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Clinical Studies and Practice

Is the timing of caloric intake associated with variation in diet-induced thermogenesis and in the metabolic pattern? A randomized cross-over study



Food-induced thermogenesis is generally reported to be higher in the morning, although contrasting results exist because of differences in experimental settings related to the preceding fasting, exercise, sleeping and dieting. To definitively answer to this issue, we compared the calorimetric and metabolic responses to identical meals consumed at 0800 hours and at 2000 hours by healthy volunteers, after standardized diet, physical activity, duration of fast and resting.


Twenty subjects (age range 20–35 years, body mass index=19–26 kg m2) were enrolled to a randomized cross-over trial. They randomly received the same standard meal in the morning and, 7 days after, in the evening, or vice versa. A 30-min basal calorimetry was performed; a further 60-min calorimetry was done 120-min after the beginning of the meal. Blood samples were drawn every 30-min for 180-min. General linear models, adjusted for period and carry-over, were used to evaluate the ‘morning effect’, that is, the difference of morning delta (after-meal minus fasting values) minus evening delta (after-meal minus fasting values) of the variables.


Fasting resting metabolic rate (RMR) did not change from morning to evening; after-meal RMR values were significantly higher after the morning meal (1916; 95% confidence interval (CI)=1792, 2041 vs 1756; 1648, 1863 kcal; P<0.001). RMR was significantly increased after the morning meal (90.5; 95% CI=40.4, 140.6 kcal; P<0.001), whereas differences in areas-under-the-curve for glucose (−1800; −2564,−1036 mg dl−1 × h, P<0.001), log-insulin (−0.19; −0.30,−0.07 μU ml−1 × h; P=0.001) and fatty free acid concentrations (−16.1;−30.0,−2.09 mmol l−1 × h; P=0.024) were significantly lower. Delayed and larger increases in glucose and insulin concentrations were found after the evening meals.


The same meal consumed in the evening determined a lower RMR, and increased glycemic/insulinemic responses, suggesting circadian variations in the energy expenditure and metabolic pattern of healthy individuals. The timing of meals should probably be considered when nutritional recommendations are given.


An increasing number of studies have shown that the timing of food intake influences energy regulation, the risk of weight gain and obesity, independent from total daily caloric intake, dietary composition and estimated energy expenditure.1

Early insulin secretion after a meal ingestion is significantly higher in the morning than in the evening, leading to a more rapid glucose clearance from blood,2 whereas insulin sensitivity decreases later during the day.3, 4 Circadian variations in the concentrations of hormones and peptides regulating satiety and appetite as well as genetic patterns of the circadian clock genes have been implicated in the daily modification of specific metabolic pathways.1 In addition, gastric emptying seems to be more rapid at morning than in the evening,5 and an increased efficacy of dietary carbohydrates absorption has been demonstrated under late suppertime conditions.6

A few studies evaluated the circadian variation of the energy balance with contrasting results.7, 8, 9, 10, 11, 12 The thermic effect of food, also called diet-induced thermogenesis (DIT), is defined as the increase in resting metabolic rate (RMR) after the ingestion of a meal. This component accounts for a small proportion of the total energy expenditure (about 10%), but it has been reported to be implicated in the development and persistence of obesity.13 DIT is significantly higher after the consumption of a snack in the morning than after the same snack at night,7 and a reduced evening thermic response may be due to nocturnal insulin resistance.8 Furthermore, habitual nighttime eating or snacking have been associated with reduced fat oxidation, potentially promoting weight gain.14

However, data in the literature often show contrasting results9, 10, 11, 12 with differences in the exercise level, hours of sleeping, antecedent diets, variation in the duration of the fasting state, presence of comorbidity and low number of the subjects enrolled likely acting as confounding factors.15 Indeed, the ideal setting to study diurnal variation in energy expenditure is to measure post-absorptive RMR under the same conditions at different times of the day. The aim of our study was therefore to compare the calorimetric and metabolic responses to identical meals (a high-protein, low-carbohydrates meal) consumed in the morning (0800 hours) and in the evening (2000 hours) by healthy volunteers, after standardizing diet, physical activity level, duration of fast and resting.

Subjects and methods

Recruitment of participants

Twenty healthy volunteers (ten males and ten females) were enrolled among students and graduates attending the Department of Medical Sciences of Turin (Italy).

Inclusion criteria were as follows: age 20–35 years, body mass index 19–26 kg m2, habitual moderate exercise level, smoking <10 cigarettes per day. Exclusion criteria were as follows: any acute or chronic diseases, menopause, any drugs or supplementations, any alimentary restrictions or specific diets, being a shift or night workers, unable to give a written informed consent.


This was a randomized cross-over trial.


The primary outcome was evaluating changes in RMR after the morning meal consumption compared with changes in RMR after the evening meal. The secondary outcomes were analyzing changes in circulating concentrations of glucose, insulin, free fatty acids (FFAs) and triglycerides after the morning and evening meal consumption.


