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Sleep hygiene recommendations discourage eating before bedtime; however, the impact of mealtime on sleep has been inconsistent. We examined gender-stratified associations between eating or drinking <1, <2 and <3 h before bedtime, sleep duration and wake after sleep onset (WASO >30 min). This study utilised 2003–2018 data from the American Time Use Survey, a nationally representative sample of USA residents aged ≥15 years. Participants recorded weekday/weekend activities during a 24-h period. Age-specific sleep duration and WASO were estimated categorically and continuously. Eating or drinking were identified from all activities recorded <1, <2 and <3 h before bedtime. Mean ± se sleep duration was 8·0 ± 0·006 h, and 6% of participants ate or drank <1 h prior to weekdays bedtime. Overall, eating or drinking <1 h prior to bedtime was associated with longer weekdays sleep duration. Women and men who ate or drank <1 h before bedtime, v. those who did not, had 35 min (95% CI (30,39)) and 25 min (95 % CI (21,29)) longer sleep duration, respectively, as well as increased odds of WASO; women (OR=2·03, 95% CI (1·66,2·49)) and men (OR=2·64, 95% CI (2·08,3·36)). As the interval of eating or drinking prior to bedtime expanded, odds of short and long sleep durations and WASO decreased. This population-based data linked eating or drinking <1 h before bedtime to longer sleep duration, but increased WASO. Eating or drinking further from bedtime lowers the odds of short and long sleep duration and WASO. Causal pathways are difficult to discern, though inefficient sleep after late-night eating could increase WASO and trigger compensatory increases in sleep duration. [ABSTRACT FROM AUTHOR]

Summary: Physiological evidence suggests that sleep modulates kidney function. Our objective was to examine the cross‐sectional association between kidney function and objectively‐estimated habitual sleep duration, quality and timing in a cohort of patients with mild to moderate chronic kidney disease. This study involved two US clinical centers of the Chronic Renal Insufficiency Cohort (CRIC) study, including 432 participants in a CRIC ancillary sleep study. Habitual sleep duration, quality and timing were measured using wrist actigraphy for 5–7 days. Validated sleep questionnaires assessed subjective sleep quality, daytime sleepiness and risk of sleep apnea. Kidney function was assessed with the estimated glomerular filtration rate using the Chronic Kidney Disease Epidemiology Collaboration equation, and the urinary protein to creatinine ratio. Lower estimated glomerular filtration rate was associated with shorter sleep duration (−1.1 mL min−1 1.73 m−2 per hour less sleep, P = 0.03), greater sleep fragmentation (−2.6 mL min−1 1.73 m−2 per 10% higher fragmentation, P < 0.001) and later timing of sleep (−0.9 mL min−1 1.73 m−2 per hour later, P = 0.05). Higher protein to creatinine ratio was also associated with greater sleep fragmentation (approximately 28% higher per 10% higher fragmentation, P < 0.001). Subjective sleep quality, sleepiness and persistent snoring were not associated with estimated glomerular filtration rate or protein to creatinine ratio. Thus, worse objective sleep quality was associated with lower estimated glomerular filtration rate and higher protein to creatinine ratio. Shorter sleep duration and later sleep timing were also associated with lower estimated glomerular filtration rate. Physicians treating patients with chronic kidney disease should consider inquiring about sleep and possibly sending for clinical sleep assessment. Longitudinal and interventional trials are needed to understand causal direction. [ABSTRACT FROM AUTHOR]

The authors respond to the commentary "How Much Do We Really Sleep?," by Stuart Quan. They express enjoyment in reading Quan's perspective on the importance of sleep. They note that Quan addressed two possible sources of bias: that actigraphy might underestimate sleep compared with other measurement modes and that actigraphy is sleep deprived. The authors agree that persons in metropolitan areas in the U.S. might sleep less than other persons. They express excitement about the growing epidemiologic interest in sleep.

Background: In addition to quantity and quality, meal timing and eating duration are additional dietary characteristics that impact cardiometabolic health. Given that cardiometabolic health disparities exist among racial and ethnic groups, we examined whether meal timing and eating duration are additional diet-related differences among racial and ethnic groups. Methods: Participants (n = 13,084) were adults (≥20 years) from the National Health and Nutrition Examination (NHANES, 2011−2018) Survey. Times of first and last meal and the interval between them (eating duration) were derived from two 24-h dietary recalls. Multiple linear regression analyses compared these variables among race and ethnicity after adjusting for potential confounders. Results: Compared to non-Hispanic White adults, the first mealtime was significantly later for Mexican American (23 min), Non-Hispanic Asian (15 min), Non-Hispanic Black (46 min), and Other Hispanic (20 min) and Other Racial (14 min) adults (all p < 0.05). Mexican American and Non-Hispanic Asian adults had a significantly different last mealtime by 13 min earlier and 25 min later, respectively, compared to Non-Hispanic White adults. Compared to Non-Hispanic White adults, the mean eating duration was shorter for other Hispanic (20 min), Mexican American (36 min), and Non-Hispanic Black (49 min) adults. Conclusions: Meal timing and eating duration are additional dietary characteristics that vary significantly among racial and ethnic groups.

Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs)., Methods: The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy., Results: Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics., Conclusions: The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs)., Methods: The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease., Results: Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics., Conclusions: The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Background: The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs)., Methods: The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2020 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals., Results: Each of the 26 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics., Conclusions: The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Objectives: Although numerous studies have reported negative associations between sleep duration and body size, no studies of this association have focused on Hispanic groups, which was the goal of this work., Methods: Data are from adults in the 1982-1984 Hispanic Health and Nutrition Examination Survey (HHANES), which enrolled Cuban-Americans, Mexican-Americans, and Puerto Ricans. HHANES included self-reported sleep duration and several anthropometric measures. Principle component analysis extracted a single variable to represent body size. Linear regression models stratified by Hispanic group predicted body size from sleep duration adjusting for age, sex, education, income, marital status, household size, and acculturation., Results: Average age was 36-44 years and 52-64% were women. Average sleep duration was 7.3-7.7 h. Shorter sleep duration was associated with larger body size in Mexican-Americans only. The regression coefficient indicated that on average a Mexican-American adult who reported sleeping for 4 h would have a body size that was larger by 0.12 times the standard deviation for body size than a Mexican-American adult reporting 8 h of sleep (all other covariates being equal). This effect was similar to the effect of 10 years of age, which would be associated with an increase in body size by 0.10 times the standard deviation of body size., Conclusions: These results underscore the importance of examining factors associated with obesity in different ethnic groups. It may be inappropriate to combine different Hispanic ethnicities together., (© 2010 Wiley-Liss, Inc.)

Study Objectives: To determine (1) whether short sleep has increased over 31 years; (2) whether trends in short sleep differed by employment status; (3) which sociodemographic factors predict short sleep; and (4) how short sleepers spend their time., Design: Time diaries from eight national studies conducted between 1975 and 2006., Patients or Participants: U.S. adults > or = 18 years., Measurements and Results: Short sleepers were defined as those reporting < 6 hours of sleep in their time diary. Unadjusted percentages of short sleepers ranged from 7.6% in 1975 to 9.3% in 2006. The 1998-99 study had the highest odds of short sleep. The odds ratio for the 31-year period predicting short sleep was 1.14 (95% CI: 0.92, 1.50, P = 0.22), adjusting for age, sex, education, employment, race, marital status, income, and day of week. When stratified by employment, there was a significant increase for full-time workers (P = 0.05), who represented over 50% of participants in all studies, and a significant decrease for students (P = 0.01), who represented < 5% of participants. The odds of short sleep were lower for women, those > or = 65 years, Asians, Hispanics, and married people. The odds were higher for full-time workers, those with some college education, and African Americans. Short sleepers in all employment categories spent more time on personal activities. Short sleepers who were full- and part-time workers spent much more time working., Conclusions: Based on time diaries, the increase in the odds of short sleep over the past 31 years was significant among full-time workers only. Work hours are much longer for full-time workers sleeping < 6 hours.

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.

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 > or =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.

Many hormones play important roles in both pubertal development and sleep regulation. Because of the possible consequences of impaired sleep, including impaired health and cognition, it is important to examine whether an association between pubertal stage and sleep exists. The aim of this analysis is to examine the association between sleep and adolescent growth and developmental stage in a large sample of adolescents ages 12-16 years from a nationally representative longitudinal study. This analysis used the public-use data set of the National Longitudinal Study of Adolescent Health, an extensive survey of health and behavior among adolescents in the United States. The study included two interviews approximately 1 year apart. Pubertal development, sleep variables, and height are self-reported. Pubertal development scores were calculated by summing responses to three questions for each sex. The sleep variables include sleep duration, frequent insomnia (once/week or more), frequently waking tired (once/week or more), and insufficient sleep. The results indicate a sex difference in the association between sleep problems and pubertal development. Among females, there was a significant increase in sleep problems with increasing pubertal development score, but not among males. The negative association between sleep duration and pubertal development score, however, was significant in both males and females. There is no association between sleep duration and height velocity (inches/year) in this sample. The results, which are based on a large sample size, warrant further examination with more objective measures into the association between sleep and growth and development among adolescents., (Copyright 2005 Wiley-Liss, Inc)