Chrononutrition and Cardiometabolic Health: An Overview of Epidemiological Evidence and Key Future Research Directions

Chrononutrition is a rapidly evolving field of nutritional epidemiology that addresses the complex relationship between temporal eating patterns, circadian rhythms, and metabolic health to elucidate how eating timing metrics influence health preservation and chronic disease risk [1,2,3]. The timing of food intake relative to circadian rhythms, representing the innate 24 h cycles in human behavior, physiology, and metabolism, may be particularly important for preserving cardiometabolic health (CMH) and preventing cardiovascular disease (CVD). While light exposure is the predominant zeitgeber, food intake also entrains the circadian system, and research shows that metabolic health is influenced not just by the quantity and quality of dietary intake, but also by the timing, regularity, and energy distribution of eating occasions in the 24 h day and across days [3,4]. Indeed, aspects of chrononutrition, stemming from environmental, cultural, and physiological factors as well as personal preference and lifestyle choices that alter eating behaviors, have been linked to the etiology of CVD, type 2 diabetes, metabolic syndrome, hypertension, and obesity [5].

Enhancing cardiometabolic disease prevention approaches with strategies grounded in chrononutrition could play a pivotal role in reducing the public health burden of these conditions [1]. Through targeted health education and promotion measures, individuals can be informed about the implications of eating timing on health and guided towards establishing and preserving consistent eating routines synchronous with their circadian rhythms. Such measures could potentially delay the emergence of metabolic risk factors linked to cardiometabolic and cardiovascular diseases or aid in their management. For example, "Life's Essential 8", a cardiovascular health construct developed by the American Heart Association (AHA) to guide primordial prevention efforts, includes diet as a metric [6]. However, this metric mainly addresses dietary quality and excludes dietary dimensions related to the timing of meals and other eating occasions. Screening for and addressing eating timing and regularity could potentially provide a more comprehensive assessment of nutritional health and unlock the true potential of dietary approaches in primordial prevention efforts aimed at CMH preservation.

Despite the immense promise of this field for addressing the chronic disease burden and persistent CMH inequities, many knowledge gaps remain. This topical review summarizes the epidemiologic evidence, encompassing both observational and intervention studies, on temporal eating patterns in relation to CMH. Given that multiple prior reviews have focused on time-restricted feeding and nightly fasting duration in relation to CMH [3,7,8], we focused this review on associations of eating timing, meal skipping, and eating timing regularity with cardiometabolic outcomes and CVD. We also highlight knowledge gaps and important research directions necessary to advance the field and translate chrononutrition research into public health policy and action.

Despite the widely held view that breakfast holds paramount importance as the day's initial meal, research indicates that 20% to 30% of US adults regularly omit this eating occasion [9]. Further, there has been a decline in the reported consumption of breakfast and lunch over the past 40 years [10]. Similar trends are observed in Asian populations; for instance, a multicenter Japanese study showed that ~23% of adults skipped breakfast [11], and ~45% of Korean adults do not report caloric intake during the morning hours [12]; this proportion is even higher among Korean office workers (~70%) who report skipping breakfast due to time constraints [13]. In the Mediterranean population, breakfast, lunch, and dinner are typically consumed later than in the US and other populations [14,15,16]. For example, lunch is consumed, on average, between 2:00 and 3:00 pm, compared to 1:00 and 2:00 pm in the US population [14,15]. Notably, within the framework of the Mediterranean diet, lunch holds particular importance, accounting for approximately 40% of the daily caloric consumption compared to about 24% in the US [17,18].

In terms of the distribution of calories across the 24 h day, data from a smartphone application show that US adults eat around the clock and that calorie consumption extends beyond typical meal hours [19]. There is also a tendency for later eating timing, as >75% of caloric intake occurs after noon with ~38% of calories consumed after 6:00 pm [19]. A tendency for substantial nighttime eating was also observed in the National Health and Nutrition Examination (NHANES) survey, whereby over a third of individuals reported consuming ≥25% of their daily caloric intake after 7:00 pm and ~10% reported consuming ≥50% of caloric intake after 7:00 pm or any calorie intake after 11:00 pm [20].

