Distribution of device-measured 24-h movement behaviors in older adults: cross-sectional findings from the HUNT4 study

Read full text
Authors: Karen Sverdrup, Astrid Ustad, Gro Gujord Tangen, Atle Kongsvold, Beatrix Vereijken, Bjørn Heine Strand, Geir Selbæk, Linda Ernstsen, Paul Jarle Mork
Cited by: 0
References: 47

Abstract

Comprehensive mapping of key physical activity (PA) types, postures, and sleep among older adults is important for informing public health policies and interventions. This study aimed to describe the 24-h time distribution of key PA types, postures, and sleep in a population-based sample of community-dwelling older adults and explore whether age, sex, and educational level influenced this distribution. Participants 65 years and older from the fourth survey of the Trøndelag Health Study (HUNT4, 2017-19) with ≥ 1 day of complete accelerometer recording were included (n = 8,114). PA types (walking, running, cycling), postures (standing, sitting, lying (awake)), and sleep were derived from the accelerometer data using validated machine learning models. Survey-weighted regression models were applied to describe the 24-h time distribution of PA types, postures, and sleep by age, sex, and education. Participants spent 4.1 h standing (SD 85.3 min), 82.8 min (SD 40.3 min) walking, 0.2 min (SD 1.7 min) running, 4.6 min (SD 7.2 min) cycling, 9.2 h (SD 115.5 min) sitting, 2.1 h (SD 86.6 min) lying (awake), and 7.1 h (SD 50.4 min) sleeping per day. Time spent standing and walking decreased, while time spent sitting, lying (awake), and sleeping increased with higher age. Women spent more time standing and sleeping, and less time walking, sitting, and lying (awake) than men. Higher education was associated with more time standing and walking and less time sitting. This study provides novel insights into the distribution of 24-h movement behaviors among older adults and can serve as a benchmark for future research on key PA types, postures, sleep, and their interactions.

Fields of Study & Subjects

Physical Activity and Health Context-Aware Activity Recognition Systems Sleep and related disorders

Publication details

Journal / source
Scientific Reports
Volume
16
Issue
1
Pages
5268–5268
Publication date
15 January 2026
Language
EN