AN INVESTIGATION OF FACTORS AFFECTING THE OVERWEIGHT STATUS 
OF ALABAMA HIGH SCHOOL ADOLESCENTS 
 
Carolyn Davis Corliss 
 
 
 
 
 
A Dissertation 
 
Submitted to 
 
The Graduate Faculty of 
 
Auburn University  
 
In Partial Fulfillment of the 
 
Requirements for the 
 
Degree of 
 
Doctor of Education 
 
 
 
 
 
 
Auburn, Alabama 
 
August 8, 2005 
 
 iii
 
 
 
 
 
 
 
 
 
VITA 
 
 
 Carolyn Davis Corliss, daughter of the late Sydney Troy Davis and Constance 
Morissette Davis, was born September 20, 1954, in Demopolis, Alabama. She graduated 
from Troy State University with a Bachelor of Science degree in 1978. She has teaching 
degrees in Health and Physical Education and Art Education. She taught in the Troy City 
School system before moving to Atlanta, Georgia. She moved to Montgomery, Alabama 
in 1992, where she began working for Auburn University Montgomery, as the Director of 
Field and Laboratory Programs in the School of Education. She received the Master of 
Education degree in Exercise Science from Auburn University Montgomery in 1997. In 
1997, she began teaching adjunct classes for the department of Foundation, Secondary, 
and Physical Education. She has one married daughter, Janel Morissette Corliss-Gay.  
 
 iv
 
 
 
 
 
 
 
 
 
DISSERTATION ABSTRACT 
AN INVESTIGATION OF FACTORS AFFECTING THE OVERWEIGHT STATUS 
OF ALABAMA HIGH SCHOOL ADOLESCENTS 
 
Carolyn Davis Corliss 
Auburn University, August 8, 2005 
(M.S., Auburn University ? Montgomery, 1997) 
(B.S., Troy State University 1978) 
 
117 Typed Pages 
Directed by Dr. James E. Witte 
 
 
Obesity in children and adolescents has reached epidemic proportions in the 
United States. According to the National Center for Health Statistics (NCHS, 2000) the 
percentage of overweight young people in the United States has doubled since 1980, 
currently affecting one in seven children and adolescents. 
Current national nutrition surveillance data suggest that the diet of adolescents is 
putting them at risk for cardiovascular disease, cancer, and osteoporosis, based on their 
intakes of saturated fat, total fat, fruits, vegetables, fiber, sodium, and soft drinks (CDC, 
2004). In addition, the United States is experiencing an epidemic of overweight 
conditions that extends to the adolescent population; some of the related factors may be 
an excess in energy intake, low levels of physical activity, and high levels of sedentary 
 v
behaviors. The intent of this research is to investigate these three variables and their 
relationship to the overweight status of Alabama high school adolescents.  
This study will explore three lifestyle and environmental risk factors that relate to 
adolescent overweight status. Using the 2003 Youth Risk Behavior Survey results this 
study examined the relationship between television viewing, physical activity and fruit 
and vegetable consumption and overweight status of Alabama high school adolescents.  
The Youth Risk Behavior Survey (YRBS) was completed by 1088 students in 39 
public high schools in Alabama during Spring 2003. Students participating in the survey 
completed a self-administered, anonymous, 87 item questionnaire. Adolescents attending 
the ninth, tenth, eleventh, and twelfth grades in Alabama were included in this study.  
 Results indicated that race, gender, grade in school, television viewing, physical 
activity levels and fruit and vegetable consumption were not statistically significant 
predictors for body mass index using the 2003 Youth Risk Behavior Survey.  
 vi
 
 
 
 
 
 
 
 
 
ACKNOWLEDGEMENTS 
 
 
 I could not have accomplished a project of this magnitude without the 
encouragement of many people. It has been both an honor and a privilege to work with 
the members of my committee. Your support, constructive comments, guidance, and 
open door policy has made this project manageable and successful. 
 Dr. James Witte, as chair of my committee, you have been outstanding in every 
way. Your insights, guidance, and editing are much appreciated. Words simply could not 
begin to express the thanks for all that you have done to make my graduate school 
experience a pleasant, meaningful, and successful endeavor. Thank you so much for 
providing me with so many opportunities to succeed professionally. 
 Dr. Maria Witte, I have never met a more encouraging and caring individual. 
Your enthusiasm, knowledge, and mentoring have been a great benefit to me. You are a 
wonderful person. Thank you. 
 Dr. Hank Williford, you have a gift for making the intimidating statistics process 
manageable. I appreciate the hours you devoted to helping me wade through and better 
understand the data. 
 Dr. Allen Dyal, you have been one of my biggest supporters from the very 
beginning. Your continuous insistence for me to begin the doctorate program and 
believing in me will always be remembered and appreciated. Thank you. 
 vii
 I have many friends and AUM colleagues who have encouraged me in this 
endeavor. I especially would like to thank Drs. Pam Stockinger, Shelly Bowden, and 
Michele Olson for their unwavering support and encouragement throughout this process. 
You epitomize true friendship. I could not have possibly completed this program without 
the support from the entire education faculty at AUM. Thank you for your patience 
during this process.  
 Lastly, I would like to thank my daughter, Janel Morissette Corliss-Gay for her 
patience and confidence in me. Janel has stood by me every step of the way prodding me 
forward and never allowing me to give up. Her positive influence has taught me more 
than she will ever know. I love you with all my heart.  
 
 viii
 
 
 
 
 
 
 
 
 
 Style manual used:   Publication Manual of the American Psychological   
Association, 5
th
 ed. (2001)          
 
 Computer software used:     Microsoft Word XP,       
             
 
  
 
 ix
 
 
 
 
 
 
TABLE OF CONTENTS 
 
Page 
 
LIST OF TABLES..................................................................................................... xii 
 
CHAPTER 
 
I. INTRODUCTION ......................................................................................... 1 
 
Background of the Problem........................................................................... 1 
Importance of the Study ................................................................................ 4 
Purpose of the Study...................................................................................... 4 
Data Source ................................................................................................... 5 
Research Questions ....................................................................................... 6 
Limitations of the Study ................................................................................ 6 
Assumptions of the Study.............................................................................. 7 
Definition of Terms ....................................................................................... 7 
Summary ....................................................................................................... 9 
 
II. REVIEW OF LITERATURE ........................................................................ 10 
 
Purpose of the Study...................................................................................... 10 
Research Questions ....................................................................................... 11 
Theoretical Foundations of Adolescent Development .................................. 12 
 
 Models and Theories.......................................................................... 12 
 Environmental Theories..................................................................... 13 
 Organismic Theories.......................................................................... 14 
 Psychodynamic Theories ................................................................... 15 
 
Diagnosis of Obesity ..................................................................................... 16 
 
 Factors Associated with Overweight Conditions............................... 18 
 Overweight Conditions and Television Viewing............................... 18 
 Overweight Conditions and Physical Activity................................... 20 
 Overweight Conditions and Eating Behaviors................................... 24 
 Childhood Overweight Conditions and Adult Obesity...................... 33 
 
 x
Summary ....................................................................................................... 36 
 
III. METHODS .................................................................................................... 38 
 
Purpose of the Study...................................................................................... 38 
Description of Study Participants.................................................................. 39 
Research Questions ....................................................................................... 39 
Research Variables ........................................................................................ 40 
An Overview of the Youth Risk Behavior Survey (YRBS).......................... 41 
 
Background and Rationale................................................................. 41 
Purpose of the YRBS......................................................................... 42 
Initial Questionnaire Development.................................................... 42 
Questionnaire Revisions.................................................................... 44 
Questionnaire Reliability and Validity.............................................. 44 
Sampling, Weighting, and Response Rates....................................... 45 
 
Data Collection.............................................................................................. 47 
Research Design ............................................................................................ 47 
Summary ....................................................................................................... 48 
 
IV. RESULTS ...................................................................................................... 50 
 
Purpose of the Study...................................................................................... 51 
Results ........................................................................................................... 52 
 
Results of Research Question One .................................................... 52 
 
 Race........................................................................................ 54 
 Grade Levels .......................................................................... 55 
 Vigorous Physical Activity Level.......................................... 55 
 Moderate Physical Activity Levels........................................ 57 
 Fruit and Vegetable Consumption ......................................... 57 
 Television Viewing................................................................ 58 
 
Results of Research Question Two.................................................... 58 
 
 Gender.................................................................................... 59 
 Race........................................................................................ 60 
 Grade Level............................................................................ 60 
 Television Viewing................................................................ 60 
 
Results of Research Question Three.................................................. 61 
 
 Gender.................................................................................... 63 
 xi
 Race........................................................................................ 63 
 Grade Levels .......................................................................... 64 
 Vigorous Physical Activity Levels ........................................ 64 
 Moderate Physical Activity Levels........................................ 64 
 
Results of Research Question Four.................................................... 66 
 
 Gender.................................................................................... 67 
 Race........................................................................................ 68 
 Grade Levels .......................................................................... 68 
 Fruit and Vegetable Consumption ......................................... 68 
 
Summary ....................................................................................................... 69 
 
V. SUMMARY, DISCUSSION, AND RECOMMENDATIONS .................... 72 
 
 Purpose of the Study ...................................................................................... 72 
 Summary........................................................................................................ 73 
 Discussion...................................................................................................... 75 
 Limitations ..................................................................................................... 77 
 Recommendations.......................................................................................... 78 
 
REFERENCES .......................................................................................................... 80 
 
 
 
 
 
 xii
 
 
 
 
 
 
 
 
 
LIST OF TABLES 
 
Table 
 
 1 Odd Ratios (OR) and 95% Confidence Intervals (CI) for 
  Vigorous Physical Activity Levels, Moderate Physical 
  Activity Levels, Fruit and Vegetable Consumption, and 
  Television Viewing (TV) of Alabama High School 
  Adolescents............................................................................................... 53 
 
 2 Prevalence of Body Mass Index (BMI) and Confidence 
  Intervals (CI) for Alabama High School Adolescents.............................. 56 
 
 3 Odd Ratios (OR) and 95% Confidence Intervals (CI) for 
  Television Viewing (TV) for Alabama High School 
  Adolescents .............................................................................................. 59 
 
4 Prevalence of Body Mass Index (BMI) and Confidence 
  Intervals (CI) for Alabama High School Adolescents.............................. 61 
 
5 Odd Ratios (OR) and 95% Confidence Intervals (CI) for 
  Vigorous Physical Activity Levels (VAL) and Moderate 
  Physical Activity Levels (MAL) for Alabama High 
  School Adolescents .................................................................................. 62 
 
6  Prevalence of Body Mass Index (BMI) and Confidence 
  Intervals (CI) for Alabama High School Adolescents.............................. 65 
 
 7 Odd Ratios (OR) and 95% Confidence Intervals (CI) for 
  Fruit and Vegetable Consumption for Alabama High 
  School Adolescents .................................................................................. 67 
 
 8 Prevalence of Body Mass Index (BMI) and Confidence 
  Intervals (CI) for Alabama High School Adolescents.............................. 69 
 
 1
 
 
 
 
 
 
 
 
 
I. INTRODUCTION 
 
Background of the Problem 
Obesity in children and adolescents has reached epidemic proportions in the 
United States. According to the National Center for Health Statistics (NCHS, 2000), the 
percentage of overweight young people in the United States has doubled since 1980, 
currently affecting one in seven children and adolescents. Overweight conditions for 
children and adolescents is estimated by the age and sex specific 95
th
 percentile of body 
mass index (BMI) compared to the population in the National Health Examination 
Surveys (NHES) II and III, measured between 1963 and 1970 (Berkowitz & Stunkard, 
2002; Himes & Dietz, 1994; Troiano & Flegal, 1998; Troiano, Flegal, Kuczmarski, 
Campbell, & Johnson, 1995). Children and adolescents between the 85
th
 and 95
th
 
percentiles of BMI are described as at risk for overweight. The incidence and prevalence 
of obesity and overweight conditions are increasing despite efforts to prevent and treat 
this condition (Berkowitz & Stunkard, 2002). 
According to the 1999 National Health and Nutrition Examination Survey 
(NHANES) and Centers for Disease Control [CDC], 2001 approximately 13% of children 
age 6 to 11 years old and 14% of children age 12 to 19 years old are overweight (body 
mass index [BMI] values greater than the 95
th
 percentile). The prevalence of overweight 
children has more than doubled since the first NHANES, which was conducted over 30 
 2
years ago. According to the National Center for Health Statistics (NCHS, 2000), over the 
past 20 years, the percentage of overweight adolescents has nearly tripled from 5% to 
14%. Numerous studies have investigated such detrimental effects of overweight children 
as heredity, dietary intake, exercise fitness level, and social environment (DeLany, 1998; 
Faith, Pietrobelli, Nenez, Heo, Heymsfield, & Allison, 1999; Francis, Bope, MaWhinney, 
Czajka-Narins & Alford, 1999; Gazzaniga & Burns, 1993; Perusse & Bouchard, 2000; 
Tucker, Selijaas & Hager, 1997; Whitaker, Wright, Pepe, Seidel & Dietz, 1997). 
According to the United States Department of Health and Human Services (2001), 
presently one of every seven children in the United States is classified as being 
overweight (defined as a body mass index [BMI] above 95% for age) and being 
overweight has been shown to track from childhood through adolescence and into 
adulthood. Thus, children who are overweight are more likely to become overweight as 
adults (Freedman, Khan, Dietz, Srinivasan, & Berenson, 2001; Guo & Chumlea, 1999; 
Guo, Roche, Chumlea, Gardner, & Siervogel, 1994; Guo, Wu, Chumlea, & Roche, 2002; 
Stephens, Harrison, Wilson, Ringler, & Robinson, 2003), with all the morbidity 
associated with being overweight, such as diabetes hypertension, hyperlipidemia, and 
coronary artery disease (Calle, Thun, & Petrelli, 1999). Adolescents who are overweight 
are at risk for being overweight or obese adults. One quarter to one half of individuals 
who are overweight in adolescence remain overweight or obese in adulthood (Charney, 
Goodman, McBride, Lyon, & Pratt, 1976; Freedman, Shear, Burke, Srinivasan, Webber, 
Harsha, & Berenson, 1987; Gam, 1995; Must & Strauss, 1999; Whitaker, Wright, Pepe, 
Seidel & Dietz, 1997). The prevalence of overweight and obese conditions continues to 
increase in the United States adult population (CDC, 1994; Kuczmarski, Flegal, 
 3
Campbell, & Johnson, 1994; Troiano, Flegal, Kuczmarski, Campbell & Johnson, 1995). 
In the twelve years between the second National Health and Nutrition Examination 
Survey (NHANES II, 1976 through 1980) and NHANES III (1988 through 1991), 
(Troiano, Flegal, Kuczmarski, Campbell & Johnson, 1995) the prevalence of overweight 
conditions in United States adults increased from 25% to 33%. The prevalence of 
overweight conditions also increased to similar magnitudes among all sex and age groups 
of children and adolescents.  
Childhood overweight status represents the most prevalent nutritional disease 
among youth in the United States (CDC, 1999; Gazzaniga & Burns, 1993). 
Epidemiological data on the prevalence of overweight status can be linked to the societal 
and cultural changes seen within our population and communities in recent decades. 
Societal factors have undoubtedly been pivotal in the increase of overweight status in 
adolescents. Fruhbeck (2000) suggested that the increasing prevalence of overweight 
people reflects a population and cultural shift towards positive energy balance. There has 
been a move towards sedentary (low activity) lifestyles in children, an increase in 
television viewing, changes in eating habits, choices of transport, and other cultural 
signifiers that lifestyle and environment have impacted the physical energy output of 
adolescents. Children in the United States are less active and more overweight than ever 
before (National Center for Health Statistics, 2000). Currently, 40 percent of United 
States children five to eight years of age have at least one risk factor for heart disease 
(Faigenbaum, 1998), and one in eight is considered overweight. While the health effects 
of this rise in overweight status will not be known for years (Hill & Throwbridge, 1998), 
the time to act is now because risk factors track from childhood to adolescence (Marshall, 
 4
Sarkin, Sallis, & McKenzie, 1998) to adulthood (Harsha, 1995; Nieto, Szklo, & 
Comstock, 1992). To overcome this pandemic of sedentary behavior and resultant 
obesity, multiple factors must be addressed.  
 
