Intermittent Fasting for Metabolic Health, Does Meal Timing Matter?

Obesity is a serious medical condition, the adverse consequences of which include increased risk of cardiovascular disease, diabetes mellitus, reduced fertility and cancer. The economic cost of obesity was placed at $58 billion dollars in Australia in 2008. Studies in mice and non-human primates have shown that moderate caloric restriction (CR) increases lifespan and reduces the incidence of cardiovascular disease, cancer, and type 2 diabetes. Reduced risk of chronic diseases is also observed in humans following CR. However, daily CR is difficult to maintain long term, since the body defends against weight loss by inducing "metabolic adaptation" and altering the hormonal appetite response. An emerging number of studies are examining the effects of limiting food intake to prescribed time periods per day, or every other day. Intermittent, or time restricted feeding describes a dieting approach where food is available ad libitum, however only for a limited period of time (i.e. 3-12 hours). This study will examine the effects of fasting for 15h/day and eating for 9-h per day on glycemic control and metabolic health. This study will build on the existing knowledge base in humans as to whether meal timing, rather than caloric restriction per se, is important to provide the stimulus required to improve metabolic health and reduce risk of chronic disease. Moreover, it will examine whether restricting feeding to later in the day is of lesser benefit to health.

Study Overview

• Status: Completed
• Conditions: Insulin Resistance; Type 2 Diabetes
• Intervention / Treatment: Behavioral: Lifestyle intervention B; Behavioral: Lifestyle Intervention D

Detailed Description

The timing of meal intakes distributed across the wake cycle may play a role in body weight regulation and metabolic health in humans. However, only a limited number of studies have interrogated this in humans. Epidemiological evidence shows that individuals who report consuming more of their daily energy intake at the evening meal were more overweight, than those who reported consumed more of their energy intake before lunch. Similarly, eating lunch late in the day (after 15:00 hrs) was predictive of poorer weight loss during a 20-week dietary intervention study and individuals randomized to consume more calories at breakfast had greater weight loss versus those randomized to eat more calories at dinner after 12 weeks. Taken together these data suggest that consuming more calories in the morning may be beneficial for weight management.

Randomised controlled cross-over intervention, where lean individuals were instructed either to consume all of their calories required for weight maintenance over a 4 hour period from 1700-2100h, or as 3 meals/d for 8 weeks. Significant reductions in body weight and body fat mass, by 1.4 and 2.1 kg respectively, were noted when following the TRF protocol. Consumption of the evening meal was supervised within the laboratory, to ensure subjects consumed the entire meal. In light of evidence that rats switched from a nibbling diet to 1 meal/d increased gluconeogenesis and free fatty acid flux from fat depots, the authors postulated that the greater weight loss may be associated with changes in metabolism. Despite this small amount of weight loss, fasting blood glucose levels were increased, and TRF resulted in poorer glucose tolerance in response to an oral glucose tolerance test (OGTT). Thus, consuming a single, large "dinner" meal was detrimental for metabolic health, although no differences in insulinemia were noted. It is unclear whether responses may have differed if the food allowance was prescribed at breakfast or lunch times. Just one other study has performed a randomised controlled TRF protocol in humans. In this study, healthy, lean male subjects were allowed to eat ad libitum for 13h per day (6am-7pm) for 2 weeks. Participants reported eating significantly less on the TRF versus the control condition, and lost -0.4kg compared with a gain of +0.6kg in the control condition. Whilst this is a minor change in body weight, this pattern is not that atypical of modern eating patterns, and further restriction of eating times, and assessment of obese individuals under these conditions is warranted. The metabolic health impacts were not reported in that study.

Several studies in animals have shown that, when fed in the "wrong" phase (i.e. eating when the animal would normally rest) the mice become obese, despite similar energy intake and expenditure, suggesting that the timing of food intake is important in driving the obese phenotype. Moreover, when high-fat energy intake is restricted to the active phase, the animals become obese, but do not develop the metabolic sequelae that are observed when the same foods are provided in the inactive phase. In humans, shift workers are at higher risks of metabolic disorders, including obesity and type 2 diabetes, possibly as a result of clock desynchronization. Alternatively, this may be the result of mis-timing of meals. For example, epidemiological evidence suggests that a shift toward consuming more calories at night is more likely to result in being overweight when compared with breakfast eaters, while eating a greater proportion of calories at the dinner meal is associated with a higher overall intake and an increased risk for obesity, metabolic syndrome and non-alcoholic fatty liver disease. When 10 healthy adults were subjected to a 28 hour "day" during which they consumed 4 isocaloric meals, the resulting circadian misalignment was associated with increased blood glucose, even in the presence of increased insulin. Moreover, in 3 of the subjects, a postprandial glucose response was observed that would suggest a pre-diabetic state. Under these circumstances, it appears that consuming calories at "night" in humans may have deleterious effects on health, and suggests that meal timing may play a key role in mitigating the metabolic impairment that occurs when the circadian rhythm is disrupted. To further confuse the matter, among breakfast skippers, a higher eating frequency (i.e. ≥ 4 eating occasions per day) has been shown to be associated with a higher risk for type 2 diabetes, compared with breakfast eaters who consumed 1-3 meals per day. In light of this evidence, and the apparent beneficial effects of TRF on metabolic health, the importance of the morning meal and its synchronisation with circadian rhythms is unclear.

