Caloric and Macronutrient Intake Differ with Circadian Phase and between Lean and Overweight Young Adults

Environmental, social, and behavioral challenges of the human circadian clock in real-life conditions

Urban environments, in which ambient light has become a less-reliable entrainer, are challenging for the biological clock to maintain performance. As a consequence, human circadian rhythms are less robust and more variable among individuals. Assessing the individual phase of entrainment, as well as its plastic shifts in response to disturbances of the physical and social environment, is a way to measure circadian disruption. However, this is still difficult to address in real-life scenarios in which several factors modulate the circadian phase not always in a concerted manner. In this perspective, we present the contribution of two real-life situations, in which the circadian system is challenged by important alterations in entraining signals: 1) a trip to the Antarctic summer (socio-environmental challenge), and 2) dancers trained in morning/night shifts (socio-behavioral challenge). Both natural chronobiological experiments are helpful in exploring the functioning and plasticity of the circadian clock and allow for considering individual characteristics and history.

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.

Nightshift imposes irregular lifestyle behaviors in police academy trainees

Study Objective

Shiftwork increases risk for numerous chronic diseases, which is hypothesized to be linked to disruption of circadian timing of lifestyle behaviors. However, empirical data on timing of lifestyle behaviors in real-world shift workers are lacking. To address this, we characterized the regularity of timing of lifestyle behaviors in shift-working police trainees.

Methods

Using a two-group observational study design (N = 18), we compared lifestyle behavior timing during 6 weeks of in-class training during dayshift, followed by 6 weeks of field-based training during either dayshift or nightshift. Lifestyle behavior timing, including sleep-wake patterns, physical activity, and meals, was captured using wearable activity trackers and mobile devices. The regularity of lifestyle behavior timing was quantified as an index score, which reflects day-to-day stability on a 24-hour time scale: Sleep Regularity Index, Physical Activity Regularity Index, and Mealtime Regularity Index. Logistic regression was applied to these indices to develop a composite score, termed the Behavior Regularity Index (BRI).

Results

Transitioning from dayshift to nightshift significantly worsened the BRI, relative to maintaining a dayshift schedule. Specifically, nightshift led to more irregular sleep-wake timing and meal timing; physical activity timing was not impacted. In contrast, maintaining a dayshift schedule did not impact regularity indices.

Conclusions

Nightshift imposed irregular timing of lifestyle behaviors, which is consistent with the hypothesis that circadian disruption contributes to chronic disease risk in shift workers. How to mitigate the negative impact of shiftwork on human health as mediated by irregular timing of sleep-wake patterns and meals deserves exploration.

Nightshift Imposes Irregular Lifestyle Behaviors in Police Academy Trainees

Study Objective

Shiftwork increases risk for numerous chronic diseases, which is hypothesized to be linked to disruption of circadian timing of lifestyle behaviors. However, empirical data on timing of lifestyle behaviors in real-world shift workers are lacking. To address this, we characterized the regularity of timing of lifestyle behaviors in shift-working police trainees.

Methods

Using a two-group observational study design (N=18), we compared lifestyle behavior timing during 6 weeks of in-class training during dayshift, followed by 6 weeks of field-based training during either dayshift or nightshift. Lifestyle behavior timing, including sleep/wake patterns, physical activity, and meals, was captured using wearable activity trackers and mobile devices. The regularity of lifestyle behavior timing was quantified as an index score, which reflects day-to-day stability on a 24h time scale: Sleep Regularity Index (SRI), Physical Activity Regularity Index (PARI) and Mealtime Regularity Index (MRI). Logistic regression was applied to these indices to develop a composite score, termed the Behavior Regularity Index (BRI).

Results

Transitioning from dayshift to nightshift significantly worsened the BRI, relative to maintaining a dayshift schedule. Specifically, nightshift led to more irregular sleep/wake timing and meal timing; physical activity timing was not impacted. In contrast, maintaining a dayshift schedule did not impact regularity indices.

Conclusion

Nightshift imposed irregular timing of lifestyle behaviors, which is consistent with the hypothesis that circadian disruption contributes to chronic disease risk in shift workers. How to mitigate the negative impact of shiftwork on human health as mediated by irregular timing of sleep/wake patterns and meals deserves exploration.

Maternal melatonin levels and temporal dietary intake: results from MY-CARE cohort study

Chrononutrition emerges as a novel approach to promote circadian alignment and metabolic health by means of time-of-the-day dietary intake. However, the relationship between maternal circadian rhythm and temporal dietary intake during pregnancy remains understudied. This study aimed to determine the change in melatonin levels in pregnant women across gestation and its association with temporal energy and macronutrient intake. This was a prospective cohort involving 70 healthy primigravidas. During the second and third trimesters, pregnant women provided salivary samples collected at 9:00, 15:00, 21:00, and 3:00 h over a 24 h day for melatonin assay. Data on chrononutrition characteristics were collected using a 3-day food record. Parameters derived from melatonin measurements including mean, amplitude, maximal level, area under the curve with respect to increase (AUC_I), and area under the curve with respect to ground (AUC_G) were computed. A rhythmic melatonin secretion over the day that remained stable across trimesters was observed among the pregnant women. There was no significant elevation in salivary melatonin levels as pregnancy advanced. In the second trimester, higher energy intake during 12:00-15:59 h and 19:00-06:59 h predicted a steeper melatonin AUC_I (β=-0.32, p = 0.034) and higher AUC_G (β = 0.26, p = 0.042), respectively. Macronutrient intake within 12:00-15:59 h was negatively associated with mean melatonin (Fat: β=-0.28, p = 0.041) and AUC_G (Carbohydrate: β=-0.37, p = 0.003; Protein: β=-0.27, p = 0.036; Fat: β=-0.32, p = 0.014). As pregnant women progressed from the second to the third trimester, a flatter AUC_I was associated with a reduced carbohydrate intake during 12:00-15:59 h (β=-0.40, p = 0.026). No significant association was detected during the third trimester. Our findings show that higher energy and macronutrient intakes particularly during 12:00-15:59 h and 19:00-06:59 h are associated with the disparities in maternal melatonin levels. Findings suggest the potential of time-based dietary approaches to entrain circadian rhythm in pregnant women.

