UNASSIGNED: Time-restricted eating (TRE), a dietary pattern reducing the duration of daily food consumption, has recently gained popularity. Existing studies show the potential benefits of TRE for cardiometabolic health. Uncertainty remains about whether these benefits are solely from altered meal timing or influences on other health behaviors, including sleep. Despite growing scientific interest in the effects of TRE on sleep parameters, the topic has not been systematically explored.
UNASSIGNED: This review examined the effects of TRE interventions (daily fasting duration ≥14 h) lasting at least 8 weeks on objective and subjective sleep parameters. Six randomized control trials were identified through Pubmed, Embase, Google Scholar, and Scopus through September 2023.
UNASSIGNED: Of the included studies, three employed objective sleep measures using wearables and five studies assessed sleep subjectively through self-report questionnaires. Only one study reported significant improvements in subjective sleep quality following a TRE intervention. Additionally, one study found significant decreases in sleep duration, two studies found significant decreases in sleep efficiency, and one found significant increases in sleep onset latency.
UNASSIGNED: Current evidence indicates that short to mid-term TRE does not typically worsen sleep parameters. However, some populations may experience reduced sleep disturbances, while others may experience reductions in sleep efficiency. Longer duration studies with objective sleep assessments are needed to better understand the effects of TRE on sleep parameters.

UNASSIGNED: This protocol paper outlines the methods that will be used to examine the impact of altering meal timing on metabolism, cognitive performance, and mood during the simulated night shift.
UNASSIGNED: Participants (male and female) will be recruited according to an a priori selected sample size to complete a 7-day within and between participant\'s laboratory protocol. Participants will be randomly assigned to one of the three conditions: meal at night or snack at night or no meal at night. This protocol includes an 8-hour nighttime baseline sleep, followed by 4 consecutive nights of simulated nightshift (7 hours day sleep; 10:00-17:00 hours), and an 8-hour nighttime sleep (return to dayshift). During the simulated night shift, meals will be provided at ~06:30, 09:30, 14:10, and 19:00 hours (no eating at night); ~06:30, 19:00, and 00:30 hours (meal at night); or ~06:30, 14:10, 19:00, and 00:30 hours (snack at night). Meal composition will be strictly controlled throughout the study (45%-65% carbohydrates, 15%-25% protein, and 20%-35% fat per day) with daily energy provided to meet individual needs using the Harris-Benedict equation (light/sedentary activity). The primary outcome measures are serum concentrations of blood glucose, insulin, and free fatty acids area under the curve in response to the oral glucose tolerance test. Mixed-effect ANOVAs will be conducted.
UNASSIGNED: This protocol paper describes a methodology to describe an innovative approach to reduce the metabolic disease impact associated with shift work.

BACKGROUND: Preliminary evidence suggests that meal timing is associated with higher quality diets. Less is known about whether types of food consumed during specific eating episodes (i.e., day-level eating patterns) predict diet quality.
OBJECTIVE: We investigated the association between day-level eating patterns and diet quality.
METHODS: Decision tree models were built using 24-h dietary recall data from the National Health and Nutrition Examination Survey 2015 and 2017 cycles in a cross-sectional study. Sixteen food groups and 12 eating episodes (e.g., breakfast, lunch) were included as input parameters. Diet quality was scored using the Healthy Eating Index-2020 and categorized as higher or lower quality diets based on the median score. Mean decrease in impurity (MDI) ± standard deviation determined the relative contribution that day-level eating patterns had on diet quality; higher values represented greater contributions.
RESULTS: We analyzed 12,597 dietary recalls from 9347 United States adults who were aged 18 y and older with ≥1 complete recall. Meals (breakfast, lunch, dinner) and respective snacking episodes had the greatest variety of dietary groups that contributed to the Healthy Eating Index-2020 score. Any whole-grain intake at breakfast predicted a higher quality diet (MDI = 0.08 ± 0.00), followed by lower solid fat intake (<8.94 g; MDI = 0.07 ± 0.00) and any plant protein intake at dinner (MDI = 0.05 ± 0.00).
CONCLUSIONS: Day-level eating patterns were associated with diet quality, emphasizing the relevance of both food type and timing in relation to a high-quality diet. Future interventions should investigate the potential impact of targeting food type and timing to improve diet quality.

