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Association of bedtime with mortality and major cardiovascular events: an analysis of 112,198 individuals from 21 countries in the PURE study
Abstract
Objectives
This study aimed to examines the association of bedtime with mortality and major cardiovascular events.
Methods
Bedtime was recorded based on self-reported habitual time of going to bed in 112,198 participants from 21 countries in the Prospective Urban Rural Epidemiology (PURE) study. Participants were prospectively followed for 9.2 years. We examined the association between bedtime and the composite outcome of all-cause mortality, non-fatal myocardial infarction, stroke and heart failure. Participants with a usual bedtime earlier than 10PM were categorized as ‘earlier’ sleepers and those who reported a bedtime after midnight as ‘later’ sleepers. Cox frailty models were applied with random intercepts to account for the clustering within centers.
Results
A total of 5633 deaths and 5346 major cardiovascular events were reported. A U-shaped association was observed between bedtime and the composite outcome. Using those going to bed between 10PM and midnight as the reference group, after adjustment for age and sex, both earlier and later sleepers had a higher risk of the composite outcome (HR of 1.29 [1.22, 1.35] and 1.11[1.03, 1.20], respectively). In the fully adjusted model where demographic factors, lifestyle behaviors (including total sleep duration) and history of diseases were included, results were greatly attenuated, but the estimates indicated modestly higher risks in both earlier (HR of 1.09 [1.03-1.16]) and later sleepers (HR of 1.10 [1.02-1.20]).
Conclusion
Early (10 PM or earlier) or late (Midnight or later) bedtimes may be an indicator or risk factor of adverse health outcomes.
... The AASM and the SRS guidelines recognize also that sleep duration exceeding 9 h per night may be beneficial for young adults, but it is uncertain if a longer duration of sleep is associated with health outcomes in adults [2]. On the other hand, both short and long sleep durations have been associated with an increased risk of mortality, type 2 diabetes, cardiovascular diseases (CVD), stroke, coronary heart disease (CHD), and obesity [3][4][5][6][7][8]. Short sleep duration in middle age has been also associated with an increased risk of dementia [9]. ...
... Knutson et al. [12] reported an association between later sleep timing and a higher risk of insulin resistance, especially in older participants. The association between sleep duration or bedtime and CVD events and mortality has been recently investigated in the global Prospective Urban and Rural Epidemiology Study (PURE) [4,8]. ...
... Considering the total duration of sleep, we divided the participants into three groups: (1) <6 h of sleep, (2) 6-8 h of sleep, and (3) >8 h of sleep. Following the approach presented by Wang et al. [8], introducing 10:00 p.m. and 00:00 a.m. (midnight) as cut-offs, the participants were divided into three groups: (1) bedtime before 10 p.m., (2) bedtime between 10 p.m. and midnight, and (3) bedtime after midnight. ...
(1) Background: The objective was to investigate the association between sleep duration, bedtime, and noncommunicable diseases in the PURE Poland cohort study. (2) Methods: The baseline study was conducted in 2007–2010. The study group comprised 2023 adult inhabitants of urban and rural areas in Lower Silesia, Poland. The study protocol included questionnaires, blood pressure measurements, blood draws, and anthropometric measurements. Sleep duration and bedtime were self-reported. (3) Results: The median sleep duration of women was 30 min longer than men (8 h vs. 7.5 h; p = 0.001). The average time of sleep increased along with the age of the participants. A sleep duration of >8 h was more common in rural than in urban participants (40.2% vs. 27.1%; respectively; p < 0.001). The relative risk of diabetes, stroke, hypertension, cardiovascular diseases (CVD), and obesity was significantly higher in participants who went to bed between 6 p.m. and 10 p.m. in comparison to those who went to bed between 10 p.m. and 12 a.m. (RR 2.23, 95%CI 1.06–4.67; RR 2.52, 95%CI 1.28 to 4.97; RR 1.12, 95%CI 1.04–1.20; RR 1.36; 95%CI 1.1–1.68; RR 1.38; 95%CI 1.15–1.66, respectively). The relative risk of respiratory diseases was two-fold higher in those who went to bed after midnight in comparison to those who went to bed between 10 p.m. and 12 a.m. (RR 2.24; 95%CI 1.19–4.22). (4) Conclusions: In our study, an earlier bedtime was associated with a higher risk of diabetes, stroke, obesity, hypertension, and CVD.
... Shift workers were defined as having bedtime between 4:00 AM and 6:00 PM or wake-up time between 12:00 PM and 4:00 AM. In line with previous studies, 15,16 bedtime was further categorized as ≤10:00 PM, 10:01 PM-12:00 AM, and > 12:00 AM, while wake-up time was categorized as ≤ 6:00 AM, 6:01 AM-8:00 AM, and > 8:00 AM. The sleep midpoints were divided into the following categories: ≤ 2:00 AM, 2:01 AM-4:00 AM, and > 4:00 AM. ...
... 8,10,[21][22][23][24] A recent large study showed that earlier and later bedtimes were associated with major CVD and mortality. 15 Early bedtime has also been associated with a high risk of elevated blood pressure in adolescents. 25 However, most previous studies have focused on linear relationships. ...
Study objectives:
Previous studies have highlighted the importance of sleep patterns for human health. This study aimed to investigate the association of sleep timing with all-cause and cardiovascular disease mortality.
Methods:
Participants were screened from two cohort studies: the Sleep Heart Health Study (SHHS; n = 4,824) and the Osteoporotic Fractures in Men Study (n = 2,658). Sleep timing, including bedtime and wake-up time, was obtained from sleep habit questionnaires at baseline. The sleep midpoint was defined as the halfway point between the bedtime and wake-up time. Restricted cubic splines and Cox proportional hazards regression analyses were used to examine the association between sleep timing and mortality.
Results:
We observed a U-shaped association between bedtime and all-cause mortality in both the SHHS and Osteoporotic Fractures in Men Study groups. Specifically, bedtime at 11:00 pm and waking up at 7:00 am was the nadir for all-cause and cardiovascular disease mortality risks. Individuals with late bedtime (> 12:00 am) had an increased risk of all-cause mortality in SHHS (hazard ratio 1.53, 95% confidence interval 1.28-1.84) and Osteoporotic Fractures in Men Study (hazard ratio 1.27, 95% confidence interval 1.01-1.58). In the SHHS, late wake-up time (> 8:00 am) was associated with increased all-cause mortality (hazard ratio 1.39, 95% confidence interval 1.13-1.72). No significant association was found between wake-up time and cardiovascular disease mortality. Delaying sleep midpoint (> 4:00 am) was also significantly associated with all-cause mortality in the SHHS and Osteoporotic Fractures in Men Study.
Conclusions:
Sleep timing is associated with all-cause and cardiovascular disease mortality. Our findings highlight the importance of appropriate sleep timing in reducing mortality risk.
Citation:
Ma M, Fan Y, Peng Y, et al. Association of sleep timing with all-cause and cardiovascular mortality: the Sleep Heart Health Study and the Osteoporotic Fractures in Men Study. J Clin Sleep Med. 2024;20(4):545-553.
... Although several studies have investigated the association of individual lifestyle factors with adverse health outcomes (6)(7)(8)(9)(10)(11) , both protective and risk factors interact with each other and should not be investigated in isolation. For instance, people who sleep less are also more likely to have higher stress levels (12,13) . ...
... International studies have shown inverse associations between healthy lifestyle scores and all-cause mortality (14)(15)(16)(17)(18)(19) . Even if there is no evidence from prospective cohort studies in Chile looking at the link between lifestyle behaviours and mortality risk, a few studies have looked at the association between single risk factors and health outcomes in the country (7)(8)(9)20) . Considering this gap, this study investigated the association between a lifestyle score and all-cause mortality in the Chilean population. ...
Objective
To investigate the association between a lifestyle score and all-cause mortality in the Chilean population.
DesignProspective study
SettingsThe score was based on seven modifiable behaviours: salt intake, fruit and vegetable intake, alcohol consumption, sleep duration, smoking, physical activity, and sedentary behaviours. 1-point was assigned for each healthy recommendation. Points were summed to create an unweighted score from 0 (less healthy) to 7 (healthiest). According to their score, participants were then classified into: less healthy (0-2 points), moderately healthy (3-4 points), and the healthiest (5-7 points). Associations between the categories of lifestyle score and all-cause mortality were investigated using Cox proportional hazard models adjusted for confounders. Nonlinear associations were also investigated.
