Relationship of Taste Status & Food Environment on Body Mass Index Second Draft of Final Paper

TASTE, ENVIORNMENT, & BMI 1
Running Head: TASTE, ENVIORNMENT, & BMI
Relationship of Taster Status to Food Environment on Body Mass Index
Horacio Ruiz & Kenneth Curiel
Dr. Thomas
La Sierra University
Department of Health and Exercise Science
EXSC 364 Research Methods
June 1, 2015

Abstract
The study looks at how taster and environment statuses may have an effect on body mass
index (BMI) values. 41 adult participants volunteered, with 22 males and 19 females. All
participants tasted the 6-n-Propylthiouracil (PROP) slip, which is used to measure oral taste
responsiveness, and we used it to determine the perceived bitterness values. Participants also
completed a questionnaire on food environment perception and had their height and weight
measured for BMI values. The results indicated BMI levels were not significantly different for
taste status, (p = .196), environment, (p = .905), or the interaction between them, (p = .918). The
null hypothesis states that there will be no significant difference in BMI values when using taste
status and food environment as independent variables. A 2 x 3 factorial analysis of variance
(ANOVA) was conducted indicating results of (.579) significance, reflecting that we accept the
null hypothesis. This represents that there was no significant relationship between taste and
environment statuses on BMI. We believe that using Geographic Information System (GIS) to
better assess food environment can improve the results if the study is replicated.

Introduction
Obesity is a big problem in the western hemisphere, and as more countries become
developed and begin introducing western customs of fast food intake, there is an increase in the
amount of people who become obese. A fact that highlights the high-fat diet and low-exercise
community is that more than 1/3 of United States adults and 17 percent of children ages 2-19 are
obese (CDC, 2014). Our interest in this topic is to help add to the literature about how taste status
awareness & food environment identification may affect Body Mass Index levels (BMI). Taste is
one of the senses that almost everyone possesses. Taste has many influences such as genetic
traits inherited from parents, environmental factors such as race and culture, and accessibility to
healthy or unhealthy food. We explored whether taster status and accessibility to healthy food
are predictors for BMI. We hypothesized that most people who are supertasters will have lower
BMI’s than those who are non-tasters. However, we believed that environment is the other
significant independent variable that also contributes to the BMI calculation results.
Literature Review
Taste Status Importance
In the research article by Catanzaro, Chesbro and Velkey, found that approximately 25%
of the human population that do not detect bitterness in the response to 6-n-Propylthiouracil
(PROP) are categorized as non-tasters. Of the 75% that do detect bitterness, the 25% who detect
the most intense, aversive sensation are categorized as supertasters. The remaining 50% are
considered medium tasters who perceive PROP as bitter but not as intense as the supertasters
report (Catanzaro, Chesbro & Velkey, 2013, p. 125). The participant places a small paper soaked
in a liquid PROP or Phenylthiocarbamide (PTC) solution on their tongue and rates the intensity

of sensation experienced, from 0-100, on the modified general Labeled Magnitude Scale (LMS)
(p. 125). For our research design we used a scale of 1 to 10, where 8-10 was very bitter, 4-7 was
in between, and 1-3 was not bitter at all. This will determine the participant's category of
measuring their taste.
Burd’s research team found that taste was a critical component that the researchers
assessed. They wanted to look at the relationship between genetic predispositions such as taste
and food environment, which can potentially influence the result of negative eating behaviors
and obesity. The PROP test was used to accurately determine taste status because it measures
oral taste responsiveness effectively and has been used in many studies (Burd, et al, 2013, p.
786). The particular focus of taste in the study was to demonstrate how genes play an important
role in the choices that people make when consuming food. According to their literature review,
they found ethnic data, which stated that Caucasians had more than 70 percent of the population
that taste the bitterness quickly of the PROP- slip (p. 787). If we have a greater amount of
Caucasians in our study then the population, we may have more supertasters than non-tasters.
Tasters in many studies have been shown to dislike foods that are very bitter such as black
coffee, grapefruit, and certain vegetables (p. 787). Any type of factor that reduces the interest of
eating vegetables is something worth learning about because if the bitterness of vegetables
makes people not eat them regularly, then one could say that there is a potential that the
vegetable inhibition has contributed to the obesity condition. Burd’s group was also able to find
literature that suggested that non-tasters tended to eat foods that are high in fat (p. 789). This

