Healthy sleep pattern reduce the risk of cardiovascular disease: A 10-year prospective cohort study

Zhong, Qiuyan; Qin, Zhongshu; Wang, Xiaowei; Lan, Jian; Zhu, Tingping; Xiao, Xiao; Li, Su; Pei, Pei; Long, Jianxiong; Zhou, Lifang

doi:10.1016/j.sleep.2023.03.003

Cited by 10 publications

(8 citation statements)

References 40 publications

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“…In this study, we used the sleep score created by Fan et al to categorize the participants into three sleep patterns: poor sleep pattern (0–2 points), Intermediate sleep pattern (3–4 points), and healthy sleep pattern (5 points) [ 34 ]. Our findings are consistent with previous studies that evaluated the association between sleep patterns and CVD [ 34 , 37 , 55 ]. A study conducted in China revealed that maintaining healthy sleep patterns can significantly decrease the risk of cardiovascular diseases, coronary heart disease, and stroke [ 55 ].…”

Section: Discussionsupporting

confidence: 93%

“…Our findings are consistent with previous studies that evaluated the association between sleep patterns and CVD [ 34 , 37 , 55 ]. A study conducted in China revealed that maintaining healthy sleep patterns can significantly decrease the risk of cardiovascular diseases, coronary heart disease, and stroke [ 55 ]. Similarly, a study based on the UK Biobank database indicated that poor sleep patterns can worsen the risk of cardiovascular diseases, especially in individuals with poor glucose tolerance [ 56 ].…”

Section: Discussionsupporting

confidence: 93%

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Sleep patterns and risks of incident cardiovascular disease and mortality among people with type 2 diabetes: a prospective study of the UK Biobank

Hu,

Wang,

Cheng

et al. 2024

Diabetol Metab Syndr

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Background To explore the relationship between sleep patterns and cardiovascular disease (CVD) incidence and mortality risk in a population with type 2 diabetes through a UK Biobank sample. Methods A total of 6860 patients with type 2 diabetes were included in this study. Five sleep factors (including Chronotype, sleep duration, insomnia, daytime sleepiness, and snoring) were collected as a questionnaire. The calculation generates a sleep score of 0–5, and then three sleep patterns were defined based on the sleep scores: poor sleep pattern (0–2), Intermediate sleep pattern (3–4), and healthy sleep pattern (5). HRs and 95% confidence intervals were calculated by multivariate COX proportional risk model adjustment. Restricted cubic splines were used to validate linear associations between sleep scores CVD events. Results Our results found a reduced risk of CVD events in individuals with healthy sleep patterns compared to participants with poor sleep patterns. CVD Mortality (HR, 0.690; 95% CI 0.519–0.916), ASCVD (Atherosclerosis CVD) (HR, 0.784; 95% CI 0.671–0.915), CAD (Coronary Artery Disease) (HR, 0.737; 95% CI 0.618–0.879), PAD (Peripheral Arterial Disease) (HR, 0.612; 95% CI 0.418–0.896), Heart Failure (HR, 0.653; 95% CI 0.488–0.875). Restricted cubic spline responded to a negative linear correlation between sleep scores and CVD Mortality, ASCVD, CAD, PAD, and Heart Failure. Conclusions Healthy sleep patterns are significantly associated with a reduced risk of CVD Mortality, ASCVD, CAD, PAD, and Heart Failure in the diabetes population.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionsupporting

confidence: 93%

Sleep patterns and risks of incident cardiovascular disease and mortality among people with type 2 diabetes: a prospective study of the UK Biobank

Hu,

Wang,

Cheng

et al. 2024

Diabetol Metab Syndr

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“…A cohort study in China found that there was a dose-response relationship between sleep health score and CVD risk after adding snoring, daytime sleepiness, insomnia, and sleep duration. This was consistent with our research conclusion, that was, the superposition of various dangerous sleep factors would increase the CVD risk ( 40 ). Our study further carried out hierarchical analysis and found that this relationship was more significant among participants with hypertension and diabetes.…”

Section: Discussionsupporting

confidence: 93%

Association of sleep characteristics with cardiovascular disease risk in adults over 40 years of age: a cross-sectional survey

Hou,

Li,

et al. 2024

Front. Cardiovasc. Med.