Associations of timing of food intake with energy intake, eating behaviour traits and psychosocial factors in adults with overweight and obesity

Introduction

Whether a late distribution of food intake impacts obesity through increased energy intake remains uncertain and the behavioural characterization of late eating needs to be further investigated. The first objective of this study was to assess the associations between late eating and body mass index (BMI) and total energy intake (TEI), and whether TEI mediates the association between late eating and BMI. The second objective was to assess the associations between late eating and eating behaviour traits or psychosocial factors and whether eating behaviour traits mediate the association between late eating and TEI.

Methods

Baseline data from 301 individuals (56% women, age = 38.7 ± 8.5 years; BMI = 33.2 ± 3.4 kg/m²), who participated in four weight loss studies were used in this cross-sectional study. Total energy intake was assessed using a three-day food record from which the percentage of TEI after 17:00 and after 20:00 was calculated. Eating behaviour traits and psychosocial factors were assessed with questionnaires. Pearson correlations and mediation analyses adjusted for age, sex, underreporting of energy intake, sleep duration and bedtime were performed.

Results

Percent TEI after 17:00 and after 20:00 were associated with TEI (r = 0.13, p = 0.03 for both), and TEI mediated the association between percent TEI after 17:00 and BMI (β = 0.01 ± 0.01, 95% CI: 0.001, 0.02). Percent TEI after 17:00 was associated with disinhibition (r = 0.13, p = 0.03) and percent TEI after 20:00 was associated with susceptibility to hunger (r = 0.13, p = 0.03), stress (r = 0.24, p = 0.002) and anxiety (r = 0.28, p = 0.0004). In women, disinhibition mediated the association between percent TEI after 17:00 and TEI (β = 3.41 ± 1.43, 95% CI: 0.92, 6.47). Susceptibility to hunger mediated the association between percent TEI after 20:00 and TEI (β = 0.96 ± 0.59, 95% CI: 0.02, 2.34) in men and women.

Conclusion

Late eating is associated with TEI and suboptimal eating behaviours which could contribute to explaining the association between timing of food intake and obesity.

Reciprocal Interactions between Circadian Clocks, Food Intake, and Energy Metabolism

Like other biological functions, food intake and energy metabolism display daily rhythms controlled by the circadian timing system that comprises a main circadian clock and numerous secondary clocks in the brain and peripheral tissues. Each secondary circadian clock delivers local temporal cues based on intracellular transcriptional and translational feedback loops that are tightly interconnected to intracellular nutrient-sensing pathways. Genetic impairment of molecular clocks and alteration in the rhythmic synchronizing cues, such as ambient light at night or mistimed meals, lead to circadian disruption that, in turn, negatively impacts metabolic health. Not all circadian clocks are sensitive to the same synchronizing signals. The master clock in the suprachiasmatic nuclei of the hypothalamus is mostly synchronized by ambient light and, to a lesser extent, by behavioral cues coupled to arousal and exercise. Secondary clocks are generally phase-shifted by timed metabolic cues associated with feeding, exercise, and changes in temperature. Furthermore, both the master and secondary clocks are modulated by calorie restriction and high-fat feeding. Taking into account the regularity of daily meals, the duration of eating periods, chronotype, and sex, chrononutritional strategies may be useful for improving the robustness of daily rhythmicity and maintaining or even restoring the appropriate energy balance.

Later energy intake relative to mathematically modeled circadian time is associated with higher percentage body fat

OBJECTIVE

Later circadian timing of energy intake is associated with higher body fat percentage. Current methods for obtaining accurate circadian timing are labor- and cost-intensive, limiting practical application of this relationship. This study investigated whether the timing of energy intake relative to a mathematically modeled circadian time, derived from easily collected ambulatory data, would differ between participants with a lean or overweight/obesity body fat percentage.

METHODS

Participants (N = 87) wore a light- and activity-measuring device (actigraph) throughout a cross-sectional 30-day study. For 7 consecutive days within these 30 days, participants used a time-stamped-picture phone application to record energy intake. Body fat percentage was recorded. Circadian time was defined using melatonin onset from in-laboratory collected repeat saliva sampling or using light and activity or activity data alone entered into a mathematical model.

RESULTS

Participants with overweight/obesity body fat percentages ate 50% of their daily calories significantly closer to model-predicted melatonin onset from light and activity data (0.61 hours closer) or activity data alone (0.86 hours closer; both log-rank p < 0.05).

