We aimed to compare all-cause mortality risk across clusters of adults 50+ (n = 1,035) with common lifestyle behaviors patterns. Log-ratio coordinates of 24h movement pattern and z-scores of diet quality were used as input into a model-based clustering analysis. A Cox regression model was fitted to ascertain the all-cause mortality risk associated with each cluster. Participants were clustered into 4 groups: (1) a group characterized by a better physical activity profile and longer sleep duration coupled with an average diet quality (Cluster 1); (2) a group with the poorest activity profile and shortest sleep but also the best diet quality (Cluster 2); (3) another group featuring lower levels of activity of either intensity and higher levels of sedentary behavior and also a poor diet quality score (Cluster 3); and lastly (4) a group with an average diet quality and the best activity profile in the sample (Cluster 4). The Cox regression model fitted suggested that a combination of a poorer diet and activity profile increased the prospective risk of all-cause mortality. Our estimations reaffirm the importance of considering diet quality and the 24h movement pattern when developing interventions to improve health and, ultimately, risk of premature mortality.