How Sleep and Meal Timing Relate to Blood Sugar in People with Obesity During a Time-Restricted Eating Study

The circadian system, governed by the master clock in the hypothalamic suprachiasmatic nuclei (SCN), regulates daily rhythms including the sleep–wake cycle, feeding behavior, and central and peripheral energy metabolism [1]. The primary zeitgeber (time-giver) for this system is light, perceived by the retina and relayed to the SCN via the retinohypothalamic tract. Through hormonal and neuronal pathways, this central clock synchronizes peripheral clocks throughout the body to ensure coordinated physiological rhythms [1]. Beyond light, meal timing serves as a major zeitgeber for peripheral clocks, exerting significant influence on systemic energy metabolism.

Circadian misalignment, resulting from mistimed sleep, light exposure, or eating, drives adverse health outcomes including impaired glucose metabolism, systemic inflammation, obesity, and increased cardiovascular mortality [2,3,4]. Night-shift workers, who eat and sleep out of sync with natural circadian rhythms, face significantly higher risks of hypertension, diabetes, and cancer, as well as poorer glycemic control [5]. Even subtle circadian shifts, such as delayed sleep or meal timing, are linked to metabolic dysfunction. For instance, individuals with a late chronotype have an increased risk of diabetes and poorer glycemic control [6]. Population-based data further show that every one-hour delay in the start of daily eating is associated with a 0.6% increase in fasting glucose and a 3% increase in insulin resistance [7]. Similarly, higher late-day caloric intake and later timing of the final meal are linked to abdominal obesity, elevated fasting glucose, and weight-loss resistance [8,9]. Critically, clock time may differ from internal circadian timing. Research in young adults demonstrates that food intake relative to melatonin onset, a primary biological marker, is significantly associated with body fat and BMI, whereas clock time alone is not [10].

Time-restricted eating (TRE) is an increasingly popular dietary strategy that limits food intake to a 4–12 h daily window, typically 8–10 h, allowing ad libitum consumption during that period [11]. While initial TRE studies focused primarily on window duration, recent studies have begun comparing early TRE (window starting before 10 am, ending at or before 6 pm) versus late TRE (window starting at noon), reflecting growing recognition of circadian timing. [12]. A recent meta-analysis of 41 randomized studies found that early TRE significantly reduced body weight (mean difference: 1.15 kg) and fasting insulin concentrations compared to late TRE [13]. Although these studies categorized TRE by clock time, the practice inherently shifts meal timing relative to other circadian-regulated behaviors, such as sleep. Therefore, we examined the relationship between sleep–meal timing gaps and continuous glucose monitoring (CGM) outcomes to evaluate the association of TRE with glucose metabolism, leveraging CGM to capture high-resolution metrics including mean glucose and glucose distribution over 24 h and overnight periods [14]. This secondary analysis explored the relationship between meal to sleep intervals and glycemic parameters in a cohort with obesity participating in a randomized trial comparing TRE, caloric restriction (CR), and unrestricted eating (UE). We focused on two intervals: (1) awakening to first meal (Awake-AM meal), and (2) last meal to sleep onset (PM meal-Sleep). We hypothesized that greater temporal separation between meals and sleep, both in the morning (Awake-AM meal interval) and evening (PM meal-Sleep interval), would improve CGM-derived glycemic measures over 24 h and during the overnight period (1–5 AM).

Characteristics of participants (n = 44) are shown in Table 1. Mean (SD) age was 42.8 (11.5) years with a BMI of 36.6 (5.3) kg/m²; the majority were female. Meal start and end times at baseline and end-intervention, average wake time and bedtime, and baseline glycemic parameters are also shown in Table 1. On average, each participant contributed 9.3 (2.1) days of observations. At end-intervention, participants tended to reduce their eating interval by ending their eating period earlier: median eating time started 33 min later and ended 68 min earlier, with most changes occurring in the TRE group compared to CR and UE. Wake time and bedtime did not change significantly during the study.

Supplemental Table S1 shows changes in CGM variables between baseline and end-intervention, with a significant reduction in overnight average glucose (p = 0.043).

