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

ABSTRACT: 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.

SUBMITTER: Dumuid D

PROVIDER: S-EPMC7177981 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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

Dumuid Dorothea D Pedišić Željko Ž Palarea-Albaladejo Javier J Martín-Fernández Josep Antoni JA Hron Karel K Olds Timothy T

International journal of environmental research and public health 20200326 7

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 unde ...[more]

PMID: 32224966

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Project description:BACKGROUND:To examine compositional associations between short sleep duration and sedentary behavior (SB), light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) among children and adolescents. METHODS:Multi-day 24-h data on sleep, SB, LPA and MVPA were collected using accelerometers among 343 children (8-13 years old) and 316 adolescents (14-18 years old). Children and adolescents with sleep duration of < 9 and < 8 h, respectively, were classified as short sleepers. Robust compositional regression analysis was used to examine the associations between short sleep duration and the waking-time composition. RESULTS:Seventy-one percent of children and 75.3% of adolescents were classified as short sleepers. In children, being a short sleeper was associated with higher SB by 95 min/day (p < 0.001) and lower MVPA by 16 min/day (p = 0.002). Specifically, it was associated with a higher amount of time spent in long sedentary bouts (βilr1 = 0.46, 95% confidence interval [CI] = 0.29 to 0.62) and lower amounts of time spent in sporadic SB (βilr1 = - 0.17, 95% CI = -0.24 to - 0.10), sporadic LPA (βilr1 = - 0.09, 95% CI = -0.14 to - 0.04) and sporadic MVPA (βilr1 = - 0.17, 95% CI = -0.25 to - 0.10, p < 0.001 for all), relative to the remaining behaviours. In adolescents, being a short sleeper was associated with a higher amount of time spent in SB by 67 min/day (p = 0.001) and lower LPA by 2 min/day (p = 0.035). Specifically, it was associated with more time spent in sedentary bouts of 1-9 min (βilr1 = 0.08, 95% CI = 0.02 to 0.14, p = 0.007) and 10-29 min (βilr1 = 0.10, 95% CI = 0.02 to 0.18, p = 0.015), relative to the remaining behaviours. CONCLUSIONS:Among children and adolescents, short sleep duration seems to be highly prevalent and associated with less healthy waking time. Public health interventions and strategies to tackle the high prevalence of short sleep duration among children and adolescents are warranted.

Project description:BackgroundMovement behaviours performed over a finite period such as a 24 h day are compositional data. Compositional data exist in a constrained simplex geometry that is incongruent with traditional multivariate analytical techniques. However, the expression of compositional data as log-ratio co-ordinate systems transfers them to the unconstrained real space, where standard multivariate statistics can be used. This study aimed to use a compositional data analysis approach to examine the adiposity and cardiorespiratory fitness predictions of time reallocations between children's daily movement behaviours.MethodsThis study used cross-sectional data from the Active Schools: Skelmersdale study, which involved Year 5 children from a low-income community in northwest England (n = 169). Measures included accelerometer-derived 24 h activity (sedentary time [ST], light physical activity [LPA], moderate-to-vigorous physical activity [MVPA], and sleep), cardiorespiratory fitness determined by the 20 m shuttle run test, objectively measured height, weight and waist circumference (from which zBMI and percent waist circumference-to-height ratio (%WHtR) were derived) and sociodemographic covariates. Log-ratio multiple linear regression models were used to predict adiposity and fitness for the mean movement behaviour composition, and for new compositions where fixed durations of time had been reallocated from one behaviour to another, while the remaining behaviours were unchanged. Predictions were also made for reallocations of fixed durations of time using the mean composition of three different weight status categories (underweight, normal-weight, and overweight/obese) as the starting point.ResultsReplacing MVPA with any other movement behaviour around the mean movement composition predicted higher adiposity and lower CRF. The log-ratio model predictions were asymmetrical: when time was reallocated to MVPA from sleep, ST, or LPA, the estimated detriments to fitness and adiposity were larger in magnitude than the estimated benefits of time reallocation from MVPA to sleep, ST or LPA. The greatest differences in fitness and fatness for reallocation of fixed duration of MVPA were predicted at the mean composition of overweight/obese children.ConclusionsFindings reinforce the key role of MVPA for children's health. Reallocating time from ST and LPA to MVPA in children is advocated in school, home, and community settings.

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

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

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