Effect of sodium alginate addition to chocolate milk on ... - Nature

European Journal of Clinical Nutrition (2014) 68, 613–618 © 2014 Macmillan Publishers Limited All rights reserved 0954-3007/14 www.nature.com/ejcn

ORIGINAL ARTICLE

Effect of sodium alginate addition to chocolate milk on glycemia, insulin, appetite and food intake in healthy adult men D El Khoury1, HD Goff2, S Berengut1, R Kubant1 and GH Anderson1 BACKGROUND/OBJECTIVES: Sodium alginate reduces appetite and glycemia, when consumed in water- and sugar-based drinks. But, its effects when added to other commonly consumed beverages have not been reported. Because chocolate milk (CM) is criticized for raising blood glucose more than unflavored milk, the aim of our study was to investigate the effect of adding a stronggelling sodium alginate to CM on glycemia, insulinemia, appetite and food intake. SUBJECTS/METHODS: In a randomized crossover design, 24 men (22.9 ± 0.4 years; 22.5 ± 0.3 kg/m2) were provided with isovolumetric (325 ml) treatments of CM, 1.25% alginate CM, 2.5% alginate CM or 2.5% alginate solution. Sodium alginate had a ratio of 0.78:1 of mannuronic acid (M) to guluronic acid (G) residues, and was block distributed. Treatments were standardized for lactose, sucrose and calcium content, and provided 120 min before an ad libitum pizza meal during which food intake was measured. Appetite and blood glucose and insulin were measured at baseline and at intervals pre- and post-meal. RESULTS: Addition of 2.5% alginate to CM reduced peak glucose concentrations, at 30 min, by an average of 6% and 13% compared with 1.25% alginate CM (95% confidence intervals (CIs): 0.02–1.08; P = 0.037) and CM alone (95% CIs: 0.49–1.55; P = 0.000) respectively. Insulin peaks at 30 min were lower by 46% after 2.5% alginate CM relative to CM (95% CIs: 3.49–31.78; P = 0.009). Pre-meal appetite was attenuated dose dependently by alginate addition to CM; CM with 2.5% alginate reduced mean appetite by an average of 134% compared with CM alone (95% CIs: 8.87–18.98; P = 0.000). However, total caloric intake at the pizza meal did not differ among treatments. CONCLUSIONS: The addition of a strong-gelling sodium alginate to CM decreases pre-meal glycemia, insulinemia and appetite, but not caloric intake at a meal 2 h later, in healthy adult men. European Journal of Clinical Nutrition (2014) 68, 613–618; doi:10.1038/ejcn.2014.53; published online 26 March 2014

INTRODUCTION The rising incidence of obesity and type 2 diabetes has stimulated a search for functional foods that may contribute to a healthy body weight and controlled glucose homeostasis.1 The viscous and gel-forming soluble fibers alginates have recently received considerable attention because of their potential role in reducing appetite, food intake and glycemia when added to foods and beverages.2 Additions of sodium alginate to beverages have provided inconsistent results. Whereas a number of studies have demonstrated that sodium alginates, when added most commonly to water- and sugar-based drinks, reduce postprandial appetite and food intake both in the short-3–5 and long-term,6,7 and attenuate postprandial blood glucose8–10 and insulin concentrations,9 others have not.11,12 These inconsistencies may be due to variation in the characteristics of the alginates used, particularly the ratios of β-D-mannuronic acid (M) to α-L-guluronic acid (G) residues. Alginate is a linear polyuronic saccharide, consisting of 1 → 4 linked G and M residue segments, which combine to form alternating G-rich (G-blocks), M-rich (M-blocks) or MG-rich

(MG-blocks) areas.13 It is isolated from a number of brown seaweed species and certain soil bacteria. Upon interaction with protons in the gastric environment (pHo 3.5), as well as in the presence of multivalent cations such as calcium, sodium alginate fibers readily form a gel.14 Product viscosity and gel strength are not solely dependent on the amount of alginate but also on its M/G block ratio. Alginates containing lower amounts of M-blocks relative to G-blocks form stronger gels,15 and promote greater feelings of fullness.16 Gastric rigid lumps formed after the ingestion of strong-gelling alginate-based meals, leading to gastric distension, activated antral mechanoreceptors and consequently enhanced feeling of satiety.5 None of the previous studies has reported the effects of sodium alginate added, at different doses, to a commonly consumed beverage, and therefore its functional value in this context is unknown. For the current study, we hypothesized that sodium alginate with a strong gelling potential, when added to chocolate milk (CM), reduces glycemia, induces satiety and decreases food intake in a dose-dependent manner. Therefore, the objective of this study was to determine the effect of sodium alginate addition

1 Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada and 2Department of Food Science, University of Guelph, Guelph, Ontario, Canada. Correspondence: Professor GH Anderson, Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, 150 College Street, Room 322, Toronto, M5S3E2 Ontario, Canada. E-mail: [email protected] Contributors: DEK contributed to conception and design of the study, carried out the study, performed data analysis and interpretation, and drafted the manuscript; HDG contributed to conception and design of the study, analyzed the physicochemical properties of sodium alginate and treatments, and reviewed the manuscript; SB carried out the study, and assisted in data analysis; RK assisted in data analysis, and contributed to manuscript revision; GHA contributed to conception and design of the study, data interpretation and manuscript review; all authors read and approved the final manuscript. Received 11 October 2013; revised 10 January 2014; accepted 5 February 2014; published online 26 March 2014

