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Compositional functional regression and isotemporal substitution analysis: Methods and application in time-use

Paulína Jašková1, Javier Palarea-Albaladejo2, Aleš Gába3

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Shifting time towards higher intensity physical activity is linked to reduced adiposity in children. This study introduces novel compositional functional methods to analyze physical activity time use and its health impacts.

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Area of Science:

  • Public Health
  • Biostatistics
  • Human Physiology

Background:

  • Physical activity, sedentary behavior, and sleep are interconnected components of daily time use.
  • Analyzing these behaviors separately overlooks their compositional nature and health implications.
  • Understanding the relationship between physical activity intensity distribution and health is crucial.

Purpose of the Study:

  • To investigate how reallocating time between different physical activity intensities affects health outcomes.
  • To introduce and apply novel compositional functional statistical methods for analyzing time-use data.
  • To explore the dose-response relationship between physical activity intensity and adiposity in children.

Main Methods:

  • Utilized compositional scalar-on-function regression and compositional functional isotemporal substitution analysis.
  • Treated physical activity intensity data as probability density functions, analyzed in Bayes spaces via centered logratio (clr) transformation.
  • Applied methods to a cross-sectional study dataset of school-aged children in the Czech Republic.

Main Results:

  • Theoretical time reallocations to higher intensity physical activity were associated with significant decreases in adiposity.
  • Demonstrated a detailed dose-response relationship between physical activity intensity and adiposity.
  • The compositional functional approach provided novel insights into physical activity and health.

Conclusions:

  • The study highlights the health benefits of increasing time spent in higher intensity physical activity.
  • Novel statistical methods enable a more accurate analysis of complex physical activity patterns.
  • Findings contribute to a better understanding of physical activity's role in managing childhood adiposity.