Physical Activity and Sedentary Behavior Clustering: Segmentation to Optimize Active Lifestyles.

Background: Increasingly the health impacts of physical inactivity are being distinguished from those of sedentary behavior. Nevertheless, deleterious health prognoses occur when these behaviors combine, making it a Public Health priority to establish the numbers and salient identifying factors of people who live with this injurious combination.

Methods: Using an observational between-subjects design, a nonprobability sample of 22,836 participants provided data on total daily activity. A 2-step hierarchical cluster analysis identified the optimal number of clusters and the subset of distinguishing variables. Univariate analyses assessed significant cluster differences.

Results: High levels of sitting clustered with low physical activity. The Ambulatory & Active cluster (n = 6254) sat for 2.5 to 5 h·d(-1) and were highly active. They were significantly younger, included a greater proportion of males and reported low Indices of Multiple Deprivation compared with other clusters. Conversely, the Sedentary & Low Active cluster (n = 6286) achieved ≤60 MET·min·wk(-1) of physical activity and sat for ≥8 h·d(-1). They were the oldest cluster, housed the largest proportion of females and reported moderate Indices of Multiple Deprivation.

Conclusions: Public Health systems may benefit from developing policy and interventions that do more to limit sedentary behavior and encourage light intensity activity in its place.