Sodium alginate for glucose and appetite regulation D El Khoury et al

614 to CM on postprandial responses of glucose, insulin and appetite ratings and on food intake at an ad libitum meal served 2 h later. CM was chosen as the food vehicle for two reasons. First, consumption of CM is increasing in both the United States17 and Canada.18 But, CM has been criticized for its high caloric and sugar contents. Second, CM is a nutritionally complete beverage, known to possess inherent satiating characteristics.19 MATERIALS AND METHODS Participants Twenty-four healthy males, between the ages of 20–30 years and with a body mass index ranging from 20 to 24.9 kg/m2, were recruited through advertisements in the University of Toronto campus. Exclusion criteria included smoking, dieting, skipping breakfast, lactose intolerance, allergies to milk or soy, diabetes (fasting blood glucose ⩾ 7.0 mmol/l) or other metabolic diseases that could interfere with study outcomes. Restrained eaters, identified by a score of ⩾ 11 on the Eating Habits Questionnaire,20 and those taking medications were also excluded. The sample size required for detection of treatment effects on subjective appetite and food intake, the secondary study measures, was 24 based on previous shortterm studies conducted in our laboratory.19,21 A sample size of 16, needed to detect significant effects of treatments on postprandial responses of the primary measures glucose and insulin, was also estimated based on previous studies in our group.21 Subjects were financially compensated for completing the study. The procedures of the study were approved by the Human Subject Review Committee, Ethics Review Office, at the University of Toronto, and participants, informed about the purpose of the study, gave their written consent.

Treatments Four treatments were administered using a within-subject single-blinded repeated-measures design. Treatments were as follows: sodium alginatefree CM (1% fat; Beatrice Ltd., Toronto, Ontario, Canada; control 1), 1.25% sodium alginate CM, 2.5% sodium alginate CM and 2.5% sodium alginate milk-free water-based solution (control 2). Sodium alginate, extracted from the brown seaweed Laminaria hyperborea and rich in G monomers, was supplied by FMC Biopolymer Inc. (Market Street, PA, USA). Calcium carbonate (Nutrition for Optimal Wellness (NOW) Foods, Bloomingdale, IL, USA) was added at 716 mg per 325 ml of the alginate solution to match the calcium content of milk-based treatments, and to facilitate the gelling process of the water-based alginate solution via interaction of sodium alginate with added calcium ions. Both lactose (Davisco Foods International, Inc., Eden Prairie, MN, USA) and sucrose (Lantic Natural Granulated Sugar, Canada) were added to the alginate solution at 15.7 and 20.8 g per 325 ml, respectively, to equalize their sugar content and composition with the milk-based treatments. Vanilla extract (1.2 ml) and sucralose were added to all four treatments to match taste and sweetness. The composition of each treatment is outlined in Table 1. All products were isovolumetric (325 ml), based on the commercially available serving size of milk products. Treatments were served chilled. All preloads were prepared 12 h before the start of each session, and stored overnight at a temperature of 4 °C.

Physicochemical properties of treatments Alginate polymers are characterized with a wide range of molecular weights, degrees of polymerization and gelling properties, which depend on alginate species sources and extraction conditions.22 The polydisperse nature of sodium alginate, with different ratios of G-rich, M-rich and MG-rich areas, strongly shapes its viscosity grade, which is one of the most industrially relevant properties of alginate products. The G and M composition of sodium alginate were determined at the University of Guelph according to Grasdalen et al.,23 with minor modifications. The alginate sample (100 mg) was dissolved in deionized water (40 ml), and the sample solution was put into a spectra/Por dialysis tube (molecular weight cutoff 3500 Da) and dialyzed against deionized water containing EDTA (1.0%, w/w) for 24 h, which was followed by dialysis against deionized water for another 24 h. The content in the dialysis tube was then freeze dried and the dry sample was re-dissolved in deionized water to form a 1.0% solution (w/w), adjusted to pH 3.0 using 0.1 M HCl and heated at 100 °C for 30 min. The solution was adjusted to pH 7.0 using 0.1 M NaOH, and then freeze dried to obtain the partially hydrolyzed alginate sample. Twenty milligram of the partially hydrolyzed sample was European Journal of Clinical Nutrition (2014) 613 – 618

Table 1.

Nutritional information of treatments Treatments

Nutritional informationa

CM

CM+1.25% alginate

CM+2.5% alginate

2.5% alginate

Weight (g) Calories (kCal) Protein (g) Energy (%) Fat (g) Energy (%) Carbohydrates (g) Energy (%) Lactose (g) Sucrose (g) Sodium alginate (g) Calcium (mg) Viscosity (Pa s)b

325 221 11.7 21.2 3.25 13.2 36.4 65.9 15.6 20.8 0 325 0.04

325 221 11.7 21.3 3.25 13.2 36.4 65.9 15.6 20.8 4.06 337 1.20

325 221 11.8 21.3 3.25 13.2 36.4 65.9 15.6 20.8 8.13 349 10.00

325 146 0.1 0.3 0 0 36.4 100 15.6 20.8 8.13 325 2.90

Abbreviation: CM, chocolate milk. aNutritional information of each treatment as prepared. bMeasured at the University of Guelph.

