A composite measure of sleep health is associated with glycaemic target achievement in young adults with type 1 diabetes

Abstract

We investigated whether sleep health (each individual dimension and a composite measure) was associated with better glycaemia among a cohort of young adults with type 1 diabetes (mean age 21.5 years, mean body mass index 24.55 kg m À2 ). Multiple validated self-report questionnaires were completed, and raw continuous glucose monitor data were shared. One self-reported sleep characteristic for each of the five sleep health dimensions was selected. A composite score was calculated by summing the number of "good" sleep health dimensions. We evaluated the associations between sleep health and glycaemia, and whether covariates, including age, type 1 diabetes duration and sleep apnea risk, influenced the relationships among the study variables using multivariable linear regression. Individual dimensions of sleep satisfaction (β = 0.380, p = 0.019; β = À0.414, p = 0.010), timing (β = 0.392, p = 0.015; β = À0.393, p = 0.015) and sleep efficiency (β = 0.428, p = 0.007) were associated with higher achievement of glycaemic targets (J-index and time in range); however, these associations did not persist after considering covariates. A better Sleep Health Composite score was associated with higher achievement of glycaemic targets even after considering covariates. Using a multidimensional framework can guide future research on causal pathways between sleep and diabetes health, interventions to target sleep health profiles, and may improve sleep screening in routine diabetes care.

Recent Progress in Long-Term Sleep Monitoring Technology

“…For example, blood drug concentration detection using electrochemistry [ 215 ], wearable continuous glucose monitoring [ 216 ], etc. These devices can also be used while sleeping, and there have been reports about them [ 217 ]. In this paper, we focus on three biochemical assays that are closely related to sleep, shown in Figure 16 .…”