Poster Presentation Australian and New Zealand Obesity Society Annual Scientific Conference 2024

Exploring the Associations of Glycaemic Variability Indices and Blood Pressure Measures in Adults with Elevated Fasting Glucose (#217)

You Jin Chang 1 2 , Laurent Turner 1 2 , Xiao Tong Teong 1 2 , Lijun Zhao 1 2 , Athena Variji 1 2 , Morag Young 3 , Amy Hutchison 1 2 , Leonie Heilbronn 1 2
  1. Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA, Australia
  2. Lifelong Health Theme, South Australian Health and Medical Research Institute, Adelaide, SA, Australia
  3. Baker Heart and Diabetes Institute, Melbourne, VIC, Australia

Background: High glucose variability is associated with vascular endothelial dysfunction and cardiovascular events.1 Emerging evidence suggests a link between elevated blood glucose levels and increased blood pressure (BP),2 but the effects of glycaemic variability on BP outcomes remain unclear. This study examined associations between glycaemic variability measures and 24-h BP parameters in an at-risk population.

Methods: Seventy-three participants (15 males and 58 females), aged 59±10 years, with an elevated fasting glucose (6.0±0.4 mmol/L), and overweight/obesity (BMI 32.9±4.5 kg/m2) underwent a 2-week continuous glucose monitoring (FreeStyle Libre Pro) protocol, before attending a 26-h overnight visit from ~7 a.m.. During the visit, participants were fitted with a 24-hour ambulatory BP monitor (OnTrak) from ~ 7:45 a.m.,and were provided with three identical meals at 8 a.m., 2 p.m. and 8 p.m.. Multiple regression analysis with adjustment for age, sex, and fat mass was performed to evaluate the association between glucose variability [mean amplitude of glycaemic excursions (MAGE), mean of daily glucose differences (MODD)] with BP parameters [24-hour mean pulse pressure, systolic BP (SBP), diastolic BP (DBP), heart rate, and mean arterial pressure (MAP) and nocturnal SBP and DBP dipping].

Results: MAGE statistically significantly predicted MAP in both unadjusted (B = 3.21, p = 0.04) and adjusted (B = 3.11, p = 0.05) models, and pulse pressure (B = 4.82, p = 0.04) and heart rate (B = 2.72, p = 0.05) in the adjusted model. No other statistically significant associations were found between MAGE, or MODD and BP parameters.

Conclusions: In this at-risk population, MAGE independently correlated with higher MAP, pulse pressure, and heart rate. Further research is warranted to explore the relationship between glycaemic excursions and BP parameters in people at risk of type 2 diabetes. Understanding this relationship underscores the importance of minimising glycaemic variability to mitigate risk of hypertension-related complications.

  1. Martinez M, Santamarina J, Pavesi A, Musso C, Umpierrez GE. Glycemic variability and cardiovascular disease in patients with type 2 diabetes. BMJ Open Diabetes Research & Care. 2021;9(1):e002032.
  2. Yan Q, Sun D, Li X, Chen G, Zheng Q, Li L, et al. Association of blood glucose level and hypertension in Elderly Chinese Subjects: a community based study. BMC Endocr Disord. 2016;16(1):40.