Time-restricted feeding protocol -
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Jones R, Pabla P, Mallinson J, et al. Two weeks of early time-restricted feeding eTRF improves skeletal muscle insulin and anabolic sensitivity in healthy men. Poggiogalle E, Jamshed H, Peterson CM.
Circadian regulation of glucose, lipid, and energy metabolism in humans. Marinac CR, Nelson SH, Breen CI, et al. Prolonged nightly fasting and breast cancer prognosis.
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Kesztyüs D, Vorwieger E, Schönsteiner D, Gulich M, Kesztyüs T. Applicability of time-restricted eating for the prevention of lifestyle-dependent diseases in a working population: results of a pilot study in a pre-post design.
Przulj D, Ladmore D, Smith KM, Phillips-Waller A, Hajek P. Time restricted eating as a weight loss intervention in adults with obesity. Domaszewski P, Konieczny M, Pakosz P, Bączkowicz D, Sadowska-Krępa E. Effect of a six-week intermittent fasting intervention program on the composition of the human body in women over 60 years of age.
Antoni R, Robertson TM, Robertson MD, Johnston JD. A pilot feasibility study exploring the effects of a moderate time-restricted feeding intervention on energy intake, adiposity and metabolic physiology in free-living human subjects.
Karras SN, Koufakis T, Adamidou L, et al. Similar late effects of a 7-week orthodox religious fasting and a time restricted eating pattern on anthropometric and metabolic profiles of overweight adults. Stratton MT, Tinsley GM, Alesi MG, et al. Four weeks of time-restricted feeding combined with resistance training does not differentially influence measures of body composition, muscle performance, resting energy expenditure, and blood biomarkers.
Kotarsky CJ, Johnson NR, Mahoney SJ, et al. Time-restricted eating and concurrent exercise training reduces fat mass and increases lean mass in overweight and obese adults.
Moro T, Tinsley G, Pacelli FQ, Marcolin G, Bianco A, Paoli A. Twelve months of time-restricted eating and resistance training improves inflammatory markers and cardiometabolic risk factors. Brady AJ, Langton HM, Mulligan M, Egan B.
Effects of 8 wk of time-restricted eating in male middle- and long-distance runners. Liu D, Huang Y, Huang C, et al. Calorie restriction with or without time-restricted eating in weight loss. Moro T, Tinsley G, Longo G, et al. Time-restricted eating effects on performance, immune function, and body composition in elite cyclists: a randomized controlled trial.
Tinsley GM, Forsse JS, Butler NK, et al. Time-restricted feeding in young men performing resistance training: a randomized controlled trial. PubMed Google Scholar Crossref. Tovar AP, Richardson CE, Keim NL, Van Loan MD, Davis BA, Casazza GA.
Jakubowicz D, Barnea M, Wainstein J, Froy O. High caloric intake at breakfast vs. dinner differentially influences weight loss of overweight and obese women. Madjd A, Taylor MA, Delavari A, Malekzadeh R, Macdonald IA, Farshchi HR. Effects of consuming later evening meal v.
earlier evening meal on weight loss during a weight loss diet: a randomised clinical trial. Dashti HS, Gómez-Abellán P, Qian J, et al.
Late eating is associated with cardiometabolic risk traits, obesogenic behaviors, and impaired weight loss. Keim NL, Van Loan MD, Horn WF, Barbieri TF, Mayclin PL. Weight loss is greater with consumption of large morning meals and fat-free mass is preserved with large evening meals in women on a controlled weight reduction regimen.
Lombardo M, Bellia A, Padua E, et al. Morning meal more efficient for fat loss in a 3-month lifestyle intervention. Allison KC, Hopkins CM, Ruggieri M, et al. Prolonged, controlled daytime versus delayed eating impacts weight and metabolism.
Kelly KP, McGuinness OP, Buchowski M, et al. Eating breakfast and avoiding late-evening snacking sustains lipid oxidation. Appel LJ, Moore TJ, Obarzanek E, et al; DASH Collaborative Research Group.
A clinical trial of the effects of dietary patterns on blood pressure. Cornelissen VA, Smart NA. Exercise training for blood pressure: a systematic review and meta-analysis. Stote KS, Baer DJ, Spears K, et al. A controlled trial of reduced meal frequency without caloric restriction in healthy, normal-weight, middle-aged adults.
Arnason TG, Bowen MW, Mansell KD. Effects of intermittent fasting on health markers in those with type 2 diabetes: a pilot study. Shea SA, Hilton MF, Hu K, Scheer FAJL. Existence of an endogenous circadian blood pressure rhythm in humans that peaks in the evening.
Scheer FA, Hilton MF, Mantzoros CS, Shea SA. Adverse metabolic and cardiovascular consequences of circadian misalignment. Jamshed H, Beyl RA, Della Manna DL, Yang ES, Ravussin E, Peterson CM. Early time-restricted feeding improves hour glucose levels and affects markers of the circadian clock, aging, and autophagy in humans.
Jakubowicz D, Wainstein J, Ahrén B, et al. High-energy breakfast with low-energy dinner decreases overall daily hyperglycaemia in type 2 diabetic patients: a randomised clinical trial. Effects of caloric intake timing on insulin resistance and hyperandrogenism in lean women with polycystic ovary syndrome.
Nakamura K, Tajiri E, Hatamoto Y, Ando T, Shimoda S, Yoshimura E. Eating dinner early improves h blood glucose levels and boosts lipid metabolism after breakfast the next day: a randomized cross-over trial. Parr EB, Devlin BL, Radford BE, Hawley JA.
Carlson O, Martin B, Stote KS, et al. Impact of reduced meal frequency without caloric restriction on glucose regulation in healthy, normal-weight middle-aged men and women. Time-Restricted Eating to Improve Health—A Promising Idea in Need of Stronger Clinical Trial Evidence. See More About Lifestyle Behaviors Diet Obesity.
Select Your Interests Select Your Interests Customize your JAMA Network experience by selecting one or more topics from the list below. Save Preferences. Privacy Policy Terms of Use. This Issue. Views 74, Citations View Metrics. X Facebook More LinkedIn. Cite This Citation Jamshed H , Steger FL , Bryan DR, et al.
Original Investigation. Humaira Jamshed, PhD 1,2 ; Felicia L. Steger, PhD 1,3 ; David R. Bryan, MA 1 ; et al Joshua S. Richman, MD, PhD 4 ; Amy H. Warriner, MD 5 ; Cody J. Hanick, MS 1 ; Corby K. Martin, PhD 6 ; Sarah-Jeanne Salvy, PhD 7 ; Courtney M. Peterson, PhD 1.
Author Affiliations Article Information 1 Department of Nutrition Sciences, University of Alabama at Birmingham. visual abstract icon Visual Abstract. Invited Commentary. Key Points Question Is early time-restricted eating more effective than eating over a period of 12 or more hours for losing weight and body fat?
Intervention Groups and Randomization. Weight Loss Treatment. Outcome Measures. Body Composition. Cardiometabolic Risk Factors. Food Intake, Physical Activity, Mood, Sleep, and Satisfaction.
Secondary aims included the acute effects of TRF on blood glucose and physiological parameters. This study protocol was approved by the ethics committee of Ruijin Hospital affiliated to Shanghai Jiaotong University Ref.
cn as ChiCTR A CONSORT flow diagram outlining the study protocol is displayed in Figure 1. Fourteen healthy participants were recruited from subjects who were interested in this study and submitted our lifestyle questionnaire online.