may suggest that the non- tasting population will desire to be satisfied so they rely on fat-rich
food that has a lot of flavor.
Food Environment Importance
Many factors other than biology and genetics play a role in food preference. These
include early exposures to a variety of foods, health beliefs, classically conditioned positive and
negative associations, observational learning, and cognitive interpretations of sensory
experiences with various flavors. To some individuals the bitter taste and spicy foods are
enjoyable (Catanzaro, et al, 2013, pp.126-127). Culture actually begins to impact the child prior
to birth. During pregnancy the developing child in the womb is engulfed in and ingests amniotic
fluid. In a well-controlled experimental research they have found that if a mother drinks carrot
juice 4 times a week for 3 weeks in the last trimester of pregnancy the child will enjoy carrot
flavored cereals more than a mother that had just drank water in the same amount of time
(Catanzaro, et al, 2013, p. 127). Many American children know that they are not going to like
spinach, tofu, liver, or any “healthy foods” because they were brought up to like the “crave
foods” like the burgers, the soda, the delicious cereals because of the sweet taste (Catanzaro, et
al, 2013, p. 129).
Burd’s group also felt that the environment was a very significant factor that contributed
to obesity and negative eating behaviors (2013, p. 786). They focused on children so the cultural
customs greatly affected what the children ate. They used a Geographic Information System

(GIS) that helped determine if the children’s environment was “healthy” or “unhealthy” based on
the accessibility to businesses promoting vegetables/fruits vs. fast food respectfully (p. 786).
This is something that we potentially wanted to use but as undergraduate students and with the
limited time frame that we have, it was not a realistic choice. In the literature review that the
researchers did they were able to find that children that have more healthy options available, at
closer proximities, like grocery stores, had ideal BMI’s (p. 787). In the study they also were able
to get the zip codes of the children for the GIS System Version 9.0 (ESRI Redlands, California)
to measure the proximity of businesses within a half-mile radius (p. 790). This would be ideal to
get better results but we are going to use the method described above in Catanzaro’s study where
they used a food environmental questionnaire to assess the environment that the children were
exposed to (Catanzaro, et al, 2013, p. 125).
In as study with Dinehart’s group the objective was to look at why people do not
consume vegetables based on sweetness or bitterness of vegetables. Research literature has
claimed that bitterness of vegetables will hinder consumption of this important food group that
improves health and lowers risk of chronic disease onset (Dinehart, et al, 2005, p. 304). The
dependent variable was vegetable preference (Brussels sprouts, kale, asparagus, and vegetables
typically consumed) and the independent variables were whether the vegetables were sweet or
bitter. They also used a taste pathology (quinine, function) genetic marker test, which also tests
bitterness detection but it focuses on chorda tympani nerve that is used for taste sensation of the
whole mouth (Dinehart, et al, 2005, p. 304).

The total participants in the study were 71 females and 39 males from ages 18 to 60. The
research was conducted using a Label Magnitude Scale that quantitatively addressed the
pleasantness or unpleasantness sensation of the vegetable consumed. The statistical tests used for
the data were multiple linear regression and structural equation modeling. The results were that
the PROP-test of taste pathology (quinine) was able to explain the variability of the vegetable
preference and intake via vegetable bitterness and sweetness (Dinehart, et al, 2005, p. 307). The
PROP-taste-test (6-n-propylthiouracil) was better able to explain the variability of the vegetable
preference and intake via vegetable bitterness only. They were able to demonstrate that bitterness
and sweetness of vegetables are significant factors that help determine whether people consume
them or not. If the vegetable were sweet, more people would accept it but if more bitter, it would
not be consumed favorably. (Dinehart, et al, 2005, p. 308). A way to improve the study was to
have a much more ethnically diverse sample population.
BMI Importance
Oftedal and Tepper used a tape measure attached to a flat wall to get the participant’s
height, and an electronic scale to get the participant’s weight to determine the BMI. We are
going to use a simple Weight Watcher scale to save on costs for the research study. After the
data was collected they put the participant’s height, weight, gender, and age information in the
Body Mass Index (BMI) machines to figure out the individual's percentile of being categorized
as normal, overweight, or obese. Anyone in the 85 percentile was categorized as “overweight,”