dissolved in 2 ml of heavy water (D2O), and the solution was then freeze dried against three changes of D2O. The alginate sample recovered from the final freeze drying was re-dissolved in 2 ml of D2O, and passed through a nylon syringe filter (pore size 2.0 μm). A volume of 0.6 ml of the filtrate was transferred to a 5-mm nuclear magnetic resonance tube. Onedimensional 1 H nuclear magnetic resonance spectrum was acquired on a Bruker Mac 600 MHz spectrometer (Bruker Co., Rheinstetten, Germany) at 90 °C. Trimethylsilyl propionate in D2O was used as the chemical shift standard for the nuclear magnetic resonance analysis. The steady-shear apparent viscosities of the treatments were measured at 4 °C immediately after adding the sodium alginate (0 h), and 1, 24 and 72 h after dissolution by a controlled-stress rheometer (Advanced Rheometer 2000, TA Instruments, New Castle, DE, USA) with a 6 cm, 2° cone and plate geometry. The sample was loaded onto the plate, and allowed to ‘rest’ for 1 min. The change in viscosity over a period of 15 min was measured in triplicate using a typical oral shear rate of 50 s 1. A shear rate of 50 s 1 for determining viscosity was used in order to reveal lower viscosity values that are indicative of the higher shear rate range of normal swallowing conditions, as discussed by van Vliet.24

Protocol Participants attended the Department of Nutritional Sciences at the University of Toronto following a 12-h overnight fast, except for water, which was permitted until 1 h before each session. To minimize withinsubject variability, each participant was scheduled to arrive at the same time and on the same day of the week for each treatment, and was instructed to refrain from alcohol consumption and to maintain the same dietary and exercise patterns the evening before each test. To ensure that instructions were followed, participants completed visual analog scale questionnaires assessing their ‘Sleep Habits’, ‘Stress Factors’, ‘Food Intake and Activity Level’, and ‘Feelings of Fatigue’ upon arrival to the department.19 If they reported significant deviations from their usual pattern, they were asked to reschedule. Participants were also administered a ‘Motivation to Eat’ 100 mm visual analog scale, which has been used in previous studies,19,21 to measure subjective appetite. A composite score of the four appetite questions in the ‘Motivation to Eat’ visual analog scale was calculated to obtain the average appetite score for statistical analysis. Before the beginning of each test, participants provided a baseline finger prick capillary blood sample using a Monoejector Lancet device (Sherwood Medical, St Louis, MO, USA). Capillary blood glucose was immediately measured using a glucose meter (Accu-Chek Compact; Roche Diagnostics Canada, Laval, Canada), and serum insulin was stored at − 80 °C for later analysis using a specific human insulin kit (ALPCO Diagnostics, Salem, NH, USA). A baseline glucose measurement of >5.5 mmol/l suggested non-compliance with the fasting instructions, and subjects were rescheduled accordingly. Treatments were provided in random order once per week, over a period of 4 weeks. Following the completion of baseline measurements, each person was instructed to consume the treatment within 10 min at a © 2014 Macmillan Publishers Limited


615 constant pace using a spoon. The order of treatments was randomized using randomization block design, which was generated with a random generator script in SAS version 9.2. Participants were blinded to the treatment. Pleasantness, taste and texture of treatments were assessed and compared using ‘Palatability’ visual analog scale.21 Subjective appetite and capillary blood glucose were measured at 10, 20, 30, 45, 60, 75, 90 and 120 min (pre-meal, which refers to the period before the pizza test meal) and 140, 170, 200, 230 and 260 min (post-meal, which refers to the period after the pizza test meal) after consumption of the treatments for 24 individuals. For insulin analysis, samples of capillary blood were collected from 16 participants at 0, 30, 60, 120, 140, 170 and 200 min. Subjects were asked to remain seated for the duration of the experimental session, and were permitted to read, do homework or listen to music. Food intake of 24 participants was measured at an ad libitum pizza meal, served 120 min after consumption of the treatments as described previously.19,25 Three varieties (Pepperoni, Deluxe and Three Cheese) of Deep’n Delicious pizza (McCain Foods Ltd, Florenceville, NB, Canada) were offered to participants, according to their preference at screening, and their same choices were provided at all four sessions. All three varieties were similar in content, averaging 11 g protein, 6 g fat, 26 g carbohydrate and 205 kCal/100 g energy, and size (5 inch diameter). Because of the lack of a thick outer crust, the pizzas have a uniform energy content that eliminates the possibility that participants would eat the energy-dense filling and leave the outside crust of the pizza.26 Each pizza (cooked for 8 min at 430 oF and cut in four slices) was weighed before serving. Pizzas were served on trays at 10-min intervals; each tray contained two pizzas of their first choice and one pizza of their second and third choices. Participants were asked to eat until they were ‘comfortably full’, over a duration of 20 min. Ad libitum water was served with the ad libitum pizza lunch meal. Energy intake from the pizza meal was calculated based on the weight consumed and the compositional information provided by the manufacturer, whereas water intake was measured by weight. Cumulative energy intake was calculated by adding the energy consumed from the pre-meal treatment to the energy consumed at the test meal.

