A good night's rest: A contemporary review of sleep and cardiovascular health

Abstract

Sleep is increasingly recognized as a significant contributor to the development of cardiovascular disease (CVD). Recent American Heart Association guidelines incorporate sleep duration into the “Life's Essential Eight” framework of ideal cardiovascular health. This article will review the evidence relating sleep duration, regularity, and quality with all-cause and cardiovascular mortality, cardiometabolic syndrome, and coronary artery disease in adults. Short sleep duration is strongly associated with cardiovascular mortality, cardiometabolic risk factors, and coronary artery disease. Limited studies also suggest a possible U-shaped association, with long sleep duration also associated with greater cardiovascular risk. Sleep regularity has emerged as a strong and independent risk factor for CVD-related mortality, cardiometabolic syndrome, and subclinical atherosclerosis. Less is known about the impact of sleep quality on CVD, though a number of observational studies suggest a possible association with metabolic syndrome and subclinical atherosclerosis. This review provides an update of the literature on the cardiovascular impact of sleep for the everyday clinician and highlights gaps in knowledge that warrant future research.

1. Introduction

Sleep is a foundational element of human biology with wide-ranging implications across multiple physiologic systems in the body [1]. Numerous epidemiological studies have demonstrated an association between poor sleep health and all-cause mortality [[2], [3], [4]]. In the past two decades, there has been a consistent and growing body of literature linking adverse sleep health to heightened risk of cardiovascular disease (CVD) and CVD-related mortality [5]. In response to mounting evidence highlighting the independent association between sleep and cardiovascular health, the American Heart Association (AHA) recently added sleep duration as a part of its “Life's Essential 8′' framework of ideal cardiovascular health, along with a formal recommendation that adults aim for an average 7–9 h of sleep per night [6].

Though much of the existing literature on sleep health has focused on average sleep duration, there is growing recognition that sleep is a multi-dimensional construct with overlapping components [7]. Recent studies have found that metrics such as sleep regularity and sleep quality add independent predictive value for CVD in addition to sleep duration [8]. Within the field of preventive cardiology, there is increasing interest in addressing sleep as a modifiable behavioral risk factor, akin to smoking, diet, or physical activity [9].

In this review, we summarize existing evidence on the relationship between sleep and cardiovascular health and highlight directions for future research. Specifically, we synthesize the evidence linking various dimensions of sleep with all-cause and cardiovascular mortality, cardiometabolic disease, and atherosclerotic disease in adults.

2. Defining sleep health

There is no universally agreed upon definition for sleep health [7]. The vast majority of sleep research has focused on sleep duration in isolation. However, more recent studies have shed light on the independent contribution of sleep regularity, quality, and architecture on overall health and wellbeing. Here, we review definitions for common metrics used in sleep research (Table 1).

Table 1.

Common metrics used in sleep research.

	Common metrics	Definition
Duration	Sleep Duration	Total sleep time between sleep onset and offset
Regularity	Sleep Duration Regularity	Intra-individual standard deviation of nightly total sleep time
	Sleep Onset Regularity	Intra-individual standard deviation of nightly total sleep timing onset
	Sleep Regularity Index	Probability of an individual being in the same sleep state (awake vs asleep) at any two time points 24 h apart
Quality	Wake after sleep onset (WASO) time	Total amount of time spent awake after sleep onset and before sleep offset
	Sleep Efficiency	Percentage of time spent asleep between sleep onset and sleep offset
	Number of nightly awakenings	Number of nightly episodes in which an individual is awake for > 5 min
	Sleep onset latency (SOL)	Total time it takes to transition from wake to sleep
	Sleep Fragmentation Index	Measure of sleep continuity and estimates disruption in sleep throughout the sleep period

Sleep duration is commonly defined as total sleep time measured either overnight or over a 24-hour period and is frequently averaged over a period of time. Earlier studies primarily relied on self-reported sleep duration, which has been shown to overestimate objective measurements of sleep duration [10]. More recent studies have moved towards objective assessment of sleep using wearable wrist actigraphy devices and polysomnography (PSG). Survey data from the National Health Interview Survey (NHIS) showed that over one-third of U.S. adults average less than the optimal 7–9 h of nightly sleep recommended by the AHA, with significant variation observed by age, sex, race, and socioeconomic status [11].

