OBJECTIVES:  Wearable devices such as fitness trackers allow an unprecedented ability to passively track behaviors related to health. The objective of this analysis is to explore the feasibility of using such devices to track patterns of activity and the relationship between activity and health-related quality of life (HRQoL). METHODS:  Adults with type 2 diabetes (T2D) in the United States already using an online portal to share their wearable fitness tracker data were recruited to participate in a survey. Participants consented to provide access to the fitness tracking and glucose monitoring data uploaded to the portal, and also completed online surveys and completed three weekly internet-based surveys (Baseline, 1^st follow-up, 2^nd follow-up) including the mental (MCS) and physical (PCS) component summary scores from the SF-36v1 and other measures. The current analysis focuses on baseline survey data and average activity data over the full study period. RESULTS: Baseline surveys and activity tracker data was available for 99 participants. Mean length of diagnosis was 4.3 years, and 23% were treated with insulin. The mean number of daily steps was 6,687 (SD=3,420), though participants had a very wide range of mean daily steps over the observation period (898 to 34,420 per day). The sample had high functional health status for a chronic disease sample, with a PCS score above the US general population norm of 50 (52.7, SD=8.4) and MCS scores slightly below the norm of 50 (45.7, SD=10.4). As expected, there was a significant correlation between mean daily steps and PCS scores (r=.28, p<0.01). CONCLUSIONS:  Recruiting survey respondents with T2D who are already tracking their activity through wearable devices is likely to result in healthier and more active samples than the T2D population, though such bias does not prevent exploration of relationships between activity and outcomes within this population.