Statistical analyses Statistical analyses were conducted using SPSS software (version 20.0; SPSS, Chicago, IL, USA). Two-factor repeated-measures analysis of variance (ANOVA) was performed to analyze the effects of time, treatment and their interaction on dependent variables including blood glucose, serum insulin and subjective appetite. When a treatment and time significant interaction was revealed, one-factor ANOVA followed by Tukey’s post-hoc test was performed on changes from baseline for blood glucose, serum insulin and subjective appetite at each time of measurement. Pre-meal changes from baseline were calculated from 0 min (immediately before treatment consumption) and post-meal changes from 120 min (immediately before pizza test meal consumption). Incremental areas under the curve (iAUCs) were also calculated for appetite scores, blood glucose and serum insulin using the trapezoidal method, whether cumulatively or separately for each

the pre-meal and the post-meal time period, but were not reported to avoid the false negatives that arise from the use of iAUCs.27–29 In addition, glucoseto-insulin ratios were compared among treatments by calculating the ratios of blood glucose to insulin iAUCs (mmol*min*L 1/μU*min*ml 1), pre-meal, post-meal and cumulative. Glucose-to-insulin ratio evaluates the efficacy of insulin action.30 The lower the postprandial ratio, the higher the effectiveness of insulin activity. The effects of treatment on palatability and food, total energy and water intakes, and on pre-meal, post-meal and cumulative mean changes from baseline for glucose, insulin and appetite as well as glucose to insulin iAUC ratios were tested using one-factor ANOVA followed by Tukey’s post-hoc test. Pearson’s correlation coefficients were used to detect associations between dependent measures. Results are presented as mean ± standard error of the mean (s.e.m.). Statistical significance was concluded with a P-value less than 0.05.

RESULTS Participant characteristics Twenty-four healthy adult males (age: 22.9 ± 0.4 years; body mass index: 22.5 ± 0.3 kg/m2) completed the study. There were five dropouts because of non-compliance to treatments and/or session schedule. Physicochemical properties and palatability of treatments The sodium alginate had an M/G ratio of 0.78:1, reflecting a composition of 56% G and 44% M residues. Diad frequencies were as follows: GG: 0.44, MM: 0.32, GM: 0.12 and MG: 0.12. GGG triad fragments demonstrated much higher peak intensity than either GGM or MGG fragments in the nuclear magnetic resonance spectrum. These results indicated that G and M were very blockdistributed along the length of the polymeric chain. Viscosity of treatments remained relatively constant over the four time periods, 0, 1, 24 and 72 h, confirming the stable viscosity of our alginate-based treatments prepared 12 h before the session. Treatment composition affected pleasantness (P o 0.0001), taste (P o 0.0001) and texture (P o 0.0001). Sodium alginate reduced pleasantness, taste and texture of CM in a dose-dependent manner. But, the palatability of 2.5% alginate CM and 2.5% alginate solution was comparable. Blood glucose In the pre-meal period (0–120 min), blood glucose changes from baseline were affected by time (P o 0.0001), treatment (P o0.05) and a time and treatment interaction (P o 0.0001; Figure 1). At the

Figure 1. Effect of treatments on pre-meal and post-meal glucose changes from baseline (mmol/l). Means with different superscripts are significantly different at each measurement time (one-factor ANOVA followed by Tukey’s post-hoc test; P o 0.05). Pre-meal period: 0–120 min, and post-meal period: 120–260 min. All values are mean ± s.e.m. (n = 24). FI, food Intake at the ad libitum lunch meal. © 2014 Macmillan Publishers Limited

European Journal of Clinical Nutrition (2014) 613 – 618


616 peak time, 30 min, glucose increments were lower following 2.5% alginate CM than 1.25% alginate CM and CM by 32% and 46%, respectively. In the post-meal period (120–260 min), glucose changes from baseline were also affected by time (P o 0.0001), treatment (P o0.05) and a time and treatment interaction (P o 0.05; Figure 1). Treatment affected mean glucose changes from baseline during pre- (P o 0.05) and post-meal (P o 0.0001) periods, and for the duration of the study (Po 0.0001). In the pre-meal period, 2.5% alginate CM resulted in lower mean blood glucose compared with CM alone and 2.5% alginate solution (Po 0.05). All three alginateenriched preloads reduced post-meal and total glucose responses compared with CM alone (P o 0.0001). Serum insulin In the pre-meal period (0–120 min), serum insulin changes from baseline were affected by time (P o 0.0001), treatment (P o0.01) and a time and treatment interaction (P o 0.0001). Insulin peaks, at 30 min, were lower by 46% following 2.5% alginate CM compared with CM alone (P o0.01). The 2.5% alginate solution also resulted in lower insulin increments in comparison to 1.25% alginate CM (P o 0.05) and CM (P o0.0001) at 30 min, but similar to the 2.5% alginate CM. In the post-meal period (120–200 min), insulin changes from baseline were affected only by time (P o0.0001). Treatment affected mean insulin changes from baseline in the pre-meal period (P o0.05), but not the post-meal phase or over the duration of the study (Table 2). Only the 2.5% alginate solution resulted in lower pre-meal insulin concentrations compared with CM alone (P o0.05). Glucose to insulin ratio The ratios of pre- and post-meal as well as cumulative blood glucose to insulin iAUCs did not differ among treatments. Subjective appetite In the pre-meal period (0–120 min), appetite changes from baseline were affected by time (P o 0.0001), treatment (P o0.05) and time and treatment interaction (P o 0.0001). All treatments suppressed pre-meal appetite over time, but 2.5% alginate CM suppressed appetite to a greater extent than CM alone, but similar to 1.25% alginate CM and 2.5% alginate solution, up to 60 min. In the post-meal period (120–200 min), only time (P o 0.0001) affected appetite changes from baseline.

