Impact of the Timing of Pasta Consumption on Health

Impact of Pasta Consumption Timing on Multiple Health Outcomes

To date, the optimal timing for pasta consumption remains uncertain. Based on recent evidence in the field of chrono-nutrition, it is speculated that eating pasta at dinner may have a negative impact on cardio-metabolic health. Carbohydrate intake during a period of minimal glucose tolerance could potentially alter the glycaemic profile and increase the risk of overweight and obesity. Conversely, other studies indicate that consuming carbohydrates at dinner may enhance sleep efficiency and quality. Thus, the aim of this study is, for the first time, to evaluate whether there are discernible differences between consuming pasta at lunch or dinner for the human health.

Study Overview

• Status: Recruiting
• Conditions: Normal Weight
• Intervention / Treatment: Other: Dietary intervention - Pasta at dinner; Other: Dietary intervention - Pasta at lunch

Detailed Description

Background:

Pasta plays an indisputable role in the Mediterranean diet pyramid. Indeed, it is an excellent source of carbohydrates that can be part of a varied, balanced, and healthy diet. Despite this, more and more people are avoiding it because they consider it too caloric and associate it with weight gain, especially if eaten in the evening.

While it is known with certainty that the consumption of pasta, in the right quantities, is associated with positive health effects, there is limited information on the optimal time to consume it. The most common hypothesis is that it is better to consume it at lunch, as metabolism undergoes a physiological and progressive reduction as the evening approaches. Furthermore, recent findings in the field of chrono-nutrition have highlighted that glucose tolerance is high during the day and minimal during the night, suggesting that consuming a high amount of carbohydrates in the evening may predispose to weight gain and a worsened cardio-metabolic profile. On the other hand, according to some studies, consuming carbohydrates in the evening may ensure good sleep quality, as they are an excellent source of tryptophan, an amino acid that promotes serotonin production, also known as the sleep hormone.

Recently, some studies on animal models have suggested that the timing of carbohydrate consumption could also impact the composition and functionality of the gut microbiota. For example, it has been observed that the production of short-chain fatty acids (SCFA) fluctuates throughout the day under the control of the host's circadian rhythms. Considering that SCFA are produced from carbohydrates and are fundamental regulators for many metabolic processes, it could be extremely interesting to explore the relationship between "when carbohydrates are consumed" and microbial functionality.

In conclusion, to date, studies that have evaluated the timing of carbohydrate consumption are limited and rely on physiological and chrono-biological assumptions rather than experimental evidence. Consequently, it is not known whether consuming pasta at lunch or dinner, in the right quantities, may have effects on human weight and health.

Objective of the study:

The aim of this study is to assess, for the first time, whether there is a difference between consuming pasta at lunch or dinner in terms of sleep quality, anthropometric parameters, cardiovascular risk factors, composition and functionality of the gut microbiota in a sample of normal-weight subjects. Additionally, individual chronotype will be taken into consideration, a construct indicating when a subject is most active during the day, as recent studies have highlighted its impact on dietary habits, especially in terms of "meal timing," and human health.

• Study Type: Interventional
• Enrollment (Estimated): 70
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Francesco Sofi, MD, PhD; Phone Number: +390552758042; Email: francesco.sofi@unifi.it

Study Locations

• Italy
  • Florence, Italy, 50134
    • Recruiting
    • Unit of Clinical Nutrition, University Hospital of Careggi
    • Contact: Francesco Sofi, Prof.; Phone Number: +390552758042; Email: francesco.sofi@unifi.it

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• normal weight condition (BMI=18.5-24.9 kg/m2)
• age between 18 and 65 years
• willing to give informed consent

Exclusion Criteria:

• subjects who were involved in night work, planned long-distance jet travel during the study period, had irregular sleeping schedules or were taking any drugs known to affect sleep or metabolism
• presence of current chronic illness or unstable condition (e.g., cardiovascular disease, chronic liver disease, inflammatory bowel disease)
• current or recent (past 2 months) use of antibiotics or probiotics
• pregnancy or intention to become pregnant in the next 12 months
• breastfeeding

Study Plan

How is the study designed?

