Comparison of aspartame- and sugar-sweetened soft drinks on postprandial metabolism

Abstract

Aim: We compared the impact of artificially- and sugar-sweetened beverages co-ingested with a mixed meal on postprandial fat and carbohydrate oxidation, blood glucose, and plasma insulin and triglyceride concentrations. Methods: Eight college-aged, healthy males completed three randomly assigned trials, which consisted of a mixed macronutrient meal test with 20oz of Diet-Coke (AS), Coca-Cola (NS), or water (CON). One week separated each trial and each participant served as his own control. Resting energy expenditure (REE) via indirect calorimetry, blood pressure, and blood samples were obtained immediately before, 5, 10, 30, 60, 120, and 180 min after meal and beverage ingestion. A two-way (treatment × time) repeated-measures ANOVA was conducted to assess REE, fat and carbohydrate oxidation rates, blood glucose, and plasma insulin and triglyceride concentrations. Results: There was a significant main effect of treatment on total fat oxidation (P = 0.006), fat oxidation was significantly higher after AS (P = 0.006) and CON (P = 0.001) compared to following NS. There was a significant main effect of treatment on total carbohydrate oxidation (P = 0.005), carbohydrate oxidation was significantly lower after AS (P = 0.014) and CON (P = 0.001) compared to following NS. Plasma insulin concentration AUC was significantly lower after AS (P = 0.019) and trended lower in CON (P = 0.054) compared to following NS. Conclusion: Ingestion of a mixed meal with an artificially-sweetened beverage does not impact postprandial metabolism, whereas a sugar-sweetened beverage suppresses fat oxidation and increases carbohydrate oxidation compared to artificially-sweetened beverage and water.

Keywords

non-nutritive sweetener artificial sweetener postprandial fat oxidation

1. Introduction

Increased Weight status amplifies the risk of cardiometabolic disease (Roth et al., 2004). One potential source of added weight gain is the increasing consumption of added sugars over the past decades. Americans are consuming on average 83% over the recommended limit, leading to roughly an added 366 calories per day (Bentley, 2017), much of which comes from sugar-sweetened beverages (An, 2016). The consumption of added sugars influences the glycemic load of an individual's diet putting them at risk of developing type-2 diabetes (Willett et al., 2002), obesity (Anton et al., 2010; Raben et al., 2002), and dyslipidemia (Le et al., 2009; Rippe and Angelopoulos, 2016) ultimately resulting in pathologic changes in metabolism and vascular function.

To encourage a weight loss, the substitution of artificial sweeteners (AS) into the diet as a replacement of sugar has been suggested (Mattes and Popkin, 2009). The introduction of AS into a diet has been shown to reduce intra-hepatocellular lipid concentrations (Campos et al., 2015), promote weight loss (Blackburn et al., 1997; Raben et al., 2002; Tate et al., 2012; Tordoff and Alleva, 1990), and to have minimal influences on postprandial glucose and insulin when compared to a nutritive sweetener (NS) (Anton et al., 2010; Carlson and Shah, 1989; Tey et al., 2017). Aspartame, specifically, has not been shown to affect energy expenditure (Mattes and Popkin, 2009), but advantageous effects are due to a reduction in caloric intake (Prat-Larquemin et al., 2000). These data have resulted in the increased use of AS for weight loss and maintenance (Mattes and Popkin, 2009).

While there have been substantial claims for AS use for weight loss, the health effects of sugar replacement with AS are controversial (Gardner et al., 2012; Hedrick et al., 2017). Epidemiological studies have shown AS usage to be linked with an increased risk of long-term obesity (Dhingra et al., 2007; Fowler et al., 2008), cardiovascular disease (Fowler et al., 2015; Nettleton et al., 2009), greater glucose intolerance (Kuk and Brown, 2016), and type-2 diabetes (Nettleton et al., 2009). The interpretation of these studies is limited due to dietary intake tools mainly focusing on AS beverages and do not necessarily specify type or beverage brand of diet sodas (Fowler et al., 2008; Fowler et al., 2015; Gardner et al., 2012), allowing for underestimates of consumption (Dhingra et al., 2007).

One proposed mechanism that may be responsible for AS causing weight gain is the role of the cephalic phase insulin response (CPIR). The CPIR is a neurally-mediated spike in insulin that heads a postprandial glycemic response (Teff et al., 1991). Saccharin has been identified to elicit a CPIR resulting in a rapid rise of insulin (Just et al., 2008), similar to that caused by NS ingestion (Dušková et al., 2013; Härtel et al., 1993). While aspartame has not been associated with a CPIR (Dušková et al., 2013), it does trigger pancreatic β-cell intracellular signaling (Nakagawa et al., 2013) consistent with potential downstream effects evoked by other AS (Dhillon et al., 2017) and sucrose (Anton et al., 2010). While some AS may moderate postprandial glycemia (Woods et al., 2000), none have been shown to exacerbate the response relative to NS (Anton et al., 2010; Bryant et al., 2014; Madjd et al., 2017; Tey et al., 2017). The magnitude of a CPIR is influenced by food palatability (LeBlanc et al., 1991; Lucas et al., 1987), emphasizing the need for assessing hunger and satiety levels.

Excess NS consumption promotes metabolic disorders via direct and indirect mechanisms resulting in dysregulation of fat and carbohydrate metabolism (Stanhope, 2016). Directly, fructose consumption has been found to increase de novo lipogenesis and dyslipidemia, and decreased fat oxidation and insulin sensitivity (Cox et al., 2012; Stanhope et al., 2009). Honey, sucrose and fructose were all found to increase triglyceride (TG) concentration in healthy participants (Raatz et al., 2015). Additionally, the liquid form of NS intake is more important for insulin resistance than sugar type (Sadowska and Bruszkowska, 2019). Indirectly, excess NS consumption in absence of matching physical activity can lead to a positive energy balance resulting in weight gain (Hill and Commerford, 1996). Due to the irregularity among studies examining different AS, and between observational and experimental studies, there is a need for controlled studies evaluating differences between AS and NS effects on postprandial metabolism.

