Menstrual Cycle × Glucose Variability in Type 1 Diabetes

In the realm of diabetes management, women living with type 1 diabetes (T1D) face an additional challenge that remains largely underappreciated: the hormonal fluctuations of the menstrual cycle and their impact on blood glucose control. While insulin therapy and modern technologies such as continuous glucose monitoring (CGM) and automated insulin delivery (AID) systems have transformed diabetes care, they often overlook the unique physiological rhythms that shape glycemic variability in women.

During the menstrual cycle, shifts in estrogen and progesterone levels influence insulin sensitivity and glucose metabolism. Evidence from clinical studies and real-world CGM data has shown that many women experience higher glucose levels and increased insulin needs in the luteal phase of the cycle, while some also report a greater risk of hypoglycemia during exercise in specific phases. These fluctuations complicate insulin dosing and daily management, and yet current diabetes guidelines and most closed-loop systems remain cycle-blind, failing to provide tailored adjustments.

This oversight has important implications. Women with T1D may struggle with unexplained glycemic swings, higher time above range, or even rare but critical events such as catamenial diabetic ketoacidosis (DKA). Clinicians, meanwhile, often attribute morning highs to general phenomena like the “Dawn effect” without considering that some of these may represent luteal-phase–specific Somogyi rebounds triggered by nocturnal hypoglycemia. The result is that cycle-phase dynamics remain an unmet need in diabetes care, leaving women to shoulder the additional burden of pattern recognition and manual adjustments.

Against this backdrop, the Menstrual Cycle × Glucose Research Initiative within DiabetesDAO seeks to advance our understanding of cycle-phase impacts on glucose dynamics. Through systematic literature reviews, CGM studies, exercise physiology investigations, and ongoing large-scale projects, we aim to quantify how insulin sensitivity, glucose variability, and clinical outcomes differ across menstrual phases. Building on this evidence base, we are developing research hypotheses, such as progesterone-driven reductions in insulin sensitivity via GLUT4 modulation or phase-specific differences in exercise-related hypoglycemia risk and proposing study protocols to validate them in real-world populations.

The ultimate vision is to translate these insights into cycle-aware algorithms, clinical guidelines, and digital tools that empower women to anticipate and manage predictable glucose shifts. By integrating menstrual cycle dynamics into diabetes technology and care pathways, we can move closer to truly hyper-personalized management, reducing frustration, improving safety, and giving women with T1D better control over their health.