Table 2. Effect of treatment on pre- and post-meal overall mean serum insulin concentrations changes from baseline1 Treatment CM CM+1.25% alginate CM+2.5% alginate 2.5% alginate P

Alginate (g)

Pre-meal (μU/ml)2

Post-meal (μU/ml)3

Total (μU/ml)4

0 4.06 8.13 8.13

12.4 ± 2.24a 9.2 ± 1.99a,b 7.9 ± 1.47a,b 5.5 ± 0.94b o0.05

32.7 ± 3.09 32.5 ± 3.30 30.5 ± 3.02 27.9 ± 2.72 NS

21.1 ± 2.07 19.2 ± 2.11 17.6 ± 1.87 15.1 ± 1.65 NS

Abbreviations: CM, chocolate milk; NS, non-significant. 1Values are means ± s.e.m.; n = 16. Means in the same column with different superscript letters are significantly different, Po0.05 (one-factor ANOVA for treatment effect followed by Tukey’s post-hoc test). 2Pre-meal values are means of changes from baseline (0 min) of all observations before the test meal: 0, 30, 60 and 120 min. 3Post-meal values are means of changes from baseline (120 min) of all observations after the test meal: 140, 170 and 200 min. 4Total values are means of changes from baseline of all observations: 0–200 min.


Pre-meal (P o0.0001), post-meal (P o0.0001) and cumulative (P o 0.05) mean appetite changes from baseline were affected by treatment (Table 3). Only in the pre-meal period, mean appetite reduction by alginate in treatments was dose dependent. The 2.5% alginate CM resulted in lower appetite responses compared with CM (P o0.0001) and 1.25% alginate CM (P = 0.001). Furthermore, 2.5% alginate CM resulted in lower appetite responses than 2.5% alginate solution (P o 0.0001). Food intake, cumulative energy intake and water intake All treatments resulted in similar food intake, cumulative energy intake and water intake at the ad libitum lunch. Correlations among dependent variables Pleasantness (r = − 0.636; P o0.0001), taste (r = − 0.622; P o 0.0001) and texture (r = − 0.621; P o 0.0001) of treatments were inversely correlated with their alginate content; treatment palatability, pleasantness (r = − 0.494; P o0.0001), taste (r = − 0.437; P o 0.0001) and texture (r = − 0.554; P o 0.0001) were also negatively correlated with product viscosity. Product viscosity, in turn, positively associated with alginate dose (r = 0.727; P o 0.0001), and was negatively correlated with pre-meal appetite changes from baseline (r = − 0.275; P o 0.05), pre-meal glucose changes from baseline (r = − 0.292; P o 0.05) and insulin changes from baseline at 30 min (r = − 0.293; P o0.05). Food intake at the pizza meal correlated with pre-meal (r = 0.320; P = 0.010) and cumulative (r = 0.260; P o 0.05) appetite changes from baseline. Similarly, cumulative energy intake from the treatment and lunch meal combined was positively associated with pre-meal (r = 0.304; P o 0.05) and cumulative (r = 0.256; Po 0.05) appetite changes from baseline. DISCUSSION This study is the first to show an effect of adding a strong-gelling viscous sodium alginate to a commonly consumed beverage, CM, on postprandial glycemia, insulin and subjective appetite in healthy men. Sodium alginate additions to CM reduced postprandial glucose and insulin excursions and promoted satiety in a dose-dependent manner, with no effect on food intake at a meal served 120 min later. The addition of sodium alginate at 2.5% to CM attenuated pre-meal glycemia by 38%, while reducing insulin peaks at 30 min by 46%, and pre-meal appetite by 134% compared with CM alone. The reduction in mean glucose responses after the alginatebased beverages compared with CM (Figure 1) is consistent with Table 3. Effect of treatment on pre-meal, post-meal and total mean appetite score changes from baseline1 Treatment

CM CM+1.25% alginate CM+2.5% alginate 2.5% Alginate P

Alginate (g) 0 4.06 8.13 8.13

Pre-meal (mm)2 10.4 ± 1.04a 16.9 ± 1.56b 24.3 ± 1.58c 14.4 ± 1.30a,b o 0.0001

Post-meal (mm)3 45.8 ± 2.19a 34.6 ± 2.30b 35.9 ± 2.33b 45.2 ± 2.23a o 0.0001

Total (mm)4 23.0 ± 1.39a 23.2 ± 1.38a 28.4 ± 1.35b 25.4 ± 1.41a,b o 0.05

Abbreviation: CM, chocolate milk. 1Values are means ± s.e.m.; n = 24. Means in the same column with different superscript letters are significantly different, P o0.05 (one-factor ANOVA for treatment effect followed by Tukey’s post-hoc test). 2Pre-meal values are means of changes from baseline (0 min) of all observations before the test meal: 0, 10, 20, 30, 45, 60, 75, 90 and 120 min. 3Post-meal values are means of changes from baseline (120 min) of all observations after the test meal: 140, 170, 200, 230 and 260 min. 4Total values are means of changes from baseline of all observations: 0–260 min.

