Influence of the Fruit Matrix on Glucose and Insulin Responses After the Intake of Orange Juice in Healthy Human Males (ZULEMA)

Role of the Fruit Matrix on the Absorption of Glucose From Orange Juice in Humans

QUALIFICATION: Role of the fruit matrix in glucose absorption from orange juice in healthy human volunteers.

MAIN OBJECTIVE:

Added sugars may have different effects on glycemic response than natural sugars present in fruit juice. The juice matrix (fiber, polyphenols, citric acid, vitamins, minerals) may positively influence this glycemic response. The main objective of this project is to investigate how, for the same qualitative and quantitative sugar composition, the variation in the percentage of fruit matrix present in the juice may affect the glycemic response in healthy male participants.

CLINICAL STUDY:

This is a randomized, double-blind, dose-response, crossover study in healthy male adult participants (18-45 years, 18.5-29.9 kg/m2, N=30). The participants will repeat the entire study (duplicate results) to address interindividual variability and increase the reliability of the results. Participants who agree to take part in the study will complete a series of validated questionnaires about their lifestyle habits. The company AMC Natural Drinks (Murcia, Spain) will prepare the following juices: 100% orange juice versus 50% orange juice and 0% orange juice (same sugar composition as 100% juice but with reduced or absent matrix, respectively). The drinks will be fully characterized in their composition.

The day before each trial, participants will complete a food diary to verify compliance with a polyphenol-free diet and estimate the amount of nutrients consumed (carbohydrates, fiber, water). They will arrive at the UCAM laboratory on an empty stomach where they will drink each of the juices on separate dates. The researchers will measure glycemic response by vein cannulation at baseline (0 min, baseline) and after the consumption of the drinks (time points: 15, 30, 45, 60, 90 and 120 minutes). Results will be compared with the response to a single oral dose of glucose (glycemic index). The participants will repeat some of the test drinks (total: 6 interventions at least 2 or 3 days apart). The researchers will also measure insulin (at the same time points after drinking the test drinks) and analyze the differences in the effects on glycemic and insulin responses between the three types of juices using appropriate statistical analysis.

Study Overview

• Status: Completed
• Conditions: Healthy Nutrition
• Intervention / Treatment: Other: 100% Orange juice; Other: 50% Orange juice; Other: 0% Orange juice; Other: Glucose; Other: 100% Orange juice Rep; Other: 0% Orange juice Rep

Detailed Description

Project proposal: Role of the fruit matrix on the absorption of glucose from orange juice in humans (ZULEMA)

Background assumptions: Excessive consumption of free sugars can have negative health effects and, poor post-prandial control of glucose could be a marker for longer term type 2 diabetes risk. Sugars drive the glycemic index (GI) of beverages but, contrary to expectations, fruit juices and sugar-sweetened beverages provide different GI results despite often having the same total sugar content. This implies that natural and added sugars may have different effects on glycemic control, or that the combination of sugars within the juice matrix is somehow ameliorating the effect of the sugars on glycemic control.

Research question: How does varying the matrix and source of sugars but not total sugars in fruit juices and drinks impact GI? The researchers assume that the free sugars will be the driver of GI but this may not be the case.

Hypothesis: For the same amount of free sugars (sucrose, glucose and fructose) in juices and beverages, the fruits juice matrix (i.e. fiber, complex carbohydrates, citric acid, polyphenols and other phytochemicals, minerals, vitamins), will have a modulatory effect on the absorption of glucose.

Objective: The primary objective of this study is to assess the effect of the presence of the juice matrix in 100% orange juice against manipulated juice drinks (to reduce the percentage of fruit matrix) on postprandial glycemia responses in healthy subjects. The secondary objective will be to characterize the effect on the insulin response.

Experimental design: The glucose-responses will also be compared to that of glucose alone (Glycemic Index, GI).

Methods:

Juice preparation and logistics. The orange drinks will be produced and supplied by AMC Natural Drinks (Murcia, Spain). A 100% fruit juice (orange juice) will be compared with drinks containing 50%, and 0% of juice although with the same total sugar qualitative and quantitative composition (sucrose, fructose, glucose) as in the 100% juice.

Chemical analyses:

The researchers will characterize the sugar composition and the main fruit matrix components:

Soluble and insoluble fiber chemical analysis.

Sugars analysis. The juices will be manufactured and the sugar composition (sucrose, glucose and fructose) measured and adjusted to make sure that the sugar content does not changed during the storage period. Analyses will be performed by High Performance Liquid Chromtagraphy (HPLC) using the appropriate Refractive Index (RI) detectors.