Participants2,706 participants from the Chilean National Health Survey 2009-2010.
ResultsAfter a median follow-up of 10.9 years, 286 (10.6%) participants died. In the maximally adjusted model, and compared with the healthiest participants, those less healthy had 2.55 (95% CI: 1.75 to 3.71) times higher mortality risk due to any cause. Similar trends were identified for the moderately healthy group. Moreover, there was a significant trend toward increasing the mortality risk when increasing unhealthy behaviours (HR model 3: 1.61 [95% CI: 1.34 to 1.94]). There was no evidence of nonlinearity between the lifestyle score and all-cause mortality.
Conclusion
Individuals in the less healthy lifestyle category had higher mortality risk than the healthiest group. Therefore, public health strategies should be implemented to promote adherence to a healthy lifestyle across the Chilean population.
... Meanwhile, time of sleep onset also yielded a significant influence on circadian rhythm, which could increase the risk of multiple diseases, including cardiovascular and nervous system disorders [7,17]. A previous cohort study conducted in multiple countries showed that bedtimes earlier than 10:00 p.m. or later than midnight might be a risk for all-cause mortality and major cardiovascular events [18]. However, to the best of our knowledge, this is the first study to assess the relation between bedtime and hearing loss. ...
... The underlying mechanisms behind associations of sleep duration and bedtime with hearing loss have not been documented. The development of hearing loss attributed to inner ear homeostasis was relevant to microvascular damage [29], which was reported to be associated with longer sleep duration in our prior studies [18,30]. Long sleep duration or early bedtime also showed a positive relation with nervous system impairment, systemic inflammation, and oxidative stress [31,32]. ...
Evidence available on the independent and combined associations of sleep duration, bedtime, and genetic predisposition with hearing loss was lacking. The present study included 15,827 participants from the Dongfeng–Tongji cohort study. Genetic risk was characterized by polygenic risk score (PRS) based on 37 genetic loci related to hearing loss. We conducted multivariate logistic regression models to assess the odds ratio (OR) for hearing loss with sleep duration and bedtime, as well as the joint association and interaction with PRS. Results showed that hearing loss was independently associated with sleeping ≥9 h/night compared to the recommended 7 to 9:00 p.m. to 10:00 p.m. compared to those with bedtime >10:00 p.m. to 11:00 p.m., with estimated ORs of 1.25, 1.27, and 1.16, respectively. Meanwhile, the risk of hearing loss increased by 29% for each 5-risk allele increment of PRS. More importantly, joint analyses showed that the risk of hearing loss was 2-fold in sleep duration ≥9 h/night and high PRS, and 2.18-fold in bedtime ≤9:00 p.m. and high PRS. With significant joint effects of sleep duration and bedtime on hearing loss, we found an interaction of sleep duration with PRS in those with early bedtime and an interaction of bedtime with PRS in those with long sleep duration on hearing loss (Pint
... Shift workers were defined as having bedtime between 4:00 AM and 6:00 PM or wake-up time between 12:00 PM and 4:00 AM . Sleep timing including bedtime, wake-up time and sleep midpoint were further grouped according to previous studies and important time points such as midnight (12:00 AM ) [14][15][16][17]. Bedtime was divided into four groups: ≤10:00 PM , 10:01 PM -11:00 AM , 11:01 PM -12:00 AM and > 12:00 AM . ...
Objectives
Sleep characteristics such as duration, continuity, and irregularity are associated with the risk of hypertension. This study aimed to investigate the association between sleep timing (including bedtime, wake-up time, and sleep midpoint) and the prevalence of hypertension.
Methods
Participants were selected from the Sleep Heart Health Study (n = 5504). Bedtime and wake-up times were assessed using sleep habit questionnaires. The sleep midpoint was calculated as the halfway point between the bedtime and wake-up time. Restricted cubic splines and logistic regression analyses were performed to explore the association between sleep timing and hypertension.
Results
A significant nonlinear association was observed between bedtime (Poverall<0.001; Pnonlinear<0.001), wake-up time (Poverall=0.024; Pnonlinear=0.076), sleep midpoint (Poverall=0.002; Pnonlinear=0.005), and the prevalence of hypertension after adjusting for potential confounders. Multivariable logistic regression showed that both late (> 12:00AM and 23:01PM to 12:00AM) and early (≤ 22:00PM) bedtimes were associated with an increased risk of hypertension compared to bedtimes between 22:01PM and 23:00PM. In addition, individuals with late (> 7:00AM) and early (≤ 5:00AM) wake-up times had a higher prevalence of hypertension than those with wake-up times ranging between 5:01AM and 6:00AM. Delaying the sleep midpoint (> 3:00AM) was also associated with an increased risk of hypertension. Furthermore, no significant interaction effect was found in the subgroup analyses stratified by age, sex, or apnea-hypopnea index.
Conclusions
Our findings identified a nonlinear association between sleep timing and hypertension. Individuals with both early and late sleep timing had a high prevalence of hypertension.
... Fan et al. revealed that individuals with weekday bedtime at 10:01-11:00 PM had the lowest occurrence of MI compared to other time periods in middle-aged and older populations [27]. Another study also reported a similar condition that earlier (< 10:00 PM) and later (≥ 12:00 PM) sleepers had a higher risk of the composite outcome [28]. Different from the previous studies, which found a U-shaped association between bedtime and MACEs, patients in our study with bedtime < 22:00 were prone to have a low incidence of MACEs despite no significant difference. ...
Background
Sleeping late has been a common phenomenon and brought harmful effects to our health. The purpose of this study was to investigate the association between sleep timing and major adverse cardiovascular events (MACEs) in patients with percutaneous coronary intervention (PCI).
Methods
Sleep onset time which was acquired by the way of sleep factors questionnaire in 426 inpatients was divided into before 22:00, 22:00 to 22:59, 23:00 to 23:59 and 24:00 and after. The median follow-up time was 35 months. The endpoints included angina pectoris (AP), new myocardial infarction (MI) or unplanned repeat revascularization, hospitalization for heart failure, cardiac death, nonfatal stroke, all-cause death and the composite endpoint of all events mentioned above. Cox proportional hazards regression was applied to analyze the relationship between sleep timing and endpoint events.
Results
A total of 64 composite endpoint events (CEEs) were reported, including 36 AP, 15 new MI or unplanned repeat revascularization, 6 hospitalization for heart failure, 2 nonfatal stroke and 5 all-cause death. Compared with sleeping time at 22:00–22:59, there was a higher incidence of AP in the bedtime ≥ 24:00 group (adjusted HR: 5.089; 95% CI: 1.278–20.260; P = 0.021). In addition, bedtime ≥ 24:00 was also associated with an increased risk of CEEs in univariate Cox regression (unadjusted HR: 2.893; 95% CI: 1.452–5.767; P = 0.003). After multivariable adjustments, bedtime ≥ 24:00 increased the risk of CEEs (adjusted HR: 3.156; 95% CI: 1.164–8.557; P = 0.024).
Conclusion
Late sleeping increased the risk of MACEs and indicated a poor prognosis. It is imperative to instruct patients with PCI to form early bedtime habits.
... In a subsequent analysis, findings from MESA reported elevated risk for incident CVD with higher variability in both sleep duration and sleep onset timing with each additional hour of variability being associated with increased risk of 36% and 18%, respectively (Huang et al., 2020). Bedtimes and wake times are also important to consider as both early (before 10:00 p.m.) and late (after 12:00 a.m.) bedtimes have been reported as potential risk factors for cardiovascular events (Wang et al., 2021). Notably, the shift in sleep patterns occurring with daylight savings time coincides with an increase in MI and stroke (Manfredini et al., 2018;Sipilä et al., 2016). ...
Sleep has important physiological functions in maintaining a healthy metabolism. Aberrations in sleep such as shortened sleep duration and irregular sleep patterns along with undiagnosed and untreated sleep disorders can contribute to heightened cardiovascular risk. Importantly, poor sleep quantity and quality is increasingly pervasive. With increases in obesity and an aging population, sleep disorders are also more prevalent. This article highlights the detrimental effects of altered sleep on cardiovascular health. Evidence from observational and experimental studies linking different aspects of sleep with cardiovascular risk are presented. Lastly, potential sleep targeted cardiovascular risk mitigation strategies are discussed.