Importance of the Study 
This study is important because overweight conditions in children and adolescents 
pose a national health challenge. Thus, it is prudent to examine the lifestyle and 
environmental threats that offset the balance between energy intake and expenditure so 
that interventions may be effective in reducing the alarming increase in overweight status 
and related risk factors.  
 
Purpose of the Study 
Intervention in the epidemic of adolescent overweight conditions is critical if we 
are to reduce the problem. Current national nutrition surveillance data suggest that the 
diet of adolescents is putting them at risk for cardiovascular disease, cancer, and 
osteoporosis, based on their intakes of saturated fat, total fat, fruits, vegetables, fiber, 
sodium, and soft drinks (CDC, 2004). In addition, the United States population is 
experiencing an epidemic of overweight conditions that extends to the adolescent 
population; some of the related factors may be an excess in energy intake, low levels of 
physical activity, and high levels of sedentary behaviors. The intent of this research was 
to study these three variables and their relationship to the overweight status of Alabama 
high school adolescents.  
 5
This study explored three lifestyle and environmental risk factors that relate to 
adolescent overweight status. Using the 2003 Youth Risk Behavior Survey results, this 
study examined the relationship between television viewing, physical activity and fruit 
and vegetable consumption, and overweight status of Alabama high school adolescents.  
 
Data Source 
This study analyzed data from the 2003 national school based Youth Risk 
Behavior Survey (YRBS), part of the Youth Risk Behavior Surveillance System 
(YRBSS) implemented by the Centers for Disease Control and Prevention (CDC) to 
monitor the prevalence of priority health risk behaviors among youth. The YRBS was 
developed in 1989 by the CDC to monitor health risk behaviors that contribute to the 
leading causes of mortality, morbidity, and social problems among youth and adults in 
the United States. Data from the YRBSS are used to develop policies and programs to 
prevent health risk behaviors among youth (Everett, Kann & McReynolds, 1997). The 
YRBSS monitors six categories of behaviors: (a) those that contribute to unintentional 
injuries and violence; (b) tobacco use; (c) alcohol and other drug use; (d) sexual 
behaviors that contribute to unintended pregnancy and sexually transmitted disease, 
including human immunodeficiency virus infection; (e) dietary behaviors; and (f) 
physical activity. The CDC conducts the YRBS biennially using a national probability 
sample of high school students.  
 The YRBSS consists of national, state, and local school based surveys of 
representative samples of students grades 9 through 12, a national household based 
survey of 12 through 21 year olds, a national survey of college students, a national survey 
 6
of alternative school students, and other surveys of special populations of young people. 
These surveys all use a similar instrument, the Youth Risk Behavior Survey (YRBS) 
questionnaire, which was developed with extensive research and testing (Kolbe, Kann, & 
Collins, 1993). For the purpose of this study the results of the school based survey of 
students in grades 9 through 12 were collected and analyzed. 
 
Research Questions 
1. What, if any, is the relationship between television viewing, physical 
activity levels, fruit and vegetable consumption and overweight status among Alabama 
high school adolescents? 
2. If so, to what extent does overweight status (BMI) affect prevalence rates 
for television viewing of Alabama high school adolescents? 
3. If so, to what extent does overweight status (BMI) affect prevalence rates 
in physical activity levels of Alabama high school adolescents? 
4. If so, to what extent does overweight status (BMI) affect prevalence rates 
by fruit and vegetable consumption of Alabama high school adolescents? 
 
Limitations of the Study 
 
 Limitations are conditions beyond the control of the researcher that might restrict 
the conclusions of the study and how they can be applied to other situations (Best & 
Kahn, 1993). For this study, the following limitations were considered: 
1. Collection of data from adolescents in school did not account for dropout, 
homeless, or runaway adolescents. 
 7
2. Scantron sheets were used for recording responses to the questions, which 
may have affected the accuracy of coding by the students.  
3. Four grade levels of students (9?12) were used to represent the entire 
adolescent population. Thus, results cannot be generalized to junior 
high/middle school adolescents.  
 
Assumptions of the Study 
1. The students completing the instrument were honest and accurate in their 
responses. 
2. The instrument was assessed for and produced appropriate measures of 
reliability and validity. 
3. The instrument accurately addresses and depicts priority health risks for 
adolescents as defined by the Center for Disease Control (CDC). 
4. Data were accurately coded by the researcher prior to the primary analysis. 
 
Definition of Terms 
Adolescents ? defined as a person between ten and nineteen years of age.  
Body Mass Index (BMI) ? an index that incorporates height and weight to 
estimate critical fat values at which risk for disease increases. For youth aged 2 to 20 
years, growth charts developed by the Center for Disease Control and Prevention are used 
(http://www.cdc.gov/growthcharts). 
Coronary Artery Disease ? means narrowing of the coronary arteries (arteries that 
supply blood to the heart).  
 8
Diabetes ? a condition characterized by hyperglycemia resulting from the body?s 
inability to use blood glucose for energy.  
Epidemiology ? is the field of medicine concerned with the study of epidemics, 
outbreaks of disease that affect large numbers of people.  
Human Immunodeficiency Virus (HIV) ? either of two closely related 
retroviruses that invade T-helper lymphocytes and are responsible for AIDS.  
Hyperlipidemia ? an elevation of lipids (fats) in the bloodstream. 
Hypertension ? a disorder characterized by high blood pressure; generally this 
includes systolic blood pressure (the top number of your blood pressure measurement, 
which represents the pressure generated when the heart beats) consistently higher than 
140, or diastolic blood pressure (the bottom number of your blood pressure measurement, 
which represents the pressure in the vessels when the heart is at rest) consistently over 90.  
Obesity ? a condition resulting from excessive storage of fat in the body (20% 
above what is considered normal according to standard age, height, and weight tables).  
Overweight ? A child or adolescent is considered overweight when their BMI is 
at or above the 85
th
 percentile on the Center for Disease Control and Prevention growth 
chart (http://www.cdc.gov/growthcharts). 
Rickets ? a bone disease caused by a deficiency of vitamin D or calcium.  
Type 2 Diabetes ? also called non-insulin-dependent diabetes mellitus. Type 2 
diabetes is associated with insulin resistance and impaired ?-cell function.  
 
 9
Summary 
 The number of overweight children and adolescents, in the United States, has 
substantially increased over the past twenty years and is of national concern. Although 
there has been no direct evidence as to the cause of this rapid increase in the incidence of 
overweight status, many factors have been identified that may contribute, including 
television viewing, physical activity levels, and eating behaviors.  
 Children and adolescents who are overweight are at greater risk for adverse health 
outcomes when compared with children and adolescents from prior generations (Goran & 
Treuth, 2001). Evidence repeatedly demonstrates the rising prevalence of overweight 
conditions and overweight related illnesses, with 30% of the United States children and 
adolescents having a body mass index (BMI) higher than the 85
th
 percentile for their age 
(Dietz, 1998; Ludwig & Ebbeling, 2001; Ogden, Flegal, Carroll, & Johnson, 2002; 
Power, Lake, & Cole, 1997; Robinson, 1999). The Youth Risk Behavior Survey (YRBS) 
was developed to monitor the health behaviors of adolescents in six critical areas, 
including television viewing, physical activity levels, and fruit and vegetable 
consumption. 
 Chapter II will provide a review of the literature concerning children and 
adolescent development and the background of overweight status, as well as factors 
associated with its possible cause. Chapter III will discuss the research design and data 
analysis. The results of the research study will be discussed in Chapter IV. Chapter V will 
include the summary, discussion, and recommendations based on study findings.  
 
 10
 
 
 
 
 
 
 
 
 
II. REVIEW OF LITERATURE 
 
Purpose of the Study 
Intervention in the epidemic of adolescent overweight conditions is critical if we 
are to reduce the problem. Current national nutrition surveillance data suggest that the 
diet of adolescents is putting them at risk for cardiovascular disease, cancer, and 
osteoporosis, based on their intakes of saturated fat, total fat, fruits, vegetables, fiber, 
sodium, as well as soft drinks (CDC, 2004). In addition, the United States is experiencing 
an epidemic of overweight conditions that extends to the adolescent population; some of 
the related factors may be an excess in energy intake, low levels of physical activity, and 
high levels of sedentary behaviors. This research was intended to investigate these three 
variables and their relationship to the overweight status of Alabama high school 
adolescents.  
 This study explored three lifestyle and environmental risk factors that relate to 
adolescent overweight status. Using the 2003 Youth Risk Behavior Survey results this 
study examined the relationship between television viewing, physical activity and fruit 
and vegetable consumption and overweight status of Alabama high school adolescents. 
 
 11
Research Questions 
The following research questions were developed for investigation by this study. 
1. What, if any, is the relationship between television viewing, physical 
activity levels, fruit and vegetable consumption, and overweight status among Alabama 
high school adolescents?  
2.  If so, to what extent does overweight status (BMI) affect prevalence rates 
for television viewing of Alabama high school adolescents? 
3.  If so, to what extent does overweight status (BMI) affect prevalence rates  
in physical activity levels of Alabama high school adolescents? 
4. If so, to what extent does overweight status (BMI) affect prevalence rates  
by fruit and vegetable consumption of Alabama high school adolescents?  
 Although studies review some areas of these research questions, few focus 
specifically on the nature of the relationship between these variables (Chakravarthy & 
Booth, 2003; Kimm & Obarzanek, 2002; Neumark-Sztainer, Story, Hannan, Tharp, & 
Rex, 2003). Hammerberg?s (1992) correlational study addressed the relationship between 
overweight status, activity level, and television viewing of fourth grade children. Results 
of this study suggested that although genetic factors and familial environment affect the 
relative weight of fourth grade children, their exact influence remains unclear. Earlier 
studies addressed some environmental factors in adolescent overweight status 
(Aristimuno, Foster, Voors, Srinvasan, & Berenson, 1984; Bullen, Reed, & Mayer, 1964; 
Chirico & Stunkard, 1963; Southam, Kirkley, Murchison, & Berkowitz, 1984). While 
other studies focused on a wider network of factors that may influence the development 
and treatment of adolescent overweight status: activity level (Manos, Gutin, Rhodes, 
 12
Spandorfer, Jackson, & Litaker, 1993), and other personal habits (Dietz & Gortmaker, 
1985; Wolf, Gortmaker, Cheung, Gray, Herzog, & Colditz, 1993). While these studies 
offer some clarification of the role of various environmental factors in the prevalence of 
adolescent overweight status, additional clarification is needed.  
Theoretical foundations of adolescent development will be discussed in this 
section along with the definition of obesity, obesity and television viewing, obesity and 
physical activities, obesity and eating behaviors, and childhood overweight status and 
adult obesity. 
 
