Associations between Fasting Duration, Timing of First and Last Meal, and Cardiometabolic Endpoints in the National Health and Nutrition Examination Survey

Scoping review: Exploring the relationship between chrononutrition and glycemic responses in the adult population

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.

Associations between sleep duration, sleep disturbance and cardiovascular disease biomarkers among adults in the United States

BACKGROUND

Sleep problems are associated with abnormal cardiovascular biomarkers and an increased risk of cardiovascular diseases (CVDs). However, studies investigating associations between sleep problems and CVD biomarkers have reported conflicting findings. This study examined the associations between sleep problems and CVD biomarkers in the United States.

METHODS

Data were from the National Health and Nutrition Examination Survey (NHANES) (2007-2018) and analyses were restricted to adults ≥ 20 years (n = 23,749). CVD biomarkers [C-reactive Protein (CRP), low-density lipoproteins, high-density lipoproteins (HDL), triglycerides, insulin, glycosylated hemoglobin (HbA1c), and fasting blood glucose] were categorized as abnormal or normal using standardized cut-off points. Sleep problems were assessed by sleep duration (short [≤ 6 h], long [≥ 9 h], and recommended [> 6 to < 9 h) and self-reported sleep disturbance (yes, no). Multivariable logistic regression models explored the associations between sleep duration, sleep disturbance, and CVD biomarkers adjusting for sociodemographic characteristics and lifestyle behaviors.

RESULTS

The mean sleep duration was 7.1 ± 1.5 h and 25.1% of participants reported sleep disturbances. Compared to participants with the recommended sleep duration, those with short sleep duration had higher odds of abnormal levels of HDL (adjusted odds ratio [aOR] = 1.20, 95% confidence interval [CI] = 1.05-1.39), CRP (aOR = 3.08, 95% CI = 1.18-8.05), HbA1c (aOR = 1.25, 95% CI = 1.05-1.49), and insulin (aOR = 1.24, 95% CI = 1.03-1.51). Long sleep duration was associated with increased odds of abnormal CRP (aOR = 6.12, 95% CI = 2.19-17.15), HbA1c (aOR = 1.54, 95% CI = 1.09-2.17), and blood glucose levels (aOR = 1.45, 95% CI = 1.07-1.95). Sleep disturbance predicted abnormal triglyceride (aOR = 1.18, 95% CI = 1.01-1.37) and blood glucose levels (aOR = 1.24, 95% CI = 1.04-1.49).

CONCLUSION

Short and long sleep durations were positively associated with abnormal CRP, HDL, HbA1c, blood glucose, and insulin levels, while sleep disturbance was associated with abnormal triglyceride and blood glucose levels. Since sleep is a modifiable factor, adopting healthy sleeping habits may create a balanced metabolism and reduce the risk of developing a CVD. Our study may provide insights into the relationship between sleep duration, sleep disturbance, and CVD risk.

A late eating midpoint is associated with increased risk of diabetic kidney disease: a cross-sectional study based on NHANES 2013-2020

BACKGROUND

Modifying diet is crucial for diabetes and complication management. Numerous studies have shown that adjusting eating habits to align with the circadian rhythm may positively affect metabolic health. However, eating midpoint, eating duration, and their associations with diabetic kidney disease (DKD) are poorly understood.

METHODS

The National Health and Nutrition Examination Survey (2013-2020) was examined for information on diabetes and dietary habits. From the beginning and ending times of each meal, we calculated the eating midpoint and eating duration. Urinary albumin-to-creatinine ratio (UACR) ≥ 30 mg/g and/or estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 were the specific diagnostic criteria for DKD.

RESULTS

In total, details of 2194 subjects with diabetes were collected for analysis. The overall population were divided into four subgroups based on the eating midpoint quartiles. The prevalence of DKD varied noticeably (P = 0.037) across the four categories. When comparing subjects in the second and fourth quartiles of eating midpoint to those in the first one, the odds ratios (ORs) of DKD were 1.31 (95% CI, 1.03 to 1.67) and 1.33 (95% CI, 1.05 to 1.70), respectively. And after controlling for potential confounders, the corresponding ORs of DKD in the second and fourth quartiles were 1.42 (95% CI, 1.07 to 1.90) and 1.39 (95% CI, 1.04 to 1.85), respectively.

CONCLUSIONS

A strong correlation was found between an earlier eating midpoint and a reduced incidence of DKD. Eating early in the day may potentially improve renal outcomes in patients with diabetes.