We found that each additional hour increase in the Awake-AM meal interval was associated with 0.19 (95% CI: 0.10 to 0.28) fewer hours for the PM meal-Sleep interval, suggesting that a later first meal compresses the time between the last meal and sleep onset. In Figure 1: each one-hour increase in the Awake-AM meal interval was associated with lower overnight (1–5 AM) average glucose and glycemic variability (SD), reduced %time > 180 mg/dL, and increased %time < 70 mg/dL.

Fully adjusted models (Table 2; covariates: baseline sleep duration, HbA1c, and randomization assignment) confirm these associations.

In Figure 2, each one-hour increase in the PM meal-Sleep interval was associated with lower overnight (1–5 AM) average glucose, and this association persisted after adjustment for the same covariates (Table 3).

In this secondary analysis of participants with obesity enrolled in a randomized trial of dietary interventions (TRE vs. CR vs. UE), each hour increase in the Awake-AM meal interval was associated with lower overnight (1 AM–5 AM) average glucose, lower glucose variability (SD), increased time below target, and decreased time above target. Each hour increase in the PM meal-Sleep interval was associated with lower overnight average glucose. Both associations persisted after adjustment for baseline sleep duration, HbA1c, and randomization assignment. These findings demonstrate that morning and evening meal timing, relative to wake time and bedtime, respectively, were differentially associated with 24 h and overnight CGM measures, with relevance to eating window selection for individuals practicing TRE.

In the primary paper, we found no differences in CGM-measured mean glucose or TIR between 3 months of TRE, CR (15% reduction), and UE among patients without diabetes [15]. These results contrast with a 6-month trial in patients with type 2 diabetes, where TRE reduced mean glucose compared to unrestricted eating [23]; however, that difference was primarily driven by rising glucose in the UE group, as the TRE group showed no significant improvement from baseline.

Increasing the Awake-AM meal interval was associated with reduced overnight glucose, glycemic variability (SD), and time above target (>180 mg/dL), while increasing time below target (<70 mg/dL); these findings warrant discussion. Although prolonged AM fasting was associated with a slight increase in time <70 mg/dL, this remained <1% in participants without diabetes, consistent with healthy ranges [24]. One potential explanation for these findings is that prolonged morning fasting disrupts circadian rhythm and blunts AM cortisol [25], an effect also observed in Ramadan [26,27]. Since meal timing influences peripheral clocks, prolonged morning fasting may speculatively influence overnight glycemia through circadian entrainment, thereby reducing hepatic glucose output. Despite these glucose-lowering findings, ample evidence supports the benefit of early eating, which generally corresponds to shorter Awake-AM meal intervals. Early TRE appears more effective than late TRE for improving fasting glucose, body weight, and blood pressure [13,28]. Chronic breakfast skipping is associated with increased risks of obesity, diabetes, and poor glycemic control [29,30], although the reduced caloric intake with TRE [15] may offset the adverse glycemic effects of a shorter PM meal-sleep interval, a known consequence of breakfast skipping [31]. Caution is warranted for individuals using insulin or insulin secretagogues during prolonged overnight fasts due to the potential risk of hypoglycemia, consistent with American Diabetes Association recommendations [32].

Our results (unadjusted and adjusted) suggest that a longer PM meal-Sleep interval reduces overnight average glucose. These findings contribute to the growing literature on the adverse effects of late eating on cardiometabolic parameters. For instance, National Health and Nutrition Examination Survey (NHANES) data linked late-day eating to a 12% higher risk of abdominal obesity and a 65% increased risk of elevated fasting glucose [8]. Furthermore, late eaters in weight-loss programs face greater biological barriers and lower motivation than early eaters [33], while night eating in patients with diabetes correlates with poor glycemic control [34]. Mechanistically, late eating impairs pre-meal carbohydrate utilization, increases postprandial and overnight glucose, blunts cortisol profiles [35], and reduces overnight fatty acid oxidation [36]. Consuming carbohydrates during peak endogenous melatonin levels further impairs glucose tolerance, particularly in carriers of the MTNR1B risk allele [31,37].