and anyone in the 95 percentile was categorized as “obese.” The participants were asked to wear
light clothing to get a more accurate measurement.
According to the Centers For Diseases Control and Prevention (CDC), body mass index
is an ideal number that assesses the fatness of most people accurately (CDC, 2015). The reason
why most researchers use it instead of other methods of measuring fat is because it is relatively
inexpensive and easy to perform when working with unhealthy weight problems (CDC, 2015). In
our study we decided that because BMI is seen an acceptable standard in the kinesiology and
health sciences literature, then it would be the convenient test to use in our study.
We will measure BMI using a measuring tape and a weight scale to determine if body
composition is healthy or not as Burd’s group did (p. 786). The BMI numbers will be the
dependent variable in this study, and we believe that food environment and taste status will
potentially influence whether that number is healthy or not.

Methods
Participants
41 adults in Southern California participated in this study. Participants ranged from 18 –
59 years of age. There were a total of 22 males and 19 females. The method of getting the
sample size was through convenience sampling.
Equipment
BMI was measured using a portable scale (Model WW52, Conair Corporation) and
measuring tape. PROP (6-n-propylthiouracil) test slips were used to properly analyze taste
statuses: supertaster, non-taster, or in between.
Procedures
First, participants were given instructions and read and signed the informed consent for
this research project. Then they completed a small questionnaire by Freedman titled “Perceptions
of Food Environment Scale,” in order to determine food environment status. The questionnaire
makes six statements about perceived environmental exposure to food by having them rate on a
Likert scale, their exposure to the statement’s subject. Next, they use the PROP-test, which has
been used in multiple studies to assess oral-taste responsiveness (Oftedal & Tepper, 2013, p.
104) (Burd, et al, 2013, p. 786). This test involves licking a PROP-test slip and addressing if the
bitterness was strong, in between, or not detectable. Finally, we also tested BMI through use of a
scale and a height measuring tape to record these anthropometric values (CDC, 2015).

Results
Statistics
Our dependent variable in the research study was BMI. The independent variables were
food environment and taster status. Food environment will have two categories, which are
unhealthy or healthy using the questionnaire specified above. Taster status had three categories,
which were PROP taster (supertaster), taster, or non-taster. For this type of scenario, by
referencing Hall and Getchell’s textbook, we decided that a 2 x 3 factorial analysis of variance
(ANOVA) was the best method for statistical analysis (2014, p. 256) We used Statistical Package
for the Social Sciences (SPSS) predictive analysis software to analyze the data. Our design was
static group comparisons because we are analyzing the relationship of taste status and food
environment on BMI.
SPSS Data Analysis
The 2 x 3 factorial ANOVA was used to determine if taste status, environment status, or
their interaction were related to BMI. No main effect was seen for environment status (F(1,39) =
0.01, p = .91), for taste status (F(2,38) = 1.71, p = .20), or for the interaction between them
(F(2,38) = 0.09, p = .92) When we look at taste status relation with BMI there is a strong
possibility that because our sample size was underpowered, we potentially could have acquired a
statistically significant result of the relationship.

Table 1: 2x3 Factorial Analysis of Variance Test of Between-Subjects Effects

Graph 1: Taste Status Related to BMI
The graph above was designed on Google sheets to help give our data a visual appeal on
our poster. The graph simply describes the relationship of the values of taster status for each
participant compared to the BMI of each participant. The gender is separated by the colors,
which indicate that males are red on taster status and blue in BMI values. For females the green
was used to reveal taster status and the yellow indicated the BMI values.
The reason we saw no variables that were significant in are study is because of the
inability to find a consistent trend when comparing the lines. For taster status we hypothesized
that females would have a high taster status and therefore a higher BMI, which was not evident
in the raw data that is displayed above. For example, the first girl had a value of 10 (supertaster)