CONCLUSIONS

Use of mathematically modeled circadian timing resulted in similar relationships between the timing of energy intake and body composition as that observed using in-laboratory collected metrics. These findings may facilitate use of circadian timing in time-based interventions.

Macronutrient intake: Hormonal controls, pathological states, and methodological considerations

A plethora of studies to date has examined the roles of feeding-related peptides in the control of food intake. However, the influence of these peptides on the intake of particular macronutrient constituents of food - carbohydrate, fat, and protein - has not been as extensively addressed in the literature. Here, the roles of several feeding-related peptides in controlling macronutrient intake are reviewed. Next, the relationship between macronutrient intake and diseases including diabetes mellitus, obesity, and eating disorders are examined. Finally, some key considerations in macronutrient intake research are discussed. We hope that this review will shed light onto this underappreciated topic in ingestive behavior research and will help to guide further scientific investigation in this area.

Characteristics of smartphone-based dietary assessment tools: a systematic review

Smartphones have become popular in assessing eating behaviour in real-life and real-time. This systematic review provides a comprehensive overview of smartphone-based dietary assessment tools, focusing on how dietary data is assessed and its completeness ensured. Seven databases from behavioural, social and computer science were searched in March 2020. All observational, experimental or intervention studies and study protocols using a smartphone-based assessment tool for dietary intake were included if they reported data collected by adults and were published in English. Out of 21,722 records initially screened, 117 publications using 129 tools were included. Five core assessment features were identified: photo-based assessment (48.8% of tools), assessed serving/ portion sizes (48.8%), free-text descriptions of food intake (42.6%), food databases (30.2%), and classification systems (27.9%). On average, a tool used two features. The majority of studies did not implement any features to improve completeness of the records. This review provides a comprehensive overview and framework of smartphone-based dietary assessment tools to help researchers identify suitable assessment tools for their studies. Future research needs to address the potential impact of specific dietary assessment methods on data quality and participants' willingness to record their behaviour to ultimately improve the quality of smartphone-based dietary assessment for health research.

Work Around the Clock: How Work Hours Induce Social Jetlag and Sleep Deficiency

A growing body of evidence has placed an increasing emphasis on how sleep affects health. Not only does insufficient sleep make one subjectively feel worse, but is associated with chronic diseases that are considered epidemics in industrialized nations. This is partly caused by the growing need for prolonged work and social schedules, exemplified by shift work, late-night weekends, and early morning work/school start times (social jetlag). Here, we consider fundamental relationships between the circadian clock and biologic processes and discuss how common practices, such as shift work and social jetlag, contribute to sleep disruption, circadian misalignment, and adverse health outcomes.

Evaluation of environmental, social, and behavioral modulations of the circadian phase of dancers trained in shifts

The interplay of environmental, social, and behavioral factors influencing human circadian phase in ecological conditions remains elusive. The Uruguayan national dance school END-SODRE operating in two shifts (morning: 8:30–12:30 and night: 20:00–24:00) allowed us to evaluate how social demands, chronotype, environmental light, physical activity, and sleep patterns affected individual circadian phase measured by the onset of the nocturnal increase of melatonin (DLMO) in a single study. The DLMO was 1.5 h earlier in morning-shift dancers (n = 7) compared to night-shift dancers (n = 11). Sleep time and chronotype (only in night-shift dancers) were associated with the circadian phase. In training days, during each participant’s phase-advance and phase-delay time windows, light exposure was similar between morning and night-shift dancers and did not correlate with DLMO. In contrast, the time spent in moderate-vigorous physical activity during each participant’s phase-lag time window was higher in night-shift dancers than in morning-shift dancers and positively correlated with DLMO.

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Circadian phase was earlier in morning than in night dancers in real-life conditions

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Sleep time (and night-shift chronotypes) correlated with the circadian phase

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In the phase-advance and phase-lag windows, light was not associated with DLMO

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In the phase-lag time window, the longer the intense exercise the later the phase

Chronic Circadian Disruption and Sleep Restriction Influence Subjective Hunger, Appetite, and Food Preference

Chronic circadian disruption (CCD), such as occurs during rotating shiftwork, and insufficient sleep are each independently associated with poor health outcomes, including obesity and glucose intolerance. A potential mechanism for poor health is increased energy intake (i.e., eating), particularly during the circadian night, when the physiological response to energy intake is altered. However, the contributions of CCD and insufficient sleep to subjective hunger, appetite, food preference, and appetitive hormones are not clear. To disentangle the influences of these factors, we studied seventeen healthy young adults in a 32-day in-laboratory study designed to distribute sleep, wakefulness, and energy intake equally across all phases of the circadian cycle, thereby imposing CCD. Participants were randomized to the Control (1:2 sleep:wake ratio, n = 8) or chronic sleep restriction (CSR, 1:3.3 sleep:wake ratio, n = 9) conditions. Throughout each waking episode the participants completed visual analog scales pertaining to hunger, appetite, and food preference. A fasting blood sample was collected to assess appetitive hormones. CCD was associated with a significant decrease in hunger and appetite in a multitude of domains in both the Control and CSR groups. This change in hunger was significantly correlated with changes in the ghrelin/leptin ratio. These findings further our understanding of the contributions of CCD and insufficient sleep on subjective hunger and appetite as well as of their possible contributions to adverse health behaviors.