Design Details

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

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Group 1; Group starting with the dietary intervention of eating pasta at dinner for 3 months.	Other: Dietary intervention - Pasta at dinner; The "pasta at dinner" nutritional intervention will consist, as the name suggests, in eating pasta at dinner for 3 months. The dietary intervention will consist of a normo-caloric diet, defined on the basis of the individual basal metabolic rate measured by indirect calorimetry and on the calculation of the participant's calorie intake extrapolated from a 3-day food diary. The diet will be of the Mediterranean type with 30% of energy coming from fats, 15-20% from proteins and the remaining 50-55% from carbohydrates (mainly complexes). Calorie intake will be distributed as follows: 20% calories at breakfast, 5% calories in the mid-morning snack, 40% calories at lunch, 5% calories in the mid-afternoon snack, 30% calories at dinner.; Other: Dietary intervention - Pasta at lunch; The "pasta at lunch" nutritional intervention will consist, as the name suggests, in eating pasta at lunch for 3 months. The dietary intervention will consist of a normo-caloric diet, defined on the basis of the individual basal metabolic rate measured by indirect calorimetry and on the calculation of the participant's calorie intake extrapolated from a 3-day food diary. The diet will be of the Mediterranean type with 30% of energy coming from fats, 15-20% from proteins and the remaining 50-55% from carbohydrates (mainly complexes). Calorie intake will be distributed as follows: 20% calories at breakfast, 5% calories in the mid-morning snack, 40% calories at lunch, 5% calories in the mid-afternoon snack, 30% calories at dinner.
Experimental: Group 2; Group starting with the dietary intervention of eating pasta at lunch for 3 months.	Other: Dietary intervention - Pasta at dinner; The "pasta at dinner" nutritional intervention will consist, as the name suggests, in eating pasta at dinner for 3 months. The dietary intervention will consist of a normo-caloric diet, defined on the basis of the individual basal metabolic rate measured by indirect calorimetry and on the calculation of the participant's calorie intake extrapolated from a 3-day food diary. The diet will be of the Mediterranean type with 30% of energy coming from fats, 15-20% from proteins and the remaining 50-55% from carbohydrates (mainly complexes). Calorie intake will be distributed as follows: 20% calories at breakfast, 5% calories in the mid-morning snack, 40% calories at lunch, 5% calories in the mid-afternoon snack, 30% calories at dinner.; Other: Dietary intervention - Pasta at lunch; The "pasta at lunch" nutritional intervention will consist, as the name suggests, in eating pasta at lunch for 3 months. The dietary intervention will consist of a normo-caloric diet, defined on the basis of the individual basal metabolic rate measured by indirect calorimetry and on the calculation of the participant's calorie intake extrapolated from a 3-day food diary. The diet will be of the Mediterranean type with 30% of energy coming from fats, 15-20% from proteins and the remaining 50-55% from carbohydrates (mainly complexes). Calorie intake will be distributed as follows: 20% calories at breakfast, 5% calories in the mid-morning snack, 40% calories at lunch, 5% calories in the mid-afternoon snack, 30% calories at dinner.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Sleep quality	The assessment of sleep quality will be done by actigraphy and the following parameters will be evaluated: sleep onset time, end of sleep time, waking after sleep onset, total sleep time, sleep efficiency, number of awakenings, duration of awakenings, movement index, activity index and sleep regularity index.This assessment will be carried out at the beginning and end of each of the two intervention phases.	7 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Weight change	Measurement of body weight change in kg at the beginning and end of each of the two intervention phases.	7 months
Body mass index (BMI) changes	Measurement of BMI change at the beginning and end of each of the two intervention phases. Weight and height will be combined to report BMI in kg/m^2	7 months
Fat mass changes	Measurement of fat mass change at the beginning and end of each of the two intervention phases. Percentage of fat mass will be assessed using the Akern bioelectrical impedance analyser (model SE 101).	7 months
Basal Metabolic Rate	Measurement of basale metabolic rate change at the beginning and end of each of the two intervention phases. The basal metabolism will be defined by indirect calorimetry.	7 months
Fasting Blood Glucose changes	Measurement of blood glucose concentration change in mg/dL at the beginning and end of each of the two intervention phases.	7 months
Glycated Haemoglobin (HbA1c) changes	Measurement of glycated haemoglobin (HbA1c) change in mmol/mol at the beginning and end of each of the two intervention phases.	7 months
Total cholesterol changes	Measurement of total cholesterol change in mg/dL at the beginning and end of each of the two intervention phases.	7 months
LDL-cholesterol changes	Measurement of LDL cholesterol change in mg/dL at the beginning and end of each of the two intervention phases.	7 months
HDL-cholesterol changes	Measurement of HDL cholesterol change in mg/dL at the beginning and end of each of the two intervention phases.	7 months
Triglycerides changes	Measurement of triglycerides change in mg/dL at the beginning and end of each of the two intervention phases.	7 months
Homocysteine changes	Measurement of homocysteine change in micromoli/L at the beginning and end of each of the two intervention phases.	7 months
Aspartate transaminase changes	Measurement of aspartate transaminase change in U/l at the beginning and end of each of the two intervention phases.	7 months
Alanine transaminase changes	Measurement of alanine transaminase change in U/l at the beginning and end of each of the two intervention phases.	7 months
Gamma-glutamyl transferase changes	Measurement of gamma-glutamyl transferase change in U/l at the beginning and end of each of the two intervention phases.	7 months
Urea changes	Measurement of urea change in mg/dL at the beginning and end of each of the two intervention phases.	7 months
Creatinine changes	Measurement of creatinine change in mg/dL at the beginning and end of each of the two intervention phases.	7 months
Uric acid changes	Measurement of uric acid change in mg/dL at the beginning and end of each of the two intervention phases.	7 months
Gut microbiota changes	Measurement of gut microbiota profile change at the beginning and end of each of the two intervention phases. Each subject will be asked for a stool sample at the beginning and at the end of each intervention phases in order to analyse the composition of the gut microbiota and short-chain fatty acids production.	7 months
Individual circadian rhythms	Circadian rhythms and the individual chronotype will be analysed for each participant through the Dim Light Melatonin Onset (DMLO) at the beginning and end of each of the two intervention phases. For this purpose, the NovoLytiX ELISA kit for Direct Melatonin on Saliva (EK-DSM) will be used.	7 months
TBARS changes	Measurement of TBARS changes at the beginning and end of each of the two intervention phases.	7 months
ROS changes	Measurement of ROS changes at the beginning and end of each of the two intervention phases.	7 months
Leptin changes	Measurement of leptin changes at the beginning and end of each of the two intervention phases.	7 months
Ghrelin changes	Measurement of ghrelin changes at the beginning and end of each of the two intervention phases.	7 months
Insulin changes	Measurement of insulin changes at the beginning and end of each of the two intervention phases.	7 months
IL-6 changes	Measurement of IL-6 changes at the beginning and end of each of the two intervention phases.	7 months
C-Peptide YY	Measurement of C-Peptide YY changes at the beginning and end of each of the two intervention phases.	7 months

