Self-reported Daytime Napping Research Articles

Self-reported daytime napping, daytime sleepiness, and other sleep phenotypes in the development of cardiometabolic diseases: a Mendelian randomization study.

Sleep disorders are associated with an increased risk of cardiometabolic diseases in observational studies, but the causality remains unclear. In this study, we leveraged two-sample Mendelian randomization (MR) analyses to assess the causal associations of self-reported daytime napping, daytime sleepiness, and other sleep phenotypes with cardiometabolic diseases including ischaemic stroke (IS), coronary artery disease (CAD), heart failure (HF), and Type 2 diabetes mellitus (T2DM). We selected genetic variants as instrumental variables for self-reported daytime napping, daytime sleepiness, morning person, insomnia, short sleep duration, and long sleep duration from European-descent genome-wide association studies (GWASs). Summary statistics for cardiometabolic diseases originated from four different GWASs with a total of 2 500 086 participants. We used the inverse-variance weighted method to explore the role of self-reported sleep phenotypes on the aetiology of cardiometabolic diseases in the main analyses, followed by several sensitivity analyses for robustness validation. Genetically predicted self-reported daytime napping [T2DM: OR, 1.56 (95% confidence interval, 1.21-2.02)], insomnia [IS: OR, 1.07 (1.04-1.11)]; CAD: OR, 1.13 (1.08-1.17); HF: OR, 1.10 (1.07-1.14); T2DM: OR, 1.16 (1.11-1.22); and short sleep duration [CAD: OR, 1.37 (1.21-1.55)] were causally associated with an elevated risk of cardiometabolic diseases. Moreover, genetically determined self-reported daytime sleepiness [CAD: OR, 2.05 (1.18-3.57); HF: OR, 1.82 (1.15-2.87)] and morning person [HF: 1.06 OR, (1.01-1.11)] had potential detrimental effect on cardiometabolic risks. Self-reported daytime napping, insomnia, and short sleep duration had causal roles in the development of cardiometabolic diseases, while self-reported daytime sleepiness and morning person was the potential risk factor for cardiometabolic diseases.

0424 Influence of daytime napping on the discrepancy between subjective and objective nighttime sleep measures in pregnant women with insomnia

Abstract Introduction Previous research has documented a tendency among adults with insomnia to underestimate nighttime sleep duration compared to actigraphy estimates. We examined whether discrepancy in nighttime sleep parameters is impacted by daytime napping behavior. Methods We used baseline data from a randomized controlled trial of insomnia treatment during pregnancy for this cross-sectional analysis (n=97). Women self-reported daytime napping and nighttime sleep characteristics using a 7-day sleep diary and wore an Actiwatch 2 during the same 7-day period. Two women napped daily and were excluded from this analysis. The remaining sample was categorized as intermittent nappers [naps on some but not all days; n=62 (65%)] or non-nappers [no naps on any days; n=33 (35%)]. We summarized daily discrepancy between self-reported and actigraphy-measured nighttime sleep duration and efficiency by daytime napping behavior using means and t-tests. Results Intermittent nappers provided data for 130 days with naps and 260 days without naps. Non-nappers provided data for 198 days. Among intermittent nappers, there was no meaningful subjective-objective discrepancy for nighttime sleep duration or efficiency (mean discrepancy=1 minute for duration; -0.4% for efficiency); this did not differ between days with naps and days without naps (p=0.98 for sleep duration; p=0.33 for sleep efficiency). Among non-nappers, subjective-objective discrepancy was present (intermittent nappers vs non-nappers p=0.001 for duration; p=0.04 for efficiency), with self-report underestimating actigraphy-measured nighttime sleep duration by 28 minutes and nighttime sleep efficiency by 3.5%. Conclusion Pregnant women with insomnia who did not nap tended to underestimate nighttime sleep duration and efficiency compared to actigraphy measurement, as has been reported in the general population of adults with insomnia. However, there was no meaningful subjective-objective discrepancy for nighttime sleep duration and efficiency among those who napped intermittently, regardless of that day’s napping behavior. It is possible that daytime napping impacts overall accuracy of perceived nighttime sleep. However, because some people with insomnia are unable to nap even when given the opportunity, it is possible that not napping and sleep discrepancy share a common underlying cause. Future research is needed to test if results replicate to non-pregnant populations and explore mechanisms that may explain these findings. Support (If Any) National Institutes of Health (K99HD100585, R01NR013662)

Genetic determinants of daytime napping and effects on cardiometabolic health

Daytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remain unclear. Here, we perform a genome-wide association study of self-reported daytime napping in the UK Biobank (n = 452,633) and identify 123 loci of which 61 replicate in the 23andMe research cohort (n = 541,333). Findings include missense variants in established drug targets for sleep disorders (HCRTR1, HCRTR2), genes with roles in arousal (TRPC6, PNOC), and genes suggesting an obesity-hypersomnolence pathway (PNOC, PATJ). Association signals are concordant with accelerometer-measured daytime inactivity duration and 33 loci colocalize with loci for other sleep phenotypes. Cluster analysis identifies three distinct clusters of nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization shows potential causal links between more frequent daytime napping and higher blood pressure and waist circumference.

