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ANALYZING AWARENESS OF OBESITY AMONG STUDENTS IN THE
SCHOOL OF AGRICULTURE & CONSUMER SCIENCES AT TENNESSEE
STATE UNIVERSITY
A Thesis
Submitted to the Graduate School
of
Tennessee State University
in
Partial Fulfillment of the Requirementsfor the Degree ofMaster of Science
Graduate Research Series No. ______
Kashin A. Thompson
August, 2011
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All rights reserved
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UMI Number: 1497847
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ANALYZING AWARENESS OF OBESITY AMONG STUDENTS IN THE
SCHOOL OF AGRICULTURE & CONSUMER SCIENCES AT TENNESSEE
STATE UNIVERSITY
A Thesis
Submitted to the Graduate School
of
Tennessee State University
in
Partial Fulfillment of the Requirementsfor the Degree ofMaster of Science
Kashin A. ThompsonAugust 2011
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To the Graduate School:
We are submitting a thesis by Kashin A. Thompson entitled "Analyzing
Awareness of Obesity Among Students in the School of Agriculture & Consumer
Sciences at Tennessee State University" We recommend that it be accepted in partial
fulfillment of the requirements for the degree, Master of Science in Agricultural Sciences.
_Dr_Eisshea Tegegne__________________Chairperson
__Dr Barbara Canada__________________Committee Member
__Dr. Lan Li_________________________Committee Member
_Dr.Surendra P. Singh_________________Committee Member
Accepted for the Graduate School:
_Alex Sekwat _________________Dean of the Graduate School
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DEDICATION
This thesis is dedicated to my father, Ray Thompson who passed away on June
17, 2011. He will be missed and forever in my heart. It is also dedicated to my mother,
Kim Thompson without her encouraging words and support I would have never made it
to this point in my life.
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ii
ACKNOWLEDGEMENTS
This thesis took the work of many family members, friends, and professors. First
and foremost I would like to thank God. When things seemed rough, I referred to the
scripture "look to thehills from which your help cometh", because through him all things
are possible. I would like to express my sincere thanks to my committee members, Dr. S.
Singh, Dr. F. Tegegne, Dr. B. Canada and Dr. L. LI for sharing their knowledge on
strengthening the thesis. Assistance by Dr. E. Ekanem is also acknowledged.
I would also like to acknowledge my colleagues Derrick, Steven, and Simba, who
have been supportive, checking on me to make sure I was making progress every other
hour if not every hour, and aiding me in areas that I struggled. I would also like to
acknowledge my wonderful friend Angela Knowlton who made sacrifices, and provided
positive attitude, and letting me utilize her computer. I would like to extend a very special
thanks to Denise Mitchell, and Mrs. Mary Ekanem. Last but not least I would like to
thank my family who gave me motivation and encouragement.
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ABSTRACT
KASHIN THOMPSON Analyzing Awareness of Obesity Among Students in the School
of Agriculture & Consumer Sciences at Tennessee State University (under the direction
of Dr. FISSEHA TEGEGNE)
Obesity is excessive accumulation of body fat, which can lead to an adverse effect on
health, resulting in reduced life expectancy and/or increased health problems. It is a
major public health problem found in men, women, and children of all ages, races, ethnic
background, and socioeconomic groups in the United States and around the world. The
objectives of this study are as follows: 1) To assess awareness levels about obesity and
related issues among students in the school of Agriculture and Consumer Sciences at
Tennessee State University, 2) To characterize the prevalence of obesity and knowledge
about it among the students, 3) To discuss suggestions by the students involved in this
study. This study can contributes to a better understanding of factors related to students
awareness about obesity and their suggestions to tackle the problem. In order to
accomplish the objectives of this study data were collected from primary and secondary
sources. Face- to-Face surveys of graduate and undergraduate students at Tennessee State
University in the School of Agriculture and Consumer Sciences were conducted in spring
2011 A total of one hundred forty one completed responses were received. The data were
checked for completeness coded and entered into the computer. Spss-Pc was used to
conduct descriptive and statistical analysis of the data. Results show that there are
various factors affecting awareness about obesity and strategies to tackle it.
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TABLE OF CONTENTS
Acknowledgments.............................................................................................................ii
Abstract.............................................................................................................................iii
Table of Contents..............................................................................................................iv
List of Tables......................................................................................................................v
Chapter I. Introduction......................................................................................................1
Statement of the problem....................................................................................10
Objectives............................................................................................................11
Hypothesis...........................................................................................................11
Significance of the Project..................................................................................12
Chapter II. Review of Literature......................................................................................14
Chapter III. Methodology................................................................................................21
Chapter IV. Results and Discussion.................................................................................23
Chapter V. Summary and Recommendations...................................................................44
Recommendations for future research..................................................................45
References........................................................................................................................47
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LIST OF TABLES
Table 1 Prevalence of Obesity among adults, by black/white race or
Hispanic ethnicity, census region and sex-behavioral Risk Factor
Surveillance System surveys, United States, 2006-2008
3
Table 2 U.S. Obesity Trends Amongst the States 5
Table 3 Prevalence and trends data in Tennessee 7
Table 4 Prevalence of overweight, obesity and Class II Obesity by Socio-
Demographic Characteristics
15
Table 5 Classification and Exercise Habits Cross Tabulation 25
Table 6 Classification and Aware that Poor Diets Put Health at Risk Cross
Tabulation
26
Table 7 Plans to Change Eating Habits and Which would Encourage plans to
change eating habits Cross Tabulation
27
Table 8 Classification and Plan to Change Your Eating Habits Cross
Tabulation
29
Table 9 Distribution Frequencies of Awareness of Obesity Problems among
designed groups
30
Table 10 Results of Chi-Square Tests of Awareness of Obesity Among
designed Groups
32
Table 11 Anova Results of Awareness Level of Obesity Problems 35
Table 12 BMI Among Students 43
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CHAPTER I
INTRODUCTION
Obesity is a growing problem in the United States. It is an excessive accumulation of
body fat, which can lead to adverse effects on health, resulting in reduced life expectancy
and/or increased health problems. It is considered to be a chronic illness requiring
lifelong treatment and management (Mauro 2008). Obesity is usually associated with
other conditions that can be controlled but not cured, such as high blood pressure and
diabetes. When dealing with weight there are several topics that come into play varying
from child to adult, they are:
Extreme obesitya BMI (body mass index) greater than or equal to 40
Obesityan excessive amount of body fat in relation to lean body mass or a body
weight that is 30 percent over the ideal weight for a specified height; BMI of 30or greater.
Normal Weightideal weight per height measurements; a classification of BMIof 18.5-24.9.
Underweightweighing less than normal, healthy, or required; BMI less than18.5.
Obesity is a major public health problem found in men, women, and children of all
ages, race, ethnic backgrounds, and socioeconomic groups in the United States and
around the world. According to the United States Center for disease control (CDC) more
than one third of adult Americans are obese. Approximately 300,000 deaths a year due to
obesity, which puts it as the second leading cause of preventable deaths in the United
States (Carson- Dewitt, MD 2009)
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Even though obesity is found in men, women, and children, it is more prevalent
among women. The forty to fifty year age group has the largest percentage of obesity
with, 53% of Black women and 51% of Mexican women and almost 39% of White
women. Racial/ethnic differences in obesity rates are not found in men. Table 1 provides
some obesity statistics by various taxonomies for different regions of the United States.
American children and teens are also affected by the most common nutritional disorder.