but a healthy BMI of roughly 19. For the fifth male he indicated a value of 8 (supertaster) but
also had a healthy BMI of roughly 22.
Therefore, because our both major studies from the literature review indicated that
supertaster were uninterested in healthier options of foods like vegetables and grapefruits, which
have positive benefits such as containing antioxidants, we conclude that there must be another
variable or factors we have not accounted for. We also found in the literature that non-tasters
also like to eat very unhealthy food so this is why they may also have BMI’s that are non-ideal.
After doing this research it is evident that there is more to improving BMI then just taster
status and food environment. We have to account for other variables that may improve the BMI
relationship like amount of hours of sleep and total hours of exercise in a week participants get.
This would give us the opportunity to make our research design a little more complicated by
creating a two-x three-x-two-x-two factorial analysis of variance. We would determine more
than seven hours of sleep but less than nine hours as healthy and anything less than seven would
be unhealthy. Then for exercise we would use American College of Sport Medicine’s
recommendation of hours of exercise a week to determine healthy and unhealthy amount of
exercise. We believe that this design can help create a stronger analysis on the link between
taster statuses and BMI that we saw in the design for this research project.

Discussion & Conclusion
In conclusion, the study showed that there was no significant difference in BMI values
for taster status and environment. Therefore we must accept the null hypothesis. The reason this
study is important is because in our present western society, obesity is still growing, and this
research has helped us learn new insights about how taster status and food environment may
affect BMI. In our results, the relationship between taste status and BMI had the closest
significant value at (F(2,38) = 1.71, p = .20), which indicates that if we had more participants in
our study there may have been a significance between taster status and BMI.
Taster status is important because in a study where researchers analyzed similar data,
they found that Supertasters tended to avoid bitter foods such as black coffee, grapefruit, and
certain vegetables (Burd, et al, 2013, p.788). Any type of vegetable reduction in diets is
unacceptable when desire to maximize health is high; because the nutrients they provide to the
body are essential. Burd’s group also found that there was a strong link of non-taster preferring
to eat very fat-rich food. This is why we felt that non-tasters would have significantly higher
BMI values.
Factors that play a role in food preference include early exposure to a variety of foods,
health beliefs, classically conditioned negative and positive associations, observational learning
and cognitive interpretations of sensory experiences with various flavors. (Cantanzaro, et al,
2013, pp. 126-127) This is why it was important to look at the food environment as well because
the choices you make are strongly influenced by the factors mentioned above.
Finally, BMI was used to numerically validate the fatness of most people accurately,
which is ideal according to the Center for Disease Control and Prevention (CDC, 2015). If done

again we would probably try using bioelectrical impendence or bod pod to get much more
accurate results of body composition.
For a follow up study we would suggest using GIS instead of a questionnaire to
appropriately assess who has a healthy or unhealthy environment. Next, we would also
encourage researchers to use bioelectrical impedance to also look at body fat percentage. We
believe that figuring out how to get more people with a healthy BMI is a very important topic to
do research on, which may be dependent on other factors than just environment and taster status,
like amount of exercise participated in a week.

References
About BMI for Adults. (2015, February 23). Retrieved May 1, 2015, from
http://www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html
Burd, C., Senerat, A., Chambers, E., & Keller, K. (2013). PROP taster status interacts with the
built environment to influence children's food acceptance and body weight status.
Obesity, 21(8), 786-794, doi:10.1002/oby.20059.
Catanzaro, D., Chesbro, E., & Velkey, A. (2013). Relationship between food preferences and
PROP taster status of college students. Appetite, 68, 124-131.
Dinehart, M., Hayes, J., Bartoshuk, L., Lanier, S., & Duffy, V. (2005). Bitter taste markers
explain variability in vegetable sweetness, bitterness, and intake. Physiology & Behavior,
87, 304-313, doi:10.1016/j.physbeh.2005.10.018.
Hall, S., & Getchell, N. (2014). Selecting statistical tests within research designs. In Research
Methods in Kinesiology and the Health Sciences (1st ed., pp. 246-261). Philadelphia,
Pennsylvania: Wolters Kluwer Health.
Oftedal, K., & Tepper, B. (2013). Influence of the PROP bitter taste phenotype and eating
attitudes on energy intake and weight status in pre-adolescents: A 6-year follow-up study.
Physiology & Behavior, 118, 103-111, doi:10.1016/j.physbeh.2013.05.016.

