Integrating Mobile Health Technology into Sleep Research and Environmental Epidemiology

Abstract

Sleep is fundamental to human health. In aspects of both duration and quality, the majority of adults in the United States suffer from suboptimal sleep. During sleep and during wake, through the simultaneous presence of sensory stimuli, neighborhood-level contextual factors, and structural forces that inform our movement through a city, our environments affect our sleep. Sleep is an outcome that individuals experience on a daily basis and environmental exposures are ubiquitous; therefore, interrogations of the relationship between sleep and environment can be highly impactful for advancing public health. Using sleep data collected in the prospective cohort of the Nurses’ Health Study 3, this dissertation explores how mobile health technologies like consumer wearable sleep trackers and smartphone global positioning systems (GPS), as well as exposome-based approaches that aim to capture an individual’s environmental exposures more comprehensively, can increase the depth of insights from sleep research and environmental epidemiology. In Chapter 2, we quantified differences in sleep measurement between a consumer wearable and a research-grade accelerometer in free-living adults. We observed modest differences in measurement of total sleep time, time in bed, and sleep efficiency between the consumer wearable (Fitbit) and research-standard actigraphy. In Chapter 3, we examined the association between daily GPS-derived walkability exposure and consumer wearable-measured sleep. We did not observe an association between walkability and sleep duration or sleep efficiency. In Chapter 4, we investigated the associations of multiple environmental exposures assessed at the residential address, including greenness, light at night, noise, neighborhood socioeconomic status (SES), and walkability, with self-reported sleep duration and quality. We observed consistent associations between higher neighborhood SES and reduced odds of adverse sleep health outcomes. We also observed protective associations for light at night, and harmful associations for noise and greenness. With these three dissertation aims, we examined how measurement tools, study design, and exposure assessment approaches can be improved to advance studies of sleep and the environment. We first demonstrated viability for consumer wearables in epidemiologic studies. Then, we illustrated how they can be embedded into a population-level study alongside smartphone GPS to study an environmental exposure, walkability. Finally, we expanded the range of exposures studied with sleep and identified neighborhood SES as a key environmental contextual factor impacting sleep health in the US. Together, this body of work contributes to our understanding of how modifiable environmental exposures can be leveraged to improve sleep on a population-level.Population Health Science