Children have become heavier in the past 30 years, and the prevalence of childhood obesity has
more than doubled among children ages 2-5 (5.0% to 13.9%), has tripled among youth ages 6-11
(6.5% to 18.8%), and has more than tripled among adolescents ages 12-19 (5.0% to 17.4%)
(Barnes 2011). Once again Black and Hispanics are more likely to be overweight than White
children. However, recent data suggest that the rate of overweight in children did not increase
significantly between 1999 and 2008, except in the heaviest boys. This rate, though, remains
alarmingly high; all are drastic changes that occurred over a thirty year span. The twenty to
seventy-four age groups showed the highest increases compared to the two to five and six to
eleven age groups. The World Health Organization (WHO 2008) estimated that 1.5 billion
adults, 20 and older were overweight in 2008. Of these over 200 million men and almost 300
million women were obese.
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______________________________
Source: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5827a2.htm#tab1
Nearly 43 million children under the age of five were overweight in 2010. WHO refers
to the global epidemic as globesity. Figure 1 shows thepercentages of obesity across
the states.
Table 1: Prevalence of obesity among adults, by black/white race or hispanic
ethnicity, census region, and sex - Behavioral Risk Factor Surveillance
System surveys, United States, 20062008
Census regions White, non-Hispanic
(n = 900,629)
Black, non-Hispanic
(n = 84,838)
Hispanic
(n = 63,825)
Percent (95% CI) Percent (95% CI) Percent (95% CI)
Overall
Both sexes 23.7 (23.523.9) 35.7 (35.036.3) 28.7 (28.029.5)
Men 25.4 (25.125.7) 31.6 (30.632.7) 27.8 (26.728.9)
Women 21.8 (21.622.1) 39.2 (38.540.0) 29.4 (28.530.3)
Northeast
Both sexes 22.6 (22.223.0) 31.7 (30.033.4) 26.6 (25.028.3)
Men 25.0 (24.425.6) 26.5 (24.029.1) 26.9 (24.329.6)
Women 20.0 (19.620.5) 36.1 (34.038.3) 26.0 (24.128.0)
Midwest
Both sexes 25.4 (25.125.8) 36.3 (34.937.9) 29.6 (27.431.9)
Men 27.0 (26.527.6) 32.1 (29.734.5) 29.7 (26.433.1)
Women 23.8 (23.324.2) 40.1 (38.342.0) 29.2 (26.631.9)
South
Both sexes 24.4 (24.124.7) 36.9 (36.237.7) 29.2 (28.130.3)Men 26.3 (25.826.8) 32.6 (31.433.9) 28.3 (26.630.1)
Women 22.5 (22.122.9) 40.6 (39.741.5) 29.7 (28.331.1)
West
Both sexes 21.0 (20.621.5) 33.1 (29.736.7) 29.0 (27.730.3)
Men 22.1 (21.522.8) 34.1 (29.039.6) 27.3 (25.529.2)
Women 19.8 (19.320.4) 32.0 (28.236.1) 30.4 (28.732.1)
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Figure 1: U.S. Obesity Trend
Source: U.S. Obesity Trends 19852009, CDC, August, 2010
http://www.cdc.gov/obesity/data/trends.htmlhttp://www.cdc.gov/obesity/data/trends.htmlhttp://www.cdc.gov/obesity/data/trends.htmlhttp://www.cdc.gov/obesity/data/trends.html -
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______________________Source: Extracted and modified from U.S. Obesity Trends 19852009, CDC, August,2010.
Table 2: U.S. Obesity Trends Amongst the States
State Percent State PercentAlabama 31.0 Illinois 26.5
Alaska 24.8 Indiana 29.5
Arizona 25.5 Iowa 27.9Arkansas 30.5 Kansas 28.1California 24.8 Kentucky 31.5Colorado 18.6 Louisiana 33.0Connecticut 20.6 Maine 25.8Delaware 27.0 Maryland 26.2Washington DC 19.7 Massachusetts 21.4Florida 25.2 Michigan 29.6
Georgia 27.2 Minnesota 24.6Hawaii 22.3 Mississippi 34.4Idaho 24.5 Missouri 30.0Montana 23.2 Rhode Island 24.6 Nebraska 27.2 South Carolina 29.4 Nevada 25.8 South Dakota 29.6 New Hampshire 25.7 Tennessee 32.3 New Jersey 23.3 Texas 28.7 New Mexico 25.1 Utah 23.5 New York 24.2 Vermont 22.8 North Carolina 29.3 Virginia 25.0
North Dakota 27.9 Washington 26.4Ohio 28.8 West Virginia 31.1Oklahoma 31.4 Wisconsin 28.7Oregon 23.0 Wyoming 24.6Pennsylvania 27.4
http://www.cdc.gov/obesity/data/trends.htmlhttp://www.cdc.gov/obesity/data/trends.htmlhttp://www.cdc.gov/obesity/data/trends.htmlhttp://www.cdc.gov/obesity/data/trends.html -
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Figure 2: Percentages of Overweight and Obesity in Tennessee
__________________________
Source: (BRFSS Prevalence and Trends Data www.thecenterformichigan.net/wp-
content/uploads/2010/01/Obesity.xls)
http://www.thecenterformichigan.net/wp-content/uploads/2010/01/Obesity.xlshttp://www.thecenterformichigan.net/wp-content/uploads/2010/01/Obesity.xlshttp://www.thecenterformichigan.net/wp-content/uploads/2010/01/Obesity.xlshttp://www.thecenterformichigan.net/wp-content/uploads/2010/01/Obesity.xls -
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Notes and Definitions of Terms:
P=Prevalence and Trends Data
T= Tennessee Available Years
BMI=Weight classification by Body Mass Index (BMI)
Ov= Overweight and Obesity (BMI)
Percent (%) = Weighted Percentage
CI = Confidence Interval
n = Cell Size (Numerator
Table 3: Prevalence and Trends Data in Tennessee
Year: Tennessee
Percent CI n
1995 18.4 (16.6-20.2) 359
1996 17.4 (15.8-19.0) 508
1997 17.7 (16.1-19.3) 510
1998 19.2 (17.5-20.9) 556
1999 20.5 (18.8-22.2) 596
2000 22.9 (21.1-24.7) 656
2001 23.4 (21.6-25.2) 653
2002 24.5 (22.7-26.3) 740
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____________________
Source: BRFSS Prevalence and Trends Data available at
www.thecenterformichigan.net/wp-content/uploads/2010/01/Obesity.xls
Notes and Definitions of Terms:
P=Prevalence and Trends Data
T= Tennessee Available Years
BMI=Weight classification by Body Mass Index (BMI)
Ov= Overweight and Obesity (Ov-BMI)
Percent (%) = Weighted Percentage
CI = Confidence Interval
n = Cell Size (Numerator)
Table 3: Continued
Year: Tennessee
Percent CI n
2003 25 (23.0-27.0) 616
2004 27.2 (25.2-29.2) 933
2005 27.4 (25.4-29.4) 1245
2006 28.8 (26.8-30.8) 1195
2007 30.7 (28.5-32.9) 1428
2008 31.2 (29.0-33.4) 1453
2009 32.9 (30.9-34.9) 1674
2010 31.7 (29.7-33.7) 1730
http://www.thecenterformichigan.net/wp-content/uploads/2010/01/Obesity.xlshttp://www.thecenterformichigan.net/wp-content/uploads/2010/01/Obesity.xlshttp://www.thecenterformichigan.net/wp-content/uploads/2010/01/Obesity.xlshttp://www.thecenterformichigan.net/wp-content/uploads/2010/01/Obesity.xls -
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Many American communities are characterized by unhealthy options when it comes
to dieting and exercising. According to the Centers for Disease Control and prevention
(CDC 2008), public health approaches that make healthy options affordable and easily
available for Americans are needed. The main focus of the CDCs division of nutrition,
physical activity and obesity (DNPAO) is to create policy and environmental changes to
increase physical activity, consumption of fruits and vegetables, breastfeeding and to
reduce television viewing, consumption of sugar, sweetened beverages and high energy
dense foods. Tennessee had a population of 6,346,105 in 2010 (metro pulse 2011).