In addition to eating timing within the 24 h day, eating timing across days has emerged as a novel potential contributor to CMH [19,2021,22]. The term 'eating jet lag' describes the difference in mealtimes between weekdays and weekends [21,22]. In a 2021 study examining racially and ethnically diverse US women, the timing of the first eating occasion was ~1.5 h later on weekends than on weekdays [22]. Similarly, breakfast timing was ~2 h later on weekends relative to weekdays in a study of young Spanish and Mexican adults [21]. In NHANES and the Continuing Survey of Food Intakes by Individuals, night eating (i.e., ≥25% kcal after 7:00 pm, ≥50% kcal after 7:00 pm, and any eating after 11:00 pm) was more common during the weekend than weekday [20]. Consistent with these findings, data from a smartphone app revealed that US adults have erratic eating timing patterns with substantial day-to-day variation, particularly for timing of the first eating occasion with later eating start times being observed on weekends compared to weekdays (10:26 vs. 09:21 am) [19].

Sociocultural, economic, and environmental factors can substantially influence when someone eats and could help to explain differences in temporal eating patterns observed across populations [23]. In Mediterranean cultures, lunch accounts for a substantial proportion of daily caloric intake, despite the later overall timing of lunches and dinners; whereas in the USA and in central and northern European countries, dinner and after dinner snacks tend to account for the largest percentage of daily caloric intake [10,16,23]. Further, the emphasis on breakfast consumption could vary across cultures with breakfast skipping predisposing to later eating timing and higher caloric intake in the evening and generally being linked to having a lower socioeconomic status [24,25]. Relatedly, being an essential worker and/or a shift worker is also associated with later and irregular eating timing patterns [25,26]. This can help to explain the higher prevalence of adverse cardiometabolic outcomes among essential workers and shift workers and among minoritized populations that tend to be overrepresented in these occupations.

Individual behavioral factors can also influence the timing of food intake, the most notable of which is sleep. Having a shorter sleep duration and going to bed later provides more opportunities for later eating timing; in addition, irregular sleep schedules are likely correlated with irregular eating schedules [23]. This is exacerbated by light exposure at night, which can delay sleep and extend eating periods later into the night. Other dietary dimensions can also influence meal timing; for instance, food insecurity can lead to less structured mealtimes and irregular eating timing patterns [27]. In addition, there is likely a bidirectional association between chrononutrition metrics and diet quality, with later eating times being linked to unhealthy food choices and exacerbating the adverse health effects of poor diet quality [28,29]. However, there is a dearth of evidence on the behavioral underpinnings of temporal eating patterns, particularly the influence of sleep health, physical activity, and other diet dimensions on when someone eats. Other individual-level characteristics such as age, sex, chronotype, genetic predisposition and health status could also shape eating timing patterns, with later and less structured eating times observed among those with later chronotypes (representing the behavioral manifestation of endogenous circadian rhythms), in younger age groups, and among individuals with obesity [23,30]. The multi-level predictors of chrononutrition metrics influencing cardiometabolic outcomes and the attainment of health equity and warranting further investigation are summarized in Figure 1.