Sleep regularity is a rapidly emerging area of interest. Studies have examined both sleep duration regularity, defined the night-to-night variability in sleep duration, as well as sleep timing regularity, measured as night-to-night variability in sleep onset or midpoint. Both sleep duration and timing regularity are frequently reported as the standard deviation of sleep duration or timing onset over a period of time. The sleep regularity index (SRI) metric was developed specifically to assess circadian disruption. Compared to more standard indices of sleep regularity, which only tend to assess a single dimension (e.g. sleep duration variability), SRI takes into account irregularity due to a combination of fragmented sleep, variable onset, offset, duration, and daytime napping and is thus thought to be a more comprehensive measure of circadian disruption. Regardless of metric used, assessment of sleep regularity requires assessment of sleep timing and duration across multiple nights and is often quantified by use of wrist actigraphy over a period of time. There are no population level descriptive statistics available on sleep regularity in healthy adults, though studies have found that sleep onset regularity >90 min and sleep duration regularity >120 min confer a greater risk for metabolic syndrome and CVD events [12].

Sleep quality is a broad term that has been inconsistently defined in the literature. In some studies, it has been operationalized as self-reported sleep satisfaction, or subjective report of feeling well-rested. With the advent of wearable digital health devices, recent studies have examined metrics such as sleep efficiency, wake after sleep onset time (WASO), number of nightly awakenings, and sleep fragmentation. The Sleep Fragmentation Index is a measure of sleep continuity and estimates disruption in sleep throughout the sleep period [13]. While there are no high-quality population level statistics available on sleep quality, NHIS data showed that 14.5 % of adults reported trouble falling asleep and 17.8 % of adults reported trouble staying asleep, suggesting a high prevalence of poor sleep quality [14]. According to the National Sleep Foundation, good quality sleep is characterized by sleep onset latency <15 min, one or fewer nightly awakenings, ≤20 min of wake after sleep onset time, and sleep efficiency ≥85 % (Fig. 1).

Fig. 1.

Association between sleep and cardiovascular disease.

While many studies have examined the independent association between the sleep metrics described above and CVD, there has also been growing interest in capturing the complex interactions between a multitude of sleep metrics into a single framework. In the AHA's Life's Essential Eight framework, sleep is scored only based on sleep duration, excluding other informative dimensions of sleep and failing to capture the complex interactions between these metrics. Some studies have operationalized a “sleep score” or leveraged techniques such as principal component analysis to capture several sleep metrics—including sleep duration, regularity, and multiple measures of sleep quality—into a single variable [15,16]. However, there is not yet consensus on the approach to incorporate multiple dimensions of sleep into a single framework [7].

3. All-Cause and cardiovascular mortality

Individuals with more favorable sleep across multiple sleep metrics, including duration, regularity, and quality, have been associated with lower all-cause and CVD-related mortality rates. Both short (<7 h) and long (>9 h) sleep have consistently been shown to be significant predictors of all-cause and CVD-related mortality across multiple, diverse cohorts [[2], [3], [4],17]. In a cohort of 2846 patients with known obstructive CAD enrolled in the Emory Cardiovascular Biobank, both short and long sleep duration was associated with increased all-cause mortality, but only short sleep duration was independently associated with higher cardiovascular mortality [18].

