The health effects of daily activity behaviours (physical activity, sedentary time and sleep) are widely studied. While previous research has largely examined activity behaviours in isolation, recent studies have adjusted for multiple behaviours. However, the inclusion of all activity behaviours in traditional multivariate analyses has not been possible due to the perfect multicollinearity of 24-h time budget data. The ensuing lack of adjustment for known effects on the outcome undermines the validity of study findings. We describe a statistical approach that enables the inclusion of all daily activity behaviours, based on the principles of compositional data analysis. Using data from the International Study of Childhood Obesity, Lifestyle and the Environment, we demonstrate the application of compositional multiple linear regression to estimate adiposity from children's daily activity behaviours expressed as isometric log-ratio coordinates. We present a novel method for predicting change in a continuous outcome based on relative changes within a composition, and for calculating associated confidence intervals to allow for statistical inference. The compositional data analysis presented overcomes the lack of adjustment that has plagued traditional statistical methods in the field, and provides robust and reliable insights into the health effects of daily activity behaviours.

• MeSH
• cvičení * MeSH
• dítě MeSH
• interpretace statistických dat * MeSH
• lidé MeSH
• obezita dětí a dospívajících * MeSH
• sedavý životní styl * MeSH
• spánek * MeSH
• Check Tag
• dítě MeSH
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

How people use their time has been linked with their health. For example, spending more time being physically active is known to be beneficial for health, whereas long durations of sitting have been associated with unfavourable health outcomes. Accordingly, public health messages have advocated swapping strategies to promote the reallocation of time between parts of the time-use composition, such as "Move More, Sit Less", with the aim of achieving optimal distribution of time for health. However, the majority of research underpinning these public health messages has not considered daily time use as a composition, and has ignored the relative nature of time-use data. We present a way of applying compositional data analysis to estimate change in a health outcome when fixed durations of time are reallocated from one part of a particular time-use composition to another, while the remaining parts are kept constant, based on a multiple linear regression model on isometric log ratio coordinates. In an example, we examine the expected differences in Body Mass Index z-scores for reallocations of time between sleep, physical activity and sedentary behaviour.

• MeSH
• algoritmy MeSH
• cvičení * MeSH
• lidé MeSH
• obezita dětí a dospívajících MeSH
• organizace času * MeSH
• sedavý životní styl * MeSH
• spánek * MeSH
• statistické modely * MeSH
• zdravotní stav MeSH
• životní styl MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

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.

• MeSH
• adipozita MeSH
• analýza dat * MeSH
• činnosti denního života MeSH
• cvičení * MeSH
• dítě MeSH
• kohortové studie MeSH
• lidé MeSH
• longitudinální studie MeSH
• sedavý životní styl * MeSH
• spánek MeSH
• Check Tag
• dítě MeSH
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Austrálie MeSH

OBJECTIVES: Growing evidence supports the important role of 24-hour movement behaviours (MB) in preventing childhood obesity. However, research to understand the heterogeneity and variability of MB among individuals and what kind of typologies of individuals are at risk of developing obesity is lacking. To bridge this gap, this study identified typologies of 24-hour MB in children and adolescents and investigated their associations with adiposity indicators. METHODS: In this cross-sectional study, 374 children and 317 adolescents from the Czech Republic wore wrist-worn accelerometers for seven consecutive days. Time spent in moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), sedentary behaviour (SB), and sleep was quantified using raw accelerometery data. Adiposity indicators included body mass index (BMI) z-score, fat mass percentage (FM%), fat mass index (FMI), and visceral adipose tissue (VAT). Bias-adjusted latent profile analysis was used on the 24-hour MB data to identify MB typologies and their associations with adiposity indicators. The models were adjusted for potential confounders. The identified typologies were labelled to reflect the behavioural profiles of bees to aid interpretability for the general public. RESULTS: Two typologies were identified in children: highly active Workers characterised by high levels of MVPA and LPA, and inactive Queens characterised by low levels of MVPA and LPA, high levels of SB and longer sleep duration compared to Workers. In adolescents, an additional typology labelled as Drones was characterised by median levels of MVPA, LPA, SB and longest sleep duration. After controlling for covariates, we found that children labelled as Queens were associated with 1.38 times higher FM%, 1.43 times higher FMI, and 1.67 times higher VAT than Workers. In adolescents, Drones had 1.14 times higher FM% and Queens had 1.36 higher VAT in comparison with Workers, respectively. CONCLUSION: Our study highlights the importance of promoting active lifestyles in children and adolescents to potentially reduce adiposity. These findings can provide insights for interventions aimed at promoting healthy MB and preventing childhood obesity.

• MeSH
• adipozita * fyziologie   MeSH
• akcelerometrie MeSH
• cvičení * MeSH
• dítě MeSH
• index tělesné hmotnosti MeSH
• lidé MeSH
• mladiství MeSH
• obezita dětí a dospívajících * epidemiologie   MeSH
• průřezové studie MeSH
• sedavý životní styl * MeSH
• spánek fyziologie   MeSH
• Check Tag
• dítě MeSH
• lidé MeSH
• mladiství MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Česká republika MeSH