Assessing temporal eating pattern in free living humans through the myCircadianClock app

The quality and quantity of nutrition impact health. However, chrononutrition, the timing, and variation of food intake in relation to the daily sleep-wake cycle are also important contributors to health. This has necessitated an urgent need to measure, analyze, and optimize eating patterns to improve health and manage disease. While written food journals, questionnaires, and 24-hour dietary recalls are acceptable methods to assess the quantity and quality of energy consumption, they are insufficient to capture the timing and day-to-day variation of energy intake. Smartphone applications are novel methods for information-dense real-time food and beverage tracking. Despite the availability of thousands of commercial nutrient apps, they almost always ignore eating patterns, and the raw real-time data is not available to researchers for monitoring and intervening in eating patterns. Our lab developed a smartphone app called myCircadianClock (mCC) and associated software to enable long-term real-time logging that captures temporal components of eating patterns. The mCC app runs on iOS and android operating systems and can be used to track multiple cohorts in parallel studies. The logging burden is decreased by using a timestamped photo and annotation of the food/beverage being logged. Capturing temporal data of consumption in free-living individuals over weeks/months has provided new insights into diverse eating patterns in the real world. This review discusses (1) chrononutrition and the importance of understanding eating patterns, (2) the myCircadianClock app, (3) validation of the mCC app, (4) clinical trials to assess the timing of energy intake, and (5) strengths and limitations of the mCC app.

Too Much Dietary Flexibility May Hinder, Not Help: Could More Specific Targets for Daily Food Intake Distribution Promote Glycemic Management among Youth with Type 1 Diabetes?

Average glycemic levels among youth with type 1 diabetes (T1D) have worsened in some parts of the world over the past decade despite simultaneous increased uptake of diabetes technology, thereby highlighting the persistent need to identify effective behavioral strategies to manage glycemia during this life stage. Nutrition is fundamental to T1D management. We reviewed the evidence base of eating strategies tested to date to improve glycemic levels among youth with T1D in order to identify promising directions for future research. No eating strategy tested among youth with T1D since the advent of flexible insulin regimens—including widely promoted carbohydrate counting and low glycemic index strategies—is robustly supported by the existing evidence base, which is characterized by few prospective studies, small study sample sizes, and lack of replication of results due to marked differences in study design or eating strategy tested. Further, focus on macronutrients or food groups without consideration of food intake distribution throughout the day or day-to-day consistency may partially underlie the lack of glycemic benefits observed in studies to date. Increased attention paid to these factors by future observational and experimental studies may facilitate identification of behavioral targets that increase glycemic predictability and management among youth with T1D.

Effects of Dietary Fat to Carbohydrate Ratio on Obesity Risk Depending on Genotypes of Circadian Genes

Although the impacts of macronutrients and the circadian clock on obesity have been reported, the interactions between macronutrient distribution and circadian genes are unclear. The aim of this study was to explore macronutrient intake patterns in the Korean population and associations between the patterns and circadian gene variants and obesity. After applying the criteria, 5343 subjects (51.6% male, mean age 49.4 ± 7.3 years) from the Korean Genome and Epidemiology Study data and nine variants in seven circadian genes were analyzed. We defined macronutrient intake patterns by tertiles of the fat to carbohydrate ratio (FC). The very low FC (VLFC) was associated with a higher risk of obesity than the optimal FC (OFC). After stratification by the genotypes of nine variants, the obesity risk according to the patterns differed by the variants. In the female VLFC, the major homozygous allele of CLOCK rs11932595 and CRY1 rs3741892 had a higher abdominal obesity risk than those in the OFC. The GG genotype of PER2 rs2304672 in the VLFC showed greater risks for obesity and abdominal obesity. In conclusion, these findings suggest that macronutrient intake patterns were associated with obesity susceptibility, and the associations were different depending on the circadian clock genotypes of the CLOCK, PER2, and CRY1 loci.

Disruption of the circadian rhythms and its relationship with pediatric obesity

The circadian clock system is an evolutionarily conserved system by which organisms adapt their metabolic activities to environmental inputs, including nutrient availability. The disruption of this system has been pathogenically linked to the disintegration of metabolic homeostasis, leading to the development of metabolic complications, including obesity. Lifestyle factors that disrupt this system have been found to be associated with the development of metabolic disorder, which is most evidenced by the finding that shift workers are at an increased risk of developing various disorders, such as obesity and obesity-related complications. Lifestyle factors that contribute to a misalignment between the internal clock system and environmental rhythms have also been identified in children. A short sleep duration and skipping breakfast are prevalent in children and there is mounting evidence that these factors are associated with an increased risk of pediatric obesity; however, the underlying mechanisms have not yet been elucidated in detail. Our current understanding of the impact of lifestyle factors that cause a misalignment between the internal clock system and environmental rhythms on the development of pediatric obesity is summarized herein, with a discussion of potential mechanistic factors.

