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Dynamic Associations Between Glucose and Ecological Momentary Cognition in Type 1 Diabetes

Abstract

Type 1 diabetes (T1D) is a chronic condition characterized by glucose fluctuations. Laboratory studies suggest that cognition is reduced when glucose is very low (hypoglycemia) and very high (hyperglycemia). Until recently, technological limitations prevented researchers from understanding how naturally-occurring glucose fluctuations impact cognitive fluctuations. This study leveraged advances in continuous glucose monitoring (CGM) and cognitive ecological momentary assessment (EMA) to characterize dynamic, within-person associations between glucose and cognition in naturalistic environments. Using CGM and EMA, we obtained intensive longitudinal measurements of glucose and cognition (processing speed, sustained attention) in 200 adults with T1D. First, we used hierarchical Bayesian modeling to estimate dynamic, within-person associations between glucose and cognition. Consistent with laboratory studies, we hypothesized that cognitive performance would be reduced at low and high glucose, reflecting cognitive vulnerability to glucose fluctuations. Second, we used data-driven lasso regression to identify clinical characteristics that predicted individual differences in cognitive vulnerability to glucose fluctuations. Large glucose fluctuations were associated with slower and less accurate processing speed, although slight glucose elevations (relative to person-level means) were associated with faster processing speed. Glucose fluctuations were not related to sustained attention. Seven clinical characteristics predicted individual differences in cognitive vulnerability to glucose fluctuations: age, time in hypoglycemia, lifetime severe hypoglycemic events, microvascular complications, glucose variability, fatigue, and neck circumference. Results establish the impact of glucose on processing speed in naturalistic environments, suggest that minimizing glucose fluctuations is important for optimizing processing speed, and identify several clinical characteristics that may exacerbate cognitive vulnerability to glucose fluctuations.

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References
1.
Van Belle T, Coppieters K, von Herrath M . Type 1 diabetes: etiology, immunology, and therapeutic strategies. Physiol Rev. 2011; 91(1):79-118. DOI: 10.1152/physrev.00003.2010. View

2.
McAulay V, Deary I, Sommerfield A, Matthews G, Frier B . Effects of acute hypoglycemia on motivation and cognitive interference in people with type 1 diabetes. J Clin Psychopharmacol. 2006; 26(2):143-51. DOI: 10.1097/01.jcp.0000203202.41947.6d. View

3.
Esterman M, Noonan S, Rosenberg M, DeGutis J . In the zone or zoning out? Tracking behavioral and neural fluctuations during sustained attention. Cereb Cortex. 2012; 23(11):2712-23. DOI: 10.1093/cercor/bhs261. View

4.
Cameron F, Northam E, Ryan C . The effect of type 1 diabetes on the developing brain. Lancet Child Adolesc Health. 2019; 3(6):427-436. DOI: 10.1016/S2352-4642(19)30055-0. View

5.
Axelsson J, Kecklund G, Akerstedt T, DOnofrio P, Lekander M, Ingre M . Sleepiness and performance in response to repeated sleep restriction and subsequent recovery during semi-laboratory conditions. Chronobiol Int. 2008; 25(2):297-308. DOI: 10.1080/07420520802107031. View