Individual barriers to weight loss and physical activity goals in the Diabetes Prevention Program, a randomized trial with 3.2 years average treatment duration, have not been previously reported. Evaluating barriers and the lifestyle coaching approaches used to improve adherence in a large, diverse participant cohort can inform dissemination efforts. Lifestyle coaches documented barriers and approaches after each session (mean session attendance = 50.3 ± 21.8). Subjects were 1076 intensive lifestyle participants (mean age = 50.6 years; mean BMI = 33.9 kg/m2; 68% female, 48% non-Caucasian). Barriers and approaches used to improve adherence were ranked by the percentage of the cohort for whom they applied. Barrier groupings were also analyzed in relation to baseline demographic characteristics. Top weight loss barriers reported were problems with self-monitoring (58%); social cues (58%); holidays (54%); low activity (48%); and internal cues (thought/mood) (44%). Top activity barriers were holidays (51%); time management (50%); internal cues (30%); illness (29%), and motivation (26%). The percentage of the cohort having any type of barrier increased over the long-term intervention period. A majority of the weight loss barriers were significantly associated with younger age, greater obesity, and non-Caucasian race/ethnicity (p-values vary). Physical activity barriers, particularly thought and mood cues, social cues and time management, physical injury or illness and access/weather, were most significantly associated with being female and obese (p < 0.001 for all). Lifestyle coaches used problem-solving with most participants (≥75% short-term; > 90% long term) and regularly reviewed self-monitoring skills. More costly approaches were used infrequently during the first 16 sessions (≤10%) but increased over 3.2 years. Behavioral problem solving approaches have short and long term dissemination potential for many kinds of participant barriers. Given minimal resources, increased attention to training lifestyle coaches in the consistent use of these approaches appears warranted.

OBJECTIVE Sleep disturbances and circadian misalignment (social jet lag, late chronotype, or shift work) have been associated with worse glycemic control in type 2 diabetes (T2D). Whether these findings apply to adults with prediabetes is yet unexplored. We hypothesized that self-reported short sleep, poor sleep quality, and/or circadian misalignment are associated with higher glycemia, BMI, and blood pressure (BP) in adults with prediabetes or recently diagnosed, untreated T2D. RESEARCH DESIGN AND METHODS Our cohort included 962 overweight/obese adults ages 20–65 years with prediabetes or recently diagnosed, untreated T2D who completed a 2-h oral glucose tolerance test and validated sleep questionnaires. Independent associations of sleep and circadian variables with glycemia, BMI, and BP were evaluated with regression models. RESULTS The multiethnic cohort was 55% men, with mean ± SD age 52.2 ± 9.5 years and BMI 34.7 ± 5.5 kg/m². Mean sleep duration was 6.6 ± 1.3 h. Poor sleep quality was reported by 54% and high risk for obstructive sleep apnea by 64%. HbA_1c was significantly higher in those reporting 8 h sleep per night. Sleep duration >8 h was also associated with higher fasting glucose and <6 h with higher BMI. Shift work was also associated with higher BMI. Social jet lag and delayed chronotype were associated with higher BP. CONCLUSIONS In our cohort, self-reported short and long sleep were both associated with adverse measures of glycemia, and short sleep and shift work were associated with higher BMI. Further research using objective measures of sleep is needed to better delineate the relationship between sleep and glycemia in adults with prediabetes or T2D.

OBJECTIVE To identify predictors of glycemic worsening among youth and adults with impaired glucose tolerance (IGT) or recently diagnosed type 2 diabetes in the Restoring Insulin Secretion (RISE) Study. RESEARCH DESIGN AND METHODS A total of 91 youth (10–19 years) were randomized 1:1 to 12 months of metformin (MET) or 3 months of glargine, followed by 9 months of metformin (G-MET), and 267 adults were randomized to MET, G-MET, liraglutide plus MET (LIRA+MET), or placebo for 12 months. All participants underwent a baseline hyperglycemic clamp and a 3-h oral glucose tolerance test (OGTT) at baseline, month 6, month 12, and off treatment at month 15 and month 21. Cox models identified baseline predictors of glycemic worsening (HbA_1c increase ≥0.5% from baseline). RESULTS Glycemic worsening occurred in 17.8% of youth versus 7.5% of adults at month 12 (P = 0.008) and in 36% of youth versus 20% of adults at month 21 (P = 0.002). In youth, glycemic worsening did not differ by treatment. In adults, month 12 glycemic worsening was less on LIRA+MET versus placebo (hazard ratio 0.21, 95% CI 0.05–0.96, P = 0.044). In both age-groups, lower baseline clamp-derived β-cell responses predicted month 12 and month 21 glycemic worsening (P < 0.01). Lower baseline OGTT-derived β-cell responses predicted month 21 worsening (P < 0.05). In youth, higher baseline HbA_1c and 2-h glucose predicted month 12 and month 21 glycemic worsening, and higher fasting glucose predicted month 21 worsening (P < 0.05). In adults, lower clamp- and OGTT-derived insulin sensitivity predicted month 12 and month 21 worsening (P < 0.05). CONCLUSIONS Glycemic worsening was more common among youth than adults with IGT or recently diagnosed type 2 diabetes, predicted by lower baseline β-cell responses in both groups, hyperglycemia in youth, and insulin resistance in adults.

Introduction: Observational studies of SARS-CoV-2 vaccine effectiveness depend on accurate ascertainment of vaccination receipt, date, and product type. Self-reported vaccine data may be more readily available to and less expensive for researchers than assessing medical records. Methods: We surveyed adult participants in the COVID-19 Community Research Partnership who had an authenticated Electronic Health Record (EHR) (N = 41,484) concerning receipt of SARS-CoV-2 vaccination using a daily survey beginning in December 2020 and a supplemental survey in September–October 2021. We compared self-reported information to that available in the EHR for the following data points: vaccine brand, date of first dose, and number of doses using rates of agreement and Bland–Altman plots for visual assessment. Self-reported data was available immediately following vaccination (in the daily survey) and at a delayed interval (in a secondary supplemental survey). Results: For the date of first vaccine dose, self-reported “immediate” recall was within ±7 days of the date reported in the “delayed” survey for 87.9% of participants. Among the 19.6% of participants with evidence of vaccination in their EHR, 95% self-reported vaccination in one of the two surveys. Self-reported dates were within ±7 days of documented EHR vaccination for 97.6% of the “immediate” surveys and 92.0% of the “delayed” surveys. Self-reported vaccine product details matched those in the EHR for over 98% of participants for both “immediate” and “delayed” surveys. Conclusions: Self-reported dates and product details for COVID-19 vaccination can be a good surrogate when medical records are unavailable in large observational studies. A secondary confirmation of dates for a subset of participants with EHR data will provide internal validity.