Disturbance of the Circadian System in Shift Work and Its Health Impact

The various non-standard schedules required of shift workers force abrupt changes in the timing of sleep and light-dark exposure. These changes result in disturbances of the endogenous circadian system and its misalignment with the environment. Simulated night-shift experiments and field-based studies with shift workers both indicate that the circadian system is resistant to adaptation from a day- to a night-oriented schedule, as determined by a lack of substantial phase shifts over multiple days in centrally controlled rhythms, such as those of melatonin and cortisol. There is evidence that disruption of the circadian system caused by night-shift work results not only in a misalignment between the circadian system and the external light-dark cycle, but also in a state of internal desynchronization between various levels of the circadian system. This is the case between rhythms controlled by the central circadian pacemaker and clock genes expression in tissues such as peripheral blood mononuclear cells, hair follicle cells, and oral mucosa cells. The disruptive effects of atypical work schedules extend beyond the expression profile of canonical circadian clock genes and affects other transcripts of the human genome. In general, after several days of living at night, most rhythmic transcripts in the human genome remain adjusted to a day-oriented schedule, with dampened group amplitudes. In contrast to circadian clock genes and rhythmic transcripts, metabolomics studies revealed that most metabolites shift by several hours when working nights, thus leading to their misalignment with the circadian system. Altogether, these circadian and sleep-wake disturbances emphasize the all-encompassing impact of night-shift work, and can contribute to the increased risk of various medical conditions. Here, we review the latest scientific evidence regarding the effects of atypical work schedules on the circadian system, sleep and alertness of shift-working populations, and discuss their potential clinical impacts.

Temporal Eating Patterns and Eating Windows among Adults with Overweight or Obesity

We aim to describe temporal eating patterns in a population of adults with overweight or obesity. In this cross-sectional analysis, data were combined from two separate pilot studies during which participants entered the timing of all eating occasions (>0 kcals) for 10-14 days. Data were aggregated to determine total eating occasions, local time of the first and last eating occasions, eating window, eating midpoint, and within-person variability of eating patterns. Eating patterns were compared between sexes, as well as between weekday and weekends. Participants (n = 85) had a median age of 56 ± 19 years, were mostly female (>70%), white (56.5%), and had a BMI of 31.8 ± 8.0 kg/m². The median eating window was 14 h 04 min [12 h 57 min-15 h 21 min], which was significantly shorter on the weekend compared to weekdays (p < 0.0001). Only 13.1% of participants had an eating window <12 h/d. Additionally, there was greater irregularity with the first eating occasion during the week when compared to the weekend (p = 0.0002). In conclusion, adults with overweight or obesity have prolonged eating windows (>14 h/d). Future trials should examine the contribution of a prolonged eating window on adiposity independent of energy intake.

Do Temporal Eating Patterns Differ in Healthy versus Unhealthy Overweight/Obese Individuals?

This study examined whether the temporal patterns of energy and macronutrient intake in early and late eating windows were associated with metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) among non-shift workers. A total of 299 overweight/obese non-shift workers (Age: 40.3 ± 6.9 years; 73.6% women; BMI: 31.7 ± 5.0 kg/m²) were recruited in the Klang Valley area of Malaysia. The biochemical parameters were determined from fasting blood samples, whereas information on dietary intake and timing was obtained from a 7-day diet history questionnaire. The midpoint of eating was used to determine the early and late windows. Compared to MHO non-shift workers (n = 173), MUO non-shift workers (n = 126) had lower energy intake from carbohydrates and protein during the early window. In contrast, MUO participants had greater energy intake from carbohydrates and fat during the late window. Participants with unhealthy metabolic status (regardless of their chronotypes) had similar temporal patterns of energy intake characterized by smaller energy intake during the early window and greater energy intake during the late window compared with participants with healthier metabolic status. Overall, the lowest percentile of energy intake during the early window was associated with an increased risk of MUO, after adjustment for potential confounders [odds ratio (OR) = 4.30, 95% confidence interval (CI) 1.41-13.11]. The greater the energy intake during the late window, the greater the risk of MUO (OR = 2.38, 95% CI 1.11-5.13) (OR = 2.33, 95% CI 1.03-5.32) (OR = 4.45, 95% CI 1.71-11.56). In summary, consuming less energy earlier in the day and more energy and carbohydrate later in the day was associated with a greater risk of MUO. Thus, a prospective study is needed to explore the potential role of chrono-nutrition practices in modifying risk factors to delay the transition of MHO to MUO.

Chronobiology and Metabolism: Is Ketogenic Diet Able to Influence Circadian Rhythm?

Circadian rhythms underpin most physiological processes, including energy metabolism. The core circadian clock consists of a transcription-translation negative feedback loop, and is synchronized to light-dark cycles by virtue of light input from the retina, to the central clock in the suprachiasmatic nucleus in the hypothalamus. All cells in the body have circadian oscillators which are entrained to the central clock by neural and humoral signals. In addition to light entrainment of the central clock in the brain, it now emerges that other stimuli can drive circadian clock function in peripheral tissues, the major one being food. This can then drive the liver clock to be misaligned with the central brain clock, a situation of internal misalignment with metabolic disease consequences. Such misalignment is prevalent, with shift workers making up 20% of the working population. The effects of diet composition on the clock are not completely clarified yet. High-fat diet and fasting influence circadian expression of clock genes, inducing phase-advance and phase-delay in animal models. Ketogenic diet (KD) is able to induce a metabolic switch from carbohydrate to fatty acid oxidation, miming a fasting state. In recent years, some animal studies have been conducted to investigate the ability of the KD to modify circadian gene expression, and demonstrated that the KD alters circadian rhythm and induces a rearrangement of metabolic gene expression. These findings may lead to new approaches to obesity and metabolic pathologies treatment.