Theoretical Foundations of Adolescent Development 
Models and Theories 
 Models are sets of assumptions researchers make about the nature of reality. 
These assumptions are too general to be tested; however, theories which derive from 
models, are more specific explanations of phenomena, and can be confirmed or 
disconfirmed. Theories serve four major functions: (a) They serve as a guide to 
formulating questions, (b) they describe phenomena by allowing one to relate isolated 
facts to a body of knowledge, (c) they make it possible to predict new behavior based on 
explanations of previous actions, and (d) they suggest ways for changing the behavior 
they describe by allowing one to identify antecedent events (Kuhn, 1962; Overton, Ward, 
Noveck, Black & O?Brien, 1987; Reese & Overton, 1970). 
 The assumptions that make up a model can frequently be expressed as a 
metaphor. The machine is a popular metaphor for human behavior, and models based on 
this metaphor assume that behavior is as predictable as that of a machine. Such models, 
 13
however, allow no room for self initiated action. Three models of human behavior are the 
environmental, organism, and psychodynamics models (Reese & Overton, 1970). 
 The environmental model views humans as passive and sees their actions as 
reactions to environmental events. People are assumed to remain quiescent until 
something stimulates them to act. Behavior is linked to external events through simple 
associations; these are formed through respondent and operant conditioning (Bandura, 
1989; Havighurst, 1972; Skinner, 1961). 
 The organismic model takes the living, biological system as its metaphor for 
human behavior. Theories derived from this model assume that variables tied to the 
nature of the organism structure development. These theorists assume that the human 
organism is active and does not passively await stimulation, and that activity is internally 
organized instead of structured by environmental events. Behavior is seen as an unfolding 
of developmental stages, each of which is qualitatively different from the last (Hall, 
1904; Gilligan, 1988; Piaget, 1954).  
 The psychodynamic model emphasizes both inner processes and external events 
in explaining behavior. Freud, the major theorist for this model, assumed that biological 
impulses are housed in the id and social standards in the superego; the ego balances the 
demand for expression of the id against the realities of social constraints (Chodorow, 
1978; Erikson, 1968; Freud, 1961; Horney, 1967). 
Environmental Theories 
 Havighurst traces development across a succession of developmental tasks that 
reflect social expectations for more mature behavior with age; physical maturation sets 
the pace for these expectations (Havighurst, 1972). The theory of B. F. Skinner is a 
 14
radical departure from the way most people understand their behavior. Skinner assumes 
that behavior is under the control of the events that follow it instead of reflecting 
preceding motives or intentions. Skinner refers to these antecedent events as reinforcers 
(Skinner, 1938, 1953, 1961). 
 Bandura also emphasizes the importance of learning in development, but believes 
that most human learning occurs through observing others rather than through direct 
conditioning. Inner processes such as attention and memory are important in Bandura?s 
social cognitive theory (Bandura, 1986, 1989).  
Organismic Theories 
Hall assumed that stages of development mirrored evolutionary changes from 
earliest times to the present. Even though his own theoretical assumptions were not 
supported, Hall laid the foundation for a scientific study of human development (Hall, 
1904). 
Piaget succeeded where Hall had failed. Piaget also, extended Darwin?s theory of 
evolution to human development. He viewed intelligence as a means of adapting to one?s 
environment only those forms of thought that promotes adaptation surviving with 
increasing age. Piaget viewed intelligence as biologically based. He assumed that 
knowledge, rather than being a simple copy of reality, is an active construction of what 
we know of the world. He also assumed that these experiences are organized in 
qualitatively different stages with age (Piaget, 1954). 
Gilligan focuses on the interpersonal aspects of development. She notes striking 
gender differences in the ways individuals of either sex define themselves. Males tend to 
 15
view themselves as separate from others; females typically describe themselves in terms 
of their relationships with others (Gilligan, 1988; Gilligan & Attanucci, 1988). 
Psychodynamic Theories 
Freud assumed that all thoughts and actions are motivated; he termed the life 
force motivating these as the libido. Different aspects of the personality control the 
expression of the libido. The id, present from birth, has limited means for gratifying 
libidinal impulses. The ego, next to develop, seeks to gratify as many libidinal impulses 
as possible within social constraints. The last aspect of the personality to develop, the 
superego, contains the moral values of one?s culture and dictates what one should and 
should not do (Freud, 1954, 1961). 
Horney (1967) considers the development of a healthy personality in terms of the 
ability to value oneself and see that one is valued by others. Horney placed less emphasis 
than Freud on biological instinct and more stress on the impact of one?s culture. Though 
she, like Freud, considered early experiences to be important, she did not view them as 
having the determining effect on later personality that Freud did. In particular, Horney 
reinterpreted Freud?s analysis of the feminine personality as a reflection of living in a 
male dominated society and of women?s economic dependence on men (Horney, 1967). 
Erikson (1963, 1968) assumes, as did Freud, that personality develops through a 
sequence of stages, but he carries these through the lifespan. He assumes that society 
challenges us with new demands as we age and that we experience these as crises. Each 
crisis takes a slightly different form and gives each stage its unique characteristics. 
Achievement of a personal identity is the central crisis of adolescence; this involves 
 16
adolescents in a set of commitments to life goals that give definition to the self (Erikson, 
1963, 1968). 
Chodorow (1978) builds on a foundation provided by Freud but attributes gender 
differences to the social fact that for almost all children the first intimate relationship is 
with a female, the mother. Girls can continue to define themselves within the context of 
this first relationship, but boys must separate themselves in order to develop as males. As 
a consequence, girls? development is characterized by attachment and boys? by separation 
and individuation (Chodorow, 1978).  
 
Diagnosis of Obesity 
 Obesity is generally defined as a condition in which there is an excessive energy 
supply (mostly fat) (Bloomgarden, 2002; Cohen, 1985; Roberts, 1993; Shah & Jeffrey, 
1991). It is also defined as fat storage that occurs when energy intake is greater than 
energy output (Bouchard, 1991; Pace, Webster, & Garrow, 1986; Shah & Jeffrey, 1991). 
The American College of Sports Medicine (2001) defines obesity as an excess of total 
body fat. Narrower definitions define obesity as a range of percent of ideal body weight. 
Some researchers have defined obesity as 10 to 30 percent over ideal body weight (Jette, 
Berry, & Pearlman, 1977; Zakus, Chin, Cooper, Makovsky & Merrill, 1981). Others 
suggest that 20 percent more than desirable weight usually defines obesity (Felts, 
Tavasso, Chenier, & Dunn, 1992; Foreyt & Cousins, 1989; Williams, Bollella, & Carter, 
1993).  
 Overweight status refers to an excess of weight (Foreyt, 1987). It is also defined 
in terms of body mass index (BMI) [weight in kilograms divided by height in meters 
 17
squared] (Foreyt, 1987). For children and adolescents, the state of being overweight 
occurs when body weight is equal to or greater than the 85
th
 percentile; and severely 
overweight (or obese) is defined as a BMI greater than the 95
th
 percentile (Foreyt, 1987). 
When referring to children and adolescents risk of overweight and overweight are the 
terms used, not obesity. For the purpose of this study overweight status will be 
considered as a BMI equal to or greater than the 85
th
 percentile. 
Since 1959, the Metropolitan Life Insurance Company weight/height charts have 
provided a standard for defining overweight status (Foreyt, 1987). According to the 
American College of Sports Medicine (2001), body fat content is usually estimated by 
one of two techniques, measuring skinfold thickness or computing the ratio of body 
weight to height.  
 Measurement by skinfold thickness with calipers is the most common technique 
for testing overweight conditions (Foreyt & Cousins, 1989; Williams, Bollella, & Carter, 
1993). With this type of measurement overweight is defined by triceps skinfold 
exceeding the 85
th
 percentile in adolescents (Dietz, 1987; Obarzanek, 1993). According 
to Foreyt and Cousins (1989), the ideal way to diagnose overweight conditions is to 
estimate the percentage of body fat through the methods of hydrostatic means (under 
water weighing). This method of measurement is both expensive and inconvenient 
(Foreyt & Cousins, 1989). Another way of measuring overweight conditions is called 
dual energy x-ray absorptiometry (DEXA); this type of measurement has shown great 
promise as an effective laboratory standard for measuring overweight conditions in 
adolescents (Gutin & Manos, 1993). DEXA is a computerized x-ray technique at two 
 18
energy levels to image body fat, lean tissues, and bone mineral content. This type of 
measurement is also expensive.  
Factors Associated with Overweight Conditions 
 This review of the literature focuses on lifestyle and environmental factors that 
may be associated with the epidemic rise in childhood and adolescent overweight 
conditions. Television viewing, physical activity, and eating behaviors have been 
determined to be causal factors. Selected literature to date on these critical factors is 
reported here. 
Overweight Conditions and Television Viewing 
Television viewing may promote overweight conditions both by displacing 
participation in physical activity that would expend energy, and by increasing dietary 
energy intake, possibly during viewing or food advertisements (Christakis, Zimmerman, 
DiGiuseppe, & McCarty, 2004; Dietz & Gortmaker, 1985; DuRant, Baranowski, 
Johnson, & Thompson, 1994; Kennedy, 2000; Kennedy, Strzempki, Danford, Kools, 
2002; Kraak & Pelletier, 1998; Taras, Sallis, Patterson, Nader, & Nelson, 1989). 
Television viewing has increased significantly during the past 20 years, in part because of 
increased program development, availability, and marketing (Dennison, Russo, Burdick, 
& Jenkins, 2004). Time spent viewing television is the single greatest source of physical 
inactivity among American children, other than sleep (Dietz & Gortmaker, 1993; Dietz & 
Strasburger, 1991; Robinson, 1995, 1998). 
 Children and adolescents today participate in many activities that require little to 
no energy. Further complicating this issue is the use of computers, the Internet, video 
games, and television viewing, media outlets that could also contribute to the rapid 
 19
increase in childhood and adolescent overweight conditions over the past few decades 
(Gortmaker, Must, Sobol, Peterson, Colditz, & Dietz, 1996).  
Arluk, Branch, Swain and Dowling (2003) evaluated different types of sedentary 
behaviors of military dependent children aged nine to twelve, to explore any relationship 
to childhood overweight status. Participants included one hundred and one children, 
along with their parents, who completed three questionnaires that collected data on 
sedentary activities. Using body mass index (BMI) as an indicator, 39.8 percent of the 
children were overweight. These children had a BMI greater than or equal to the 95
th
 