Plant-based and Early Time-restricted Eating for Prevention and Treatment of Type 2 Diabetes in Adults: A Narrative Review

Type 2 diabetes (T2D) is a significant public health challenge for which effective lifestyle interventions are needed. A growing body of evidence supports the use of both plant-based eating patterns and early time-restricted eating (eTRE) for the prevention and treatment of T2D, but research has not yet explored the potential of these dietary strategies in combination. In this narrative review we assessed the evidence by which plant-based diets, in conjunction with eTRE, could support T2D care. The electronic databases MEDLINE and the Web of Science were searched for relevant articles published throughout the last decade. Observational research has shown that healthy plant-based eating patterns and eTRE are associated with reductions in T2D risk. Interventional trials demonstrated that plant-based diets promote improvements in glycated hemoglobin, insulin resistance, glycemic control, and cardiometabolic risk factors. These changes may be mediated, in part, by reductions in oxidative stress, dietary acid load, and hepatocellular and intramyocellular lipids. The eTRE strategies were also shown to improve insulin resistance and glycemic control, and mechanisms of action included enhanced regulation of circadian rhythm and increased metabolic flexibility. Integrating these dietary strategies may produce additive benefits, mediated by reduced visceral adiposity and beneficial shifts in gut microbiota composition. However, potential barriers to concurrent implementation of these interventions may exist, including social challenges, scheduling constraints, and tolerance. Prospective trials are needed to examine their acceptability and clinical effects.

Is time of eating associated with BMI and obesity? A population-based study

PURPOSE

Time-related eating patterns have been associated with metabolic and nutritional diseases such as obesity. However, there is a lack of representative studies on this subject. This study's aim was to assess the association between the timing of eating and obesity in a large and representative sample of the Brazilian adult population (POF 2008-2009 survey).

METHODS

Two days of adults' food diary (n = 21,020) were used to estimate tertiles of first and last meal intake times, eating midpoint, caloric midpoint time, and calories consumed from 18:00 h onwards. BMI was estimated and its values, as well as excess weight (BMI ≥ 25 kg/m2) and obesity (BMI ≥ 30 kg/m2) were used as outcomes. Multiple linear and logistic regressions were performed.

RESULTS

The first (β = 0.65, 95% CI 0.37-0.93) and last food intake time (β = 0.40, 95% CI 0.14-0.66), eating midpoint (β = 0.61, 95% CI 0.34-0.88) and calories consumed after 21:00 h (β = 0.74, 95% CI 0.32-1.16) and 22:00 h (β = 0.75, 95% CI 0.18-1.32) were positively associated with BMI. The likelihood of having excess weight or obesity was significantly higher in the third tertile of the first food intake time (OR = 1.28, 95% CI 1.13-1.45 and OR = 1.34, 95% CI 1.13-1.58, respectively), last food intake time (OR = 1.16, 95% CI 1.03-1.32; and OR = 1.18, 95% CI 1.00-1.41, respectively), eating midpoint (OR = 1.28, 95% CI 1.13-1.45; and OR = 1.35, 95% CI 1.14-1.59, respectively) and energy consumption after 21:00 h (OR = 1.33, 95% CI 1.10-1.59).

CONCLUSION

Chrononutrition meal patterns indicative of late meal intake were significantly associated with high BMI, excess weight and obesity in the Brazilian population.

Chrononutrition in traditional European medicine-Ideal meal timing for cardiometabolic health promotion

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.

Night eating in timing, frequency, and food quality and risks of all-cause, cancer, and diabetes mortality: findings from national health and nutrition examination survey

OBJECTIVE

To investigate the association of timing, frequency, and food quality of night eating with all-cause, cancer, and diabetes mortality.

METHODS

This study included 41,744 participants from the US National Health and Nutrition Examination Survey (2002-2018). Night eating information was collected by 24-h dietary recall and the exposures were timing, frequency, and food quality of night eating. Food quality was assessed by latent class analysis. The outcomes were all-cause, cancer, and diabetes mortality, which were identified by the National Death Index and the International Classification of Diseases 10th Revision. Adjusted hazard ratios [aHR] with 95% confidence intervals [CI] were computed by Cox regression.