Bress 2009 says about 4.8 million of the population are adults of which thirty-six percent
are considered overweight and thirty-two percent are classified as obese.
Three in ten Tennessee adults report no leisure time for physical activity:
Only twenty-three percent of adults eat fruits and vegetables at least 5 times a day
Sixteen percent of Tennessee youth ninth through twelve grades are overweight and
another sixteen percent are obese according to 2009 youth risk behavior survey data
(http://www.cdc.gov/obesity/stateprograms/fundedstates/tennessee.html)
Only twenty-four percent of the youth ninth through twelve grade meet physical
activity recommendation levels which are 60 or more minutes of physical activity a
day
Only eighteen percent eat fruits and vegetables five times a day
Forty one percent drank one plus non diet soda a day
Thirty-eight percent watched three or more hours of television a day
http://www.cdc.gov/obesity/stateprograms/fundedstates/tennessee.htmlhttp://www.cdc.gov/obesity/stateprograms/fundedstates/tennessee.html -
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Tennessees obesity task force received CDC funding to develop a state nutrition,
physical activity and obesity plan, Eat well, play more Tennessee.
BMI
In classifying an individual as obese or not Body Mass Index (BMI) is observed
that is a heuristic proxy for human body fat based on an individuals height and weight.
Body mass index is defined as the individuals body weight divided by the square of his
or her height.
Statement of the problem
Tennessee is ranked second out of the fifty states in terms of obesity. The
epidemic of obesity took off from about 1980 and in almost all countries has been rising
excessively ever since. When the Society of Actuaries (SOA) (U.S. world news 2011)
researchers separated the economic cost of overweight and obesity to the United States in
2009, they found that it was $72 billion for overweight and $198 billion for obesity. The
findings are based on a review of papers published primarily between January 1980 and
June 2009. Tennessee alone spends $1.5 billion each year on obesity-related health costs
(Sanchez 2010). According to data from the Behavioral Risk Factor Surveillance System
(BRFSS), no state met the Healthy People 2010 objective of 15 percent, and 30 states
were 10 or more percentage points away from the objective
(http://www.obesity.org/resources-for/obesity-statistics.htm). Obesity increase risks of
acquiring diabetes, heart disease and other chronic illnesses. Obesity is now being
http://www.health.gov/healthypeoplehttp://www.obesity.org/resources-for/obesity-statistics.htmhttp://www.obesity.org/resources-for/obesity-statistics.htmhttp://www.health.gov/healthypeople -
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considered a disease, and sixty nine percent of adults and thirty nine percent of children
in Tennessee are considered obese.
Objectives
The objectives of this study are as follows:
To assess awareness levels about obesity and related issues among students in the
school of Agriculture and Consumer Sciences at Tennessee State University,
To characterize the prevalence of obesity and knowledge about it among the
students,
To discuss suggestions by the students involved in this study.
Hypothesis
It is hypothesized that awareness about obesity and its prevalence among college
students will be related to: (a) access to information about it, (b) characteristics of the
students, (c) reading food labels, (d) familiarity with USDA dietary guidelines, (e) eating
habits, and (f) exercise habits. The hypothesis will be tested using primary data collected
on the above factors these variables were looked at based on literature from Weicha et al
2006, Hasse et al 2004 and Edman et al 2005.
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Significance of the problem
This study can contribute to understanding about factors that are related or
contribute to obesity among college students in Tennessee. The study can also raise
awareness levels of obesity amongst college students. Responses received from the
participants can suggest how to go about addressing the obesity issue, in regards to as
exercise facilities, watching what is consumed; attending classes that pertain to healthy
living and dieting. This study can contribute to a better understanding of students
awareness about obesity and their suggestions to tackle the problem. Research focusing
on college students is limited in general and at the historically black colleges and
universities in particular.
Figure 3: Prevalence Percentages of Obesity Among Men and Women
The graph shows trends in the prevalence of obesity for adults aged 20to 74 years in the
United States from 1960 to 2000 as percentage of the total population.
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The rest of the thesis is organized as follows: chapter II will present review of
relevant literature that will highlight what has been done. Chapter III focuses on
methodology. This provides the hypothesis to be tested, description of data collected and
methods used in analyzing it. The last chapter will analyze data, present and discuss the
results including their implications.
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CHAPTER II
LITERATURE REVIEW
According to Nelson (2007) the transition from adolescence to adulthood is one
developmental period that may be a critical stage for weight gain. Weicha et al (2006)
came to a conclusion that television viewing is associated with exposure to food and
beverage advertising and with between meal snacking. Majority of youth and college
students watch television in their leisure time Hasse (2004). Nelsons study is the first to
examine prevalence, trends and social disparities, overweight, obesity, and class II
obesity in a nationally representative sample of college students in the United States. The
purpose of their study was to examine social disparities and behavioral correlates of
overweight and obesity overtime among college students. They took a sample of 24,613
college students 12,786 in 1993 and 11,827 in 1999 all under the age of twenty five
(mean 20.4 S.D 1.6). The questions focused on physical activity, television viewing, and
BMI analysis. Respondents reported current height in feet and inches and weight in
pounds. Self-report measures of height and weight are generally considered to be valid
and reliable for large-scale surveillance surveys. Their results were descriptive analyses
and cross tabulations which came from a program similar to SPSS and SAS. They ran
tests on gender and overweight then added television viewing to the analyses; they also
added information that pertained to the objectives. They concluded overweight rose
21.7% in 1993 to 26.8% in 1999, obesity rose 4.1% in 1993 to 6.5% in 1999, and class II
obesity rose 0.9% to 1.9%. Significantly higher rates of overweight and obesity occurred
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among students in their later years of college. Males were significantly more likely to be
overweight and obese, than their female colleagues, and out of the race classification
African American males were more obese as seen in the table below.