Phytochemicals analysis. Individual phenolics and other phytochemicals characteristic of orange juice. Flavanones, polymethoxyflavones, hydroxycinnamic acid derivatives, flavones, carotenoids, will be analysed using reversed phase HPLC with Ultraviolet-Diode Array (UV-DAD) detectors and Mass Spec (MS) detectors.

Clinical trial:

This study is a crossover, randomized, double-blind, dose-response intervention trial. All participants will repeat the study in separate times (to attain duplicate results). The study protocol has been already approved by the Catholic University Ethical Committee.

Participants, Inclusion and Exclusion Criteria:

The researchers will recruit male healthy adults aged 18 to 45 years of age via online classified advertisements, social media, and by word-of-mouth. Females are not eligible since menstrual cycle can influence glycaemic control. To meet the inclusion criteria, the participants will be required to have Body a Mass Index (BMI) between 18.5 and 29.9 kg/m2, to be habitual breakfast consumers, and to be willing to consume the study beverages. Participants will be excluded if they are on a diet or have food allergies or aversion to the drinks of the study. Furthermore, participants will be excluded if they had significant weight fluctuations within the past 6 months or a previous diagnosis of diabetes, pre-diabetes, gastrointestinal disease, liver disease, kidney disease, or a metabolic disorder.

Sample size:

The researchers estimated the sample size for a randomized crossover study in which the effects of the intervention (different test orange drinks) will be tested in a healthy adult sample population. For this purpose, the researchers used the free available software G*Power 3.1.9.7 assuming a two-tails statistical power of 80% (1-β=0.80), a level of statistical significance of 5% (α=0.05) and an effect size of d=0.6. According to this, the minimum number of participants in the study should be N=24. These participants should also take part in the second round of tests (duplicate results). The final number of participants was increased up to 30 to count for potential withdrawals.

Study Consent:

A telephone screening interview will provide initial eligibility criteria. Participants who pass the telephone screening will be scheduled to attend an in-person information and final screening session at the laboratory to review study protocols and obtain written informed consent. The researchers will take some anthropometric measures and will explain to the participants the intervention and procedures during the whole study. The participants will also complete a series of general validated questionnaires about their dietary and lifestyle habits.

Intervention Design:

Eligible participants will complete four test sessions (+ two repetitions) at least 2-3 day apart. On separate mornings, participants will arrive at the laboratory at 8:00 am following a 10 to 12 h fast, except for a small amount of water which will be permitted up to 1 h before arriving. On the day before to each test session, the participants will complete a food diary to verify adherence to the polyphenol-free and citric fruits-free diet, fasting protocol, and to estimate the amount of nutrients consumed (principally, total carbohydrates, free sugars, fiber, and water).

The participants will rapidly (within five minutes) consume one of the three drinks: (1) 100% orange juice, (2) orange beverage with 50% orange juice and 50% water with added sugars to match the content of the 100% juice, and (3) 100% water with added sugars to match the content of the 100% juice. Standard serving sizes (around 250 mL) will be calculated on the basis of total available carbohydrate to reach an intake of 25 g of free sugars. In addition, the participants will also consume a glucose solution (25 g) to estimate the GI. All test drinks will be served cold plastic containers with lids. Glycemic response will be measured at baseline (0 minutes), and 15, 30, 45, 60, 90 and 120 minutes post-consumption of the drink.

After completion of the study, the participants will have a 2-3 weeks rest and will come back to the laboratory for a second test session. The aim of this repetition is to have amore robust analysis of the results and evaluate intra- and interindividual variability.

Post-Prandial Glycemic Response:

The researchers will collect blood samples by vein cannulation and will measure glucose by means of a Glucose Oxidase (GOD) Activity Assay Kit (E-BC-K520-M) (Elabscience, Texas, USA).

Insulin measurement:

Additional samples of blood will be collected from the vein. After centrifugation (1200-1500 ×g, 10 min, 4 ºC), the serum samples will be rapidly frozen and kept at -80 ºC until analysis of insulin levels. Insulin will be measured using a highly sensitive Human Insulin ELISA Kit (E-EL-H2665) (Elabscience, Texas, USA).

Statistical Analyses:

Statistical analyses will be performed using SPSS and R applying a Linear Mixed Model and post-hoc constrast to determine the effects and differences between the four interventions (i.e., glucose, 100% OJ, 50% OJ and 0% OJ) on blood glucose and insulin iAUC, Cmax, and T15min. A p-value < 0.05 will be considered statistically significant.