RESULTS

During a median follow-up of 8.7 years, 6066 deaths were documented, including 1381 from cancer and 206 from diabetes. Compared with no night eating (eating before 22:00), the later timing of night eating was associated with higher risk of all-cause and diabetes mortality (each P-trend <0.05) rather than cancer mortality, with the highest risk of eating being 00:00-1:00 (aHR 1.38, 95% CI 1.02-1.88) and being 23:00-00:00 (aHR 2.31, 95% CI 1.21-4.40), respectively. However, the increased risks were not observed for 22:00-23:00. Likewise, one time or over frequency of night eating was associated with higher all-cause and diabetes mortality (each P < 0.05). That risks were further observed in high-dietary-energy-density group of night eating (all-cause mortality: aHR 1.21 [95% CI 1.06-1.38]; diabetes mortality: aHR 1.97 [95% CI 1.13-3.45]), but not in low-dietary-energy-density group. Finally, correlation analysis found positive associations of night eating with glycohemoglobin, fasting glucose, and OGTT.

CONCLUSIONS

Night eating was associated with increased all-cause, cancer and diabetes mortality; however, reduction of excess mortality risk was observed when eating before 23:00 or low-dietary-energy-density foods.

Dietary circadian rhythms and cardiovascular disease risk in the prospective NutriNet-Santé cohort

Daily eating/fasting cycles synchronise circadian peripheral clocks, involved in the regulation of the cardiovascular system. However, the associations of daily meal and fasting timing with cardiovascular disease (CVD) incidence remain unclear. We used data from 103,389 adults in the NutriNet-Santé study. Meal timing and number of eating occasions were estimated from repeated 24 h dietary records. We built multivariable Cox proportional-hazards models to examine their association with the risk of CVD, coronary heart disease and cerebrovascular disease. In this study, having a later first meal (later than 9AM compared to earlier than 8AM) and last meal of the day (later than 9PM compared to earlier than 8PM) was associated with a higher risk of cardiovascular outcomes, especially among women. Our results suggest a potential benefit of adopting earlier eating timing patterns, and coupling a longer nighttime fasting period with an early last meal, rather than breakfast skipping, in CVD prevention.

Temporal associations between nightly sleep with daytime eating and activity levels in free-living young adults

STUDY OBJECTIVES

This study aimed to quantify the temporal associations between nightly sleep quantity and timing with daytime eating behavior and activity levels in free-living (i.e. non-experimental) settings.

METHODS

Generally healthy young adults (N = 63; 28.9 ± 7.1 years) completed concurrent sleep (wrist actigraphy), eating (photo-assisted diet records), and activity (waist actigraphy) assessments over 14 days. Multilevel models quantified the associations between nightly sleep (total sleep time, timing of sleep and wake onset) with next-day eating behavior (diet quality, caloric intake, timing of eating onset/offset, eating window duration) and activity levels (total physical activity, sedentary time). Associations in the reverse direction (i.e. eating and activity predicting sleep) were explored. Models adjusted for demographic and behavioral confounders and accounted for multiple testing.

RESULTS

At within- and between-subject levels, nights with greater-than-average total sleep time predicted a shorter eating window the next day (all p ≤ 0.002). Later-than-average sleep and wake timing predicted within- and between-subject delays in next-day eating onset and offset, and between-subject reductions in diet quality and caloric intake (all p ≤ 0.008). At within- and between-subject levels, total sleep time was bidirectionally, inversely associated with sedentary time (all p < 0.001), while later-than-average sleep and wake timing predicted lower next-day physical activity (all p ≤ 0.008).

CONCLUSIONS

These data underscore the complex interrelatedness between sleep, eating behavior, and activity levels in free-living settings. Findings also suggest that sleep exerts a greater influence on next-day behavior, rather than vice versa. While testing in more diverse samples is needed, these data have potential to enhance health behavior interventions and maximize health outcomes.

Sleep Variability, Eating Timing Variability, and Carotid Intima-Media Thickness in Early Adulthood