Participants were randomly allocated to receive a standard meal at 0800 hours and the week after the same standard meal at 2000 hours, or vice versa. Eight hours before the meal (respectively, at 1200 hours or at 0000 hours), participants received the same standard meal (without protein supplementation) at their home, and then were asked to spend the following 6 h in bed. Drinking coffee, alcohol or other beverages, and smoking were not permitted. The week preceding each test, participants were instructed not to change their usual diet and to refrain from heavy physical activity. A 24-h urine collection was collected the day before each test in order to determine total urinary nitrogen excretion.

The standard meal consisted of: 100 g white bread, 100 g ham, 50 g cheese, 125 g yogurt, 200 ml fruit juice, plus 25 g protein supplement (Resource Instant Protein, Nestlè, Losanna, Switzerland). The nutritional composition of the meal was: 30% protein, 31% fat, 39% carbohydrates; total kcal 1168. The participants had to consume each meal in 25–30 min. Participants were taken by car to the laboratory. At 0700 hours (or 1900 hours, according to the randomization), the participants underwent to anthropometric measurements and to the insertion of a 16-G indwelling catheter into an antecubital vein of the forearm, subsequently kept patent by the slow infusion of 500 ml of saline solution until the end of the testing session. To avoid blood drawing-related stress, all the blood samples have been withdrawn from an extension line tubing.

A 30-min basal calorimetric exam was performed (Figure 1). Participants remained in a supine position but awake and motionless on a hospital bed for the whole period, except during the meal, when they could sit to eat and were allowed to void. At 0800 hours (or 2000 hours), the participants consumed the meal, and then rested in a supine position for 90-min, followed by a second 60-min calorimetric evaluation. To obtain a better compliance to the experiment, the second calorimetric evaluation lasted 60 min (from 120 to 180 min from the beginning of the meal), as we have previously performed a pilot study in six volunteers to evaluate the tolerance to the calorimetric exam, and have found that maintaining immobility while awaking was difficult for more than 1 h consecutive.

Figure 1

The arrows (↓) indicate the time when the blood samples were drawn. During the visit, participants were submitted to anthropometric measures and a venous catheter was peripherally inserted. ‘Basal’ corresponded to the time before the first calorimetric examination was performed. The time 0 was after the first calorimetry and before the meal. The times 30, 60, 90, 120, 150 and 180 were referred to the time interval in minutes from the beginning of the meal. The same time schedule was adopted in the case of the morning meal (at 0800 hours) and the evening meal (at 2000 hours).

Blood samples were drawn every 30-min from the first calorimetric exam (baseline) until the end of the second (postprandial; Figure 1) exam. Time 0 was after the first calorimetry and before the meal. Times 30, 60, 90, 120, 150 and 180 were referred to the time intervals in minutes from the beginning of the meal. The same time schedule was adopted in the case of the morning meal (at 0800 hours) and the evening meal (at 2000 hours). The second test was carried out after 7 days from the first.

Sample size

A sample size of 20 subjects (10 in the ‘morning-first’ group and 10 in the ‘evening-first’ group) was required to test a 0.66 effect size with a power equal to 80% and a two-tailed α-value=0.05.


The random sequence (morning/evening, evening/morning meal) was computer generated, using blocks of different lengths in random order.


The Minnesota Leisure Time Physical Activity questionnaire,16 previously validated in an European cohort,17 was completed by all the participants together with a 3-day food record, which consisted of a detailed written food diary.18 Subjects were instructed to record everything they ate or drank during 2 consecutive week days and 1 week-end day. The 3-day food record data were loaded on the Win Food Pro 3 software (Medimatica, Colonnella, Teramo, Italy), and the mean nutritional values for the 3 days were reported.

Body weight and height were measured with subjects wearing light clothes using a mechanical column scale (SECA 711, Hamburg, Germany) to the nearest 0.1 kg and 0.1 cm, respectively. Waist circumference was measured by a plastic tape meter at the top of the iliac crest, after a normal expiration. Fat mass and fat-free mass (FFM) were determined by single frequency bioelectrical impedance using manufacturer equations (BIA 101, Akern, Florence, Italy). Indirect calorimetry by Deltatrac II (DATEX, Division of Instruments Corp. Helsinki, Finland) was used to measure the rate of energy expenditure, by measuring the inspired and expired concentrations of oxygen (VO2) and carbon dioxide (VCO2), which reflect nutrient metabolism. Deltatrac II has become one of the reference tools for reliable measurements, validated in vitro and in vivo, and its accuracy has been detailed in several studies.19 Before measurements, the instrument was warmed-up for 30-min. The canopy was placed over the subjects’ face and carefully checked to prevent air leakage. After 5-min of initial calibration, gas sample were continuously analyzed by a paramagnetic and infrared gas chamber for sensing O2 and CO2, respectively. During the calorimetric exam, participants were not allowed to talk. The exams were performed in a quiet room with a temperature kept at 23–25 °C. The energy expenditure was calculated within 3-h from the beginning of the meal, because it has been reported that the DIT response to meal can be assessed with sufficient precision within 3-h and prevent the movements occurring with more prolonged periods of immobility.15

