SB periods increased by 79.8 min/day and 62 min/day (p < 0.001 for both), respectively. FM%, FMI, and VAT increased by 2.4 percent points, 1.0 kg/m2, and 31.5 cm2 (p < 0.001 for all), respectively. Relative to the remaining movement behaviors, the increase in time spent in middle sedentary bouts was significantly associated with higher FM% (βilr1 = 0.27, 95% confidence interval [CI]: 0.02 to 0.53) at follow-up. Lower VAT by 3.3% (95% CI: 0.8 to 5.7), 3.8% (95% CI: 0.03 to 7.4), 3.9% (95% CI: 0.8 to 6.9), and 3.8% (95% CI: 0.7 to 6.9) was associated with substituting 15 min/week spent in total SB and in short, middle, and long sedentary bouts, respectively, with an equivalent amount of time spent in vigorous PA.Conclusions: This study showed unfavorable changes in SB patterns and adiposity status in the transition from childhood to adolescence. Incorporating high-intensity PA at the expense of SB appears to be an appropriate approach to reduce the risk of excess adiposity in the pediatric population.

scholarly journals Changes in Sedentary Behavior Patterns During the Transition From Childhood to Adolescence and Their Association With Adiposity: a Prospective Study Based on Compositional Data Analysis

2021 ◽  
Author(s):  
Lukáš Rubín ◽  
Aleš Gába ◽  
Jana Pelclová ◽  
Nikola Štefelová ◽  
Lukáš Jakubec ◽  
...  
Keyword(s):  
Data Analysis ◽  
Sedentary Behavior ◽  
Fat Mass ◽  
Compositional Data ◽  
Longitudinal Design ◽  
Pediatric Population ◽  
Compositional Data Analysis ◽  
Compositional Approach ◽  
Sedentary Bouts

Abstract Background: To date, no longitudinal study using a compositional approach has examined sedentary behavior (SB) patterns in relation to adiposity in the pediatric population. Therefore, our aims were to (1) investigate the changes in SB patterns and adiposity from childhood to adolescence, (2) analyze the prospective compositional associations between changes in SB patterns and adiposity, and (3) estimate the changes in adiposity associated with substituting SB with physical activity (PA) of different intensities.Methods: The study presents a longitudinal design with a 5-year follow-up. A total of 88 participants (61% girls) were included in the analysis. PA and SB were monitored for seven consecutive days using a hip-worn accelerometer. Adiposity markers (fat mass percentage [FM%], fat mass index [FMI], and visceral adiposity tissue [VAT]) were assessed using the multi-frequency bioimpedance analysis. The prospective associations were examined using compositional data analysis.Results: Over the follow-up period, the proportion of time spent in total SB increased by 154.8 min/day (p < 0.001). The increase in total SB was caused mainly by an increase in middle and long sedentary bouts, as these SB periods increased by 79.8 min/day and 62 min/day (p < 0.001 for both), respectively. FM%, FMI, and VAT increased by 2.4 percent points, 1.0 kg/m2, and 31.5 cm2 (p < 0.001 for all), respectively. Relative to the remaining movement behaviors, the increase in time spent in middle sedentary bouts was significantly associated with higher FM% (βilr1 = 0.27, 95% confidence interval [CI]: 0.02 to 0.53) at follow-up. Lower VAT by 3.3% (95% CI: 0.8 to 5.7), 3.8% (95% CI: 0.03 to 7.4), 3.9% (95% CI: 0.8 to 6.9), and 3.8% (95% CI: 0.7 to 6.9) was associated with substituting 15 min/week spent in total SB and in short, middle, and long sedentary bouts, respectively, with an equivalent amount of time spent in vigorous PA.Conclusions: This study showed unfavorable changes in SB patterns and adiposity status in the transition from childhood to adolescence. Incorporating high-intensity PA at the expense of SB appears to be an appropriate approach to reduce the risk of excess adiposity in the pediatric population.

