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Background Little is known about the contribution of genetic variation to food timing, and breakfast has been determined to exhibit the most heritable meal timing. As breakfast timing and skipping are not routinely measured in large cohort studies, alternative approaches include analyses of correlated traits. Objectives The aim of this study was to elucidate breakfast skipping genetic variants through a proxy-phenotype genome-wide association study (GWAS) for breakfast cereal skipping, a commonly assessed correlated trait. Methods We leveraged the statistical power of the UK Biobank (n  = 193,860) to identify genetic variants related to breakfast cereal skipping as a proxy-phenotype for breakfast skipping and applied several in silico approaches to investigate mechanistic functions and links to traits/diseases. Next, we attempted validation of our approach in smaller breakfast skipping GWAS from the TwinUK (n  = 2,006) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium (n  = 11,963). Results In the UK Biobank, we identified 6 independent GWAS variants, including those implicated for caffeine (ARID3B/CYP1A1), carbohydrate metabolism (FGF21), schizophrenia (ZNF804A), and encoding enzymes important for N 6-methyladenosine RNA transmethylation (METTL4, YWHAB , and YTHDF3), which regulates the pace of the circadian clock. Expression of identified genes was enriched in the cerebellum. Genome-wide correlation analyses indicated positive correlations with anthropometric traits. Through Mendelian randomization (MR), we observed causal links between genetically determined breakfast skipping and higher body mass index, more depressive symptoms, and smoking. In bidirectional MR, we demonstrated a causal link between being an evening person and skipping breakfast, but not vice versa. We observed association of our signals in an independent breakfast skipping GWAS in another British cohort (P =  0.032), TwinUK, but not in a meta-analysis of non-British cohorts from the CHARGE consortium (P  = 0.095). Conclusions Our proxy-phenotype GWAS identified 6 genetic variants for breakfast skipping, linking clock regulation with food timing and suggesting a possible beneficial role of regular breakfast intake as part of a healthy lifestyle. [ABSTRACT FROM AUTHOR]

In recent years, strong evidence has emerged suggesting that insufficient duration, quality, and/or timing of sleep are associated with cardiovascular disease (CVD), and various mechanisms for this association have been proposed. Such associations may be related to endophenotypic features of the sleep homeostat and the circadian oscillator, or may be state-like effects of the environment. Here, we review recent literature on sleep, circadian rhythms and CVD with a specific emphasis on differences between racial/ethnic groups. We discuss the reported differences, mainly between individuals of European and African descent, in parameters related to sleep (architecture, duration, quality) and circadian rhythms (period length and phase shifting). We further review racial/ethnic differences in cardiovascular disease and its risk factors, and develop the hypothesis that racial/ethnic health disparities may, to a greater or smaller degree, relate to differences in parameters related to sleep and circadian rhythms. When humans left Africa some 100,000 years ago, some genetic differences between different races/ethnicities were acquired. These genetic differences have been proposed as a possible predictor of CVD disparities, but concomitant differences in culture and lifestyle between different groups may equally explain CVD disparities. We discuss the evidence for genetic and environmental causes of these differences in sleep and circadian rhythms, and their usefulness as health intervention targets. [ABSTRACT FROM AUTHOR]

Abstract: Sleep is a biological imperative associated with cardiometabolic disease risk. As such, a thorough discussion of the sociocultural and demographic determinants of sleep is warranted, if not overdue. This paper begins with a brief review of the laboratory and epidemiologic evidence linking sleep deficiency, which includes insufficient sleep and poor sleep quality, with increased risk of chronic cardiometabolic diseases such as obesity, diabetes and hypertension. Identification of the determinants of sleep deficiency is the critical next step to understanding the role sleep plays in human variation in health and disease. Therefore, the majority of this paper describes the different biopsychosocial determinants of sleep, including age, gender, psychosocial factors (depression, stress and loneliness), socioeconomic position and race/ethnicity. In addition, because sleep duration is partly determined by behavior, it will be shaped by cultural values, beliefs and practices. Therefore, possible cultural differences that may impact sleep are discussed. If certain cultural, ethnic or social groups are more likely to experience sleep deficiency, then these differences in sleep could increase their risk of cardiometabolic diseases. Furthermore, if the mechanisms underlying the increased risk of sleep deficiency in certain populations can be identified, interventions could be developed to target these mechanisms, reduce sleep differences and potentially reduce cardiometabolic disease risk. [Copyright &y& Elsevier]

Laboratory studies have found that short-term sleep restriction is associated with impairments in glucose metabolism, appetite regulation and blood pressure regulation. This chapter reviews the epidemiologic evidence for an association between habitual sleep duration and quality and risk of cardiometabolic diseases including obesity, diabetes and hypertension. Multiple studies observed a cross-sectional association between short sleep duration (generally <6 h per night) and increased body mass index or obesity, prevalent diabetes and prevalent hypertension. Many studies also reported an association between self-reported long sleep duration (generally >8 h per night) and cardiometabolic disease. There have been a few prospective studies and several, but not all, have found an association between short sleep and incident diabetes, hypertension and markers of cardiovascular disease. Future prospective epidemiologic studies need to include objective measures of sleep, and intervention studies are needed in order to establish a causal link between impaired or insufficient sleep and cardiometabolic disease risk. [ABSTRACT FROM AUTHOR]