Blood samples were immediately centrifuged and aliquots of plasma were stored separately at −80 °C until analysis. The following determinations were performed: glucose, insulin, FFA, triglycerides. Serum glucose was measured by enzymatic colorimetric assay (Menarini Diagnostics, Florence, Italy); serum insulin was determined by immunoradiometric assay (Beckman Coulter, Immunotech, Prague, Czech Republic; intra-assay coefficients of variation 3.99% and inter-assay coefficients of variation 4.8%). FFA concentrations were measured by a fluorometric assay (Sigma-Aldrich, St Louis, MO, USA). Plasma triglycerides were assayed by enzymatic colorimetric method (Hitachi, Roche Diagnostics, Mannheim, Germany). Total urinary nitrogen excretion was determined on the 24-h urine collection of the day before each test. Total nitrogen excretion was assessed by a kinetic assay (Hitachi, Roche Diagnostics).


The physical activity level was calculated as the product of the duration and frequency of each activity (in hours/week), weighted by an estimate of the metabolic equivalent of the activity and summed for the activities performed.

Both basal and after-meal RMR were calculated according to the formula of Weir.20 RMR was calculated also in relation to FFM determined by bio-impedance as: RMR/FFM and expressed as kcal/kg.

DIT was considered as the difference between average after-meal RMR and the basal RMR (after-meal RMR – basal RMR).

The Respiratory Quotient (RQ) was the ratio between VCO2 and VO2 (VCO2/VO2).

Glucose and fat oxidation were calculated according to the Ferranini formulas:21

VO2=oxygen consumption; VCO2=carbon dioxide production; N=urinary nitrogen excretion.

Rate of N, an index of protein oxidation, was assumed to be constant during the calorimetry.

Area-under-the-curve (AUC) values for glucose, insulin, FFA and triglycerides were calculated according to the trapezoidal model.22

We defined as Delta the difference between each variable at fasting and after the meal:

In the case of the calorimetric variables, the values at fasting corresponded to the results of the basal calorimetry; delta RMR therefore coincided with DIT. In the case of the laboratory variables, the values at fasting corresponded to the values at time 0.


Owing to the nature of the intervention, blinding participants and health professionals were not feasible. The laboratory personnel who performed the biochemical analyses was blinded to the group assignment.


The study was approved by the ethics committee of ‘Città della Salute e della Scienza’ of Turin; all the procedures conformed to the principles of the Helsinki Declaration. All participants provided written informed consent to take part in the study.

Statistical methods

Clinical and laboratory variables were presented as mean and standard deviation (s.d.). Triglyceride and insulin values were logarithmically transformed in order to approximate normal distribution. The Student’s t-test for paired data was applied to investigate within-subject changes of the variables at morning and at evening.

Within-subject changes in the variables after the morning and the evening meal consumption were further analyzed to estimate the ‘morning effect’, that is, the difference between the morning delta and the evening delta:

In the case of the AUCs, the ‘morning effect’ was the difference between morning AUC for the variable minus evening AUC for the variable.

General linear models (GLMs) with patients as random effects were performed to assess and adjust for the possible period and carry-over effects and to estimate crude and adjusted ‘morning effects’ and 95% confidence intervals (95% CIs). To make easier the interpretation of log-transformed variables, the adjusted estimates of triglycerides and insulin AUCs were expressed both as differences and as ratios.

In an explorative analysis, we analyzed the ‘morning effect’ on glucose, insulin, FFA and triglyceride values at all time points by GLM.

The repeated measures from 0 to 180 min of glucose, insulin, FFA and triglycerides were graphically reported as means and 95% CIs of variations from time 0.

Statistical analyses were performed using STATA 13.1 (StataCorp LP, College Station, TX, USA).


Mean age, weight, height, body mass index and waist circumference of the participants were 27.6±3.4 years, 67.3±12.5 kg, 1.70±0.01 m, 23.4±3.2 kg m−2 and 81.8±8.0 cm, respectively. Fat mass and FFM determined by bioelectrical impedance analyses were 14.5±6.0 kg and 53.5±11.3 kg.

Participants were moderately active: their median metabolic equivalent of the activity were 46.3 h per week, and usually consumed a high-lipid low-fiber diet (total kcal 1989.9±523.0; fat 39.9±15.7% total kcal; saturated fatty acids 11.1±2.6% total kcal; monounsaturated fatty acids 14.9±4.2% total kcal; carbohydrates 46.6±6.6% total kcal; fiber 11.9±3.5 g per day).