Background Day-to-day variability in sleep patterns and eating timing may disrupt circadian rhythms and has been linked with various adverse cardiometabolic outcomes. However, the extent to which variability in sleep patterns and eating timing relate to atherosclerotic development in subclinical stages remains unclear. Methods and Results Generally healthy adults (N=62, 29.3±7.3 years, 66% female) completed 14 days of sleep and dietary assessments via wrist accelerometry and photo-assisted diet records, respectively. Variability in sleep duration, sleep onset, eating onset (time of first caloric consumption), eating offset (time of last caloric consumption), and caloric midpoint (time at which 50% of total daily calories are consumed) were operationalized as the SD across 14 days for each variable. Separate regression models evaluated the cross-sectional associations between sleep and eating variability metrics with end-diastolic carotid intima-media thickness (CIMT) measured via ultrasonography. Models adjusted for age, sex, systolic blood pressure, sleep duration, and total energy intake. Each 60-minute increase in sleep duration SD and sleep onset SD were associated with a 0.049±0.016 mm (P=0.003) and 0.048±0.017 mm (P=0.007) greater CIMT, respectively. Variability in eating onset and offset were not associated with CIMT; however, each 60-minute increase in caloric midpoint SD was associated with a 0.033±0.015 mm greater CIMT (P=0.029). Exploratory post hoc analyses suggested that sleep duration SD and sleep onset SD were stronger correlates of CIMT than caloric midpoint SD. Conclusions Variability in sleep patterns and eating timing are positively associated with clinically relevant increases in CIMT, a biomarker of subclinical atherosclerosis, in early adulthood.

Timing Matters: The Interplay between Early Mealtime, Circadian Rhythms, Gene Expression, Circadian Hormones, and Metabolism-A Narrative Review

Achieving synchronization between the central and peripheral body clocks is essential for ensuring optimal metabolic function. Meal timing is an emerging field of research that investigates the influence of eating patterns on our circadian rhythm, metabolism, and overall health. This narrative review examines the relationship between meal timing, circadian rhythm, clock genes, circadian hormones, and metabolic function. It analyzes the existing literature and experimental data to explore the connection between mealtime, circadian rhythms, and metabolic processes. The available evidence highlights the importance of aligning mealtime with the body's natural rhythms to promote metabolic health and prevent metabolic disorders. Specifically, studies show that consuming meals later in the day is associated with an elevated prevalence of metabolic disorders, while early time-restricted eating, such as having an early breakfast and an earlier dinner, improves levels of glucose in the blood and substrate oxidation. Circadian hormones, including cortisol and melatonin, interact with mealtimes and play vital roles in regulating metabolic processes. Cortisol, aligned with dawn in diurnal mammals, activates energy reserves, stimulates appetite, influences clock gene expression, and synchronizes peripheral clocks. Consuming meals during periods of elevated melatonin levels, specifically during the circadian night, has been correlated with potential implications for glucose tolerance. Understanding the mechanisms of central and peripheral clock synchronization, including genetics, interactions with chronotype, sleep duration, and hormonal changes, provides valuable insights for optimizing dietary strategies and timing. This knowledge contributes to improved overall health and well-being by aligning mealtime with the body's natural circadian rhythm.

Circadian rhythms, gut microbiota, and diet: Possible implications for health

AIMS

Over the past years, interest in chrono-nutrition has grown enormously as the fundamental role of circadian rhythms in regulating most physiological and metabolic processes has become clearer. Recently, the influence of circadian rhythms on the gut microbiota (GM) composition has also emerged, as more than half of the total microbial composition fluctuates rhythmically throughout the day. At the same time, other studies have observed that the GM itself synchronises the host's circadian biological clock through signals of a different nature. Therefore, it has been hypothesised that there is a two-way communication between the circadian rhythms of the host and the GM, but researchers have only just begun to identify some of its action mechanisms. The manuscript aim is, therefore, to gather and combine the latest evidence in the field of chrono-nutrition with the more recent research on the GM, in order to investigate their relationship and their potential impact on human health.

DATA SYNTHESIS

Considering current evidence, a desynchronization of circadian rhythms is closely associated with an alteration in the abundance and functionality of the gut microbiota with consequent deleterious effects on health, such as increased risk of numerous pathologies, including cardiovascular disease, cancer, irritable bowel disease, and depression. A key role in maintaining the balance between circadian rhythms and GM seems to be attributed to meal-timing and diet quality, as well as to certain microbial metabolites, in particular short-chain fatty acids.

CONCLUSIONS

Future studies are needed to decipher the link between the circadian rhythms and specific microbial patterns in relation to different disease frameworks.

Association of meal timing with body composition and cardiometabolic risk factors in young adults

PURPOSE

To investigate the association of meal timing with body composition and cardiometabolic risk factors in young adults.