Table 4: Prevalence of Overweight, Obesity and Class II Obesity by
Socio-Demographic Characteristics
SelectedDemography
Sample Size OverweightBMI>=25
ObesityBMI>=30
Class IIobesity
BMI>=35
Year 1993 1999 1993 1999 1993 1999 1993 1999GenderFemale 7369 7258 13.5 20.0 2.9 5.4 1.0 2.0
Male 5417 4569 30.8 35.0 5.4 7.8 0.8 1.8
RaceWhite 10624 9307 21.5 26.7 3.9 6.2 0.7 1.7African American 568 633 33.3 38.3 11.2 13.9 4.4 5.3Asian 849 978 13.6 16.4 2.0 2.3 0.2 0.6 Native/American 745 909 23.9 30.6 3.4 8.2 0.6 2.1Hispanic 733 743 25.0 30.2 2.8 8.3 0.4 2.2
Socioeconomic positionBoth ParentsAttended College
7454 7412 20.4 25.0 3.6 5.9 0.7 1.6
One Parent (notboth) AttendedCollege
3256 2841 23.4 29.1 4.6 7.6 1.2 2.0
Neither ParentAttended College
2076 1574 23.5 31.4 4.9 7.2 1.2 2.9
Years in SchoolFirst Year 2864 2993 18.9 23.0 3.1 5.2 0.7 1.7Sophomore 2648 2845 19.5 27.3 4.0 6.7 0.8 2.5Junior 3110 2912 22.0 27.6 4.3 7.2 0.9 1.5Senior 3045 2382 23.8 27.5 4.3 5.7 1.0 1.3Fifth Year 1119 695 28.7 37.2 5.7 10.9 1.2 3.7
___________________________
Source: Disparities in overweight and obesity among U.S. college students. AmericanJournal of Health Behavior. Volume 31 issue 4, 1 July 2007, 363-373Toben F Nelson
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A study carried out by Anderson et al (2003), the transition from high school to
college may be such a critical period, because it is associated with many lifestyle changes
that can lead to weight gain, such as changes in eating habits and increased alcohol
intake. A total of 192 individuals were weighed on a digital scale and their heights were
taken in September. Only 76% of participants returned to the lab in December and
provided data on weight and eating changes during their first semester in college. At that
time they were weighed again and completed follow up questionnaires as in September.
Of the 76%, 135 provided complete data at both times they were interviewed. A subset
of participants came back and provided the same information in May. In conclusion the
percentage of participants defined as overweight or obese from September to May
doubled, so for the group provided itssafe to say the freshman year of college could be
considered a critical period for weight gain Anderson et al (2003). Anderson also stated
identifying critical periods for weight gain such as the freshman year of college and the
factors that influence them may lead to the development of effective obesity prevention
programs.
In a study carried out by Levi et al (2007) 358 college students were surveyed at
state university in the western United States to test the applicability of involvement on
issues of obesity and eating habits. What they found was that women focused more on
the types of food they ate than men. They concluded that mens food choices are fixed in
the ideology of what it means to be male and female in American society.
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In a study done by Anne house et al (2004) a cross sectional survey was carried
out with 19,298 university students from 23 countries varying in culture and level of
economic development. The study focused on leisure time physical activity, health
beliefs, and health knowledge. The study showed prevalence of inactivity in leisure time
varied with cultural and economic developmental factors, 23% north Western Europe and
United States, 30% central and Eastern Europe, 39% Mediterranean, 42% pacific Asian
and 44% developing countries. They concluded that knowledge about activity and health
was disappointing with only 40-60% of students being aware that physical activity was
relevant to risk of heart disease. In the Journal of American College Health a study was
carried out by Terry et al (2003) that zeroed in on 738 college students aged 18 to 27 to
assess overweight, obesity, dietary habits, and physical activity. They used BMI >
25kg/m^2 or BMI>85th percentile and BMI>30 kg/m^1 or BMI>95th percentile to
estimate overweight and obesity for ages less than up to 19. For the ages 20 and up they
used BMI > 25kg/m^2 and BMI>30 kg/m^2. The study gave results of overweight rates
of 21.6% and obesity rates of 4.9%, 69% of the respondents reported less than five
servings of fruits and vegetables per day, and more than 67% reported less than twenty
grams of fiber per day. The respondents also indicated that physical activity was done
less than three days a week. Most college students are not meeting dietary and physical
activity guidelines Terry et al (2003). These authors suggested the need for prevention,
interventions and increased understanding of overweight in college students.
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Edman (2005) wanted to examine the relationship between negative emotions,
body dissatisfaction, exercise, and disordered eating attitudes and behaviors among obese
college students. The participants were 190 students of which are 88 male and 102 are
female those that had a BMI above 30, were all required to take surveys. In this study
compared to Real men dont read food labels the females reported higher levels of
disorderly eating, uncomfortable with body size, and more frequent dieting, while the
males worked out more. The significance of the study carried out by Edman et al (2005)
was that body discomfort, anger discomfort, and self-discouragement went with the drive
for thinness for both males and females. They also concluded that anger discomfort is the
only factor that could predict disorderly eating in both genders. Anger management
may be an important component in treatment of disordered eating among obese young
adults Edman et al (2005).
The objectives of the study titled association between the body mass index of
first year female university students and their weight-related perceptions and practices,
psychological health physical activity and other physical health indicators. Cilliers et al
(2006) were investigating the association between the weight status of freshman female
students and various weight management-related characteristics to identify possible
components of a weight management program for students. What they looked at were
weight measured in light clothes with no shoes, and height taken with no shoes, blood
pressure, physical activity, body shape, eating attitudes, and self concept. Additional
questions included previous schooling, medication use, chronic disease, and smoking
habits. What they came up with was the management program should include
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19
information about supplement use, smoking, realistic weight goals, safe and sound
weight loss methods, weight cycling, body shape, perceptions, eating attitudes and
behaviors, self concept and physical activity Cilliers et al (2006).
In the study conducted by Sira et al (2010) they used a cross-sectional survey to
investigate the rates of overweight and obesity and eating attitudes among 582 students
with 106 male and 420 female college students. The respondents came from a
southeastern university whose age ranged from 18-25, heights and weights were self
reported for BMI calculations. Sira et al (2010) used the chi-square to determine if the
students with a BMI greater than 25 between gender and ethnic background were
significant. Males had significantly higher mean BMI than females (48.1% Vs 28.9%)
Chi-square = 15.26 with a degrees of freedom =1and p less than 0.001. According to the
report about a third (29.8%) of college students were overweight or obese. Sira et al
(2010) conducted a study of students who tried to lose weight but went about it
incorrectly. These findings call for obesity prevention intervention, lifestyle
modification, and outreach programs among college students. The study further
highlights the importance of the college years as an excellent time for health promotion.
Morrow et al (2006) wanted to investigate changes in body weight, BMI, body
composition, and fat among freshman women during first year of college. They surveyed
137 women and found they gained about 2.4 pounds, and not the myth of fifteen pounds
associated with freshmen women. Grahm et al (2002) reported that the fixation on the
freshman fifteen myth is responsible for freshmen students having negative feelings
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about their body weight and image while being more likely to categorize themselves as
being overweight.
Racette et al (2008) conducted a survey to assess height and weight changes,
exercise and dietary behaviors among college students from freshman year to the end of
the senior year. The major finding of the study was BMI increased significantly through
the four years of college. The result also suggests that if weight gain of freshman year
continued throughout the four years, it will be a dramatic increase in the incidence of
overweight and obesity among young adults.
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CHAPTER III
METHODOLOGY
Data for this study were collected from primary and secondary sources to analyze
objectives of this study. The secondary sources include books, journals, publications by
CDC, and others. Face to Face survey of graduate and undergraduate students in the
school of Agriculture and Consumer sciences were conducted in spring 2011. A total of
one hundred forty-one completed responses were received. Seventy-seven percent of
respondents were female with the balance being male.
Data Collection
Data collection involved face-to-face surveys of Agriculture and Consumer
Science students at Tennessee State University. The survey instrument was pre-tested
using a few students to get feedback to finalize it. The questions in the survey included
types of food consumed and where, height and weight, exercise habits, socioeconomic
background, awareness levels about obesity and knowledge of USDA dietary guidelines.
The data were coded, entered into the computer and analyzed using the Statistical
Package for the Social Sciences (SPSS). Descriptive and inferential statistics including
frequencies, chi-square test and analysis of variance (ANOVA) were used in explaining
results of the findings.