There were no meaningful differences between the two groups of randomization (morning-first versus evening-first) for anthropometric and fasting RMR values (Supplementary Table 1SI, Supplementary Information).

In Table 1, the morning and evening calorimetric variables at fasting and after meal in the 20 participants are reported. Fasting RMR was slightly lower at evening. After-meal RMR and DIT values were significantly higher after the morning meal. Fasting and after-meal RQs at morning were significantly higher than the corresponding RQs at evening. Both fasting and after-meal CHO oxidation values were significantly higher and fasting and after-meal fat oxidation significantly lower in the morning in comparison with the evening values.

Table 1 Calorimetric variables before and after morning and evening meals

Period and carry-over effects were tested by using GLM and resulted not statistically significant for all variables. The crude and un-adjusted effects of the ‘morning effects’ did not differ; therefore, only the adjusted effects were reported. The difference in delta RMR values, that is, the difference in DIT, indicated a higher DIT increase after the morning than after the evening meal (Table 2). On the other hand, the difference in delta RQ values, and the differences between morning and evening AUCs for glucose, insulin and FFA concentrations were negative, indicating a significantly higher effect of the evening meal on these variables than the morning meal.

Table 2 Estimates of 'morning effect' adjusted for period and carry-over effects by GLMs

Adjusted estimates of the ‘morning effects’ tested by GLM showed significantly lower values of glucose at time 60, 90, 120, 150 min; lower values of insulin at time 90, 120, 150 min; lower values of FFA at time 120, 150, 180 min, and lower values of triglycerides at time 60 min (Supplementary Table 2SI, Supplementary Information).

Basal values of glucose, insulin, FFA and triglycerides did not differ from morning to evening. In Figures 2,3,4,5 (panels a), the mean values according to the different time points of glucose, insulin, FFA and triglycerides were reported. In the panels b of the Figures 25, the mean and 95% CI variations from time 0 of the same variables were presented.

Figure 2

Mean glucose values at the different time points (a). Variation of glucose from time 0: morning mean changes from the value at time 0 (black dot), evening mean changes from the value at time 0 (gray dot). The whiskers indicate the 95% CIs (a and b).

Figure 3

Mean insulin values at the different time points (a). Variation of insulin from time 0: morning mean changes from the value at time 0 (black dot), evening mean changes from the value at time 0 (gray dot). The whiskers indicate the 95% CIs (a and b).

Figure 4

Mean FFA values at the different time points (a). Variation of FFA from time 0: morning mean changes from the value at time 0 (black dot), evening mean changes from the value at time 0 (gray dot). The whiskers indicate the 95% CIs (a and b).

Figure 5

Mean triglyceride values at the different time points (a). Variation of triglycerides from time 0: morning mean changes from the value at time 0 (black dot), evening mean changes from the value at time 0 (gray dot). The whiskers indicate the 95% CIs (a and b).


The results of the present paper indicate that the time of food intake per se affects both the thermogenic and the metabolic responses to meals. This could have practical implications since the time to eat should probably be considered when planning a healthy diet.

Energy expenditure and metabolic responses to meals

Our data showed that the meal-induced DIT increase after the morning meal was higher than that observed at dinner, whereas basal RMRs were only slightly lower at evening, consistent with data available in the literature.7, 15 Furthermore, glucose, insulin and FFA AUC values resulted significantly higher after the evening meal rather than at the morning.

A circadian pattern in the thermic and metabolic responses to nutrients could be therefore hypothesized.

DIT consists of two components: an obligatory component, linked to the energy expenditure by digestion, absorption and metabolism of nutrients, and an additional facultative component, likely mediated by the sympathetic nervous system.23, 24 A circadian rhythmicity of circulating norepinephrine and epinephrine has been found, with increased values in the morning.25 Epinephrine increases metabolic rate, RQ and glucose oxidation.26 Other explanations for the reduced evening postprandial thermic and metabolic answers may be the slower evening gastric emptying, with increased efficacy of dietary carbohydrates absorption,5, 6 and the reported decrement in insulin sensitivity as evening progresses.3 Possible contributors to the daily variations in insulin secretion, with higher morning beta-cell function and action, could be the circadian fluctuation in the concentrations of cortisol, Adrenocorticotropic hormone, glucagon-like peptide 1, glucose-dependent insulinotropic polypeptide, as well as in the meal-induced glucagon responses, showing a delayed peak after evening meals.2, 3, 27, 28, 29 Insulin resistance may determine a decreased thermic effect of glucose because of the diminished insulin-mediated glucose uptake and metabolism by skeletal muscle that results in diminished glucose-induced thermogenesis.8, 30 Furthermore, sympathetically mediated thermogenesis is decreased in the presence of hyperinsulinemia or insulin resistance.26, 30 Therefore, both the circadian variation in catecholamine concentrations and in insulin sensitivity might contribute to the evening reduction of DIT. Consistent with the reported reduced insulin sensitivity at the evening, we found lower glucose/insulin AUCs in the morning and delayed and larger increases in the concentrations of glucose and insulin in the evening (Figures 2 and 3, Supplementary Table 2SI, Supplementary Information).

