Objective: Early time-restricted feeding (eTRF) is an intermittent fasting strategy restricting caloric intake to the first 6-8 hours of the day. While previous studies have shown that eTRF improves glycemia, it is unclear if the effect is due to associated weight loss or metabolic benefits of the feeding strategy itself. In this study, we evaluated the weight-independent effects of eTRF on glycemia using multiple CGM-based time in range (TIR) metrics. Methods: We conducted a randomized 7-day isocaloric crossover supervised feeding study comparing eTRF (80% of calories consumed between 8am-1pm) to a usual feeding pattern (UFP, 50% of calories consumed after 4pm) among participants with prediabetes and BMI > 28 kg/m2 in a metabolic ward. Participants were randomized 1:1 to eTRF or UFP for days 1-7, then crossed over to the other arm on days 8-14. Food intake was tailored to meet weight stable caloric needs. Participants also wore blinded Abbott Freestyle Libre CGMs throughout the study period. We evaluated time spent below 70 mg/dL (TBR<70), in 70-140 mg/dL (TIR70-140), and in 140-180 mg/dL (TIR140-180) glucose range per arm. Further, we compared TIR140-180 between arms stratified by time of day: Daytime and Overnight (6am-12am and 12am-6am CGM readings, respectively) using linear mixed effect regression adjusting for type and order of intervention. Results: We analyzed data from 10 participants (age 58 (10) years, 50% female, 80% Black, BMI: 37.3 (5.4) kg/m2, HbA1c: 5.8 (0.1)%). Weight change over the study period was not significant (p=0.08). Compared to UFP, eTRF was associated with a decrease in TIR140-180 overall (3.3%, p=0.01) and during Daytime (4.3%, p=0.02) but not Overnight (0.4%, p=0.73). We observed no significant differences in TBR<70 (p=0.28) and TIR70-140 (p=0.88) between arms. Conclusion: eTRF may improve glucose control in adults with prediabetes and high BMI by reducing daytime excursions into the elevated 140-180 mg/dL range. Disclosure S. Barua: None. J. Bruno: None. S. Nasserifar: None. S. M. Vanegas: None. C. Popp: None. J. M. Walker: None. J. O. Aleman: Advisory Panel; Intellihealth, Consultant; Novo Nordisk, Employee; Veterans Administration, Research Support; NIH - National Institutes of Health, Veterans Administration. Funding Shapiro-Silverberg Foundation; The Rockefeller University; Doris Duke Charitable Foundation; American Heart Association (17-SFRN33490004); National Institutes of Health (K08DK117064); National Heart, Lung, and Blood Institute (5T32HL098129-12)
Hispanic/Latinos in the U.S. bear an excess burden of type 2 diabetes (T2D) . In type 1 diabetes and insulin-treated T2D, continuous glucose monitoring (CGM) is an established technology to guide therapy, yet CGM use and studies are rare in people with/at-risk of non-insulin treated T2D and ethnic minorities. In this study, CGM was used to assess breakfast glycemic response in free-living adults with or at risk of non-insulin treated T2D. For 9-14 days, 35 Hispanic/Latino adults (28 female, median HbA1c 6.0% [IQR 5.5%, 6.8%]) wore blinded Abbott Freestyle Libre CGM and logged food via the MyFitnessPal app. Start and peak time of glycemic responses associated with a glucose rise ≥20 mg/dL between 5-a.m. were manually annotated. Median variation between annotated and logged time was 39 [20, 78] minutes. Participants were stratified using HbA1c into at risk for T2D, pre-T2D, and T2D. Median starting glucose (SG) ; maximum glucose rise (Max GR) ; time-to-peak (TTP) ; and incremental area under the curve over 2, 3, and 4 hours (iAUC2hr, iAUC3hr, iAUC4hr) were computed (Table 1) . The T2D group had significantly higher post-breakfast glycemic measures than the at-risk group for all measures. The T2D group also had higher measures than pre-T2D for all but Max GR. Increases in response from at-risk to pre- to T2D in Hispanic/Latino adults suggest post-breakfast glycemic profiles may potentially be used to monitor diabetes progression. Disclosure A.Pai: Employee; Apple. R.F.Santiago: Research Support; Abbott. W.C.Bevier: Research Support; Abbott Diabetes. N.M.Glantz: Research Support; Abbott. S.Barua: None. A.Sabharwal: None. D.Kerr: Advisory Panel; Abbott Diabetes, Novo Nordisk A/S, Sanofi, Consultant; Evidation Health, Research Support; Novo Nordisk A/S, Stock/Shareholder; Glooko, Inc., Hi.Health. Funding Elsevier Foundation