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The BMI data was compiled on excel spreadsheet using the following formula:
BMI=Weight (kg)/Height (M)2. For example, the BMI for an individual who is 57 and
weighs 150 pounds is given below:
BMI = Weight (kg) Height2
(m)An individual who is 5'7'' in height and weighs 150 pounds
Weight conversion (lb to kg):To convert from lbs to kg: weight in lbs divided by 2.2Example: 150 lb 2.2 = 68 kg
Height conversion (inches to meters):To convert from inches to meters: (height in inches x 2.54) 100Example: 67 x 2.54 = 170170 100 = 1.70 meters
BMI = 68 (1.7)2 = 68 2.89 = 23.5Source:http://www.acefitness.org/fitnessqanda/fitnessqanda_display.aspx?itemid=324)
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CHAPTER IV
RESULTS AND DISCUSSION
Sixty-one percent of respondents had urban background with the remaining
coming from rural areas. Of the 39% from rural areas, 10.6% were male and 28.4% were
female. For the urban background, 12% were male and 48.9% were female. In terms of
age, the results showed the following: 18-22 year old (57.7%), 23-27 (27.0%), 28-32
(7.1%), 33-37 (3.5%) and 38-42 (2.1%) only a miniscule proportion (2.1%) accounted for
those beyond the age of forty-two.
Regarding parents education 32.6% indicated their mothers had a high
school/GED level of education, 26.2% attended college but did not finish, 20.6% hold a
college degree, and 19.1% received a graduate degree. When dealing with fathers
educational level, 38.3% indicated that they received a high school diploma or GED,
18.4% had some college education, 22.0% finished college and 12.1% attained a graduate
degree.
Students who participated in the survey varied in terms of department and
concentrations. Of the 141 respondents, 73 (51.8%) were agricultural science students
and 48.2% were enrolled in the Department of Family and Consumer Sciences. Figure 4
below shows the percentage distribution of respondents in the different concentrations in
the two departments.
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Figure 4: Distribution of students enrolled in different concentrations
Not only did the students vary in terms of department and concentrations in which
they were enrolled but also differed in classification. Graduate students accounted for
27.0%. In the undergraduate category the distribution is as follows: seniors (24.8%),
juniors (22.7%), sophomore (16.3%), 9.2% and freshman. Research shows that 96.5% of
students that had taken the survey consume snacks, and over 90% of these students
consume snacks 1-10 times a day. A small proportion (3.5%) stated they consume no
snacks.
When the participants were asked about reading food labels and the types of food
they buy, a combined 74.5% indicated that they often make it a point to read food labels
or seldom read food labels. In terms of food purchased 46.1% and 26.2% purchased low
fat foods and low calorie food respectively. This may reflect that they have some
concern about their diet and healthy living.
0 10 20 30 40 50
1
2
3
4
5
Agribusiness
22.7
Food & Nutrition
7.1
Family and early
childhood
education 40.4
Plant & soil
science 17.7
Animal Science
12.1
Series1
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Table 5 shows the workout habits of the individuals in the two departments by
classification. Of the five classifications the graduate class has the most individuals with
28.9% that workout daily. The senior class that workout often 34.3%, the junior class
had 43.8% that workout sometimes, and the sophomore class works out often 21.7%.
The freshman class had the lowest total of individuals 9.2% who attempted exercising.
Table 5: Classification and Exercise Habits Cross Tabulation
Classification Daily Often Sometimes Rarely Not at all TotalFreshman (Count) 3 4 5 0 1 13
(%) within Classification 23.1 30.8 38.5 .0 7.7 100
(%) within Exercise habits 12.0 9.8 10.6 .0 14.3 9.2
(%) of Total 2.1 2.8 3.5 .0 .7 9.2
Sophomore (Count) 1 5 10 5 2 23
(%) within Classification 4.3 21.7 43.5 21.7 8.7 100
(%) within Exercise habits 4.0 12.2 21.3 23.8 28.6 16.3
(%) of Total .7 3.5 7.1 3.5 1.4 16.3
Junior (Count) 6 8 14 3 1 32
(%) within Classification 18.8 25.0 43.8 9.4 3.1 100
(%) within Exercise habits 24.0 19.5 29.8 14.3 14.3 22.7
(%) of Total 4.3 5.7 9.9 2.1 .7 22.7
Senior (Count) 4 12 11 7 1 35
(%) within Classification 11.4 34.3 31.4 20.0 2.9 100
(%) within Exercise habits 16.0 29.3 23.4 33.3 14.3 24.8
(%) of Total 2.8 8.5 7.8 5.0 .7 24.8
Graduate (Count) 11 12 7 6 2 38
(%) within Classification 28.9 31.6 18.4 15.8 5.3 100.0
(%) within Exercise habits 44.0 29.3 14.9 28.6 28.6 27.0(%) of Total 7.8 8.5 5.0 4.3 1.4 27.0
Total Count 25 41 47 21 7 141
(%) within Classification 17.7 29.1 33.3 14.9 5.0 100
(%) within Exercise habits 100.0 100.0 100.0 100.0 100 100
(%) of Total 17.7 29.1 33.3 14.9 5.0 100
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When the individuals were questioned as to whether or not they were aware of
poor diets can jeopardize health, 124 responded yes (87.9%) and 17 no (12.1%). The
graduate class had the most yes responses with 33 (86.8%) and the freshman class had the
fewest no responses, with 0 indicating that individuals are aware of poor diet but obesity
doesnt concern them. Therefore they had no reason to inquire about the issue.
Table 6: Classification Aware that Poor Diets Put Health at Risk CrossTabulation
ClassificationAware that poor diets put health at risk
TotalYes No
Freshman 13 0 13
Sophomore 19 4 23
Junior 28 4 32
Senior 31 4 35
Graduate 33 5 38
Total 124 17 141
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Table 7: Plans to Change Eating Habits Which Would Encourage Plans to
Change Eating Habits Crosstabulation
Selected Variables
Which would encourage change in eating habits
Nutrition
Education
Availabil
ity of
low cost
exercise
facilities
Reduced
portion
sizes of
foods Other Total
Yes (Count) 47 28 18 9 102
Percent within Plan to
change your eating habits
46.1 27.5 17.6 8.8 100.0
Percent within Which
would encourage change
in eating habits
71.2 82.4 75.0 60.0 73.4
Percent of Total 33.8 20.1 12.9 6.5 73.4
No (Count) 19 6 6 6 3
Percent within Plan to
change your eating habits
51.4 16.2 16.2 16.2 100.0
Percent within Which
would encourage change
in eating habits
28.8 17.6 25.0 40.0 26.6
Percent of Total 13.7 4.3 4.3 4.3 26.6
Total Count 66 34 24 15 139
Percent within Plan to
change your eating habits
47.5 24.5 17.3 10.8 100.0
Percent within Which
would encourage change
in eating habits
100.0 100.0 100.0 100.0 100.0
Percent of Total 47.5 24.5 17.3 10.8 100.0
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A question in the survey inquired about changing eating habits, and what would
help encourage change. Of those responding, 47.5 percent indicated that nutrition
education can help change eating habits while, 24.5 percent agreed that availability of
low cost exercise facilities and 17.3percent indicated reduced portion sizes of food can
help change eating habits. The category other is selected by 10.8 percent of the
respondents. The importance of more events that inform about healthy eating, free
exercise facilities, reading labels, eating more fruits and vegetables, and eating less fast
foods are underscored by the respondents.