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BackgroundThe relationship between sleep characteristics and cardiovascular disease (CVD) risk has yet to reach a consistent conclusion, and more research needs to be carried out. This study aimed to explore the relationship between snoring, daytime sleepiness, bedtime, sleep duration, and high-risk sleep patterns with CVD risk.MethodsData from the National Health and Nutrition Examination Survey (NHANES) 2015–2018 were collected and analyzed. Multivariable logistic regression was used to evaluate the relationship between snoring, daytime sleepiness, bedtime, sleep duration, high-risk sleep patterns, and CVD risk. Stratified analysis and interaction tests were carried out according to hypertension, diabetes and age.ResultsThe final analysis contained 6,830 participants, including 1,001 with CVD. Multivariable logistic regression suggested that the relationship between snoring [OR = 7.37,95%CI = (6.06,8.96)], daytime sleepiness [OR = 11.21,95%CI = (9.60,13.08)], sleep duration shorter than 7 h [OR = 9.50,95%CI = (7.65,11.79)] or longer than 8 h [OR = 6.61,95%CI = (5.33,8.19)], bedtime after 0:00 [OR = 13.20,95%CI = (9.78,17.80)] compared to 22:00–22:59, high-risk sleep patterns [OR = 47.73,95%CI = (36.73,62.04)] and CVD risk were statistically significant. Hypertension and diabetes interacted with high-risk sleep patterns, but age did not.ConclusionsSnoring, daytime sleepiness, excessive or short sleep duration, inappropriate bedtime, and high-risk sleep patterns composed of these factors are associated with the CVD risk. High-risk sleep patterns have a more significant impact on patients with hypertension and diabetes.

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“…Due to the heterogeneity of the compared studies, only a qualitative comparison and narrative summary could be performed; however, the results supported the thesis that sleep bruxism could be associated with systemic inflammation [26]. In the last few years, more attention has been paid to the study of sleep architecture in patients experiencing bruxism during sleep, as it has been proven successive micro-arousals increased cardiovascular risk [33]. In the international case-control study of patients presenting with first acute stroke called INTERSTROKE, it has been observed sleep disturbance symptoms were common and they were significantly associated with a graded increased risk of stroke [34].…”

Section: Introductionmentioning

confidence: 77%

Inflammatory Markers and Sleep Architecture in Sleep Bruxism—A Case-Control Study

Fulek,

Wieckiewicz,

Szymanska-Chabowska

et al. 2024

JCM

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Background: Sleep bruxism (SB) is a common sleep-related movement behavior with a multifaceted etiology and a deficiently understood pathophysiology. A recent hypothesis suggests a link between SB and systemic inflammation. The scope of the study was to determine whether bruxers have altered sleep structure and different levels of inflammatory parameters compared to nonbruxers. Methods: A total of 83 adults underwent full-night polysomnography. The polysomnograms were evaluated using the American Academy of Sleep Medicine (AASM) guidelines. Then, the blood samples were obtained from the participants by venipuncture and the analyses were performed. The study group was divided based on bruxism episode index (BEI) into two groups: BEI ≤ 4 and BEI > 4. Results: In comparison with nonbruxers, the oxygen desaturation index (ODI) was significantly higher in severe bruxers (7.5 ± 11.08 vs. 3.33 ± 5.75, p < 0.005), as well as the arousal parameters (7.77 ± 4.68 vs. 4.03 ± 2.97, p < 0.001), and the mean oxygen desaturation (3.49 ± 0.69 vs. 3.01 ± 0.67, p < 0.05). Moreover, the differences in sleep architecture and deprivation of the deep sleep phase were observed, the non-REM sleep stage 3 was significantly shorter in severe bruxers (p < 0.03). Differences were also noted in non-REM sleep stage 1 and REM sleep phase. In the investigated group, there were no statistical differences in inflammatory cytokines levels between bruxers and nonbruxers. Conclusions: Sleep bruxism is associated with sleep structure alterations and may be associated with deep sleep phase deprivation. The inflammatory markers are not linearly correlated with the severity of sleep bruxism expressed as BEI.

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Healthy sleep pattern reduce the risk of cardiovascular disease: A 10-year prospective cohort study

Cited by 10 publications

References 40 publications

Sleep patterns and risks of incident cardiovascular disease and mortality among people with type 2 diabetes: a prospective study of the UK Biobank

Sleep patterns and risks of incident cardiovascular disease and mortality among people with type 2 diabetes: a prospective study of the UK Biobank

Association of sleep characteristics with cardiovascular disease risk in adults over 40 years of age: a cross-sectional survey

Inflammatory Markers and Sleep Architecture in Sleep Bruxism—A Case-Control Study

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