Use of Compositional Data Analysis to Show Estimated Changes in Cardiometabolic Health by Reallocating Time to Light-Intensity Physical Activity in Older Adults

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.

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

Journal of Physical Activity and Health ◽

10.1123/jpah.2020-0487 ◽

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.

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

International Journal of Behavioral Nutrition and Physical Activity ◽

10.1186/s12966-021-01092-0 ◽

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.

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Correction to: The difference in sleep, sedentary behaviour, and physical activity between older adults with ‘healthy’ and ‘unhealthy’ cardiometabolic profiles: a cross-sectional compositional data analysis approach

European Review of Aging and Physical Activity ◽

10.1186/s11556-020-0236-z ◽

2020 ◽

Vol 17 (1) ◽

Author(s):

Declan John Ryan ◽

Jorgen Antonin Wullems ◽

Georgina Kate Stebbings ◽

Christopher Ian Morse ◽

Claire Elizabeth Stewart ◽

...

Keyword(s):

Physical Activity ◽

Older Adults ◽

Data Analysis ◽

Sedentary Behaviour ◽

Compositional Data ◽

Analysis Approach ◽

Compositional Data Analysis ◽

Cross Sectional ◽

The Difference

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

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18084191 ◽

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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Duration–Response of Light-Intensity Physical Activity and Glucose Dynamics in Older Adults

Journal of Physical Activity and Health ◽

10.1123/jpah.2017-0557 ◽

2019 ◽

Vol 16 (1) ◽

pp. 37-42 ◽

Cited By ~ 3

Author(s):

Whitney A. Welch ◽

Scott J. Strath ◽

Michael Brondino ◽

Renee Walker ◽

Ann M. Swartz

Keyword(s):

Physical Activity ◽

Older Adults ◽

Light Intensity ◽

Intensity Physical Activity ◽

Glucose Dynamics

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

PLoS ONE ◽

10.1371/journal.pone.0206013 ◽

2018 ◽

Vol 13 (10) ◽

pp. e0206013 ◽

Cited By ~ 18

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

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Objective Light-Intensity Physical Activity Associations With Rated Health in Older Adults

American Journal of Epidemiology ◽

10.1093/aje/kwq249 ◽

2010 ◽

Vol 172 (10) ◽

pp. 1155-1165 ◽

Cited By ~ 325

Author(s):

M. P. Buman ◽

E. B. Hekler ◽

W. L. Haskell ◽

L. Pruitt ◽

T. L. Conway ◽

...

Keyword(s):

Physical Activity ◽

Older Adults ◽

Light Intensity ◽

Intensity Physical Activity

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Light-Intensity Physical Activity and Cardiometabolic Risk Among Older Adults With Multiple Chronic Conditions

American Journal of Health Promotion ◽

10.1177/0890117118796459 ◽

2018 ◽

Vol 33 (4) ◽

pp. 507-515 ◽

Cited By ~ 4

Author(s):

Yueyao Li ◽

Kellee White ◽

Katherine R. O’Shields ◽

Alexander C. McLain ◽

Anwar T. Merchant

Keyword(s):

Physical Activity ◽

Risk Factors ◽

Blood Pressure ◽

Older Adults ◽

Light Intensity ◽

Total Cholesterol ◽

Chronic Conditions ◽

Cardiometabolic Risk ◽

Multiple Chronic Conditions ◽

Intensity Physical Activity

Purpose: To assess the relationship between light-intensity physical activity (LIPA) and cardiometabolic risk factors among middle-aged and older adults with multiple chronic conditions. Design: Cross-sectional design utilizing data from the Health and Retirement Study (2010, 2012). Setting: Laboratory- and survey-based testing of a nationally representative sample of community-dwelling middle aged and older adults. Participants: Adults aged 50 years and older (N = 14 996). Measures: Weighted metabolic equivalent of tasks was calculated using self-reported frequency of light, moderate, and vigorous physical activity. Cardiometabolic risk factors (systolic and diastolic blood pressure, glycosylated hemoglobin [HbA1c], high-density lipoprotein cholesterol [HDL-C], total cholesterol, and non-HDL-C) were objectively measured. A multiple chronic condition index was based on 8 self-reported chronic conditions. Analysis: Weighted multivariate linear regression models. Results: Light-intensity physical activity was independently associated with favorable HDL-C (β = 1.25; 95% confidence interval [CI]: 0.46-2.05) and total cholesterol (β = 2.72; 95% CI: 0.53-4.90) after adjusting for relevant confounders. The HDL-C health benefit was apparent when stratified by number of chronic conditions, for individuals with 2 to 3 conditions (β = 1.73; 95% CI: 0.58-2.89). No significant associations were observed between LIPA and blood pressure, HbA1c, or non-HDL-C. Conclusions: Engaging in LIPA may be an important health promotion activity to manage HDL-C and total cholesterol. Additional longitudinal research is needed to determine the causal association between LIPA and cardiometabolic risk which can potentially inform physical activity guidelines targeting older adults with multiple chronic conditions.

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

International Journal of Obesity ◽

10.1038/s41366-020-0638-z ◽

2020 ◽

Vol 45 (1) ◽

pp. 266-275 ◽

Cited By ~ 1

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.

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