... Our findings agree with previous studies that recognized such a shift in chronotype toward eveningness in adult population (2), small children (3), and high-school children (4). The SSQ enabled a valid assessment of sleep timing, which is relevant during the ongoing COVID-19 pandemic considering the association of sleep habits changes with public health outcomes (37)(38)(39). The use of the SSQ as a single-administration questionnaire in the general population may enable low-cost, easy administration, not requiring long-term commitment from respondents as is required for the use of sleep diaries or actigraphy devices. ...
Aim:
To construct a single-format questionnaire on sleep habits and mood before and during the COVID-19 pandemic in the general population.
Methods:
We constructed the Split Sleep Questionnaire (SSQ) after a literature search of sleep, mood, and lifestyle questionnaires, and after a group of sleep medicine experts proposed and assessed questionnaire items as relevant/irrelevant. The study was performed during 2021 in 326 respondents distributed equally in all age categories. Respondents filled out the SSQ, the Pittsburgh Sleep Quality Index (PSQI), and State Trait Anxiety Inventory (STAI), and kept a seven-day sleep diary.
Results:
Cronbach alpha for Sleep Habits section was 0.819, and 0.89 for Mood section. Test-retest reliability ranged from 0.45 (P=0.036) for work-free day bedtime during the pandemic to 0.779 (P<0.001) for sleep latency before the pandemic. Workday and work-free day bedtime during the COVID-19 pandemic assessed with SSQ were comparable to the sleep diary assessment (P=0.632 and P=0.203, respectively), as was the workday waketime (P=0.139). Work-free day waketime was significantly later than assessed in sleep diary (8:19±1:52 vs 7:45±1:20; P<0.001). No difference in sleep latency was found between the SSQ and PSQI (P = 0.066).
Conclusion:
The SSQ provides a valid, reliable, and efficient screening tool for the assessment of sleep habits and associated factors in the general population during the COVID-19 pandemic.
... Responses were used to calculate sleep duration pre-pandemic and during the pandemic. Based on other literature (21,22), bedtime categories were created using reported time to bed (earlier than 10 pm = early; 10 pm to 12 am = mid; later than 12 am = late). Shift in bedtime was defined as the change in bedtime category from pre-pandemic to during the pandemic. ...
The objective of this study was to investigate the differences in sleep patterns among individuals with and without laboratory-confirmed SARS-CoV-2 infection. Laboratory-confirmed SARS-CoV-2 test results and self-reported measures recalling sleep habits prior to and during the pandemic were collected from May 2020 to March 2021 among 1,848 individuals in The Arizona CoVHORT Study. We used linear and logistic regression to model the association between test status, presentation of symptoms, and time since test result with sleep duration and trouble sleeping, respectively. Mixed models were used to investigate change in sleep duration prior to the pandemic compared to during the pandemic. Overall, 16.2% of the sample were SARS-CoV-2 positive, 64.3% were SARS-CoV-2 negative, and 19.5% were untested for SARS-CoV-2. Independent of SARS-CoV-2 infection status, all participants slept longer during the pandemic compared to pre-pandemic (Δ SARS-CoV-2 positive: 77.7 min, 95% CI 67.9, 87.5; Δ SARS-CoV-2 negative: 13.4 min, 95% CI 8.4, 18.3). However, SARS-CoV-2 positive participants slept 60.9 min longer (95% CI 49.1, 72.8) than SARS-CoV-2 negative participants in multivariable-adjusted models and had greater odds of trouble sleeping three or more times per week since the start of the pandemic (OR: 1.34 95% CI 1.02, 1.77) This greater odds of trouble sleeping persisted for participants who reported sleep habits > 30 days after their positive SARS-CoV-2 (OR: 2.11 95% CI 1.47, 3.03). Sleep patterns among non-hospitalized individuals with COVID-19 were altered following infection, regardless of the presentation of symptoms and time since infection.
... In a subsequent analysis, findings from MESA reported elevated risk for incident CVD with higher variability in both sleep duration and sleep onset timing with each additional hour of variability being associated with increased risk of 36% and 18%, respectively (Huang et al., 2020). Bedtimes and wake times are also important to consider as both early (before 10:00 p.m.) and late (after 12:00 a.m.) bedtimes have been reported as potential risk factors for cardiovascular events (Wang et al., 2021). Notably, the shift in sleep patterns occurring with daylight savings time coincides with an increase in MI and stroke (Manfredini et al., 2018;Sipilä et al., 2016). ...
Sleep has important physiological functions in maintaining a healthy metabolism. Aberrations in sleep such as shortened sleep duration and irregular sleep patterns along with undiagnosed and untreated sleep disorders can contribute to heightened cardiovascular risk. Importantly, poor sleep quantity and quality is increasingly pervasive. With increases in obesity and an aging population, sleep disorders are also more prevalent. This article highlights the detrimental effects of altered sleep on cardiovascular health. Evidence from observational and experimental studies linking different aspects of sleep with cardiovascular risk are presented. Lastly, potential sleep targeted cardiovascular risk mitigation strategies are discussed.
... However, no evidence regarding the impact of late bedtime on the incidence of MI has been reported. A recent study found that there was a U-shaped association between bedtime and the composite cardiovascular disease (25). We also observed the similar condition when explore the association of weekday bedtime and incident MI. ...
Objective: Sleep has a significant influence on the incidence of myocardial infarction (MI). The purpose of this study was to investigate the association between sleep timing including bedtime, wake-up time and sleep midpoint, and the incidence of MI.
Methods: A total of 4,576 patients (2,065 men, 2,511 women; age 63.4 ± 11.0 years) were selected from the Sleep Heart Health Study. Sleep timings on weekdays and weekends were recorded or calculated based on the sleep habits questionnaire completed by the participants at baseline. Bedtime was divided into 10:00 PM and before, 10:01 PM−11:00 PM, 11:01 PM−12:00 AM, and later than 12:00 AM. Cox proportional hazards regression analysis was used to examine the relationship between sleep timings and MI.
Results: Participants with a weekday bedtime later than 12:00 AM, between 11:01 PM−12:00 AM, and 10:00 PM or before had a higher incidence of MI than those with a bedtime between 10:01 PM and 11:00 PM (9.2% vs. 7.0% vs. 6.9% vs. 5.1%, respectively; P = 0.008). Multivariable Cox regression analysis showed that sleeping on weekdays later than 12:00 AM was associated with an increased risk of incident MI after adjusting for potential covariates (hazard ratio, 1.628; 95% confidence interval, 1.092–2.427; P = 0.017). However, there was no significant association between late bedtime on weekends and MI. In addition, no significant association of late wake-up time and delayed sleep midpoint on both weekdays and weekends with the incidence of MI was observed.
Conclusion: Sleeping late on weekday (>12:00 AM) independently increased the risk of MI. This finding emphasizes the importance of a proper bedtime for the maintenance of the health of the cardiovascular system.
Importance
The associations of changes in sleep patterns with incident cardiovascular disease (CVD) are not fully elucidated, and whether these associations are modified by genetic susceptibility remains unknown.
Objectives
To investigate the associations of 5-year changes in sleep patterns with incident CVD and whether genetic susceptibility modifies these associations.
Design, Setting, and Participants
This prospective cohort study of the Dongfeng-Tongji cohort was conducted from 2008 to 2018 in China. Eligible participants included those with complete sleep information at baseline survey (2008-2010) and the first follow-up survey (2013); participants who had no CVD or cancer in 2013 were prospectively assessed until 2018. Statistical analysis was performed in November 2023.
Exposures
Five-year changes in sleep patterns (determined by bedtime, sleep duration, sleep quality, and midday napping) between 2008 and 2013, and polygenic risk scores (PRS) for coronary heart disease (CHD) and stroke.
Main Outcomes and Measures
Incident CVD, CHD, and stroke were identified from 2013 to 2018. Cox proportional hazards regression models were applied to estimate hazard ratios (HRs) and 95% CIs.