Finally, twelve participants completed this study. All participants provided written informed consent prior to participation in the trial. The total design of this study was exhibited in Supplementary Figure 1A. Each eligible subject underwent a cross-over dietary intervention, in which participants were treated with TRF eat within 5.
The order of two dietary schedules for each individual was randomized with a one-week washout period. Each dietary intervention was confined to the metabolic chamber for 3 days, during which calories of each meal and physical activities were rigorously controlled.
Participants underwent standardized acclimatization on the first day before the conduction of two diet interventions on the second day. Then all participants were asked to maintain the same lifestyle on the third day until all feces sourced from day 2 intervening food were completely excreted.
During the first day and third day, all the food provided was labeled with carmine dye. During the second day, all food was labeled with brilliant green dye to trace and collect the excretion of feces from this day.
Individual daily energy requirements were calculated based on body weight, height, and age, using the Harris-Benedict equation with a fixed physical active level PAL of 1. Each meal was consumed at a constant rate within 30 minutes during the intervention.
Daily activities during the intervention were strictly controlled according to the standardized schedule Supplementary Figure 1B. During the unconstrained hours, participants were only allowed to engage in mild activities including watching videos, using computers, walking in the chamber.
To meet the PAL of 1. Daytime was defined as to and nighttime was defined as to of the next day. All food and feces labeled with brilliant green dye used in the intervention were collected, mixed well, and lyophilized.
Lyophilization was performed at °C using an instrument SJIA-5FE, ShuangJia Instrument, Ningbo, China. Calories were measured by using bomb calorimetry according to the published protocol 29 Parr Calorimeter, PARR Instrument Co.
To minimize the error of measurements, all samples were measured repeatedly. We averaged two qualified measurements as the final calories of each sample. Food and fecal protein concentration were determined by the Kjeldahl method, fat concentration was determined by the Soxhlet method, and carbohydrates concentration was calculated by subtracting the protein, fat, water, and ash from the total weight of the sample.
To measure the substrate oxidation and energy expenditure, participants resided in the metabolic chamber for the whole experiment period.
The metabolic chamber is an airtight room with a volume of 30,L each Fuji Medical Science Co. The chamber is furnished with an adjustable bed, desk, chair, bicycle ergometer, wash basin, and toilet. Room temperature and relative humidity were maintained at Concentrations of oxygen O2 and carbon dioxide CO2 in the sample air were analyzed using an online process mass spectrometer Prima PRO, Thermo Fisher Scientific, Cheshire, UK after dehydration.
The mass spectrometry was calibrated monthly using standard gas and the accuracy for O2 and CO2 is 0. O2 consumption VO2 and CO2 production VCO2 were calculated by Henning method To minimize the error of the metabolic chamber, we calibrated the accuracy by alcohol combustion. The precision of metabolic chamber was And then we aggregated these minute-based data into hourly-based for statistical comparison.
Macronutrient oxidation and energy expenditure were calculated using the Weir equation with urinary nitrogen excretion To correct the measured RQ for protein oxidation, nonprotein RQ npRQ was calculated by using nitrogen excretion in h urine.
Twenty-four-hour thermic effect of food TEF was determined by plotting energy expenditure against physical activity level, and the intercept of the regression line at the lowest physical activity represents SMR and TEF. All women performed respiratory chamber testing during the follicular or luteal phases of their menstrual cycle.
All participants were fitted with a CGM sensor and transmitter Dexcom G5, Dexcom, San Diego, CA, USA during the study period. The glucose-oxidase-based electrochemical sensor was inserted into subcutaneous tissue of the abdomen, followed by an initial warm-up period for 2 hours after sensor insertion.
Sensor insertion began the day before the first acclimatization day and there was two days of calibration before data collection during the dietary intervention. According to company recommendations, the sensors were calibrated at least once every 12 hours by finger prick FreeStyle Lite; Abbott Laboratories, Abbott Park, IL.
After a washout period, participants were asked to insert a new sensor the day before the study. Prior to the trial, each participant performed a maximal oxygen uptake VO 2max test on a cycle ergometer E, Monark Ltd, Vansbro, Sweden. Oxygen consumption and carbon dioxide production were measured by a breath-by-breath portable gas analyzer K5, COSMED, Rome, Italy.
Then, the workload was increased by 25W or 20W every minute for men or women, respectively, while participants maintained a pedaling rate of 60 rpm until exhaustion despite verbal encouragement. Noninvasive blood pressure, 3-lead ECG, and peripheral pulse oximetry SpO2 were continuously monitored by a Cardiac Telemetry System WEPC, Nihon Kohden Co.
Systolic and diastolic blood pressure were measured every 10 minutes during the study. Heart rate, breath rate, and SpO2 were measured every second during the study. Equivital LifeMonitor system EQ02 LifeMonitor, Hidalgo Ltd, Cambridge, UK , capable of logging physiological data including respiratory inductance plethysmography, posture, activity, and skin temperature every 15 seconds was used during study.
Participants were fitted with a correctly sized chest vest dependent on their chest circumference. Axillary skin temperature was measured by an infrared sensor. Ambulation status was measured by accelerometer sensor and divided into different levels: stationary, moving slowly, and moving fast.
Bioelectrical impedance analysis Inbody , Inbody Co. Height was measured in centimeters using a height measurement instrument RGZ, DongFang Scales Co. Blood sampling was performed at 0h before and 0.
Samples were collected by using a standard venipuncture. Plasma and serum were centrifugated at 4°C and stored at °C until analysis. Insulin was measured by an autoanalyzer ARCHITECT ci analyzer, Abbott Laboratories, USA.
Participants rated their hunger, fullness, stomach fullness, desire to eat, capacity to eat, and sleepiness using Visual Analog Scales VAS; a mm scale. The higher the scale, the stronger the sensation.
VAS surveys were administered for total fourteen times at pre-meal 0h , 0. Based on our preliminary data and a previous report 29 , we assumed that the hour calories excretion is 6.
Participants were randomly allocated in ratio to 5. After the washout period, crossover was carried out for both groups. The generation of allocation sequence was based on the random-number table.
Statistical analyses were performed using R Studio version 3. Since the sample size of this study is comparatively small, we exert pairwise t-test with Holm—Bonferroni adjustment to reduce the sampling error.
The Shapiro-Wilk test was used to check the data distribution. For parameters with non-Gaussian distribution, the Mann-Whitney test was used. For parameters with normal Gaussian distribution, a two-tailed pairwise t-test was applied.
When applicable, non-parametric Wilcoxon matched-pairs signed ranks test was used. To analysis the time course data, two-way repeated measures ANOVA models were used to evaluated the interaction between time and groups on dependent variable.
Baseline data are reported as mean ± standard deviation SD , and other data are presented as mean ± standard error of the mean SEM. AUCs were calculated by the trapezoidal rule. To evaluate the contribution of insulin and carbohydrate oxidation in explaining TRF-induced change of postprandial glycemic response, a linear mixed-effects model with incremental glucose AUC as the dependent variable, diet intervention control as the reference and pre-prandial glucose as independent variable, participants and meals as random effect was constructed, and pre-prandial insulin and postprandial carbohydrate oxidation were added as independent variable to observed the changes of each effect.
