Chrononutrition is a rapidly evolving field of nutritional epidemiology that addresses the complex relationship between temporal eating patterns, circadian rhythms, and metabolic health, but most prior research has focused on the cardiometabolic consequences of time-restricted feeding and intermittent fasting. The purpose of this topical review is to summarize epidemiological evidence from observational and intervention studies regarding the role of chrononutrition metrics related to eating timing and regularity in cardiometabolic health preservation and cardiovascular disease prevention. Observational studies are limited due to the lack of time-stamped diet data in most population-based studies. Findings from cohort studies generally indicate that breakfast skipping or the later timing of the first eating occasion, a later lunch and dinner, and a greater proportion of caloric intake consumed in the evening are associated with adverse cardiometabolic outcomes, including higher risk for coronary heart disease, hypertension, type 2 diabetes, obesity, dyslipidemia, and systemic inflammation. Randomized controlled trials are also limited, as most in the field of chrononutrition focus on the cardiometabolic consequences of time-restricted feeding. Overall, interventions that shift eating timing patterns to earlier in the day and that restrict evening caloric intake tend to have protective effects on cardiometabolic health, but small sample sizes and short follow-up are notable limitations. Innovation in dietary assessment approaches, to develop low-cost validated tools with acceptable participant burden that reliably capture chrononutrition metrics, is needed for advancing observational evidence. Culturally responsive pragmatic intervention studies with sufficiently large and representative samples are needed to understand the impact of fixed and earlier eating timing schedules on cardiometabolic health. Additional research is warranted to understand the modifiable determinants of temporal eating patterns, to investigate the role of chrononutrition in the context of other dimensions of diet (quantity, quality, and food and nutrition security) in achieving cardiometabolic health equity, and to elucidate underlying physiological mechanisms.

UNASSIGNED: Chrononutrition studies the relation between diet, circadian rhythms and metabolism, which may alter the metabolic intrauterine environment, influencing infant fat-mass (FM) development and possibly increasing obesity risk.
UNASSIGNED: To evaluate the association of chrononutrition in pregnancy and infant FM at 6 months.
UNASSIGNED: Healthy pregnant women and term-babies (n = 100pairs) from the OBESO cohort (2017-2023) were studied. Maternal registries included pregestational body-mass-index (BMI), gestational complications/medications, weight gain. Diet (three 24 h-recalls, 1 each trimester) and sleep-schedule (first and third trimesters) were evaluated computing fasting (hours from last-first meal), breakfast and dinner latencies (minutes between wake up-breakfast and dinner-sleep, respectively), number of main meals/day, meal skipping (≥1 main meal/d on three recalls) and nighttime eating (from 9:00 pm-5:59 am on three recalls). Neonatal weight, length, BMI/age were assessed. At 6 months, infant FM (kg, %; air-displacement plethysmography) was measured, and FM index (FMI-kgFM/length2) computed. Exclusive breastfeeding (EBF) was recorded. Multiple linear regression models evaluated the association between chrononutrition and 6 month infant FM.
UNASSIGNED: Mean fasting was 11.7 ± 1.3 h; breakfast, dinner latency were 87.3 ± 75.2, 99.6 ± 65.6 min, respectively. Average meals/day were 3.0 ± 0.5. Meal skipping was reported in 3% (n = 3) of women and nighttime eating in 35% (n = 35). Most neonates had normal BMI/age (88%, n = 88). Compared to those who did not, mothers engaged in nighttime-eating had infants with higher %FM (p = 0.019). Regression models (R 2 ≥ 0.308, p ≤ 0.001) showed that nighttime eating was positively associated with %FM (B: 2.7, 95%CI: 0.32-5.16). When analyzing women without complications/medications (n = 80), nighttime eating was associated with higher FM [%FM, B: 3.24 (95%CI: 0.59-5.88); kgFM, B: 0.20 (95%CI: 0.003-0.40); FMI, B: 0.54 (95%CI: 0.03-1.05)]. Infant sex and weight (6 months) were significant, while maternal obesity, pregnancy complications/medications, parity, energy intake, birth-BMI/age, and EBF were not.
UNASSIGNED: Maternal nighttime eating is associated with higher adiposity in 6 month infants.