Results
Among 15 306 individuals (mean [SD] age, 65.8 [7.4] years; 8858 [57.9%] female and 6448 male [42.1%]), 5474 (35.78%) had persistent unfavorable sleep patterns and 3946 (25.8%) had persistent favorable sleep patterns. A total of 3669 incident CVD cases were documented, including 2986 CHD cases and 683 stroke cases, over a mean (SD) follow-up of 4.9 (1.5) years. Compared with those with persistent unfavorable sleep patterns, individuals with persistent favorable sleep patterns over 5 years had lower risks of incident CVD (HR, 0.80; 95% CI, 0.73-0.87), CHD (HR, 0.84; 95% CI, 0.76-0.92), and stroke (HR, 0.66; 95% CI, 0.54-0.82) in the subsequent 5-year period. No significant effect modification by PRS was observed for sleep pattern change and CHD or stroke risk. However, sleep pattern changes and PRS were jointly associated with the CHD and stroke risk in a dose-dependent manner, with the lowest risk being among those with persistent favorable sleep patterns combined with low PRS (HR for CHD, 0.65; 95% CI, 0.52-0.82 and HR for stroke, 0.48; 95% CI, 0.29-0.79).
Conclusions and Relevance
In this cohort study of middle-aged and older Chinese adults, individuals with persistent favorable sleep patterns had a lower CVD risk, even among those with higher genetic risk. These findings highlight the importance of maintaining favorable sleep patterns for CVD prevention.
We aim to examine the association of sleep duration, sleep quality, late chronotype and circadian misalignment with glycemic control and risk of complications in young adults with youth-onset type 2 diabetes followed in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study. Self-reported sleep duration, quality, timing, and circadian misalignment were assessed via a modified Pittsburgh Sleep Quality Index (PSQI) questionnaire, and chronotype was assessed via the Morningness-Eveningness Questionnaire (MEQ). We examined diabetes complications including loss of glycemic control (defined as hemoglobin A1c ≥8%), hypertension, dyslipidemia, albuminuria, and diabetic peripheral neuropathy. Multivariable logistic regression models were constructed to assess associations between sleep and circadian measures with outcomes of interest, such as loss of glycemic control and diabetes complications. A total of 421 participants (34.2% male), mean age 23.6±2.5 years, mean BMI of 36.10±8.26 kg/m ² and mean diabetes duration of 10.0±2.5 years were evaluated. Self-reported short sleep duration, daytime sleepiness, and sleep quality were not associated with loss of glycemic control or diabetes complications. Late self-reported bedtime (after midnight) on work/school nights, rather than self-expressed chronotype or circadian misalignment, was independently associated with loss of glycemic control. An association was seen between late bedtimes and albuminuria but was attenuated after adjusting for depression. In conclusion, late bedtime on work/school days, rather than short sleep duration, daytime sleepiness, or poor sleep quality, was independently associated with loss of glycemic control in this longitudinal cohort of young adults with youth-onset type 2 diabetes.
Objective:
This study aims to investigate the associations of bedtime and its combination with sleep duration and sleep quality with all-cause mortality.
Methods:
We conducted a prospective cohort study using data collected from 2008 to 2018 in the Dongfeng-Tongji cohort. Among 40,097 participants aged 62.1 on average at baseline, we applied Cox regression models to assess hazard ratios and 95% confidence intervals for mortality risk.
Results:
During a mean follow-up of 8.2years, 4345 deaths were documented. U-shaped associations of bedtime and sleep duration with all-cause mortality were observed. Compared with bedtime between 10:01 PM and 11:00 PM, the hazard ratio (95% confidence interval) for all-cause mortality was 1.34 (1.20-1.49) for ≤9:00 PM, 1.18 (1.09-1.27) for 9:01-10:00 PM, and 1.50 (1.13-2.00) for >12:00 AM, respectively. Participants with sleep duration of <6, 6-<7, 8-<9, and ≥9 h/night had a respective 39%, 21%, 11%, and 25% higher all-cause mortality risk than those sleeping 7-<8 h/night. Additionally, participants with a healthy sleep score of 3, characterized as proper bedtime (10:01 PM-12:00 AM), moderate sleep duration (7-<8h/night), and good/fair sleep quality, had a significantly 36% (hazard ratio, 0.64; 95% confidence interval, 0.56-0.74) lower all-cause mortality risk than those with a score of 0.
Conclusions:
Individuals with early or late bedtimes and short or long sleep duration were at higher all-cause mortality risks. Having healthy sleep habits may significantly reduce death risk.
Objectives:
To investigate the associations of bedtime and a low-risk sleep pattern with incident cardiovascular disease (CVD).
Methods:
A total of 31,500 retirees were included from the Dongfeng-Tongji cohort in 2008-2010 and 2013. Sleep information was collected by questionnaires. CVD events were identified through the health care system until December 31, 2018. Cox proportional hazards regression models were performed to estimate hazard ratios (HRs) and 95% confidence intervals (CIs).
Results:
During an average follow-up of 7.2 years, 8324 cases of incident CVD, including 6557 coronary heart disease (CHD) and 1767 stroke, were documented. U-shaped associations of bedtime with the risks of incident CVD and stroke were observed. Compared with bedtime between 10:01 p.m.-11:00 p.m., the HR (95% CI) for CVD was 1.10 (1.01-1.20) for ≤9:00 p.m., 1.07 (1.01-1.13) for 9:01 p.m.-10:00 p.m., and 1.32 (1.11-1.58) for >12:00 a.m., respectively, mainly driven by stroke risk (22%, 14%, and 70% higher for ≤9:00 p.m., 9:01 p.m.-10:00 p.m., and >12:00 a.m., respectively). The number of low-risk sleep factors, namely bedtime between 10:01 p.m.-12:00 a.m., sleep duration of 7-< 8 h/night, good/fair sleep quality, and midday napping ≤60 min, exhibited dose-dependent relationships with CVD, CHD, and stroke risks. Participants with 4 low-risk sleep factors had a respective 24%, 21%, and 30% lower risk of CVD, CHD, and stroke than those with 0-1 low-risk sleep factor.
Conclusions:
Individuals with early or late bedtimes had a higher CVD risk, especially stroke. Having low-risk sleep habits is associated with lower CVD risks.
Study question:
What is the association between late bedtime, night sleep duration, and lifetime cardiovascular disease (CVD) risk in women with polycystic ovary syndrome (PCOS)?
Summary answer:
Both late bedtime (≥1:00) and short sleep duration (<7 h/night) were independently associated with a high-lifetime CVD risk among women with PCOS.
What is known already:
Previous studies indicated that sleep disturbances, including altered sleep duration and staying up late (SUL), occurred more frequently among women with PCOS compared to women without PCOS. Studies have shown that both PCOS and sleep disturbances are associated with deterioration in cardiometabolic health in the longer term. However, there are limited data regarding the possible association between sleep disturbances and CVD risk among reproductive-aged women with PCOS.
Study design, size, duration:
From the original 393 women identified at our center, a total of 213 women with PCOS aged 18-40 years were enrolled in a cross-sectional study between March 2020 and July 2022.
Participants/materials, setting, methods:
Bedtime and night sleep duration were obtained from a standardized self-administered questionnaire. The prediction for atherosclerotic CVD risk in the China risk model was applied to estimate the lifetime CVD risk in the PCOS population. Restricted cubic spline regression was applied to explore the non-linear association between sleep duration and lifetime CVD risk in a series of models. Multivariable logistic regression analyses were performed to determine the association between bedtime, night sleep duration, and lifetime CVD risk.
Main results and the role of chance:
In our study, we found that the proportion of SUL was 94.25% and the mean (±SD) of night sleep duration was 7.5 ± 1.1 h in women with PCOS. Restricted cubic spline regression analysis showed a U-shaped relation between sleep duration and lifetime CVD risk. After adjusting for occasional drinking, fasting insulin, triglyceride, low-density lipoprotein cholesterol, and testosterone in multivariable logistic analyses, compared with going to bed at 23-24 o'clock, those who went to bed after 1 o'clock were independently associated with high-lifetime CVD risk [odds ratio (OR) = 3.87, 95% CI: 1.56-9.62]; compared with optimal sleep duration (7-8 h/night), short sleep (<7 h/night) was also independently associated with high-lifetime CVD risk (OR = 2.46, 95% CI: 1.01-5.97).
Limitations, reasons for caution:
Inferring causality is limited owing to the cross-sectional design. All sleep variables data were obtained from a standardized self-administered questionnaire rather than measurements using objective approaches. Even after adjusting for potential confounders, we still cannot completely rule out the possibility of residual confounding from unmeasured factors such as socioeconomic status. Future studies with larger sample sizes are needed to further explore the relation between long sleep duration and lifetime CVD risk. Although these findings are not generalizable to non-SUL PCOS populations, they could be used for guiding multidimensional treatment. Lastly, there is no non-PCOS group in the current cross-sectional study, which limits the interpretation of the findings from the PCOS group.