This study’s strengths include day-to-day analysis of objective sleep assessments, documentation of eating occasions, and CGM parameters assessed at end-intervention, which may capture greater variability in eating–sleeping intervals than baseline. Limitations include the exploratory nature of this analysis, small sample size, and use of pooled samples, although we adjusted for randomization assignment. We also lacked a gold-standard circadian timing measure, such as dim light melatonin onset, which could further characterize the relationship between meal timing and internal circadian markers. Our participants did not have diabetes, an important consideration when interpreting our findings, and may explain the modest effect sizes on glucose parameters, as glycemic variability is generally lower in this population than in individuals with diabetes. Finally, as an exploratory analysis, we did not adjust for multiple comparisons.

In conclusion, a longer Awake-AM meal interval was associated with lower overnight average glucose, less glycemic variability, and less hyperglycemia, but at the cost of increased hypoglycemia risk. A longer PM meal-Sleep interval was associated with lower overnight average glucose without increasing hypoglycemia risk. These findings suggest that delaying breakfast may be associated with improved CGM-assessed glycemic measures more than an earlier dinner, albeit with greater hypoglycemia risk, making a longer PM meal-Sleep interval preferable for individuals at risk for hypoglycemia. Taken together, meal timing relative to sleep is associated with alterations in CGM metrics, highlighting the potential to personalize TRE programs based on individual glycemic risk profiles.

We thank the study participants, University of Minnesota Clinical Research Unit staff, Chow’s study team (Abdisa Taddese, Brad P. Yentzer, Lesia Lysne, Alison Wong, Michelle Hanson, Julie D. Anderson, Alison Alvear, Nicole LaPage) and Dexcom (product support) for their contributions to this study.

The following abbreviations are used in this manuscript:

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/nu18111824/s1↗, Table S1: CGM measures at baseline and end-intervention; Figure S1: Consort for primary study published previously.

Conceptualization, D.G.M., N.O. and L.S.C.; Methodology, S.R. (Sirimon Reutrakul), S.L.S., S.P., E.H., D.G.M., N.O. and L.S.C.; Formal analysis, Q.W., E.N.C.M., Z.G., C.G. and E.H.; Investigation, L.S.C.; Resources, L.S.C.; Data curation, L.S.C.; Writing—original draft, S.R. (Sirimon Reutrakul), S.L.S., S.R. (Suryeon Ryu), E.H. and L.S.C.; Writing—review & editing, S.R. (Sirimon Reutrakul), S.L.S., Q.W., E.N.C.M., S.P., S.R. (Suryeon Ryu), Z.G., C.G., E.H., Doug Mashek, N.O. and L.S.C.; Supervision, S.R. (Sirimon Reutrakul), E.N.C.M., D.G.M., N.O. and L.S.C.; Project administration, E.N.C.M., N.O. and L.S.C.; Funding acquisition, L.S.C. All authors have read and agreed to the published version of the manuscript.

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of THE UNIVERSITY OF MINNESOTA (protocol code STUDY00008545) and SALK INSTITUTE (15-0003) on 24 February 2020.

Informed consent was obtained from all subjects involved in the study.

Protocol: posted as data supplement on website. Documented analytic dataset: Data available 1-year post-publication with IRB approval and MTAs, upon request to Dr. Chow’s team. This data will be provided de-identified. Statistical Code: Code available with dataset upon request to facilitate interpretation.

The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. SP has authored a book “The Circadian Code” for which he receives author royalty and specifically recommends time-restricted eating. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

This study was supported by the UMN CTSA Award (UM1TR004405-01A1) from the National Center for Advancing Translational Sciences, the National Institutes of Health, (R01DK124484 to L.S.C.), Robert Wood Johnson Foundation (Grant 76014 to SP for mCC app support) and Dexcom (Dexcom Pro sensors, product only). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Center for Advancing Translational Sciences, the National Institutes of Health or Dexcom. E.N.C.M was in part supported by the National Institute of Diabetes and Digestive Kidney Diseases of the National Institutes of Health under Award Number R01DK139356.