percentile as determined by the newly revised Centers for Disease Control and Prevention 
Pediatric growth charts (CDC, 2000).  
Television has become the most ubiquitous communication medium in American 
households over the past three decades. The number of households with more than three 
television sets increased sevenfold from 1970 to 2000, with the number of households 
using cable television service, which would allow for an increase in program selections, 
increasing tenfold (Crespo, Smit, Troiano, Bartlett, Macera, & Anderson, 2001; Epstein, 
Paluch, Gordy & Dorn, 2000). Currently, 99 percent of adolescents have a television in 
their home, and approximately 65 percent of adolescents have a television in their 
bedroom (Robinson, 1999). Due to the rapid increase in childhood and adolescent 
overweight status (National Center for Health Statistics, 2000; Story, Neumark-Sztainer, 
& French, 2002; Shannon, Peacock, & Brown, 1991), time spent watching television has 
become a factor of interest in understanding the overweight epidemic.  
In another related study, Utter, Neumark-Sztainer, Jeffery and Story (2003) 
described the demographic characteristics of adolescent boys and girls who engage in 
 20
three sedentary behaviors (television/video use, computer use, and reading/homework). 
They explored how each sedentary activity is associated with body mass index (BMI). A 
large population (4,746) of Midwestern, metropolitan school children from three schools 
was surveyed. Results revealed that among boys, television/video use and time spent 
reading/homework were positively associated with BMI (p < .05). Among girls, 
television/video use and computer use was positively associated with BMI (p < .05). All 
differences were considered statistically significant at p < .05. Thus, television viewing 
appears to be important in exploring the epidemic rise in overweight conditions. Physical 
activity is another causal factor. 
Overweight Conditions and Physical Activity 
 Results of the National Health and Nutrition Survey (Briefel, Sempos, McDowell, 
Chien, & Alaimo, 1997) revealed that 4.7 million American children ages six through 
seventeen are more than twice their ideal body weight. As compared to the youth of the 
1960s, a more sedentary lifestyle and poor dietary habits has led to a greater than 50 
percent increase in the prevalence of overweight conditions and a nearly 100 percent 
increase in the super-overweight conditions (95
th
 percentile) (Epstein & Goldfield, 1999; 
Sadowksy, Sawdon, Scheiner, & Sticklin, 1999). 
 Physical activity is an important component of a healthy lifestyle, with 
implications for the prevention of chronic diseases and overweight conditions (Caspersen 
& Merritt, 1995; Goran & Treuth, 2001; United States Department of Health and Human 
Services, 1996). However, physical activity declines sharply during adolescence, 
especially among girls (Gortmaker, Dietz, & Cheung, 1990; Neumark-Sztainer, Story, 
Hannan, Tharp, & Rex, 2003). 
 21
 To prevent this decline in physical activity among adolescent girls, it is essential 
to identify factors that correlate with physical activity that are amenable to change and 
can be addressed within intervention. It is important to identify factors likely to influence 
the physical activity of adolescence girls at greatest risk for low levels of physical activity 
(Neumark-Sztainer, Story, Hannan, Tharp, & Rex, 2003). 
Neumark-Sztainer, Story, Hanna, Tharp, and Rex (2003) conducted a study with 
the purpose of identifying factors associated with changes in physical activity in 
adolescent girls at risk for sedentary lifestyles and overweight status. Two hundred one 
(201) adolescent girls attending six high schools in the Minneapolis/St. Paul area were 
recruited. The adolescent girls were in ninth through twelfth grade with all ethnic groups 
sampled. Three assessments by the school-based obesity prevention physical education 
program were performed during an eight month period. 
 The assessments explored the association between physical activity and a range of 
personal factors (self-worth, body image, enjoyment of physical activity, self-efficacy, 
body mass index, body image and self-acceptance), behavior factors (watching television 
and time constraints), and socioenvironmental factors (social support and cost resources). 
The two strongest and most consistent factors associated with change in physical activity 
were support for physical activity from peers, parents and teachers, and time constraints. 
Measures assessing self-perception (self-worth) and specific to physical activity (self-
efficacy to be physical active) were also associated with change in physical activity. 
 Data concluded support from family and friends may be an effective intervention 
strategy. In addition, addressing real and perceived time constraints may be an effective 
way to increase physical activity levels in adolescent girls.  
 22
 Physical activity is an integral part of a healthy lifestyle and has been associated 
with many health benefits (Hu, Leitzmalm, Stampfer, Colditz, Willet, & Rimm, 2001; 
Simons-Morton, Parcel, Baranowski, Forthofer, & O?Hara, 1991; Steptoe & Butler, 
1996). Since physical activity may track from adolescence to adulthood (Raitakari, 
Porkka, Taimela, Telama, Rasanen, & Vikari, 1994; Telama, Xiaolin, Laakso, Vilkari, 
1997), there is a growing concern that morbidity and mortality associated with physical 
inactivity will increase. 
Feldman, Barnett, Shier, Rossignol, and Abenhaim (2003) conducted a study to 
determine whether there is a relationship between the time adolescents spend in physical 
activity and time they spend in different sedentary pursuits, i.e., watching television, 
playing video games, working on computers, doing homework, and reading. Seven 
hundred forty three (743) students from Montreal, Quebec in grades seven through 
twelve participated in this study. Students at two inner-city and one private school were 
surveyed using a self-administered questionnaire. This questionnaire addressed time 
spent in physical activity and time spent in sedentary pursuits.  
 Levels of physical activity were measured as low, moderate or high. Girls 
outnumbered boys in the low and moderate physical activity groups and boys 
outnumbered girls in the high activity group. The results also showed that increased time 
spent in productive sedentary behaviors (reading or doing homework and working on 
computers) was associated with increased physical activity. On the other hand, time spent 
watching television and playing video games was not associated with decreased physical 
activity. 
 23
Andersen, Crespo, Bartlett, Cheskin, and Pratt (1998) explored participation in 
vigorous activity and television viewing habits and their relationship to body weight and 
fatness in United States children. The design was a nationally representative cross 
sectional survey with an in person interview and medical examination. Between 1988 and 
1994, 4,063 children aged 8 through 16 were examined as part of the National Health and 
Nutrition Examination Survey III. Mexican Americans and non-Hispanic Blacks were 
over sampled to produce reliable estimates for these groups. 
 Vigorous activity was measured by the estimated number of weekly bouts (or 
sessions) that resulted in sweating or hard breathing. Overall, 80% reported participating 
in play or exercise that made them sweat or breathe hard three or more times per week; 
the rate was higher in boys (85%) than in girls (74%). Vigorous activity levels were 
lowest among non-Hispanic Blacks and Mexican Americans. The study also revealed a 
decrease in exercise level as students increased in age (Andersen, Crespo, Bartlett, 
Cheskin, & Pratt (1998). 
 Television viewing was measured by the number of hours spent watching 
television per day. Overall, 26% of the students reported watching four of more hours of 
television per day; the rate was lower in girls (23%) than in boys (29%). Boys and girls 
who watch four or more hours of television each day had greater body fat (p = .001) and 
had a greater body mass index (p = .001) than those who watch less than 2 hours per day 
(Andersen, Crespo, Bartlett, Cheskin, & Pratt (1998).  
 Andersen, Crespo, Bartlett, Cheskin, and Pratt (1998) concluded that many United 
States children and adolescents watch a great deal of television and are not vigorously 
active. They suggest that intervention strategies to promote lifelong physical activity 
 24
among United States children and adolescents are needed to prevent the adverse health 
consequences of inactivity.  
 The prevalence of overweight and obese conditions not only continues to increase 
in the United States population but in children and adolescents as well. People in 
industrialized countries are expending less energy in activities of daily living and work. 
 The Centers for Disease Control and Prevention (CDC, 1997) has recommended 
that comprehensive school and community programs be developed to promote physical 
activity among children and adolescents. The goals of these programs are to increase 
knowledge about activity and exercise and to develop behavioral and motor skills that 
promote lifelong activities. Such recommendations indicate a need to explore 
interventions in the physical activity levels of children. The third causal factor explored 
in this study, eating behaviors, also reveals a critical need to seek interventions into the 
problem.  
Overweight Conditions and Eating Behaviors 
 Efforts to both prevent and manage overweight conditions in adulthood and 
adolescence often emphasize nutrition information and knowledge. An underlying 
assumption of this approach is poor understanding or lack of knowledge about nutrition 
could lead to weight gain (American Dietetic Association, 1999; Burns, Richman, & 
Caterson, 1987; Maloney, McGuire, Daniels, & Specker, 1989; Munoz, Krebs-Smith, 
Ballard-Barbash, & Cleveland, 1997; Nader, 1993). The risk of obesity and obesity 
related conditions in adulthood is greater in individuals who are overweight during 
adolescence (Battle & Brownell, 1996; Gifford, 2002; Lytle, 2002; Must, Jacques, Dallal, 
Bajema, & Dietz, 1992; Troiano, Flegal, Kuczmarski, Campbell, & Johnson, 1995).  
 25
Thakur and D?Amico (1999) explored whether a lack of nutritional knowledge is 
correlated with overweight conditions in adolescents. A survey was distributed to 289 
ninth through twelfth grade students at three urban high schools in Philadelphia. For this 
study student responses indicated a 26% prevalence of overweight status. Overweight 
was defined as a body mass index (BMI) greater than or equal to the 85
th
 percentile, 
adjusted for age and gender using criteria from the National Health and Nutrition 
Examination Survey II (Public Health Service, 1991).  
 Results indicated no significant differences in nutrition knowledge between the 
overweight and non-overweight students with the exception that overweight students 
were better able to identify high fiber foods. In addition, overweight students were more 
likely to report infrequent meals with their families. Otherwise, there were no significant 
differences in nutritional behaviors or food preferences.  
 Two recent trends in the American lifestyle are possible contributors to recent 
trends in overweight status: fast food consumption and passive entertainment through 
television. Before 1980, the proportion of food dollars spent away from home showed a 
sharp upward trend, from 26 percent to 37 percent (Kinsey, 1994). Substantial increases 
were also seen in the availability of television entertainment via wide market use of home 
VCRs and cable television (Salvaggio & Bryant, 1989). Increased availability of fast 
foods and television entertainment could contribute to overweight conditions by making 
eating more attractive and physical activity less so.  
Overweight status is an important public health problem that, in recent years, has 
reached epidemic proportions. The prevalence of overweight conditions has increased 
gradually throughout this century, and it has risen sharply (Kuczmarski, Flegal, 
 26
Campbell, & Johnson, 1994) in the last ten years despite improvements in the quality of 
the American diet (Committee on Diet and Health, Food, and Nutrition Board, 1989; 
McDowell, Briefel, & Alaimo, 1994). 
Jeffery and French (1998) conducted a study to examine the association between 
television viewing, fast food eating, and body mass index (BMI). One thousand fifty-nine 
(1059) men and women were recruited to participate in the year long study. The 
participants were 198 men, 529 high income women and 332 low income women. Half of 
the participants were randomly assigned to one of two low intensity intervention groups 
designed to reduce weight gain, and half were assigned to a no-contract control condition. 
Eighty-six percent of the participants entering the study completed the one year follow up 
survey. 
 This study explored the hypothesis that television viewing and fast food eating 
may contribute to obesity conditions in the United States. The results of this study found 
television viewing hours and fast food meals were positively associated with energy 
intake and body mass index in women but not in men. Jeffery and French (1998) 
suggested that further studies need to be conducted due to a small sample size and how 
changes in population exposure to fast foods and television may be related to secular 
trends in obesity prevalence in the United States.  
 The decrease in physical activity and the popularity of high-fat, high calorie foods 
has been implicated as causative factors in the rise of overweight conditions (Berkey, 
Rockett, & Field, 2000). The prevalence of overweight conditions has been growing in 
alarming rate for decades in both adolescents and adults (Gortmaker, Dietz, Sobol, & 
Wehler, 1987; Shear, Freedman, Burke, Harsha, Webber, & Berenson, 1988; Sugarman, 
 27
White, & Gilbert, 1990; Troiano & Flegal, 1998). In children, the prevalence doubled 
from the late 1970s to 1994, and it is currently estimated that 25 percent have a body 
mass index (BMI) above the 85
th
 percentile and 11 percent have a BMI above the 95
th
 
percentile (Troiano & Flegal, 1998). In adults, obesity is known to be an important risk 
factor for several chronic diseases (DiPietro, Mossberg, & Stunkard, 1994; Freedman, 
Dietz, Srinivasan, & Berenson, 1999; Johnston, 1985), and among children and 
adolescents overweight status has been linked to several conditions, including glucose 
intolerance (Steinberger, Moran, Hong, Jacobs, & Sinaiko, 2001), and hypertension and 
dyslipidemia (Freedman, Dietz, Srinvasan, & Berenson, 1999). Moreover, two studies 
reported that half of all overweight children remain overweight as adults (Serdula, Ivery, 
Coates, Freedman, Williamson, & Byers, 1993; Vanhala, Vanhala, Kumpusalo, Halonen, 
& Takala, 1998).  
 The major epidemiologic (factors controlling the presence or absence of a 
disease) transition in the 20
th
 century was the shift in mortality (number of deaths in a 
given time or place) and morbidity (relative incidence of disease) from infectious 
diseases to chronic diseases, with cardiovascular diseases leading the list. This transition 
was primarily attributable to the social, economic, and public health changes that took 
place in the United States during the first half of the century. The availability of abundant 
food led not only to better overall nutrition and improved child health, but also to the 
current population?s state of excess positive energy balance, accelerated by an 
increasingly sedentary lifestyle in recent decades. At the beginning of this millennium, a 
new challenge has emerged. This challenge is to understand the increase in overweight 
prevalence with a parallel increase in overweight status associated with chronic diseases 
 28
and their clinical onset at ever younger ages. Type 2 diabetes, a condition traditionally 
associated with middle age adults, is beginning to occur several decades earlier as 
overweight conditions afflict a greater number of children and adolescents in the United 
States (Glaser, 1997; Kimm & Obarzanek, 2002; Pinhas-Hamiel, Dolan, Daniels, 
Staniford, Khoury, & Zeitler 1996; Rocchini, 2002).  
Until recently, one of the major consequences of overweight status, type 2 
diabetes mellitus, accounted for fewer than 5 percent of cases of all childhood diabetes 
(Neufeld, Raffel, Landon, Chen, & Vadheim, 1998). Current research shows some 
studies of pediatric diabetes clinic populations have reported that as many as 45 percent 
of new cases of diabetes are type 2 (American Diabetes Association Consensus 
Statement, 2000; Neufeld, Raffel, Landon, Chen & Vadheim, 1998). The number of cases 
of type 2 diabetes is increasing in tandem with the rise in overweight rates in this age 
group (American Diabetes Association Consensus Statement, 2000; Young, Dean, Flett, 
& Wood-Steiman, 2000). It is important to look at some of the factors that could possibly 
cause this increase.  
 A recent study conducted by Giammattei, Blix, Marshak, Wollitzer and Pettitt 
(2003) explored the prevalence of overweight status among sixth and seventh grade 
students in a school based setting, and identified lifestyle parameters associated with 
overweight conditions. There were 186 boys and 199 girls from three schools that 
participated in a school based screening study and participants (N = 319) completed a 
short questionnaire. Height and weight were measured, and body fat as a percentage of 
body weight was obtained. 
 29
 The overall results revealed that 35.3% of students had a body mass index (BMI; 
calculated as the weight in kilograms divided by the height in meters squared) at or above 
the 85
th
 percentile, and half of these students (17.4%) had a BMI at or above the 95
th
 
