Accelerometry-Based Characteristics of Overall Sedentary Behavior and Sitting in Middle-Aged Adults

ABSTRACT

The purpose of this study was to describe the accelerometry-based characteristics of overall sedentary behavior (SB) and sitting among adults under free-living conditions. Thirty-six (mean age 47.6 years) volunteers carried a waist-worn accelerometer for ≥4 days with data ≥600 min/d during 14 consecutive days. A machine learning (ML) based method was used to classify the patterns of SB and sitting from raw 3D acceleration. The participants spent most (69.3%) of their waking time in SB, and a half (52.2%) of the SB was performed in a sitting posture. Men broke their overall sedentary time less often (4.1 vs. 6.1 bouts/h), but women sat more; however, women broke their sitting time as often as men (7.6 bouts/h). This study confirms that SB and sitting can be distinguished using ML methods, and more information about SB can be achieved when overall SB and sitting are analyzed separately in free-living conditions.

KEYWORDS:

• Sedentary behavior
• sitting
• accelerometer
• raw data
• machine learning

Acknowledgments

The authors would like to thank the volunteer study participants, the NFBC project center, and the study nurses for their efforts in the field work. This work was in part financially supported by University of Oulu [Grant number 24000692], Oulu University Hospital [Grant number 24301140], ERDF European Regional Development Fund [Grant number 539/2010 A31592], and Ministry of Education and Culture, and Finnish Cultural Foundation.

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Funding

This work was supported by the Oulu University Hospital [24301140]; Finnish Cultural Foundation;University of Oulu [24000692]; ERDF European Regional Development Fund [539/2010 A31592]; Ministry of Education and Culture, Finland.