Wider implications of the findings:
This is the first study to report that both late bedtime (≥1:00) and short sleep duration (<7 h/night) were independently associated with a high-lifetime CVD risk among reproductive-aged women with PCOS, in a sample of Chinese adults. Predicting cardiovascular risk and examining the association between sleep disturbances and predicted CVD risk among women with PCOS help to highlight the need for early interventions on sleep to improve their cardiovascular outcomes.
Study funding/competing interest(s):
This study was funded by the Natural Science Foundation of Fujian Province (No. 2020J011242), the Fujian provincial health technology project (No. 2022CXB016), the Joint Research Projects of Health and Education Commission of Fujian Province (No. 2019-WJ-39), and the Medical and Health project of Xiamen Science & Technology Bureau (No. 3502Z20214ZD1001). The authors declare that they have no conflict of interest.
Trial registration number:
N/A.
Importance
Unhealthy sleep behaviors and sleep disturbances are associated with higher risk of multiple diseases and mortality. The current profiles of sleep habits and disturbances, particularly the differences between workdays and free days, are unknown in the contemporary US.
Objective
To comprehensively evaluate sleep habits on workdays and free days and the prevalence of sleep disturbances among US adults.
Design, Setting, and Participants
This study is a cross-sectional analysis of US nationally representative data from the National Health and Nutrition Examination Survey (2017-2020) among adults aged 20 years or older. Data analysis was performed from February to May 2022.
Main Outcomes and Measures
The main outcomes were means and/or distributions of sleep habits, including sleep duration and sleep-wake timing on workdays and free days, sleep debt (ie, the difference between sleep duration on free days and mean weekly sleep duration), and social jet lag (ie, the difference between the midpoint between sleep and wake time on workdays and free days). Prevalence of trouble sleeping (ie, participants told a doctor or other health professional that they have trouble sleeping) and daytime sleepiness (ie, self-reported feeling of being overly sleepy during the day ≥5 times per month) were also determined.
Results
A total of 9004 individuals (mean [SE] age, 48.3 [0.53] years; 4635 women [51.9%]; 3158 non-Hispanic White [62.8%]) were included in the current study. The mean sleep duration was 7.59 hours (95% CI, 7.54 to 7.64 hours) on workdays and 8.24 hours (95% CI, 8.17 to 8.31 hours) on free days (difference, 0.65 hour). The mean sleep and wake times were at 11:02 pm (95% CI, 10:57 pm to 11:17 pm ) and 6:41 am (95% CI, 6:36 am to 6:45 am ), respectively, on workdays and 11:25 pm (95% CI, 11:21 pm to 11:35 pm ) and 7:41 am (95% CI, 7:37 am to 7:46 am ), respectively, on free days (differences, 0.23 hour for sleep time and 1.00 hour for wake time). On workdays, 23.1% (95% CI, 21.3% to 24.9%) of adults slept less than 7 hours and 25.4% (95% CI, 24.1% to 26.6%) went to sleep at midnight or later; the corresponding percentages changed to 12.9% (95% CI, 11.6% to 14.1%) and 40.9% (95% CI, 38.4% to 43.5%), respectively, on free days. Furthermore, the mean sleep debt was 0.73 hours (95% CI, 0.68 to 0.77 hours), and mean social jet lag was 1.10 hours (95% CI, 1.05 to 1.15 hours); 30.5% (95% CI, 26.8% to 33.3%) of adults experienced 1 hour or more of sleep debt, and 46.5% (95% CI, 42.6% to 50.3%) experienced 1 hour or more of social jet lag. The prevalence of trouble sleeping was 29.8% (95% CI, 28.2% to 31.5%), and that of daytime sleepiness was 27.2% (95% CI, 25.0% to 29.5%).
Conclusions and Relevance
In 2017 to 2020, US adults showed variability in sleep habits between workdays and free days, with longer sleep duration and later sleep-wake phases on free days, and high percentages of US adults experienced long-term sleep deprivation, chronic social jet lag, and frequent sleep disturbances. These findings provide evidence to further investigate potential approaches to optimize overall US sleep health.
Introduction:
Hypertension affects up to 5% of children worldwide and predicts later cardiovascular morbidity. Associations of short sleep and hypertension have been frequently reported in adults but less consistently in children. This study aims to examine the role of late bedtimes, a marker of short sleep duration and potentially-misaligned circadian rhythms, on incident elevated blood pressure (BP) in a large cohort of Mexican children.
Methods:
Participants included 2,033 adolescents recruited from public schools in Morelos, Mexico, free from elevated BP (<90th sex, age, and height-standardized percentile). Fourteen months later, all adolescents had a second blood pressure assessment. We abstracted baseline habitual bedtimes from questionnaires to evaluate the association between bedtime and elevated BP incidence (≥90th percentile). Risk ratios and 95% confidence intervals were estimated with discrete-time mixed survival models, adjusting for potential confounders and accounting for clustering by school.
Results:
Participants were 12.5 (SD=0.6) years old at baseline. At the follow-up visit 10% of adolescents had developed elevated BP. Compared to participants with a habitual weekday bedtime between 9 and 10 PM, those with a weekday bedtime 11 PM or later had a 1.87 times higher risk of developing elevated BP over the follow-up period (95% CI 1.09 to 2.21), after accounting for confounders. Participants with earlier weekday bedtimes also had a higher risk of elevated BP (RR=1.96; 95% CI 1.27, 3.01). The associations persisted after accounting for wake time.
Conclusion:
These data showed a U-shaped association between weekday bedtime and elevated/high BP risk among Mexican adolescents.
Aims:
To investigate the association of estimated total daily sleep duration and daytime nap duration with deaths and major cardiovascular events.
Methods and results:
We estimated the durations of total daily sleep and daytime naps based on the amount of time in bed and self-reported napping time and examined the associations between them and the composite outcome of deaths and major cardiovascular events in 116 632 participants from seven regions. After a median follow-up of 7.8 years, we recorded 4381 deaths and 4365 major cardiovascular events. It showed both shorter (≤6 h/day) and longer (>8 h/day) estimated total sleep durations were associated with an increased risk of the composite outcome when adjusted for age and sex. After adjustment for demographic characteristics, lifestyle behaviours and health status, a J-shaped association was observed. Compared with sleeping 6-8 h/day, those who slept ≤6 h/day had a non-significant trend for increased risk of the composite outcome [hazard ratio (HR), 1.09; 95% confidence interval, 0.99-1.20]. As estimated sleep duration increased, we also noticed a significant trend for a greater risk of the composite outcome [HR of 1.05 (0.99-1.12), 1.17 (1.09-1.25), and 1.41 (1.30-1.53) for 8-9 h/day, 9-10 h/day, and >10 h/day, Ptrend < 0.0001, respectively]. The results were similar for each of all-cause mortality and major cardiovascular events. Daytime nap duration was associated with an increased risk of the composite events in those with over 6 h of nocturnal sleep duration, but not in shorter nocturnal sleepers (≤6 h).
Conclusion:
Estimated total sleep duration of 6-8 h per day is associated with the lowest risk of deaths and major cardiovascular events. Daytime napping is associated with increased risks of major cardiovascular events and deaths in those with >6 h of nighttime sleep but not in those sleeping ≤6 h/night.
Introduction
Sleep is increasingly being viewed as an issue of public health concern, yet few epidemiologic studies have explored associations between sleep habits and metabolomic profile.
Objectives
To assess the association between sleep and blood metabolites.
Methods
We examined the association between sleep and 891 fasting plasma metabolites in a subgroup of 106 participants from the Dietary Approaches to Stop Hypertension (DASH)—Sodium feeding trial (1997–1999). We produced two sleep variables to analyze, sleep midpoint (median time between bedtime and waketime) and sleep duration, as well as bedtime and wake time. Metabolites were measured using liquid and gas chromatography, coupled with mass spectrometry. We assessed associations between sleep variables and log transformed metabolites using linear mixed-effects models. We combined the resulting p-values using Fisher’s method to calculate associations between sleep and 38 metabolic pathways.
