Meal type and size are the most important factors influencing the accuracy of carb-counting for the control of blood sugar in type 1 diabetes, according to new research presented at the European Association for the Study of Diabetes  Annual Meeting in Barcelona, Spain.

The results highlighted the need for better information to help people with type 1 diabetes improve the accuracy of their carb-counting and reduce the risk of hypoglycemia that can lead to cognitive decline, cardiovascular events, and even death, researchers said.

To investigate which factors affect carb-counting errors most, researchers analysed data on 50 adults with type 1 diabetes from a previously published study of carbohydrate counting accuracy. Over three days, participants estimated the amount of carbohydrate in their meals. To determine participant's carb-counting error, the carbohydrate content of each meal was also calculated by a dietitian.

Type 1 diabetes and errors in carb counting

Researchers then used modelling to identify which patient- and meal-related factors had an effect on carb-counting error. These included a participant's level of education, duration of insulin treatment, age, body weight, meal's carbohydrate, fat, energy, protein, and fibre content, and type of meal (i.e., breakfast, lunch, dinner, or snack).

They found that carbohydrate content and meal type were the most important factors influencing the accuracy of carb counting. Specifically, participants made more carb-counting errors for larger meals (i.e. lunch and dinner), and smaller errors for smaller meals (i.e. breakfast and snacks).

"Glucose control around meal times remains challenging for people with type 1 diabetes. Our findings underscore the need for better information to help patients better estimate the carbohydrate content of their meals", says author Dr Martina Vettoretti from the University of Padova in Italy, where the research was conducted as part of the ongoing European research project Hypo-RESOLVE.

"Once included in type 1 diabetes computer simulations, our model will enable researchers to assess the impact of carb-counting error on blood sugar control and, more in general, to help study behavioural risk factors for hypoglycemia and assess the potential benefits of addressing them."