Chronotype-adapted Diet and Weight Loss

Overweight and Obesity Clinical Trial

— CHRONODIET  

Official title:

Diet and Chronotype: a Randomized Controlled Trial to Evaluate the Effects of a Chronotype-adapted Diet on Weight Loss in Overweight/Obese Subjects

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05941871
• Other study ID #: CHRONODIET
• Status: Recruiting
• Phase: N/A
• Start date: March 6, 2023
• Est. completion date: March 6, 2025

Study information

• Verified date: July 2023
• Source: Azienda Ospedaliero-Universitaria Careggi
• Contact: Francesco Sofi, MD, PhD
• Phone: +390552758042
• Email: francesco.sofi[@]unifi.it
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

In humans, prolonged alterations in the circadian rhythm have been linked to cognitive impairments, premature ageing, and oncological and metabolic disorders such as diabetes and obesity. Obesity, in particular, is an ever-increasing condition with innumerable deleterious effects on human health. In recent years, studies have shown a relationship between a person's chronotype (morning or evening) and eating habits, as well as the importance of adapting these habits to physiological rhythms. Furthermore, it has been suggested that customising the caloric distribution of meals according to personal circadian rhythms may influence body weight and be one of the strategies to control overweight and obesity. In spite of the strong interest in this topic and the increasing number of observational studies conducted, there is currently a lack of intervention studies evaluating whether a low-calorie diet that takes into account the individual chronotype may be more effective than a standard low-calorie diet in the treatment of overweight and/or obesity.

Description:

Background

Society has changed enormously in recent decades and this has had a strong impact on the processes regulating circadian rhythms, in particular the sleep-wake and fasting-eating cycles. The 'normalisation' of the environment, favoured by technological progress, has in fact caused light pollution, noise pollution, excessive thermoregulation, continuous work shifts and disordered eating, leading to an uncoordinated circadian cycle with consequences on physical and mental balance. In humans, prolonged alterations of the biological clock have been linked to cognitive disorders, premature ageing, and oncological and metabolic diseases such as diabetes and obesity. Obesity, in particular, is a condition with innumerable negative effects on human health.

In recent years, a new branch of nutritional research has aroused growing interest in the scientific community: this is chrono-nutrition, which combines elements of nutritional research with elements of chronobiology and studies the impact of eating times on health. The first to use the term "chrono-dystrophy" as a chronic desynchronisation of circadian rhythms were Erren and colleagues, who in their work reported how a loss of synchronisation between environmental signals and physiological processes can lead to alterations in the communication between the central nervous system and peripheral clocks and a change in the subject's metabolism. Subsequently, numerous studies have evaluated the impact of the thirteen dimensions of eating behaviour - timing, frequency and regularity - on health, hypothesising a possible role of the individual circadian rhythm, or chronotype, on the risk of developing overweight and/or obesity. Recent data have demonstrated a relationship between a person's chronotype (morning or evening) and eating habits, as well as the importance of adapting these habits to physiological rhythms. Furthermore, it has been suggested that customising the caloric distribution of meals according to personal circadian rhythms may influence body weight and be one of the strategies to control overweight and obesity. Indeed, recent research has shown that calories ingested at different times of the day have different effects on energy utilisation, leading to differential weight loss, even in the presence of isocaloric quantities.

Despite the strong interest in this topic and the increasing number of observational studies conducted, there is currently a lack of intervention studies evaluating whether a dietary regimen can be used to control body weight. Evidence to date suggests that in order to increase the effectiveness of low-calorie diets, it may be of great interest to consider not only patients' daily energy expenditure but also their circadian preferences. Overall, chrono-nutrition could mediate the effects between sleep, diet and urbanisation, but further research is needed to elucidate the precise physiological and metabolic mechanisms underlying this phenomenon, the importance of chronotype for metabolic health and its impact on public health.