Results
Sixteen pathways were associated (p < 0.05) with midpoint. Only the γ-glutamyl amino acid metabolism pathway reached Bonferroni-corrected threshold (0.0013). Eighty-three metabolites were associated with midpoint (FDR < 0.20). Similar associations were found for wake time. Neither bed time nor duration were strongly associated. The top metabolites (pathways given in brackets) associated with sleep were erythrulose (advanced glycation end-product) (positive association) and several γ-glutamyl pathway metabolites, including CMPF (fatty acid, dicarboxylate), isovalerate (valine, leucine and isoleucine and fatty acid metabolism) and HWESASXX (polypeptide) (inverse association).
Conclusion
Within our study, several metabolites that have previously been linked to inflammation and oxidative stress (processes involved in diseases such as cardiovascular disease and cancer) were found to be associated with sleep.
Background:
The relationship between macronutrients and cardiovascular disease and mortality is controversial. Most available data are from European and North American populations where nutrition excess is more likely, so their applicability to other populations is unclear.
Methods:
The Prospective Urban Rural Epidemiology (PURE) study is a large, epidemiological cohort study of individuals aged 35-70 years (enrolled between Jan 1, 2003, and March 31, 2013) in 18 countries with a median follow-up of 7·4 years (IQR 5·3-9·3). Dietary intake of 135 335 individuals was recorded using validated food frequency questionnaires. The primary outcomes were total mortality and major cardiovascular events (fatal cardiovascular disease, non-fatal myocardial infarction, stroke, and heart failure). Secondary outcomes were all myocardial infarctions, stroke, cardiovascular disease mortality, and non-cardiovascular disease mortality. Participants were categorised into quintiles of nutrient intake (carbohydrate, fats, and protein) based on percentage of energy provided by nutrients. We assessed the associations between consumption of carbohydrate, total fat, and each type of fat with cardiovascular disease and total mortality. We calculated hazard ratios (HRs) using a multivariable Cox frailty model with random intercepts to account for centre clustering.
Findings:
During follow-up, we documented 5796 deaths and 4784 major cardiovascular disease events. Higher carbohydrate intake was associated with an increased risk of total mortality (highest [quintile 5] vs lowest quintile [quintile 1] category, HR 1·28 [95% CI 1·12-1·46], ptrend=0·0001) but not with the risk of cardiovascular disease or cardiovascular disease mortality. Intake of total fat and each type of fat was associated with lower risk of total mortality (quintile 5 vs quintile 1, total fat: HR 0·77 [95% CI 0·67-0·87], ptrend<0·0001; saturated fat, HR 0·86 [0·76-0·99], ptrend=0·0088; monounsaturated fat: HR 0·81 [0·71-0·92], ptrend<0·0001; and polyunsaturated fat: HR 0·80 [0·71-0·89], ptrend<0·0001). Higher saturated fat intake was associated with lower risk of stroke (quintile 5 vs quintile 1, HR 0·79 [95% CI 0·64-0·98], ptrend=0·0498). Total fat and saturated and unsaturated fats were not significantly associated with risk of myocardial infarction or cardiovascular disease mortality.
Interpretation:
High carbohydrate intake was associated with higher risk of total mortality, whereas total fat and individual types of fat were related to lower total mortality. Total fat and types of fat were not associated with cardiovascular disease, myocardial infarction, or cardiovascular disease mortality, whereas saturated fat had an inverse association with stroke. Global dietary guidelines should be reconsidered in light of these findings.
Funding:
Full funding sources listed at the end of the paper (see Acknowledgments).
Background:
Obesity is one of the leading causes of preventable death worldwide. Circadian rhythms are known to control both sleep timing and energy homeostasis, and disruptions in circadian rhythms have been linked with metabolic dysfunction and obesity-associated disease. In previous research, social jetlag, a measure of chronic circadian disruption caused by the discrepancy between our internal versus social clocks, was associated with elevated self-reported body mass index, possibly indicative of a more generalized association with obesity and metabolic dysfunction.
Methods:
We studied participants from the population-representative Dunedin Longitudinal Study (N=1037) to determine whether social jetlag was associated with clinically assessed measurements of metabolic phenotypes and disease indicators for obesity-related disease, specifically, indicators of inflammation and diabetes.
Results:
Our analysis was restricted to N=815 non-shift workers in our cohort. Among these participants, we found that social jetlag was associated with numerous clinically assessed measures of metabolic dysfunction and obesity. We distinguished between obese individuals who were metabolically healthy versus unhealthy, and found higher social jetlag levels in metabolically unhealthy obese individuals. Among metabolically unhealthy obese individuals, social jetlag was additionally associated with elevated glycated hemoglobin and an indicator of inflammation.
Conclusions:
The findings are consistent with the possibility that 'living against our internal clock' may contribute to metabolic dysfunction and its consequences. Further research aimed at understanding that the physiology and social features of social jetlag may inform obesity prevention and have ramifications for policies and practices that contribute to increased social jetlag, such as work schedules and daylight savings time.
Objective: Increasing evidence suggests an association between insomnia and cardiovascular disease. We performed a systematic review with meta-analysis of all the available prospective studies that investigated the association between insomnia and risk of developing and/or dying from cardiovascular disease.Design: Systematic review and meta-analysis of prospective cohort studies.Methods: We conducted an electronic literature search through MedLine, Embase, Google Scholar, Web of Science, The Cochrane Library and bibliographies of retrieved articles up to December 2011. Studies were included if they were prospective, had assessment of insomnia or sleep complaints at baseline, evaluated subjects free of cardiovascular disease at baseline and measured the association between insomnia and risk of developing and/or dying from cardiovascular disease.Results: After the review process 13 prospective studies were included in the final analysis. These studies included 122,501 subjects followed for a time ranging from three to 20 years. A total of 6332 cardiovascular events occurred during the follow-up. Insomnia was assessed through questionnaire and defined as either difficulty of initiating or maintaining sleep or presence of restless, disturbed nights. The cumulative analysis for all the studies under a random-effects model showed that insomnia determined an increased risk (+45%) of developing or dying from cardiovascular disease during the follow-up (relative risk 1.45, 95% confidence interval 1.29-1.62; p < 0.00001), with no evidence of heterogeneity across the studies (I(2): 19%; p = 0.14).Conclusion: Insomnia is associated with an increased risk of developing and/or dying from cardiovascular disease.
AimsTo assess the relationship between duration of sleep and morbidity and mortality from coronary heart disease (CHD), stroke, and total cardiovascular disease (CVD).Methods and resultsWe performed a systematic search of publications using MEDLINE (19662009), EMBASE (from 1980), the Cochrane Library, and manual searches without language restrictions. Studies were included if they were prospective, follow-up >3 years, had duration of sleep at baseline, and incident cases of CHD, stroke, or CVD. Relative risks (RR) and 95 confidence interval (CI) were pooled using a random-effect model. Overall, 15 studies (24 cohort samples) included 474 684 male and female participants (follow-up 6.925 years), and 16 067 events (4169 for CHD, 3478 for stroke, and 8420 for total CVD). Sleep duration was assessed by questionnaire and incident cases through certification and event registers. Short duration of sleep was associated with a greater risk of developing or dying of CHD (RR 1.48, 95 CI 1.221.80, P < 0.0001), stroke (1.15, 1.001.31, P 0.047), but not total CVD (1.03, 0.931.15, P 0.52) with no evidence of publication bias (P 0.95, P 0.30, and P 0.46, respectively). Long duration of sleep was also associated with a greater risk of CHD (1.38, 1.151.66, P 0.0005), stroke (1.65, 1.451.87, P < 0.0001), and total CVD (1.41, 1.191.68, P < 0.0001) with no evidence of publication bias (P 0.92, P 0.96, and P 0.79, respectively).Conclusion
Both short and long duration of sleep are predictors, or markers, of cardiovascular outcomes.
Increasing evidence suggests an association between both short and long duration of habitual sleep with adverse health outcomes.
To assess whether the population longitudinal evidence supports the presence of a relationship between duration of sleep and all-cause mortality, to investigate both short and long sleep duration and to obtain an estimate of the risk.