In the present study, we compared the impact of AS- and NS-sweetened beverages co-ingested with a mixed meal on postprandial fat and carbohydrate oxidation. Furthermore, we measured whole blood concentrations of glucose, and plasma insulin and TG concentrations to determine if an AS beverage via aspartame affects CPIR, postprandial glycemia or lipemia. We hypothesized the metabolic response to a mixed meal containing an AS beverage would be similar to that of one containing water and would be favorable compared to a mixed meal containing a NS-sweetened beverage.

2. Methods

2.1. Ethical Approval

The study was approved by University of Georgia Institutional Review Board (study no. 254) with written informed consent being obtained prior to any experimental procedures. The study conformed to the standards set by the Declaration of Helsinki, except for registration in a database.

2.2. Participant Characteristics

Eight healthy, non-smoking, recreationally active (cardiovascular exercise ≥150 min week⁻¹ and resistance exercise ≥2 h week⁻¹) male participants were recruited (age 22 ± 1.79 years, height 176.85 ± 5.96 cm, weight 82.40 ± 6.20 kg, and body fat percentage 21.56 ± 7.80%). Participants were free of any history of cardiovascular, metabolic or musculoskeletal disease, or of illness requiring the ingestion of medications that affect metabolism.

2.3. Design

A repeated-measures study design was used in which each participant served as his own control. Participants completed three randomly assigned trials, which consisted of a mixed meal test with 20oz of Coca-Cola (NS), Diet-Coke (AS), or water (CON). One week separated each trial. Participants refrained from exercise and alcohol ingestion for 48 h before each trial and did not consume caffeine for 12 h before each trial.

2.4. Baseline Measurements

On the first visit, participants’ height, weight, and body composition (via duel-energy X-ray absorptiometry, Horizon DXA System, Hologic, Inc., Marlborough, MA, USA) were measured. After anthropometric measurements were taken, participants completed a non-nutritive sweetener specific food frequency questionnaire (Myers et al., 2018).

2.5. Trial Protocol

On the day of each trial, participants were instructed to consume a pre-trial meal, consisting of 25% predicted resting energy expenditure (50% carbohydrate, 30% fat, and 20% protein) (Mifflin et al., 1990). Participants were given guidance on food selection to meet the prescribed energy content and macronutrient composition for this meal, as well as instructed to take a picture of the meal for reference for other trial days. The pre-trial meal was consumed at ∼08.00 h, four hours prior to each trial. After pre-trial meal consumption, participants were instructed to only consume clear water prior to arrive to the laboratory. At ∼12.00 h, participants arrived at the laboratory, and confirmed consuming the recommended meal and abstaining for exercise, alcohol, and caffeine for the recommended time. See Supplemental Figure 1 for an overview of experimental procedures conducted during each trial. Briefly, blood pressure (Omron Healthcare Inc., model: HEM-712C, Bannockburn, IL, USA) and blood samples were collected at baseline, 5, 10, 30, 60, 120, and 180 min postprandial. Resting energy expenditure (REE) was measured at baseline, 10, 60, 120, and 180 min postprandial.

2.6. Mixed Macronutrient meal test

After initial weighing, an intravenous catheter was placed in the antecubital region and flushed to maintain patency. After, participants rested in a supine position on a bed while the participants’ REE was measured using indirect calorimetry. Participants then ingested a mixed macronutrient test meal consisting of 0.8 g carbohydrate, 0.4 g fat and 0.3 g protein per kg of fat free mass (∼40% carbohydrate, ∼45% fat and ∼15% protein). The test meal consisted of 57 g Ensure (Original Milk Chocolate Nutrition Shake, Abbott Laboratories, Columbus, OH, USA), 45 mL of heavy whipping cream, and ZonePerfect Nutrition Bar (Abbott Laboratories, Chicago, IL, USA). The amount of ZonePerfect Nutrition Bar was individualized for each participant to achieve the prescribed macronutrient profile. With this meal, participants drank either 20oz of Coca-Cola (NS), Diet-Coke (AS) or water (CON), equating to 240, 0, and 0 kcals respectively. Participants were allowed a maximum of 10 min to consume the test meal including the experimental beverage. Each test beverage was delivered via a black unlabeled container, as to not allow for participants to visually recognize what beverage they were consuming, in a single-blind fashion. Participants rested in the supine position throughout the 3 h postprandial period, only getting up to use the restroom at the 30 min postprandial timepoint. All participants were walked to and from the restroom at the 30 min postprandial timepoint.

2.7. REE Measurements

Each REE (kcal day⁻¹) measurement was recorded for 20 min with a metabolic cart (TrueOne 2400, Parvo Medics, Sandy, UT, USA). Participants were instructed to remain motionless without sleeping in a supine position while a plastic hood was placed over their head to measure respiratory gases. Twenty minutes of respiratory gases were collected, but only the final 15 min of data was used to calculate REE using the Weir equation (Weir, 1949) and macronutrient oxidation using equations developed by Frayn (Frayn, 1983): fat (g min⁻¹) = [1.67 × VO₂ (l min⁻¹)] – [1.67 × VCO₂ (l min⁻¹)], and carbohydrate (g min⁻¹) = [4.55 × VCO₂ (l min⁻¹)] – [3.21 × VO₂ (l min⁻¹)]. The first 5 min of each 20 min test was discarded to ensure analysis of steady state metabolic data.

2.8. Hunger And satiety questionnaires

Immediately following meal consumption, participants completed a visual analog scale (VAS) to assess hunger, thirst, nausea, and desire to eat (Flint et al., 2000). Additionally, participants completed a sensory evaluation form to assess appearance, flavor, texture, aroma, and overall acceptability of the test meal (Peryam and Pilgrim, 1957).

2.9. Blood Sample analysis

For each blood sample, 6 ml of blood was collected from an antecubital vein via intravenous catheter into an EDTA vacutainer (Becton, Dickinson and Company, Franklin Lakes, NJ, USA). One drop (∼0.05 ml) of whole blood was used to measure blood glucose levels. The tubes were then centrifuged at 3000 g for 15 min at 4 C. Plasma was separated, divided into aliquots and stored at −80 C until analyzed for insulin and TG concentrations. Samples were frozen within 45 min of collection.