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Table 8: Classification: Plan to Change Your Eating Habits Cross Tabulation
Plan to changeyour eating habits
Classification Yes No Total
Freshman (Count) 8 5 13
Percent within Classification 61.5 38.5 100.0
Percent within Plan to change your eating habits 7.7 13.5 9.2
Percent of Total 5.7 3.5 9.2
Sophomore (Count) 21 2 23
Percent within Classification 91.3 8.7 100.0
Percent within Plan to change your eating habits 20.2 5.4 16.3
Percent of Total 14.9 1.4 16.3
Junior (Count) 23 9 32
Percent within Classification 71.9 28.1 100.0
Percent within Plan to change your eating habits 22.1 24.3 22.7
Percent of Total 16.3 6.4 22.7
Senior Count 27 8 35
Percent within Classification 77.1 22.9 100.0
Percent within Plan to change your eating habits 26.0 21.6 24.8
Percent of Total 19.1 5.7 24.8
Graduate (Count) 25 13 38Percent within Classification 65.8 34.2 100.0
Percent within Plan to change your eating habits 24.0 35.1 27.0
Percent of Total 17.7 9.2 27.0
Total Count 104 37 141
Percent within Classification 73.8 26.2 100.0
Percent within Plan to change your eating habits 100.0 100.0 100.0
Percent of Total 73.8 26.2 100.0
When the students were asked if they had planned to change their eating habits,
73.8 said yes and 26.2 responded no. The individuals who agreed can be said to have
some knowledge of healthy diet, or unhappy with their current body build. Those who
responded no either dont care about their body build, they could be physically fit, or are
content with their current diet status.
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Table 9: Distribution Frequencies of Awareness of Obesity Problems Among
Designed Groups
Awareness Levels of ObesityProblems
A lot Some VeryLittle
None Total
Total Number of respondents 74 51 11 5 141
Percent 52.5 36.2 7.8 3.5 100.0
Awareness of the Effects of Poor DietsYes (# of resp.) 71 42 7 4 124
Percent 57.3 33.9 5.6 3.2 100.0 No (# of resp.) 3 9 4 1 17
Percent 17.6 52.9 23.5 5.9 100.0
Knowledge of Dietary GuidelinesYes (# of resp.) 52 23 0 3 78
Percent 66.7 29.5 .0 3.8 100.0 No (# of resp.) 22 28 11 2 63
Percent 34.9 44.4 17.5 3.2 100.0
Reading Food LabelsOften (# of resp.) 33 15 4 0 52
Percent 63.5 28.8 7.7 .0 100.0Seldom (# of resp.) 31 17 2 3 53
Percent 58.5 32.1 3.8 5.7 100.0 Never (# of resp.) 10 19 5 2 36
Percent 27.8 52.8 13.9 5.6 100.0
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Table 9: Continued
Distribution of Frequencies Awareness Levels of Obesity Problems
A Lot Some VeryLittle
None Total
Vegetable Consumption Habits
Yes (# of resp.) 56 26 3 2 87
Percent 64.4 29.9 3.4 2.3 100.0
No (# of resp.) 18 25 8 3 54
Percent 33.3 46.3 14.8 5.6 100.0
Exercise Habits
Daily (# of resp.) 15 8 1 1 25
PercentOften (# of resp.)
60.023
32.016
4.02
4.00
100.041
PercentSometimes (# of resp.)
56.126
39.017
4.93
.01
100.047
Percent 55.3 36.2 6.4 2.1 100.0
Seldom (# of resp.) 8 8 4 1 21
PercentNever (# of resp.)
38.12
38.12
19.01
4.82
100.07
Percent 28.6 28.6 14.3 28.6 100.0
Plan to Change Eating HabitsYes (# of resp.) 58 39 5 2 104
Percent 55.8 37.5 4.8 1.9 100.0
No (# of resp.) 16 12 6 3 37
Percent 43.2 32.4 16.2 8.1 100.0
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Table 10: Results of Chi-Square Tests of Awareness of Obesity Problems Among
Designed Groups
Pearson Chi-Square Test Likelihood Ratio Test2-Stat DF P-Value 2-Stat DF P-Value
Awareness of the Effect of Poor Diet
12.40 3 0.006 11.73 3 0.008
Knowledge of Dietary Guidelines
22.51 3 0.000 26.86 3 0.000
Reading Food Labels
14.87 6 .021 16.995 6 .009
Vegetable Consumption Habits
15.11 3 .002 15.26 3 .002
Exercise Habits
21.38 12 .045 14.70 12 .258
Plan to Change Eating Habits
8.50 3 .037 7.503 3 .057
Analysis of Variance of Awareness of Obesity Problem
The one-way Analysis of Variance (ANOVA) was applied to assess how the
awareness levels of obesity vary among different groups that was defined according to a
given group or categorical variable. ANOVA uses least squares to fit the linear models.
The model of the one-way ANOVA is:
(1)
Yij = m+a2 +a3 + ...+aj + ...+aJ +eij
Where Yij denotes the dependent variable-the awareness level of obesity, ranging from 1
to 4, for each individual i in the sample that belongs to group j (j=1,,J). The sample
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can be divided intoJgroups according to a categorical variable. For example, the sample
can be divided into three groups: respondents who often, seldom and never read food
labels. Where is the intercept to be estimated, 2 J is fixed-effects coefficients to be
estimated, which measures the deviation of the average awareness level of group j from
the average awareness of the omitted group. Group 1 is the omitted or base group to be
compared with. ij represents the error term which is assumed to be independently and
identically distributed (i.i.d).
Define
Yjas the average awareness of obesity of group j, and
Y is the overall
average awareness of the whole sample. The total variation in obesity awareness among
respondents in the sample is measured by the total sum of squares (TSS) as
(2)
SST= (Yij -Y)2
ji
The between-group sum of squares (SS), or equivalently SS of the model (1)
(SSR) measures the variation in obesity awareness between groups, and is defined as
(3)
SSR = (Yj -Y)2
j
The variation of obesity awareness within a group is measured by the within-
group SS. It is also the SS of residuals of the model (1) (SSE), which indicates the
variation in obesity awareness due to factors, observed or unobserved, that are not
included in model (1). SSEis computed as SSE= SST SSR.R2 measures to what extent
the total variation in obesity awareness in the sample is explained by differences in
obesity awareness between groups, i.e.,R2 = SSR/SST.
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The F-test is applied to test whether the average awareness levels of obesity
problems are jointly equal among groups. The null hypothesis of F-test can be written as
2= 3= =J=0. The F-test is also equivalent to testing whether or not the between-
group variation in obesity awareness is significant in explaining the total variation in
obesity awareness across individuals in the entire sample (Snedecor and Cochran, 1989).
F-test statistic is the ratio ofSSR/J 1 overSSE/NJ.
Furthermore, the F-test serves as a robustness check to the Pearson Chi-square
test, which assumes specific distribution assumption. In comparison, F-test is not limited
by specific distributions, and is applied in this study because the sample has sufficient
number of observations. If the results of F-tests are consistent with those of the Pearson
Chi-square test, it suggests that the findings are robust to the tests and test statistics.
In the following analysis, the ANOVA models was estimated by designating the
awareness of obesity problems as the dependent variables as specified in model (1), and
selecting the knowledge of USDA dietary guidelines, awareness of the effects of poor
dieting, reading of food labels, vegetable consumption, exercise habits, and intention to
change eating habits, respectively, as the categorical variable by which the sample was
divided into definite groups.