The influence of eating timing on CMH operates through various mechanisms related to circadian rhythm disruption, metabolic and inflammatory processes, hormonal imbalances, and other behavioral factors (Figure 2) [3,31,32]. Although the rhythm of the central circadian clock (located in the suprachiasmatic nucleus of the hypothalamus) aligns predominantly with photic cues, the rhythms of peripheral tissues are primarily governed by external cues such as food intake, a powerful zeitgeber [33,34]. Adverse temporal eating patterns, characterized by delayed and irregular eating timing, can disrupt the synchrony of these peripheral clocks with the central clock, resulting in circadian misalignment [34]. Circadian misalignment disrupts metabolic regulation or homeostasis, resulting in impaired glucose control, increased insulin levels, insulin resistance, and a glucose response that mimics a prediabetic state [35]. Notably, late eating has been shown to decrease glucose tolerance and impair pancreatic beta cell function in individuals carrying the MTNR1B type 2 diabetes risk variant [36]. Eating timing also entrains blood pressure (BP) levels and circadian patterns [37]. Short-term circadian misalignment has been shown to elevate BP by modulating the autonomic nervous system, reducing sympathetic activity while increasing parasympathetic activity. Circadian misalignment also diminishes the secretion of melatonin, which is known to lower BP [38]. Additionally, later and irregular eating timing patterns are associated with higher C-reactive protein (CRP), a marker of systemic inflammation linked to high BP and other cardiovascular complications [32,39].

Later eating timing and circadian misalignment from mismatched eating patterns and endogenous rhythms can also alter appetite-regulating hormones, increasing the risk of obesity and its metabolic sequelae [35]. For example, inverting behavioral cycles by ~12 h can suppress leptin and lead to increased appetite and decreased energy expenditure. Overall, later eating timing alters appetite-regulating hormones by reducing 24 h serum leptin and increasing the 24 h ghrelin–leptin ratio, promoting increased hunger [40]. It is also associated with decreased energy expenditure during the day and changes in gene expression that favor increased lipid storage and promote obesity [40]. Lastly, the timing of high-energy meals can impact fat accumulation and metabolism through the adipose tissue clock, potentially contributing to dyslipidemia and obesity [41].

Other potential mechanisms requiring further investigation include the impact of eating timing on the gut microbiome and gene expression. Alterations in the composition, function, and rhythms of the human gastrointestinal microbiota, as well as changes in clock and metabolic gene expression, have been reported in response to eating timing cues in emerging studies [42,43]. For example, later eating timing has been shown to induce changes in the microbiota similar to those observed in women with obesity or in older age [44]. In terms of the interplay of eating timing with genetic factors, the PERIOD2 (PER2) genes have been associated with Night Eating Syndrome in prior research [45]. In addition, the minor allele (G) of the CLOCK rs4580704 SNP, associated with obesity, has been shown to be more prevalent among late eaters (after 3:00 pm) compared to early eaters (before 3:00 pm) and has been linked to consumption of a later lunch [17]. Indeed, it appears that the heritability of food timing may vary by meal; a Spanish study of twins showed that it ranged from 56% for breakfast, 38% for lunch, to being undetectable for dinner [46]. Another study of twin pairs showed ~24% heritability for the timing of breakfast, and lower heritability estimates for lunch and dinner timing (18–22%) [47]. There is also evidence of a potential shared genetic architecture between food timing and chronotype that warrants further investigation [46,47].

There is likely a bidirectional association between eating timing and mental health, which can influence eating habits and the quality of food intake [48,49,50]. Shift workers, who often experience misalignment between their internal circadian rhythms and daily eating schedules, are at increased risk of depression and anxiety [49,51]. Consuming meals during daytime hours versus during both the daytime and nighttime has been shown to reduce levels of depression-like and anxiety-like moods [52]. Furthermore, the timing and regularity of eating patterns may influence other health behaviors that impact CMH [53,54,55,56]. For example, both skipping breakfast and irregular eating patterns have been linked to lower sleep quality and reduced physical activity [55,57]. Lastly, eating timing may influence diet quality; individuals who consume food during the nighttime tend to have a higher energy intake from snacks, a greater percentage of their daily energy intake coming from fats, and lower dietary diversity scores [58].