A circadian control of FFA metabolism has been described, with highest levels around noon31 or in the afternoon,2 and an increased activity of lipoprotein lipase during the daytime.27 The circadian activity of clock target genes in adipocytes may impact on lipid breakdown and adipokine function, by regulating FFA mobilization from adipose tissue, thus acting on energy homeostasis and metabolic processes.32, 33 It is difficult to establish with our data if the higher increase in FFA AUC after the evening meal was the consequence of insulin resistance or rather the cause of the impaired insulin sensitivity, because of the known effects of FFA on the reduction in glucose uptake and phosphorylation in skeletal muscles and on the impairment in insulin signaling and action.34, 35

Not all the authors found a lower DIT after the evening meal.9, 10, 11, 12 Westrate failed to find a significant difference between morning and afternoon DIT in 10 normal weight young men, but the fasting period was shorter in the afternoon than in the morning and the metabolic conditions of the participants to this study were not the same.9 Nevertheless, in the morning, DIT was slightly higher, energy balance (the difference between energy intake and expenditure) lower, and early post-meal values of RQs and CHO oxidation significantly increased, in line with our results.9 Another study found a higher energy expenditure at night during enteral nutrition, but it involved older patients hospitalized in a Neurologic unit on artificial nutrition, therefore these results are difficult to be compared with those in our healthy individuals.11 Sato found no differences in 24-h energy expenditure in a room-size respiratory chamber between normal (1900 hours) or late (2230 hours) evening meals in 10 young Japanese, but the measure of DIT was not available, the times of the two experimental meals were not so different (~3 h) and, consistent with our results, postprandial glucose AUC values were significantly increased after the late meal.10 Similarly, delaying the time of an identical meal of about 3 h for a week did not change postprandial energy expenditure, but decreased CHO oxidation and glucose tolerance.12

In our study protocol, we used extreme conditions (meals at 12 h distance) and a high-protein content, which is known to exert a greater effect on energy expenditure.36, 37 It is possible that with a mixed meal we could have found lower values of DIT and lower differences between the morning and evening tests.

Nevertheless, the circadian variation in DIT might explain at least in part the previously found large intra-individual variability in DIT and CHO and fat oxidation, which could not be accounted by variation in the antecedent diets or in the method of measurement.7, 15 Intriguingly, the significant difference in morning–evening DIT in our sample persisted even when energy expenditure was calculated in relation to the FFM (Table 2).

Respiratory quotients

RQ values generally range within 0.70–1.00, with 100% lipid oxidation at 0.70, and 100% carbohydrate oxidation at 1.00.19 We found reduced CHO oxidation and RQ values and increased fat oxidation (Table 1) in the evening, suggesting a modification of the metabolic pathways toward a higher utilization of lipid substrates in the evening, supported by the faster reduction of FFA levels after the evening meal (Figure 3b), although starting from higher FFA values (Figure 3a).

After the experimental infusion of glucose/insulin23 as well as after a meal,38 both an increase in CHO oxidation and a decreased lipid oxidation have been reported, in line with our data. Other studies have found a higher RQ in the morning than in the evening.7, 9, 12, 15, 39 A significantly higher lipid oxidation and a lower CHO oxidation were described with meals at 1800 hours when compared with meals at 1000 hours in obese subjects both after a short-term (3 days) and a long-term (18 days) protocol, and the morning has been considered the time of the day in which anabolic functions take place,40 in line with the circadian rhythm of the glycogen synthesis.41 Even if delta RQs were slightly higher after the evening meal (Table 2), the increased evening fat oxidation and FFA AUCs in our sample suggested, in line with the higher insulin resistance at that clock time, a preferential use of lipid substrates in our sample.

Clinical perspectives

Human studies have shown that both in adolescents and in adults, consuming more of the daily energy intake at evening is associated with an increased risk of obesity, hyperglycemia, lipid abnormalities, metabolic syndrome, non-alcoholic fatty liver diseases and cardiovascular diseases.1, 4, 12, 14, 28, 42, 43, 44, 45 Circadian misalignment has adverse metabolic and cardiovascular consequences.4, 46 Examples of chronic conditions of this phenomenon are shift work and sleep deprivation, both conditions being associated with an increased risk of obesity, metabolic syndrome and cardiovascular diseases.27, 31, 33

The timing of meals also influences the success of weight-loss strategies: late-lunch eaters lose less weight than early eaters;47 overweight/obese women lose significantly more weight after a low-calorie dinner weight-loss program than after an isocaloric high-calorie dinner program.48 Therefore, dietary recommendations should probably include indications on the time-of-day for food consumption, besides advice on food quality and quantity.


