A closer look at the relationship among accelerometer-based physical activity metrics: ICAD pooled data

Area of Science:

• Pediatrics
• Exercise Physiology
• Biomedical Data Science

Background:

• Accelerometers are standard tools for measuring child physical activity (PA).
• Analyzing accelerometer data yields various PA metrics.
• Understanding relationships between these metrics enhances PA pattern comprehension and cross-study comparability.

Purpose of the Study:

• To investigate the interrelationships among diverse accelerometer-derived PA metrics in children.
• To inform the selection and interpretation of PA metrics in research and health studies.

Main Methods:

• Utilized data from 24,316 children (aged 5-18 years) from the International Children's Accelerometer Database (ICAD) 2.0.
• Calculated correlation coefficients between wear time, sedentary behavior (SB), light-intensity PA (LPA), moderate-intensity PA (MPA), vigorous-intensity PA (VPA), moderate- and vigorous-intensity PA (MVPA), and total activity counts (TAC).

Main Results:

• Total activity counts (TAC) increased with longer wear time, but moderate- and vigorous-intensity PA (MVPA) remained consistent across wear durations (≥8 h/day).
• MVPA showed a very high correlation with TAC (r=0.91).
• Wear time-adjusted correlations revealed a very high inverse relationship between sedentary behavior (SB) and light-intensity PA (LPA) (r=-0.96), and a moderate correlation between VPA and MPA (r=0.58).

Conclusions:

• Total activity counts (TAC) are influenced by both MVPA and wear time.
• MVPA is a reliable metric across different wear durations (≥8 h/day), facilitating cross-study comparisons.
• The significant correlations among PA metrics necessitate addressing potential collinearity in statistical models to avoid bias in health effect analyses.