Fourteen participants were included and twelve 5 men and 7 women of them completed this study Figure 1. Each participant underwent a crossover trial, in which participants were treated with TRF eating period: AM to AM and control eating period: AM to AM dietary schedules.
The order of two dietary schedules for each individual was randomized and the two interventions were separated by a one-week washout period. During the washout period, participants kept their usual lifestyle and the mean body weight upon entering the chamber were same The baseline characteristics of participants were measured from to in the morning of the intervening day Table 1 , during which participants maintained supine position without other activities.
Neither biochemical nor physiological profiles were significantly different between groups. Table 1 Basal characteristics of participants and pre-intervention parameters.
We confirmed the food energy density and macronutrients components by bomb calorimetry and chemical method, respectively.
As shown in Table 2 , no significant differences in total energy, carbohydrate, fat, and protein intake were observed. Meanwhile, the intake time of three meals also showed no statistical difference. Fluid intake volumes were same among two groups. In Figure 2A there is an overview of hourly energy expenditure for two groups.
These differences were mainly attributed to postprandial TEF. Figure 2 Hourly energy expenditure A , thermic effect of food B , mean energy expenditure C , and total energy expenditure D between control and TRF groups.
As shown in previous results, the energy intake and expenditure showed no difference between groups and then we examined a third part, as an often-neglected factor, fecal energy loss. The absolute number of calories lost in TRF group was significantly increased by However, calories in urine showed In aggregate, Figure 3J shows the energy balance status of both groups.
Compared with control group, TRF intervention induced a lower energy balance level Figure 3 Fecal wet weight A , fecal water content B , fecal energy loss C , fecal carbohydrate loss D , fecal fat loss E , fecal protein loss F , intestinal transit time G , urine volume H , urine energy loss I , and energy balance J between control and TRF groups.
After correction for macronutrients intake and lost in feces, carbohydrate balance was significantly decreased in TRF group, as residual carbohydrate was Figure 4 Hourly npRQ A , mean npRQ B , delta day-night npRQ C , total substrate oxidation D , and substrate balance E between control and TRF groups.
Postprandial glycemic and insulinogenic responses to the two time-shifted meals the 2nd and 3rd meals were both significantly attenuated in TRF group as compared to control.
The incremental area under curves of postprandial glucose and insulin were paralleling decreased Figures 5F, G and Supplementary Table 4. Pre- and post-prandial free fatty acid FFA were measured simultaneously with insulin and intravenous blood glucose.
While no statistical differences of FFA between groups were observed around the 1st meal, both pre- and post-prandial FFA were substantially reduced during TRF Figure 5H and Supplementary Table 6.
However, there were no significant interaction between time and group on either blood pressure or skin temperature Supplementary Table 7. Neither hourly nor 24h-average data in blood pressure and skin temperature alternation were observed Figures 6C — F, I, J.
Figure 5 The effect of TRF on hour CGM data A. Comparison of hour mean glucose B , CV C , MAGE D , LAGE E , postprandial glycemic F , postprandial insulin G , and postprandial FFA H between control and TRF groups.
Figure 6 Heart rate A, B , systolic blood pressure C, D , diastolic blood pressure E, F , respiration rate G, H , and skin temperature I, J between TRF and control group. As shown in Figure 7 , we also evaluated the subjective appetite and sleepiness level by VAS.
Significant interactions between time and groups on hunger, fullness was observed in stomach fullness, desire to eat, and capacity to eat were showed in the two-way repeated ANOVA model Supplementary Table 8.
However, there were not any significant differences in subjective appetite between groups the next day morning. Figure 7 Subjective hunger A , fullness B , stomach fullness C , desire to eat D , capacity to eat E , and sleepiness F responses to VAS from participants during TRF and control intervention.
Although current available data did not support a stronger effect of TRF on body weight and metabolic improvement as compared to continuous caloric restriction, the mechanistic explanation behind this phenomenon remains raised great interest to researchers.
Some controversial issues, including inaccurate recording of food intake, unmonitored energy expenditure and the involvement of physiological adaptation were still need to be determined 8 — 11 , 13 , 14 , 21 — 24 , 26 , 32 , Therefore, we conducted the first rigorous trial to systematically quantify and compare the energy balance during TRF intervention in healthy subjects.
We strictly controlled and ensured that energy intake, fluid intake, and lifestyle were consistent during the interventions except for eating schedules, while energy expenditure was monitored using metabolic chamber and all energy excretion including feces and urine were measured by bomb calorimeter.
Surprisingly, TRF could evoke a significant fecal energy loss and a trend in urine energy loss without energy expenditure alteration, which caused a negative energy balance, while hour blood glucose and heart rate were also improved during TRF.
Our findings are consistent with the benefits of long-term TRF intervention reported previously, supporting the use of TRF as an alternative dietary strategy for obesity.
In this study, we found no significant differences in total energy expenditure during the whole intervention period. Despite that some studies suggested that TRF induced adiponectin elevation might contribute to increased energy expenditure 10 , 25 , 34 , the results of the current study are consistent with previous studies: through hour energy monitoring or resting metabolic rate measurements, there is no convincing evidence in support of increased energy expenditure due to TRF 20 , 26 , But several components of total energy expenditure are inconsistent with a prior study, including higher TEF, increased diurnal energy expenditure, and decreased nocturnal energy expenditure in TRF group These negligible differences might be explained by different food macronutrient compositions and time schedules among two studies, respectively.
The precise measurement of the third and often neglected factor, energy excretion finally helped reveal that TRF has resulted in a negative energy balance of Kcal, which is equivalent to In fact, adherence to daily energy restriction decreases after 1 month and continues to decline thereafter [ 8 ].
Although TRF is a well-known strategy to lose weight [ 9 , 10 ], improvement in insulin sensitivity, blood pressure, and oxidative stress are seen even without weight loss in human studies [ 11 ]. Several randomized controlled trials RCTs have reported that weight loss reduces mortality in obese individuals [ 6 ].
Therefore, there is an inconsistency of whether or not weight loss is associated with changes in classical blood biomarkers such as glycemia and lipid profile. Since obesity has multifactorial factors, it is feasible to consider that blood biomarkers should be linked with body composition evaluation to follow the process of weight loss.
Despite growing bodies of studies, TRF is still a matter of debate among clinicians due to different approaches and the uncertainties of its impact on whole-body function, i. Herein, weight loss was associated with blood markers of metabolic syndrome and cardiovascular risk.
It is known that the extended morning fasting period observed in TRF does not cause compensatory intake during an ad libitum lunch nor does it increase appetite during the afternoon [ 12 ].
Therefore TRF could be an alternative to those individuals who struggle with restrictive diets which changes substantially their daily habits. Physically inactive women were excluded less than min of moderate or less than 75 min of intense physical activity per week.
Women with non-communicable diseases other than T2DM and hypertension were excluded and individuals who were using medications other than birth control pill were also excluded. A non-randomized controlled clinical trial on TRF was performed over 3 months in obese women. Volunteers were recruited by social networks of people inserted in the community and instant messaging applications.
Outcomes were assessed at baseline and after 3 months. The control group was recruited by social media as well but participants were informed that they would be engaged in diet habit research. Participants in the TRF group were asked to continue their regular nutritional habits during the non-fasting hours while the control group was instructed to maintain their habitual nutrition throughout the whole period.