We performed a systematic search of publications using MEDLINE (1966-2009), EMBASE (from 1980), the Cochrane Library, and manual searches without language restrictions. We included studies if they were prospective, had follow-up >3 years, had duration of sleep at baseline, and all-cause mortality prospectively. We extracted relative risks (RR) and 95% confidence intervals (CI) and pooled them using a random effect model. We carried out sensitivity analyses and assessed heterogeneity and publication bias.
Overall, the 16 studies analyzed provided 27 independent cohort samples. They included 1,382,999 male and female participants (followup range 4 to 25 years), and 112,566 deaths. Sleep duration was assessed by questionnaire and outcome through death certification. In the pooled analysis, short duration of sleep was associated with a greater risk of death (RR: 1.12; 95% CI 1.06 to 1.18; P < 0.01) with no evidence of publication bias (P = 0.74) but heterogeneity between studies (P = 0.02). Long duration of sleep was also associated with a greater risk of death (1.30; [1.22 to 1.38]; P < 0.0001) with no evidence of publication bias (P = 0.18) but significant heterogeneity between studies (P < 0.0001).
Both short and long duration of sleep are significant predictors of death in prospective population studies.
Physical inactivity is a global concern, but diverse physical activity measures in use prevent international comparisons. The International Physical Activity Questionnaire (IPAQ) was developed as an instrument for cross-national monitoring of physical activity and inactivity.
Between 1997 and 1998, an International Consensus Group developed four long and four short forms of the IPAQ instruments (administered by telephone interview or self-administration, with two alternate reference periods, either the "last 7 d" or a "usual week" of recalled physical activity). During 2000, 14 centers from 12 countries collected reliability and/or validity data on at least two of the eight IPAQ instruments. Test-retest repeatability was assessed within the same week. Concurrent (inter-method) validity was assessed at the same administration, and criterion IPAQ validity was assessed against the CSA (now MTI) accelerometer. Spearman's correlation coefficients are reported, based on the total reported physical activity.
Overall, the IPAQ questionnaires produced repeatable data (Spearman's rho clustered around 0.8), with comparable data from short and long forms. Criterion validity had a median rho of about 0.30, which was comparable to most other self-report validation studies. The "usual week" and "last 7 d" reference periods performed similarly, and the reliability of telephone administration was similar to the self-administered mode.
The IPAQ instruments have acceptable measurement properties, at least as good as other established self-reports. Considering the diverse samples in this study, IPAQ has reasonable measurement properties for monitoring population levels of physical activity among 18- to 65-yr-old adults in diverse settings. The short IPAQ form "last 7 d recall" is recommended for national monitoring and the long form for research requiring more detailed assessment.
Study objectives:
The aim of this study was to investigate the association of bedtime with the prevalence of diabetes mellitus (DM) based on a large community-based population.
Methods:
In total, 5,420 participants (2,574 males and 2,846 females; aged 63.5 ± 11.0 years) from the Sleep Heart Health Study database were selected in this study. Sleep habit was recorded based on a questionnaire administered to patients upon recruitment. Bedtime was categorized as 11:00 pm and before, 11:00 pm to 12:00 am, and 12:00 am and later in the current study. Multivariate logistic regression was used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) to determine the relationship between bedtime and the prevalence of DM.
Results:
The distribution of weekday bedtime at 11:00 pm and before, 11:00 pm to 12:00 am, 12:00 am and later was observed in 3,316 participants (61.2%), 991 participants (18.3%), and 1,113 participants (20.5%), respectively. Meanwhile, individuals with weekday bedtime of 12:00 am and later had a higher prevalence of DM than those with bedtime at 11:00 pm to 12:00 am, and 11:00 pm and before (10.6% versus 5.7% versus 6.6%, respectively; P < .001). In the adjusted multivariate logistic regression model, bedtime at 12:00 am and later on a weekday was significantly associated DM prevalence (OR 1.446, 95% CI 1.107-1.888, P = .007). No significant association was found between weekend bedtime and DM.
Conclusion:
Late bedtime at 12:00 am and later on a weekday may be a risk factor for the prevalence of DM. Stable sleep timing leads to lower risk of DM deserves future exploration.
Background:
Physical activity has a protective effect against cardiovascular disease (CVD) in high-income countries, where physical activity is mainly recreational, but it is not known if this is also observed in lower-income countries, where physical activity is mainly non-recreational. We examined whether different amounts and types of physical activity are associated with lower mortality and CVD in countries at different economic levels.
Methods:
In this prospective cohort study, we recruited participants from 17 countries (Canada, Sweden, United Arab Emirates, Argentina, Brazil, Chile, Poland, Turkey, Malaysia, South Africa, China, Colombia, Iran, Bangladesh, India, Pakistan, and Zimbabwe). Within each country, urban and rural areas in and around selected cities and towns were identified to reflect the geographical diversity. Within these communities, we invited individuals aged between 35 and 70 years who intended to live at their current address for at least another 4 years. Total physical activity was assessed using the International Physical Activity Questionnaire (IPQA). Participants with pre-existing CVD were excluded from the analyses. Mortality and CVD were recorded during a mean of 6·9 years of follow-up. Primary clinical outcomes during follow-up were mortality plus major CVD (CVD mortality, incident myocardial infarction, stroke, or heart failure), either as a composite or separately. The effects of physical activity on mortality and CVD were adjusted for sociodemographic factors and other risk factors taking into account household, community, and country clustering.
Findings:
Between Jan 1, 2003, and Dec 31, 2010, 168 916 participants were enrolled, of whom 141 945 completed the IPAQ. Analyses were limited to the 130 843 participants without pre-existing CVD. Compared with low physical activity (<600 metabolic equivalents [MET] × minutes per week or <150 minutes per week of moderate intensity physical activity), moderate (600-3000 MET × minutes or 150-750 minutes per week) and high physical activity (>3000 MET × minutes or >750 minutes per week) were associated with graded reduction in mortality (hazard ratio 0·80, 95% CI 0·74-0·87 and 0·65, 0·60-0·71; p<0·0001 for trend), and major CVD (0·86, 0·78-0·93; p<0·001 for trend). Higher physical activity was associated with lower risk of CVD and mortality in high-income, middle-income, and low-income countries. The adjusted population attributable fraction for not meeting the physical activity guidelines was 8·0% for mortality and 4·6% for major CVD, and for not meeting high physical activity was 13·0% for mortality and 9·5% for major CVD. Both recreational and non-recreational physical activity were associated with benefits.
Interpretation:
Higher recreational and non-recreational physical activity was associated with a lower risk of mortality and CVD events in individuals from low-income, middle-income, and high-income countries. Increasing physical activity is a simple, widely applicable, low cost global strategy that could reduce deaths and CVD in middle age.
Funding:
Population Health Research Institute, the Canadian Institutes of Health Research, Heart and Stroke Foundation of Ontario, Ontario SPOR Support Unit, Ontario Ministry of Health and Long-Term Care, AstraZeneca, Sanofi-Aventis, Boehringer Ingelheim, Servier, GSK, Novartis, King Pharma, and national and local organisations in participating countries that are listed at the end of the Article.
Background:
The association between intake of fruits, vegetables, and legumes with cardiovascular disease and deaths has been investigated extensively in Europe, the USA, Japan, and China, but little or no data are available from the Middle East, South America, Africa, or south Asia.
Methods:
We did a prospective cohort study (Prospective Urban Rural Epidemiology [PURE] in 135 335 individuals aged 35 to 70 years without cardiovascular disease from 613 communities in 18 low-income, middle-income, and high-income countries in seven geographical regions: North America and Europe, South America, the Middle East, south Asia, China, southeast Asia, and Africa. We documented their diet using country-specific food frequency questionnaires at baseline. Standardised questionnaires were used to collect information about demographic factors, socioeconomic status (education, income, and employment), lifestyle (smoking, physical activity, and alcohol intake), health history and medication use, and family history of cardiovascular disease. The follow-up period varied based on the date when recruitment began at each site or country. The main clinical outcomes were major cardiovascular disease (defined as death from cardiovascular causes and non-fatal myocardial infarction, stroke, and heart failure), fatal and non-fatal myocardial infarction, fatal and non-fatal strokes, cardiovascular mortality, non-cardiovascular mortality, and total mortality. Cox frailty models with random effects were used to assess associations between fruit, vegetable, and legume consumption with risk of cardiovascular disease events and mortality.