percentile. Rates were higher among Latino and lower among Asian than non-Hispanic 
white students. Significant association was found between BMI and hours of television 
watching per evening and daily soft drink consumption. Giammattei, Blix, Marshak, 
Wollitzer and Pettitt (2003) concluded that time spent watching television and the 
number of soft drinks consumed was significantly associated with overweight conditions. 
Latinos spent more time watching television and consumed more soft drinks than did 
non-Hispanic White or Asian students.  
 Epidemiologic evidence indicates protective benefits of fruit and vegetable 
consumption against cardiovascular disease (Hu, Manso, & Willett, 2001; Renaud, 2001), 
diabetes (Ford & Mokdad, 2001; Lindquist, Gower, & Goran, 2000), and various forms 
of cancer (LaVecchia & Tavani, 1998; Steinmetz & Potter, 1991). The promotion of 
adequate dietary intake of fruit and vegetables by youth is reflected in Healthy People 
2010 objectives for persons > 2 years old (U.S. Department of Health and Human 
Services, 2000). However, recent national surveys indicate that children and adolescents 
in the United States fail to meet public health guidelines (Dixon, Cronin, & Krebs-Smith, 
2001). While the U.S. Department of Agriculture Food Guide Pyramid recommends three 
to five servings of vegetables per day and two to four servings of fruits (Dixon, Cronin, & 
Krebs-Smith, 2001), only one in five children consumes five or more servings of fruits 
and vegetables daily (Dixon, Cronin, & Krebs-Smith, 2001). 
 30
 Social and environmental factors, such as television viewing, are thought to 
contribute to development of dietary habits among youth (Neumark-Sztainer, Story, 
Resnick, & Blum, 1996). Through the extensive search of literature, limited studies were 
found addressing the association between television viewing and fruit and vegetables 
intake among youth. One study that was found was conducted by Boynton-Jarrett et al. 
(2003).  
 Five hundred forty eight public school ethnically diverse students from four 
Massachusetts communities were studied for a nineteen month period from October 1995 
to May 1997. Boynton-Jarrett et al. (2003) examined the associations between baseline 
and change in hours of television and video viewing per day and change in energy 
adjusted intake of fruits and vegetables. The results of the study indicated for each 
additional hour of television viewed per day, fruit and vegetable consumption decreased 
by 0.14 servings. Baseline hours of television viewed per day was also independently 
associated with change in fruit and vegetable servings (-0.16). 
 Boynton-Jarrett et al. (2003) concluded that television viewing was found to be 
inversely associated with intake of fruit and vegetables among adolescents. They further 
suggested that this association may be a result of the replacement of fruit and vegetables 
in youths? diet by foods highly advertised on television.  
 Children?s diets have been complicated by soft drinks, fast food, and high calorie 
poor quality snacks, with per capita soda consumption having increased fivefold over the 
past fifty years and now comprising more than ten percent of caloric intake for the 
average adolescent. Fast food has contributed to an increase from two to fifteen percent 
of calories in children?s diets in all aspects of society since the 1970s, leading to food 
 31
high in refined carbohydrates, high in trans fatty acids, low in fiber, and low in vitamins 
(Lin, Guthrie, & Frazao, 1999).  
Fast food is especially popular among adolescents, who on average visit a fast 
food outlet twice a week (Lin, Guthrie, & Blaylock, 1996; Lin, Guthrie, & Frazao, 1999). 
A survey of 4,746 students eleven to eighteen years of age reported that about 75 percent 
ate at a fast food restaurant during the week before the survey (French, Story, Neumark-
Sztainer, Fulkerson, & Hannan, 2001). The same survey showed that fast food use was 
associated with higher intake of fried potatoes, hamburgers, pizza, and soft drinks, and 
lower intake of fruits, vegetables, and milk.  
Approximately one in four children and adolescents in the United States is 
overweight (Troiano & Flegal, 1998). Dramatic increases in overweight conditions 
during the past several decades suggest the predominance of environmental factors over 
genetic factors (Bouchard, 1997; Rosenbaum, Leibel, & Hirsch, 1997). Clearly 
overweight conditions are the result of a positive balance between energy intake and 
expenditure. Dietary composition may be related to energy imbalance (Stubbs, Prentice, 
& James, 1997).  
According to the National Health and Nutrition Examination Survey, nearly 13 
percent of children six to eleven years of age are overweight (body mass index [BMI] 
values equal to or greater than 85
th
 percentile) (CDC, 1999). The prevalence of 
overweight children and adolescents has more than doubled since the first nutrition 
examination survey, which was conducted over 30 years ago.  
Approximately one in four adolescents drink more than 26 ounces of soda per 
day, averaging 12 percent to 15 percent of his or her daily energy need (Jacobson, 1998). 
 32
Liquid candy, the term for soft drinks, are now the leading source of added sugar in the 
American adolescent diet (Fried & Nestle, 2002; Schlosser, 2002). A study by Ludwig, 
Peterson, and Gortmaker (2001) found that each additional serving of sugar sweetened 
beverages (defined as soda and other sweetened drinks such as Kool-Aid and lemonade) 
is associated with increases in body mass index and risk of overweight status.  
 For more than 30 percent of adults and 15 percent of children and adolescents in 
the United States, overweight conditions is a threat to a shortened life span (Flegal, 
Carroll, Ogden, & Johnson, 2002; Ogden, Flegal, Carroll, & Johnson, 2002). For children 
and adolescents cultural changes such as vending machines and soda sales as well as 
reduced frequency of physical education classes are commonplace in the school 
environment (Fried & Nestle, 2002; Lowry, Wechsler, Kann, & Collins, 2001).  
 Eating behaviors are central to an adolescent?s physical development, health, and 
identity. Adolescents? eating practices and nutritional intake may have long-term impacts 
on health (U. S. Department of Health and Human Services, 1988). Many youth engage 
in unhealthy dieting practices and have erratic eating patterns that include high intakes of 
fast foods and other foods high in fat and sugar, as well as low intakes of fruits and 
vegetables, and calcium rich foods (Neumark-Sztainer, Story, Resnick, & Blum, 1996). 
Studies to date show a lack of concern for healthy eating on the part of young people and 
little normative support for healthy eating (Croll, Neumark-Sztainer, & Story, 2001; Fried 
& Nestle, 2002; Schlosser, 2002). With the research indicating that overweight status in 
childhood tracks to obesity in adulthood, the need for intervention support for healthy 
eating habits is critical.  
 33
Childhood Overweight Conditions and Adult Obesity 
Overweight conditions track from childhood into adulthood (Klesges, Klesges, 
Eck, & Shelton, 1995; Whitaker, Wright, Pepe, Seidel, & Dietz, 1997), and adolescent 
overweight status has been linked to higher all-cause mortality in adulthood (Must, 
Jacques, Dallal, Bajema, & Dietz, 1992). More than 60 percent of overweight children 
have at least one risk factor for cardiovascular disease, such as elevated blood pressure, 
hyperlipidemia, or hyperinsulinemia (Freedman, Dietz, Scrinivasin, & Berenson, 1999).  
 Overweight conditions in children, and particularly in adolescence, is a key 
predictor for obesity conditions in adulthood, leading to a host of more serious health 
problems, including gallbladder disease, coronary heart disease, respiratory disease, 
arthritis, and some cancers (Deckelbaum & Williams, 2001). Overweight children and 
adolescents are vulnerable to a number of health problems. Type-2 diabetes mellitus is 
becoming a more common diagnosis in pediatric clinics (Sylper, 1998). Overweight 
conditions at age 20 can significantly lessen life expectancy (Fontaine, Redden, Wang, 
Westfall, & Allison, 2003). Must, Jacques, Dallal, Bajema, and Dietz (1992) suggest 
adolescent overweight status increases the long-term (approximately 50 year) risk of 
adult morbidity and mortality independent of adult obesity status and 70% of overweight 
ten to thirteen year old children become obese adults.  
 Whitaker, Wright, Pepe, Seidel, and Dietz (1997) investigated the risk of obesity 
in young adulthood associated with both overweight conditions in childhood and 
adolescence with obesity in one or both parents. Height and weight measurements were 
taken from records of 854 subjects born at a health maintenance organization in 
Washington State between 1965 and 1971. Their parents? medical records were also 
 34
reviewed. Childhood overweight status was defined in this study as a body mass index 
(BMI) at or above the 85
th
 percentile for age and sex, and obesity in adulthood as a mean 
body mass index at or above 27.8 for men and 27.3 for women.  
 The results from this study revealed in young adulthood (defined as 21 to 29 years 
of age), 135 subjects (16%) were obese. Among those who were overweight during 
childhood or adolescence, the chance of obesity conditions in adulthood ranged from 
eight percent for one or two year olds without obese parents to 79 percent for ten to 
fourteen year olds with at least one obese parent.  
 Whitaker, Wright, Pepe, Seidel, and Dietz (1997) concluded that overweight 
children under three years of age without obese parents are at low risk for obesity 
conditions in adulthood, but among older children and adolescences, overweight status is 
an increasingly important predictor of adult obesity status regardless of whether the 
parents were obese. In this study, parental obesity more than doubled the risk of adult 
obesity among both overweight and non-overweight children less than ten years of age.  
 Dietary practices during adolescence may have long-term health implications. For 
example, being overweight as an adolescent is associated with obesity as an adult, high 
fat intake during adolescent and into adulthood is associated with an increase risk of heart 
disease, and low calcium intake during adolescence is associated with low bone density 
and an increased risk for osteoporosis later in life (CDC, 1996).  
 Public health has a long history of addressing important community issues 
through regulatory and policy mechanisms. Examples of successful public health policy 
interventions include the near elimination of rickets through supplementation of milk 
with vitamin D and the reduction in dental caries through fluoridation of our drinking 
 35
water. A contemporary example of healthy public policy is the reduction in the number of 
cigarette smokers. Smoking has been reduced through clean indoor air regulation, 
targeted taxes, and restrictions on access (Dietz, Bland, Gortmaker, Molloy, & Schmid, 
2002). 
 Public policy is now required to address the growing childhood and adolescent 
overweight epidemic. Between 1980 and 1999, the prevalence of overweight status 12 ? 
19 year old adolescents tripled. Almost 15 percent of children and adolescents are now 
overweight (CDC, 2004). Multiple changes have occurred with respect to the source, 
location, and types of food consumption that have likely increased caloric intake. 
Furthermore, physical activity as part of daily life appears to have declined, and 
television viewing among children and adolescents have increased (CDC, 2004).  
 Healthy eating patterns in childhood and adolescence promote optimal childhood 
health, growth, and intellectual development, prevent immediate health problems such as 
iron deficiency anemia, overweight status, eating disorders, and dental caries, and may 
prevent health problems later in life (CDC, 1996). Diet is a risk factor for the nation?s 
three leading causes of death (coronary heart disease, cancer, and stroke) as well as other 
important health problems such as diabetes, high blood pressure, obesity, and 
osteoporosis (U.S. Public Health Service, 1988; CDC, 1996). Many diet-related diseases 
mostly affect adults, but the eating patterns that contribute to them are typically 
established during youth and continue into adulthood (CDC, 1996; Wechsler, Brener, 
Kuester, & Miller, 2001). Therefore, it is efficacious to teach persons healthy eating 
patterns when they are young.  
 36
 The need to promote healthy eating among young people has intensified in recent 
years due to the growing national epidemic of overweight conditions. The prevalence of 
overweight status among children aged six to eleven years in the United States has nearly 
doubled in recent years, from 7 percent in 1976?1980 to 13 percent in 1999, and the 
prevalence of overweight conditions among adolescents aged twelve to nineteen years 
has increased from five percent to fourteen percent during this time (CDC, 1999). An 
emerging, and possibly related, public health problem is the dramatic rise during the past 
two decades in cases of Type 2 diabetes among adolescents. Most adolescents diagnosed 
with this disorder, previously called adult-onset diabetes, are overweight (Fagot-
Campagna, Saadinem, Flegal, & Beckles, 2001; Wechsler, Brener, Kuester, & Miller, 
2001). 
 
Summary 
 Adolescence is recognized as a stage in life when youth prepare for adulthood. It 
is a time marked by changes in physical and emotional characteristics. During 
adolescence, youth are more prone to low self-esteem and engage in risky behaviors. 
There is a growing epidemic of increased overweight conditions among adolescents. The 
intent of this study will be to look for factors which cause this rapid increase in 
overweight status among adolescents.  
 Chapter II provides a review of related literature concerning adolescent 
overweight status, theoretical foundations of adolescent development, and a diagnosis of 
obesity. Chapter III will discuss the research design and data analysis. The results of the 
 37
research study will be discussed in Chapter IV. Chapter V will include the summary, 
discussion, conclusion, and recommendations based on study findings.  
 38
 
 
 
 
 
 
 
 
 
III. METHODS 
 
 Chapter III contains a description of the research methods that provided the 
framework for the analysis of the Youth Risk Behavior Survey (YRBS) data. 
 
Purpose of the Study 
 Intervention in the epidemic of adolescent overweight conditions is critical if we 
are to reduce the problem. Current national nutrition surveillance data suggest that the 
diet of adolescents is putting them at risk for cardiovascular disease, cancer, and 
osteoporosis based on their intake of saturated fat, total fat, fruits, vegetables as well as 
soft drinks (CDC, 2004). In addition, the United States is experiencing an epidemic of 
overweight conditions that extends to the adolescent population; some of the related 
factors may be an excess in energy intake, low levels of physical activity, and high levels 
of sedentary behaviors. This research investigated these three variables and their 
relationship to overweight status of Alabama high school adolescents. 
 This study explored three lifestyle and environmental risk factors that relate to 
adolescent overweight status. Using the 2003 Youth Risk Behavior Survey (YRBS) 
results this study examined the relationships between television viewing, physical 
activity, and fruit and vegetable consumption and overweight status of Alabama high 
school adolescents.  
 39
Description of Study Participants 
 The Youth Risk Behavior Survey (YRBS) was completed by 1088 students in 39 
public high schools in Alabama during spring 2003. Students participating in the survey 
completed a self-administered, anonymous, 87 item questionnaire. Survey procedures 
were designed to protect the privacy of all students by allowing for voluntary and 
anonymous participation. White (61.1%) and Black (35.7%) adolescents attending the 
ninth, tenth, eleventh, and twelfth grades in Alabama were included in this study. The cell 
sizes for all other ethnic groups were too small to analyze. Females made up the majority 
of the sample (51.1%). No significant differences existed between the participants in any 
of the demographic categories. 
 
Research Questions 
 The following research questions provided the basis for the analysis of the YRBS 
data. 
1. What, if any, is the relationship between television viewing, physical 
activity levels, eating behaviors, and overweight status among Alabama high school 
adolescents? 
2.  If so, to what extent does overweight status (BMI) affect prevalence rates 
for television viewing of Alabama high school adolescents? 
3.  If so, to what extent does overweight status (BMI) affect prevalence rates 
in physical activity levels of Alabama high school adolescents? 
4. If so, to what extent does overweight status (BMI) affect prevalence rates 
by fruit and vegetable consumption of Alabama high school adolescents?  
 40
Approval for this study was granted by the Auburn University Institutional 
Review Board for Research Involving Human Subjects on February 22, 2005. 
 
Research Variables 
The three independent variables for this study are: television viewing, physical 
activity levels, and fruit and vegetable consumption. The dependent variable is adolescent 
overweight status. 
The grade in school variable includes students in the ninth, tenth, eleventh, and 
twelfth grades. The race/ethnicity for this study includes White non-Hispanic and Black 
non-Hispanic. Due to low response rates that resulted in low cell sizes too small for 
accurate analysis, other groups were not included in this study. The other groups were 
Hispanic, Asian, Pacific Islander, Alaskan Native, and Native Americans. 
The dependent variables coincide with the YRBS items for television viewing, 
physical activity levels, and fruit and vegetable consumption. Television viewing was 
assessed by the following question from the 2003 YRBS: ?On an average school day, 
how many hours do you watch TV?? Response options range from ?I do not watch TV on 
an average school day? to ?5 or more hours per day.?  
Participation in moderated physical activity and vigorous physical activity were 
assessed by the following two questions: ?On how many of the past 7 days did you 
participate in physical activity for at least 30 minutes that did not make you sweat or 
breathe hard, such as fast walking, slow bicycling, skating, pushing a lawn mower, or 
mopping floors?? and ?On how many of the past 7 days did you exercise or participate in 
physical activity for at least 20 minute that made you sweat and breathe hard, such as 
 41
basketball, soccer, running, swimming laps, fast bicycling, fast dancing, or similar 
aerobic activities?? Response options range from 0 days to 7 days for both questions. 
Consumption of fruits and vegetables was measured by six separate questions, all 
of the form: ?During the past 7 days, how many times did you? [eat fruit; eat green 
salad; eat potatoes; eat carrots; eat other vegetables]?? Response options for each food 
frequency question ranged from 0 times (in the past 7 days) to 4 or more times per day.  
Students were also asked for their current height and weight without shoes. Self 
reported height and weight were used to calculate body mass index (BMI), expressed as 
body weight in kilograms divided by the square of height in meters (kg/m2). Current 
guidelines for evaluation and treatment of childhood obesity, students with a BMI equal 
to or greater than the 95
th
 percentile, using gender and age-specific cut points recently 
revised growth charts produced by Centers for Disease Control and Prevention (CDC, 
2004). 
 