© 2014 Macmillan Publishers Limited


five out of eight human trials, which reported an improved glycemic control after supplementation of drinks and solid foods with alginate.8–10,31,32 However, a novel observation from the present study was that sodium alginate in a pre-meal beverage affected glucose homeostasis in both the pre-meal and post-meal periods. A primary effect of sodium alginate addition to CM was to reduce pre-meal glycemic excursions concurrent with reduced insulin peak concentrations. This may be mainly attributed to a combined effect of both sodium alginate9 and dairy proteins33 on slowing gastric emptying. The ratios of glucose to insulin iAUCs did not differ among treatments in the pre-meal period. However, insulin peaks at 30 min were reduced by 46% after 2.5% alginate CM compared with CM alone, consistent with the effect on blood glucose (Figure 1). These results are also consistent with the lowered insulin responses observed after consumption of 3% alginate in a milk powder-based beverage in men with type 2 diabetes,9 and support the application of these results to at-risk populations as well as healthy individuals. In the post-meal period, alginate attenuated glycemic excursions, but not insulin, irrespective of the dose and the beverage vehicle by an average of 37% compared with CM alone. The lack of effect on insulin is to be expected because of the potential saturation of insulin synthesis pathways in response to consumption of a large carbohydrate load of 127 g and calories averaging 985 kCal at the ad libitum meal.34 In addition, because post-meal insulin changes from baseline did not differ among treatments (Table 2), it is possible that insulin-independent mechanisms contributed to the reduced postprandial glycemia through a combination of, first, the actions of alginate on reducing glucose uptake32 by decreasing the contact between food and digestive enzymes,2 and, second, the actions of free alginic acid, a byproduct of alginate hydrolysis by gastric acid, on inhibiting glucose absorption by acting on Na+-dependent glucose transporters in the small intestine.35 A dose-dependent effect of alginate on the suppression of subjective appetite was found in the pre-meal period (Table 3), consistent with a previously reported dose-dependent suppression of hunger and increase of fullness over 5 h post-consumption of sodium alginate added at 0, 0.6 or 0.8% to a CM drink (325 ml) of low viscosity.36 For strong-gelling alginates, a concentration of 0.6% seems to be sufficient in liquid formulations for a robust satiating effect. For this study, we added higher alginate doses to CM in order to detect significant effects not only on appetite but also on food intake, glycemia and insulinemia, which were not reported previously.36 Food intake and cumulative food intake at the test meal served 120 min after consumption of treatments did not differ among preloads, but this is consistent with the low energy content (146 and 221 kCal) of the treatments37 and the lengthy interval between preload intake and lunch meal,38 which is beyond the duration of the transient effects of the treatments. Other studies, using 3% alginate solution, found reductions in food intake of 8% at an ad libitum meal served 30 min later in normal-weight participants.3 Reduced glycemia, insulinemia and appetite after consumption of the 2.5% alginate CM are consistent with the increased viscosity of the treatment because of sodium alginate, but in addition result from a synergistic interaction between the proteins in CM and sodium alginate. Product viscosity was negatively correlated with pre-meal glucose (r = − 0.292) and appetite (r = − 0.275) changes from baseline and with insulin changes from baseline at 30 min (r = − 0.293). In the present study, 2.5% alginate CM (10 Pa s) had approximately a 3-fold higher viscosity than 2.5% alginate solution (2.9 Pa s), 8-fold higher than 1.25% alginate CM (1.2 Pa s) and 300-fold higher than CM alone (0.035 Pa s; Table 1). Our treatments were designed to promote gel formation independent of endogenous acid secretions, because the ingestion of ‘ionicgelling’ alginate drink composed of sodium alginate and calcium © 2014 Macmillan Publishers Limited

617 carbonate was found to attenuate glycemic responses to a greater extent than a drink containing ‘acid-induced’ gelling alginate without calcium ions.31 The uronic acid groups of sodium alginate adopt a spatial conformation that facilitates the formation of stronger gels in the presence of multivalent cations such as calcium.14 In addition, sodium alginate molecules may also aggregate into a gel matrix in the presence of protein structures such as casein.39 This may explain why the addition of 2.5% alginate to CM suppressed pre-meal appetite scores by 69% more than that in water solutions (Table 3). Increased product viscosity is known to promote elevations in gastric viscosity levels, expansion of the stomach and slower gastric emptying, contributing to satiety and dampening of postprandial glucose excursions.40 As expected, reductions in treatment palatability occurred in response to sodium alginate-based beverages. The addition of alginate to CM reduced its pleasantness, taste and texture in a dose-dependent manner, consistent with the progressive increase of its viscosity, which is known to decrease palatability41 and in turn reduce appetite.41,42 This was confirmed by the inverse correlations found between product palatability and viscosity, in the present study. Increased product viscosity reduces the perception of flavor and sweetness through two mechanisms; either by limiting the mobility of free water in the solution resulting in decreased sweetness and thus flavor intensity, or by the perception of viscosity itself in the mouth affecting the perception of tastants and consequently overall flavor.43 However, the primary satiating effects of sodium alginate in CM, particularly over the first 2 h, were independent of palatability, for several reasons. First, treatment effects remained significant after correcting for product palatability as a covariate in one-way ANOVA. Second, despite having similar palatability scores, the 2.5% alginate in CM suppressed pre-meal appetite to a greater extent than that in water solutions (Table 3). Finally, palatability has been reported to be a significant factor in modulating responses of appetite and food intake only during the first postprandial 60 min.44 In addition to the duration of time between the preload and lunch meal, another limitation of the present study could be the serving of a palatable and familiar lunch to this age group of young men. However, the present design has been used frequently to quantify the effects of protein45 or other caloric preloads on appetite and food intake.46 Although women have been recruited in many of our studies,19,21,47 resources were not available for their inclusion in this study. Also, our results on adults cannot be extrapolated with certainty to other age groups. However, targeting adult men in the present study was based on consumption patterns in the United States showing that males drink more fluid milk than females and that the typical age for consuming CM is more widely distributed than teenage years.48 Seventeen percent of adults aged 20–49 years consume flavored milk as a beverage, similar to that reported for 12- to 19-year-old adolescents. Furthermore, the results do not necessarily reflect changes in energy balance and glucose homeostasis over a longer duration. Future studies are required to explore mechanisms of action, gastric emptying as well as hormonal regulators of satiety and glycemia. Finally, our findings are specific to the addition of 2.5% sodium alginate to CM; however, they provide an indication that sodium alginate may have a potential in other commonly consumed beverages to reduce blood glucose, insulin and appetite responses. In conclusion, the addition of a strong-gelling sodium alginate to CM decreases pre-meal glycemia, insulinemia and appetite, but not caloric intake at a meal 2 h later, in healthy adult men. CONFLICT OF INTEREST The authors declare no conflict of interest.