scholarly journals O5A.6 Objectively assessed arm elevation and the course of neck and shoulder pain during a 2-year follow-up: a compositional approach

2019 ◽  
Vol 76 (Suppl 1) ◽  
pp. A42.3-A43
Author(s):  
Suzanne Merkus ◽  
Lars-Kristian Lunde ◽  
Markus Koch ◽  
Stein Knardahl ◽  
Kaj Bo Veiersted
Keyword(s):  
Data Analysis ◽  
Shoulder Pain ◽  
Compositional Data ◽  
Healthcare Personnel ◽  
Compositional Data Analysis ◽  
Compositional Approach ◽  
Neck And Shoulder Pain ◽  
Statistical Analysis Method ◽  
Arm Elevation

PurposeTo use a compositional data analysis approach and objective exposure assessments to study the association between the duration of arm elevation and the course of neck and shoulder pain (NSP) during a 2-year follow-up in physically demanding occupations.MethodsConstruction (n=59) and healthcare (n=59) employees wore accelerometers on the dominant upper-arm during a full working day at baseline. Objective assessments using accelerometers addresses biases found in previous studies that estimate duration of arm elevation with self-reports. At baseline and every 6 months for two years, participants reported on NSP (scale 0–3). Duration of arm elevation within predefined ranges (<30°; 30–60°; ≥60) formed the parts of the composition. Compositional data analysis is a new statistical analysis method within occupational health and it is the correct way of analysing data with a compositional nature. The associations between the relative importance of the duration within the levels of arm elevation and the course of NSP during the 2-year follow-up were estimated with compositional linear mixed models, adjusted for confounders.ResultsIn non-adjusted analyses, only duration arm elevation <30° was associated with NSP at baseline (β = 0.37; p=0.015). Duration arm elevation <30° had a tendency to be associated with an improvement in NSP over the 2-year follow-up (<30°*time (β=-0.07; p=0.089)). Neither duration 30–60° nor ≥60 were associated with the course of NSP during follow-up. After adjusting for confounders, none of the durations of arm elevation were associated with the course of NSP over the 2-year period (<30° and NSP (β = 0.20; p=0.126); <30°*time (β=-0.06; p=0.097)).ConclusionAmong construction and healthcare personnel, duration of working in awkward arm elevation postures was not associated with the course of NSP over a 2-year period. Arm elevation alone, without considering force exertion, may not be sufficient to influence the course of NSP.

scholarly journals Sedentary behavior patterns and adiposity in children: a study based on compositional data analysis

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Aleš Gába ◽  
Željko Pedišić ◽  
Nikola Štefelová ◽  
Jan Dygrýn ◽  
Karel Hron ◽  
...  
Keyword(s):  
Data Analysis ◽  
Sedentary Behavior ◽  
Compositional Data ◽  
Behavior Patterns ◽  
Compositional Data Analysis

scholarly journals Analysis of relative abundances with zeros on environmental gradients: a multinomial regression model

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5643 ◽  
Author(s):  
Fiona Chong ◽  
Matthew Spencer
Keyword(s):  
Data Analysis ◽  
Regression Model ◽  
Compositional Data ◽  
Environmental Gradients ◽  
Compositional Data Analysis ◽  
Multinomial Regression ◽  
Point Count ◽  
Compositional Approach ◽  
Multinomial Regression Model ◽  
Relative Abundances

Ecologists often analyze relative abundances, which are an example of compositional data. However, they have made surprisingly little use of recent advances in the field of compositional data analysis. Compositions form a vector space in which addition and scalar multiplication are replaced by operations known as perturbation and powering. This algebraic structure makes it easy to understand how relative abundances change along environmental gradients. We illustrate this with an analysis of changes in hard-substrate marine communities along a depth gradient. We fit a quadratic multivariate regression model with multinomial observations to point count data obtained from video transects. As well as being an appropriate observation model in this case, the multinomial deals with the problem of zeros, which often makes compositional data analysis difficult. We show how the algebra of compositions can be used to understand patterns in dissimilarity. We use the calculus of simplex-valued functions to estimate rates of change, and to summarize the structure of the community over a vertical slice. We discuss the benefits of the compositional approach in the interpretation and visualization of relative abundance data.