The protocol was approved by the Committee of Ethical Research from the Federal University of Fronteira Sul protocol number 2. Trial registration: ensaiosclinicos.
br Registered 16 June —retrospectively registered. TRF is based on the manipulation of timing fasting that aims the energy intake abstention [ 9 ]. The TRF protocol adopted here was a fasting period no energy intake whatsoever of 16 h 8 pm to 12 pm and ad libitum feeding for 8 h 12 pm to 8 pm.
The protocol was performed 7 days per week for 3 months. All participants received daily a reminder through instant messaging that informed the time to stop eating and the time in which food was allowed. In addition, periodic meetings were promoted one every 15 days for participants to share their experience and receive support from physicians.
The control group was instructed to maintain the same dietary and living habits. The primary outcome was the effect of intermittent fasting on body weight and composition after 3 months compared to baseline values. Secondary outcomes were the characterization of metabolic risk factors and their association with weight loss.
We also measured the cardiovascular risk of the participants at baseline and post 3 months. Weight was collected using the digital weight balance Urano, PS Height was measured by the wall stadiometer and waist circumference upper edge of the iliac crest with fine metric Sanny, fiberglass tape.
Body mass index BMI values were calculated from these measurements. For body composition analysis, we used anthropometric prediction equations, which were validated by the National Health and Nutrition Examination Survey NHANES.
We used the equation of Lee et al. All anthropometric measurements were performed thrice by one subject. Estradiol, insulin, free thyroxine T 4 , and Thyroid-stimulating hormone TSH were analyzed by UniCel DxI Access Immunoassay System Beckman Coulter following the instructions and protocols provided by the manufacturer.
To evaluate whether or not women presented MetS, we followed the criteria from Alberti et al. Participants were classified in 0—5 score according to the MetS criteria. We have used the Framingham Heart Study, which provided an estimation of the year CVD risk CVDRisk30y for each individual [ 18 ].
Framingham risk scores FRS for CVD covers the full spectrum of CVD, including coronary heart disease, peripheral vascular disease, stroke, and heart failure [ 19 ]. The Quality of Life QOL assessed by WHOQOL-bref questionnaire has been translated and validated in Brazil [ 20 ].
The abbreviated WHOQOL-bref provides scores for four domains related to QOL: physical health, psychological, social relationships, and environment. Also, a self-perception of quality of life is measured by this questionnaire [ 21 ]. The WHOQOL-bref consists of 26 items rated on a 5-point Likert scale.
The scores are transformed and vary from 0 to , with higher scores representing better QOL [ 22 ]. The Mini-Mental State Examination MMSE evaluates the cognition health and it has been translated and validated in Brazil [ 23 ].
The test provides a score of 0— Given the low levels of education among older adults in Brazil, specific cut-off points are used based on the schooling level of the older adults: 13 for illiterate people, 18 for those with 1—11 years of schooling, and 26 for those with more than 11 years of schooling [ 23 ].
This questionnaire was used as a tool to characterize the participants and assess whether or not they would fully understand the protocol in order to follow it. This study was conducted as an exploratory pilot study with the recruitment of women who were engaged in performing the protocol.
Therefore, a sample size calculation did not seem possible. In order to reduce the influence of within-group variability, a univariate test of significance ANCOVA was performed. For multiple comparisons sensitivity analyses Bonferroni correction of p-values was used.
TRF group vs. Control group were assumed as categorical predictors. A paired Student t-test was performed between baseline and 3 months for each group. Statistical analyses were made with the statistical software package Statistical Package for the Social Science SPSS , version Fifty-eight interested subjects contacted our staff willing to engage in the intermittent fasting protocol, twenty-eight subjects after screening met the eligibility criteria, and one subject had to be excluded due to a coagulation disorder Fig.
All women who were enrolled in this study attended the following criteria: sedentarily, non-communicable diseases, and physically inactive.
Figure 1 shows the flowchart of the study with the dates that each event occurred. No significant between-group differences were observed at baseline in any measurement performed.
Baseline values for participants of both groups reflect middle-aged women with obesity with no cognition impairment. Table 2 summarizes the body weight and composition outcomes. Despite changes in body weight and body composition, there were no significant changes in blood biomarkers associated with metabolic and cardiovascular risk.
Figure 2 a shows the criteria and the number of participants with the respective risk of MetS at baseline and post-intervention. According to Alberti et al. Figure 2 b shows the number of women who presented 1, 2, 3, 4, or 5 risk factors at baseline pre and post-intervention. a Metabolic Syndrome risk factors and the number of individuals that have each factor in TRF and control groups in pre and post-intervention.
b The number of participants who have 1, 2, 3, 4, or 5 risk factors. We have conducted an analysis of CVDRisk30y based on The Framingham Heart Study. To evaluate anthropometric changes with cardiovascular risk other than the ones predict in the Framingham Heart Study, we correlated all anthropometric indexes to CVDRisk30y Additional file 1 : Table S1.
The total score for WHOQOL-bref questionnaire and the scores by subdomain are represented in Fig. Participants after TRF protocol obtained a higher score when compared to baseline values, and this fact was due to a self-perception of a better quality of life, as seen in Fig.
Total a and subdomains b scores of the WHOQoL. pre refers before intervention and post after intermittent fasting protocol. IF pre. In this study, the short-term effects of TRF on metabolic, hormonal, and anthropometric parameters were evaluated.
TRF has shown to be an effective protocol to promote weight loss, anthropometric, and body composition changes, but did not show significant changes in blood biomarkers associated with metabolic and cardiovascular risk.
Our findings differ from previous results in which TRF promotes changes in blood exams and metabolic parameters glycemia, HDL, LDL, cholesterol, among others [ 11 , 24 ].
The TREAT Randomized Clinical Trial reported similar findings with no changes in fasting insulin and glycemia in a h time-restricted eating protocol in overweighted adults [ 25 ].
It is widely accepted that obesity is associated with all-cause mortality and the development of cardiovascular events in mid-age adults [ 26 , 27 ].
Also, overweight per se, without the presence of MetS, is an independent factor related to increased mortality and cardiovascular events [ 28 , 29 , 30 ]. This aspect is extremely relevant once any significant change in blood exams glucose, triglycerides, HDL-c, etc.
may not appear before three months, confirming that obesity first-line treatment should aim weight-loss strategies. Evidence in humans suggests that the benefits of TRF are due mostly or only to weight loss [ 8 , 31 , 32 , 33 ].
The variation among participants with distinct risk factors may be taken into account for different responses to the TRF protocol.
Further studies are necessary to evaluate whether or not these factors impact on individual responses to TRF. Except for weight and height, WC was the only direct anthropometric measurement performed in this study and it was reduced with TRF. It is well-known that WC is an indicator of visceral adiposity and a predictor of morbidity and mortality [ 34 ].
RCTs reveal that reduction in WC promoted by lifestyle change is associated with a significant decrease in cardiometabolic risk independently from gender or age [ 35 , 36 ]. Our study has shown that TRF is a benefic dietary intervention that leads to an increase in self-reported quality of life, which can be explained by weight loss [ 37 , 38 ].
Besides, obese women often report dissatisfaction concerning their bodies when compared to subjects with normal weight [ 39 ]. Since TRF promoted a reduction in weight and waist circumference, the improvement in the quality of life seen in these women may be indeed attributed to a self-perception of a better body image [ 40 ].