METHODS

In this cross-sectional study participated 118 young adults (82 women; 22 ± 2 years old; BMI: 25.1 ± 4.6 kg/m²). Meal timing was determined via three non-consecutive 24-h dietary recalls. Sleep outcomes were objectively assessed using accelerometry. The eating window (time between first and last caloric intake), caloric midpoint (local time at which ≥ 50% of daily calories are consumed), eating jetlag (variability of the eating midpoint between non-working and working days), time from the midsleep point to first food intake, and time from last food intake to midsleep point were calculated. Body composition was determined by DXA. Blood pressure and fasting cardiometabolic risk factors (i.e., triglycerides, total cholesterol, high-density lipoprotein-cholesterol, low-density lipoprotein-cholesterol, and insulin resistance) were measured.

RESULTS

Meal timing was not associated with body composition (p > 0.05). The eating window was negatively related to HOMA-IR and cardiometabolic risk score in men (R² = 0.348, β = - 0.605; R² = 0.234, β = - 0.508; all p ≤ 0.003). The time from midsleep point to first food intake was positively related to HOMA-IR and cardiometabolic risk score in men (R² = 0.212, β = 0.485; R² = 0.228, β = 0.502; all p = 0.003). These associations remained after adjusting for confounders and multiplicity (all p ≤ 0.011).

CONCLUSIONS

Meal timing seems unrelated to body composition in young adults. However, a longer daily eating window and a shorter time from midsleep point to first food intake (i.e., earlier first food intake in a 24 h cycle) are associated with better cardiometabolic health in young men.

CLINICAL TRIAL REGISTRATION

NCT02365129 ( https://www.

CLINICALTRIALS

gov/ct2/show/NCT02365129?term=ACTIBATE&draw=2&rank=1 ).

Intermittent fasting with ketogenic diet: A combination approach for management of chronic diseases

Intermittent Fasting (IF) is the consumption of food and drinks within a defined time, while the ketogenic diet (KD) switches the metabolism from glucose to fats. Continuation of intermittent fasting leads to the generation of ketones, the exact mechanism for a ketogenic diet. This article discusses the types of IF and KD, the monitoring required, and the mechanisms underlying IF and KD, followed by disorders in which the combination strategy could be applied. The strategies for successfully applying combination therapy are included, along with recommendations for the primary care physicians (PCP) which could serve as a handy guide for patient management. This opinion article could serve as the baseline for future clinical studies since there is an utmost need for developing new wholesome strategies for managing chronic disorders.

Identifying the Associations of Nightly Fasting Duration and Meal Timing with Type 2 Diabetes Mellitus Using Data from the 2016–2020 Korea National Health and Nutrition Survey

Nightly fasting duration and meal timing are associated with metabolic disorders. This study aimed to investigate the relationships of nightly fasting duration and meal timing with type 2 diabetes mellitus (T2DM) using data from the 2016–2020 Korea National Health and Nutrition Survey. A total of 22,685 adults ≥ 19 years were included in this study. Nightly fasting duration was calculated by subtracting the interval between the day’s first and last meal eating times from 24 h. The meal timing were analyzed using various parameters, including the times of the first and last eating episodes and the percentage of energy intake during the morning (05:00 to 9:00 a.m.), evening (06:00 to 09:00 p.m.), and night (after 09:00 p.m.). Men who fasted nightly for ≥ 12 h had lower odds of T2DM (odds ratio (OR): 0.86; 95% confidence interval (CI): 0.75–0.99) than those who fasted for < 12 h. Individuals who had their last meal after 09:00 p.m. had higher odds of T2DM (OR: 1.19, 95% CI: 1.03–1.38, men; OR: 1.19, 95% CI: 1.01–1.40, women). Additionally, the percentage of energy intake during the evening was associated with increased odds of T2DM (OR: 1.41, 95% CI: 1.08–1.84, men; OR: 1.32, 95% CI: 1.02–1.70, women). These findings emphasize the importance of nightly fasting duration and meal timing in modulating the risk of T2DM among Korean adults.

Associations between Timing and Duration of Eating and Glucose Metabolism: A Nationally Representative Study in the U.S

Diabetes is highly prevalent and is associated with dietary behaviors. Time-restricted eating, which consolidates caloric intake to a shortened eating duration, has demonstrated improvement in metabolic health. Timing of eating could also impact metabolism. Our objective was to examine whether the timing of eating was associated with metabolic health independently of eating duration. Data (n = 7619) are from four cycles (2005-2012) of the National Health and Nutrition Examination Survey (NHANES), a nationally representative U.S. survey that included surveys, physical examinations, and dietary recalls. The primary exposures are eating duration and eating start time estimated from two non-consecutive dietary recalls. Primary outcomes were fasting glucose and estimated insulin resistance using the homeostatic model assessment method (HOMA-IR). The mean (95% CI) eating duration was 12.0 h (11.9-12.0) and the mean (95% CI) start time was 8:21 (8:15-8:26). Earlier eating start time was significantly associated with lower fasting glucose and estimated insulin resistance but eating interval duration was not. Every hour later that eating commenced was associated with approximately 0.6% higher glucose level and 3% higher HOMA-IR (both p < 0.001). In this cross-sectional study, earlier eating start time was associated with more favorable metabolic measures, indicating that meal timing is another important characteristic of dietary patterns that may influence metabolism.

