This study are to: 1. objectively measure physical behaviour outcomes of adults participating in the move for life study; 2. develop distinct activity profiles based on six behaviour variables; 3. investigate whether health outcomes differ across the activity profiles. methods participants were irish adults aged 50 years and older. using the activpal, objectively measured data were collected on average daily: light intensity physical activity (hours); moderate to vigorous intensity physical activity (minutes); step count; time in bed (hours); standing time (hours); and waking sedentary time (hours). data were obtained on chronic illness and health service utilisation. validated questionnaires were used to collect data on wellbeing, loneliness and social isolation. hierarchical cluster analysis using squared euclidian distance was used to cluster behaviours based on similarity, using spss version 26. regression models explored associations between health out- comes and activity profiles, adjusted for age and results data from 485 participants were analysed, profiles were identified: sedentary (n = 50, active (n = 295, 60.8%), moderate active higher active (n = 29, 6%). we will present across the activity profiles for chronic morbidity, health service utilisation and tools, comparing to data from the irish on ageing (tilda) and the english ageing (elsa). conclusions the use of physical activity behaviour clusters may identify people with multi-morbidity and higher utilisation of health services. these findings could be factored into the develop-