Findings:
Participants were enrolled into the study between Jan 1, 2003, and March 31, 2013. For the current analysis, we included all unrefuted outcome events in the PURE study database through March 31, 2017. Overall, combined mean fruit, vegetable and legume intake was 3·91 (SD 2·77) servings per day. During a median 7·4 years (5·5-9·3) of follow-up, 4784 major cardiovascular disease events, 1649 cardiovascular deaths, and 5796 total deaths were documented. Higher total fruit, vegetable, and legume intake was inversely associated with major cardiovascular disease, myocardial infarction, cardiovascular mortality, non-cardiovascular mortality, and total mortality in the models adjusted for age, sex, and centre (random effect). The estimates were substantially attenuated in the multivariable adjusted models for major cardiovascular disease (hazard ratio [HR] 0·90, 95% CI 0·74-1·10, ptrend=0·1301), myocardial infarction (0·99, 0·74-1·31; ptrend=0·2033), stroke (0·92, 0·67-1·25; ptrend=0·7092), cardiovascular mortality (0·73, 0·53-1·02; ptrend=0·0568), non-cardiovascular mortality (0·84, 0·68-1·04; ptrend =0·0038), and total mortality (0·81, 0·68-0·96; ptrend<0·0001). The HR for total mortality was lowest for three to four servings per day (0·78, 95% CI 0·69-0·88) compared with the reference group, with no further apparent decrease in HR with higher consumption. When examined separately, fruit intake was associated with lower risk of cardiovascular, non-cardiovascular, and total mortality, while legume intake was inversely associated with non-cardiovascular death and total mortality (in fully adjusted models). For vegetables, raw vegetable intake was strongly associated with a lower risk of total mortality, whereas cooked vegetable intake showed a modest benefit against mortality.
Interpretation:
Higher fruit, vegetable, and legume consumption was associated with a lower risk of non-cardiovascular, and total mortality. Benefits appear to be maximum for both non-cardiovascular mortality and total mortality at three to four servings per day (equivalent to 375-500 g/day).
Funding:
Full funding sources listed at the end of the paper (see Acknowledgments).
Background:
Inadequate sleep duration, sleep patterns, and sleep quality have been associated with metabolic, circadian, and behavioral changes that promote obesity. Adolescence is a period during which sleep habits change to include less sleep, later bedtimes, and greater bedtime shift (e.g., difference between weekend and weekday bedtime). Thus, sleep may play a role in adolescent obesity and weight-related behaviors. This study assesses sleep duration, quality, and schedules and their relationships to relative weight and body fat percentage as well as diet, physical activity, and screen time in adolescents with overweight/obesity.
Methods:
Adolescents between 12 and 17 years old (n = 186) were weighed and measured, reported typical sleep and wake times on weekdays and weekends, and responded to questionnaires assessing diet, physical activity, and screen time habits.
Results:
Controlling for sleep duration, later weekend bedtime and greater bedtime shift were associated with greater severity of overweight (β = 0.20; β = 0.16) and greater screen time use (β = 0.22; β = 0.2). Later bedtimes on the weekdays and weekends were associated with fewer healthy diet practices (β = -0.26; β = -0.27). In addition, poorer sleep quality was associated with fewer healthy diet habits (β = -0.21), greater unhealthy diet habits (β = 0.15), and less physical activity (β = -0.22). Sleep duration was not associated with any weight or weight-related behavior.
Conclusions:
Sleep patterns and quality are associated with severity of overweight/obesity and various weight-related behaviors. Promoting a consistent sleep schedule throughout the week may be a worthwhile treatment target to optimize behavioral and weight outcomes in adolescent obesity treatment.
Inadequate sleep has negative effect on health including obesity, diabetes, and cardiovascular diseases. Current evidence showed that delayed night sleep may impair endocrine function, disrupt glucose metabolism and promote abnormal weight gain, irrespective of caloric intake. The aim of this analysis was to investigate the longitudinal relation between bedtime, salivary glucose levels, and waist circumference among Kuwaiti children. Repeated measures data were collected from 6316 children 8–14 years old at two time points: 2012 and 2014. Children were approximately equally distributed among 138 elementary schools representing the six governorates of Kuwait. Trained examiners conducted body weight measurements, sleep evaluation interviews, and collected saliva samples. Mixed-effect multivariate linear regression model was conducted to determine the longitudinal relationship between bedtime and the rate of change in abdominal obesity. Other explanatory variables, mediator, or potential confounders assessed were glucose level (>1.13 mg/dL), systolic blood pressure, fitness, ethnicity, and gender. There was a significant increase of waist circumference with later bedtime over time (P < 0.05). A higher salivary glucose level (higher than 1.13 mg/dL) was a positive partial mediator in the relation between bedtime and waist circumference. There were statistically significant variations between schools across time (P < 0.05). Longitudinal analysis of Kuwaiti children revealed that going to bed late increases salivary glucose (and presumably plasma glucose) and predicts abdominal obesity in Kuwaiti children with strong clustering effect within schools over time.
Study objectives:
Recent studies implicate inadequate sleep duration and quality in metabolic disease. Fewer studies have examined the timing of sleep, which may be important because of its potential impact on circadian rhythms of metabolic function. We examined the association between sleep timing and metabolic risk among Hispanic/Latino adults.
Methods.:
Cross-sectional data from community-based study of 13,429 participants aged 18-74 years. People taking diabetes medications were excluded. Sleep timing was determined from self-reported bedtimes and wake times. Chronotype was defined as the midpoint of sleep on weekends adjusted for sleep duration on weekdays. Other measurements included body mass index (BMI), fasting glucose levels, estimated insulin resistance (HOMA-IR), glucose levels 2 hours post oral glucose ingestion, and hemoglobin A1c. Survey linear regression models tested associations between sleep timing and metabolic measures. Analyses were stratified by diabetes status and age group when significant interactions were observed.
Results.:
Among participants with diabetes, fasting glucose levels were positively associated with bedtime (approximately +3%/hour later, p<.01) and midpoint of sleep (approximately +2%/hour later, p<.05). In participants with and without diabetes combined, HOMA-IR was positively associated with midpoint of sleep (+1.5%/hour later, p<.05), and chronotype (+1.2%/hour later, p<.05). Associations differed by age group. Among those <36 years, later sleep timing was associated with lower BMI, lower fasting glucose, and lower HbA1c, but the opposite association was observed among older participants.
Conclusions.:
Later sleep timing was associated with higher estimated insulin resistance across all groups. Some associations between sleep timing and metabolic measures may be age-dependent.
Sleep is increasingly recognized as an important lifestyle contributor to health. However, this has not always been the case, and an increasing number of Americans choose to curtail sleep in favor of other social, leisure, or work-related activities. This has resulted in a decline in average sleep duration over time. Sleep duration, mostly short sleep, and sleep disorders have emerged as being related to adverse cardiometabolic risk, including obesity, hypertension, type 2 diabetes mellitus, and cardiovascular disease. Here, we review the evidence relating sleep duration and sleep disorders to cardiometabolic risk and call for health organizations to include evidence-based sleep recommendations in their guidelines for optimal health.
Clinic-based observational studies in men have reported that obstructive sleep apnea is associated with an increased incidence of coronary heart disease. The objective of this study was to assess the relation of obstructive sleep apnea to incident coronary heart disease and heart failure in a general community sample of adult men and women.
A total of 1927 men and 2495 women > or =40 years of age and free of coronary heart disease and heart failure at the time of baseline polysomnography were followed up for a median of 8.7 years in this prospective longitudinal epidemiological study. After adjustment for multiple risk factors, obstructive sleep apnea was a significant predictor of incident coronary heart disease (myocardial infarction, revascularization procedure, or coronary heart disease death) only in men < or =70 years of age (adjusted hazard ratio 1.10 [95% confidence interval 1.00 to 1.21] per 10-unit increase in apnea-hypopnea index [AHI]) but not in older men or in women of any age. Among men 40 to 70 years old, those with AHI > or =30 were 68% more likely to develop coronary heart disease than those with AHI <5. Obstructive sleep apnea predicted incident heart failure in men but not in women (adjusted hazard ratio 1.13 [95% confidence interval 1.02 to 1.26] per 10-unit increase in AHI). Men with AHI > or =30 were 58% more likely to develop heart failure than those with AHI <5.
Obstructive sleep apnea is associated with an increased risk of incident heart failure in community-dwelling middle-aged and older men; its association with incident coronary heart disease in this sample is equivocal.