An Investigation of the Consumption of Artificial Sweeteners in America

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Candy bars, cakes, and cokes: The average American is now estimated to consume about 150 to 170 pounds of refined sugar every year. Only a decade ago, this consumption was a mere 5 pounds a year for every American (Regan)! This massive intake of sugar is rapidly growing and is fueling America’s sweet-tooth, and although high-fructose corn syrup is replacing most granulated sugar, the race to find the sweetest, cheapest, and “safest” form of sugar is still growing with lightning speed. In turn, as these new forms of added sugar emerge, so do the questions and controversies surrounding it.

Artificial sweeteners have quickly become popular for a number of reasons. They are a zero-calorie substitute for sugar, generally easy to produce, and tend to have low impacts on blood sugar levels for those with diabetes or other health problems ("Low-Calorie Sweeteners"). There are three main types of artificial sweeteners: saccharin (Sweet ’N’ Low), aspartame (NutraSweet), and acesulfame potassium (Sweet One). Saccharin is the oldest type of artificial sugar invented and is said to be 300 times sweeter than regular table sugar (Kicks). However, much controversy over its health benefits and impacts have been rigorously tested and studied. For example, although this artificial sweetener is now being regarded as a safe alternative for diabetics who wish to keep their blood sugar in check, some studies have demonstrated that it may affect gut bacteria that regulates blood sugar, which may actually work to increase blood sugar levels (Brookshire). So, since artificial sweeteners have made some consumers weary, others have turned to new types of natural sugars for a solution.

Stevia (or Steviol Glycosides Trials) is a natural sugar, 250 times sweeter than regular sugar that has been extracted from the Stevia rebaudiana plant, commonly found in South America. Because of its components, Stevia has been regarded as a zero-calorie sweetener that, much like artificial sweeteners, does not raise blood sugar levels (Bruso). As of 2008, Stevia was approved under the FDA as being generally regarded as safe (GRAS). However, The Center for Science in the Public Interest (CSPI), a consumer advocacy group, believes that Stevia’s GRAS status was granted prematurely (Gunnars).

With 80% of food products containing some type of added sugar (Mercola), Americans face a variety of choices and a variety of conflicting data to choose from. Another problem arises as we are limited in the amount of data available, especially for a new product available to the public like Stevia. Preliminary tests have been conducted but these tests were done with a substance not available for purchase (Bruso). Therefore, the effects of the Stevia bought at a regular supermarket remains unknown.

Do we put trust in companies to provide data that may or may not be forged in order to allow for their products to be sold without scrutiny? Or do we take the question of sugar into our own hands, and stop the trend of acceptance and ignorance in how sugar affects our bodies?

Problem:

What is the effect of stevia on blood glucose levels, as compared to sucrose (table sugar) and saccharin (Sweet-N-Low)?

Experimental Hypothesis

Stevia will have the same effect on glucose levels as sucrose and the effect will be less extreme than that of saccharin.

Null Hypothesis:

There will be no difference in the effect of the three types of sugars (Stevia, saccharin, and sucrose) on blood glucose levels.

Pre-Testing Procedure:

The equally-sized, empty mouse cages, labeled A-D, were set up by putting pine shavings, a supply of water, and an equal supply (50g) of dog food.

The mice were weighed on an electronic balance using a cup as a holding container(Figure 1)

If the weight of the mice is within a 5g range from one another, the mice are place in the same cage. Using an animal marking spray and a Q-Tip, the mice within a cage were marked (Figure 2 & Diagram 1).

  1. Paw Marked
  2. Front Right
  3. Front Left
  4. Hind Left
  5. Hind Right
  6. No Mark

Testing Procedure:

Mice underwent a 4 hour fast before blood testing.

After a sterile area was set up, blood was drawn from mice using the “tail prick” method (Figure 3).

Readings were taken by the glucometer (Figure 4).

Two minutes elapsed between the baseline tests for each mouse.

Mice were force fed 1% of their body weight, according to average group weight, of 1M solution of the corresponding substance for each group using a syringe and a pipette.

Mice were retested 15 minutes after the baseline test using the same procedure as Step 2.

Mice were retested 30 minutes after the baseline test using the same procedure as Step 2.

Data Analysis:

Test of the Mean Difference Based on Paired Observations

Hypothesis

Ho: µdo = 0 Ha: µd ≠0

Where µdo is the hypothetical difference in mean blood glucose levels, and µd is the actual difference in mean blood glucose levels.

Calculations

_ _

t= d -µdo where d is the mean difference in blood glucose levels,

sd/√n µdo is the hypothetical mean difference in blood glucose (zero), sd is the standard deviation mean difference in blood glucose, n is the population size, and t is the test statistic.

Combined Water Trials- Mice treated with water.

Initial mean: 90.2 mg/dL

Initial standard deviation: 29.7052 mg/dL

Mean after 15 minutes: 85.0 mg/dL

Standard deviation after 15 minutes: 35.8329 mg/dL

Mean after 30 minutes: 80.6 mg/dL

Standard deviation after 30 minutes: 27.0276 mg/dL

Test statistic for the difference in blood glucose levels after initial and after 15 minutes:

t= = 5.2 - 0 = -2.6835= P-value= 0.98747

-6.1277/√10

Our P-value falls above the critical value (α) of 0.05, indicating that there is a 98% probability that the resulting difference in mean blood glucose levels happened simply be chance. Because of this, we do not reject the null hypothesis that the difference in blood glucose levels equals zero.

