How composition of device-measured 24-h movement behaviors differs between office and remote workdays among hybrid workers?

Abstract Background There is limited evidence, especially from the post‑pandemic period, on how remote workdays differ from office workdays in 24‑h movement behaviors, that is, sleep, sedentary behavior (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA), and how time is reallocated when work shifts from the office to remote environment. This study examined differences in 24-h movement behaviors between office and remote workdays among hybrid workers. Methods Overall, 97 university employees (84% women, mean age 42 ± 10 years) self-reported their time in bed (TiB) and wore a thigh-worn Fibion SENS sensor for 7 consecutive days, including at least one office and one remote workday (on average 2.4 office and 2.6 remote workdays). Sensor-identified body postures and activity types were further categorized into SED, LPA, and MVPA. The compositional linear mixed models were used to examine within-individual differences in 24-h movement behaviors between remote and office workdays, adjusting for sex, age, and body mass index (BMI). To aid further interpretation, time flow analysis was used to examine how time was redistributed between movement behaviors when changing the work environment from office to remote. Results The ratio of active behaviors (LPA, MVPA) to passive behaviors (TiB, SED) was lower on a remote workday compared to office workday ( p <.0001). This corresponded to 14 min more TiB, 44 min more SED, 37 min less LPA, and 21 min less MVPA (compared with office workday including 7.6 h TiB, 10.6 h SED, 5.0 h LPA, and 49 min MVPA). Moreover, the ratio of LPA to MVPA was higher on a remote workday when compared to an office workday ( p <.0001). No significant differences were observed in the ratio of SED to TiB ( p = .15). Mainly, the time spent standing and cycling was replaced with SED and TiB when changing the work environment from office to a remote. Conclusions Compared with office workdays, remote workdays included slightly longer TiB and substantially more SED, alongside lower physical activity. In particular, the higher SED and lower physical activity observed during remote work suggest that exploring feasible ways to compensate for these behavioral differences may be warranted.

Authors

Institutions

Publication Details

Journal
International Journal of Behavioral Nutrition and Physical Activity
Published
2026-07-28
DOI
https://doi.org/10.1186/s12966-026-01959-0
Primary Topic
Physical Activity and Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

How composition of device-measured 24-h movement behaviors differs between office and remote workdays among hybrid workers?

Kristin Suorsa, Miika Tuominen, Sanna Pasanen, Jesse Pasanen et al.
International Journal of Behavioral Nutrition and Physical Activity
Physical Activity and Health
article

How composition of device-measured 24-h movement behaviors differs between office and remote workdays among hybrid workers?

Kristin Suorsa, Miika Tuominen, Sanna Pasanen, Jesse Pasanen, Sari Stenholm, Nidhi Gupta, Tuija Leskinen
article en

Abstract

Abstract Background There is limited evidence, especially from the post‑pandemic period, on how remote workdays differ from office workdays in 24‑h movement behaviors, that is, sleep, sedentary behavior (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA), and how time is reallocated when work shifts from the office to remote environment. This study examined differences in 24-h movement behaviors between office and remote workdays among hybrid workers. Methods Overall, 97 university employees (84% women, mean age 42 ± 10 years) self-reported their time in bed (TiB) and wore a thigh-worn Fibion SENS sensor for 7 consecutive days, including at least one office and one remote workday (on average 2.4 office and 2.6 remote workdays). Sensor-identified body postures and activity types were further categorized into SED, LPA, and MVPA. The compositional linear mixed models were used to examine within-individual differences in 24-h movement behaviors between remote and office workdays, adjusting for sex, age, and body mass index (BMI). To aid further interpretation, time flow analysis was used to examine how time was redistributed between movement behaviors when changing the work environment from office to remote. Results The ratio of active behaviors (LPA, MVPA) to passive behaviors (TiB, SED) was lower on a remote workday compared to office workday ( p <.0001). This corresponded to 14 min more TiB, 44 min more SED, 37 min less LPA, and 21 min less MVPA (compared with office workday including 7.6 h TiB, 10.6 h SED, 5.0 h LPA, and 49 min MVPA). Moreover, the ratio of LPA to MVPA was higher on a remote workday when compared to an office workday ( p <.0001). No significant differences were observed in the ratio of SED to TiB ( p = .15). Mainly, the time spent standing and cycling was replaced with SED and TiB when changing the work environment from office to a remote. Conclusions Compared with office workdays, remote workdays included slightly longer TiB and substantially more SED, alongside lower physical activity. In particular, the higher SED and lower physical activity observed during remote work suggest that exploring feasible ways to compensate for these behavioral differences may be warranted.

International Journal of Behavioral Nutrition and Physical Activity
University of Turku (FI), Turku University Hospital (FI), National Research Centre for the Working Environment (DK)
Openalex Percentile: Top 10%
Physical Activity and Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.