Incorporating sleep health into cardiovascular health outcomes may predict CVD risk

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) CVD prevention guidelines, although sleep is considered 1 of the 3 pillars of health. The researchers of the current study investigated whether adding sound sleep to the AHA Life Simple 7 (LS7) test, which assesses CVH, is the best measure for predicting CVD risk.

The researchers used the Multi-Ethnic Study of Atherosclerosis (MESA) for data for this study. Patients enrolled in Trial 5, which ran from 2010 to 2012, participated in the sleep study, which included a single overnight polysomnography, 7-day wrist actigraphy, and validated questionnaires.

All participants had actigraphy performed over 7 consecutive days, which assessed duration, efficiency, and regularity; a sleep duration of 7 to 9 hours is considered sufficient. Overnight polysomnography was also performed, insomnia was assessed with the Women’s Health Initiative Insomnia Rating Scale, and the Epworth Sleepiness Scale was used to measure daytime sleepiness.

Operationalization of CVH outcomes was done by collecting information on CVH indicators. Participants who developed CVD at or before the sleep examination were classified as prevalent cases (n = 95), whereas patients who received a CVD diagnosis after the sleep examination were considered incident cases (n = 93). The mean follow-up period was 4.4 years.

The mean (SD) age of a total of 1,920 participants was 69 (9) years, 54% were female, 40% were white, 27% were black, 23% were Hispanic, and 10% were Chinese. Seventy-three percent of participants were overweight and 18% had diabetes. The mean LS7 score was 7.3, and the mean CVH score, which includes sleep, ranged from 7.4 to 7.8.

Actigraphy found that 63% of participants slept less than 7 hours and 30% slept less than 6 hours. Thirty-nine percent and 25% of participants, respectively, had high variability between night and sleep duration and sleep onset time, respectively; 14% and 36% had excessive daytime sleepiness and severe insomnia symptoms, respectively.

Linear models found that longer sleep duration and higher 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 and sleep timing and moderate to severe obstructive sleep apnea (OSA). Logistic 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 time to sleep (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 greater odds of poor CVH.

Participants in the highest tertile of LS7 score had 75% lower odds of CVD (OR, 0.25; 95% CI, 0.13-0.49) compared with those in the lowest. Participants in the highest tertile of CVH score 1, including sleep duration, and CVH score 2 had 71% (OR, 0.29; 95% CI, 0.16-0.54) and 80% (OR, 0, 20; 95% CI, 0.10-0.41) correspondingly lower odds of prevalent CVD. Participants in the highest tertile of CVH score 3, which includes studied sleep characteristics associated with CV risk, and CVH score 4, which examines 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 odds of CVD.

A Cox proportional hazards model found that participants in the highest tertile of CVH score 1 had a 43% lower risk of CVD (HR, 0.57; 95% CI, 0.33-0.97) compared with the lowest tertile. Participants with the highest tertile of CVH score 4 also had a 47% lower CVD risk (HR, 0.53; 95% CI, 0.32-0.89).

There were some limitations of this study: there were few CVD events in the follow-up period, and there was limited power to properly test for subgroup differences in gender, race, and ethnicity. In addition, the full picture of an individual’s sleep health status may not be captured in sleep health scores.

The researchers concluded that incorporating sleep health into CVH scores may help more accurately predict participants who may develop CVD in the future.

reference

Makarem N, Castro-Diehl C, St-Onge MP, et al. Redefining cardiovascular health to include sleep: prospective associations with cardiovascular disease in the MESA Sleep Study. J Am Heart Assoc. Published online 19 October 2022 doi:10.1161/jaha.122.025252

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