Test statistic for the difference in blood glucose levels after 15 minutes and after 30 minutes:

t= = 4.4 - 0 = 1.58019= P-value= 0.074261

8.8053/√10

Our P-value falls above the critical value (α) of 0.05, indicating that there is a 7% probability that the resulting difference in mean blood glucose levels happened simply be chance. Because of this, we do not reject the null hypothesis that the difference in blood glucose levels equals zero.

Combined Sucrose Trials- Mice treated with regular cane sugar.

Initial mean: 116.7 mg/dL

Initial standard deviation: 25.6287 mg/dL

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Mean after 15 minutes: 141.7 mg/dL

Standard deviation after 15 minutes: 29.3752 mg/dL

Mean after 30 minutes: 131.6 mg/dL

Standard deviation after 30 minutes: 33.2907 mg/dL

Test statistic for the difference in blood glucose levels after initial and after 15 minutes:

t= = -25 - 0 = 21.158= P-value= 0.00000000276185

-3.7365/√10

Our P-value falls below the critical value (α) of 0.05, indicating that there is less than a 1% probability that the resulting difference in mean blood glucose levels happened simply by chance. Because of this, we reject the null hypothesis that the difference in blood glucose levels equals zero, indicating this mean difference is significant and could be a result of the treatment.

Test statistic for the difference in blood glucose levels after 15 minutes and after 30 minutes:

t= = 10.1 - 0 = -8.15707= P-value= 0.999991

--3.9155/√10

Our P-value falls above the critical value (α) of 0.05, indicating that there is a 99% probability that the resulting difference in mean blood glucose levels happened simply by chance. Because of this, we do not reject the null hypothesis that the difference in blood glucose levels equals zero.

Combined Saccharin Trials- Mice treated with artificial sweetener (Sweet’ N Low) .

Initial mean: 112.1 mg/dL

Initial standard deviation: 27.8187 mg/dL

Mean after 15 minutes: 133.0 mg/dL

Standard deviation after 15 minutes: 33.9607 mg/dL

Mean after 30 minutes: 124.7 mg/dL

Standard deviation after 30 minutes: 30.4669 mg/dL

Test statistic for the difference in blood glucose levels after initial and after 15 minutes:

t= = -20.9 - 0 = 10.7606= P-value= 0.000000968841

-6.14199/√10

Our P-value falls below the critical value (α) of 0.05, indicating that there is less than a 1% probability that the resulting difference in mean blood glucose levels happened simply by chance. Because of this, we reject the null hypothesis that the difference in blood glucose levels equals zero, indicating this mean difference is significant and could be a result of the treatment.

Test statistic for the difference in blood glucose levels after 15 minutes and after 30 minutes:

t= = 8.3 - 0 = 7.51242= P-value= 0.000018

3.4938/√10

Our P-value falls below the critical value (α) of 0.05, indicating that there is less than a 1% probability that the resulting difference in mean blood glucose levels happened simply by chance. Because of this, we reject the null hypothesis that the difference in blood glucose levels equals zero, indicating this mean difference is significant and could be a result of the treatment.

Combined Steviol Glycosides Trials- Mice treated with Stevia.

Initial mean: 92.3 mg/dL

Initial standard deviation: 29.4771 mg/dL

Mean after 15 minutes: 204 mg/dL

Standard deviation after 15 minutes: 85.9909 mg/dL

Mean after 30 minutes: 196.3 mg/dL

Standard deviation after 30 minutes: 90.4385 mg/dL

Test statistic for the difference in blood glucose levels after initial and after 15 minutes:

t= = -111.7 - 0 = 6.25027= P-value= 0.000075

-56.5138/√10

Our P-value falls below the critical value (α) of 0.05, indicating that there is less than a 1% probability that the resulting difference in mean blood glucose levels happened simply by chance. Because of this, we reject the null hypothesis that the difference in blood glucose levels equals zero, indicating this mean difference is significant and could be a result of the treatment.

Test statistic for the difference in blood glucose levels after 15 minutes and after 30 minutes:

t= = 7.7 - 0 = 5.47476= P-value= 0.000196

-4.4476/√10

Our P-value falls below the critical value (α) of 0.05, indicating that there is less than a 1% probability that the resulting difference in mean blood glucose levels happened simply by chance. Because of this, we reject the null hypothesis that the difference in blood glucose levels equals zero, indicating this mean difference is significant and could be a result of the treatment.

Conclusion:

The data did not support the experimental hypothesis because the blood glucose levels in the mice given stevia increase significantly more than the levels of the mice that consumed sucrose and saccharin. Though there was a significant difference in blood glucose levels with the consumption of all the different sugars, the biggest difference was in the levels resulting from the consumption of stevia. This indicates that stevia affects blood sugar levels more dramatically compared to sucrose and saccharin.

Due to the fact that the experiment involved live animals, completely controlling the trials proved difficult. The first obstacle faced was sorting the mice into groups based on weight. A mouse’s weight fluctuates largely, so keeping all groups within 5g of each other proved difficult. However, this was essential for the experiment because if a mouse was too dominant, it caused fights and even deaths among the rest of the group. Also, since there was not enough mice to have groups based on gender, this variable may have affected the experiment. In addition, since the exact age of the mice was unknown, metabolism rates may have varied and may have affected the results. When experimentation involving blood began, an entirely new set of obstacles arose. First and foremost, there were many errors with the glucometer that caused a lapse in time intervals. Also, the reluctance of mice to drink the solution may have cause a certain degree of difference in the consumption levels of each mouse.

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