Photo Credit: Fizkes
Researchers examining sleep patterns observe a varied and complex progression of cardiac deterioration from baseline health to first cardiovascular disease.
The complexity of sleep in terms of varied patterns and clinical impediments creates challenges to quantifying the relationship between disrupted sleep and gauging potential cardiovascular risk. Previous studies examining the correlation between poor sleep and adverse cardiovascular events were generalized and did not incorporate the effects of complex sleep patterns. Most studies instead focused on single adverse sleep events and single adverse cardiovascular events.
Multistate Regression Models
To address this gap in knowledge, Huang Lin, PhD, and colleagues developed a prospective study to observe the associations between individual sleep behaviors and sleep patterns while observing a more varied and complex progression of cardiac deterioration from baseline health to first cardiovascular disease (FCVD) identification to cardiovascular multimorbidity (CVM) to all-cause death. “Multistate regression models, which could simultaneously assess the effect of risk factors on the temporal progression of disease, have been used to optimally understand the complex medical phenomenon,” wrote Dr. Lin and colleagues in an article published in the Journal of the American Heart Association. “Thus, we used a multistate model in our study to improve the understanding of the cause and prognosis of CVDs [cardiovascular disease] and CVMs,” the authors continued.
The researchers identified 381,179 patients from the UK Biobank to include in the study. The participants’ mean age was 56.08±8.08 years, and 56.7% were women. Regarding sleep patterns, the study team classified 18.2% as having healthy sleep, 62.2% as intermediate sleep, and 19.6% as poor sleep.
Sleep behaviors evaluated to determine a participant’s sleep pattern included sleep duration, chronotype, insomnia, snoring, and daytime sleepiness. Dr. Lin and colleagues combined the values of each sleep behavior to quantify sleep patterns in a score ranging from 0, indicating low-risk sleep characteristics, to 5, indicating high-risk sleep characteristics.
Cardiovascular Transitions
In the multistate analyses, the research team examined four cardiovascular transitions in relation to adverse sleep patterns. Related hazard ratios per 1-factor increase sleep scores were 1.14 for baseline to FCVD (95% CI, 1.13–1.15), 1.08 for FCVD to CVM (95% CI, 1.06–1.10), 1.10 for baseline to death (95% CI, 1.08–1.11), and 1.03 for FCVD to death (95% CI, 1.00–1.06). After adjusting the results for socioeconomic characteristics, lifestyle, medical history, and the administration of sleep medications, the associations between sleep patterns and the transition of baseline health to FCVD, from FCVD to CVM, and from baseline health to death remained noteworthy. (Table)
When further categorizing FCVD into specific disease states such as coronary heart disease, stroke, atrial fibrillation (AF), and heart failure (HF), the study results show that adverse sleep patterns have a clear and persistent adverse effect on cardiac health.
“To our knowledge, this is the first prospective study to delineate the associations of overall sleep patterns with the dynamic progression from being free from CHD [coronary heart disease], stroke, AF, and HF at baseline to the first occurrence of CVD, to the occurrence of CVM, and further to mortality using the multistate model,” wrote Dr. Lin and colleagues. “Our findings indicate the importance of improving overall sleep behaviors to slow the progression of CHD, stroke, AF, and HF multimorbidity, and thereby lower mortality.”