scholarly journals Calibration of Self-Reported Time Spent Sitting, Standing and Walking among Office Workers: A Compositional Data Analysis

2019 ◽  
Vol 16 (17) ◽  
pp. 3111 ◽  
Author(s):  
David M. Hallman ◽  
Svend Erik Mathiassen ◽  
Allard J. van der Beek ◽  
Jennie A. Jackson ◽  
Pieter Coenen
Keyword(s):  
Data Analysis ◽  
Compositional Data ◽  
Self Report ◽  
Office Workers ◽  
Compositional Data Analysis ◽  
Calibration Models ◽  
Self Reports ◽  
Objectively Measured ◽  
Rms Errors

We developed and evaluated calibration models predicting objectively measured sitting, standing and walking time from self-reported data using a compositional data analysis (CoDA) approach. A total of 98 office workers (48 women) at the Swedish Transport Administration participated. At baseline and three-months follow-up, time spent sitting, standing and walking at work was assessed for five working days using a thigh-worn accelerometer (Actigraph), as well as by self-report (IPAQ). Individual compositions of time spent in the three behaviors were expressed by isometric log-ratios (ILR). Calibration models predicting objectively measured ILRs from self-reported ILRs were constructed using baseline data, and then validated using follow-up data. Un-calibrated self-reports were inaccurate; root-mean-square (RMS) errors of ILRs for sitting, standing and walking were 1.21, 1.24 and 1.03, respectively. Calibration reduced these errors to 36% (sitting), 40% (standing), and 24% (walking) of those prior to calibration. Calibration models remained effective for follow-up data, reducing RMS errors to 33% (sitting), 51% (standing), and 31% (walking). Thus, compositional calibration models were effective in reducing errors in self-reported physical behaviors during office work. Calibration of self-reports may present a cost-effective method for obtaining physical behavior data with satisfying accuracy in large-scale cohort and intervention studies.

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.

scholarly journals Compositional Data Analysis in Time-Use Epidemiology: What, Why, How

2020 ◽  
Vol 17 (7) ◽  
pp. 2220 ◽  
Author(s):  
Dorothea Dumuid ◽  
Željko Pedišić ◽  
Javier Palarea-Albaladejo ◽  
Josep Antoni Martín-Fernández ◽  
Karel Hron ◽  
...  
Keyword(s):  
Physical Activity ◽  
Data Analysis ◽  
Sedentary Behavior ◽  
Time Use ◽  
Compositional Data ◽  
Compositional Data Analysis ◽  
Health It ◽  
Future Directions ◽  
The Relationship ◽  
Daily Time

In recent years, the focus of activity behavior research has shifted away from univariate paradigms (e.g., physical activity, sedentary behavior and sleep) to a 24-h time-use paradigm that integrates all daily activity behaviors. Behaviors are analyzed relative to each other, rather than as individual entities. Compositional data analysis (CoDA) is increasingly used for the analysis of time-use data because it is intended for data that convey relative information. While CoDA has brought new understanding of how time use is associated with health, it has also raised challenges in how this methodology is applied, and how the findings are interpreted. In this paper we provide a brief overview of CoDA for time-use data, summarize current CoDA research in time-use epidemiology and discuss challenges and future directions. We use 24-h time-use diary data from Wave 6 of the Longitudinal Study of Australian Children (birth cohort, n = 3228, aged 10.9 ± 0.3 years) to demonstrate descriptive analyses of time-use compositions and how to explore the relationship between daily time use (sleep, sedentary behavior and physical activity) and a health outcome (in this example, adiposity). We illustrate how to comprehensively interpret the CoDA findings in a meaningful way.

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