Obesity is characterized by the accumulation of adipose tissue and an increase in body mass, which develops under a chronic positive energy balance. Therefore the reduction of this excess of adipose mass is the main goal of the clinical approach to treat obesity [ 41 , 42 , 43 ].
Most of the subjects in our study are obese but did classic biomarkers are not altered, corroborating data from populational studies [ 44 ]. Nonetheless, these individuals are targets of the deleterious effects of excess adipose tissue that will trigger MetS at any time.
This study points out the importance of a more comprehensive evaluation of overweight or obese subjects, which includes anthropometric measurements.
This study was not a randomized controlled trial and does not include detailed nutritional aspects of the subject´s diet since we found conflicting data reported by individuals, such as an incomplete description of the amount of food ingested, the frequency of meals, and the type of foods e.
In addition, the dietary intake self-report can differ or underestimate the real value, offering an inconclusive and misleading analysis [ 45 , 46 ]. Energy restriction is the main factor that leads to weight loss independently of the type of diet [ 9 ].
Therefore, it is feasible to assume that a reduction in total energy consumed was achieved, considering that energy expenditure has maintained constant. A recent meta-analysis has shown a dose—response between weight loss and reduction in energy intake [ 47 ].
Therefore, one can assume that weight loss was higher in those women who had more energy balance deficit. Another concern is the protocol adherence, which can interfere in the outcomes. Since we are not able to control whether or not the subjects followed the TRF strictly for three months without any gap, explaining differences in weight loss among subjects is a hard task.
TRF is an effective dietary strategy to promote weight loss and to decrease WC with no remarkable changes in blood biomarkers. This can be explained by the considerable number of obese women without MetS, in which they have an excess of weight and WC, but not always altered blood biomarkers.
We may provide all raw data to the Journal upon request. Relevant data may be provided to readers upon request.
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A, Shown are the times of Tume-restricted mean [SD] that participants started eating left Time-restricted feeding protocol of box and left whisker Prottocol stopped eating right end of box and right whisker in each group. The vertical line within the boxes indicates the median time of the eating window averaged across all participants. eTable 1. Baseline Characteristics of Completers Versus Non-Completers. eTable 3. Time-restricted eating TRE involves rpotocol regular, Time-restrictwd cycle proyocol eating and fasting, with meals, Time-restricted feeding protocol, and Time-restricted feeding protocol drinks Time-restricted feeding protocol limited to the same Plant-based protein sources hour window each day. Tume-restricted is a form of intermittent fasting IF in which people can eat what they like during a set period but must fast for the rest of the time. A new study in mice shows that time-restricted feeding TRF influences the activity of genes in 22 diverse tissues all over the body, including the brain, heart, lungs, liver, and gut. The researchers report their results in Cell Metabolism. A review of research notes that pilot studies in humans suggest that the health benefits of TRE include improvements in obesity, diabetes, and cardiovascular disease.
Time-restricted feeding protocol -
Capturing the timing of all ingestion events except for water and medication in a free-living population is rare and has been documented only recently. Even within most TRE clinical trials, the timing of eating and the eating window are not assessed Table 1. Food recall and written food journals are typically for only 1 to 7 days and are frequently inaccurate , Assessing solely the first and last calorie intake can be informative in describing the eating window but fails to fully capture eating pattern.
This continuous collection of data allows for a full description of the eating pattern and the simplicity of logging taking a time-stamped picture and making a quick annotation provides a large amount of information while easing participant burden.
German Register for Clinical Trials DRKS. NIH Clinicaltrials. gov Number NCT. If height was not reported, weight was provided. CI is provided if that was reported in place of SD.
b Mean SEM reported in place of mean SD. Eating duration is reported as daily average unless otherwise noted. TRF models in rodents and flies have used 8- to hour eating windows and found similar benefits, with greater results at 8- to 9-hour eating windows 65 , 68 , 85 , Animal models of TRF have not used eating intervals shorter than 8 hours to ensure that both TRE and ad lib groups can consume the same amount of calories.
When food is restricted to less than 8 hours, there is a calorie deficit that can confound results. In humans, clinical trials on TRE typically choose 8-to hour intervals, with some studies using an eating interval as short as 4 or 6 hours and others as long as 12 hours see Table 1.
Interestingly, a hour eating window has also been used as a control arm in TRE intervention 75 , A recently completed hour TRE intervention failed to find significant improvement in factors for metabolic syndrome However, it is unclear if patients who habitually eat over 16 hours or longer will benefit from a hour TRE.
There is not yet a consensus on the duration of a daily eating window that is needed to achieve the benefits of TRE. In rodents, cardiometabolic benefits were still observed for 9- and hour eating windows. However, additional improvements in endurance were observed with a 9-hour eating window, but not hour In clinical trials, a hour eating window has been used as an active control compared to a 6-hour and hour eating window 75 , In both cases, there were significant metabolic benefits in comparison to the hour eating window.
Multiple trials with hour eating windows have shown comparable health benefits to short eating windows of 6 to 8 hours. Moreover, eating windows of 6 hours or less have reported mild adverse side effects such as headaches. A study comparing 4-hour TRE to 6-hour TRE found no significant differences between the groups Thus, an eating window of 8 to 10 hours is an eating window that has shown promising results and is long enough to work with most schedules to allow for proper compliance.
More studies are needed to determine the optimal eating window for a variety of individuals. An eating window should be a consistent daily interval that optimally aligns endocrine mediators of sleep and alertness with eating and fasting. To achieve this, it is ideal for individuals to consider their sleep patterns and any required meal times.
First, an eating window should be concurrent with the active phase to coordinate with circadian rhythms in metabolism and sleep.
Melatonin is secreted at night, and in the absence of light, to aid sleep. Melatonin also inhibits insulin secretion. Thus, eating when melatonin levels are high late at night, or in the early morning , can inhibit a proper glucose response to food.
As a general guide, to avoid eating when melatonin levels are high, choose an eating window that does not start for at least an hour after waking and at least 3 hours before sleep onset. Assuming there is an 8-hour window allotted for sleep, that leaves only a hour window for possible eating times.
Second, an eating window should be consistent and thus needs to be appropriate both for work and off days. If any meal times cannot be changed, such as a family dinner, it should be taken into consideration during the eating window selection.
Finally, some research suggests eating in the earlier phase of the day is better than delayed eating Thus, it may be beneficial to select an earlier eating window when possible. Unlike in animal studies where time-restricted access to food is easy to impose in a vivarium, implementing TRE in humans faces challenges inherent in lifestyle intervention programs.
Successful lifestyle interventions involve a evaluating the current lifestyle, b educational and informational program enabling desired behavioral change, c assessing compliance to the new lifestyle, and d measuring the impact of the lifestyle change both on clinical and psychosomatic outcomes.
Because TRE is a relatively new intervention, there are a vast majority of published studies on TRE that do not report on the existing pattern of participants before the intervention, monitor eating patterns during the intervention, or report compliance other than self-reported compliance from participants see Table 1.
As seen with the Diabetes Prevention Program and numerous follow-up studies, the success of lifestyle intervention on obesity and diabetes prevention is closely associated with self-monitoring, education, and compliance Nevertheless, the vast majority of TRE studies have reported positive health outcomes; which suggest that attention to the stages of TRE lifestyle intervention, self-monitoring, and compliance monitoring can further improve outcomes, identify potential hurdles, and develop cognitive behavioral therapy to adopt TRE.