Objective: We quantified the association of overall and daytime time in range (TIR, 70-140 mg/dL) with weight change in a behavioral weight loss intervention. Methods: Data for this study came from the Personal Diet Study, a 6-month weight loss trial in adults with prediabetes or moderately controlled T2D (HbA1c<8%) involving remote behavioral counseling and dietary self-monitoring via a smartphone app. Participants wore blinded Abbott Freestyle Libre Pro CGMs for ≤2 weeks at baseline and 6 months. Based on clinically meaningful changes in two TIR metrics: “All-TIR” (all CGM readings) and “Day-TIR” (6am-midnight CGM readings), participants were categorized as “Improved” (>5%), “No Change” (-5 to 5%), or “Declined” (<-5%). Associations between TIR change categories and %weight change were determined using one-way ANOVAs. Results: We analyzed baseline and 6-month CGM data from 66 participants (age 63±8 years, 62% female, 64% White, 20% African American, BMI 31.5±5.0 kg/m2, HbA1c 5.8±0.5%). When stratified by Day-TIR change, Improved had greater weight loss compared to No Change and Declined (p=0.006) (Figure 1). When stratifying using All-TIR, no significant weight change differences were observed across groups (p=0.15). Conclusion: Improved daytime TIR, but not overall TIR, was associated with greater weight loss in a behavioral weight loss intervention. Disclosure S. Barua: None. M. Mottern: None. D. St-jules: Consultant; Ardelyx, Inc. E. Segal: None. M. Bergman: None. J. O. Aleman: Advisory Panel; Intellihealth, Consultant; Novo Nordisk, Employee; Veterans Administration, Research Support; NIH - National Institutes of Health, Veterans Administration. A. Schmidt: None. M. Sevick: None. D. A. Upadhyay: None. C. Popp: None. L. Hu: None. M. Curran: None. L. Berube: None. H. Li: None. C. Wang: None. M. Pompeii: None. Funding American Heart Association (17SFRM33590133)
Physical activity (PA) provides numerous health benefits for individuals with T1D. However, the threat of exercise-induced hypoglycemia may impede the desire for regular PA. We aimed to study the association between three common types of PA (walking, running, and cycling) and hypoglycemia risk in 50 individuals with T1D. Real-world data including characteristics of PA, CGM values, and insulin doses were available from the Tidepool Big Data Donation Project. Participants were aged 38.0 ± 13.1 yrs with 21.4 ± 12.9 yr duration of diabetes and avg 26.2 weeks of CGM data available. We built a linear regression model for each of the three PA types to predict the probability of level 1 hypoglycemia (<70 mg/dL) during the 2 hours after start of PA using the following predictors: PA duration (mins) , PA intensity (calories burned) , 2-hr pre-exercise glucose AUC, glucose value at start of PA, and total bolus insulin within 2 hrs before PA. Regression results are provided in Table 1. Our models indicated that glucose value at the start of exercise (p<0.0for all three activities) and pre-exercise glucose AUC (p<0.0for walking and cycling) were the most significant predictors of hypoglycemia. Duration and intensity of PA and 2-hr bolus insulin were weakly associated with hypoglycemia for certain exercises. These findings may provide T1D individuals with a data-driven approach in preparing for PA that minimizes hypoglycemia risk. Disclosure S.Prasanna: None. S.Barua: None. J.J.Johnson: None. A.F.Siller: None. A.Sabharwal: None. D.Desalvo: Consultant; Dexcom, Inc., Insulet Corporation, Research Support; Insulet Corporation. Funding National Science Foundation (1648451)
Metformin used as adjuvant therapy in youth with T1D and elevated BMI decreased total daily insulin dose (TDID) and insulin resistance, although hemoglobin A1c (A1c) did not change. Yet, the factors that are associated with greater benefit from metformin are not well known. Here, we tested whether baseline measures predict response to metformin in youth with T1D and increased BMI-z score. We analyzed publicly available data from the metformin treatment arm of the T1D Exchange Metformin Study (NCT01881828) , with 61 adolescents (median age 15.3 yrs, range 12-18.9; 36% males; 72% non-Hispanic Whites, 98% overweight or obese; median diabetes duration 7.4 yrs, range 1.7-15) . We assessed baseline age, sex, diabetes duration, race/ethnicity, BMI z-score, waist circumference, body fat percentage (BF%) measured by Dual-energy X-ray Absorptiometry (DXA) scan and serum adipokines. Outcome measures included changes in A1c, TDID and BF% at 13 and 26 weeks (wks) . After adjusting for baseline values, multiple linear regression models were used to identify predictors for the outcomes. Decreases in TDID at 13 and 26 wks showed a significant negative association with baseline leptin (p=0.0008, p=0.004, respectively) . Decreases in BF% at 26 wks were positively associated with baseline BMI z-score (p=0.03) and negatively associated with baseline BF% (p=0.0002) . Increase in A1c at 26 wks trended towards a positive association with baseline BF% (p=0.07) and a negative association with baseline adiponectin (p=0.06) . Compared to females, males showed a significant reduction in BF% at 26 wks (p<0.0001) and a trend towards a reduction in TDID at 13 wks (p=0.06) .In sum, in adolescents with T1D and elevated BMI treated with metformin as adjuvant to insulin, baseline leptin was the strongest predictor of decrease in TDID at 13 and 26 wks. Decrease in BF% was predicted by higher BMI z-score and lower BF% at baseline. These findings may aid a precision medicine approach in this population. Disclosure J.Wang: None. S.Barua: None. M.Tosur: Advisory Panel; Provention Bio, Inc. M.J.Redondo: Advisory Panel; Provention Bio, Inc. H.M.Ismail: n/a.
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