Glucose was measured using a handheld glucometer (OneTouch UltraMini, LifeScan, Inc., Milpitas, CA, USA). Blood samples were only available for insulin and TG assays from five study participants due to technical errors with placing the intravenous catheter during one or more visits. ELISA sandwich assays were used to measure plasma insulin (Insulin ELISA Kit, Crystal Chem, Inc., Elk Grove Village, IL, USA). The inter-assay coefficient of variation was 5.94% with an intra-assay coefficient of variation 7.82% for insulin samples. Identification of a CPIR was assessed by an increase of 25% above baseline corresponding to a minimum increase of 2 mU/L at 5 min postprandial (Teff, 2000; Teff, 2011). Enzymatic, colorimetric assays were used to measure plasma triglycerides (Wako L-Type TG-M assay, Wako Chemicals USA, Richmond, VA, USA). The inter-assay coefficient of variation was 10.64% with an intra-assay coefficient of variation 4.42% for TG samples.

2.10. Dietary Analysis

Participants were instructed to consume similar foods during the entire study enrollment period, with food choices being similar to their normal dietary habits. One-week dietary records were collected at the beginning of the enrollment period and assessed using the United States Department of Agriculture National Nutrient Database for Standard Reference (https://fdc.nal.usda.gov) to ensure that quantity of macronutrients and total energy consumed by each participant did not vary significantly between study visits. Before the mixed meal tests, participants were asked to confirm they ate the recommended pre-appointment meal and had only consumed clear water between the meal and trial.

2.11. Statistical Analyses

A two-way (treatment × time) repeated-measures ANOVA was conducted to assess the statistical significance of the effects of the trials (NS, AS, and CON) on REE, fat and carbohydrate oxidation rates, whole blood glucose, and plasma insulin and TG concentrations. Total areas under postprandial fat and carbohydrate oxidation curves were calculated using the trapezoid rule (Matthews et al., 1990). One-way ANOVA was used to compare calculations of total fat and carbohydrate oxidized, total fat and carbohydrate oxidation AUC, total postprandial fat and carbohydrate oxidized, and incidence of a CPIR among trials. Assumptions of normality were verified for all outcome measures. Plasma insulin and TG concentration data did not meet the assumption of sphericity; these variables were log-transformed for analysis. Statistical significance was accepted at P ≤ 0.05. Data are presented as means ± SD. All statistical analyses were performed with SPSS Statistics version 26.0 (IBM Corp., Armonk, NY, USA).

3. Results

3.1. Dietary Analysis

Participants reported consuming an average of 2010.02 ± 240.77 kcals/day, consisting of 48.8 ± 2.9% carbohydrate, 32.03 ± 2.7% fat, and 20.1 ± 1.5% protein. Additionally, participants reported an average consumption of 0 g/day of erythritol, 27.30 ± 9.13 mg/day of acesulfame potassium, 51.15 ± 17.22 mg/day of aspartame, 0 mg/day of saccharin, and 13.58 ± 4.41 mg/day of sucralose. All participants had no significant changes in body weight between trials (NS: 82.7 ± 2.4 kg, AS: 82.9 ± 2.5, and CON: 82.6 ± 2.5, P > 0.05). Therefore, all participant's data were retained in the final analysis.

3.2. Substrate Oxidation

There was a significant condition main effect of fat oxidation F(2,6) = 14.185, P = 0.005, η_p² = 0.825. There was not a significant time main effect of fat oxidation F(4,4) = 4.129, P = 0.099, η_p² = 0.805. Fat oxidation was significantly higher in CON compared to AS at 10 min postprandial (P = 0.002). Fat oxidation was significantly higher in CON compared to NS at 10 min (P < 0.001), 60 min (P = 0.011), 120 min (P = 0.004), and 180 min postprandial (P = 0.036). Fat oxidation was significantly higher in AS compared to NS at 10 min (P = 0.003), 120 min (P = 0.005), 180 min postprandial (P = 0.005), Figure 1(a). There was a significant main effect of total fat oxidized F(2,6) = 13.372, P = 0.006, η_p² = 0.817. Total fat oxidized was significantly higher in CON and AS compared to NS (P = 0.001 and P = 0.006, respectively), Figure 1(b). There was a significant main effect for total fat oxidation AUC F(2,6) = 14.680, P = 0.005, η_p² = 0.830. Total fat oxidation AUC was significantly higher in CON and AS compared to NS (P = 0.001 and P = 0.004, respectively), Figure 1(c). There was a significant main effect for total postprandial fat oxidation AUC F(2,6) = 15.021, P = 0.005, η_p² = 0.834. Total postprandial fat oxidized was significantly higher in CON and AS compared to NS (P = 0.001 and P = 0.003, respectively), Figure 1(d).

There was a significant condition main effect of carbohydrate oxidation F(2,6) = 15.747, P = 0.004, η_p² = 0.840. There was a significant time main effect of carbohydrate oxidation F(4,4) = 7.259, P = 0.040, η_p² = 0.879. Carbohydrate oxidation was significantly lower in CON compared to AS at 10 min postprandial (P = 0.001). Carbohydrate oxidation was significantly lower in CON compared to NS at 10 min (P < 0.001), 60 min (P = 0.005), 120 min (P = 0.003), and 180 min postprandial (P = 0.045). Carbohydrate oxidation was significantly lower in AS compared to NS at 10 min (P = 0.008), 120 min (P = 0.012), and 180 min postprandial (P = 0.020), Figure 2(a). There was a significant main effect of total carbohydrate oxidized F(2,6) = 15.038, P = 0.005, η_p² = 0.834. Total carbohydrate oxidized was significantly lower in CON and AS compared to NS (P = 0.001 and P = 0.014, respectively), Figure 2(b). There was a significant main effect of total carbohydrate oxidation AUC F(2,6) = 17.238, P = 0.003, η_p² = 0.852. Total carbohydrate oxidation AUC was significantly lower in CON and AS compared to NS (P < 0.001 and P = 0.010, respectively), Figure 2(c). There was a significant main effect of total postprandial carbohydrate oxidized F(2,6) = 17.519, P = 0.003, η_p² = 0.854. Total postprandial carbohydrate oxidized was significantly lower in CON and AS compared to NS (P < 0.001 and P = 0.008, respectively), Figure 2(d).

