Related Experiment Video
Updated: Jun 25, 2025
Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
Accelerometry-assessed physical activity and sedentary behavior patterns using single- and multi-component latent
Kelly R Evenson1, Fang Wen1, Chongzhi Di2
1Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Background:
Patterns of physical activity and sedentary behavior among postmenopausal women are not well characterized.
Objectives:
To describe the patterns of accelerometer-assessed physical activity and sedentary behavior among postmenopausal women.
Design:
Cross-sectional study.
Methods:
Women 63-97 years (n = 6126) wore an ActiGraph GT3X + accelerometer on their hip for 1 week. Latent class analysis was used to classify women by patterns of percent of wake time in physical activity and sedentary behavior over the week.
Results:
On average, participants spent two-thirds of their day in sedentary behavior (62.3%), 21.1% in light low, 11.0% in light high, and 5.6% in moderate-to-vigorous physical activity. Five classes emerged for each single-component model for sedentary behavior and light low, light high, and moderate-to-vigorous physical activity. Six classes emerged for the multi-component model that simultaneously considered the four behaviors together.
Conclusion:
Unique profiles were identified in both single- and multi-component models that can provide new insights into habitual patterns of physical activity and sedentary behavior among postmenopausal women.
Implications:
The multi-component approach can contribute to refining public health guidelines that integrate recommendations for both enhancing age-appropriate physical activity levels and reducing time spent in sedentary behavior.
