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. 2023 Dec;9(6):968-976.
doi: 10.1016/j.sleh.2023.07.007. Epub 2023 Sep 13.

Association between sleep variability and time in range of glucose levels in patients with type 1 diabetes: Cross-sectional study

Sirimon Reutrakul  1 , Ghada Abu Irsheed  2 , Minsun Park  2 , Alana D Steffen  3 , Larisa Burke  4 , Sarida Pratuangtham  5 , Kelly Glazer Baron  6 , Jennifer Duffecy  7 , Rose Perez  2 , Laurie Quinn  2 , Margaret H Clark Withington  2 , Adam Hussain Saleh  2 , Bernardo Loiacono  2 , Dan Mihailescu  8 , Pamela Martyn-Nemeth  2
Affiliations

Association between sleep variability and time in range of glucose levels in patients with type 1 diabetes: Cross-sectional study

Sirimon Reutrakul et al. Sleep Health. 2023 Dec.

Abstract

Objective: Sleep and circadian disturbances emerge as novel factors influencing glycemic control in type 1 diabetes (T1D). We aimed to explore the associations among sleep, behavioral circadian parameters, self-care, and glycemic parameters in T1D.

Methods: Seventy-six non-shift-working adult T1D patients participated. Blinded 7-day continuous glucose monitoring (CGM) and hemoglobin A1C (A1C) were collected. Percentages of time-in-range (glucose levels 70-180 mg/dL) and glycemic variability (measured by the coefficient of variation [%CV]) were calculated from CGM. Sleep (duration and efficiency) was recorded using 7-day actigraphy. Variability (standard deviation) of midsleep time was used to represent sleep variability. Nonparametric behavioral circadian variables were derived from actigraphy activity recordings. Self-care was measured by diabetes self-management questionnaire-revised. Multiple regression analyses were performed to identify independent predictors of glycemic parameters.

Results: Median (interquartile range) age was 34.0 (27.2, 43.1) years, 48 (63.2%) were female, and median (interquartile range) A1C was 6.8% (6.2, 7.4). Sleep duration, efficiency, and nonparametric behavioral circadian variables were not associated with glycemic parameters. After adjusting for age, sex, insulin delivery mode/CGM use, and ethnicity, each hour increase in sleep variability was associated with 9.64% less time-in-range (B = -9.64, 95% confidence interval [-16.29, -2.99], p ≤ .001). A higher diabetes self-management questionnaire score was an independent predictor of lower A1C (B = -0.18, 95% confidence interval [-0.32, -0.04]).

Conclusion: Greater sleep timing variability is independently associated with less time spent in the desirable glucose range in this T1D cohort. Reducing sleep timing variability could potentially lead to improved metabolic control and should be explored in future research.

Data availability statement: Data are available upon a reasonable request to the corresponding author.

Keywords: Continuous glucose monitor; Glycemic control; Hemoglobin A1C; Sleep; Sleep variability; Time-in-range; Type 1 diabetes.

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Conflict of interest statement

Declaration of conflicts of interest Sirimon Reutrakul: Speaker fee from Eli Lilly. Kelly Baron: Unrestricted research gift, not applicable to this project, from Google and the National Sleep Foundation. Other authors declare no conflict of interest.

Figures

Figure 1:
Figure 1:
Flow of the study.
Figure 2:
Figure 2:
An example of actigraphy recordings (left) and CGM download (right) in two participants. A: a 25-year-old female, using insulin pump with CGM, with a low sleep variability (SD of midsleep time 0.6 h), sleep duration of 7.2 h, and time-in-range of 95%; B: a 24-year-old female, using insulin pump and CGM, with a high sleep variability (SD of midsleep time 1.2 h), sleep duration of 6.7 h, and time-in-range of 36%.
See this image and copyright information in PMC

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References

    1. Holt RIG, DeVries JH, Hess-Fischl A, Hirsch IB, Kirkman MS, Klupa T, et al. The Management of Type 1 Diabetes in Adults. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetes Care. 2021;44(11):2589–625. - PubMed
    1. Mobasseri M, Shirmohammadi M, Amiri T, Vahed N, Hosseini Fard H, Ghojazadeh M. Prevalence and incidence of type 1 diabetes in the world: a systematic review and meta-analysis. Health Promot Perspect. 2020;10(2):98–115. - PMC - PubMed
    1. Foster NC, Beck RW, Miller KM, Clements MA, Rickels MR, DiMeglio LA, et al. State of Type 1 Diabetes Management and Outcomes from the T1D Exchange in 2016–2018. Diabetes Technology & Therapeutics. 2019;21(2):66–72. - PMC - PubMed
    1. DeSalvo DJ, Noor N, Xie C, Corathers SD, Majidi S, McDonough RJ, et al. Patient Demographics and Clinical Outcomes Among Type 1 Diabetes Patients Using Continuous Glucose Monitors: Data From T1D Exchange Real-World Observational Study. Journal of diabetes science and technology. 2021:19322968211049783. - PMC - PubMed
    1. Zhu B, Abu Irsheed GM, Martyn-Nemeth P, Reutrakul S. Type 1 Diabetes, Sleep, and Hypoglycemia. Current diabetes reports. 2021;21(12):55. - PubMed