First of all, caution is needed when trying to link results from short-term studies to long-term effects.

We did not evaluate the energy expenditure longer than 3 h after the beginning of the meal, according to some,7 but not other authors who recommended >5 h measurements.13 However, our experiment was consistent with studies showing that energy expenditure is lower after 3 h and that DIT response to meals can be assessed with sufficient accuracy for the comparison across subjects within this time interval.7, 15, 49 Furthermore, most of the differences in the metabolic patterns we found were present in the first 2-h after meal. We used the glucose equation to calculate CHO oxidation,21 even if after an overnight fast most of plasma glucose turnover is derived from liver glycogenolysis, but comparisons were performed within-individuals under the same conditions and, as Ferrarini stated,21 assuming exclusive glucose oxidation does not introduce a major error.


Consuming a high-protein, low-carbohydrates meal at evening seems energetically and metabolically unfavorable with respect to the consumption of the same meal at morning. Energy expenditure and metabolism may be tightly linked to circadian rhythms; gaining further insights into these processes may be useful to curb the current increasing rate of metabolic disorders.


  1. 1

    Garaulet M, Gómez-Abellán P . Timing of food intake and obesity: a novel association. Physiol Behav 2014; 134: 44–50.

    CAS  Article  Google Scholar 

  2. 2

    Lindgren O, Mari A, Deacon CF, Carr RD, Winzell MS, Vikman J et al. Differential islet and incretin hormone responses in morning versus afternoon after standardized meal in healthy men. J Clin Endocrinol Metab 2009; 94: 2887–2892.

    CAS  Article  Google Scholar 

  3. 3

    Van Cauter E, Desir D, Decoster C, Fery F, Balasse EG . Nocturnal decrease of glucose tolerance during constant glucose infusion. J Clin Endocrinol Metab 1989; 69: 604–611.

    CAS  Article  Google Scholar 

  4. 4

    Scheer FAJL, Hilton MF, Mantzoros CS, Shea SA . Adverse metabolic and cardiovascular consequences of circadian misalignment. Proc Natl Acad Sci USA 2009; 106: 4453–4458.

    CAS  Article  Google Scholar 

  5. 5

    Goo RH, Moore JG, Greenberg E, Alazraki HP . Circadian variation in gastric emptying of meals in humans. Gastroenterology 1987; 93: 515–518.

    CAS  Article  Google Scholar 

  6. 6

    Tsuchida Y, Hata S, Sone Y . Effects of a late supper on digestion and the absorption of dietary carbohydrates in the following morning. J Physiol Anthropol 2013; 32: 9.

    Article  Google Scholar 

  7. 7

    Romon M, Edme JL, Boulenguez C, Lescroart JL, Fritmat P . Circadian variation of diet-induced thermogenesis. Am J Clin Nutr 1993; 57: 476–480.

    CAS  Article  Google Scholar 

  8. 8

    Ravussin E, Acheson KJ, Vernet O, Danforth E, Jéquier E . Evidence that insulin resistance is responsible for the decreased thermic effect of glucose in human obesity. J Clin Invest 1985; 76: 1268–1273.

    CAS  Article  Google Scholar 

  9. 9

    Weststrate JA, Weys PJM, Poortvliet EJ, Deureunberg P, Hautvast GAJ . Diurnal variation in postabsorptive resting metabolic rate and diet-induced thermogenesis. Am J Clin Nutr 1989; 50: 908–914.

    CAS  Article  Google Scholar 

  10. 10

    Sato M, Nakamura K, Ogata H, Miyashita A, Nagasaka S, Omi N et al. Acute effect of late evening meal on diurnal variation of blood glucose and energy metabolism. Obes Res Clin Pract 2011; 5: e220–e228.

    Article  Google Scholar 

  11. 11

    Leuck M, Levandovski R, Harb A, Quiles C, Hidalgo MP . Circadian rhythm of energy expenditure and oxygen consumption. J Parenter Enteral Nutr 2014; 38: 263–268.

    Article  Google Scholar 

  12. 12

    Bandin C, Scheer FAJL, Luque AJ, Ávila-Gandía V, Zamora S, Madrid JA et al. Meal timing affects glucose tolerance, substrate oxidation and circadian-related variables: a randomized, crossover trial. Int J Obesity 2014; 39: 828–833.

    Article  Google Scholar 

  13. 13

    Reed GW, Hill JO . Measuring the thermic effect of food. Am J Clin Nutr 1996; 63: 164–169.