An emerging field of research has revealed a bidirectional relationship between sleep and diet, highlighting the potential role of a healthy diet in improving sleep. However, the impact of chrono-nutrition on sleep remains less explored. Here we conducted a systematic scoping review, considering the multiple dimensions of chrono-nutrition, to describe the extent, range, and nature of the existing literature in this area (PROSPERO: CRD42021274637). There has been a significant increase in the literature exploring this topic over the past six years (almost 67 % of the evolving literature). A breakdown of the included studies was performed according to three major chrono-nutritional dimensions: meal timing [n = 35], irregular eating patterns [n = 84], and frequency of eating occasions [n = 3]. Meal timing included three sub-dimensions: breakfast skipping [n = 13], late eating [n = 16], and earlier vs later meals schedules [n = 6]. Irregular meal patterns included three sub-dimensions: diurnal fasting [n = 65], intermittent fasting [n = 16], and daily meal patterns [n = 3]. Frequency was the least studied dimension (n = 3). We provided a synthetic and illustrative framework underlining important preliminary evidence linking the temporal characteristics of eating patterns to various facets of sleep health. Nonetheless, much work remains to be done to provide chrono-nutrition guidelines to improve sleep health in the general population.

This observational pilot study examined the association between diet, meal pattern and glucose over a 2-week period under free-living conditions in 26 adults with dysglycemia (D-GLYC) and 14 with normoglycemia (N-GLYC). We hypothesized that a prolonged eating window and late eating occasions (EOs), along with a higher dietary carbohydrate intake, would result in higher glucose levels and glucose variability (GV). General linear models were run with meal timing with time-stamped photographs in real time, and diet composition by dietary recalls, and their variability (SD), as predictors and glucose variables (mean glucose, mean amplitude of glucose excursions [MAGE], largest amplitude of glucose excursions [LAGE] and GV) as dependent variables. After adjusting for calories and nutrients, a later eating midpoint predicted a lower GV (β = -2.3, SE = 1.0, p = 0.03) in D-GLYC, while a later last EO predicted a higher GV (β = 1.5, SE = 0.6, p = 0.04) in N-GLYC. A higher carbohydrate intake predicted a higher MAGE (β = 0.9, SE = 0.4, p = 0.02) and GV (β = 0.4, SE = 0.2, p = 0.04) in N-GLYC, but not D-GLYC. In summary, our data suggest that meal patterns interact with dietary composition and should be evaluated as potential modifiable determinants of glucose in adults with and without dysglycemia. Future research should evaluate causality with controlled diets.

BACKGROUND: Limited data exist examining whether timing and/or duration of eating behaviors throughout the day affect sleep health.
OBJECTIVE: The aim of this study was to identify the relationship between eating behaviors and sleep in young adults without chronic diseases or conditions.
METHODS: This was a cross-sectional study using 7 days of baseline data from a randomized crossover trial.
METHODS: Participants included 52 young adults. The study took place in West Lafayette, Indiana, between April 2017 and May 2018.
METHODS: Timing and duration of eating were assessed via 3 nonconsecutive, 24-hour dietary recalls. Bedtime, wake time, total sleep time, sleep latency, sleep efficiency, and wake after sleep onset were measured over 7 days via wrist actigraphy and sleep diaries.
METHODS: Two-way analyses of variance were applied to assess group differences based on timing of consumption (early vs late eating) and duration of eating (long: >13 hours, short: <11 hours, or standard: 11-13 hours) with post-hoc pairwise comparisons.
RESULTS: Main effects of timing of consumption, but not duration of eating, were detected for wake time, bedtime, and sleep efficiency (all, P < .05). Specifically, participants with later eating patterns that included breakfast skipping had later wake times and later bedtimes than those with earlier eating patterns. In addition, those who had later eating patterns that included breakfast skipping and nighttime eating experienced lower sleep efficiency (mean [SE], 77.0% [2.3%]) vs those who consumed breakfast and no nighttime eating (mean [SE], 84.6% [1.4%]; P < .001) and those who skipped breakfast but had no nighttime eating (mean [SE], 84.2% [2.5]; P < .05). Those who consumed breakfast but also had nighttime eating had a mean (SE) sleep efficiency of 82.4% (1.4%) (P = .09).
CONCLUSIONS: The timing of eating was associated with sleep-wake onset and sleep efficiency. This study provides the preliminary characterization of eating behaviors relative to sleep-wake cycles and highlights the need for experimental studies to understand whether manipulating the timing of eating occasions to better align with sleep-wake cycles could improve sleep health.