Optimal nutrition is essential for health and physiological performance. Nutrition-related diseases such as obesity and diabetes are major causes of death and reduced quality of life in modern Western societies. Thanks to combining nutrigenetics and nutrigenomics, genomic nutrition allows the study of the interaction between nutrition, genetics and physiology. Currently, interrelated multi-genetic and multifactorial phenotypes are studied from a multiethnic and multi-omics approach, step by step identifying the important role of pathways, in addition to those directly related to metabolism. It allows the progressive identification of genetic profiles associated with specific susceptibilities to diet-related phenotypes, which may facilitate individualised dietary recommendations to improve health and quality of life.

Circadian rhythms in humans are biological rhythms that regulate various physiological processes within a 24-hour time frame. Critical illness can disrupt the circadian rhythm, as can environmental and clinical factors, including altered light exposure, organ replacement therapies, disrupted sleep-wake cycles, noise, continuous enteral feeding, immobility, and therapeutic interventions. Nonpharmacological interventions, controlling the ICU environment, and pharmacological treatments are among the treatment strategies for circadian disruption. Nutrition establishes biological rhythms in metabolically active peripheral tissues and organs through appropriate synchronization with endocrine signals. Therefore, adhering to a feeding schedule based on the biological clock, a concept known as \"chrononutrition,\" appears to be vitally important for regulating peripheral clocks. Chrononutritional approaches, such as intermittent enteral feeding that includes overnight fasting and consideration of macronutrient composition in enteral solutions, could potentially restore circadian health by resetting peripheral clocks. However, due to the lack of evidence, further studies on the effect of chrononutrition on clinical outcomes in critical illness are needed. The purpose of this review was to discuss the role of chrononutrition in regulating biological rhythms in critical illness, and its impact on clinical outcomes.

OBJECTIVE: We aimed to evaluate the association of temporal patterns of food consumption with cardiovascular disease (CVD) risk.
METHODS: This cross-sectional study included male rotating shift workers in an iron ore extraction company. Data on food consumption was collected using a 24 h recall, applied by trained interviewers. The variables for temporal patterns of food consumption were: eating window, eating at night, number of meals and omission of breakfast. CVD-risk was measured by calculating the Framingham coronary heart disease risk score (FCRS), and classified as low risk or intermediate to high risk. Descriptive, univariate and multivariate logistic regression analyses examined the association between variables related to temporal patterns of food consumption and CVD-risk.
RESULTS: The study assessed 208 workers, the majority with 20-34 years (45.1%), non-white (77.2%), and 5 years or more in shift work (76.0%). Most participants had a feeding window exceeding 12 h (63.9%), consumed meals until 10 p.m. (68.1%), had five or more meals per day (54.8%), and did not skip breakfast (86.5%). Regarding CVD-risk, 43.8% of the participants were classified with intermediate to high risk for CVD. In the multivariate model, a feeding window (OR: 2.32; 95%CI: 1.01-5.35), eating after 10 p.m. (OR: 3.31; 95%CI: 1.01-11.0), and skipping breakfast (OR: 2.58; 95%CI: 1.07-6.19) increased the likelihood of intermediate to high CVD-risk. Conversely, having five or more meals per day decreased the odds (OR: 0.27; 95%CI: 0.08-0.92).
CONCLUSIONS: Eating window longer than 12 h, eating after 10 p.m., less than four meals a day and omission of breakfast, are associated with cardiovascular risk in shift workers.

The concept of Circadian Syndrome (CircS) aims to emphasize the circadian disruptions underlying cardiometabolic conditions. Meal timing and shiftwork may disrupt circadian rhythms, increasing cardiometabolic risk. This study aimed to assess the associations of meal timing, meal skipping, and shiftwork with CircS in US adults and explore effect modifications by sociodemographic and lifestyle factors. CircS was defined using Metabolic Syndrome components in addition to short sleep and depression symptoms. Data from 10,486 participants of the National Health and Nutrition Examination Survey 2005-2016 were analyzed cross-sectionally. Mealtime was assessed by calculating the midpoint of intake between breakfast and dinner and dichotomizing it into favorable mealtime (between 12:30 and 13:15) and unfavorable mealtime using a data-driven approach. Meal skippers were categorized separately. Participants working evening, night, or rotating shifts were classified as shift workers. In the multivariable logistic regression analysis, an unfavorable mealtime, meal skipping, and shiftwork were associated with a higher likelihood of CircS (OR = 1.24; 95%CI 1.07-1.44, OR = 1.39; 95%CI 1.16-1.67, and OR = 1.37; 95%CI 1.01-1.87, respectively). Subgroup analyses revealed no significant interactions between meal timing, meal skipping, or shiftwork and socioeconomic status or lifestyle regarding CircS. These findings highlight the importance of aligning mealtimes with circadian rhythms for improved circadian health.