The impact of circadian timing on energy balance: an extension of the energy balance model

A significant proportion of the population is classified as having overweight or obesity. One framework which has attempted to explain biobehavioral mechanisms influencing the development of overweight and obesity is the energy balance model. According to this model, the body continually attempts to balance energy intake with energy expenditure. When energy intake and energy expenditure become imbalanced, there is an increase in homeostatic and allostatic pressure, generally to either increase energy intake or decrease energy expenditure, so as to restore energy homeostasis.Recent research has indicated that circadian aspects of energy intake and energy expenditure may influence energy balance. This paper provides a narrative review of existing evidence of the role of circadian timing on components of energy balance. Research on the timing of food intake, physical activity, and sleep indicates that unhealthy timing is likely to increase risk of weight gain. Public health guidelines focus on how much individuals eat and sleep, what foods are consumed, and the type and frequency of exercise, but the field of circadian science has begun to demonstrate that when these behaviors occur may also influence overweight and obesity prevention and treatment efforts.

Robust stability of melatonin circadian phase, sleep metrics, and chronotype across months in young adults living in real-world settings

Appropriate synchronization of the timing of behaviors with the circadian clock and adequate sleep are both important for almost every physiological process. The timing of the circadian clock relative to social (ie, local) clock time and the timing of sleep can vary greatly among individuals. Whether the timing of these processes is stable within an individual is not well-understood. We examined the stability of circadian-controlled melatonin timing, sleep timing, and their interaction across ~ 100 days in 15 students at a single university. At three time points ~ 35-days apart, circadian timing was determined from the dim-light melatonin onset (DLMO). Sleep behaviors (timing and duration) and chronotype (ie, mid-sleep time on free days corrected for sleep loss on school/work days) were determined via actigraphy and analyzed in ~ 1-month bins. Melatonin timing was stable, with an almost perfect relationship strength as determined via intraclass correlation coefficients ([ICC]=0.85); average DLMO timing across all participants only changed from the first month by 21 minutes in month 2 and 5 minutes in month 3. Sleep behaviors also demonstrated high stability, with ICC relationship strengths ranging from substantial to almost perfect (ICCs = 0.65-0.85). Average DLMO was significantly associated with average chronotype (r²  = 0.53, P <.01), with chronotype displaying substantial stability across months (ICC = 0.61). These findings of a robust stability in melatonin timing and sleep behaviors in young adults living in real-world settings holds promise for a better understanding of the reliability of previous cross-sectional reports and for the future individualized strategies to combat circadian-associated disease and impaired safety (ie, "chronomedicine").

Harnessing SmartPhones to Personalize Nutrition in a Time of Global Pandemic

The soar in COVID-19 cases around the globe has forced many to adapt to social distancing and self-isolation. In order to reduce contact with healthcare facilities and other patients, the CDC has advocated the use of telemedicine, i.e., electronic information and telecommunication technology. While these changes may disrupt normal behaviors and routines and induce anxiety, resulting in decreased vigilance to healthy diet and physical activity and reluctance to seek medical attention, they may just as well be circumvented using modern technology. Indeed, as the beginning of the pandemic a plethora of alternatives to conventional physical interactions were introduced. In this Perspective, we portray the role of SmartPhone applications (apps) in monitoring healthy nutrition, from their basic functionality as food diaries required for simple decision-making and nutritional interventions, through more advanced purposes, such as multi-dimensional data-mining and development of machine learning algorithms. Finally, we will delineate the emerging field of personalized nutrition and introduce pioneering technologies and concepts yet to be incorporated in SmartPhone-based dietary surveillance.

Chrono-nutrition: From molecular and neuronal mechanisms to human epidemiology and timed feeding patterns

The circadian timing system governs daily biological rhythms, synchronising physiology and behaviour to the temporal world. External time cues, including the light-dark cycle and timing of food intake, provide daily signals for entrainment of the central, master circadian clock in the hypothalamic suprachiasmatic nuclei (SCN), and of metabolic rhythms in peripheral tissues, respectively. Chrono-nutrition is an emerging field building on the relationship between temporal eating patterns, circadian rhythms, and metabolic health. Evidence from both animal and human research demonstrates adverse metabolic consequences of circadian disruption. Conversely, a growing body of evidence indicates that aligning food intake to periods of the day when circadian rhythms in metabolic processes are optimised for nutrition may be effective for improving metabolic health. Circadian rhythms in glucose and lipid homeostasis, insulin responsiveness and sensitivity, energy expenditure, and postprandial metabolism, may favour eating patterns characterised by earlier temporal distribution of energy. This review details the molecular basis for metabolic clocks, the regulation of feeding behaviour, and the evidence for meal timing as an entraining signal for the circadian system in animal models. The epidemiology of temporal eating patterns in humans is examined, together with evidence from human intervention studies investigating the metabolic effects of morning compared to evening energy intake, and emerging chrono-nutrition interventions such as time-restricted feeding. Chrono-nutrition may have therapeutic application for individuals with and at-risk of metabolic disease and convey health benefits within the general population.