There was a condition main effect on REE that approached statistical significance F(2,6) = 5.054, P = 0.052, η_p² = 0.627. There was a significant time main effect of REE F(4,4) = 17.772, P = 0.008, η_p² = 0.947. REE was significantly lower in CON compared to AS at 10 min (P = 0.037) and 60 min postprandial (P = 0.007). REE was significantly lower in CON compared to NS at 10 min (P = 0.025), 60 min (P = 0.008), and 120 min postprandial (P = 0.027), Figure 3(a). There was a condition main effect on total energy expended that approached statistical significance F(2,6) = 4.495, P = 0.064, η_p² = 0.600. Total energy expended was significantly lower in CON compared to AS and NS (P = 0.026 and P = 0.036, respectively), Figure 3(b).

3.3. Blood Sample analysis

There was not a significant condition main effect of blood glucose F(2,6) = 1.035, P = 0.411, η_p² = 0.257. There was not a significant time main effect of blood glucose F(6,2) = 4.372, P = 0.198, η_p² = 0.929. Blood glucose concentration was significantly lower in CON compared to AS at 10 min postprandial (P = 0.032) and trended lower in CON compared to NS at 10 min postprandial (P = 0.057), Figure 4(a). There was not a significant main effect of blood glucose AUC F(2,6) = 0.400, P = 0.687, η_p² = 0.118. There was not a significant condition main effect of change in plasma insulin F(2,3) = 3.528, P = 0.163, η_p² = 0.702. Plasma insulin concentration was significantly lower in AS compared to NS at 30 and 120 min postprandial (P = 0.019 and P = 0.031, respectively), Figure 5(a). There was not a significant condition main effect of plasma insulin AUC F(2,3) = 6.101, P = 0.088, η_p² = 0.803. Plasma insulin concentration AUC was significantly lower in AS (P = 0.019) and trended lower in CON (P = 0.054) compared to the NS trial, Figure 5(b). There was not a significant condition main effect of frequency of a CPIR F(1,4) = 2.667, P = 0.178, η_p² = 0.400. No significant differences were found among trials for the frequency of a CPIR, Figure 5(c). There was not a significant condition main effect of change in plasma TG concentration F(2,3) = 0.845, P = 0.512, η_p² = 0.360. Plasma TG concentration was significantly lower in CON compared to NS at 180 min postprandial (P = 0.032), Figure 6(a). There was not a significant condition main effect of plasma TG AUC F(2,3) = 0.680, P = 0.571, η_p² = 0.312. Absolute concentrations for blood glucose, plasma insulin and TG are represented in Table 1.

Table 1.

Baseline and postprandial blood glucose, and plasma insulin and triglyceride concentration response to each condition.

Condition	Time (min)	Glucose (mg/dL)	Insulin (mU/L)	Triglyceride (mg/dL)
Condition	Time (min)	n = 8	n = 5	n = 5
Control	0	101.38 ± 10.86	2.83 ± 1.31	114.22 ± 122.95
	5	107.50 ± 8.93	3.37 ± 1.56	99.53 ± 108.24
	10	113.38 ± 11.54^a†	11.48 ± 11.29	97.38 ± 108.02
	30	122.25 ± 19.75	30.50 ± 11.93	115.31 ± 102.19
	60	98.25 ± 14.12	17.27 ± 15.07	135.04 ± 117.99
	120	106.38 ± 9.18	9.17 ± 6.16	121.42 ± 108.90
	180	102.63 ± 5.26	2.84 ± 1.56	113.22 ± 113.01 ^b
Artificial Sweetener	0	106.38 ± 8.57	2.85 ± 2.05	72.68 ± 60.88
	5	110.00 ± 16.16	9.40 ± 8.67	74.37 ± 67.33
	10	119.75 ± 12.42 ^a	19.19 ± 11.38	75.91 ± 75.93
	30	124.38 ± 22.33	30.22 ± 13.37 ^c	87.13 ± 60.38
	60	96.75 ± 14.11	12.11 ± 6.35	101.29 ± 85.09
	120	106.50 ± 11.45	8.32 ± 9.22	113.64 ± 115.17
	180	105.88 ± 7.14	2.90 ± 1.59 ^c	112.80 ± 119.55
Nutritive Sweetener	0	102.38 ± 8.02	3.03 ± 1.46	85.90 ± 72.06
	5	114.75 ± 9.42	10.05 ± 8.64	85.44 ± 76.17
	10	118.88 ± 9.85 ^†	16.69 ± 11.72	82.73 ± 76.27
	30	135.50 ± 24.76	39.73 ± 17.03 ^c	96.66 ± 72.98
	60	99.38 ± 17.66	28.01 ± 21.88	109.13 ± 82.96
	120	103.38 ± 16.29	15.60 ± 16.81	110.14 ± 83.23
	180	102.63 ± 8.43	6.90 ± 10.04 ^c	131.42 ± 114.53 ^b

Note: Baseline and postprandial blood glucose response to each condition (ANOVA; condition: P = 0.411, η_p² = 0.257, time: P = 0.198, η_p² = 0.929, n = 8). Baseline and postprandial plasma insulin response to each condition (ANOVA; condition: P = 0.163, η_p² = 0.702, n = 5). Baseline and postprandial plasma triglyceride response to each condition (ANOVA; condition: P = 0.512, η_p² = 0.360, n = 5). a = significant difference between CON and AS, b = significant difference between CON and NS, c = significant difference between AS and NS, and † = approached significant difference between CON and NS.