0016 Genetic Basis of Daytime Napping and Consequence on Cardiometabolic Health

Abstract Introduction Although daytime napping is a common, evolutionarily conserved behavior, its genetic basis is unknown. Elucidating its genetic basis may clarify relevant underlying biological pathways and determine causal links with cardiometabolic health. Methods We performed a genome-wide association study of self-reported daytime napping using linear regression in adults of European ancestry in the UK Biobank (n=452,633) and assessed robustness of signals with accelerometer-derived daytime inactivity duration (n=84,671). Next, we conducted a phenome-wide association study in a hospital-based clinical biobank (n=30,683) using napping genome-wide polygenic score (GPS), and Mendelian randomization (MR) with cardiometabolic traits. To deconstruct the napping genetic variants, we applied a novel “soft clustering” Bayesian nonnegative matrix factorization method and generated partitioned cluster-specific polygenic risk scores (PRS). Results We identified 121 distinct genome-wide significant loci for daytime napping, with lead signals at or near genes KSR2 (kinase-suppressor of ras 2), HCRTR1/HCRTR2 (hypocretin-receptor 1/2), SKOR2 (SKI family transcriptional-corepressor 2), and MAPT (microtubule-associated protein tau), among others. The loci associated with accelerometer-derived daytime inactivity duration. Gene enrichment analyses pointed to pathways involved in neurogenesis and others including nervous system development and opioid signaling. Genetic overlaps were evident in a clinical biobank where highest, compared to lowest, decile of napping GPS associated with 30%, 40%, and 50% higher odds for essential hypertension, obesity, and nonalcoholic liver disease, respectively (P<0.0001). In MR, potential causal links were identified with higher diastolic blood pressure (2.67 mmHg per napping category-increase, 95% CI 1.62–3.23, P=6.80e-07), systolic blood pressure (3.65mmHg, 1.86–5.44, P=6.40e-05), and waist circumference (0.28 SD-units, 0.11–0.45, P=0.0015). The clustering of variants identified 3 robust clusters (cluster-1: “higher sleep propensity”; cluster-2: “more fragmented/inefficient night sleep”; cluster-3: “early sleep timing”). Only clusters 2 and 3 PRSs were associated with worse cardiometabolic health outcomes, including higher BMI, waist circumference, CRP, and triglycerides (all P<0.05). Conclusion These findings expand our understanding of the genetic architecture of napping implicating multiple biological pathways, indicating possible genetic overlap and causal links to cardiometabolic traits, and suggesting distinct nap-promoting mechanisms with differential associations with health outcomes. Support This work is supported by grants NIH-F32DK102323, NIH-4T32HL007901, NIH-R01DK107859, NIH-R35HL135818, and MGH Research Scholar Fund.

Is disrupted sleep a risk factor for Alzheimer's disease? Evidence from a two-sample Mendelian randomization analysis.

BackgroundIt is established that Alzheimer’s disease (AD) patients experience sleep disruption. However, it remains unknown whether disruption in the quantity, quality or timing of sleep is a risk factor for the onset of AD.MethodsWe used the largest published genome-wide association studies of self-reported and accelerometer-measured sleep traits (chronotype, duration, fragmentation, insomnia, daytime napping and daytime sleepiness), and AD. Mendelian randomization (MR) was used to estimate the causal effect of self-reported and accelerometer-measured sleep parameters on AD risk.ResultsOverall, there was little evidence to support a causal effect of sleep traits on AD risk. There was some suggestive evidence that self-reported daytime napping was associated with lower AD risk [odds ratio (OR): 0.70, 95% confidence interval (CI): 0.50–0.99). Some other sleep traits (accelerometer-measured ‘eveningness’ and sleep duration, and self-reported daytime sleepiness) had ORs of a similar magnitude to daytime napping, but were less precisely estimated.ConclusionsOverall, we found very limited evidence to support a causal effect of sleep traits on AD risk. Our findings provide tentative evidence that daytime napping may reduce AD risk. Given that this is the first MR study of multiple self-report and objective sleep traits on AD risk, findings should be replicated using independent samples when such data become available.

