Cardiovascular risks and sociodemographic correlates of multidimensional sleep phenotypes in two samples of US adults

Sleep Adv. 2022 Feb 18;3(1):zpac005. doi: 10.1093/sleepadvances/zpac005. eCollection 2022.


Study objectives: Sleep is a modifiable risk factor for cardiovascular conditions. Holistic examination of within-person, multidimensional sleep patterns may offer more detailed information about the sleep-cardiovascular condition link, including who is more vulnerable to both. This study aimed to identify common sleep phenotypes in adulthood, establish the validity of the phenotypes in relation to cardiovascular conditions, and explore sociodemographic and background characteristics of the phenotypes.

Methods: Across two independent samples of adults (N 1 = 4600; N 2 = 2598) from the Midlife in the United States Study, latent class analysis (LCA) extracted sleep phenotypes using five key self-reported sleep dimensions. Log-binomial regression was used to determine whether sleep phenotypes differentially predicted cardiovascular conditions, adjusting for known risk factors. LCA with covariates was used to compare sociodemographic characteristics of the identified sleep phenotypes.

Results: Four sleep phenotypes were identified consistently across the two samples: good sleepers, nappers, dissatisfied/inefficient sleepers, and irregular sleepers. Compared to good sleepers (reference), dissatisfied/inefficient sleepers exhibited a higher risk of cardiovascular conditions in both samples (RR Sample1: 29%, RR Sample2: 53%) and consisted of relatively more racial/ethnic minorities. Nappers exhibited a higher risk of cardiovascular conditions in one sample (RR Sample1: 38%) and consisted of more women and older adults. Irregular sleepers exhibited no significantly different cardiovascular risk and were relatively younger.

Conclusions: Common sleep phenotypes in adulthood exhibit differential risks for cardiovascular conditions. Cooccurring sleep dissatisfaction and inefficiency, in particular, may relate to increased risk of cardiovascular conditions. Certain sociodemographic groups (racial minorities, women, older adults) disproportionately fit within high-risk sleep phenotypes.

Keywords: cluster analysis; heart disease; middle adulthood; sleep health; sleep phenotypes; social disparities.