Time-related meal patterns and breakfast quality in a sample of Iranian adults

BACKGROUND

Some evidence shows that meal timing is associated with diet quality. We aimed to investigate the relationship between meal timing and breakfast quality in a sample of Iranian adults.

METHODS

This cross-sectional study was conducted on 850 men and women living in Tehran, Iran. Dietary data was recorded by three non-consecutive 24-h dietary recalls. The Breakfast Quality Index (BQI) was calculated. Time-related meal patterns included the interval between the first and last meal (eating and fasting window), frequency of meals, length of sleep, and time of first and last eating occasion. The multiple linear regression analysis was used to identify the relationships between time-related meal patterns and BQI.

RESULTS

The mean (95% CI) of BQI was 4.52 (4.45-4.65) and the maximum was 8. Bread, cheese, vegetables, fruits, energy, and carbohydrate intake showed positive associations with BQI scores. Longer fasting time showed a positive association with fruits (β (CI 95%)) (0.11 (0.0003-0.005), and vegetable consumption (0.12 (0.009-0.07)) and BQI score (0.39 (0.001-0.06)). Time of first eating occasions indicated a negative association with protein and fat intake and BQI score. Time of last eating occasions showed a positive association with vegetables consumption and BQI score. The longer length of sleep was associated with a higher BQI score. The frequency of meals was significantly and positively related to energy and macronutrients intake and BQI.

CONCLUSION

Earlier first and last meal, longer sleep length, longer fasting window, and a greater meal frequency were associated with a better breakfast quality.

Self-Reported Eating-Occasion Frequency and Timing are Reproducible and Relatively Valid in the American Cancer Society Cancer Prevention Study-3 Diet Assessment Substudy

BACKGROUND

Accurate assessment of eating-occasion behaviors, such as timing, frequency, and consumption intervals, is important for evaluating associations with obesity and other chronic diseases.

OBJECTIVES

The main objective of this study was to assess the relative validity of a 24-hour grid approach to assess eating-occasion timing and frequency in comparison to data derived from repeated 24-hour dietary recalls (DRs). A second objective was to assess the 1-year test-retest reproducibility of the 24-hour grid.

METHODS

Between 2015 and 2016, 626 participants in the Cancer Prevention Study-3 (CPS-3) Diet Assessment Substudy (mean age, 52 years; age range, 31-70 years; 64% female; 64% non-Hispanic white, 22% non-Hispanic black, 14% Hispanic) completed 2 grids and up to 6 unannounced, telephone, interviewer-administered DRs over 1 year. Spearman correlations (ρ; 95% CIs) were calculated to assess reproducibility between the repeated eating-occasion grid-derived variables (e.g., numbers of snacks and meals per day, timing of eating occasions) and to assess relative validity by comparing the meal grid and DR-derived summary data separately for weekdays and weekend days.

RESULTS

Reproducibility correlations for eating-occasion variables derived from the eating-occasion grids completed 1 year apart were ≥0.5 for the majority of variables analyzed for both weekdays and weekend days, including numbers of snacks and meals per day and timing of the first and last eating occasions of the day. Relative validity was highest among weekday variables and was ≥0.5 for the majority of variables, with correlations ranging from ρ values of 0.32 (number of meals per day) to 0.68 (hour of the first eating occasion).

CONCLUSIONS

These findings suggest the eating-occasion grid used in CPS-3 has good reproducibility over 1 year and yields estimates comparable to those from a more detailed method of assessment of eating timing and frequency.

Sugar Consumption Pattern among Cardiometabolic Risk Individuals: A Scoping Review

BACKGROUND

The global prevalence of noncommunicable diseases has risen rapidly over the past decade. Research has focused on dietary management, particularly dietary sugar, to prevent and treat noncommunicable diseases.

OBJECTIVE

This study undertakes a scoping review of research on the impacts of dietary sugar on cardiometabolic related health outcomes.