• Study Type: Interventional
• Enrollment (Actual): 25
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Spain
  • Murcia
    • Murcia, Murcia, Spain, 30107
      • Universidad Católica de San Antonio (UCAM)

Participation Criteria

Eligibility Criteria

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

Description

Inclusion Criteria:

• BMI between 18.5 and 29.9 kg/m2
• To be habitual breakfast consumers
• To be willing to consume the study beverages

Exclusion Criteria:

• To be on a diet
• To have food allergies
• To have some kind of sensitiviness or aversion to beverages in this study
• To have had significant weight fluctuations within the past 6 months
• Previous diagnosis of diabetes or pre-diabetes
• Previous diagnosis of other gastrointestinal disease
• Previous diagnosis of liver disease
• Previous diagnosis of kidney disease
• Previous diagnosis of a metabolic disorder

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Basic Science
• Allocation: Randomized
• Interventional Model: Crossover Assignment
• Masking: Single

Number of Arms

6

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Active Comparator: 100% Orange juice; In this arm, the participants will drink a total of 250 mL of a commercial 100% orange juice with known total sugar content (25 g) and matrix composition.	Other: 100% Orange juice; 250 mL of commercial 100% orange juice containing 25 g of total sugars (glucose, fructose, saccharose).
Experimental: 50% Orange juice; In this arm, the participants will drink 250 mL of a beverage containing 50% of the same commercial orange juice (active comparator) with added sugars to match the content of sugars the 100% juice. The content of matrix will be 50% of the active comparator.	Other: 50% Orange juice; 250 mL of 50% diluted orange juice (100% orange juice) plus added sugars to attain the same concentration and composition of sugars (glucose, fructose, saccharose) as the 100% orange juice
Experimental: 0% Orange juice; In this arm, the participants will drink 250 mL of 100% water with added sugars to match the content of sugars of the commercial 100% orange juice (active comparator). This drink will not contain the food matrix components.	Other: 0% Orange juice; 250 mL of water plus added sugars to attain the same concentration and composition of sugars (glucose, fructose, saccharose) as the 100% orange juice
Active Comparator: Glucose solution; In this arm, the participants will drink 250 mL of a glucose solution with a total 25 g of glucose (to match the total concentration of sugars in the test beverages). This arm will allow for the measurement of the glycemic indexes of the test drinks. In addition, it will allow for a characterization of the participant (basal glucose level at the start of the intervention and type of responder, e.g. biphasic, monophasic).	Other: Glucose; 250 mL of water with 25 g of glucose. To determine the glycemic index of the different drinks and to characterize the glucose and insuline response of the participants
Active Comparator: 100% Orange juice Rep; This arm will be a repetition of the 100% Orange juice arm	Other: 100% Orange juice Rep; Repetition of the 100% orange juice intervention
Experimental: 0% Orage juice Rep; Thia arm will be a repetition of the 0% Prange juice arm	Other: 0% Orange juice Rep; Repetition of the 0% orange juice intervention

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Incremental Area Under the Curve (iAUC) of blood glucose over 120 minutes.	Blood glucose samples collected via vein cannulation. Glucose measured using a Glucose Oxidase (GOD) Activity Assay Kit (E-BC-K520-M) (Elabscience, Texas, USA).	0 minutes, 15 minutes, 30 minutes, 45 minutes, 60 minutes, 90 minutes and 120 minutes following the consumption of each drink.

