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Device-Measured Physical Activity and Cardiometabolic Health
Quick Takes
- Substantial benefits in cardiometabolic outcomes were observed when 4-12 min/day were reallocated into moderate–vigorous physical activity.
- More time standing was favorably associated with cardiometabolic outcomes, while associations between sleep and low-intensity physical activity (LIPA) with cardiometabolic outcomes were complex and at times null.
- Theoretical benefits from reallocating sedentary behavior into sleep, standing, or LIPA would require substantial changes in daily activity and may not be realistic targets for behavioral interventions.
Study Questions:
What is the impact of reallocating time from one movement behavior (sleep, sedentary behavior [SB], standing, low-intensity physical activity [LIPA], moderate–vigorous physical activity [MVPA]) to another on cardiometabolic risk factors?
Methods:
This analysis used cross-sectional data from six observational cohort studies participating in the ProPASS research collaboration. All cohorts collected movement behavior using a 7-day, 24-hour/day thigh-worn accelerometer protocol. The five movement behaviors were classified as sleep, SB, standing, LIPA, and MVPA. Raw, individual-level accelerometer data were centrally processed. Data were collected on cardiometabolic outcomes (body mass index [BMI], waist circumference, lipid profile, glycated hemoglobin [HbA1c]) and covariates with known associations with movement behaviors and cardiovascular outcomes. A composition was defined as the average daily time spent in each movement behavior, normalized to 24 hours to account for nonwear. The authors conducted an individual participant meta-analysis to examine the association of each behavior relative to the other with each outcome.
Results:
A total of 15,253 participants had data on ≥1 outcome (54.7% female, mean age 53.7 years [standard deviation 9.7], 90.2% without cardiovascular disease). The mean normalized composition was 7.7 hours sleeping, 10.4 hours SB, 3.1 hours standing, 1.5 hours LIPA, and 1.3 hours MVPA. A greater proportion of time spent in SB was associated with a higher BMI, while greater time spent in other movement behaviors was associated with lower BMI. Reallocation of time from any behavior to MVPA had the largest theoretical reduction in BMI. The minimum daily behavioral change required to observe significant reductions in BMI was the displacement of 7.2 minutes of SB into MVPA. A smaller proportion of time spent in SB and a greater proportion of time spent in MVPA was associated with a more favorable lipid profile. When sleep displaced MVPA or standing outcomes, there was a deleterious association with lipid outcomes, although reallocation between sleep, SB, and LIPA resulted in negligible changes in outcomes. Displacement of any other behavior into MVPA was associated with the most favorable estimates for HbA1c with a minimal daily behavioral change being 3.8 minutes of MVPA. Replacing SB with standing had positive associations across all outcomes, although the benefits of standing were only observed after substantial amounts of time. When MVPA was dichotomized into low and high MVPA, the results were similar, although reallocation models indicated steeper associations in those with low MVPA.
Conclusions:
MVPA demonstrated the strongest, most time-efficient protective association with cardiometabolic outcomes. The benefits from reallocating SB into sleep, standing, or LIPA were only observed after substantial periods of time and may not be plausible targets for behavioral interventions.
Perspective:
Physical activity levels are grossly inadequate in US adults and many emerging behavioral interventions have focused on decreasing SB and increasing movement through standing and LIPA. This work suggests, however, that interventions targeting increases in MVPA may be most effective. In this analysis, the authors observed substantial benefits when as little as 4-12 minutes/day were reallocated to MVPA. In contrast, interventions focused on displacement between sleep, SB, standing, and LIPA would require >1 hour/day of daily behavioral change and may have limited real-world plausibility.
Important limitations of this work are of note, however. This research was conducted in largely healthy individuals who had high levels of MVPA and near recommended sleep levels. Whether similar associations would be observed amongst individuals with high levels of sleep deprivation or low levels of MVPA are unknown. In light of these high levels of MVPA, there may be a ceiling effect that may obscure potential benefits from increasing LIPA, which could be observed in a less active cohort. Second, the study was cross-sectional in nature and causality between movement behaviors and outcomes cannot be inferred. Finally, understanding what constitutes a clinically meaningful change in digital biomarkers is an important and highly clinically relevant question that cannot be answered by this study due to its cross-sectional nature.
Clinical Topics: Cardiovascular Care Team, Diabetes and Cardiometabolic Disease, Prevention, Exercise
Keywords: Cardiometabolic Risk Factors, Exercise, Sedentary Behavior
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