METHODS

Ovid Medline, Scopus and Web of Science Core collection databases were used to identify papers published from January 1, 2010 onwards. The included studies had to be cross-sectional or cohort studies, peered review, published in English and in adults, aged 18 years old and above. Articles had to determine the impacts of sugar intake on cardiometabolic related health outcomes. Study quality was measured using the Quality Assessment Tool for Observational Cohort and Cross-sectional Studies. In addition, a narrative synthesis of extracted information was conducted.

RESULTS

Thirty-one articles were included in this review. All studies had a large sample size, and the exposure measure was clearly defined, valid and applied consistently across all study participants. Exposure was measured using validated questionnaires. All data were statistically analysed and adjusted for critical potential confounding variables. Results showed that dietary sugar intake was significantly associated with metabolic syndrome, blood pressure, blood glucose, blood lipids, and body weight.

CONCLUSION

Dietary sugar intake significantly increased cardiometabolic risks through mechanisms dependent and independent of weight gain. It is essential to create public awareness on the topics of cardiometabolic risk management and dietary sugars intake.

Immune disruptions and night shift work in hospital healthcare professionals: The intricate effects of social jet-lag and sleep debt

Objectives

We aimed to examine the effects of circadian and sleep rhythm disruptions on immune biomarkers among hospital healthcare professionals working night shifts and rotating day shifts.

Methods

Hospital nurses working either as permanent night shifters (n=95) or as day shifters rotating between morning and afternoon shifts (n=96) kept a daily diary on their sleep and work schedules over a full working week. Blood samples were collected at the beginning and end of the last shift during the week, and participants were categorized into three groups based on work shift: morning shift (39 day shifters sampled at 7:00 and 14:00), afternoon shift (57 day shifters sampled at 14:00 and 21:00), and night shift (95 night shifters sampled at 21:00 and 7:00). Circulating blood counts in immune cells, interleukin-6 and C-reactive protein concentrations as well as total sleep time per 24 hours during work days (TST24w) and free days (TST24f), sleep debt (TST24f - TST24w) and social jet-lag (a behavioral proxy of circadian misalignment) were assessed.

Results

Compared with day shifters, night shifters had shorter sleep duration (TST24w=5.4 ± 1.4h), greater sleep debt (3.2 ± 1.4 h) and social jet-lag (6.7 ± 2.4 h). Variations of immune biomarkers concentrations were consistent with the expected diurnal variations among day shifters (i.e., low level in the morning, increase during the day, peak value in the evening). By contrast, in night shifters, blood concentrations of total lymphocytes, T-helper cells, cytotoxic T-cells, memory B-cells and interleukin-6 were lower at 21:00, increased during the night, and reached higher values at 7:00. Multivariate analyses ruled out significant impact of TST24w, sleep debt, and social jet-lag on immune biomarkers concentrations among day shifters. In contrast, among night shifters, multivariate analyses indicated a combined effect of total sleep time (TST24w), sleep debt and social jet-lag for total lymphocytes and T-helper cells but only a social jet-lag effect for interleukin-6 and a single total sleep time effect for neutrophil and B-Cells.

Conclusions

Altogether, our results point to intricate response patterns of immune rhythms to circadian misalignment and sleep debt in night shifters. Specifically, these altered pattern expressions of immune cells may increase vulnerability to infections and reduce vaccination efficiency in night workers.

Variable Eating Patterns: A Potential Novel Risk Factor for Systemic Inflammation in Women

BACKGROUND

The timing and regularity of eating patterns could play a role in systemic inflammation, as circadian clocks responsible for daily rhythms of inflammatory signaling are entrained by food intake.

PURPOSE

To evaluate associations of intra-weekly and weekday-weekend differences in eating timing patterns with high-sensitivity C-reactive protein (hsCRP).

METHODS

A community-based sample of 103 U.S. women from the American Heart Association Go Red for Women Strategically Focused Research Network completed a meal-timing questionnaire and provided a blood sample for measurement of hsCRP. Differences in weekday versus weekend eating start time, eating end time, and nightly fasting duration were calculated as eating jetlag metrics. Intra-weekly variability in eating timing patterns was defined by the standard deviation (SD) of these variables. Multivariable linear regression models were used to evaluate cross-sectional associations of eating timing variability metrics with hsCRP.

