Network analysis to identify interconnections between smartwatch-based lifestyle biomarkers and glycated haemoglobin (HbA1c)

Network analysis was used to investigate the interrelationships among 23 digital biomarkers characterizing lifestyle activity (derived from a smartwatch) and glycated haemoglobin (HbA1c) values over 18 months in 61 Type 2 diabetes patients with several comorbidities (hypertension, ischaemic heart disease, chronic kidney disease and chronic obstructive pulmonary disease) and who were taking 11 types of medications. Five lifestyle data categories—sleep, sleep stages, step daily counts, exercise, and heart rate—were analysed and included in the networks. The findings from this research not only reinforce those of previous studies but also suggest that the relationship between lifestyle and HbA1c depends not only on the type of comorbidity or medication but also on specific lifestyle behaviours. For example, frequent deep sleep is strongly correlated with a reduction in HbA1c levels on subsequent days. The evaluation of the centrality measures provides new insights into the relative importance of individual lifestyle characteristics within various networks that can be considered targets for HbA1c interventions.