The results reported in table 11 include (i) the sum-of-squares results of ANOVA,
andR2 as the indicator for goodness-of-the-fit of the model; and (ii) the results, i.e., F-
statistics and the resultant p-values, for the F-test for the model significance or the
significance of between-group differences.
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Table 11: ANOVA Results of Awareness Level of Obesity Problems
Sum of Squares (SS) F-Test
DF SS R2 F-Stat P-Value
Awareness of the Effects of Poor Dieting
Between-group (SSR) 1 5.90 6.93 10.35 0.00
Within-group (SSE) 139 79.18 93.04
Total (SST) 140 85.08 100
Knowledge of Dietary Guidelines
Between-group (SSR) 1 7.98 9.38 14.40 0.00
Within-group (SSE) 139 77.09 90.62
Total (SST) 140 85.08 100
Reading Food Labels
Between-group (SSR) 2 6.07 7.17 5.29 0.01
Within-group (SSE) 137 78.62 92.83
Total (SST) 139 84.69 100
Vegetable Consumption
Between-group (SSR) 1 7.97 9.37 14.37 0.00
Within-group (SSE) 139 77.11 90.63
Total (SST) 140 85.08 100
Exercise HabitsBetween-group (SSR) 4 7.45 8.76 3.27 0.01
Within-group (SSE) 136 77.63 91.24
Total (SST) 140 85.08 100
Plan to Change Eating Habits
Between-group (SSR) 1 3.60 4.23 6.14 0.01
Within-group (SSE) 139 81.48 95.77
Total (SST) 140 85.08 100
The first set of results show that the awareness levels of obesity are significantly
heterogeneous, at a better than 1 significance level, between those who were aware that
poor dieting could put health at risk and those who had no awareness. This result is
consistent with that of previous Chi-squared tests. This between-group difference
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contributed a small 6.9 percent of the overall differences in obesity awareness across
individuals in the sample. It should be noted that this implication is drawn based on the
one-way ANOVA that analyzes one categorical variable, while leaving other observed
and unobserved factors in the residual term in the model (1). This applies to all of the
following analysis.
The survey question was designed to see whether people would associate poor
diets and its adverse effect with obesity. The premise is that individuals who are aware of
obesity problems would consent that poor diets could put health at risk, and vice versa.
Therefore, it is expected that variations in awareness of the adverse effects of poor diets
would explain little of variations in awareness of obesity problems among respondents.
The low R2 measure supports this hypothesis. The evidence in the frequency table, in
addition, supports this hypothesis. Of all 141 respondents, 113 had a lot or some
awareness of obesity knew about the adverse effects of poor diets; and 5 had very little or
none awareness of obesity also knew nothing about the adverse effects of poor diets.
The second set of results indicates that respondents who had knowledge about
dietary guidelines and who did not had a significantly different degree of obesity
awareness. The null hypothesis ofF-test that average awareness is equal between these
two groups is rejected at a better than 1 significant level. R2 indicates that the difference
in obesity awareness between two groups contributed 9.38 percent of the overall
differences in obesity awareness across individuals in the sample. Though with moderate
degree based on R2 measure, this between-group difference in obesity awareness has
statistical significance in explain the total sample variation in obesity awareness
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according to F-test. The result of F-test, which suggests heterogeneity in obesity
awareness between respondents with and without the knowledge of dietary guidelines, is
consistent with that of the Pearson Chi-square test. The findings are, therefore, shown to
be robust to different tests and test statistics.
The results on distribution frequencies further show how the respondents in these
two groups differ in their awareness of obesity problems. More than half of the
respondents (78 out of 141 respondents) knew about the dietary guidelines, and majority
of them had high (52 respondents) or some (23 respondents) awareness of obesity
problems, and only a few had little (zero) (11 respondents) or none awareness of obesity
problems. On the other hand, three-quarters of the rest 68 respondents, declaring no
knowledge of dietary guidelines, were aware of obesity problem to some degree or more.
Specifically, 22, 28, 11, 2 respondents had a lot, some, little, and none awareness of
obesity.
Taken the analysis of distribution frequencies and ANOVA together, the results
and findings are summarized as follows. First, the results suggest that respondents had a
higher degree of awareness of obesity problems than of dietary guidelines. Second,
majority (88.65 percent) of the respondents had a lot or some degree of awareness of
obesity problems, regardless of whether they knew or did not know about dietary
guidelines. Therefore, the difference in obesity awareness between these two groups did
not contribute much to explaining the overall variation across individuals in the sample.
The modestR2 measure is, hence, expected.
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Third, the significant difference in obesity awareness between respondents with
and without the knowledge of dietary guidelines, according to F-test, is observed within
two awareness levels: (i) for those 74 respondents who were highly aware of obesity
problems, two-thirds of them knew dietary guidelines; and (ii) all 11 respondents who
knew very little about obesity problems did not know about dietary guidelines. This
finding suggests respondents who knew about dietary guidelines were more likely to
know a lot about obesity problems; and those who had no knowledge of dietary
guidelines mostly likely knew little about obesity problem. The evidence implies a
positive association between the knowledge of dietary guidelines and the awareness of
obesity problem.
The analysis above examines the linkage between the awareness of obesity
problems with knowledge and awareness of poor or healthy diets; and the following
analysis assesses whether and how the awareness of obesity problems is associated with
observed behavior or actions, namely reading food labels, consuming vegetables, and
exercise. This confirms the hypothesis that individuals who are more aware of obesity
problems would be more likely to read food labels, consume vegetables on a daily basis,
and exercise regularly.
The ANOVA results pertaining to reading food labels show that the awareness of
obesity is significantly different among these three groups that never, seldom, or often
read food labels. Nevertheless, the difference in awareness levels among these three
groups only explained 7.17 percent of the overall differences in awareness levels across
individuals. From the results of the distribution frequencies, the evidence was not strong
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or clear that the awareness of obesity were different between those who made a point to
read labels and who seldom read food labels. However, it was evident that the awareness
of obesity differed among those who often read labels and those who never did.
Therefore, the heterogeneity in the obesity awareness most likely is explained by the
difference between those who often read labels and those who did not.
The results show that individuals who were aware of obesity problem reflected
their awareness to some extent in behavior as reading food labels in this case. Forty-
seven out of 124 respondents (37.9 percent) who had some or a lot awareness of obesity
said that they often made a point to read labels. Nevertheless, the rest seldom or never
read food labels even though they were aware of obesity problems. On the other hand, the
result was as expected that most respondents who had little or no awareness of obesity
problems seldom or never read labels. Four respondents who had little awareness gave
some surprising answers that they often read food labels, which might be motivated by
other causes to read labels.
In the case of vegetable eating habits, the R2 measure indicates that the difference
in obesity awareness respondents who eat two servings of vegetables daily or not
contributed only 9.3 percent of the total variations in obesity awareness across
individuals in the sample; whereas other factors explain the rest 90.7 percent of the
variations in obesity awareness. The results show that the null hypothesis of the F-test is
rejected at the 5 significant level (P value = 0.000), which indicates that the awareness
levels of obesity are significantly different between people with different vegetable
consumption behavior. Taken together with R2 measure, the results suggest that obesity
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awareness was significantly different between the two groups; however, this between-
group difference contributed merely 9.3 percent of the overall differences in obesity
awareness across individuals in the sample.