Freedman’s Questionnaire

Raw Data
Participants Gender Perceived Bitterness Taste Status PFE1
1 2 10 3 10
2 2 4 1 6
3 2 4 1 6
4 1 3 1 10
5 1 5 1 8
6 1 2 1 8
7 2 1 1 8
8 2 1 1 8
9 2 1 1 10
10 2 1 1 8
11 1 3 1 10
12 2 1 1 8
13 1 1 1 10
14 2 7 2 8
15 1 7 2 10
16 1 6 2 10
17 1 5 2 10
18 1 7 2 10
19 1 7 2 10
20 2 4 2 10
21 2 4 2 8
22 1 6 2 10
23 2 10 3 10
24 2 10 3 8
25 2 8 3 10
26 1 8 3 10
27 1 8 3 10
28 1 9 3 10
29 1 9 3 10
30 1 8 3 8
31 2 10 3 8
32 1 8 3 8
33 2 5 2 10
34 1 7 2 10

35 2 5 2 10
36 1 5 2 10
37 1 5 2 10
38 1 2 1 10
39 2 1 1 10
40 2 6 2 8
41 1 8 3 10
Male = 1 Non-Taster= 1-3 Non-Taster = 1
Female = 2 Taster = 4-7 Taster = 2
Supertaster = 8-10 Supertaster = 3
PFE2 PFE3 PFE4 PFE5 PFE6 Total
2 6 6 10 10 44
4 6 4 6 6 32
10 6 4 4 6 36
10 8 10 8 10 56
6 8 4 6 8 40
4 8 4 10 10 44
2 8 2 6 6 32
6 8 6 10 10 48
2 8 2 10 10 42
6 4 2 4 8 32
6 10 6 6 10 48
2 4 4 8 8 34
4 8 4 8 8 42
4 8 4 10 8 42
2 4 2 10 10 38
2 6 2 10 10 40
2 6 2 6 6 32
8 10 2 8 10 48
4 6 4 8 10 42
6 6 4 8 8 42
4 6 4 6 8 36
2 6 2 6 8 34
6 8 6 8 10 48
6 8 6 6 8 42
4 10 4 8 10 46

2 8 4 8 8 40
2 4 2 4 8 30
6 4 2 8 10 40
2 10 2 10 10 44
10 8 2 6 10 44
2 4 2 6 4 26
2 8 2 8 6 34
6 8 6 10 10 50
4 8 2 8 10 42
2 4 2 8 10 36
2 6 2 6 8 34
4 8 2 8 4 36
4 8 4 6 2 34
4 10 2 6 8 40
4 4 4 8 10 38
2 6 2 8 10 38
Environment Status Weight (lbs) Height (in) Age BMI
1 117.5 61 22 22.2
2 174.2 67.5 22 26.9
2 177.5 66 22 28.6
1 169 68 20 25.7
1 144.4 67 21 22.6
1 239.5 74 22 30.7
2 143 59 24 30.9
2 128.4 70 18 18.4
1 120.9 64 20 20.8
2 167 71 23 21.9
1 180 72 46 24.4
2 141.2 62 20 25.8
1 118.1 70 24 16.9
1 165.7 66 59 26.7
2 221.8 69 21 32.8
1 153 67.5 21 23.6
2 175 69.5 20 25.5

1 113 65 20 18.8
1 166.9 67 18 26.1
1 137 65 21 22.8
2 167.6 64 20 28.8
2 183.7 71 24 25.6
1 104.6 62 22 19.1
1 104.8 65 18 17.4
1 125.1 62 25 22.9
1 180.1 70 22 25.8
2 157.5 71 29 22
1 185 68 22 28.1
1 136 67.5 21 21
1 220 68.5 27 33
2 130.5 69 23 19.3
2 195.4 70 20 28
1 224 62.5 24 39.7
1 237.4 71.5 36 30.5
2 156.1 67 22 24.4
2 170.9 69.5 21 24.5
2 194.3 71 24 27.1
2 171.2 70 19 24.6
1 140.1 66 24 22.6
2 121.1 65.5 18 20.2
2 232 72 22 29.8
1= Healthy More than < 40
2= Non-Healthy Less than > 39

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