3.4. Blood Pressure

There was not a significant condition main effect of systolic blood pressure F(2,6) = 3.759, P = 0.087, η_p² = 0.556. There was a significant time main effect of systolic blood pressure F(6,2) = 67.690, P = 0.015, η_p² = 0.995. Systolic blood pressure trended lower in CON compared to AS at 5 and 10 min postprandial (P = 0.055 and P = 0.064, respectively), and was significantly lower in CON compared to AS at 30 min postprandial (P = 0.006), Table 2. There was not a significant condition main effect of diastolic blood pressure F(2,6) = 1.607, P = 0.276, η_p² = 0.349. There was not a significant time main effect of diastolic blood pressure F(6,2) = 13.196, P = 0.072, η_p² = 0.975. Diastolic blood pressure was significantly higher in AS compared to CON and NS at 30 min postprandial (P = 0.014 and P = 0.035, respectively), and significantly higher in AS compared to NS at 120 min postprandial (P = 0.018), Table 2.

Table 2.
Baseline and postprandial blood pressure response to each condition.

Condition Time (min) SystolicBlood Pressure DiastolicBlood Pressure

Control 0 130.75 ± 15.68 68.88 ± 14.35

5 121.13 ± 15.62 ^† 61.75 ± 10.61

10 119.13 ± 16.37 ^† 61.00 ± 6.89

30 119.38 ± 14.25 ^a 58.13 ± 6.40 ^a

60 126.75 ± 12.80 59.00 ± 10.28

120 123.50 ± 10.99 62.13 ± 8.25

180 126.00 ± 15.58 66.00 ± 7.23

Artificial Sweetener 0 132.50 ± 12.78 64.00 ± 7.84

5 126.13 ± 15.08 ^† 66.00 ± 7.35

10 126.25 ± 15.09 ^† 63.75 ± 8.40

30 128.38 ± 16.32 ^a 65.00 ± 8.64 ^a ^c

60 128.50 ± 6.05 65.38 ± 8.03

120 126.75 ± 9.22 65.88 ± 6.40 ^c

180 129.38 ± 8.96 68.88 ± 6.27

Nutritive Sweetener 0 126.13 ± 19.73 66.75 ± 10.24

5 123.00 ± 11.80 65.13 ± 9.26

10 122.75 ± 11.68 62.63 ± 6.99

30 123.88 ± 12.77 60.63 ± 7.80 ^c

60 127.63 ± 15.79 64.00 ± 7.41

120 125.38 ± 12.12 61.50 ± 5.63 ^c

180 125.25 ± 12.10 70.25 ± 5.82

Condition	Time (min)	SystolicBlood Pressure	DiastolicBlood Pressure
Control	0	130.75 ± 15.68	68.88 ± 14.35
5	121.13 ± 15.62 ^†	61.75 ± 10.61
10	119.13 ± 16.37 ^†	61.00 ± 6.89
30	119.38 ± 14.25 ^a	58.13 ± 6.40 ^a
60	126.75 ± 12.80	59.00 ± 10.28
120	123.50 ± 10.99	62.13 ± 8.25
180	126.00 ± 15.58	66.00 ± 7.23
Artificial Sweetener	0	132.50 ± 12.78	64.00 ± 7.84
5	126.13 ± 15.08 ^†	66.00 ± 7.35
10	126.25 ± 15.09 ^†	63.75 ± 8.40
30	128.38 ± 16.32 ^a	65.00 ± 8.64 ^a ^c
60	128.50 ± 6.05	65.38 ± 8.03
120	126.75 ± 9.22	65.88 ± 6.40 ^c
180	129.38 ± 8.96	68.88 ± 6.27
Nutritive Sweetener	0	126.13 ± 19.73	66.75 ± 10.24
5	123.00 ± 11.80	65.13 ± 9.26
10	122.75 ± 11.68	62.63 ± 6.99
30	123.88 ± 12.77	60.63 ± 7.80 ^c
60	127.63 ± 15.79	64.00 ± 7.41
120	125.38 ± 12.12	61.50 ± 5.63 ^c
180	125.25 ± 12.10	70.25 ± 5.82

Note: Baseline and postprandial systolic blood pressure response to each condition (ANOVA; condition: P = 0.087, η_p² = 0.556, time: P = 0.015, η_p² = 0.556, n = 8). Baseline and postprandial diastolic blood pressure response to each condition (ANOVA; condition: P = 0.276, η_p² = 0.349, time: P = 0.072, η_p² = 0.975, n = 8). a = significant difference between CON and AS, b = significant difference between CON and NS, c = significant difference between AS and NS, and † = approached significant difference between CON and AS.

3.5. VAS And sensory questionnaires

No differences were found among trials in any variable in both the VAS and sensory questionnaires (P > 0.05), Table 3.

Table 3.
VAS and sensory questionnaires.