Recently, sleep regularity has been shown to be a stronger predictor of all-cause mortality risk compared to sleep duration in a large, prospective cohort of UK Biobank participants. Participants with a high SRI (indicating more regular sleep) had a 20–48 % lower risk of mortality compared to those with low SRI, with the largest reduction of risk seen in the cardiometabolic mortality subgroup [8]. In the Multi-Ethnic Study of Atherosclerosis (MESA) sleep study, which used objective measures of sleep collected by 7-day wrist actigraphy, participants were grouped into “regular-optimal” and “irregular-insufficient” sleep phenotypes based on sleep duration and regularity. The “regular-optimal” sleep pattern was associated with a 39 % lower mortality hazard compared to the “irregular-insufficient” group after adjustment for relevant covariates [19]. Data from the same study used a composite sleep score integrating multiple facets of sleep—including duration, regularity, quality, and sleep architecture—using principal component analysis found that higher composite sleep score was associated with 25 % lower hazard of mortality (HR 0.75, 95 % CI 0.65–0.75) after adjustment [15]. Of all sleep measures included in the composite sleep score, short sleep duration and greater sleep irregularity were most strongly associated with mortality.

A study of 1920 adults in the MESA sleep study reported that incorporating sleep as the eighth component of the original AHA “Life's Simple Seven” (LS7) score enhances prognostic information for incidence of CVD [9]. Another study of 2888 adults included in the Framingham Heart Study (FHS) found that while impaired sleep was independently associated with higher risk of CVD and death when added to LS7, there was no significant change in the C-statistic for models evaluating CVD and death [20]. One key difference between the two studies is that the MESA sleep study used objectively measured sleep duration with wrist actigraphy, while FHS relied on self-reported sleep duration.

4. Cardiometabolic disease

There is an abundance of epidemiological and observational data demonstrating the association between sleep and cardiometabolic disease. Metabolic syndrome (MetS) refers to a constellation of interrelated risk factors which compound to lead to a heightened risk of cardiovascular and other chronic diseases. According to the National Cholesterol Education Program Adult Treatment III criteria, the components of metabolic syndrome include increased triglycerides (TG), decreased high-density lipoprotein cholesterol (HDL), increased blood pressure (BP), increased central adiposity, and increased fasting glucose [21].

4.1. Sleep duration

Findings from 36 cross-sectional studies and 9 longitudinal studies assessing self-reported sleep duration and metabolic syndrome found a significant relationship between both short sleep duration (OR = 1.11, 95 % CI = 1.05–1.18) and long sleep duration (OR = 1.14, 95 % CI = 1.05–1.23) with prevalent MetS. However, only short sleep duration was associated with incident MetS (RR = 1.28, 95 % CI = 1.07–1.53) in prospective analyses [22]. This U-shaped relationship between sleep duration and MetS has been consistently reproduced in multiple large cohort studies and meta-analyses [[23], [24], [25]]. Self-reported short sleep duration has further been associated with increased risk of hypertension [26,27], obesity [28], type 2 diabetes or impaired glucose control [29], and dyslipidemia[30] in cross-sectional, observational studies. In a series of dose-response meta-analyses restricted to only prospective studies assessing incident risk of disease, there was a “U-shaped” relationship between sleep duration and incident type 2 diabetes[31] and a 9 % increased risk of obesity with each one hour of sleep less than 7 h [32].

4.2. Sleep regularity

In the Multi-Ethnic Study of Atherosclerosis (MESA) Sleep Ancillary Study of ∼2000 older adults, high night-to-night variability in both sleep duration and sleep onset timing, assessed from 7 days of wrist actigraphy, was associated with higher risk of cardiometabolic abnormalities after adjustment for sociodemographic, lifestyle, and sleep-related factors such as sleep duration [33]. In cross-sectional analyses, every one hour increase in sleep duration variability was associated with 27 % higher odds of having MetS and every one hour increase in sleep onset variability was associated with 23 % higher odds of MetS. Those with sleep onset standard deviation >90 min had 45 % higher odds of MetS. In prospective analysis of the same cohort, every one hour increase in sleep onset standard deviation was associated with 36 % higher risk of developing MetS. Notably, the associations between increased sleep onset variability persisted even after adjusting for average total sleep duration and in analyses restricted to sleep variability measured only during weekdays. Based on the same sample from the MESA Sleep ancillary study, Lunsford-Avery et al. recently validated the Sleep Regularity Index, which was cross-sectionally associated with obesity, hypertension, diabetes, and 10-year risk for incident CVD [34]. This finding has been consistent across various cohorts examining the association between sleep variability with individual components of MetS, including fasting glucose, hypertension, obesity, and dyslipidemia [[35], [36], [37], [38], [39]].

