scholarly journals A compositional analysis of time spent in sleep, sedentary behaviour and physical activity with all-cause mortality risk

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Anna E. Clarke ◽  
Ian Janssen
Keyword(s):  
Physical Activity ◽  
Data Analysis ◽  
Sedentary Behaviour ◽  
Mortality Risk ◽  
Compositional Data ◽  
Compositional Data Analysis ◽  
Movement Behaviour ◽  
All Cause Mortality ◽  
Intensity Physical Activity ◽  
Daily Time

Abstract Background Daily time spent in sleep, sedentary behaviour (SED), light intensity physical activity (LIPA), and moderate-to-vigorous intensity physical activity (MVPA) are compositional, co-dependent variables. The objectives of this study were to use compositional data analysis to: (1) examine the relationship between the movement behaviour composition (daily time spent in sleep, SED, LIPA and MVPA) and all-cause mortality risk, and (2) estimate the extent to which changing time spent in any given movement behaviour (sleep, SED, LIPA, or MVPA) within the movement behaviour composition was associated with changes in risk of all-cause mortality. Methods 2838 adult participants from the 2005–2006 cycle of the U.S. National Health and Nutrition Examination Survey were studied using a prospective cohort design. Daily time spent in SED, LIPA and MVPA were determined by accelerometer. Nightly time spent sleeping was self-reported. Survey data were linked with mortality data through to the end of December 2015. Compositional data analysis was used to investigate relationships between the movement behaviour composition and mortality. Results The movement behaviour composition was significantly associated with mortality risk. Time spent in MVPA relative to other movement behaviours was negatively associated with mortality risk (HR = .74; 95% CI [.67, .83]) while relative time spent in SED was positively associated with mortality risk (HR = 1.75; 95% CI [1.10, 2.79]). Time displacement estimates revealed that the greatest estimated changes in mortality risk occurred when time spent in MVPA was decreased and replaced with sleep, SED, LIPA or a combination of these behaviours (HRs of 1.76 to 1.80 for 15 min/day displacements). Conclusions The daily movement behaviour composition was related to mortality. Replacing time in MVPA or SED with equivalent time from any other movement behaviour was associated with an increase and decrease in mortality risk, respectively.

scholarly journals A systematic review of compositional data analysis studies examining associations between sleep, sedentary behaviour, and physical activity with health outcomes in adults

2020 ◽  
Vol 45 (10 (Suppl. 2)) ◽  
pp. S248-S257 ◽  
Author(s):  
Ian Janssen ◽  
Anna E. Clarke ◽  
Valerie Carson ◽  
Jean-Philippe Chaput ◽  
Lora M. Giangregorio ◽  
...  
Keyword(s):  
Physical Activity ◽  
Systematic Review ◽  
Data Analysis ◽  
Health Outcomes ◽  
Sedentary Behaviour ◽  
Compositional Data ◽  
Compositional Data Analysis ◽  
Movement Behaviour ◽  
Time Out ◽  
All Cause Mortality

This systematic review determined if the composition of time spent in movement behaviours (i.e., sleep, sedentary behaviour (SED), light physical activity, and moderate-to-vigorous physical activity (MVPA)) is associated with health in adults. Five electronic databases were searched in August 2019. Studies were eligible for inclusion if they were peer-reviewed, examined community-dwelling adults, and used compositional data analysis to examine the associations between the composition of time spent in movement behaviours and health outcomes. Eight studies (7 cross-sectional, 1 prospective cohort) of >12 000 unique participants were included. Findings indicated that the 24-h movement behaviour composition was associated with all-cause mortality (1 of 1 analyses), adiposity (4 of 4 analyses), and cardiometabolic biomarkers (8 of 15 analyses). Reallocating time into MVPA from other movement behaviours was associated with favourable changes to most health outcomes and taking time out of SED and reallocating it into other movement behaviours was associated with favourable changes to all-cause mortality. The quality of evidence was very low for all health outcomes. In conclusion, these findings support the notion that the composition of movement across the entire 24-h day matters, and that recommendations for sleep, SED, and physical activity should be combined into a single public health guideline. (PROSPERO registration no.: CRD42019121641.) Novelty The 24-h movement behaviour composition is associated with a variety of health outcomes. Reallocating time into MVPA is favourably associated with health. Reallocating time out of SED is associated with favourable changes to mortality risk.