Association of Daytime Napping and Diagnosed Diabetes in Middle-Aged Premenopausal, Middle-Aged Postmenopausal, and Older Postmenopausal Chinese Women

To examine associations of daytime napping and diagnosed diabetes in middle-aged premenopausal, middle-aged postmenopausal, and older postmenopausal Chinese women. Quantitative, cross-sectional. 2015 cross-sectional data from China Health and Retirement Longitudinal Study. Participants were recruited from 150 counties/districts and 450 villages/resident committees. Six thousand nine hundred and forty women aged 45 years and older (mean age = 61 years) stratified by age and menopausal status. The outcome was self-reported diagnosed diabetes. The exposure was self-reported daytime napping (0, >0-≤60, or >60 min/d). Participants were stratified to middle-aged premenopausal, middle-aged postmenopausal, and older postmenopausal women according to their age (≤60 or >60 years) and menopausal status. One-way analysis of variance and χ2 tests were conducted to explore differences on characteristics of middle-aged premenopausal, middle-aged postmenopausal, and older postmenopausal women. Multiple logistic regressions were used to estimate adjusted odds ratios (ORs) for diagnosed diabetes according to daytime napping in the total sample, middle-aged premenopausal, middle-aged postmenopausal, and older postmenopausal Chinese women. Participants' mean self-reported daytime napping duration was 34 minutes. Women who napped more than 60 minutes were more likely to report diagnosed diabetes (OR = 1.39, 95% confidence interval (CI), 1.09-1.76) comparing to those who did not nap, after adjusting for potential confounders. No statistical significance of interaction term between daytime napping and age/menopausal status was detected (P = .602 and P = .558) among total women. The stratified analysis revealed the significant association among middle-aged postmenopausal women napping more than 60 minutes (OR = 1.81, 95% CI, 1.18-2.77). The association, however, was found to be insignificant in middle-aged premenopausal women and older postmenopausal women. Long daytime nap (>60 min/d) was associated with diagnosed diabetes in middle-aged postmenopausal women in China.

Association of daytime napping with incident cardiovascular disease in a community-based population

ObjectiveTo investigate the association between self-reported daytime napping habits and cardiovascular disease (CVD) in a large community-based study population. MethodsOf the 4170 participants, 55.5% were women and the mean age was 63.1 years (SD, 11.0 years). CVD included cardiovascular death, congestive heart failure, myocardial infarction, stroke, angina, and revascularization and was defined as the first confirmed incidence of CVD during an average 11-year follow-up. Self-reported daytime napping habits were recorded using baseline questionnaires. Backward stepwise Cox regression analysis was used to explore the relationship between CVD and napping habits. ResultsIn this study, 914 participants with CVD (21.9%) were observed. Participants who took regular long naps had a higher prevalence of incident CVD than did those who took regular short naps, irregular naps, or no naps (34.5% vs. 28.4%, 22.4%, 16.6%, respectively; P < 0.001). In the final backward stepwise Cox regression model, regular long naps were found to be associated with CVD (HR: 1.403, 95% CI: 1.079–1.825, P = 0.012). ConclusionsRegular long daytime napping was an independent risk factor for CVD. Healthy sleep habits may promote human health and prevent CVD. Clinical trial registrationClinicalTrials.gov Identifier: NCT00005275.

Meta-analysis of self-reported daytime napping and risk of cardiovascular or all-cause mortality.

BackgroundWhether self-reported daytime napping is an independent predictor of cardiovascular or all-cause mortality remains unclear. The aim of this study was to investigate self-reported daytime napping and risk of cardiovascular or all-cause mortality by conducting a meta-analysis.Material/MethodsA computerized literature search of PubMed, Embase, and Cochrane Library was conducted up to May 2014. Only prospective studies reporting risk ratio (RR) and corresponding 95% confidence intervals (CI) of cardiovascular or all-cause mortality with respect to baseline self-reported daytime napping were included.ResultsSeven studies with 98,163 subjects were included. Self-reported daytime napping was associated with a greater risk of all-cause mortality (RR 1.15; 95% CI 1.07–1.24) compared with non-nappers. Risk of all-cause mortality appeared to be more pronounced among persons with nap duration >60 min (RR 1.15; 95% CI 1.04–1.27) than persons with nap duration <60 min (RR 1.10; 95% CI 0.92–1.32). The pooled RR of cardiovascular mortality was 1.19 (95% CI 0.97–1.48) comparing daytime nappers to non-nappers.ConclusionsSelf-reported daytime napping is a mild but statistically significant predictor for all-cause mortality, but not for cardiovascular mortality. However, whether the risk is attributable to excessive sleep duration or napping alone remains controversial. More prospective studies stratified by sleep duration, napping periods, or age are needed.