618

ACKNOWLEDGEMENTS We thank Ms N Yavorska for her assistance in the conduction of few sessions as part of her undergraduate research project at the University of Toronto, and X Xing for alginate compositional analyses and K Logan for viscosity analyses at the University of Guelph. This study was supported by a peer reviewed grant from the National Science and Engineering Research Council of Canada-Collaborative Research and Development (CRDJP 385597–09), in partnership with the unrestricted support of Dairy Farmers of Ontario and Kraft Canada Inc. McCain Foods Ltd (Toronto, Canada) provided the pizza for the experimental test meals.

REFERENCES 1 Fujioka K. Management of obesity as a chronic disease: nonpharmacologic, pharmacologic, and surgical options. Obes Res 2002; 10: 116S–123S. 2 El Khoury D, Goff HD, Anderson GH. The role of alginates in regulation of food intake and glycemia: a gastroenterological perspective. Crit Rev Food Sci Nutr 2013; e-pub ahead of print 11 October 2013; doi:10.1080/10408398.2012.700654. 3 Georg Jensen M, Kristensen M, Belza A, Knudsen JC, Astrup A. Acute effect of alginate-based preload on satiety feelings, energy intake, and gastric emptying rate in healthy subjects. Obesity (Silver Spring) 2012; 20: 1851–1858. 4 Solah VA, Kerr DA, Adikara CD, Meng X, Binns CW, Zhu K et al. Differences in satiety effects of alginate- and whey protein-based foods. Appetite 2010; 54: 485–491. 5 Hoad CL, Rayment P, Spiller RC, Marciani L, Alonso Bde C, Traynor C et al. In vivo imaging of intragastric gelation and its effect on satiety in humans. J Nutr 2004; 134: 2293–2300. 6 Pelkman CL, Navia JL, Miller AE, Pohle RJ. Novel calcium-gelled, alginate-pectin beverage reduced energy intake in nondieting overweight and obese women: interactions with dietary restraint status. Am J Clin Nutr 2007; 86: 1595–1602. 7 Paxman JR, Richardson JC, Dettmar PW, Corfe BM. Daily ingestion of alginate reduces energy intake in free-living subjects. Appetite 2008; 51: 713–719. 8 Williams JA, Lai CS, Corwin H, Ma Y, Maki KC, Garleb KA et al. Inclusion of guar gum and alginate into a crispy bar improves postprandial glycemia in humans. J Nutr 2004; 134: 886–889. 9 Torsdottir I, Alpsten M, Holm G, Sandberg AS, Tolli J. A small dose of soluble alginate-fiber affects postprandial glycemia and gastric emptying in humans with diabetes. J Nutr 1991; 121: 795–799. 10 Wolf BW, Lai CS, Kipnes MS, Ataya DG, Wheeler KB, Zinker BA et al. Glycemic and insulinemic responses of nondiabetic healthy adult subjects to an experimental acid-induced viscosity complex incorporated into a glucose beverage. Nutrition 2002; 18: 621–626. 11 Mattes RD. Effects of a combination fiber system on appetite and energy intake in overweight humans. Physiol Behav 2007; 90: 705–711. 12 Odunsi ST, Vazquez-Roque MI, Camilleri M, Papathanasopoulos A, Clark MM, Wodrich L et al. Effect of alginate on satiation, appetite, gastric function, and selected gut satiety hormones in overweight and obesity. Obesity (Silver Spring) 2010; 18: 1579–1584. 13 Brownlee IA, Allen A, Pearson JP, Dettmar PW, Havler ME, Atherton MR et al. Alginate as a source of dietary fiber. Crit Rev Food Sci Nutr 2005; 45: 497–510. 14 Smidsrod O, Draget K. Chemical and physical properties of alginate. Carbo in Europe 1996; 14: 6–13. 15 Draget KI, Skjak-Braek G, Smidsrod O. Alginate based new materials. Int J Biol Macromol 1997; 21: 47–55. 16 Georg Jensen M, Knudsen J, Viereck N, Kristensen M, Astrup A. Functionality of alginate based supplements for application in human appetite regulation. Food Chem 2012; 132: 823–829. 17 International Dairy Organization (eds) World Dairy Situation 2009. Bulletin of the International Dairy Federation, 2009. 18 Statistics Canada (eds) Food Statistics 2009. 19 Panahi S, Luhovyy BL, Liu TT, Akhavan T, El Khoury D, Goff D et al. Energy and macronutrient content of familiar beverages interact with pre-meal intervals to determine later food intake, appetite and glycemic response in young adults. Appetite 2013; 60: 154–161. 20 Herman C, Polivy J. Restrained eating. In: Stunkard AJ (eds) Obesity. WB Saunders and Co: Philadelphia, PA, 1980. 21 Akhavan T, Luhovyy BL, Brown PH, Cho CE, Anderson GH. Effect of premeal consumption of whey protein and its hydrolysate on food intake and postmeal glycemia and insulin responses in young adults. Am J Clin Nutr 2010; 91: 966–975. 22 McHugh DJ (ed) A guide to the seaweed industry. Food and Agriculture Organization of the United Nations: Rome, 2003.