Circadian rhythms and the gut microbiota: from the metabolic syndrome to cancer

The metabolic syndrome is prevalent in developed nations and accounts for the largest burden of non-communicable diseases worldwide. The metabolic syndrome has direct effects on health and increases the risk of developing cancer. Lifestyle factors that are known to promote the metabolic syndrome generally cause pro-inflammatory alterations in microbiota communities in the intestine. Indeed, alterations to the structure and function of intestinal microbiota are sufficient to promote the metabolic syndrome, inflammation and cancer. Among the lifestyle factors that are associated with the metabolic syndrome, disruption of the circadian system, known as circadian dysrhythmia, is increasingly common. Disruption of the circadian system can alter microbiome communities and can perturb host metabolism, energy homeostasis and inflammatory pathways, which leads to the metabolic syndrome. This Perspective discusses the role of intestinal microbiota and microbial metabolites in mediating the effects of disruption of circadian rhythms on human health.

Stability of the timing of food intake at daily and monthly timescales in young adults

Cross-sectional observations have shown that the timing of eating may be important for health-related outcomes. Here we examined the stability of eating timing, using both clock hour and relative circadian time, across one semester (n = 14) at daily and monthly time-scales. At three time points ~ 1 month apart, circadian phase was determined during an overnight in-laboratory visit and eating was photographically recorded for one week to assess timing and composition. Day-to-day stability was measured using the Composite Phase Deviation (deviation from a perfectly regular pattern) and intraclass correlation coefficients (ICC) were used to determine individual stability across months (weekly average compared across months). Day-to-day clock timing of caloric events had poor stability within individuals (~ 3-h variation; ICC = 0.12-0.34). The timing of eating was stable across months (~ 1-h variation, ICCs ranging from 0.54-0.63), but less stable across months when measured relative to circadian timing (ICC = 0.33-0.41). Our findings suggest that though day-to-day variability in the timing of eating has poor stability, the timing of eating measured for a week is stable across months within individuals. This indicates two relevant timescales: a monthly timescale with more stability in eating timing than a daily timescale. Thus, a single day's food documentation may not represent habitual (longer timescale) patterns.

Timing and Frequency of Daily Energy Intake in Adults with Prediabetes and Overweight or Obesity and Their Associations with Body Fat

Knowledge on how energy intake and macronutrients are distributed during the day and the role of daily eating patterns in body composition among adults with overweight/obesity and prediabetes is lacking. Therefore, we evaluated the diurnal dietary intake and studied the associations of daily eating patterns with body fat percentage. A total of 119 adults with prediabetes were included (mean (SD) HbA_1c 41 (2.3) mmol/mol, BMI 31.5 (5.0) kg/m², age 57.8 (9.3) years, 44% men). Information on dietary intake was obtained from self-reported food records for three consecutive days. All foods and beverages (except water) were registered with information on time of ingestion. Body fat was measured by dual-energy X-ray absorptiometry. A total of 60.5% of the participants reported a daily eating window of 12 or more hours/day, and almost half of the daily total energy intake was reported in the evening. In analyses adjusted for age, gender, and total daily energy intake, having the first daily energy intake one hour later was associated with slightly higher body fat percentage (0.64% per hour, 95% CI: 0.28; 1.01; p < 0.001), whereas higher meal frequency was associated with slightly lower body fat percentage (0.49% per extra daily meal, 95% CI: −0.81; −0.18; p = 0.002). Prospective studies are warranted to address the clinical implications of daily eating patterns on body fat and cardiometabolic health.

Circadian rhythms and meal timing: impact on energy balance and body weight

Energy metabolism and appetite regulating hormones follow circadian rhythms which, when disrupted, could lead to adverse metabolic consequences. Such circadian misalignment, a mismatch between endogenous circadian rhythms and behavior, is most severely experienced by shift workers, due to nighttime wake, daytime sleep, and eating at night. However, circadian misalignment is not restricted to shift workers; milder shifts in sleep and mealtimes, termed social and eating jetlag, are highly prevalent in the general population. Social and eating jetlag result in later mealtimes, which may promote positive energy balance and weight gain. Earlier meal timing, specific to individual endogenous circadian patterns, could serve to reduce cardiometabolic disease burden and aid in weight loss and interventions should be done to test this.

Is the timing of food intake a potential indicator of low weight loss responders? A secondary analysis of three weight loss studies

Individual variability in weight loss in response to a weight loss intervention is commonly observed. Recently, the timing of food intake has been identified as one possible factor implicated in obesity and weight loss. The objective of this study was to further characterize low weight loss responders by assessing the pre-diet distribution of daily energy and macronutrient intakes. A pooled cohort of men and women (n = 122; aged 39.1 ± 8.2 years; body mass index [BMI] 33.1 ± 3.8 kg/m² ) who participated in a 12 to 15 week energy-restricted intervention (-500 to -700 kcal/d) were included in this study. Participants were categorized into two weight loss groups (ie, low [-1.3 ± 2.3 kg] and high [-6.1 ± 2.1 kg] weight loss). Food intake and distribution of energy and macronutrient intakes were assessed using a 3-day food record at baseline. The daily distribution of energy intake (% of total energy intake) was similar in the two weight loss groups with the exception of the low weight loss group who consumed a slightly lower proportion of their total energy intake before 9:00 am compared with the high weight loss group (12.5% ± 5.8% vs 15.0% ± 6.6%, respectively, P = .03). In the low weight loss group, the percentage of energy intake consumed after 8:00 pm was positively associated with total energy intake (r = 0.27, P = .04). The results of this study suggest that the timing of food intake measured prior to a weight loss intervention does not permit the characterization of low weight loss responders.