Questionnaire Variable CON AS NS

VAS Hunger 45.25 ± 23.16 28.13 ± 24.58 26.25 ± 17.82

Thirst 27.63 ± 20.26 17.75 ± 14.69 15.25 ± 14.46

Fullness 46.88 ± 10.67 58.63 ± 21.38 53.88 ± 21.01

Nausea 1.63 ± 1.92 4.13 ± 4.64 11.25 ± 22.13

Amount you could eat 61.88 ± 20.84 49.13 ± 24.24 45.38 ± 32.63

Desire to eat 39.13 ± 25.67 34.63 ± 16.71 34.13 ± 21.80

Sensory Appearance 6.25 ± 1.49 6.25 ± 1.39 6.25 ± 1.67

Taste/ Flavor 7.13 ± 1.36 6.75 ± 1.04 6.75 1.28

Texture/ Consistency 7.13 ± 1.25 6.75 ± 1.04 6.88 ± 1.25

Aroma/ Smell 6.25 ± 1.39 6.25 ± 1.28 6.38 ± 1.41

Overall Acceptability 7.25 ± 0.89 7.75 ± 1.04 7.25 ± 0.89

Questionnaire	Variable	CON	AS	NS
VAS	Hunger	45.25 ± 23.16	28.13 ± 24.58	26.25 ± 17.82
Thirst	27.63 ± 20.26	17.75 ± 14.69	15.25 ± 14.46
Fullness	46.88 ± 10.67	58.63 ± 21.38	53.88 ± 21.01
Nausea	1.63 ± 1.92	4.13 ± 4.64	11.25 ± 22.13
Amount you could eat	61.88 ± 20.84	49.13 ± 24.24	45.38 ± 32.63
Desire to eat	39.13 ± 25.67	34.63 ± 16.71	34.13 ± 21.80
Sensory	Appearance	6.25 ± 1.49	6.25 ± 1.39	6.25 ± 1.67
Taste/ Flavor	7.13 ± 1.36	6.75 ± 1.04	6.75 1.28
Texture/ Consistency	7.13 ± 1.25	6.75 ± 1.04	6.88 ± 1.25
Aroma/ Smell	6.25 ± 1.39	6.25 ± 1.28	6.38 ± 1.41
Overall Acceptability	7.25 ± 0.89	7.75 ± 1.04	7.25 ± 0.89

Note: Hunger (ANOVA; condition: P = 0.257, η_p² = 0.364, n = 8), thirst (ANOVA; condition: P = 0.253, η_p² = 0.368, n = 8), fullness (ANOVA; condition: P = 0.328, η_p² = 0.310, n = 8), nausea (ANOVA; condition: P = 0.195, η_p² = 0.421, n = 8), amount you could eat (ANOVA; condition: P = 0.387, η_p² = 0.271, n = 8), and desire to eat (ANOVA; condition: P = 0.914, η_p² = 0.029, n = 8). Appearance (ANOVA; condition: P = 1.000, η_p² < 0.001, n = 8), taste/flavor (ANOVA; condition: P = 0.591, η_p² = 0.161, n = 8), texture/ consistency (ANOVA; condition: P = 0.261, η_p² = 0.361, n = 8), aroma/smell (ANOVA; condition: P = 0.947, η_p² = 0.018, n = 8), and overall acceptability (ANOVA; condition: P = 0.171, η_p² = 0.444, n = 8).

4. Discussion

In The current study, we compared the effects of mixed meal test containing an AS beverage via aspartame (20 oz of Diet Coke) with that containing a NS beverage (20 oz of Coca-Cola) on postprandial substrate oxidation, blood glucose, plasma insulin and TG concentrations, blood pressure, and sensory response. The major finding of this study is that that NS suppressed fat oxidation and augmented carbohydrate oxidation compared to AS and CON (water), while AS elicited a similar increase in postprandial energy expenditure to NS despite containing a lower overall caloric load. Blood glucose and plasma insulin and TG concentrations were elevated at select time points in the NS trial compared to AS and CON trials. These metabolic effects of AS were observed concomitantly with an attenuated decline in blood pressure observed with the NS and CON trials. Overall, these data suggest that co-ingestion of an AS beverage with a mixed meal does not negatively impact postprandial fat oxidation when compared to a NS beverage. Moreover, our findings indicate that the AS beverages exert positive effects on postprandial energy expenditure and insulin concentrations. The possible hemodynamic effects of AS warrant further attention.

We hypothesized that postprandial fat oxidation would be similar between AS and CON trials while different when compared to the NS trial. Our data generally support this hypothesis with the exception of the separation among all three trials at the 10 min postprandial time point. A 10-week interventional study assessed 24 h substrate oxidation after participants to consume a diet containing either sucrose-sweetened or AS foods (Sorensen et al., 2014). After the completion of the intervention the AS group had higher rates of fat oxidation throughout the 24 h testing period (Sorensen et al., 2014). Our study extends upon this previous research by demonstrating an acute suppressive effect of NS on postprandial fat oxidation. Furthermore, we report a reduction in total fat and total postprandial fat oxidized in the NS trial compared to both AS and CON trials. These findings represent a collective suppression in fat oxidation during the NS trial.

However, carbohydrate oxidation was elevated during the NS trial when compared to AS and CON trials. These differences were anticipated due to added carbohydrate substrate in the NS trial and the reciprocal relationship between fat and carbohydrate oxidation (Hue and Taegtmeyer, 2009). Higher carbohydrate oxidation has been associated with sucrose ingestion, when compared to a sucralose-sweetened condition (Chern and Tan, 2019). Our findings bring new light into how a mixed meal containing an AS beverage via aspartame affects postprandial carbohydrate oxidation. Surprisingly, we found carbohydrate oxidation was elevated at 10 min postprandial in the AS trial when compared to the CON trial. We speculate this difference is associated with the increase in blood glucose 5 min postprandial in the AS trial. However, this initial increase in carbohydrate oxidation in the AS trial did not affect the collective oxidation. This is indicated by the lack of differences in total carbohydrate and total postprandial carbohydrate oxidized between AS and CON trials. We conclude that while a mixed meal containing a NS beverage upregulates carbohydrate oxidation, whereas an AS beverage has little to no effect compared to the CON trial.

Postprandial energy expenditure is dependent on the macronutrient and caloric content of the meal stimulus provided, and reflects the metabolic costs of digesting of the foods ingested, e.g. food breakdown, nutrient uptake, and assimilation (Westerterp, 2004). Surprisingly, our results indicate an elevated postprandial energy expenditure in NS and AS trials, when compared to the CON trial. The large effect sizes associated with these differences suggest possible clinical relevance but should be interpreted with caution due to the small sample size. This finding is in contrast with previous findings of a similarly designed study. Prat-Larquemin et al., recruited healthy males to consume three test lunches in a randomized fashion after a controlled breakfast meal. While there were no differences in postprandial energy expenditure between the meal containing aspartame and non-sweetened control, the meal containing sucrose elicited a higher postprandial energy expenditure (Prat-Larquemin et al., 2000). In the current study, both experimental trials contained caffeine. While the AS trial contained slightly more caffeine than the NS trial (76 and 57 mg respectively), it seems unlikely that the small amount of caffeine in the beverages could explain the differences in energy expenditure between trials. Based on established metabolic effects of caffeine ingestion (Dulloo et al., 1989), we estimate an approximant energy expenditure increases of 34–45 and 45–60 kcal evoked by NS and AS, respectively, from the caffeine content within each beverage. Therefore, the differences between NS and AS trials when compared to the CON trial cannot solely be explained by the inclusion of caffeine within these trials. We speculate the rise in postprandial energy expenditure is mechanistically linked with the increased carbohydrate oxidation during the AS trial, although this warrants further investigation.