RESULTS

Each additional 30-min difference in weekday-weekend eating end time was related to 13% higher hsCRP (p = .023). Similarly, every 30-min increase in eating end time SD, reflecting greater variability in timing of last eating occasion, was associated with 29% higher hsCRP. Per 1-hr weekday-weekend difference in nightly fasting duration, there was a 45% elevation in hsCRP (p = .003). Every 30-min increase in nightly fasting duration SD, representing greater variability in span of the daily fasting/eating periods, was associated with 46% higher hsCRP.

CONCLUSIONS

Variable eating timing patterns were associated with higher hsCRP. Intervention studies are needed to determine whether stabilizing the timing of eating occasions may represent a novel strategy to reduce chronic inflammation.

A New Approach to Understanding Cancer-Related Fatigue: Leveraging the 3P Model to Facilitate Risk Prediction and Clinical Care

Simple Summary

For the growing number of cancer survivors worldwide, fatigue presents a major hurdle to function and quality of life. Treatment options for cancer-related fatigue are still emerging, and our current understanding of its etiology is limited. In this paper, we describe a new application of a comprehensive model for cancer-related fatigue: the predisposing, precipitating, and perpetuating (3P) factors model. We propose that the 3P model may be leveraged—particularly using metabolomics, the microbiome, and inflammation in conjunction with behavioral science—to better understand the pathophysiology of cancer-related fatigue.

Abstract

A major gap impeding development of new treatments for cancer-related fatigue is an inadequate understanding of the complex biological, clinical, demographic, and lifestyle mechanisms underlying fatigue. In this paper, we describe a new application of a comprehensive model for cancer-related fatigue: the predisposing, precipitating, and perpetuating (3P) factors model. This model framework outlined herein, which incorporates the emerging field of metabolomics, may help to frame a more in-depth analysis of the etiology of cancer-related fatigue as well as a broader and more personalized set of approaches to the clinical treatment of fatigue in oncology care. Included within this review paper is an in-depth description of the proposed biological mechanisms of cancer-related fatigue, as well as a presentation of the 3P model’s application to this phenomenon. We conclude that a clinical focus on organization risk stratification and treatment around the 3P model may be warranted, and future research may benefit from expanding the 3P model to understand fatigue not only in oncology, but also across a variety of chronic conditions.

An Earlier First Meal Timing Associates with Weight Loss Effectiveness in A 12-Week Weight Loss Support Program

Recent studies have reported that meal timing may play an important role in weight regulation, however it is unknown whether the timing of meals is related to the amount of weight loss. This study aimed to examine the relationship between indices of meal timing and weight loss during weight loss intervention in adults. A 12-week weight loss support program was conducted for 97 adults (age: 47.6 ± 8.3 years, BMI: 25.4 ± 3.7 kg/m²). After the program, body weight decreased by −3.0 ± 2.7%. Only the start of the eating window was positively correlated with the weight change rate in both sexes (men: r = 0.321, p = 0.022; women: r = 0.360, p = 0.014). The participants were divided into two groups based on the start of the eating window as follows: the early group (6:48 ± 0:21 AM) and the late group (8:11 ± 1:05 AM). The weight loss rate in the early group was significantly higher (−3.8 ± 2.7%) than that in the late group (−2.2 ± 2.5%). The present results showed that the start of the early eating window was associated with weight loss and suggested paying attention to meal timing when doing weight loss.

Chrononutrition in Cardiometabolic Health

In recent years, a healthy balanced diet together with weight reduction has risen to the forefront of minimizing the impact of cardiovascular disease. There is evidence that metabolic processes present circadian rhythmicity. Moreover, the timing of food consumption exerts a powerful influence on circadian rhythms. In this context, the subject of chrononutrition, described as the alignment of timing of food intake to the rhythms imposed by the circadian clock, has attracted considerable interest for possible beneficial effects on cardiovascular health. Current human studies suggest that chrononutrition-based dietary interventions could reduce the risk for cardiovascular disease by improving weight control, hypertension, dyslipidemia, and diabetes. However, meta-analysis of randomized control trials in this topic present varying and somehow conflicting results. Even the traditional association of breakfast skipping with adverse cardiovascular outcomes is nowadays controversial. Therefore, long-term and fairly consistent studies on the effect of chrononutrition on cardiovascular outcomes are needed. The purpose of this review is to provide concise evidence of the most recent literature involving the effects of chrononutrition and the specific chrononutrition-based dietary interventions, in particular time-restricted eating, on body weight and other cardiovascular disease risk factors.