23 Grasdalen H, Larsen B, Smidsrød O. A P.M.R. study of the composition and sequence of urinate residues in alginates. Carbohydr Res 1979; 68: 23–31. 24 van Vliet T. On the relation between texture perception and fundamental mechanical parameters for liquids and time dependent solids. Food Quality and Preference 2002; 13: 227–236. 25 El Khoury D, Brown P, Smith G, Berengut S, Panahi S, Kubant R et al. Increasing the protein to carbohydrate ratio in yogurts consumed as a snack reduces post-consumption glycemia independent of insulin. Clin Nutr 2013; 33: 29–38. 26 Akhavan T, Anderson GH. Effects of glucose-to-fructose ratios in solutions on subjective satiety, food intake, and satiety hormones in young men. Am J Clin Nutr 2007; 86: 1354–1363. 27 Wolever TM. Effect of blood sampling schedule and method of calculating the area under the curve on validity and precision of glycaemic index values. Br J Nutr 2004; 91: 295–301. 28 Allison DB, Paultre F, Maggio C, Mezzitis N, Pi-Sunyer FX. The use of areas under curves in diabetes research. Diabetes Care 1995; 18: 245–250. 29 Standl E, Schnell O, Ceriello A. Postprandial hyperglycemia and glycemic variability: should we care? Diabetes Care 2011; 34: S120–S127. 30 Vuguin P, Saenger P, Dimartino-Nardi J. Fasting glucose insulin ratio: a useful measure of insulin resistance in girls with premature adrenarche. J Clin Endocrinol Metab 2001; 86: 4618–4621. 31 Harden CJ, Richardson J, Dettmar PW, Corfe BM, Paxman JR. An ionic-gelling alginate drink attenuates postprandial glycaemia in males. J Funct Foods 2012; 4: 122–128. 32 Paxman JR, Richardson JC, Dettmar PW, Corfe BM. Alginate reduces the increased uptake of cholesterol and glucose in overweight male subjects: a pilot study. Nutr Res 2008; 28: 501–505. 33 Akhavan T, Luhovyy BL, Brown PH, Panahi S, Anderson GH. Mechanism of whey protein control of post-meal glycemia. Can J Diabetes 2011; 25: 36–43. Supplemental Issue (Abstract #190). 34 Beebe CA, Van Cauter E, Shapiro ET, Tillil H, Lyons R, Rubenstein AH et al. Effect of temporal distribution of calories on diurnal patterns of glucose levels and insulin secretion in NIDDM. Diabetes Care 1990; 13: 748–755. 35 Kimura Y, Watanabe K, Okuda H. Effects of soluble sodium alginate on cholesterol excretion and glucose tolerance in rats. J Ethnopharmacol 1996; 54: 47–54. 36 Peters HP, Koppert RJ, Boers HM, Strom A, Melnikov SM, Haddeman E et al. Dose-dependent suppression of hunger by a specific alginate in a low-viscosity drink formulation. Obesity (Silver Spring) 2011; 19: 1171–1176. 37 Almiron-Roig E, Grathwohl D, Green H, Erkner A. Impact of some isoenergetic snacks on satiety and next meal intake in healthy adults. J Hum Nutr Diet 2009; 22: 469–474. 38 Rolls BJ, Kim S, McNelis AL, Fischman MW, Foltin RW, Moran TH. Time course of effects of preloads high in fat or carbohydrate on food intake and hunger ratings in humans. Am J Physiol 1991; 260: R756–R763. 39 Suchkov VV, Grinberg VY, Muschiolik H, Schmandke H, Tolstoguzov VB. Mechanical and functional properties of anisotropic geleous fibers obtained from the two-phase system of water-casein-sodium alginate. Die Nahrung 1988; 32: 661–668. 40 Horowitz M, Dent J, Fraser R, Sun W, Hebbard G. Role and integration of mechanisms controlling gastric emptying. Dig Dis Sci 1994; 39: 7S–13S. 41 Mattes RD, Rothacker D. Beverage viscosity is inversely related to postprandial hunger in humans. Physiol Behav 2001; 74: 551–557. 42 Zijlstra N, Mars M, de Wijk RA, Westerterp-Plantenga MS, de Graaf C. The effect of viscosity on ad libitum food intake. Int J Obes (Lond) 2008; 32: 676–683. 43 Hollowood TA, Linforth RS, Taylor AJ. The effect of viscosity on the perception of flavour. Chem Senses 2002; 27: 583–591. 44 Hetherington M, Rolls BJ, Burley VJ. The time course of sensory-specific satiety. Appetite 1989; 12: 57–68. 45 Abou-Samra R, Keersmaekers L, Brienza D, Mukherjee R, Macé K. Effect of different protein sources on satiation and short-term satiety when consumed as a starter. Nutr J 2011; 10: 139. 46 Fallaize R, Wilson L, Gray J, Morgan LM, Griffin BA. Variation in the effects of three different breakfast meals on subjective satiety and subsequent intake of energy at lunch and evening meal. Eur J Nutr 2013; 52: 1353–1359. 47 Panahi S, El Khoury D, Luhovyy BL, Goff HD, Anderson GH. Caloric beverages consumed freely at meal-time add calories to an ad libitum meal. Appetite 2013; 65: 75–82. 48 Sebastian RS, Goldman JD, Enns CW, LaComb RP Fluid milk consumption in the United States: What We Eat in America, NHANES 2005-2006. In: Food Surveys Research Group The US Department of Agriculture: Beltsville, MD, USA, 2010.

© 2014 Macmillan Publishers Limited