PROJECT SUMMARY The pivotal goals of diabetes treatment are to minimize diabetes complications and improve quality of life for individuals with diabetes. In-depth analyses from large scale, randomized trials and epidemiological studies have indicated that glycated hemoglobin (HbA1c), the primary metric for assessing glycemic control, alone may not sufficiently predict the risk of diabetes complications. Near-normal HbA1c level did not consistently improve diabetes complications. People with similar HbA1c values can have markedly different glucose profiles with varying frequencies and amplitudes of hypo- and hyper-glycemia. Glucose variability (GV) refers to fluctuations in blood glucose levels throughout the day (intra-day GV) or over days (inter-day GV) and is an emerging predictor of diabetes complications. GV can be measured in real-time through continuous glucose monitoring (CGM). Considerable research in CGM to understand GV has led to the growing use of CGM in clinical practice among individuals with type 1 diabetes. However, few studies address factors that affect GV in type 2 diabetes (T2D), leaving large gaps in knowledge about how to mitigate GV and improve diabetes outcomes in T2D. Roles of individuals’ lifestyle behaviors, emotional well-being and social-built environments in glucose control have been well documented. Also, real-time data on lifestyle such as day-to-day sleep, physical activity and diet are being generated. However, how these factors are associated with GV has yet to be examined. This study will be one of the first to prospectively examine the temporal relationships among sleep, physical activity, diet, emotional well-being, and GV, incorporating between-person associations and within-person variability among adults of diverse race/ethnicity with T2D. We will use a real-time, data capture strategy, ecological momentary assessment to measure lifestyle factors and emotional well-being. Three 24-hr dietary recalls will be conducted to collect nutrient-level data. We will also use actigraphy as objective measures of sleep and physical activity paired with CGM, a real-time, unobtrusive glucose measure that will be blinded from participants during a study period of 14 days. The specific aims of the study are to: (1) identify risk factors associated with high GV among diverse adults with T2D by examining between-person associations among demographics, clinical factors, lifestyle (sleep, physical activity, diet) factors, the variability of each lifestyle factor, emotional well-being, social-built environmental factors and inter-day GV, (2) identify ‘within- person predictors’ of GV to inform the development of personalized diabetes interventions by examining within- person associations among sleep, physical activity, diet, emotional well-being and intra-day GV, and (3) examine which lifestyle factors either mediate or moderate the relationship between emotional well-being and GV among diverse adults with T2D. The findings from the proposed study will guide clinical decision-making for healthcare providers to facilitate effective treatment using CGM and inform the development of personalized interventions to mitigate GV and improve diabetes outcomes.

Project Narrative Glucose variability which reflects fluctuations into hypo- and hyperglycemic ranges have been linked to diabetes complications, but little is known about factors that affect glucose variability in type 2 diabetes. This study will examine personal factors and social-built environmental factors associated with glucose variability among multi-ethnic adults with type 2 diabetes in real-time, natural living environment. The findings from the proposed study will facilitate effective treatment by identifying risk factors of glucose variability and inform the future development of personalized just-in-time interventions targeting lifestyle behaviors with an increased understanding of glucose variability by providing support for healthcare providers’ clinical decisions and patients’ diabetes self-management.