Modeling populations of sleep hypnograms

Bruce J. Swihart, Johns Hopkins School of Public Health
Naresh M. Punjabi, John Hopkins Medical Institution
Ciprian M. Crainiceanu, Bloomberg School of Public Health, Department of Biostatistics, Johns Hopkins


We introduce methods for the analysis of large populations of sleep architectures (hypnograms) that respect the 5-state structure defined by the American Academy of Sleep Medicine. By applying these methods to the hypnograms of 5598 subjects from the Sleep Heart Health Study we: 1) provide an unprecedented high resolution view of the sleep architecture landscape in a community cohort; 2) extend current approaches to multivariate survival data analysis to populations of time-to-transition processes; and 3) provide scalable solutions for data analyses required by the case study. This allows us to provide detailed new insights into the association between sleep apnea and sleep architecture. Supporting R as well as SAS code and data are included in the online supplementary materials.