An Overview of the Youth Risk Behavior Survey (YRBS) 
Background and Rationale 
 In 1987, the Centers for Disease Control and Prevention (CDC) developed a 
program to provide fiscal and technical assistance to the 50 states and local education 
agencies for effective human immunodeficiency virus (HIV) prevention programs for 
youth. Since 1992, the CDC has funded education agencies to also provide additional 
broad based programs, often referred to as coordinated school health programs. The 
effectiveness of these programs is partially determined by their ability to positively 
influence behaviors that increase the risk for HIV infection and that are associated with 
 42
the leading causes of death and disability among youth and adults in the United States 
(CDC, 2004).  
 During the 1980s, in the United States, only a limited number of health related 
school based surveys existed (Johnson, O?Malley, & Bachman, 2002). These surveys 
were conducted only on a national level or they were a one time survey, which did not 
meet the state or local needs for health risk for youths. The CDC developed the Youth 
Risk Behavior Surveillance System (YRBSS) to monitor priority health risk behaviors 
that contribute substantially to the leading causes of death, disability, and social problems 
among youth and adults in the United States. YRBSS includes biennial national, state, 
and local school based surveys of representative samples of students ninth through 
twelfth grades (CDC, 2004).  
Purpose of the YRBSS 
 YRBSS was designed to determine the prevalence of health risk behaviors among 
high school students; assess whether these behaviors increase, decrease, or remain the 
same over time. When the YRBSS was developed the decision was made to focus on 
health risk behaviors rather than determinants of these behaviors (e.g., knowledge, 
attitudes, or beliefs). Another purpose of the YRBSS is to provide comparable national, 
state, and local data as well as comparable data among subpopulations of youth (e.g., 
racial/ethnic groups) (CDC, 2004).  
Initial Questionnaire Development 
 The CDC first reviewed the leading causes of morbidity and mortality among 
youth and adults, to determine which risk behaviors YRBSS would assess. In 1988, a 
total of 68 percent of all deaths among persons aged one to twenty-four were from only 
 43
four causes: Motor vehicle crashes (31%), other unintentional injuries (14%), homicide 
(13%), and suicide (10%). These percentages have changed only minimally since the 
original review (Arias, Anderson, Kung, Murphy, & Kochanek, 2003; CDC, 2004; 
National Center for Health Statistics, 2000). For example; alcohol use is a factor in 
approximately one half of the deaths from motor vehicle crashes, homicides, and suicides 
(CDC, 2004; Perrine, Peck, & Fell, 1988). 
 Reviews conducted in 2004 indicate that virtually all behaviors contributing to the 
leading causes of morbidity and mortality can be placed into six categories: behaviors 
that contribute to unintended injuries and violence; tobacco use; alcohol and other drug 
use; sexual behaviors that contribute to unintended pregnancies and STDs, including HIV 
infection; unhealthy dietary behaviors; and physical inactivity (CDC, 2004). These 
behaviors frequently are interrelated and often are established during youth and extend 
into adulthood (CDC, 2004).  
 The first version of the YRBS questionnaire was completed during fall 1989 and 
was reviewed by representatives from each state education agencies, the District of 
Columbia, four U.S. territories, and sixteen local education agencies funded by CDC at 
that time (CDC, 2004). A second version of the questionnaire was used during spring 
1990 to generate data from a national sample as well as 25 state and nine district samples 
of students in ninth through twelfth grades. A third version of the questionnaire was 
completed in fall 1990 (CDC, 2004).  
 During Spring 1991, a total of 26 states and 11 districts conducted the YRBS by 
using the third version questionnaire to conduct a national survey (CDC, 2004). In 1991, 
CDC determined that because behavioral change in populations typically occurs 
 44
gradually over time, biennial surveys would be sufficient to measure health risk 
behaviors among students. YRBS has since been conducted every odd year at the 
national, state, and local levels (CDC, 2004). 
Questionnaire Revisions 
 State and districts and the CDC work together to revise the questionnaire to 
reflect state, district and national priorities, before each biennial YRBS survey is 
administered. For example, two questions assessing self reported height and weight were 
added in recognition of increasing concerns regarding obesity. YRBSS now includes 
national, state, and local estimates of body mass index (BMI) calculated from self 
reported data, as a result of these revisions (CDC, 2004). All YRBS questionnaires are 
self administered, and students record their responses on a computer scantron booklet or 
on an answer sheet.  
Questionnaire Reliability and Validity 
 CDC has conducted two test-retest reliability studies of the national YRBS 
questionnaire, one in 1992 and one in 2000 (CDC, 2004). In the first study, the 1991 
version of the questionnaire was administered to a convenience sample of 1,679 students 
in grade seven through twelve. The questionnaire was administered on two occasions, 
fourteen days apart (Brener, Collins, Kann, Warren, & Williams, 1995). Approximately 
three fourths of the items were rated as having a substantial or higher reliability (kappa = 
61%?100%), and no statically significant differences were observed between the first and 
second time that the questionnaire was administered. The responses of seventh graders 
were less consistent than those of students in higher grades, indicating that the 
questionnaire is best suited for students in grades eight or above (CDC, 2004).  
 45
 In the second study, the 1999 version of the questionnaire was administered to a 
convenience sample of 4,619 high school students, on two occasions, approximately two 
weeks apart (Brener et al., 2002; CDC, 2004). Approximately one of five items (22%) 
had statistically significant difference prevalence estimates for the first and second times 
that the questionnaire was administered. Ten items (14%) had both kappas < 61% and 
statistically significant different time-1 and time-2 prevalence estimates, indicating that 
the reliability of these items is questionable. These items have been revised or deleted 
from the questionnaire (CDC, 2004).  
 Although no study had been conducted to assess the validity of all self-reported 
behaviors that are included on the YRBS questionnaire, in 2003 CDC conducted a review 
of existing empirical literature to assess cognitive and situational factors that might affect 
the validity of adolescent self-reporting of behaviors measured by the YRBS 
questionnaire (Brener, Billy, & Grady, 2003; CDC, 2004). In this review, CDC 
determined that, although self-reports of these types of behaviors are affected by both 
cognitive and situational factors, these factors do not threaten the validity of self-reports 
of each type of behavior equally (CDC, 2004).  
Sampling, Weighting, and Response Rates 
 Each state and local school based YRBS uses a two stage cluster sample design to 
produce representative samples of students in grades nine through twelve in their 
jurisdiction. In the first sampling stage, in all except a few states and districts, schools are 
selected with probability proportional to school enrollment size. In the second sampling 
stage, intact classes of a required subject (e.g., math) or intact classes during a required 
 46
period (e.g., second period) are selected randomly. All students in sampled classes are 
eligible to participate (CDC, 2004).  
 The national YRBS employs a three stage cluster sample design to obtain a 
nationally representative sample of students in grades nine through twelve in the United 
States. The target population comprises all public and private high school students in the 
50 states and the District of Columbia (CDC, 2004).  
 The first stage sampling frame from each national survey includes primary 
sampling units (PSUs) consisting of large sized counties or groups of smaller, adjacent 
counties. PSUs are selected with probability proportional to school enrollment size for 
PSUs (CDC, 2004). 
 In the second stage of sampling, school are selected from PSUs. These databases 
also include enrollment figures. Schools with all four high school grades (9?12) are 
considered whole schools. Schools with any other set of grades are considered fragment 
schools. The fragment schools are combined with other schools (whole or fragment) to 
form a cluster school that includes all four grades (CDC, 2004).  
 The final stage of sampling consists of randomly selecting, in each chosen school 
and in each of grade ninth through twelfth, one or two entire classes. Examples of classes 
include homerooms or classes of a required discipline (e.g., Science or Social Studies). 
All students in the sampled classes are eligible to participate (CDC, 2004).  
 A weight based on student race/ethnicity, sex, and school grade is applied to each 
record to adjust for student non-responses and over-sampling of Black and Hispanic 
students. Therefore, weighted estimates are representative of all ninth through twelfth 
 47
grade students who are attending public and private school in the United States (CDC, 
2004).  
 
Data Collection 
 Local procedures for obtaining parental permission are followed before 
administering YRBS in the schools. Survey procedures for the national, state, and local 
surveys are designed to protect student privacy by allowing the anonymous and voluntary 
participation. The questionnaire, containing 87 items, was administered in the classroom 
by a trained CDC data collector. The YRBS has been reviewed and approved by an 
Institutional Review Board at the CDC (CDC, 2004). 
 
Research Design 
 Examination of statistically significant predictors and prevalence rates between 
fruit and vegetable consumption, physical activity levels and television viewing were 
analyzed with logistic regression analysis using Software for the Statistical Analysis of 
Correlated Data (SUDDAN). Statistically significant predictors were determined using 
odds ratios at a .05 alpha level. Odds ratio is a statistical measure, an estimate, 
particularly important in logistical regression. It is defined as the ratio of the odds of an 
event occurring in one group to the odds of it occurring in another group. The odds ratio 
is calculated by dividing the odds in one group by the odds in another group. These 
groups, for example, might be men and women, or any other dichotomous classification. 
An odds ratio of 1.00 means the odds for one group was the same as the odds for the 
other group. Along with the odds ratio, one should calculate the range over which they 
 48
are confidence that this estimate is reliable. In this study a 95% confident level was used, 
meaning the researcher was 95% confidence the estimate would fall within that range 95 
out of 100 times. Prevalence rates were determined by using the 95% confidence 
intervals (Hosmer & Lemeshow, 1989; Kleinbaum, 1994). 
 Logistic regression is similar to that of multiple regression even though the 
mathematical criterion of maximum likelihood rather than least squares is employed. The 
independent variable should be correlated with the dichotomous criterion and contribute 
non-redundant information. Logistic regression does not assume that the dependent 
variable is a linear function of the independent variables (Glass & Hopkins, 1996).  
For this analysis, logistic regression was applied to each of the sets of variables 
addressing all research questions. Logistic regression were used to calculate odds ratios at 
95% confidence intervals. ?Because of the importance of the odds ratio as a measure of 
association, interval estimates are often used when presenting the results of a logistic 
regression analysis? (Hosmer & Lemeshow, 1989). The confidence interval is a ?range of 
values that are confident contains the population parameter? (Hinkle, Wiersma, & Jurs, 
1994, p. 197).  
 
Summary 
Chapter III contains an overview of the YRBS, data collection, research design 
and data analysis. The purpose of this analysis was to determine statistically significant 
predictors and prevalence rates between television viewing, physical activity levels, and 
fruit and vegetable consumption and overweight status among Alabama high school 
adolescents using the 2003 YRBS data. The YRBS is a school based survey that monitors 
 49
priority health risk behaviors among representative samples of student in grades nine 
through twelve, at the national, state, and local levels. 
 Logistic regression is a method of statistical analysis most often used in the health 
science, particularly epidemiology. Risk ratios and odds ratios are two methods that can 
be used to determine the probability of disease or outcome. Logistic regression is used by 
the CDC to analyze the YRBS. 
Results are discussed in Chapter IV. Chapter V includes the summary, discussion, 
conclusions, and recommendations based on this study finding.  
 50
 
 
 
 
 
 
 
 
 
IV. RESULTS 
 
 This chapter presents results for each question related to television viewing, 
physical activity levels and fruit and vegetable consumption on the 2003 Youth Risk 
Behavior Survey (YRBS). Thirty nine public schools in Alabama during Spring 2003 
were surveyed. The sample size was 1088 respectively. Five hundred forty five (545) 
were females (51.1%) and 510 were males (48.9%). White adolescents accounted for 
61.1 percent (n = 752) and Black adolescents accounted for 36.7 percent (n = 224). The 
cell size for all other groups (Hispanic/Latino, 0.7%; All Other Races 1.3%; and Multiple 
Races 1.2%) were too small to analyze. The grade levels sampled were ninth (30.1%, n = 
282), tenth (25.9%, n = 270), eleventh (22.6%, n = 240), and twelfth (20.9%, n = 251).  
Results will assess the relationships between variables by analyzing the 
independent variables, gender, race and grade in school, for each of the dependent 
variables separately. Dependent variables were:  
a) During the past 7 days, how many times did you eat fruit, green salad, 
potatoes, carrots, and other vegetables? [these are questions 74 through 78 
on the YRBS combined into one variable],  
b) On how many of the past 7 days did you exercise or participate in physical 
activity for at least 20 minutes that made you sweat or breathe hard, such 
 51
as basketball, soccer, running, swimming laps, fast bicycling, fast dancing, 
or similar aerobic activities? [this is question 80 on the YRBS],  
c) On how many of the past 7 days did you exercise or participate in physical 
activity for at least 30 minutes that did not make you sweat or breathe 
hard, such as fast walking, slow bicycling, skating, pushing a lawn mower, 
or mopping floors? [this is question 81 on the YRBS], and  
d) On an average school day, how many hours do you watch TV? [this is 
question 83 on the YRBS]). 
 
Purpose of the Study 
 Intervention in the epidemic of adolescent overweight status is critical if we are to 
reduce the problem of overweight adolescents. Current national nutrition surveillance 
data suggest that the diet of adolescents is putting them at risk for cardiovascular disease, 
cancer, and osteoporosis, based on their intake of saturated fat, total fat, fruits, 
vegetables, as well as soft drinks (CDC, 2004). In addition, the United States is 
experiencing an epidemic of overweight conditions that extends to the adolescent 
population; some of the related factors may be an excess in energy intake, low levels of 
physical activity, and high levels of sedentary behaviors. This research investigated these 
three variables and their relationship to the overweight status of Alabama adolescents. 
 This study explored three lifestyles and environmental risk factors that could 
possibly affect adolescent overweight status. Using the 2003 Youth Risk Behavior 
Survey (YRBS) results this study examined the relationship, if any, between television 
 52
viewing, physical activity, and fruit and vegetable consumption among Alabama high 
school adolescents. 
 
Results 
Results of Research Question One 
 Research Question 1 was, ?What, if any, is the relationship between television 
viewing, physical activity levels, fruit and vegetable consumption and BMI among 
Alabama high school adolescents?? 
 Data used to answer Research Question 1 were found in the responses to 
questions 2 (What is your sex?), 3 (In what grade are you?), 4 (How do you describe 
yourself?), 74 (During the past 7 days, how many times did you eat fruit?), 75 (During 
the past 7 days, how many time did you eat green salad?), 76 (During the past 7 days, 
how many times did you eat potatoes?), 77 (During the past 7 days, how many times did 
you eat carrots?), 78 (During the past 7 days, how many times did you eat other 
vegetables?), 80 (On how many of the past y days did you exercise or participate in 
physical activity for at least 20 minutes that made you sweat and breathe hard, such as 
basketball, soccer, funning, swimming laps, fast bicycling, fast dancing, or similar 
aerobic activities?), 81 (On how many of the past 7 days did you participate in physical 
activity for at least 30 minutes that did not make you sweat or breathe hard, such as fast 
walking, slow bicycling, skating, pushing a lawn mower, or mopping floors?), and 83 
(On an average school day, how many hours do you watch TV?) on the 2003 YRBS. 
There is a referent or reference group for each set of independent variables. The referent 
groups used were males, white, twelfth grade students, did not exercise vigorously, did 
 53
not exercise moderately, did not eat the recommended fruit and vegetable consumption 
and watched television 2 hours or more per day. The odds ratio for the referent group is 
1.0 (see Table 1).  
 