While the effects of AS on glycemic control have been of much debate, multiple systematic reviews have found neutral effects of AS on glucose control (Gardner, 2014; Lohner et al., 2017; Onakpoya and Heneghan, 2015; Romo-Romo et al., 2016). A recent review on epidemiological, human intervention, and animal studies on the effects of AS on glycemic control concluded that AS intake does not influence postprandial glucose responses (Kim et al., 2019). In the current study, we found a difference between AS and CON and a trending difference between NS and CON trials at 10 min postprandial with no additional differences between trials. Our results do not concur with previous reported effects of aspartame on glucose homeostasis and lead us to reject our hypothesis. We speculate our participants were insulin sensitive enough that the meal challenge did not deliver a large enough glycemic load to cause measurable intertrial disruption in blood glucose. The rise in carbohydrate oxidation coupled with similar insulin response, lead us to believe these participants were able to rapidly clear blood glucose leading to small disturbances. Additionally, the large variation within timepoints affected our ability to detect differences between trials. Therefore, based on our current data, we cannot give a conclusive verdict to if aspartame affects postprandial glycemic control.

In the present study, we assessed plasma insulin concentrations at cephalic (5 and 10 min postprandial) and subsequent postprandial timepoints to include the frequency of a CPIR among trials. With no differences found at the 5 and 10 min postprandial time points and no differences found among the frequency of CPIR, we conclude that the cephalic response between all three trials were similar. These results concur with the examination of sucralose, stevia, and aspartame (Anton et al., 2010; Dhillon et al., 2017). Additionally, insulin AUC was significantly higher in the NS trial compared to AS and trended higher compared to the CON trial. Interestingly, 60% of participants experienced a CPIR after the consumption of the AS and NS trials, compared to 20% after the CON trial (P > 0.05). A recent systematic review found that 41% of meal tests triggered a CPIR within 10 min of the food cue with only 22% of all meal tests reporting statistically significant differences between conditions (Lasschuijt et al., 2020). Inconsistent triggering of a CPIR coupled with the inability to distinguish CPIR from pulsatile insulin fluctuations have led to the theory that, in healthy adults, CPIR is not physiologically relevant (Lasschuijt et al., 2020). Additionally, the CPIR only accounts for a very small percentage of total postprandial AUC after a mixed meal test (Ahren and Holst, 2001). Our current study supports this argument by detecting statistical differences among AUC but not frequency of incidence. Increased sugar, mainly from fructose, in the NS trial elicited a greater insulin response. Chronic consumption of NS beverages can lead to reduced insulin sensitivity and ultimately the development of type-2 diabetes (Ma et al., 2016). Due to the lack of significance between AS and CON trials, we conclude that consumption of AS beverages does not elicit the same metabolic risk as NS beverages. These findings warrant the further examination of how AS beverages via aspartame might influence the cephalic response in metabolically compromised individuals.

Increased TG concentrations after consumption of a meal are associated with increased risk cardiometabolic disease (Hyson et al., 2003). In the present study, we found a significantly higher TG concentration in the NS trial comparted to the CON trial at 180 min postprandial. Coca-Cola is ∼64–65% fructose (Ventura et al., 2011). In the current study this equates to ∼42 g of fructose being ingested during the NS trial, solely from the beverage. Chronic consumption of fructose promotes de novo hepatic TG synthesis and may decrease the peripheral clearance of lipids (Stanhope et al., 2009). Additionally, 10 weeks of sucrose consumption has been shown to elevate postprandial TG concentrations compared to replacement with artificial sweetener (Raben et al., 2011). With no differences found between AS and NS trials, our current data does not support the later findings. Aspartame has been found to increase triglyceride levels and induce lipid imbalance in rats via influences on metabolic pathways of the liver and involvement of oxidative stress (Adaramoye and Akanni, 2016). Additionally, research indicates acute ingestion of fructose in a moderate amount (52 g) does not significantly elevate TG concentrations compared to sucrose or sucralose (Gallagher et al., 2016). These divergent findings warrant further investigation into the acute and chronic effects of AS on the postprandial lipemic response to include both real-world and mechanistic approaches.

The effects of consumption of an AS beverage containing aspartame on blood pressure have been minimally examined. In hypertensive rats aspartame decreases blood pressure due to elevated tyrosine levels from the rapid hydroxylation of phenylalanine (i.e. a product of aspartame metabolization) in the liver (Kiritsy and Maher, 1986). Although in humans this may not be the case, due to the phenylalanine, not tyrosine, exhibiting the greatest changes (Kiritsy and Maher, 1986). Contrary, the ingestion of fructose (i.e. a nutritive sweetener) increases blood pressure in young healthy individuals (Grasser et al., 2014). Repeated acute changes in hemodynamic homeostasis could result into chronic pathologic blood pressure changes increasing the risk for cardiovascular disease. In the present study, we found higher systolic blood pressure immediately after AS consumption when compared to the CON trial (5–30 min). Additionally, we noted higher diastolic blood pressure 30 min after the consumption of AS when compared to the CON and NS trials. Although we discovered differences between trials, there was no significant changes within each trial. We speculate that because of this there was very little effect of each trial on the postprandial blood pressure response. In a 2017 study of 200 college aged students, participants ingested an acute dose of aspartame in water resulting in lower systolic blood pressure at 60, 90 and 120 min postprandial when compared to a negative control condition, e.g. cellulose (Kazmi et al., 2018). While we found no differences at these time points, Kazmi et al. (2018) started measurements at 30 min postprandial, meaning any immediate changes in blood pressure were not detected. To our knowledge, Kazmi et al. (2018) and our study are the only two studies that have evaluated the blood pressure response following the ingestion of aspartame in humans. The results found in this study add to the growing information on how the real-world application of AS ingestion affect postprandial hemodynamic homeostasis. The postprandial hemodynamic effects of AS have not yet been fully elucidated, warranting further investigation into the macro- and microvascular responses to ingestion of artificial sweeteners.