Clinical trials on TRE started in to and have undergone a huge increase in the past 2 years alone Similarly, there are a large number of ongoing clinical trials assessing TRE that will greatly improve our understanding of a TRE intervention in the coming years.
Published studies have varied greatly in the duration and timing of fasting, duration of intervention, participant population, assessment of eating window, and outcomes see Table 1.
Here we will quickly review what has been published and note a few ongoing clinical trials. There are 2 key factors needed to define a TRE intervention.
Others focused on the Δ change in the eating window, delaying the time of the first energy intake and advancing the last intake by 1.
Another study simply aimed to eliminate nighttime eating fasting 7 pm -6 am , which allowed for up to a hour eating window Second is the phase or timing of the daily eating window. Some studies allow participants to choose the timing of the eating window that works for them sometimes with restrictions relative to sleep and others require a set time.
In studies that set eating times, they may be early in the day or later in the day or even set the timing and number of meals and or snacks see Table 1. This introduces meal frequency as another variable between studies.
Study outcomes have largely depended on the participant population being tested. In these studies, body weight and associated measures percentage of body fat, waist circumference, and body mass index were common outcomes, with other metabolic health assessments such as glucose regulation and cardiovascular health also included in some studies.
These studies assessed feasibility, performance, hunger, lean mass, physical fitness and body weight, and other cardiometabolic characteristics. Four studies studied the effects of TRE in participants who had a cardiometabolic disease or disease risk including one aspect of metabolic syndrome , metabolic syndrome and on medication 91 , prediabetes 75 , and type 2 diabetes In these, as well as some studies in participants with obesity, a deeper assessment of glucose regulation and cardiovascular health was conducted.
In fact, most studies did not assess eating windows at baseline or during the intervention. This speaks to the larger issues that most studies did not measure the timing of food intake throughout the study. Because the eating window and change in the eating window are key components of TRE, this lack of knowledge compromises the ability to conclude whether the results speak to the intervention or the potential lack of adherence.
The most common finding was a decrease in body weight and associated factors 24 studies, see Table 1. Associated factors such as percentage of body fat, body mass index, and waist circumference, were also decreased in many trials. Decreased energy intake was also observed in 6 studies without overt instruction to change diet 88 , 91 , , One study found that changes in energy intake were not sufficient to explain the changes in weight and cardiometabolic health factors 91 , yet this could contribute to some effects of TRE.
Other studies saw benefits to cardiovascular health with decreases in blood pressure as the most common factor see Table 1. It is unclear if decreased blood pressure is a common result of TRE because it was not assessed in most studies.
One pilot study assessed TRE in women with polycystic ovarian syndrome and reported weight loss, improved glycemic control, and decreased lipids and inflammation Importantly, TRE was found to be feasible and safe for all studies.
Larger randomized, controlled trials RCTs are needed because many of the studies to date are smaller pre-post or crossover trials. Yet, the replication of findings, even in diverse patient populations, speak to the potential impact of TRE as a health intervention.
There are now many clinical trials ongoing internationally as can be seen on clinicaltrials. Some to note are larger RCTs evaluating TRE as an intervention for participants with prediabetes participants, NCT , diabetes participants NCT , metabolic syndrome participants, NCT , and firefighters on hour shifts participants, NCT There are also many smaller pilot studies evaluating the effects of TRE in participants with specific diseases such as cancer NCT and polycystic ovarian syndrome NCT Over the coming years, the results of these studies will greatly improve our understanding of the implementation of TRE eg, eating window, time of day and of the potential of TRE to be used as a preventive and cotreatment for a variety of diseases.
Preclinical studies clearly point to the importance of the timing of feeding. TRF results in well-demonstrated amelioration in metabolism and obesity in various animal models.
Results from human studies with TRE are encouraging Fig. TRE reduces body weight and improves metabolism. The decrease in insulin resistance, oxidative stress, inflammation, and blood pressure is seen even when body weight is maintained constant However, many of these studies involve small sample size participants , short term, weeks , or single sex.
The focus has been on metabolism and weight, and other important clinical and physiological outcomes, such as body composition, gut motility, microbiome, liver steatosis, adipose tissue inflammation, to name a few, have remained incompletely investigated.
Summary of various metabolic and other chronic diseases or risk factors that respond favorably to time-restricted feeding TRF or time-restricted eating TRE in animal models rodents and Drosophila or in humans.
For simplicity, the green portion of the wheel represents the eating window and the gray portion represents the fasting window. Human trials are essential for clinical translation. We need RCTs with rigorous design and methods to assess the short and long-term efficacy of TRE, and the mechanisms by which it might exert its effects in humans.
Large-scale effectiveness trials in a population of various ages, sexes, ethnicities, and disease states should follow. These TRE interventions should target people who may benefit the most from it, that is, individuals who spread their calorie intake over prolonged daily windows.
While more challenging in humans than in rodents, the dose-response effect of TRE needs to be investigated. A short duration trial demonstrated the efficacy of a drastic 6-hour TRE intervention; could a more manageable 8-hour, hour, or even hour TRE also be effective in improving metabolism?
Does the restriction of the duration of the eating window need to be proportional to the duration of the baseline eating window? Will TRE 5 of 7 days, or every other week, be sufficient to obtain the desired effect, as shown with intermittent energy restriction ?
Is TRE sustainable? Calorie restriction is usually not beyond a few months. TRE should be tested in combination with other behavioral changes, such as increased physical activity, better sleep hygiene, and amelioration of diet composition.
Should the proven success of TRF in resolving metabolic consequences of obesity in animals be replicated in humans, TRE would become a significant lifestyle tool. Its modest effect on weight loss coupled with possible weight loss—independent effects could result in improved metabolic health, public health, and decreased health care cost.
Health care providers should encourage self-monitoring techniques of meal and sleep timing in high-risk patients and suggest easy-to-implement behavior changes, such as decreased after-dinner snacking, and increased regularity of bedtime. In summary, TRE represents new avenues to assess the effects of the timing of eating on metabolism.
While the mechanisms of TRE are not fully elucidated, animal experiments have generated impressive data in preventing or reversing metabolic diseases associated with obesity. More rigorous human studies are needed to assess the efficacy, mechanism, and sustainability of TRE in a wide range of populations and diseases.
Financial Support: Relevant research in S. DK, AG, CA, and AG , the Department of Defense grant No. W81XWH , the Department of Homeland Security grant No.
EMWFP , the Robert Wood Johnson Foundation grant No. is supported by NIH grant DK; L. is supported by NIH grants DK and DK; and B. is supported by NIH grants DK and AG is supported by the Hillblom Foundation. We thank I-Hsun Wu for creating illustrations for the graphical abstract.
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Secondary aims included the acute effects of TRF on blood glucose and physiological parameters. This study protocol was approved by the ethics committee of Ruijin Hospital affiliated to Shanghai Jiaotong University Ref. cn as ChiCTR A CONSORT flow diagram outlining the study protocol is displayed in Figure 1.
Fourteen healthy participants were recruited from subjects who were interested in this study and submitted our lifestyle questionnaire online. Finally, twelve participants completed this study.
All participants provided written informed consent prior to participation in the trial. The total design of this study was exhibited in Supplementary Figure 1A.
Each eligible subject underwent a cross-over dietary intervention, in which participants were treated with TRF eat within 5. The order of two dietary schedules for each individual was randomized with a one-week washout period.
Each dietary intervention was confined to the metabolic chamber for 3 days, during which calories of each meal and physical activities were rigorously controlled. Participants underwent standardized acclimatization on the first day before the conduction of two diet interventions on the second day.
Then all participants were asked to maintain the same lifestyle on the third day until all feces sourced from day 2 intervening food were completely excreted.
During the first day and third day, all the food provided was labeled with carmine dye. During the second day, all food was labeled with brilliant green dye to trace and collect the excretion of feces from this day.
Individual daily energy requirements were calculated based on body weight, height, and age, using the Harris-Benedict equation with a fixed physical active level PAL of 1.
Each meal was consumed at a constant rate within 30 minutes during the intervention. Daily activities during the intervention were strictly controlled according to the standardized schedule Supplementary Figure 1B. During the unconstrained hours, participants were only allowed to engage in mild activities including watching videos, using computers, walking in the chamber.
To meet the PAL of 1. Daytime was defined as to and nighttime was defined as to of the next day. All food and feces labeled with brilliant green dye used in the intervention were collected, mixed well, and lyophilized.
Lyophilization was performed at °C using an instrument SJIA-5FE, ShuangJia Instrument, Ningbo, China. Calories were measured by using bomb calorimetry according to the published protocol 29 Parr Calorimeter, PARR Instrument Co. To minimize the error of measurements, all samples were measured repeatedly.
We averaged two qualified measurements as the final calories of each sample. Food and fecal protein concentration were determined by the Kjeldahl method, fat concentration was determined by the Soxhlet method, and carbohydrates concentration was calculated by subtracting the protein, fat, water, and ash from the total weight of the sample.
To measure the substrate oxidation and energy expenditure, participants resided in the metabolic chamber for the whole experiment period. The metabolic chamber is an airtight room with a volume of 30,L each Fuji Medical Science Co. The chamber is furnished with an adjustable bed, desk, chair, bicycle ergometer, wash basin, and toilet.
Room temperature and relative humidity were maintained at Concentrations of oxygen O2 and carbon dioxide CO2 in the sample air were analyzed using an online process mass spectrometer Prima PRO, Thermo Fisher Scientific, Cheshire, UK after dehydration.
The mass spectrometry was calibrated monthly using standard gas and the accuracy for O2 and CO2 is 0. O2 consumption VO2 and CO2 production VCO2 were calculated by Henning method To minimize the error of the metabolic chamber, we calibrated the accuracy by alcohol combustion. The precision of metabolic chamber was And then we aggregated these minute-based data into hourly-based for statistical comparison.
Macronutrient oxidation and energy expenditure were calculated using the Weir equation with urinary nitrogen excretion To correct the measured RQ for protein oxidation, nonprotein RQ npRQ was calculated by using nitrogen excretion in h urine.
Twenty-four-hour thermic effect of food TEF was determined by plotting energy expenditure against physical activity level, and the intercept of the regression line at the lowest physical activity represents SMR and TEF. All women performed respiratory chamber testing during the follicular or luteal phases of their menstrual cycle.
All participants were fitted with a CGM sensor and transmitter Dexcom G5, Dexcom, San Diego, CA, USA during the study period. The glucose-oxidase-based electrochemical sensor was inserted into subcutaneous tissue of the abdomen, followed by an initial warm-up period for 2 hours after sensor insertion.
Sensor insertion began the day before the first acclimatization day and there was two days of calibration before data collection during the dietary intervention. According to company recommendations, the sensors were calibrated at least once every 12 hours by finger prick FreeStyle Lite; Abbott Laboratories, Abbott Park, IL.
After a washout period, participants were asked to insert a new sensor the day before the study. Prior to the trial, each participant performed a maximal oxygen uptake VO 2max test on a cycle ergometer E, Monark Ltd, Vansbro, Sweden.
Oxygen consumption and carbon dioxide production were measured by a breath-by-breath portable gas analyzer K5, COSMED, Rome, Italy. Then, the workload was increased by 25W or 20W every minute for men or women, respectively, while participants maintained a pedaling rate of 60 rpm until exhaustion despite verbal encouragement.
Noninvasive blood pressure, 3-lead ECG, and peripheral pulse oximetry SpO2 were continuously monitored by a Cardiac Telemetry System WEPC, Nihon Kohden Co. Systolic and diastolic blood pressure were measured every 10 minutes during the study.
Heart rate, breath rate, and SpO2 were measured every second during the study. Equivital LifeMonitor system EQ02 LifeMonitor, Hidalgo Ltd, Cambridge, UK , capable of logging physiological data including respiratory inductance plethysmography, posture, activity, and skin temperature every 15 seconds was used during study.
Participants were fitted with a correctly sized chest vest dependent on their chest circumference. Axillary skin temperature was measured by an infrared sensor.
Ambulation status was measured by accelerometer sensor and divided into different levels: stationary, moving slowly, and moving fast. Bioelectrical impedance analysis Inbody , Inbody Co. Height was measured in centimeters using a height measurement instrument RGZ, DongFang Scales Co.
Blood sampling was performed at 0h before and 0. Samples were collected by using a standard venipuncture. Plasma and serum were centrifugated at 4°C and stored at °C until analysis. Insulin was measured by an autoanalyzer ARCHITECT ci analyzer, Abbott Laboratories, USA. Participants rated their hunger, fullness, stomach fullness, desire to eat, capacity to eat, and sleepiness using Visual Analog Scales VAS; a mm scale.
The higher the scale, the stronger the sensation. VAS surveys were administered for total fourteen times at pre-meal 0h , 0. Based on our preliminary data and a previous report 29 , we assumed that the hour calories excretion is 6.
Participants were randomly allocated in ratio to 5. After the washout period, crossover was carried out for both groups. The generation of allocation sequence was based on the random-number table.
Statistical analyses were performed using R Studio version 3. Since the sample size of this study is comparatively small, we exert pairwise t-test with Holm—Bonferroni adjustment to reduce the sampling error. The Shapiro-Wilk test was used to check the data distribution.
For parameters with non-Gaussian distribution, the Mann-Whitney test was used. For parameters with normal Gaussian distribution, a two-tailed pairwise t-test was applied. When applicable, non-parametric Wilcoxon matched-pairs signed ranks test was used.
To analysis the time course data, two-way repeated measures ANOVA models were used to evaluated the interaction between time and groups on dependent variable. Baseline data are reported as mean ± standard deviation SD , and other data are presented as mean ± standard error of the mean SEM.
AUCs were calculated by the trapezoidal rule. To evaluate the contribution of insulin and carbohydrate oxidation in explaining TRF-induced change of postprandial glycemic response, a linear mixed-effects model with incremental glucose AUC as the dependent variable, diet intervention control as the reference and pre-prandial glucose as independent variable, participants and meals as random effect was constructed, and pre-prandial insulin and postprandial carbohydrate oxidation were added as independent variable to observed the changes of each effect.
Fourteen participants were included and twelve 5 men and 7 women of them completed this study Figure 1. Each participant underwent a crossover trial, in which participants were treated with TRF eating period: AM to AM and control eating period: AM to AM dietary schedules.
The order of two dietary schedules for each individual was randomized and the two interventions were separated by a one-week washout period.