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.

scholarly journals GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies

2021 ◽  
pp. bjsports-2020-103604
Author(s):  
Jairo H Migueles ◽  
Eivind Aadland ◽  
Lars Bo Andersen ◽  
Jan Christian Brønd ◽  
Sebastien F Chastin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Data Analysis ◽  
Sedentary Behaviour ◽  
Compositional Data ◽  
Epidemiological Studies ◽  
Future Research ◽  
Compositional Data Analysis ◽  
Accelerometer Data ◽  
Physical Behaviour ◽  
Analytical Approaches

The inter-relationship between physical activity, sedentary behaviour and sleep (collectively defined as physical behaviours) is of interest to researchers from different fields. Each of these physical behaviours has been investigated in epidemiological studies, yet their codependency and interactions need to be further explored and accounted for in data analysis. Modern accelerometers capture continuous movement through the day, which presents the challenge of how to best use the richness of these data. In recent years, analytical approaches first applied in other scientific fields have been applied to physical behaviour epidemiology (eg, isotemporal substitution models, compositional data analysis, multivariate pattern analysis, functional data analysis and machine learning). A comprehensive description, discussion, and consensus on the strengths and limitations of these analytical approaches will help researchers decide which approach to use in different situations. In this context, a scientific workshop and meeting were held in Granada to discuss: (1) analytical approaches currently used in the scientific literature on physical behaviour, highlighting strengths and limitations, providing practical recommendations on their use and including a decision tree for assisting researchers’ decision-making; and (2) current gaps and future research directions around the analysis and use of accelerometer data. Advances in analytical approaches to accelerometer-determined physical behaviours in epidemiological studies are expected to influence the interpretation of current and future evidence, and ultimately impact on future physical behaviour guidelines.

scholarly journals Using Compositional Data Analysis to Explore Associations Between Accumulation of Sedentary Behaviour and Physical Activity and Biomarkers of Cardiometabolic Health in Children and Adolescents: A Cross-Sectional Study

2020 ◽  
Author(s):  
Simone Johanna Josefa Maria Verswijveren ◽  
Karen E. Lamb ◽  
Josep A. Martín-Fernández ◽  
Elisabeth Winkler ◽  
Rebecca M. Leech ◽  
...  
Keyword(s):  
Physical Activity ◽  
Waist Circumference ◽  
Sedentary Behaviour ◽  
Time Use ◽  
Cardiometabolic Risk ◽  
Sedentary Time ◽  
Compositional Data ◽  
Compositional Data Analysis ◽  
Intensity Physical Activity ◽  
Vigorous Intensity

Abstract Background The consequences for youth cardiometabolic risk might depend on whether sedentary time and physical activity are accumulated sporadically (in shorter bouts) or in a sustained pattern (in longer bouts). This study aimed to: 1) describe daily time-use compositions of youth, including time spent in shorter and longer bouts of sedentary behaviour and physical activity; and 2) examine associations between time-use compositions with cardiometabolic biomarkers.Methods Accelerometer and cardiometabolic biomarker data (adiposity, blood pressure, lipids) from 7–13 year olds (mean ± SD: 10.4 ± 1.7) from two Australian studies were pooled (complete cases adiposity n = 772). A time-use composition of nine components was formed using compositional data analysis: time in shorter and longer bouts of sedentary behaviour, light-, moderate- and vigorous-intensity physical activity, and “other time” (i.e., non-wear/sleep). Shorter and longer bouts of sedentary time were defined as < 5 and ≥ 5 min, respectively. Longer light-, moderate- and vigorous-intensity physical activity bouts were defined as ≥ 1 min. Linear regression models examined associations between overall time-use composition and cardiometabolic biomarkers. Then, associations between ratios of longer relative to shorter activity patterns, and each intensity relative to more intense activities and/or “other time”, with cardiometabolic biomarkers were derived.Results Confounder-adjusted models showed that the overall time-use composition was associated with zBMI, waist circumference, systolic blood pressure, high-density lipoprotein cholesterol, triglycerides, and a combined cardiometabolic risk score. Specifically, more time in longer relative to shorter bouts of light-intensity physical activity was associated with greater zBMI (β = 1.79, SE = 0.70, p = 0.010) and waist circumference (β = 17.28, SE = 4.87, p < 0.001). More time in longer relative to shorter bouts of vigorous-intensity physical activity was also associated with higher waist circumference (β = 2.54, SE = 1.14, p = 0.026). More relative time in total light- and vigorous-intensity physical activity (including longer and shorter bouts) was associated with lower waist circumference. In contrast, more relative time in sedentary behaviour and moderate-intensity physical activity was detrimental for waist circumference.Conclusions Accumulating physical activity in frequent short bursts may be beneficial for adiposity compared to engaging in the same amount of these intensities in longer bouts.Trial registration: 'Lifestyle Of Our Kids’ (ACTRN12615000066583 [23/01/2015]) and ‘Transform-Us!’ (ACTRN12609000715279 [19/08/2009], ISRCTN83725066 [30/06/2010]).

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 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.

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