Artificial sweeteners, particularly aspartame, have been suggested to stimulate appetite (Blundell and Hill, 1986). Our findings do not support this notion. We assessed multiple components in relation to desire to eat and sensory perception of the meal test with no differences detected between trials. Our data supports similar findings from Anton et al., 2010, in which participants completed assessments of hunger and satiety after the consumption of preloads of stevia, aspartame, and sucrose. Even with the increased caloric content in the sucrose condition, similar to the present study, there were no differences in hunger and satiety levels by condition (Anton et al., 2010). Our findings support the notion that there is no preferential beverage, as noted by “overall acceptability” and suggests the differences observed in this study were not related to the participants’ hunger, satiety, or sensory perception of the meal test

The primary strength of the current study is the utilization of a real-world scenario in the structure of each trial. Allowing participants to eat a standardized breakfast meal followed by a lunch time mixed meal test mimics Western eating behavior thus allowing for more representative outcome assessments. Our study is not without limitations. In the current study, many outcome variables are associated with large variances. The time course of the study potentially did not allow for peak TG levels or for analysis of the full lipemic time course (approx. 4–5 h); follow-up studies should allow for the full lipemic time course to provide a more clinically relevant study design. While advising participants to refrain from exercise at least 48 h prior to each trial, we did not assess participants’ weekly physical activity. Since chronic exercise habits can affect postprandial metabolic responses, future research to greater control for weekly activity levels. We did not assess a responder/ non-responder phenomenon, this could partially explain these variances. There is some evidence that there is a responder phenomenon with respect to a possible CPIR after AS consumption (Dhillon et al., 2017). While we did not specifically assess this phenomenon, there was no significant difference among participants with their daily average AS consumption. Additionally, large variances could be due to our relatively small sample size (n = 8). COVID-19 necessitated the early termination of data collection for this study. While providing adequate effect sizes, we caution the interpretation of current results due to the small sample size. Lastly, this study was not designed to determine the mechanism underlying the present results. Future work is needed to strengthen the understanding of specific mechanisms responsible for the impact of AS on postprandial outcomes.

5. Conclusion

In Summary, we found that a mixed meal test containing AS, in the form of Diet Coke, does not negatively impact postprandial fat oxidation when compared to a NS trial. Additionally, we found similar postprandial energy expenditure increases between AS and NS trials, even though the NS trial had 240 additional calories from sugar. We speculate that the increase in postprandial REE coupled with the elevated carbohydrate oxidation rates indicates individuals are better capable of utilizing the provided substrate when consuming an AS soft drink compared to a nutritive-sweetened. Lastly, the absence of elevated insulin concentrations during the AS trial, as compared to the NS trial, indicate a decreased likelihood of hyperinsulinemia during the consumption of a mixed meal containing aspartame. Although caution is advised due to a small sample size, the current study aids to ever growing body of information that supports the absence of negative effects associated with the acute ingestion of an artificial sweetener, specifically aspartame.

Supplemental Material

sj-docx-2-nah-10.1177_02601060211057415 - Supplemental material for Comparison of aspartame- and sugar-sweetened soft drinks on postprandial metabolism

Supplemental material, sj-docx-2-nah-10.1177_02601060211057415 for Comparison of aspartame- and sugar-sweetened soft drinks on postprandial metabolism by Regis C. Pearson, Edward S. Green, Alyssa A. Olenick and Nathan T. Jenkins in Nutrition and Health

Supplemental Material

sj-tiff-3-nah-10.1177_02601060211057415 - Supplemental material for Comparison of aspartame- and sugar-sweetened soft drinks on postprandial metabolism

Supplemental material, sj-tiff-3-nah-10.1177_02601060211057415 for Comparison of aspartame- and sugar-sweetened soft drinks on postprandial metabolism by Regis C. Pearson, Edward S. Green, Alyssa A. Olenick and Nathan T. Jenkins in Nutrition and Health

Footnotes

Acknowledgements

Authors would like to thank Cali Pushee, Josie Key, and Hayden Suggs for help with participant recruitment and data collection. Authors have received permission from these individuals to be named.

Authors information

Regis C. Pearson, MS, Graduate Research Assistant, Department of Kinesiology, University of Georgia, Athens, GA USA (ORCID: 0000-0003-4704-920X)

Edward S. Green, MS, Graduate Research Assistant, Department of Kinesiology, University of Georgia, Athens, GA USA

Alyssa A. Olenick, MS, Graduate Teaching Assistant, Department of Kinesiology, University of Georgia, Athens, GA USA

Nathan T. Jenkins, PhD, Associate Professor, Department of Kinesiology, University of Georgia, Athens, GA USA (ORCID: 0000-0002-1536-0514)

Availability of data

The datasets generated during and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

Authorship declaration

Experiments were conducted in the Integrative Cardiovascular Physiology Laboratory located in the Department of Kinesiology at the University of Georgia. R.C.P. and N.T.J. conceived and designed the research. R.C.P. collected data. R.C.P. and N.T.J. analyzed the data. All authors contributed to interpretation of the results. R.C.P. and N.T.J. drafted the manuscript. All authors edited and revised manuscript. All authors have read and approved the final version of the manuscript and agree to be accountable for all aspects of the work in ensuring the questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All persons designated as authors qualify for authorship, and all those who qualify for authorship are listed.

Ethical approval

Declaration of Conflicting Interests

N.T.J. reports consultancies with CrossFit, Inc. and Renaissance Periodization, LLC separate from the submitted work.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: R.C.P. was supported by the University of Georgia Graduate School's Georgia Research Education Award Traineeship, and the University of Georgia Graduate School's Innovative and Interdisciplinary Research Grant.

ORCID iD

Regis C. Pearson

Supplemental material

Supplemental material for this article is available online.

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