Normal Weight Clinical Trial
Official title:
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.
Status | Recruiting |
Enrollment | 70 |
Est. completion date | November 13, 2025 |
Est. primary completion date | November 13, 2025 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 18 Years to 65 Years |
Eligibility | 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 |
Country | Name | City | State |
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Italy | Unit of Clinical Nutrition, University Hospital of Careggi | Florence |
Lead Sponsor | Collaborator |
---|---|
Azienda Ospedaliero-Universitaria Careggi |
Italy,
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — View Citation
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. — 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
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. — View Citation
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. — View Citation
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. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | 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 | Weight change | Measurement of body weight change in kg at the beginning and end of each of the two intervention phases. | 7 months | |
Secondary | 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 | |
Secondary | 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 | |
Secondary | 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 | |
Secondary | 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 | |
Secondary | 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 | |
Secondary | 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 | |
Secondary | 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 | |
Secondary | 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 | |
Secondary | Triglycerides changes | Measurement of triglycerides change in mg/dL at the beginning and end of each of the two intervention phases. | 7 months | |
Secondary | Homocysteine changes | Measurement of homocysteine change in micromoli/L at the beginning and end of each of the two intervention phases. | 7 months | |
Secondary | 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 | |
Secondary | 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 | |
Secondary | 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 | |
Secondary | Urea changes | Measurement of urea change in mg/dL at the beginning and end of each of the two intervention phases. | 7 months | |
Secondary | Creatinine changes | Measurement of creatinine change in mg/dL at the beginning and end of each of the two intervention phases. | 7 months | |
Secondary | 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 | |
Secondary | 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 | |
Secondary | 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 | |
Secondary | TBARS changes | Measurement of TBARS changes at the beginning and end of each of the two intervention phases. | 7 months | |
Secondary | ROS changes | Measurement of ROS changes at the beginning and end of each of the two intervention phases. | 7 months | |
Secondary | Leptin changes | Measurement of leptin changes at the beginning and end of each of the two intervention phases. | 7 months | |
Secondary | Ghrelin changes | Measurement of ghrelin changes at the beginning and end of each of the two intervention phases. | 7 months | |
Secondary | Insulin changes | Measurement of insulin changes at the beginning and end of each of the two intervention phases. | 7 months | |
Secondary | IL-6 changes | Measurement of IL-6 changes at the beginning and end of each of the two intervention phases. | 7 months | |
Secondary | C-Peptide YY | Measurement of C-Peptide YY changes at the beginning and end of each of the two intervention phases. | 7 months |
Status | Clinical Trial | Phase | |
---|---|---|---|
Active, not recruiting |
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