Objective: To examine bed times and wake times in US adolescents aged 15 to 17 years using time diaries to determine whether adolescent sleep has changed in recent years and what factors determine bed times and wake times. Study design: Time diary analysis using 2 national probability samples: 1981 Time Use Longitudinal Panel Study (n = 130) and 2003-2006 American Time Use Survey (n = 2978). Results: Average time in bed on school days was about 8 hours and was 1 to 2 hours longer on non-school days. Bed times and wake times were similar in 1981 and 2003-2006. Sociodemographic factors and daytime activities, specifically computer use and social activities, predicted bed time. On school days, school start time was the strongest predictor of wake time. Every hour earlier that school started, wake time was about 25 minutes earlier. Conclusions: Adolescents spent less than the recommended 9 hours in bed on school days. There is no evidence that this is a recent change in bed times and wake times, however. Although many factors influence bed time, school start time is the strongest determinant of wake time on school days. Increased computer use and earlier school days may be contributing to insufficient sleep in adolescents. [Copyright &y& Elsevier]

Summary: The prevalence of diabetes and obesity is increasing at an alarming rate worldwide, and the causes of this pandemic are not fully understood. Chronic sleep curtailment is a behavior that has developed over the past 2–3 decades. Laboratory and epidemiological studies suggest that sleep loss may play a role in the increased prevalence of diabetes and/or obesity. Current data suggest the relationship between sleep restriction, weight gain and diabetes risk may involve at least three pathways: (1) alterations in glucose metabolism; (2) upregulation of appetite; and (3) decreased energy expenditure. The present article reviews the current evidence in support of these three mechanisms that might link short sleep and increased obesity and diabetes risk. [Copyright &y& Elsevier]

Objective: To determine whether an association between short sleep duration and increased body mass index (BMI) exists in a sample of U.S. adolescents. Study design: Public-use dataset of the National Longitudinal Study of Adolescent Health. Final sample included 4486 adolescents (51% female). Main outcome was BMI transformed into z-scores for age and sex using reference values from the Centers for Disease Control/National Center for Health Statistics. Overweight was defined as ≥95th percentile. Linear and logistic regression models were calculated. Sleep duration was self-reported in hours. A quadratic term for sleep was added to test curvilinear association. Covariates included age, race, parental education, activity and inactivity scores. Results: Among males, linear regression indicated that sleep duration significantly predicted BMI z-score (Beta = −0.08, 95% CI: −0.12, −0.03). Logistic regression indicated that sleep duration predicted risk of overweight among males (OR = 0.90, 95% CI: 0.82, 1.00). Sleep duration was not a significant predictor among females in either regression model. Quadratic term for sleep was not significant for either sex. Conclusions: Longer sleep duration was weakly associated with lower BMI and risk of overweight among male adolescents only. This sex-related difference may be due to differences in the physiology of puberty or in sleep characteristics. [Copyright &y& Elsevier]

Aim: To test the association between cardiometabolic risk factors and subjective sleep quality assessed by the Pittsburgh sleep quality index (PSQI), independent of obstructive sleep apnea (OSA) and sleep duration.Methods: A total of 573 participants from the Baependi Heart Study, a rural cohort from Brazil, completed sleep questionnaires and underwent polygraphy for OSA evaluation. Multivariable linear regression analysis tested the association between cardiovascular risk factors (outcome variables) and sleep quality measured by PSQI, adjusting for OSA and other potential confounders (age, sex, race, salary/wage, education, marital status, alcohol intake, obesity, smoking, hypertension, and sleep duration).Results: The sample mean age was 43 ± 16 years, 66% were female, and mean body mass index (BMI) was 26 ± 5 kg/m2. Only 20% were classified as obese (BMI ≥30). Overall, 50% of participants reported poor sleep quality as defined by a PSQI score ≥5. A high PSQI score was significantly associated with higher very-low-density lipoprotein (VLDL) cholesterol levels (beta = 0.392, p = 0.012) and higher triglyceride levels (beta = 0.017, p = 0.006), even after adjustments, including the apnea-hypopnea index. Further adjustments accounting for marital status, alcohol intake, and medication use did not change these findings. No significant association was observed between PSQI scores and glucose or blood pressure. According to PSQI components, sleep disturbances (beta = 1.976, p = 0.027), sleep medication use (beta = 1.121, p = 0.019), and daytime dysfunction (beta = 1.290, p = 0.024) were significantly associated with higher VLDL serum levels. Only the daytime dysfunction domain of the PSQI components was significantly associated with higher triglyceride levels (beta = 0.066, p = 0.004).Conclusion: Poorer lipid profile was independently associated with poor sleep quality, assessed by the PSQI questionnaire, regardless of a normal sleep duration and accounting for OSA and socio-economic status. [ABSTRACT FROM AUTHOR]