A major obstacle to accurately interpreting the evidence on eating timing and regularity in relation to CMH is the heterogeneity in how eating timing, regularity, and the extent of evening eating are defined and measured, making it challenging to compare findings across both observational and intervention studies. For instance, some studies evaluate eating timing (e.g., timing of last eating occasion) while others evaluate meal timing (e.g., timing of self-defined supper or dinner). Similarly, studies evaluating the distribution of caloric intake across the 24 h day may examine the distribution of calories across time bins or meals, at the largest self-identified evening meal (e.g., dinner) or past certain clock times (e.g., % kcal consumed after 5:00 pm or 8:00 pm). In studies of eating regularity, the standard deviation of multiple eating timing metrics has been used to assess day-to-day variability [32], while weekday–weekend differences have been used to capture eating jetlag [21]. Collectively, these variables measure distinct chrononutrition concepts, limiting the ability to draw definitive conclusions and make public health recommendations.

Another important aspect to consider is the methodologies used to assess temporal eating patterns. First, most population-based cohort studies use food frequency questionnaires that lack time-stamped diet data, making the chrononutrition dimension of diet difficult to integrate into observational studies of diet and CMH. Second, most studies rely on self-report, which limits the number of days of diet assessment due to participant burden considerations and introduces measurement error. Studies typically rely on a limited number of 24 h recalls, often collected on non-consecutive days or at a single time point, which are not necessarily representative of habitual intakes. Low-cost, validated diet assessment methods with acceptable participant burden are needed to implement chrononutrition metrics measurement in population studies, enable cross-study comparisons, and support the meaningful translation of research on temporal eating patterns into interventions and public health guidelines aimed at promoting optimal CMH.

Although there is promising emerging evidence from intervention studies, which allow the establishment of causality, regarding the CMH benefits of early and regular eating schedules, modest sample sizes and short follow-up durations are notable limitations. Further, the recruitment of racially and ethnically diverse samples would enhance the generalizability of findings. These methodological limitations, coupled with the inconsistent findings across the heterogenous intervention protocols and the limited data on underlying physiological mechanisms, are barriers to making evidence-based public health guidelines related to eating timing and regularity.

To advance this field, longitudinal population-based cohort studies of racially and ethnically diverse participants encompassing different life stages are needed to evaluate chrononutrition metrics in relation to healthy longevity. The first step to achieve this is the development of innovative chrononutrition assessment tools that are easily administered in research and public health settings. Ideally, the assessment of temporal eating patterns would span 7–14 consecutive days, but at minimum should capture two weekdays and one weekend day to estimate habitual eating timing and regularity metrics. In the meantime, a promising existing tool is the NIH's ASA-24, which enables the collection of multiple, automatically coded, self-administered electronic food records and 24 h recalls, as well as sleep data using the novel sleep module [84]. Another convenient tool is the novel "Chrononutrition Questionnaire for General and Shift Work Populations", a 10–15 min questionnaire for obtaining information on shift work schedules, eating timing, regularity, and frequency, wake and sleep times, and chronotype [85]. These tools enable the investigation of the interplay between eating timing and regularity, multidimensional sleep health, and chronotype, as well as the circadian timing of food intake (i.e., eating timing relative to biological time vs. societal clock time) in relation to CMH, which are all key knowledge gaps in this field. Alternatively, novel tools such as picture-based smartphone applications or wearable technologies that detect eating timing could be developed and validated. In addition, a scientific consensus framework for chrononutrition metrics, akin to the multidimensional sleep health framework [86], should be developed to adequately and holistically capture the impact of dietary rhythms on health. Such a framework could encompass eating duration, eating timing, and eating regularity metrics.