Effects of Shift Work on the Eating Behavior of Police Officers on Patrol

Recent studies indicate that the timing of food intake can significantly affect metabolism and weight management. Workers operating at atypical times of the 24-h day are at risk of disturbed feeding patterns. Given the increased risk of weight gain, obesity and metabolic syndrome in shift working populations, further research is required to understand whether their eating behavior could contribute to these increased metabolic risks. The objective of this study was to characterize the dietary patterns of police officers across different types of shifts in their natural environments. Thirty-one police officers (six women; aged 32.1 ± 5.4 years, mean ± SD) from the province of Quebec, Canada, participated in a 28- to 35-day study, comprising 9- to 12-h morning, evening, and night shifts alternating with rest days. Sleep and work patterns were recorded with actigraphy and diaries. For at least 24 h during each type of work day and rest day, participants logged nutrient intake by timestamped photographs on smartphones. Macronutrient composition and caloric content were estimated by registered dieticians using the Nutrition Data System for Research database. Data were analyzed with linear mixed effects models and circular ANOVA. More calories were consumed relative to individual metabolic requirements on rest days than both evening- and night-shift days (p = 0.001), largely sourced from increased fat (p = 0.004) and carbohydrate (trend, p = 0.064) intake. Regardless, the proportions of calories from carbohydrates, fat, and protein did not differ significantly between days. More calories were consumed during the night, between 2300 h and 0600 h, on night-shift days than any other days (p < 0.001). Caloric intake occurred significantly later for night-shift days (2308 h ± 0114 h, circular mean ± SD) than for rest days (1525 h ± 0029 h; p < 0.01) and was dispersed across a longer eating window (13.9 h ± 3.1 h vs. 11.3 h ± 1.8 h, mean ± SD). As macronutrient proportions were similar and caloric intake was lower, the finding of later meals times on night-shift days versus rest days is consistent with emerging hypotheses that implicate the biological timing of food intake—rather than its quantity or composition—as the differentiating dietary factor in shift worker health.

Early Morning Food Intake as a Risk Factor for Metabolic Dysregulation

Increased risk of obesity and diabetes in shift workers may be related to food intake at adverse circadian times. Early morning shiftwork represents the largest proportion of shift workers in the United States, yet little is known about the impact of food intake in the early morning on metabolism. Eighteen participants (9 female) completed a counterbalanced 16 day design with two conditions separated by ~1 week: 8 h sleep opportunity at habitual time and simulated early morning shiftwork with 6.5 h sleep opportunity starting ~1 h earlier than habitual time. After wake time, resting energy expenditure (REE) was measured and blood was sampled for melatonin and fasting glucose and insulin. Following breakfast, post-prandial blood samples were collected every 40 min for 2 h and the thermic effect of food (TEF) was assessed for 3.25 h. Total sleep time was decreased by ~85 min (p < 0.0001), melatonin levels were higher (p < 0.0001) and post-prandial glucose levels were higher (p < 0.05) after one day of simulated early morning shiftwork compared with habitual wake time. REE was lower after simulated early morning shiftwork; however, TEF after breakfast was similar to habitual wake time. Insufficient sleep and caloric intake during a circadian phase of high melatonin levels may contribute to metabolic dysregulation in early morning shift workers.

Effectiveness of Intermittent Fasting and Time-Restricted Feeding Compared to Continuous Energy Restriction for Weight Loss

The current obesity epidemic is staggering in terms of its magnitude and public health impact. Current guidelines recommend continuous energy restriction (CER) along with a comprehensive lifestyle intervention as the cornerstone of obesity treatment, yet this approach produces modest weight loss on average. Recently, there has been increased interest in identifying alternative dietary weight loss strategies that involve restricting energy intake to certain periods of the day or prolonging the fasting interval between meals (i.e., intermittent energy restriction, IER). These strategies include intermittent fasting (IMF; >60% energy restriction on 2-3 days per week, or on alternate days) and time-restricted feeding (TRF; limiting the daily period of food intake to 8-10 h or less on most days of the week). Here, we summarize the current evidence for IER regimens as treatments for overweight and obesity. Specifically, we review randomized trials of ≥8 weeks in duration performed in adults with overweight or obesity (BMI ≥ 25 kg/m²) in which an IER paradigm (IMF or TRF) was compared to CER, with the primary outcome being weight loss. Overall, the available evidence suggests that IER paradigms produce equivalent weight loss when compared to CER, with 9 out of 11 studies reviewed showing no differences between groups in weight or body fat loss.

Assessment of Circadian Rhythms

Circadian rhythms are observed in most physiologic functions across a variety of species and are controlled by a master pacemaker in the brain called the suprachiasmatic nucleus. The complex nature of the circadian system and the impact of circadian disruption on sleep, health, and well-being support the need to assess internal circadian timing in the clinical setting. The ability to assess circadian rhythms and the degree of circadian disruption can help in categorizing subtypes or even new circadian rhythm disorders and aid in the clinical management of the these disorders.