Objectives of the study

The objectives of the study are to compare the effects of a diet with a daily calorie distribution adapted to the individual chronotype with a control diet with a conventional daily calorie distribution. The primary outcome is weight change from baseline. Secondary outcomes are changes in body mass index (BMI), percentage of fat mass, biochemical parameters and gut microbiota profile.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 150
• Est. completion date: March 6, 2025
• Est. primary completion date: March 6, 2025
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years to 65 Years

Eligibility

Inclusion Criteria:

• overweight or obese condition (BMI=25 kg/m2)

• age between 18 and 65 years

• willing to give informes consent

Exclusion Criteria:

• chronic illnesses or unstable conditions (e.g. cancer, kidney or liver disease, inflammatory-intestinal disease, cognitive decline, psychiatric disease)

• drug therapies (use of corticosteroids, antidiabetic drugs)

• pregnancy or intention to become pregnant in the next 12 months

• breastfeeding

• current or recent (last 3 months) adoption of a low-calorie diet

Related Conditions & MeSH terms

• Overweight
• Overweight and Obesity
• Weight Loss

Intervention

Other:
• Dietary intervention - intervention group
Low-calorie diet for 4 months with a different daily energy distribution according to the chronotype: Morning chronotype: 50% of kcal administered before lunch and 15% in the second part of the day (specifically: 40% at breakfast, 10% in the morning snack, 35% at lunch, 5% at afternoon snack and 10% at dinner) Evening chronotype: 15% of kcal given before lunch and 50% in the second half of the day (specifically: 10% of kcal at breakfast, 5% in the morning snack, 35% at lunch, 10% at snack time and 40% at dinner)
• Dietary intervention - control group
Group that will follow a low-calorie diet with a standard daily energy distribution (20% of kcal at breakfast, 10% in the morning snack, 35% at lunch, 10% at afternoon snack and 25% at dinner) for 4 months

Locations

Country	Name	City	State
Italy	Unit of Clinical Nutrition, University Hospital of Careggi	Florence

Sponsors (1)

Lead Sponsor	Collaborator
Azienda Ospedaliero-Universitaria Careggi

Country where clinical trial is conducted

Italy, 

References & Publications (13)

Almoosawi S, Vingeliene S, Gachon F, Voortman T, Palla L, Johnston JD, Van Dam RM, Darimont C, Karagounis LG. Chronotype: Implications for Epidemiologic Studies on Chrono-Nutrition and Cardiometabolic Health. Adv Nutr. 2019 Jan 1;10(1):30-42. doi: 10.1093/advances/nmy070. — View Citation

Erren TC, Reiter RJ. Defining chronodisruption. J Pineal Res. 2009 Apr;46(3):245-7. doi: 10.1111/j.1600-079X.2009.00665.x. Epub 2009 Feb 9. — View Citation

Galindo Munoz JS, Gomez Gallego M, Diaz Soler I, Barbera Ortega MC, Martinez Caceres CM, Hernandez Morante JJ. Effect of a chronotype-adjusted diet on weight loss effectiveness: A randomized clinical trial. Clin Nutr. 2020 Apr;39(4):1041-1048. doi: 10.1016/j.clnu.2019.05.012. Epub 2019 May 21. — View Citation

Horne JA, Ostberg O. A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms. Int J Chronobiol. 1976;4(2):97-110. — View Citation

Lotti S, Pagliai G, Colombini B, Sofi F, Dinu M. Chronotype Differences in Energy Intake, Cardiometabolic Risk Parameters, Cancer, and Depression: A Systematic Review with Meta-Analysis of Observational Studies. Adv Nutr. 2022 Feb 1;13(1):269-281. doi: 10.1093/advances/nmab115. — View Citation

Maukonen M, Kanerva N, Partonen T, Kronholm E, Konttinen H, Wennman H, Mannisto S. The associations between chronotype, a healthy diet and obesity. Chronobiol Int. 2016;33(8):972-81. doi: 10.1080/07420528.2016.1183022. Epub 2016 May 31. — View Citation

Maukonen M, Kanerva N, Partonen T, Kronholm E, Tapanainen H, Kontto J, Mannisto S. Chronotype differences in timing of energy and macronutrient intakes: A population-based study in adults. Obesity (Silver Spring). 2017 Mar;25(3):608-615. doi: 10.1002/oby.21747. — View Citation

