Investigation into correlates across all levels of the socio-ecological model predictive of objectively measured physical activity has rarely been assessed in adults. While considering a diversity of correlates, we determined which correlates best predict sensor-based moderate-to-vigorous physical activity (MVPA) and sedentary-time (ST) in adults. A Chi-squared Automatic Interaction Detection algorithm was used to hierarchize the correlates associated with high ST (≥66.6thpercentile) and sufficient MVPA (≥150 min/week) in 865 adults. The main correlate predictive of being active was currently partaking in sport/exercise. The following relevant correlates were being male for the exercisers and having trees in the neighbourhood for the non-exercisers. The final correlate to boost male exercisers' MVPA was having lots of shops in the neighbourhood and not having television in the bedroom for women. The primary correlate for high ST was job activity level, with individuals having highly active jobs being less likely to exhibit high levels of ST; being single, male, and a former athlete also increased the chances of being highly sedentary. To increase adults' MVPA, promotion of sport participation, neighbourhood landscape planning, shop availability, as well as limiting television in the bedroom must be prioritized. For counteracting ST, increasing workplace activity level is warranted.
Keywords: CHAID analysis; physical activity; sedentary behaviour; sensor-based data; socio-ecological model.