Collaborators and Investigators

• Sponsor: Azienda Ospedaliero-Universitaria Careggi

Publications and helpful links

General Publications

• 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.
• Henry CJ, Kaur B, Quek RYC. Chrononutrition in the management of diabetes. Nutr Diabetes. 2020 Feb 19;10(1):6. doi: 10.1038/s41387-020-0109-6.
• Huang M, Lo K, Li J, Allison M, Wu WC, Liu S. Pasta meal intake in relation to risks of type 2 diabetes and atherosclerotic cardiovascular disease in postmenopausal women : findings from the Women's Health Initiative. BMJ Nutr Prev Health. 2021 Apr 30;4(1):195-205. doi: 10.1136/bmjnph-2020-000198. eCollection 2021.
• St-Onge MP, Mikic A, Pietrolungo CE. Effects of Diet on Sleep Quality. Adv Nutr. 2016 Sep 15;7(5):938-49. doi: 10.3945/an.116.012336. Print 2016 Sep.
• Frazier K, Chang EB. Intersection of the Gut Microbiome and Circadian Rhythms in Metabolism. Trends Endocrinol Metab. 2020 Jan;31(1):25-36. doi: 10.1016/j.tem.2019.08.013. Epub 2019 Oct 31.
• la Fleur SE, Kalsbeek A, Wortel J, Fekkes ML, Buijs RM. A daily rhythm in glucose tolerance: a role for the suprachiasmatic nucleus. Diabetes. 2001 Jun;50(6):1237-43. doi: 10.2337/diabetes.50.6.1237.
• Afaghi A, O'Connor H, Chow CM. High-glycemic-index carbohydrate meals shorten sleep onset. Am J Clin Nutr. 2007 Feb;85(2):426-30. doi: 10.1093/ajcn/85.2.426. Erratum In: Am J Clin Nutr. 2007 Sep;86(3):809.
• Thaiss CA, Levy M, Korem T, Dohnalova L, Shapiro H, Jaitin DA, David E, Winter DR, Gury-BenAri M, Tatirovsky E, Tuganbaev T, Federici S, Zmora N, Zeevi D, Dori-Bachash M, Pevsner-Fischer M, Kartvelishvily E, Brandis A, Harmelin A, Shibolet O, Halpern Z, Honda K, Amit I, Segal E, Elinav E. Microbiota Diurnal Rhythmicity Programs Host Transcriptome Oscillations. Cell. 2016 Dec 1;167(6):1495-1510.e12. doi: 10.1016/j.cell.2016.11.003.
• Zhao M, Tuo H, Wang S, Zhao L. The Effects of Dietary Nutrition on Sleep and Sleep Disorders. Mediators Inflamm. 2020 Jun 25;2020:3142874. doi: 10.1155/2020/3142874. eCollection 2020.
• Gerard C, Vidal H. Impact of Gut Microbiota on Host Glycemic Control. Front Endocrinol (Lausanne). 2019 Jan 30;10:29. doi: 10.3389/fendo.2019.00029. eCollection 2019.

Study record dates

Study Major Dates

• Study Start (Actual): November 13, 2023
• Primary Completion (Estimated): November 13, 2025
• Study Completion (Estimated): November 13, 2025

Study Registration Dates

• First Submitted: December 15, 2023
• First Submitted That Met QC Criteria: December 15, 2023
• First Posted (Actual): December 29, 2023

Study Record Updates

• Last Update Posted (Actual): January 9, 2024
• Last Update Submitted That Met QC Criteria: January 7, 2024
• Last Verified: January 1, 2024

More Information

Terms related to this study

• Keywords: Cardiovascular risk; Gut microbiota; Sleep quality; Pasta; Anthropometric parameters; Mealtiming
• Other Study ID Numbers: PASTA-TIMING

Plan for Individual participant data (IPD)

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

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No