We identified data-driven multidimensional physical activity (PA) profiles using several novel accelerometer-derived metrics. Participants aged 75, 80, and 85 (n = 441) wore triaxial accelerometers for 3-7 days. PA profiles were formed with k-means cluster analysis based on PA minutes, intensity, fragmentation, sit-to-stand transitions, and gait bouts for men and women. Associations with physical capacity and life-space mobility were examined using age-adjusted general linear models. Three profiles emerged: "Exercisers" and "actives" accumulated relatively high PA minutes, with actives engaging in lighter intensity PA. "Inactives" had the highest activity fragmentation and lowest PA volume, intensity, and gait bouts. Inactives showed lower scores in physical capacity and life-space mobility compared with exercisers and actives. Exercisers and actives had similar physical capacity and life-space mobility, except female exercisers had higher walking speed in the 6-min walk test. Our findings demonstrate the importance of assessing PA as multidimensional behavior rather than focusing on a single metric.
Keywords: cluster analysis; multidimensional physical activity; physical function.