Table 1 
Odd Ratios (OR) and 95% Confidence Intervals (CI) for Vigorous Physical Activity 
Levels, Moderate Physical Activity Levels, Fruit and Vegetable Consumption, and 
Television Viewing (TV) of Alabama High School Adolescents 
Varibles     OR   95% CI 
Gender 
 
Female     1.32   (0.90, 1.94) 
 Male     1.00   Referent 
 
Race 
 
White     1.00   Referent 
 Black     0.78   (0.55, 1.10) 
 
Grade 
 
9
th
     0.80   (0.57, 1.12) 
 10
th
     0.90   (0.59, 1.37) 
 11
th
     1.03   (0.59, 1.80) 
 12
th
     1.00   Referent 
 
Vigorous Physical Activity Levels 
 
< 3 days per week   1.00   Referent 
 > 3 days per week   1.05   (0.79, 1.40) 
 
(table continues) 
 54
Table 1 (continued) 
Varibles     OR   95% CI 
Moderate Physical Activity Levels 
 
< 5 days per week   1.00   Referent 
 > 5 days per week   0.77   (0.54, 1.12) 
 
Fruit and Vegetable Consumption 
 
 < 5 per day    1.00   Referent 
 > 5 per day    1.08   (0.68, 1.73) 
 
Television Viewing 
 
 1 hour or less per day   1.33   (0.92, 1.92) 
 > 2 hours per day   1.00   Referent 
 
The prevalence of overweight status among Alabama high school adolescents by 
gender is females (White and Black = 29.97) and males (White and Black = 30.77). 
Prevalence among the different races was Whites (male and females = 26.14) and Blacks 
(males and females = 31.24). Prevalence between grade levels was ninth (30.26), tenth 
(28.74), eleventh (26.16) and twelfth (24.16). 
Race 
 The participants in this study were White (61.1%, n = 752) and Black (37.7%, n = 
224) adolescents; all other groups (2.2%) were too small to provide valid data for 
analysis. There were no statistically significant differences between BMI and the two 
races analyzed (White and Black participants).  
 55
Grade Levels 
The grade levels used in this study were ninth (30.1%, n = 282), tenth (25.9%, n = 
270), eleventh (22.6%, n = 240), and twelfth (29.9%, n = 251) grade students. There were 
no statistically significant differences between BMI and grade levels.  
Vigorous Physical Activity Levels 
 Question number 80 on the 2003 YRBS (?On how many of the past 7 days, did 
you participate in physical activity for at least 20 minutes that made you sweat and 
breathe hard, such as basketball, soccer, running, swimming laps, fast bicycling, fast 
dancing, or similar aerobic activities??) was used to assess vigorous physical activity 
levels. The United States Department of Health and Human Services (2000) recommends 
< 3 days per week for the criteria as not being vigorously physically active and > 3 days 
or more per week as the criteria for being vigorously physically active. There were no 
statistically significant differences between BMI and Alabama high school adolescents 
who were vigorously physically active and the Alabama high school adolescents who 
were not vigorously physically active (see Table 2). 
 56
Table 2 
Prevalence of Body Mass Index (BMI) and Confidence Intervals (CI) for Alabama High 
School Adolescents 
   BMI CI BMI CI 
Variable  < 85
th
 % 95% > 85
th
 % 95% 
Gender 
 
 Females 75.03  (69.42, 79.91)  24.97  (20.09, 30.58) 
 Males 69.23  (63.31, 74.57  30.77  (25.43, 36.69) 
 
Race 
 
 White 73.86  (70.87, 76.63)  26.14  (23.37, 29.13) 
 Black 68.76  (61.00, 75.60)  31.24  (24.40, 39.00) 
 
Grade in School 
 
 9
th
 69.74  (64.19, 74.77)  30.26  (25.23, 35.81) 
 10
th
 71.26  (63.56, 77.90)  28.74  (22.10, 36.44) 
 11
th
 73.84  (64.32, 81.54)  26.16  (18.46, 35.68) 
 12
th
 75.84  (70.23, 80.69)  24.16  (19.31, 29.77) 
 
Vigorous Activity Level 
 
  < 3 Days Per Wk 72.32  (67.38, 76.76)  27.68  (23.24, 32.62) 
  > 3 Days Per Wk 71.64  (66.57, 76.21)  28.36  (23.79, 33.43) 
 
Moderate Activity Level 
 
  < 5 Days Per Wk 72.92  (68.59, 76.84)  27.09  (23.16, 31.41) 
   > 5 Days Per Wk 67.87  (59.18, 75.48)  32.13  (24.52, 40.82) 
 
Fruit & Vegetable Consumption 
 
   > 5 Per Day 72.23  (68.11, 76.02)  27.77  (23.98, 31.89) 
   < 5 Per Day 72.85  (63.75, 80.37)  27.15  (19.63, 36.25) 
(table continues) 
 57
Table 2 (continued) 
   BMI CI BMI CI 
Variable  < 85
th
 % 95% > 85
th
 % 95% 
Television Viewing 
 
   <1 Hr. Per Day 75.90 (70.53, 80.56) 24.10 (19.44, 29.47) 
   >2 Hrs. Per Day 69.79 (64.55, 74.57) 30.21 (25.43, 35.45) 
 
Moderate Physical Activity Levels 
 Question number 81 on the 2003 YRBS was, ?On how may of the past 7 days, did 
you participate in physical activity for at least 30 minutes that did not make you sweat 
and breathe hard, such as fast walking, slow bicycling, skating, pushing a lawn mower, or 
mopping floors?? The United States Department of Health and Human Services (2000) 
recommends < 5 days per week for the criteria as not being moderately physically active 
and > 5 days or more per week as being moderately physically active. There were no 
statistically significant differences between BMI and adolescents who were not 
moderately physically active and adolescents who were moderately active (see Table 2). 
Fruit and Vegetable Consumption 
 The United States Department of Agriculture (2000) recommends 5 servings of 
fruits and vegetables per day. Questions 74 through 78 on the 2003 YRBS (5 questions 
were in the form of: During the past 7 days, how many times did you eat fruit, green 
salad, potatoes, carrots, and other vegetables?) were assessed. There were no statistically 
significant differences between BMI and Alabama adolescents who ate five servings of 
 58
fruits and vegetables per day and Alabama adolescents who did not eat five servings of 
fruits and vegetables per day (see Table 2).  
Television Viewing 
 The review of the literature (Kotz & Story, 1994; Kronenberg, Pereira, & 
Schmitz, 2000; Robinson, Wilde, Navracruz, Haydel, & Varady, 2001; Tucker, 1986; 
Tucker & Bagwell, 1991;) suggested two hours or more of television viewing may be a 
causal factor for obesity. Question 83 on the 2003 YRBS (?On an average school day, 
how many hours do you watch TV??) was used to evaluate the findings. The criteria were 
established using < 2 hours per day of television viewing and > 2 hours or more per day 
of television viewing. There were no statistically significant differences between BMI 
and < 2 hours of television viewing per day by Alabama adolescents and > 2 hour or 
more of television viewing per day by Alabama adolescents (see Table 2).  
Results of Research Question Two 
 Research Question 2 was ?If so, to what extent does overweight status (BMI) 
affect prevalence rates for television viewing of Alabama high school adolescents?? Data 
used to evaluate this Research Question 2 was found in the responses to questions 2 
(What is your sex?), 3 (In what grade are you?), 4 (How do you describe yourself?), and 
83 (On an average school day, how many hours do you watch TV?) on the 2003 YRBS. 
The referent or reference groups for each set of independent variables were males, White, 
twelfth grade students, and watched television 2 hours or more per day. The odds ratio 
for the referent group was established as 1.0 (see Table 3). 
 59
Table 3 
Odd Ratios (OR) and 95% Confidence Intervals (CI) for Television Viewing (TV) for 
Alabama High School Adolescents 
Varibles     OR   95% CI 
Gender 
 
 Females    1.30   (0.88, 1.90) 
 Males     1.00   Referent 
 
Race 
 
 White     1.00   Referent 
 Black     0.81   (0.58, 1.13) 
 
Grade 
 
 9
th
     0.82   (0.59, 1.14) 
 10
th
     0.90   (0.60, 1.37) 
 11
th
     0.98   (0.55, 1.74) 
 12
th
     1.00   Referent 
 
Television Viewing 
 
 1 hour or less per day   1.28   (0.87, 1.89) 
 > 2 hours per day   1.00   Referent 
 
Gender 
 Male (48.9%, n = 510) and female (51.1%, n = 545) Alabama high school 
adolescents were evaluated using the 2003 YRBS. There were no statistically significant 
differences between BMI and male and female adolescents.  
 60
Race 
 The participants in this study were White (61.1%, n = 752) and Black (36.7%, n = 
224) Alabama adolescents, and all other groups (2.2%) were again too small to provide 
valid data for analysis. There were no statistically significant differences between BMI 
and race. 
Grade Level 
 The grade levels were ninth (30.1%, n = 282), tenth (25.9%, n = 270), eleventh 
(22.6%, n = 240), and twelfth (20.9%, n = 251) grade students in Alabama. There were 
no statistically significant differences between BMI and grade levels. 
Television Viewing 
 The literature review (Kotz & Story, 1994; Kronenberg, Pereina, Schmitz, 2000; 
Robinson, Wilde, Navracruz, Haydel, Varady, 2001; Tucker, 1986; Tucker & Bagwell, 
1991) suggested two hours or more of television viewing may be a casual factor for 
obesity. Question 83 on the 2003 YRBS (On an average school day, how many hours do 
you watch TV?) was analyzed using the following criteria: < 2 hours per day of television 
viewing and > 2 hours or more per day of television viewing. There were no statistically 
significant differences between BMI and < 2 hours of television viewing per day by 
Alabama adolescents and > 2 hours or more of television viewing per day by Alabama 
adolescents (see Table 4). 
 61
Table 4 
Prevalence of Body Mass Index (BMI) and Confidence Intervals (CI) for Alabama High 
School Adolescents 
   BMI CI BMI CI 
Variable  < 85
th
 % 95% > 85
th
 % 95% 
Gender 
 
 Females  75.03  (69.42, 79.91) 24.97  (20.09, 30.58) 
 Males  69.23  (63.31, 74.57 30.77  (25.43, 36.69) 
 
Race 
 
 White  73.86  (70.87, 76.63) 26.14  (23.37, 29.13) 
 Black  68.76  (61.00, 75.60) 31.24  (24.40, 39.00) 
 
Grade in School 
 
 9
th
  69.74  (64.19, 74.77) 30.26  (25.23, 35.81) 
 10
th
  71.26  (63.56, 77.90) 28.74  (22.10, 36.44) 
 11
th
  73.84  (64.32, 81.54) 26.16  (18.46, 35.68) 
 12
th
  75.84  (70.23, 80.69) 24.16  (19.31, 29.77) 
 
Television Viewing  
 
   <1 Hr. Per Day  75.90  (70.53, 80.56) 24.10  (19.44, 29.47) 
   >2 Hrs. Per Day  69.79  (64.55, 74.57) 30.21  (25.43, 35.45) 
 
Results of Research Question Three 
 Research Question 3 was, ?If so, to what extent does overweight status (BMI) 
affect prevalence rates in physical activity levels of Alabama high school adolescents?? 
Data used to answer Research Question 3 were found in the responses to items number 2 
(What is your sex?), 3 (In what grade are you?), 4 (How do you describe yourself?), 80 
 62
(On how many of the past y days did you exercise or participate in physical activity for at 
least 20 minutes that made you sweat and breathe hard, such as basketball, soccer, 
funning, swimming laps, fast bicycling, fast dancing, or similar aerobic activities?), 81 
(On how many of the past 7 days did you participate in physical activity for at least 30 
minutes that did not make you sweat or breathe hard, such as fast walking, slow 
bicycling, skating, pushing a lawn mower, or mopping floors?), on the YRBS. The 
referent groups were males, white, twelfth grade students, and < 3 days per week of 
vigorous physical activity, and < 5 days per week of moderate physical activity (see 
Table 5). 
 
Table 5 
Odds Ratios (OR) and 95% Confidence Intervals (CI) for Vigorous Physical Activity 
Levels (VAL) and Moderate Physical Activity levels (MAL) for Alabama High School 
Adolescents 
     VAL    MAL 
             
Variables   OR 95% CI  OR  95% CI 
Gender 
 
 Female   1.31 (0.89, 1.94)  1.30  (0.88, 1.92) 
 Male   1.00 Referent  1.00  Referent 
 
Race  
 
 White   1.00 Referent  1.00  Referent 
 Black   0.77 (0.56, 1.05)  0.77  (0.56, 1.06) 
(table continues) 
 
 63
Table 5 (continued) 
 
     VAL    MAL 
             
Variables   OR 95% CI  OR  95% CI 
 
Grade 
 
 9
th
   0.76 (0.54, 1.09)  0.78  (0.54, 1.12) 
 10
th
   0.86 (0.55, 1.32)  0.87  (0.56, 1.35) 
 11
th
   0.95 (0.51, 1.75)  0.98  (0.53, 1.82) 
 12
th
   1.00 Referent  1.00  Referent 
 
Vigorous Physical Activity  
 
 < 3 days per week 1.00 Referent 
 > 3 days per week 1.06 (0.79, 1.43) 
 
Moderate Physical Activity 
 
 < 5 days per week     1.00  Referent 
 > 5 days per week     0.80  (0.54, 1.19) 
 
Gender 
 Male (48.9%, n = 510) and female (51.1%, n = 545) Alabama high school 
adolescents were analyzed using the 2003 YRBS data. There were no statistically 
significant differences between male and female adolescents based on BMI. 
Race 
 White (61.1%, n = 752) and Black (36.7%, n = 224) Alabama high school 
adolescents were the races to be evaluated in the 2003 YRBS, and all the other groups 
(2.2%) were again too small to provide valid data for analysis. There were no statistically 
significant differences between BMI and the two races.  
 64
Grade Levels 
 The grade levels used in this study were ninth (30.1%, n = 282), tenth (25.9%, n = 
270), eleventh (22.6%, n = 240), and twelfth (20.9%, n = 251) grade students in 
Alabama. There were no statistically significant differences between BMI and the grade 
levels.  
Vigorous Physical Activity Levels 
 Question number 80 on the 2003 YRBS, (?On how many of the past 7 days, did 
you participate in physical activity for at least 20 minutes that made you sweat and 
breathe hard, such as basketball, soccer, running, swimming laps, fast bicycling, fast 
dancing, or similar aerobic activities??) was used to assess vigorous physical activity 
levels. The United States Department of Health and Human Services (2000) 
recommends, < 2 days per week for the criteria as not being vigorously physically active 
and > 3 days or more per week as the criteria for being vigorously physically active. 
There were no statistically significant differences between BMI and the Alabama high 
school adolescents who are vigorously physically active and the Alabama high school 
adolescents who are not vigorously physically active (see Table 6).  
Moderate Physical Activity Levels 
 Question number 81 on the 2003 YRBS asked ?On how many of the past 7 days, 
did you participate in physical activity for at least 30 minutes that did not make you sweat 
and breathe hard, such as fast walking, slow bicycling, skating, pushing a lawn mower, or 
mopping floors? The United States Department of Health and Human Services (2000) 
recommends, < 5 days per week for the criteria as not being moderately physically active 
and > 5 days or more per week as being moderately physically active. There were no 
 65
statistically significant differences between BMI and the Alabama high school 
adolescents who were not moderately physically active and the Alabama high school 
adolescents who were moderately active (see Table 6). 
 
