Women's Health (May 2024)

Accelerometry-assessed physical activity and sedentary behavior patterns using single- and multi-component latent class analysis among postmenopausal women

  • Kelly R Evenson,
  • Fang Wen,
  • Chongzhi Di,
  • Michael Kebede,
  • Michael J LaMonte,
  • I-Min Lee,
  • Lesley Fels Tinker,
  • Andrea Z LaCroix,
  • Annie Green Howard

DOI
https://doi.org/10.1177/17455057241257361
Journal volume & issue
Vol. 20

Abstract

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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.