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.

1 型糖尿病 (T1D) 是一种以血糖波动为特征的慢性疾病。实验室研究表明，当血糖非常低（低血糖）和非常高（高血糖）时，认知能力会降低。直到最近，技术限制使研究人员无法了解自然发生的葡萄糖波动如何影响认知波动。这项研究利用连续血糖监测 (CGM) 和认知生态瞬时评估 (EMA) 的进步来表征自然环境中血糖与认知之间的动态、人体内关联。使用 CGM 和 EMA，我们对 200 名 1 型糖尿病成人进行了血糖和认知（处理速度、持续注意力）的密集纵向测量。首先，我们使用分层贝叶斯模型来估计葡萄糖和认知之间的动态、人体内关联。与实验室研究一致，我们假设认知能力在低血糖和高血糖下都会降低，反映了认知对血糖波动的脆弱性。其次，我们使用数据驱动的套索回归来识别临床特征，这些特征可以预测血糖波动认知脆弱性的个体差异。较大的葡萄糖波动与较慢且不太准确的处理速度相关，尽管轻微的葡萄糖升高（相对于个人水平的平均值）与较快的处理速度相关。血糖波动与持续注意力无关。七个临床特征预测了对血糖波动的认知脆弱性的个体差异：年龄、低血糖时间、终生严重低血糖事件、微血管并发症、血糖变异性、疲劳和颈围。结果确定了自然环境中葡萄糖对处理速度的影响，表明最小化葡萄糖波动对于优化处理速度很重要，并确定了可能加剧葡萄糖波动认知脆弱性的几种临床特征。