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Peak Blood Glucose Concentration	Maximum post-prandial blood glucose concentration (Cmax) during the 120-minute test period.	0 minutes, 15 minutes, 30 minutes, 45 minutes, 60 minutes, 90 minutes and 120 minutes following the consumption of each drink.
Blood Glucose Concentration at 15 Minutes	Blood glucose concentration at 15 minutes post-ingestion (C15min)	0 minutes, 15 minutes, 30 minutes, 45 minutes, 60 minutes, 90 minutes and 120 minutes following the consumption of each drink.
Time to peak concentration for glucose	Time (min) when Cmax of glucose is reached	0 minutes, 15 minutes, 30 minutes, 45 minutes, 60 minutes, 90 minutes and 120 minutes following the consumption of each drink.
Incremental Area Under the Curve (iAUC) of blood insulin over 120 minutes.	Additional blood samples collected from the vein via vein cannulation and centrifuged (1200-1500 ×g, 10 min, 4 °C) to obtain the serum which will be frozen quickly and kept at -80 ºC until the insulin analyses. Insulin measured using a highly sensitive Human Insulin ELISA Kit (E-EL-H2665) (Elabscience, Texas, USA).	0 minutes, 15 minutes, 30 minutes, 45 minutes, 60 minutes, 90 minutes and 120 minutes following the consumption of each drink.
Peak Blood Insulin Concentration	Maximum post-prandial blood insulin concentration (Cmax) during the 120-minute test period.	0 minutes, 15 minutes, 30 minutes, 45 minutes, 60 minutes, 90 minutes and 120 minutes following the consumption of each drink.
Blood Insulin Concentration at 15 Minutes	Blood insulin concentration at 15 minutes post-ingestion (C15min)	0 minutes, 15 minutes, 30 minutes, 45 minutes, 60 minutes, 90 minutes and 120 minutes following the consumption of each drink.
Time to peak concentration for insulin	Time (min) when Cmax of insuline is reached	0 minutes, 15 minutes, 30 minutes, 45 minutes, 60 minutes, 90 minutes and 120 minutes following the consumption of each drink.

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Dietary habits	The participants will complete the 14-MEDAS questionnaire to measure their dietary adherence to the Mediterranean Diet (MD). The score varies from 0 to 14 points; a higher value denotes a higher and better adherence to the MD.	1st visit to the study laboratory after passing the telephone interview and before starting the intervention.
Physical Activity	The participants will complete the Global Physical Activity Questionnaire (GPAQ) to determine their level of activity. The results are measured in Metabolic Equivalents of task (METs). According to the World Health Organization (WHO), 600-1200 METs per week are adequate for health maintenance. A higher METs value indicates a higher level of physical activity.	1st visit to the study laboratory after passing the telephone interview and before starting the intervention.
Sleep Quality	The participants will complete the Pittsburgh Sleep Quality Index (PSQI) questionnaire to determine the quality of their sleeping habits. The score varies from 0 to 21; a lower score means a better sleep quality.	1st visit to the study laboratory after passing the telephone interview and before starting the intervention.
Chronotype	The participants will complete the Horne and Östberg's morningness-eveningness questionnaire (MEQ) to determine whether they have more matutine or vespertine habits. The score varies between 16 and 86 points. The higher the value the more matutine type, the lower the value, the more vespertine type.	1st visit to the study laboratory after passing the telephone interview and before starting the intervention.
Body Mass Index - BMI (Kg/m2)	The Height and Weight of the volunteers will be measured to calculate the BMI = Weigh(Kg) / Height (m)2	1st visit to the study laboratory after passing the telephone interview and before starting the intervention.
Waist Circumference - WC (cm)	The WC of the volunteers will be measured using with a tape measure placed midway between the top of hip bone and the bottom of the ribs.	1st visit to the study laboratory after passing the telephone interview and before starting the intervention.
% of Fat Mass	The percentage of body fat mass of the volunteers will be measured using Bioelectrical Impedance Analysis (BIA)	1st visit to the study laboratory after passing the telephone interview and before starting the intervention.
% of Muscle Mass	The percentage of body muscle mass of the volunteers will be measured using Bioelectrical Impedance Analysis (BIA)	1st visit to the study laboratory after passing the telephone interview and before starting the intervention.

Collaborators and Investigators

• Sponsor: María-Teresa García-Conesa
• Collaborators: Universidad Católica San Antonio de Murcia
• Investigators: Study Director: Francisco-Tomás G Barberán, PhD, CEBAS-CSIC