Notably, most observational and intervention studies focus on obesity risk and weight loss as outcomes [60]; examining other aspects of CMH as outcomes and elucidating underlying physiological mechanisms and biological pathways is another important research direction. In addition, evaluating temporal eating patterns in relation to diurnal patterns of cardiometabolic markers (e.g., incorporating ambulatory BP monitoring and continuous glucose monitoring) may elucidate novel targets for improving CMH using chrononutrition approaches. Importantly, siloed approaches to research on sleep, circadian rhythms, and diet should be avoided. Future observational studies should evaluate the interplay of chrononutrition metrics, sleep and circadian health, and chronotype in CMH. On the other hand, future intervention studies should consider tailoring eating schedules to chronotype and addressing chrononutrition metrics as part of comprehensive multidimensional dietary or circadian health interventions and alongside sleep interventions for optimizing health impact. Insights from behavioral, dissemination, and implementation sciences should be leveraged to design feasible interventions that work in real-world settings and promote adherence. This includes research to understand how wearables, smartphone apps, daily reminders or nudges, educational content, social support, and working with a health professional or peer health educator could enhance participation, engagement, and retention in such studies.

Given that behavioral and endogenous circadian rhythms vary across life stages and the robustness of circadian rhythms tends to dampen with aging [87,88], adopting a life course approach in future research is crucial to understanding how eating timing and regularity impact CMH preservation, cardiovascular resilience, and healthy longevity. Finally, little is known about the social determinants of health in relation to chrononutrition metrics and how temporal eating patterns contribute to CMH inequities [89]. Chrononutrition metrics are intertwined with sleep and circadian health, which are known to be significant contributors to racial and ethnic disparities in CMH [90,91,92], suggesting that chrononutrition approaches may represent a novel and timely opportunity to promote CMH equity. The research priorities necessary to advance this field and facilitate the translation of chrononutrition research to clinical practice and public health guidelines are summarized in Figure 3.

Upon addressing the aforementioned research gaps, the field of chrononutrition holds great promise for advancing health equity and improving CMH at the individual and population level. At the individual level, personalized chrononutrition interventions addressing the circadian timing of food intake, i.e., eating timing relative to an individual's biological clock, chronotype, and circadian rhythm, could improve CMH. In clinical and research settings, this approach would involve prescribing a fixed eating schedule customized based on dim light melatonin onset or relative to sleep timing, as a less expensive, more feasible proxy. Importantly, such interventions should be contextual, and multiple levels of influence should be addressed to maximize health benefits. For example, a chrononutrition intervention that also addresses food insecurity would be necessary to ensure consistent mealtimes. The integration of chrononutrition interventions with other lifestyle approaches, such as interventions aimed at improving diet quality or promoting sleep health, could also maximize the health benefit of such interventions.

At the population level, the integration of the concept of "timing" into public health guidelines would enhance the effectiveness of lifestyle approaches for improving health. Diet guidelines could encourage keeping a consistent eating start time and eating end time each day and recommend that the timing of the last meal occurs before a certain clock time or within a specific interval prior to bedtime. However, additional questions need to be addressed before such quantitative public health recommendations can be made. For example, by how many hours or minutes can eating timing vary day to day before we start observing adverse health effects? Is there a clock time after which eating has adverse health effects for the majority of the population? When should the last eating occasion occur relative to bedtime for optimal health? Similar to individual-level interventions, community-level and population-level chrononutrition interventions should be contextual, addressing social determinants of health and other domains of influence (Figure 1). Implementation science frameworks should be leveraged and advanced to develop culturally responsive, sustainable, and scalable chrononutrition interventions that promote health equity [93].

Observational and intervention studies suggest that earlier and more regular eating timing patterns may promote CMH, but many knowledge gaps remain to be addressed before these aspects of chrononutrition can be formally integrated into public health guidelines and approaches for chronic disease prevention (Table 1). Currently, it is known that an unhealthy diet is the leading cause of death in the US, particularly from cardiovascular and cardiometabolic disease, but these estimates are based on solely on what (not when) people eat [94]. Elucidating the impact of chrononutrition dimensions on health will be key for quantifying the true impact of multidimensional diet on the chronic disease burden and unlocking the full potential of dietary approaches for addressing persistent CMH inequities by designing and implementing flexible and feasible interventions in real-world settings.