4.3. Sleep quality

A systematic review of 16 observational studies involving 20,153 participants examining the relationship between the overall sleep quality and MetS showed that overall sleep quality had a significant positive association with MetS (OR 1.37, 95 % CI 1.15–1.64) though with significant between-study heterogeneity [40]. The same study demonstrated a significant association between both difficulty falling sleep and maintaining sleep with MetS. In contrast to sleep duration and regularity, none of these studies were prospective and all relied on self-reported sleep quality. Findings pooled across 13 independent cohort samples showed that quality of sleep predicted the risk of development of type 2 diabetes. For difficulty in initiating sleep, the RR was 1.57 (95 % CI = 1.25–1.97); and for difficulty in maintaining sleep, the RR was 1.84 (95 % CI = 1.39–2.43) [29]. In one clinical trial which used wrist actigraphy to assess sleep quality, poor sleep efficiency was found to be associated with more pronounced postprandial glycemic responses to breakfast the following morning [41].

5. Atherosclerotic cardiovascular disease

There is a consistent line of cross-sectional and prospective evidence to suggest that adults with abnormal sleep characteristics are at greater risk for atherosclerotic cardiovascular disease (ASCVD), including coronary artery disease (CAD), myocardial infarction (MI), stroke, peripheral artery disease (PAD), and subclinical atherosclerosis. This data exists across multiple dimensions of sleep health, including duration, regularity, and quality. In the MESA cohort, cardiovascular health scores that included sleep duration or a measure of multidimensional sleep health, in addition to the health factors and behaviors included in the Life's Simple 7, were associated with incident ASCVD [9].

5.1. Sleep duration

Both cross-sectional survey data and prospective observational data support a “U-shaped” association between sleep duration and CAD, with greater prevalence seen at the extremes of sleep duration. A survey of a large, representative sample of U.S. adults with self-reported sleep duration found that both short and long sleep durations were positively associated with CAD in a dose-dependent fashion [42]. Similarly, a cross-sectional analysis of the 2007–2008 National Health and Nutrition Examination Survey (NHANES) found that short sleep duration (< 6 h) was associated with higher prevalence of myocardial infarction and long sleep duration (> 8 h) with higher prevalence CAD [43]. This “U-shaped” association between sleep duration and CAD has been replicated in multiple prospective cohort studies, with pooled meta-analysis showing increased risk of developing CAD with some heterogeneity among studies, no presence of publication bias, high statistical power, no difference between men and women, or duration of follow-up [44,45].

More recent studies have established a link between sleep duration and subclinical atherosclerosis, though notably there are mixed findings which may be attributable to some studies relying on objective sleep assessment and others subjective [46]. In the Chicago cohort of the CARDIA study, short duration of sleep measured by actigraphy was associated with a greater 5-year incidence of coronary artery calcifications (CAC) measured by computed tomography [47]. In the Progression of Early Subclinical Atherosclerosis (PESA) Study which included 3974 participants with objectively measured sleep metrics, very low sleep duration (<6 h) was associated with a higher burden of non-coronary atherosclerosis (as measured by carotid and femoral ultrasound) and a higher number of vascular territories affected [48]. No association between sleep duration and coronary artery calcium (CAC) was found in this cohort. In the Aragon Workers' Health Study (AWHS), cross-sectional analysis of 1968 men there was a U-shaped association between self-reported sleep duration and CAC and no significant association identified with femoral or carotid plaque [49].