Based on the results of distribution frequencies, this study found that awareness of
obesity problems is positively associated with vegetable consumption habits, with a
higher degree than with label behavior. That is 65.5 percent of respondents who had some
or a lot awareness of obesity also consumed two servings of vegetables daily. In addition,
82 out of 87 respondents who consumed two servings of vegetables daily, and 43 out of
54 who did not consume two servings of vegetables daily all had a lot or some awareness
of obesity problems. Hence, the difference in vegetable consumption behavior did not
contribute much in explaining the differences in obesity awareness across individuals,
and therefore, the lowR2 measure.
When the ANOVA test was ran on exercise habits, this study found a significant
heterogeneity in obesity awareness among these five groups. The results show that the
null hypothesis that average mean will be equal amongst groups of the F-test is rejected
with a 1.4 percent significance level, which indicates that the awareness levels of obesity
are significantly different between individuals whose exercise habits vary. This between-
group difference contributed merely 8.7 percent of the overall differences in obesity
awareness across individuals in the sample. The results of distribution frequencies show
that individuals who were aware of obesity problem were very likely to engage in some
exercise routine. Out of 125 respondents who had some or a lot of obesity awareness, 105
(84) were involved in exercises daily, often, or sometimes. In comparison, 50 or 8 out of
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16 respondents who had little or no awareness of obesity rarely or never exercises at all.
Because the majority of respondents who practiced some exercise routine also had some
or a lot of awareness of obesity problems, it is expected that differences in awareness
levels among groups with different exercise habits would explain in a mild degree the
overall variations in obesity awareness.
Finally, the study examined whether and how individuals awareness of obesity
problems would associate with individuals intention to alter their behavior, explicitly the
survey question asks about individuals plan to change their eating habit. The awareness
levels of obesity are significantly different between two groups of those who planned to
change dietary habits and those who did not. This between-group difference contributed a
minuscule 4.2 percent of the overall differences in obesity awareness across individuals
in the sample. The results show that the more awareness of the obesity problem, the more
individuals are prone to change their eating habits. For the 74 individuals who had a high
degree of awareness, 58 indicated that they planned to change; and for the 51 respondents
who had some awareness, 39 indicated they intended to change. The respondents who
had a lot or some awareness of obesity problem may already have healthy eating habits.
Therefore, the evidence that the rest of 28 who responded that they did not plan to change
did not necessarily indicate that awareness did not affect their dietary habits. For those 16
respondents who had little or no awareness of obesity, seven indicated that they would
change their eating habits.
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Conclusions:
The analysis of distribution frequencies, Chi-squared tests, and ANOVA
estimations were conducted to examine whether and how individuals awareness of
obesity problems are associated with their knowledge about healthy or poor diets, with
their observed behavior or life style, and with their intentions to change their current
habit.
First, the study examined the linkage between the awareness of obesity problems
with knowledge and awareness of the adverse effects of poor diets and knowledge of the
dietary guidelines. The results show that most respondents associated obesity problems
with the adverse effects of poor diets. The results also indicate respondents who knew
about dietary guidelines were more likely to know a lot about obesity problems; and
those who had no knowledge of dietary guidelines mostly likely knew little about obesity
problem. The evidence suggests that respondents had a higher degree of awareness of
obesity problems and the adverse effects of poor diets, than their awareness of dietary
guidelines. Consider dietary guidelines provide information on healthy diet, whereas
obesity problems relate to the adverse effects of poor diet. It implies that respondents
were more aware of obesity problems, poor diets and ensuing adverse effects, than of
healthy diets and related effects.
Second, this study assesses whether and how the awareness of obesity problems is
associated with observed behavior or actions, namely reading food labels, consuming
vegetables, and exercise. The hypothesis that individuals who are more aware of obesity
problems would be more likely to read food labels, consume vegetables on a daily basis,
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and exercise regularly was tested. The results show that individuals who were aware of
obesity problems revealed their awareness in their life-style choices and behavior.
Namely, for respondents who had some or a lot awareness of obesity problems, 84
engaged in exercises daily, often, or sometimes, 65.5 percent consumed two servings of
vegetables daily, and 37.9 percent often made it a point to read food labels.
Finally, the study evaluated the association between the awareness of obesity
problem with stated intention to change behavior in the future. The findings indicate that
individuals who had some and high awareness of obesity problems intended to make
changes in their dietary habits, regardless whether or not they were practicing healthy
diets at the time. In contrast, 50 of those who had very little or no awareness of obesity
problem indicated that they had no plans to change their eating habits. This suggests that
the awareness levels of obesity problem are likely to influence individuals intention to
change their current dietary behavior.
Table: 12 BMI Among Students
Frequency Percent Valid Percent
Cumulative
Percent
Valid .00 37 26.2 26.2 26.2
1.00 104 73.8 73.8 100.0
Total 141 100.0 100.0
Table 12 shows that of the 141 respondents 26.2 percent (37) of them are classified as
obese, and the other 73.8 percent (107) did not respond to the weight question, are
overweight, underweight or normal weight. Of the 26.2 percent it can be assumed that
they have little or no awareness about the obesity issue, simply because they are obese.
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CHAPTER V
SUMMARY AND RECOMMENDATIONS
This study focused on the awareness levels of obesity amongst Tennessee State
University Agricultural and Consumer science students. Chapter I described the obesity
issue nationally and in Tennessee the United States Center for Disease Control (CDC)
states more than one third of adult Americans are obese. Approximately 300,000 deaths
a year are due to obesity, which puts it as the second leading cause of preventable deaths
in the United States. Economic cost of overweight and obesity to the United States in
2009 was $72 billion and $198 billion respectively. Of 6,346,105 people in Tennessee
about 4.8 million are adults of which 36 percent are considered overweight and 32
percent are classified as obese. The above data show the magnitude of the obesity
problem and the need to increase awareness about it. In chapter II literature pertaining to
awareness levels of obesity, and measures that should be taken to address the issue
amongst college students are examined. The literature review also helped in identifying
research gaps involving university students in general and those attending Historically
Black Colleges and Universities in particular.
Chapter III outlined the methodology used in this study. The data were collected
in spring semester of 2011 through face to face survey of graduate and undergraduate
students in the school of Agriculture and Consumer Sciences. Hypothesis were
developed; data were analyzed using SPSS-PC, in addition to generalizing descriptive
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statistics, Chi-square test and Analysis of Variance (ANOVA) were used to conduct
quantitative analyses of the data.
The first objective was assessing awareness levels of obesity amongst Tennessee
State University Agricultural and consumer science students. The study provided that
Tennessee State University agriculture and consumer science students who read food
labels, exercise, have knowledge of healthy eating guidelines, were aware of the obesity
problem. The second objective determined the obesity levels amongst the students in the
two departments. The study found that 27 of the 141 respondents fall in the obese
category.
The final objective was to discuss the opinions of survey respondents of ways
they feel that will raise awareness levels of obesity. The findings indicated that
availability of more free exercise facilities, less consumption of food from restaurants,
attending nutrition classes, and more consumption of healthier foods can contribute to
dealing with the obesity issue.
Recommendations for Future research
This study can provide some insights on the subject of awareness about obesity
and strategies to tackle it based on responses received from the study group/college
students. An expanded study covering a mix of universities and states can yield
comparative results. Given that factors contributing to obesity are many, a concerted
effort involving different Government and non government agencies, communities,
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university researchers, outreach professionals and schools, is critical to make progress in
tackling the obesity problem.
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