    CAS  Article  Google Scholar 

  14. 14

    Hibi M, Masumoto A, Naito Y, Kiuchi K, Yoshimoto Y, Matsumoto M et al. Nighttime snacking reduces whole body fat oxidation and increases LDL cholesterol in healthy young women. Am J Physiol Regul Integr Comp Physiol 2013; 304: R94–R101.

    CAS  Article  Google Scholar 

  15. 15

    Weststrate JA . Resting metabolic rate and diet-induced thermogenesis: a methodological reappraisal. Am J Clin Nutr 1993; 58: 592–601.

    CAS  Article  Google Scholar 

  16. 16

    Taylor HL, Jacobs DR Jr, Schucker B, Knudsen J, Leon AS, Debacker G . Questionnaire for the assessment of leisure time physical activities. J Chronic Dis 1978; 31: 741–755.

    CAS  Article  Google Scholar 

  17. 17

    Elosua R, Marrugat J, Molina L, Pons S, Pujol E . Validation of the Minnesota Leisure Time Physical Activity Questionnaire in Spanish men. The MARATHOM Investigators. Am J Epidemiol 1994; 139: 1197–1209.

    CAS  Article  Google Scholar 

  18. 18

    Bo S, Ciccone G, Durazzo M, Gambino R, Massarenti P, Baldi I et al. Efficacy of antioxidant treatment in reducing resistin serum levels: A randomized study. PLoS Clin Trials 2007; 2: e17.

    Article  Google Scholar 

  19. 19

    Moreira da Rocha EE, Alves VGF . da Fonseca RBV. Indirect calorimetry: methodology, instruments and clinical applications. Curr Opin Clin Nutr Metab Care 2006; 9: 247–256.

    Article  Google Scholar 

  20. 20

    Weir JB . New methods for calculating metabolic rate with special reference to protein. J Physiol 1949; 109: 1–49.

    Article  Google Scholar 

  21. 21

    Ferranini E . The theoretical basis of indirect calorimetry: a review. Metabolism 1988; 37: 287–301.

    Article  Google Scholar 

  22. 22

    Allison DB, Paultre F, Maggio C, Mezzitis N, Pi-Sunyer FX . The use of areas under curves in diabetic research. Diabetes Care 1995; 18: 245–250.

    CAS  Article  Google Scholar 

  23. 23

    Acheson KJ, Ravussin E, Wahren J, Jéquier E . Thermic effect of glucose in man. Obligatory and facultative thermogenesis. J Clin Invest 1984; 74: 1572–1580.

    CAS  Article  Google Scholar 

  24. 24

    Astrup A, Simonsen L, Bülow J, Madsen J, Christensen NJ . Epinephrine mediates facultative carbohydrate-induced thermogenesis in human skeletal muscle. Am J Physiol 1989; 275: E340–E345.

    Google Scholar 

  25. 25

    Linsell CR, Lightman SL, Mullen PE, Brown MJ, Causon RC . Circadian rhythms of epinephrine and norepinephrine in man. J Clin Endocrinol Metab 1985; 60: 1210–1215.

    CAS  Article  Google Scholar 

  26. 26

    Müller MJ, Acheson KJ, Piolino V, Jeanpretre N, Burger AG, Jequier E . Thermic effect of epinephrine: a role for endogenous insulin. Metabolism 1992; 41: 582–587.

    Article  Google Scholar 

  27. 27

    Al-Naimi S, Hampton SM, Richard P, Tzung C, Morgan LM . Postprandial metabolic profiles following meals and snacks eaten during simulated night and day shift work. Chronobiol Intern 2004; 21: 937–947.

    CAS  Article  Google Scholar 

  28. 28

    Van Cauter E, Shapiro ET, Tillil H, Polonsky KS . Circadian modulation of glucose and insulin responses to meals: relationship to cortisol rhythm. Am J Physiol 1992; 262: E467–E475.

    CAS  PubMed  Google Scholar 

  29. 29

    Goetz F, Bishop J, Halberg F, Sothern RB, Brunning R, Senske B et al. Timing of single daily meal influences relations among human circadian rhythms in rinary cycle AMP and hemic glucagon, insulin and iron. Experientia 1976; 32: 1081–1084.

    CAS  Article  Google Scholar 

  30. 30

    Astrup A, Andersen T, Henriksen O, Christensen NJ, Bülow J, Madsen J et al. Impaired glucose-induced thermogenesis in skeletal muscle in obesity. The role of the sympathoadrenal system. Int J Obes 1987; 11: 51–66.

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31

    Dallmann R, Viola AU, Tarokh L, Cajochen C, Brown SA . The human circadian metabolome. Proc Nat Acd Sci USA 2012; 7: 2625–2629.

    Article  Google Scholar 

  32. 32

    Shostak A, Husse J, Oster H . Circadian regulation of adipose tissue. Adypocite 2013; 2: 201–206.

    CAS  Google Scholar 

  33. 33

    Huang W, Ramsey KM, Marcheva B, Bass J . Circadian rhythms, sleep, and metabolism. J Clin Invest 2011; 121: 2133–2141.