Publications and helpful links

General Publications

• Buysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989 May;28(2):193-213. doi: 10.1016/0165-1781(89)90047-4.
• Bull FC, Maslin TS, Armstrong T. Global physical activity questionnaire (GPAQ): nine country reliability and validity study. J Phys Act Health. 2009 Nov;6(6):790-804. doi: 10.1123/jpah.6.6.790.
• Garcia-Conesa MT, Philippou E, Pafilas C, Massaro M, Quarta S, Andrade V, Jorge R, Chervenkov M, Ivanova T, Dimitrova D, Maksimova V, Smilkov K, Ackova DG, Miloseva L, Ruskovska T, Deligiannidou GE, Kontogiorgis CA, Pinto P. Exploring the Validity of the 14-Item Mediterranean Diet Adherence Screener (MEDAS): A Cross-National Study in Seven European Countries around the Mediterranean Region. Nutrients. 2020 Sep 27;12(10):2960. doi: 10.3390/nu12102960.
• 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.
• Kang H. Sample size determination and power analysis using the G*Power software. J Educ Eval Health Prof. 2021;18:17. doi: 10.3352/jeehp.2021.18.17. Epub 2021 Jul 30.
• Lin G, Siddiqui R, Lin Z, Blodgett JM, Patel SN, Truong KN, Mariakakis A. Blood glucose variance measured by continuous glucose monitors across the menstrual cycle. NPJ Digit Med. 2023 Aug 11;6(1):140. doi: 10.1038/s41746-023-00884-x.
• Chen V, Khan TA, Chiavaroli L, Ahmed A, Lee D, Kendall CWC, Sievenpiper JL. Relation of fruit juice with adiposity and diabetes depends on how fruit juice is defined: a re-analysis of the EFSA draft scientific opinion on the tolerable upper intake level for dietary sugars. Eur J Clin Nutr. 2023 Jul;77(7):699-704. doi: 10.1038/s41430-023-01258-y. Epub 2023 Feb 3. No abstract available.
• Cohen, J. Statistical power analysis for the behavioral sciences (2nd ed.), Erlbaum, Hillsdale, NJ (1988).
• Guzman G, Xiao D, Liska D, Mah E, Sanoshy K, Mantilla L, Replogle R, Boileau TW, Burton-Freeman BM, Edirisinghe I. Addition of Orange Pomace Attenuates the Acute Glycemic Response to Orange Juice in Healthy Adults. J Nutr. 2021 Jun 1;151(6):1436-1442. doi: 10.1093/jn/nxab017.
• Mayr S, Buchner A, Erdfelder E, Faul F. A short tutorial of GPower. Tutorials in Quantitative Methods for Psychology, 2007, 3(2), 51-59.
• Robayo S, Kucab M, Walker SE, Suitor K, D'Aversa K, Morello O, Bellissimo N. Effect of 100% Orange Juice and a Volume-Matched Sugar-Sweetened Drink on Subjective Appetite, Food Intake, and Glycemic Response in Adults. Nutrients. 2024 Jan 12;16(2):242. doi: 10.3390/nu16020242.
• Saltaouras G, Shaw PK, Fraser AC, Hawes C, Smith H, Handley L, Whitby H, Thondre SP, Lightowler HJ. Glycaemic index, glycaemic load and dietary fibre characteristics of two commercially available fruit smoothies. Int J Food Sci Nutr. 2019 Feb;70(1):116-123. doi: 10.1080/09637486.2018.1481201. Epub 2018 Jun 11.
• Berry SE, Valdes AM, Drew DA, Asnicar F, Mazidi M, Wolf J, Capdevila J, Hadjigeorgiou G, Davies R, Al Khatib H, Bonnett C, Ganesh S, Bakker E, Hart D, Mangino M, Merino J, Linenberg I, Wyatt P, Ordovas JM, Gardner CD, Delahanty LM, Chan AT, Segata N, Franks PW, Spector TD. Human postprandial responses to food and potential for precision nutrition. Nat Med. 2020 Jun;26(6):964-973. doi: 10.1038/s41591-020-0934-0. Epub 2020 Jun 11.
• Choo VL, Viguiliouk E, Blanco Mejia S, Cozma AI, Khan TA, Ha V, Wolever TMS, Leiter LA, Vuksan V, Kendall CWC, de Souza RJ, Jenkins DJA, Sievenpiper JL. Food sources of fructose-containing sugars and glycaemic control: systematic review and meta-analysis of controlled intervention studies. BMJ. 2018 Nov 21;363:k4644. doi: 10.1136/bmj.k4644.

Study record dates

Study Major Dates

• Study Start (Actual): October 21, 2024
• Primary Completion (Actual): December 20, 2024
• Study Completion (Actual): January 31, 2025

Study Registration Dates

• First Submitted: October 7, 2024
• First Submitted That Met QC Criteria: October 9, 2024
• First Posted (Actual): October 15, 2024

Study Record Updates

• Last Update Posted (Actual): November 28, 2025
• Last Update Submitted That Met QC Criteria: November 24, 2025
• Last Verified: November 1, 2025

More Information

Terms related to this study

• Keywords: Lifestyle habits; Orange juice; Glucose response; Adult males; Sugar composition; Fruit matrix; Insuline response
• Additional Relevant MeSH Terms: Carbohydrates; Sugars; Hexoses; Monosaccharides; Glucose
• Other Study ID Numbers: CE092408

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No