Wearable gadgets are used by nearly a third of the world’s population on a daily basis to track activity, food intake, and sleep. Others monitor blood sugar, blood pressure, heart rate variability, and weight. Technological advances have made continuous 24 hour recording of real-time data accessible for health researchers. Wearable sensors yield complex data that are high frequency (sampling precision up to thousands per second), high dimensional (many different sensors capture multiple forms of data simultaneously), and high volume (copious quantities of big data). Yet, while researchers are well versed in advanced statistical modeling, simplistic data reduction with 24-hour data prevails. Overaggregation of time series repeated measurements, across time and days, masks underlying chronobiological rhythms. Alternative methods for identifying and quantifying circadian rhythmicity preserve salient nuances of continuously recorded time series data. Wearable devices offer great potential for accurate assessment of sleep, which is critical to better understand and evaluate its role in health and disease.
Sleep timing and sleep duration have changed dramatically over the past several decades. We now live in a 24-hour society with greater nighttime access to technology, exposure to artificial light at bedtime, and inconsistency in routines. In turn, this “social jetlag” disrupts the pattern of alignment between the external light-dark cycle and the internal clock, leading to circadian misalignment. Furthermore, the internal clock that regulates these rhythms is dynamic across the lifecourse: rhythmic activities such as sleep/wake patterns change markedly as we age. Changes in sleep timing, sleep architecture, and circadian rhythm are evident across infancy, childhood, adolescence, adulthood, and older adulthood - key developmental periods in the lifespan. Consider, phase delay during adolescence and phase advance during older adulthood are developmentally “normal”; these changes are ubiquitous across cultures and mammalian species. Adolescents tend to go to bed later and compensate for social jetlag and sleep debt accumulated over the school week, by oversleeping on weekends. In contrast, later in life, older people become sleepier earlier in the evening and wake earlier in the morning. The reason for these changes in sleep and circadian rhythms as we age is not clearly understood.
Researchers posit that developmental changes in sleep may influence the propensity for age-dependent diseases and susceptibility to chronic diseases, including diabetes, cardiovascular disease, and cancer. Circadian rhythms are important during each lifestage for the regulation of processes that may influence the development of these disorders. Changes in sleep and alterations in circadian timing over the lifespan impact a wide variety of physiological systems, including those that play an important role modulating weight, metabolism, inflammation, and cardiovascular functioning. Circadian misalignment is the consequence of desynchronization, or alterations in the timing and rhythm of the physiological cycles, that in turn, superimpose incompatible biochemical processes. Experimentally induced short-term circadian misalignment increases blood pressure and inflammatory markers in adults. Shift workers, who frequently undergo circadian misalignment, are at greater risk for hypertension, inflammation, and cardiovascular disease, even after accounting for traditional risk factors. Much of the research evidence is correlational; yet, intriguing questions have been raised about the plausible causal relations linking sleep, circadian misalignment, and cardiometabolic disorders. Ultimately, wearable sleep technology holds promise for advancing our understanding of sleep changes across the lifecourse and may lead to new knowledge about the mechanisms underlying cardiometabolic health to inform successful prevention targets.
Dr. Jennifer J. McGrath is a Professor at Concordia University and the inaugural PERFORM Chair in Childhood Preventive Health and Data Science. Her innovative, interdisciplinary approach to untangling social determinants of child health inequalities has led to new discoveries about the pathophysiology of cardiovascular disease precursors, and their socioeconomic gradient, during childhood and adolescence. Her research spans pathways-to-policy and is at the intersection of psychophysiology, child clinical psychology, behavioral medicine, and epidemiology. She has made compelling insights into childhood stress; pediatric sleep; autonomic and endocrine dysregulation; and, airborne nicotine and smoking initiation. She has also pioneered rigorous pediatric ambulatory measurement standards for wearables and advocates for reproducibility of science through open-source data science methods. Dr. McGrath is a member of the Clinical Psychology Training program and teaches courses in childhood assessment, intellectual and cognitive assessment, psychophysiology, and statistics. Her research has been continuously funded by CIHR since 2005, with over $17M in total funding. She has held numerous awards in recognition for her work and serves as an elected member of the CIHR University Delegate Advisory Committee.