    CAS  Article  Google Scholar 

  34. 34

    Randle PJ . Regulatory interactions between lipids and carbohydrates: the glucose fatty acid cycle after 35 years. Diabetes Metab Rev 1998; 14: 263–283.

    CAS  Article  Google Scholar 

  35. 35

    Roden M, Prince TB, Perseghin G, Petersen KF, Rothman DL, Cline GW . Mechanism of free fatty acid-induced insulin resistance in humans. J Clin Invest 1996; 97: 2859–2865.

    CAS  Article  Google Scholar 

  36. 36

    Westerterp KR, Wilson SA, Rolland V . Diet induced thermogenesis measured over 24 h in a respiration chamber: effect of diet composition. Int J Obes Relat Metab Disord 1999; 23: 287–292.

    CAS  Article  Google Scholar 

  37. 37

    Johnston CS, Day CS, Swan PD . Postprandial thermogenesis is increased 100% on a high-protein, low-fat diet versus a high-carbohydrate, low-fat diet in healthy, young women. J Am Coll Nutr 2002; 21: 55–61.

    CAS  Article  Google Scholar 

  38. 38

    Farshchi HR, Taylor MA, Macdonald IA . Decreased thermic effect of food after an irregular compared with a regular meal pattern in healthy lean women. Int J Obesity 2004; 28: 653–660.

    CAS  Article  Google Scholar 

  39. 39

    Chwalibog A, Thorbek G . Energy expenditure and oxidation of carbohydrate and fat in humans during day and night. Thermochimica Acta 2002; 394: 247–252.

    CAS  Article  Google Scholar 

  40. 40

    Sensi S, Capani F . Chronobiological aspects of weight loss in obesity: effects of different meal timing regimens. Chronobiol Int 1987; 4: 251–261.

    CAS  Article  Google Scholar 

  41. 41

    Sollberger A . The control of circadian glycogen rhythms. Ann New York Acad Sci 1964; 117: 519–554.

    CAS  Article  Google Scholar 

  42. 42

    Bo S, De Carli L, Venco E, Fanzola I, Maiandi M, De Michieli F et al. Impact of snacking pattern on overweight and obesity risk in a cohort of 11-13-y adolescents. J Pediat Gastroent Nutr 2014; 59: 465–471.

    Article  Google Scholar 

  43. 43

    Wang JB, Patterson RE, Ang A, Edmond JA, Shetty N, Arab L . Timing of energy intake during the day is associated with the risk of obesity in adults. J Hum Nutr Diet 2014; 27: 255–262.

    Article  Google Scholar 

  44. 44

    Bo S, Musso G, Beccuti G, Fadda M, Fedele D, Gambino R et al. Consuming more of daily caloric intake at dinner predisposes to obesity. A 6-year population-based prospective cohort study. PLoS ONE 2014; 9: e108467.

    Article  Google Scholar 

  45. 45

    Cahill LE, Chiuve SE, Mekary RA, Jensen MK, Flint AJ, Hu FB et al. Prospective study of breakfast eating and incident coronary heart disease in a cohort of male US health professionals. Circulation 2013; 128: 337–343.

    Article  Google Scholar 

  46. 46

    Gonnissen HKJ, Rutters F, Mazuy C, Martens EAP, Adam TC, Westerterp-Plantenga MS . Effect of a phase advance and phase delay of the 24- h cycle on energy metabolism, appetite, and related hormones. Am J Clin Nutr 2012; 96: 689–697.

    CAS  Article  Google Scholar 

  47. 47

    Garaulet M, Gómez-Abellán P, Alburquerque-Bèjar JJ, Lee YC, Ordovás JM, Scheer FA . Timing of food intake predicts weight loss effectiveness. Int J Obes 2013; 37: 604–611.

    CAS  Article  Google Scholar 

  48. 48

    Jakubowicz D, Barnea M, Wainstein J, Froy O . High caloric intake at breakfast vs dinner differentially influences weight loss of overweight and obese women. Obesity 2013; 21: 2504–2512.

    CAS  Article  Google Scholar 

  49. 49

    Segal KR, Edaño A, Thomas MB . Thermic effect of a meal over 3 and 6 hours in lean and obese men. Metabolism 1990; 39: 985–992.

    CAS  Article  Google Scholar 

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We thank Professor Gianfranco Pagano for his precious contribution in the critical reading of the manuscript. This study was supported by a grant from the Ministry of Education, University and Research of Italy (ex-60% 2014). identifier: NCT02343380.

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Bo, S., Fadda, M., Castiglione, A. et al. Is the timing of caloric intake associated with variation in diet-induced thermogenesis and in the metabolic pattern? A randomized cross-over study. Int J Obes 39, 1689–1695 (2015).

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