An improved cardiovascular health (CVH) score that included sleep health was more effective at predicting cardiovascular disease (CVD) risk in older adults in the United States, according to a new study published in Journal of the American Heart Association.
Healthy sleep is not included in the American College of Cardiology / American Heart Association (AHA) cardiovascular disease prevention guidelines, although sleep is considered one of the 3 pillars of health. Researchers in the present study investigated whether adding healthy sleep to the AHA Life Simple 7 (LS7) test that evaluates CVH was the best measure to predict CVD risk.
The researchers used the Multi-Ethnic Atherosclerosis Study (MESA) for the data for this study. Patients enrolled in Exam 5, which ran from 2010 to 2012, participated in the sleep study which included single nocturnal polysomnography, 7-day pulse actigraphy, and validated questionnaires.
All the participants were carried out an actigraphy for 7 consecutive days which assessed the duration, efficiency and regularity; a sleep duration of 7 to 9 hours was considered sufficient. Nocturnal polysomnography was also conducted, insomnia was assessed with the Women’s Health Initiative’s insomnia rating scale, and the Epworth sleepiness scale was used to measure daytime sleepiness.
The operation of CVH scores was carried out by collecting information on CVH metrics. Participants who developed CVD during or before the sleep exam were classified as prevalent cases (n = 95) while patients who received a diagnosis of CVD after the sleep exam were considered incident cases (n = 93 ). The mean follow-up was 4.4 years.
The mean age (SD) of the overall 1920 participants was 69 (9) years, 54% were female, 40% were white, 27% were black, 23% were Hispanic, and 10% were Chinese. 73% of the participants were overweight and 18% had diabetes. The LS7 mean score was 7.3, and the mean CVH scores that included sleep ranged from 7.4 to 7.8.
Actigraphy found that 63% of participants slept for less than 7 hours and 30% for less than 6 hours. 39% and 25% of participants, respectively, had high night-to-night variability in sleep duration and sleep onset times, respectively; 14% and 36% had excessive daytime sleepiness and elevated insomnia symptoms, respectively.
Linear models found that longer sleep duration and greater sleep efficiency were associated with higher LS7 scores, while lower LS7 scores were associated with greater daytime sleepiness, high night-to-night variability in sleep duration. sleep and sleep times and moderate to severe obstructive sleep apnea (OSA). Logistics models found that short sleep (odds ratio [OR], 1.25; 95% CI, 1.01-1.55), high night-to-night variability in sleep duration (OR, 1.24; 95% CI, 1.02-1.51) and sleep times (OR, 1, 31; 95% CI, 1.04-1.64) and moderate to severe OSA (OR, 2.21; 95% CI, 1.78-2.73) were associated with higher odds of poor CVH.
Participants in the highest tertile of the LS7 score were 75% less likely to have CVD (OR, 0.25; 95% CI, 0.13-0.49) than those in the lowest. Participants in the highest tertile of CVH 1 score, including sleep duration, and CVH 2 score had 71% (OR, 0.29; 95% CI, 0.16-0.54) and 80% (OR, 0.20; 95% CI, 0.10-0.41) lower probabilities of prevalent CVD, respectively. Participants in the highest tertile of the CVH score 3, which included the studied sleep characteristics associated with CV risk, and the CVH score 4, which studied sleep regularity and sleep characteristics as new sleep-related risk factors, had 68% (OR, 0.32; 95% CI, 0.17-0.60) and 67% (OR, 0.33; 95% CI, 0.18-0.59) lower rates of CVD.
A Cox proportional hazards model found that participants in the highest tertile of the CVH 1 score had a 43% lower risk of CVD (HR, 0.57; 95% CI, 0.33-0.97) compared to lower tertile. Participants in the highest tertile of the CVH 4 score also had a 47% lower risk of CVD (HR, 0.53; 95% CI, 0.32-0.89).
There were some limitations of this study: there were few cases of CVD in the follow-up period and there was limited ability to adequately test for subgroup differences of sex, race and ethnicity. Additionally, an individual’s full picture of sleep health may not have been captured in sleep health scores.
The researchers concluded that including sleep health in CVH scores could help more accurately predict participants who may develop CVD in the future.
Makarem N, Castro-Diehl C, St-Onge MP, et al. Redefining Cardiovascular Health to Include Sleep: Potential Associations with Cardiovascular Disease in the MESA Sleep Study. J Am Heart Assoc. Published online October 19, 2022. doi: 10.1161 / jaha.122.025252