5.2. Sleep regularity

Irregular sleep has been shown to be associated with prevalent and incident ASCVD. Early studies indirectly evaluating circadian disruption have suggested that irregular sleep confers an increased risk of ASCVD. There is a well-documented increase in myocardial infarction and stroke in days after shifting to daylights saving time [50]. Prospective studies of shift workers have noted a statistically significant increase in the development of coronary artery disease [[51], [52], [53]]. In the MESA Sleep Study, sleep regularity was assessed using the SD of wrist actigraphy measured sleep duration and sleep onset-timing over 7 days. Through a median follow up of 4.9 years, both sleep duration SD and sleep onset SD were associated with increased risk of developing atherosclerotic CVD (driven primarily by myocardial infarction and stroke) events in a dose-dependent fashion [54].

Results from MESA also support an association between sleep regularity and several markers of subclinical atherosclerosis. Participants with greater sleep duration irregularity (>120 min) were more likely to have high coronary artery calcium burden (>300 Agatston units) and abnormal ankle-brachial index. Those with less regular sleep timing onset were more likely to have greater coronary artery calcium burden [55].

5.3. Sleep quality

Less is known about the relationship between sleep quality and CAD. In Italian men, the presence of self-reported severe sleep disturbances (difficulty falling and remaining asleep, daytime sleepiness) was associated with 80 % higher risk of CVD, particularly from age 48 years onward [56]. Other studies have focused on sleep quality and subclinical atherosclerosis. A systematic review found that poor objective sleep quality was significantly associated with carotid intima-media thickness and endothelial dysfunction (as measured by flow-mediated dilation) but not CAC. In the PESA Study, sleep quality was assessed by the sleep fragmentation index. Participants with the most fragmented sleep had the highest risk of multiple affected non-coronary territories compared with the reference group with the least fragmented sleep (OR 1.34, 95 % CI 1.09–1.64). Similar to sleep duration, no association was identified between sleep fragmentation and CAC in this cohort [48].

6. Evidence-based interventions to improve sleep

In light of growing evidence linking sleep with cardiovascular health, there has been significant interest in identifying evidence-based interventions to improve sleep health. The American Academy of Sleep Medicine (AASM) provides the following tips on healthy sleep habits: keeping a consistent sleep schedule, allowing for at least 7 h of sleep nightly, using bedroom for only sleep, maintaining regular exercise, keeping the bedroom dark (with use of blackout curtains or eye mask to block out any light if necessary) and at a cool temperature (between 60° and 68° Fahrenheit), limiting exposure to electronic devices at least 30 min prior to bedtime, and avoiding caffeine, alcohol, and excessive fluid intake prior to bedtime. Caffeine and alcohol intake during evening hours have been shown to reduce sleep duration, increase sleep onset latency, and reduce sleep quality [57,58]. Screen use has been shown to impair sleep health among children and adolescents, although there is not yet strong evidence for adults [59]. Despite evidence linking individual components of sleep hygiene with poor sleep health, there has been a paucity of evidence demonstrating the impact of sleep hygiene recommendations on improving sleep health [60].

For patients who meet criteria for a chronic insomnia disorder, cognitive behavioral therapy for insomnia (CBT-I) has been shown to be an evidence-based method when administered by a trained CBT-I professional and is strongly recommended by AASM for the treatment of chronic insomnia disorders as the standard of treatment [61]. Pharmacologic treatments exist for the treatment of insomnia disorders, including orexin receptor agonists (e.g. suvorexant), benzodiazepine receptor agonists (e.g. zolpidem, eszopiclone), and melatonin agonists (e.g. ramelteon). However, these treatments have limited evidence and carry only a weak recommendation from AASM [62]. For patients meeting criteria for circadian-rhythm disorders, timed light exposure and timed melatonin administration are evidence-based treatments endorsed by AASM [63].

The advent of digital health is changing the landscape of sleep medicine. In particular, wrist actigraphy offers the ability to objectively assess sleep duration, regularity, and quality and offer real-time feedback. Until recently, the role of actigraphy was limited to sleep research, however in 2018 the AASM updated its guidelines to acknowledge the potential benefits of actigraphy for the diagnostic evaluation of insomnia and circadian rhythm disorders [64]. Furthermore, a large number of consumer wearable devices now offer sleep monitoring capabilities. However, not all devices use an accelerometer validated for the identification of sleep-wake periods. As this technology improves over time, there may be a role to use consumer wearable technologies as an adjunct to aid in the diagnosis and treatment of sleep disorders [65].

7. Implications for the preventive cardiologist

What are the implications of the growing body of evidence linking suboptimal sleep with elevated cardiovascular risk? Currently, there are no standardized guidelines indicating how cardiologists should screen for sleep disorders or when to refer to a sleep specialist. In contrast, screening for obstructive sleep apnea has rapidly become a routine component of preventive cardiology [66], with increasing levels of comfort in referring patients for polysomnography, home sleep testing, and subsequently to a sleep medicine specialist for treatment of OSA. In response to the growing importance of sleep as a modifiable sleep factor, preventive cardiologists should expand lifestyle counseling to include emphasis on the importance of sleep health. This may include inquiring about average sleep duration as a part of comprehensive lifestyle assessment, providing patients with evidence-based information about healthy sleep habits developed by the AHA [67], and identifying patients likely to benefit from a referral for a more comprehensive sleep disorder evaluation (Fig. 2). In particular, cardiologists may benefit from using validated screening tools such as the Epworth Sleepiness Scale, which involves asking the likelihood of dozing off or falling asleep during routine activities such as watching television or sitting in a meeting. Finally, sleep regularity may be assessed by asking the patient how often they are going to bed around the same time each evening and waking up around the same time each morning.

Fig. 2.

Incorporating sleep health into preventive cardiology visits.

8. Call to action

Optimal sleep may play a crucial role in preserving cardiovascular health. Despite overwhelming evidence suggesting an association between multiple dimensions of sleep and incident CVD, there have been no studies to date that demonstrate that real-world sleep modification modifies CVD risk. Future clinical trials in this space should focus on whether interventions that improve sleep duration, regularity, and quality modify cardiovascular risk. For example, the recent SURMOUNT-OSA trials found that participants who received tirzepatide had a clinically meaningful change in sleep-disordered breathing and alleviation of perceived sleep disturbance and sleep-related impairment, as well as reductions in common obstructive sleep apnea-related cardiovascular risk factors [68]. Furthermore, long follow-up durations would be more ideally assess the influence of sleep disturbances on health over the life course. Ongoing advances in wearable digital health technologies will likely allow for the assessment of chronic, habitual sleep patterns over an individual's lifespan. Finally, several studies have demonstrated that significant disparities in sleep health across race, ethnicity, and sex [69,70]. Further research is needed to better understand how disparities in sleep health may contribute to differences in CVD outcomes across socioeconomic subgroups.

The potential role of optimal sleep health in preventing CVD was highlighted by the inclusion of optimal sleep duration as a component of the 2022 AHA “Life's Essential 8′' construct of ideal cardiovascular health [6]. Although the AHA statement focused on sleep duration, it is clear that other dimensions of sleep have a demonstrable and independent association with CVD and cardiovascular mortality. As evidence continues to grow, future iterations of the guidelines should incorporate sleep regularity and quality as modifiable factors for cardiovascular health. In light of this, we urge preventive cardiologists to prioritize counseling patients on the vital role of sleep health in promoting overall cardiovascular health.

Central illustration

CRediT authorship contribution statement

Krunal D. Amin: Writing – review & editing, Writing – original draft, Conceptualization. Aarti Thakkar: Writing – review & editing, Conceptualization. Tara Budampati: Writing – original draft, Data curation, Conceptualization. Sarina Matai: Visualization. Esra Akkaya: Writing – review & editing, Conceptualization. Nishant P. Shah: Writing – review & editing, Writing – original draft, Supervision.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.