Changes in physical activity levels during 60-days of 6°head-down-tilt bed rest - a preliminary data analysis of the BRACE study

Introduction: Pre-flight exercise routines are associated with bone tissue adaptation in response to microgravity (Gabel et al, 2022). Physical activity may thus serve as a predictor for the rate of tissue deterioration. The aim of this study was to monitor individual physical activity levels during a 60-days of 6° head-down-tilt bed rest (HDT) study with three intervention groups (HDT only (CON), HDT+cycling (BIKE), HDT+cycling+artificial gravity (AG)).

Methods: Data were collected during the European Space Agency (ESA)-funded “Bed Rest with Artificial gravity and Cycling Exercise (BRACE)” study, a randomized controlled trial with three intervention groups (CON, BIKE and AG). Bike and AG performed a personalized loading protocol for 30 minutes (six days/week). HDT was preceded by 14 days of baseline data collection (BDC) and followed by 14 days of recovery (R). Physical activity parameters were collected by wrist-worn (non-dominant) accelerometry (GENEActiv, Activinsights Ltd, Kimbolton, UK, sampling rate: 50 Hz, dynamic range: ± 8 g) at the following time points: prestudy (during daily life) days -14 to -1, BDC-8 to BDC-4, HDT18 to HDT23, R+0 to R+13, and poststudy (during daily life) days R+14 to R+28. Physical activity levels were calculated (R-package GGIR (Migueles et al, 2019)) with the following validated cut-points: inactive (IN < 45.8 mg), light (LIG > 45.8 mg), moderate (MOD > 93.2 mg), vigorous (VIG > 418.3 mg) (Hildebrand et al, 2017). Sleep time (SPT) was detected by heuristic algorithm (van Hees et al.
2015). Data are presented as mean, minimum and maximum. A repeated measures ANOVA was computed to detect the effect of time and intervention and their interaction on physical activity parameters with Bonferroni corrected post-hoc tests (level for significance p≤0.05).

Results: In this preliminary analysis, we included the twelve healthy male participants of study campaign 1 (age 30.3 ± 5.9 years; body mass index 23.3 ± 2.1 kg/m²). Physical activity parameters are summarized in tables 1 and 2. At all time points, participants spent most of the daytime in IN with the highest percentage in HDT. Percentage of daytime spent in LIG and MOD was lowest in HDT (LIG = 3.9%; MOD = 1.8%) and highest in poststudy (LIG = 10.5%; MOD = 7.8%; table 1). Time significantly affected all physical activity parameters except VIG. There was no measurable difference in physical activity levels between interventions, and SPT was not affected by time or intervention (table 2). MOD had the greatest percent changes over time and a high inter-individual variation (prestudy vs. HDT: -68.4 % (-88.0; -47.3), prestudy vs. poststudy: 36.7% (27.7; 173.0)) (table 2).

Conclusions: Accelerometry allowed us to quantify the expected changes in physical activity levels resulting from participation in this study and the large inter-individual differences for these changes. Participation in the countermeasure groups does not lead to a quantifiable difference in physical activity levels. The greatest decrease was observed during HDT for light
and moderate activity, which were restored in recovery and poststudy periods. The individual rate of change in physical activity is likely an important mediator of musculoskeletal changes in the bed rest and countermeasure response.

References: Gabel L, et al. 2022, Br J Sports Med;56:196–203, Hildebrand M et al. 2017, Scand J Med Sci Sports 27:1814-1823, Migueles JH et al. 2019, J Meas Phys Behav. 2(3), 188-196, van Hees, et al. 2015, PLoS ONE 10 (11): e0142533.

Funding and Acknowledgements: Study participant & MEDES study team, Federal Ministry for Economic Affairs and Climate Action, Germany & German Aerospace Centre (DLR e.V.), German Space Agency 50WB2021, 50WB2021 and partially funded by the German Research Foundation (DFG) under Grant CRC 1483 EmpkinS-Project-ID 442419336.