Patterson F, Malone SK, Lozano A, Grandner MA, Hanlon AL. Smoking, Screen-Based Sedentary Behavior, and Diet Associated with Habitual Sleep Duration and Chronotype: Data from the UK Biobank. Ann Behav Med. 2016 Oct;50(5):715-726. doi: 10.1007/s12160-016-9797-5. — View Citation

Potter GD, Skene DJ, Arendt J, Cade JE, Grant PJ, Hardie LJ. Circadian Rhythm and Sleep Disruption: Causes, Metabolic Consequences, and Countermeasures. Endocr Rev. 2016 Dec;37(6):584-608. doi: 10.1210/er.2016-1083. Epub 2016 Oct 20. — View Citation

Roenneberg T, Merrow M. The Circadian Clock and Human Health. Curr Biol. 2016 May 23;26(10):R432-43. doi: 10.1016/j.cub.2016.04.011. — View Citation

Ruddick-Collins LC, Johnston JD, Morgan PJ, Johnstone AM. The Big Breakfast Study: Chrono-nutrition influence on energy expenditure and bodyweight. Nutr Bull. 2018 Jun;43(2):174-183. doi: 10.1111/nbu.12323. Epub 2018 May 8. — View Citation

Sofi F, Dinu M, Pagliai G, Cesari F, Marcucci R, Casini A. Mediterranean versus vegetarian diet for cardiovascular disease prevention (the CARDIVEG study): study protocol for a randomized controlled trial. Trials. 2016 May 4;17(1):233. doi: 10.1186/s13063-016-1353-x. Erratum In: Trials. 2016;17(1):253. — View Citation

Sofi F, Dinu M, Pagliai G, Pierre F, Gueraud F, Bowman J, Gerard P, Longo V, Giovannelli L, Caderni G, de Filippo C. Fecal microbiome as determinant of the effect of diet on colorectal cancer risk: comparison of meat-based versus pesco-vegetarian diets (the MeaTIc study). Trials. 2019 Dec 9;20(1):688. doi: 10.1186/s13063-019-3801-x. — View Citation

* Note: There are 13 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Weight change	Measurement of body weight change from baseline in kg	4 months
Secondary	Body mass index (BMI) changes	Measurement of BMI change from baseline. Weight and height will be combined to report BMI in kg/m^2	4 months
Secondary	Fat mass changes	Measurement of fat mass change from baseline. Percentage of fat mass will be assessed using the Akern bioelectrical impedance analyser (model SE 101)	4 months
Secondary	Fasting Blood Glucose changes	Measurement of blood glucose concentration change from baseline in mg/dL	4 months
Secondary	Total cholesterol changes	Measurement of total cholesterol change from baseline in mg/dL	4 months
Secondary	LDL-cholesterol changes	Measurement of LDL cholesterol change from baseline in mg/dL	4 months
Secondary	HDL-cholesterol changes	Measurement of HDL cholesterol change from baseline in mg/dL	4 months
Secondary	Triglycerides changes	Measurement of triglycerides change from baseline in mg/dL	4 months
Secondary	Aspartate transaminase changes	Measurement of aspartate transaminase change from baseline in U/l	4 months
Secondary	Alanine transaminase changes	Measurement of alanine transaminase change from baseline in U/L	4 months
Secondary	Gamma gamma-glutamyl transferase changes	Measurement of gamma-glutamyl transferase change from baseline in U/L	4 months
Secondary	Urea changes	Measurement of urea change from baseline in mg/dL	4 months
Secondary	Creatinine changes	Measurement of creatinin change from baseline in mg/dL	4 months
Secondary	Uric acid changes	Measurement of uric acid change from baseline in mg/dL	4 months
Secondary	Gut microbiota changes	Measurement of gut microbiota profile change from baseline. Each subject will be asked for a stool sample at the start of the study and at the end after 4 months in order to analyse the composition of the gut microbiota and short-chain fatty acids production	4 months