Screening (S) - Participants will attend the South Australian Health and Medical Research Institute (SAHMRI) and have the research protocol explained to them in detail. Informed consent to participate in the study, including a verbal indication that they understand the general study protocol and requirements is then obtained. Participants will be assessed by a screening questionnaire for diet, medical, and exercise history to determine their eligibility according to the above criteria. Routine clinical checks are then performed (weight, height, waist circumference, blood pressure). If subjects meet eligibility criteria, they will be invited to take part in the study. Participants will have a dual energy x-ray absorptiometry scan and be fitted with a continuous glucose monitor for one week. During this time, participants will also wear an accelerometer and complete diet diaries to complete a baseline assessment of meal intake pattern. Participants will then be randomly assigned to undergo one of two study arms (TRF-b and TRF-d) for one week each. Conditions are separated by a 2-week washout period, during which participants will be encouraged to maintain their usual dietary pattern and physical activity levels.

Metabolic Testing (D0, D7) during each study condition: Participants arrive at 0700 following an overnight fast. Weight and blood pressure is measured following a seated 10 min rest. A 20 G cannula is inserted into an antecubital vein. A fasting blood sample is drawn for lipids, cytokines and glucoregulatory hormones. Resting metabolic rate and whole body nutrient oxidation is measured via indirect calorimetry. A second fasting blood sample is taken immediately prior to a standard test meal at 0800am or 1200pm, depending on study condition and gastric emptying, postprandial glucoregulatory and gut hormone response to re-feeding will be tested for 3 hours. At the first metabolic visit of each study condition, participants will be fitted with the continuous glucose monitor (CGM), and follow their assigned TRF protocol and assessments by CGM will continue for 7 days, before returning for the D7 metabolic visit. Diet records will be taken and accelerometers worn on the upper arm for each period during the study.

• Study Type: Interventional
• Enrollment (Actual): 15
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Australia
  • South Australia
    • Adelaide, South Australia, Australia
      • University of Adelaide

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 30 years to 70 years (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: Male

Description

Inclusion Criteria:

• Waist circumference >102cm
• BMI >30 kg/m2

Exclusion Criteria:

• Personal history of cardiovascular disease, diabetes, eating disorders
• use of medications which may affect energy metabolism, gastrointestinal function, body weight or appetite (e.g. domperidone and cisapride, anticholinergic drugs, androgenic medications, metoclopramide, orlistat, diuretic medications
• use of prescribed glucose-lowering/antidiabetic medication
• recent weight change in past 3 months,or does not habitually eat breakfast
• uncontrolled asthma, current fever, upper respiratory infections
• current intake of > 140g alcohol/week
• current smokers of cigarettes/cigars/marijuana
• current intake of any illicit substance
• experience claustrophobia in confined spaces
• has donated blood within past 3-months
• unable to comprehend study protocol

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Prevention
• Allocation: Randomized
• Interventional Model: Crossover Assignment
• Masking: None (Open Label)

Number of Arms

3

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: TRF-b; Participants are instructed to eat between 8am-5pm	Behavioral: Lifestyle intervention B; Time limiting feeding from 8-5pm (TRFb)
Experimental: TRF-d; Participants are instructed to eat only between 12-9pm	Behavioral: Lifestyle Intervention D; Time limiting feeding (12-9pm)
No Intervention: Baseline; No lifestyle instruction given

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Time Frame
Postprandial glucose response to meal test	3-hours

Secondary Outcome Measures

Outcome Measure	Time Frame
Postprandial insulin response to test meal	3 hours
Post-prandial gut hormone response to test meal	3 hours
Glycaemic response over 1 week by continuous glucose monitoring	1-week

Collaborators and Investigators

• Sponsor: University of Adelaide
• Investigators: Principal Investigator: Leonie Heilbronn, PhD, The University of Adelaide

Publications and helpful links

General Publications

• Allaf M, Elghazaly H, Mohamed OG, Fareen MFK, Zaman S, Salmasi AM, Tsilidis K, Dehghan A. Intermittent fasting for the prevention of cardiovascular disease. Cochrane Database Syst Rev. 2021 Jan 29;1(1):CD013496. doi: 10.1002/14651858.CD013496.pub2.
• Hutchison AT, Regmi P, Manoogian ENC, Fleischer JG, Wittert GA, Panda S, Heilbronn LK. Time-Restricted Feeding Improves Glucose Tolerance in Men at Risk for Type 2 Diabetes: A Randomized Crossover Trial. Obesity (Silver Spring). 2019 May;27(5):724-732. doi: 10.1002/oby.22449. Epub 2019 Apr 19.

Study record dates

Study Major Dates

• Study Start: January 1, 2016
• Primary Completion (Actual): October 30, 2016
• Study Completion (Actual): July 30, 2018

Study Registration Dates

• First Submitted: December 15, 2015
• First Submitted That Met QC Criteria: December 16, 2015
• First Posted (Estimate): December 17, 2015

Study Record Updates

• Last Update Posted (Actual): October 11, 2018
• Last Update Submitted That Met QC Criteria: October 9, 2018
• Last Verified: October 1, 2018

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Glucose Metabolism Disorders; Metabolic Diseases; Hyperinsulinism; Insulin Resistance
• Other Study ID Numbers: UAdelaide

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED