Daily domain-specific time-use composition of physical behaviors and blood pressure

Previous research has shown contrasting effects on hypertension for occupational and leisure-time physical behaviors-physical activity and sedentary behavior and time in bed. However, (a) none of these studies have addressed the compositional property of the physical behaviors and (b) most knowledge on the association between domain-specific physical behaviors and hypertension relies upon self-reported physical behaviors information primarily on white-collar worker study samples. We aimed to be the first to disentangle the relationship between technically measured 24-h time-use behaviors in work and leisure domains and blood pressure among blue-collar workers using a compositional data analysis approach.

Workers (n = 669) wore accelerometers to measure daily minutes of work and leisure sedentary time, light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA), and time in bed which were isometrically log-transformed. Cross-sectional linear association between time-use composition and systolic (SBP) and diastolic (DBP) blood pressure were determined using compositional isotemporal substitutions models.

The time-use composition at the work and leisure domains was significantly associated with SBP (F = 4.98, p < 0.001) and DBP (F = 2.91, p = 0.008). Reallocating sedentary time to remaining behaviors within each domain-work and leisure-was favorably associated with SBP. Similar results were observed when reallocating time in bed from the remaining leisure behaviors. Results for reallocating time to/from MVPA and LPA at both domains were non-significant. Results regarding all physical behaviors for DBP were generally non-significant.

Time-use composition of physical behaviors at work and leisure is associated with blood pressure among blue-collar workers. At both domains, reallocating sedentary time to remaining behaviors, especially to time in bed at leisure may reduce blood pressure. Our results, based on a compositional data approach, can be used to better design accurate and comprehensive time-use recommendations both at work and leisure for high-risk groups like blue-collar workers.