The irregular eating patterns of both shift workers and evening chronotypes adversely affect cardiometabolic health. A tool that conveniently captures temporal patterns of eating alongside an indicator of circadian rhythm such as chronotype will enable researchers to explore relationships with diverse health outcome measures. We aimed to investigate the test-retest reliability and convergent validity of a Chrononutrition Questionnaire (CNQ) that captures temporal patterns of eating and chronotype in the general population (non-shift workers, university students, retirees, unemployed individuals) and shift work population. Participants attended two face-to-face/virtual sessions and completed the CNQ and food/sleep/work diaries. Outcomes included subjective chronotype, wake/sleep/mid-sleep time, sleep duration, meal/snack regularity, meal/snack/total frequency, times of first/last/largest eating occasions (EO), main meal (MM) 1/2/3, and duration of eating window (DEW). 116 participants enrolled (44.5 ± 16.5 years, BMI: 27.3 ± 5.8 kg/m2, 73% female, 52% general population); 105 completed the study. Reliability was acceptable for chronotype, sleep, and all temporal eating patterns except on night shifts. Convergent validity was good for chronotype and sleep except for certain shift/shift-free days. Generally, meal/snack regularity and frequency, and times of first/last EO showed good validity for the general population but not shift workers. Validity was good for DEW (except work-free days and afternoon shifts) and times of MM 1/2/3 (except afternoon and night shifts), while time of largest EO had poor validity. The CNQ has good test-retest reliability and acceptable convergent validity for the general and shift work population, although it will benefit from further validation, especially regarding regularity, frequency, and times of first and last eating occasions across more days amongst a larger sample size of shift workers. Use of the CNQ by researchers will expand our current understanding of chrononutrition as relationships between timing of food intake and the multitude of health outcomes are examined.

Meal timing emerges as a crucial factor influencing metabolic health that can be explained by the tight interaction between the endogenous circadian clock and metabolic homeostasis. Mistimed food intake, such as delayed or nighttime consumption, leads to desynchronization of the internal circadian clock and is associated with an increased risk for obesity and associated metabolic disturbances such as type 2 diabetes and cardiovascular diseases. Conversely, meal timing aligned with cellular rhythms can optimize the performance of tissues and organs. In this review, we provide an overview of the metabolic effects of meal timing and discuss the underlying mechanisms. Additionally, we explore factors influencing meal timing, including internal determinants such as chronotype and genetics, as well as external influences like social factors, cultural aspects, and work schedules. This review could contribute to defining meal-timing-based recommendations for public health initiatives and developing guidelines for effective lifestyle modifications targeting the prevention and treatment of obesity and associated metabolic diseases. Furthermore, it sheds light on crucial factors that must be considered in the design of future food timing intervention trials.

OBJECTIVE: Late mealtime and short sleep are known to be associated with obesity risk due to a misaligned circadian rhythm. This study aimed to investigate the relationship between obesity and mealtime and sleep duration using the Korean Genome and Epidemiology Study (KoGES) data.
METHODS: Longitudinally prospective cohort study.
METHODS: Population-based.
METHODS: KoGES analysed data from 9,474 Korean adults with an average age of 54- years old at baseline.
METHODS: Meal timing was defined as the eating occasions of the day reported by the participant eating a 24-h dietary recall method. Sleep duration was categorized as <6, 6-7, 7-8, and ≥8 h. The Cox proportional hazard model was used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for incident obesity according to meal timing, sleep duration, and nightly fasting duration.
RESULTS: During a mean follow-up of 3.5 years, 826 participants developed obesity. In the multivariable-adjusted analysis, midnight snack eating (HR, 1.20; 95% CI, 1.02-1.41) and higher energy intake from midnight snacks (HR, 1.26; 95% CI, 1.06-1.49) were associated with a higher risk of obesity. Sleeping 8 h or more (HR, 0.67; 95% CI, 0.53-0.85) was associated with a lower risk of obesity.
CONCLUSIONS: Our findings highlight the importance of meal and sleep times and suggest that healthy eating habits related to the time of day.

Meal timing plays a crucial role for cardiometabolic health, given the circadian regulation of cardiometabolic function. However, to the best of our knowledge, no concept of meal timing exists in traditional European medicine (TEM). Therefore, in this narrative review, we aim to define the optimal time slot for energy intake and optimal energy distribution throughout the day in a context of TEM and explore further implications. By reviewing literature published between 2002 and 2022, we found that optimal timing for energy intake may be between 06:00 and 09:00, 12:00 and 14:00, and between 15:00 and 18:00, with high energy breakfast, medium energy lunch and low energy dinner and possibly further adjustments according to one\'s chronotype and genetics. Also, timing and distribution of energy intake may serve as a novel therapeutic strategy to optimize coction, a concept describing digestion and metabolism in TEM. Please cite this article as: Eberli NS, Colas L, Gimalac A. Chrononutrition in traditional European medicine-Ideal meal timing for cardiometabolic health promotion. J Integr Med. 2024; 22(2);115-125.