Chrononutrition, an emerging body of evidence on the relationship between biological rhythms and metabolism, has been established to be associated with glycemic responses. However, the available evidence is inconsistent, due to protocol variations. Therefore, this review aims to summarize the findings on chrononutrition characteristics and their association with glycemic responses among adults. Systematic searches were conducted across six databases (PubMed, EBSCO Host, ProQuest Central, MEDLINE & Ovid, Scopus and Web of Science) to identify all relevant studies published from January 2012. Two reviewers independently screened the abstracts and full-text articles based on the inclusion and exclusion criteria. Details about population characteristics, study methods and key findings were extracted following the PRISMA-ScR guideline. The quality of selected studies was evaluated using the mixed methods appraisal tool. The searchers identified 49 studies eligible for analysis. The results showed that meal timing, particularly night-time eating and snacking were associated with glycemic responses. Regarding meal regularity, skipping breakfast may affect glycemic responses, but no clear conclusion was drawn about its effect on insulin. The association between meal frequency and glycemic responses was inconclusive. Night fasting duration and restricted eating window are potentially associated with glycemic responses. The current review extensively investigates the association between chrononutrition factors and glycemic responses in adults. However, more prospective cohort and interventional studies are needed to better understand this causal-effect relationship.

OBJECTIVE: Here, we present a systematic review that compiles in vivo experimental data regarding the effect of the WD on the gut microbiota and its impact on the circadian rhythm. Additionally, we reviewed studies evaluating the combined effects of WD and circadian cycle disruption on gut microbiota and circadian cycle markers.
METHODS: The original studies indexed in PubMed/Medline, Scopus, and Web of Science databases were screened according to the PRISMA strategy.
RESULTS: Preclinical studies revealed that WD triggers circadian rhythmicity disruption, reduces the alpha-diversity of the microbiota and favors the growth of bacterial groups that are detrimental to intestinal homeostasis, such as Clostridaceae, Enterococcus, Parasutterella and Proteobacteria. When the WD is combined with circadian clock disruption, gut dysbiosis become more pronounced. Reduced cycling of Per3, Rev-erb and CLOCK in the intestine, which are related to dysregulation of lipid metabolism and potential metabolic disease, was observed.
CONCLUSIONS: In conclusion, current evidence supports the potential of WD to trigger microbiota dysregulation, disrupt the biological clock, and increase susceptibility to metabolic disorders and potentially chronic diseases.

UNASSIGNED: In response to the COVID-19 pandemic, educational institutions had to swiftly adapt and transition to remote teaching in order to maintain academic activities. However, these changes presented a number of challenges for professors, which could have negative effects on their health.
OBJECTIVE: To analyze the association between changes in dietary and sleep habits, physical activity level, and sedentary behavior with the development of non-communicable diseases (NCDs) among Brazilian higher education professors during the pandemic period.
METHODS: This is a cross-sectional and retrospective study conducted using an online form. Generalized linear models, adjusted for age, sex, and body mass index, were used to verify the difference between pre-pandemic and pandemic periods. Logistic regression models were used to predict the odds ratio (OR) for the development of NCDs according to physical activity time, sedentary behavior time, dietary and sleep patterns.
RESULTS: A total of 936 professors residing across Brazil participated in the survey. The duration of sedentary behavior increased, sleep duration slightly decreased, and meal times shifted to earlier during the pandemic. A total of 22.9%of the participants reported the diagnosis of some NCDs during this period. Physical activity practice was associated with a lower risk of diseases during the pandemic, regardless of the intensity performed. On the other hand, late eating habits and excessive food consumption during the pandemic were associated with a higher risk.
CONCLUSIONS: The results provide data that can help in the development of public policies that promote health actions to minimize the consequences associated with the pandemic period.

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.