During the washout period, participants kept their usual lifestyle and the mean body weight upon entering the chamber were same The baseline characteristics of participants were measured from to in the morning of the intervening day Table 1 , during which participants maintained supine position without other activities.
Neither biochemical nor physiological profiles were significantly different between groups. Table 1 Basal characteristics of participants and pre-intervention parameters.
We confirmed the food energy density and macronutrients components by bomb calorimetry and chemical method, respectively.
As shown in Table 2 , no significant differences in total energy, carbohydrate, fat, and protein intake were observed. Meanwhile, the intake time of three meals also showed no statistical difference.
Fluid intake volumes were same among two groups. In Figure 2A there is an overview of hourly energy expenditure for two groups. These differences were mainly attributed to postprandial TEF. Figure 2 Hourly energy expenditure A , thermic effect of food B , mean energy expenditure C , and total energy expenditure D between control and TRF groups.
As shown in previous results, the energy intake and expenditure showed no difference between groups and then we examined a third part, as an often-neglected factor, fecal energy loss.
The absolute number of calories lost in TRF group was significantly increased by However, calories in urine showed In aggregate, Figure 3J shows the energy balance status of both groups. Compared with control group, TRF intervention induced a lower energy balance level Figure 3 Fecal wet weight A , fecal water content B , fecal energy loss C , fecal carbohydrate loss D , fecal fat loss E , fecal protein loss F , intestinal transit time G , urine volume H , urine energy loss I , and energy balance J between control and TRF groups.
After correction for macronutrients intake and lost in feces, carbohydrate balance was significantly decreased in TRF group, as residual carbohydrate was Figure 4 Hourly npRQ A , mean npRQ B , delta day-night npRQ C , total substrate oxidation D , and substrate balance E between control and TRF groups.
Postprandial glycemic and insulinogenic responses to the two time-shifted meals the 2nd and 3rd meals were both significantly attenuated in TRF group as compared to control. The incremental area under curves of postprandial glucose and insulin were paralleling decreased Figures 5F, G and Supplementary Table 4.
Pre- and post-prandial free fatty acid FFA were measured simultaneously with insulin and intravenous blood glucose. While no statistical differences of FFA between groups were observed around the 1st meal, both pre- and post-prandial FFA were substantially reduced during TRF Figure 5H and Supplementary Table 6.
However, there were no significant interaction between time and group on either blood pressure or skin temperature Supplementary Table 7. Neither hourly nor 24h-average data in blood pressure and skin temperature alternation were observed Figures 6C — F, I, J. Figure 5 The effect of TRF on hour CGM data A.
Comparison of hour mean glucose B , CV C , MAGE D , LAGE E , postprandial glycemic F , postprandial insulin G , and postprandial FFA H between control and TRF groups. Figure 6 Heart rate A, B , systolic blood pressure C, D , diastolic blood pressure E, F , respiration rate G, H , and skin temperature I, J between TRF and control group.
As shown in Figure 7 , we also evaluated the subjective appetite and sleepiness level by VAS. Significant interactions between time and groups on hunger, fullness was observed in stomach fullness, desire to eat, and capacity to eat were showed in the two-way repeated ANOVA model Supplementary Table 8.
However, there were not any significant differences in subjective appetite between groups the next day morning. Figure 7 Subjective hunger A , fullness B , stomach fullness C , desire to eat D , capacity to eat E , and sleepiness F responses to VAS from participants during TRF and control intervention.
Although current available data did not support a stronger effect of TRF on body weight and metabolic improvement as compared to continuous caloric restriction, the mechanistic explanation behind this phenomenon remains raised great interest to researchers. Some controversial issues, including inaccurate recording of food intake, unmonitored energy expenditure and the involvement of physiological adaptation were still need to be determined 8 — 11 , 13 , 14 , 21 — 24 , 26 , 32 , Therefore, we conducted the first rigorous trial to systematically quantify and compare the energy balance during TRF intervention in healthy subjects.
We strictly controlled and ensured that energy intake, fluid intake, and lifestyle were consistent during the interventions except for eating schedules, while energy expenditure was monitored using metabolic chamber and all energy excretion including feces and urine were measured by bomb calorimeter.
Surprisingly, TRF could evoke a significant fecal energy loss and a trend in urine energy loss without energy expenditure alteration, which caused a negative energy balance, while hour blood glucose and heart rate were also improved during TRF.
Our findings are consistent with the benefits of long-term TRF intervention reported previously, supporting the use of TRF as an alternative dietary strategy for obesity. In this study, we found no significant differences in total energy expenditure during the whole intervention period.
Despite that some studies suggested that TRF induced adiponectin elevation might contribute to increased energy expenditure 10 , 25 , 34 , the results of the current study are consistent with previous studies: through hour energy monitoring or resting metabolic rate measurements, there is no convincing evidence in support of increased energy expenditure due to TRF 20 , 26 , But several components of total energy expenditure are inconsistent with a prior study, including higher TEF, increased diurnal energy expenditure, and decreased nocturnal energy expenditure in TRF group These negligible differences might be explained by different food macronutrient compositions and time schedules among two studies, respectively.
The precise measurement of the third and often neglected factor, energy excretion finally helped reveal that TRF has resulted in a negative energy balance of Kcal, which is equivalent to Obesity is characterized by the accumulation of adipose tissue and an increase in body mass, which develops under a chronic positive energy balance.
Therefore the reduction of this excess of adipose mass is the main goal of the clinical approach to treat obesity [ 41 , 42 , 43 ]. Most of the subjects in our study are obese but did classic biomarkers are not altered, corroborating data from populational studies [ 44 ].
Nonetheless, these individuals are targets of the deleterious effects of excess adipose tissue that will trigger MetS at any time. This study points out the importance of a more comprehensive evaluation of overweight or obese subjects, which includes anthropometric measurements.
This study was not a randomized controlled trial and does not include detailed nutritional aspects of the subject´s diet since we found conflicting data reported by individuals, such as an incomplete description of the amount of food ingested, the frequency of meals, and the type of foods e.
In addition, the dietary intake self-report can differ or underestimate the real value, offering an inconclusive and misleading analysis [ 45 , 46 ].
Energy restriction is the main factor that leads to weight loss independently of the type of diet [ 9 ]. Therefore, it is feasible to assume that a reduction in total energy consumed was achieved, considering that energy expenditure has maintained constant. A recent meta-analysis has shown a dose—response between weight loss and reduction in energy intake [ 47 ].
Therefore, one can assume that weight loss was higher in those women who had more energy balance deficit. Another concern is the protocol adherence, which can interfere in the outcomes. Since we are not able to control whether or not the subjects followed the TRF strictly for three months without any gap, explaining differences in weight loss among subjects is a hard task.
TRF is an effective dietary strategy to promote weight loss and to decrease WC with no remarkable changes in blood biomarkers. This can be explained by the considerable number of obese women without MetS, in which they have an excess of weight and WC, but not always altered blood biomarkers.
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Journal Meal planning ideas Translational Medicine Tine-restricted 14Article number: Cite this article. Metrics Advanced weight tactics. Intermittent fasting IF is an increasingly Advanced weight tactics dietary approach used protocoll weight Timd-restricted and overall health. While there is an increasing body of evidence demonstrating beneficial effects of IF on blood lipids and other health outcomes in the overweight and obese, limited data are available about the effect of IF in athletes. Thus, the present study sought to investigate the effects of a modified IF protocol i.
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