Table 6 
Prevalence of Body Mass Index (BMI) and Confidence Intervals (CI) for Alabama High 
School Adolescents 
     VAL    MAL 
             
Variables  OR 95% CI  OR  95% CI 
Gender 
 
 Females 75.03  (69.42, 79.91)  24.97  (20.09, 30.58) 
 Males  69.23  (63.31, 74.57  30.77  (25.43, 36.69) 
 
Race 
 
 White  73.86  (70.87, 76.63)  26.14  (23.37, 29.13) 
 Black  68.76  (61.00, 75.60)  31.24  (24.40, 39.00) 
 
Grade in School 
 
 9
th
  69.74  (64.19, 74.77)  30.26  (25.23, 35.81) 
 10
th
  71.26  (63.56, 77.90)  28.74  (22.10, 36.44) 
 11
th
  73.84  (64.32, 81.54)  26.16  (18.46, 35.68) 
 12
th
  75.84  (70.23, 80.69)  24.16  (19.31, 29.77) 
 
Vigorous Activity Level 
 
  < 3 Days Per Wk 72.32  (67.38, 76.76)  27.68  (23.24, 32.62) 
  > 3 Days Per Wk 71.64  (66.57, 76.21)  28.36  (23.79, 33.43) 
 
Moderate Activity Level 
 
  < 5 Days Per Wk 72.92  (68.59, 76.84)  27.09  (23.16, 31.41) 
   > 5 Days Per Wk 67.87  (59.18, 75.48)  32.13  (24.52, 40.82) 
 66
Results of Research Question Four 
 Research Question 4 was ?If so, to what extent does overweight status (BMI) 
affect prevalence rates by fruit and vegetable consumption of Alabama high school 
adolescents??  
 Data used to answer Research Question 4 were found in the responses to items 
number 2 (What is your sex?), 3 (In what grade are you?), 4 (How do you describe 
yourself?), 74 (During the past 7 days, how many times did you eat fruit?), 75 (During 
the past 7 days, how many time did you eat green salad?), 76 (During the past 7 days, 
how many times did you eat potatoes?), 77 (During the past 7 days, how many times did 
you eat carrots?), and 78 (During the past 7 days, how many times did you eat other 
vegetables?) on the 2003 YRBS. The referent groups used were males, white, twelfth 
grade students, and < 5 fruit and vegetable consumed daily. The odds ratio for the 
referent group is 1.0 (see Table 7). 
 
 67
Table 7 
Odd Ratios (OR) and 95% Confidence Intervals (CI) for Fruit and Vegetable 
Consumption for Alabama High School Adolescents 
            
Variables    OR  95% CI 
            
Gender  
 
 Females   1.31  (0.89, 1.92) 
 Males    1.00  Referent 
 
Race 
 
 White    1.00  Referent 
 Black    0.76  (0.54, 1.06) 
 
Grade 
 
 9
th
    0.78  (0.54, 1.14) 
 10
th
    0.87  (0.55, 1.37) 
 11
th
    0.99  (0.54, 1.83) 
 12
th
    1.00  Referent 
 
Fruit and Vegetable Consumption  
 
 < 5 per day   1.00  Referent 
 > 5 per day   1.08  (0.71, 1.65 
            
 
Gender 
 Male (48.9%, n = 510) and females (51.1%, n = 545) Alabama high school 
adolescents were analyzed using the 2003 YRBS data. There were no statistically 
significant differences between BMI and male and females adolescents.  
 68
Race 
 White (61.1%, n = 752) and Black (36.7%, n = 224) Alabama high school 
adolescents were selected as the races analyzed in the 2003 YRBS, the cell size for all the 
other groups (2.2%) were again too small to provide valid data for analysis. There were 
no statistically significant differences between BMI and the two races.  
Grade Levels 
 The grade levels were ninth (30.1%, n = 282), tenth (25.9%, n = 270), eleventh 
(22.6%, n = 240), and twelfth (20.9%, n = 251) grade students in Alabama. There were 
no statistically significant differences between BMI and grade levels. 
Fruit and Vegetable Consumption 
 The United States Department of Agriculture (2000) recommends 5 servings of 
fruits and vegetables per day. Questions 74 through 78 on the 2003 YRBS (5 questions 
were in the form of: During the past 7 days, how many times did you eat fruit, green 
salad, potatoes, carrots, and other vegetables?) were assessed. There were no statistically 
significant differences between BMI and Alabama high school adolescents who ate five 
servings of fruits and vegetables per day and Alabama high school adolescents who did 
not eat five servings of fruits and vegetables per day (see Table 8).  
 
 
 69
Table 8 
Prevalence of Body Mass Index (BMI) and Confidence Intervals (CI) for Alabama High 
School Adolescents 
 BMI CI BMI CI 
             
Variables  < 85
th 
% 95%  > 85
th
 %  95% 
 
Gender 
 
 Females 75.03  (69.42, 79.91)  24.97  (20.09, 30.58) 
 Males  69.23  (63.31, 74.57  30.77  (25.43, 36.69) 
 
Race 
 
 White  73.86  (70.87, 76.63)  26.14  (23.37, 29.13) 
 Black  68.76  (61.00, 75.60)  31.24  (24.40, 39.00) 
 
Grade in School 
 
 9
th
  69.74  (64.19, 74.77)  30.26  (25.23, 35.81) 
 10
th
  71.26  (63.56, 77.90)  28.74  (22.10, 36.44) 
 11
th
  73.84  (64.32, 81.54)  26.16  (18.46, 35.68) 
 12
th
  75.84  (70.23, 80.69)  24.16  (19.31, 29.77) 
 
Fruit & Vegetable Consumption 
 
   > 5 Per Day  72.23  (68.11, 76.02)  27.77  (23.98, 31.89) 
   < 5 Per Day  72.85  (63.75, 80.37)  27.15  (19.63, 36.25) 
             
 
 
Summary 
 Results of the 2003 Youth Risk Behavior Survey relating to television viewing, 
physical activity levels, fruit and vegetable consumption and BMI for Alabama high 
school adolescents have been reported in this chapter. Logistic regression analyses, with a 
 70
.05 alpha level, determined the odds ratios and 95% confidence intervals for the 
dependent variables (i.e., during the past 7 days, how many times did you eat fruit, green 
salad, potatoes, carrots, and other vegetables [these are questions 74 through 78 on the 
YRBS], on how many of the past 7 days did you exercise or participate in physical 
activity for at least 20 minutes that made you sweat or breathe hard, such as basketball, 
soccer, running, swimming laps, fast bicycling, fast dancing, or similar aerobic activities 
[this is question 80 on the YRBS], on how many of the past 7 days did you exercise or 
participate in physical activity for at least 30 minutes that did not make you sweat or 
breathe hard, such as fast walking, slow bicycling, skating, pushing a lawn mower, or 
mopping floors [this is question 81 on the YRBS], and on an average school day, how 
many hours do you watch TV [this is question 83 on the YRBS]. 
 Results indicated that race, gender, grade in school, television viewing, physical 
activity levels and fruit and vegetable consumption were not statistically significant 
predictors for BMI using the 2003 Youth Risk Behavior Survey. Although the findings 
were not significant it should be noted that 27.97% of Alabama high school adolescents 
have a BMI at or greater than the 85
th
 percentile, putting them at risk of becoming 
overweight, or overweight at the present time. When broken down by gender, 24.97% of 
females and 30.77% of males had a BMI at or greater than the 85
th
 percentile, putting 
them at risk of becoming overweight, or overweight at the present time. 26.14% of White 
and 31.24% of Black Alabama adolescents had a BMI at or greater than the 85
th
 
percentile, putting them at risk of becoming overweight, or overweight at the present 
time. Alabama high school adolescents by grade level with a BMI at or above the 85
th
 
percentile level were as follows: (1) 9th grade ? 30.26% (2) 10
th
 grade ? 28.74%, (3) 11
th
 
 71
grade ? 26.16%, and (4) 12
th
 grade ? 24.16% (see Table 8). Chapter V includes the 
purpose of the study, summary, discussion limitations, and recommendations for future 
research based on study methods and findings.  
 
 72
 
 
 
 
 
 
 
 
 
V. SUMMARY, DISCUSSION, AND RECOMMENDATIONS 
 
Purpose of the Study 
 Intervention in the epidemic of adolescent body mass index (BMI) equal to or 
greater than the 85
th
 percentile is critical if we are to reduce the problem. Current national 
nutrition surveillance data suggest that the diet of adolescents is putting them at risk for 
cardiovascular disease, cancer, and osteoporosis, based on their intake of saturated fat, 
total fat, fruits, vegetables, as well as soft drinks (CDC, 2004). In addition, the United 
States is experiencing an epidemic of obesity conditions that extends to the adolescent 
population; some of the related factors may be an excess in energy intake, low levels of 
physical activity, and high levels of sedentary behaviors. This research intended to 
investigate these three variables and their relationship to the overweight status of 
Alabama adolescents. 
 This study explored three lifestyles and environmental risk factors related to 
potential adolescent overweight status. Using the 2003 Youth Risk Behavior Survey 
(YRBS) results, this study examined the relationships, if any, between television viewing, 
physical activity, and fruit and vegetable consumption among Alabama high school 
adolescents. 
 
 73
Summary 
Data from the 2003 Youth Risk Behavior Survey (YRBS) were analyzed to 
determine the statistically significant predictors and prevalence rates between BMI, 
television viewing, physical activity levels, and fruit and vegetable consumption. Thirty 
nine public schools in Alabama were surveyed in Spring of 2003. One thousand eighty-
eight (1088) students participated; 545 were females (51.1%) and 510 were males 
(48.9%). There were 752 White (61.1%) and 224 Black (36.7%) adolescents in this study. 
All Other Races (2.2%) were too small to analyze the data. There were 282 ninth 
(30.1%), 270 tenth (25.9%), 240 eleventh (22.6%), and 251 twelfth (20.9%) grade 
adolescents who completed the survey.  
The 2003 YRBS is an assessment of priority health-risk behaviors among 
representative samples of students in grades 9?12, at the national, state, and local levels. 
Six categories of behavior, identified by the Centers for Disease Control and Prevention 
(2004), which directly influence adverse health and social problems in adolescents were 
assessed. These were: 
(1) behaviors that result in unintentional and intentional injuries, 
(2) drug and alcohol use, 
(3) sexual behaviors that result in HIV infection, other sexually transmitted 
diseases and unintended pregnancy, 
(4) tobacco use, 
(5) dietary behaviors, and 
(6) physical activity. 
 74
 The categories explored in this study related to television viewing, physical 
activity levels and fruit and vegetable consumption. The survey questions used were:  
1) On an average school day, how many hours do you watch TV;  
2) On how many of the past 7 days did you participate in physical activity for 
at least 30 minutes that did not make you sweat or breathe hard, such as 
fast walking, slow bicycling, skating, pushing a lawn mower, or mopping 
floors;  
3) On how many of the past 7 days did you exercise or participate in physical 
activity for at least 20 minutes that made you sweat and breathe hard, such 
as basketball, soccer, running, swimming laps, fast bicycling, fast dancing, 
or similar aerobic activities;  
4) During the past 7 days, how many times did you eat fruit;  
5) During the past 7 days, how many times did you eat green salad;  
6) During the past 7 days, how many times did you eat potatoes;  
7) During the past 7 days, how many times did you eat carrots; and, 
8) During the past 7 days, how many times did you eat other vegetables?  
For this study, the YRBS data were made available by the Center for Disease 
Control and Prevention. The data are public use files of national data sets and are usable 
without restriction. Logistic regression was used to determine statistically significant 
predictors and prevalence rates between variables for the following research questions: 
1. What, if any, is the relationship between television viewing, physical 
activity levels, and fruit and vegetable consumption and BMI among Alabama high 
school adolescents? 
 75
2. If so, to what extent does overweight status (BMI) affect prevalence rates 
for television viewing of Alabama high school adolescents? 
3. If so, to what extent does overweight status (BMI) affect prevalence rates 
in physical activity levels of Alabama high school adolescents? 
4. If so, to what extent does overweight status (BMI) affect prevalence rates 
by fruit and vegetable consumption of Alabama high school adolescents? 
 
Discussion 
 No significant relationships between variables were found between BMI, 
television viewing, physical activity levels, and fruit and vegetable consumption among 
Alabama high school adolescents. Although numerous factors and variables related to 
BMI and television viewing, physical activity levels, and fruit and vegetable 
consumption, in general, have been identified in existing literature.  
 Television viewing is a sedentary behavior most often associated with 
adolescents. Adolescents may spend an average of 35 hours per week watching television 
(AC Nielson Company, 1989). In this study, there was no statistically significant 
differences between BMI levels and television viewing (p = 0.1931). Because watching 
television has been shown to affect energy intake and encourage consumption of high 
calorie foods it was thought that those adolescents who watched the most television 
would have the greatest dietary intake. Television viewing has been associated with 
increased energy intake due to food advertisements, snacking more often, and increased 
food consumption among obese individuals when exposed to television programs that 
incorporated food commercials (Dietz, 1991). Television viewing is the single greatest 
 76
source of physical inactivity among American children, other than sleep (Dietz & 
Strasburger, 1991).  
 Physical activity is an important component of a healthy lifestyle, with 
implications for the prevention of chronic diseases and obesity conditions (United States 
Department of Health and Human Services, 1996). However, physical activity declines 
sharply during adolescence, especially among girls (Neumark-Sztainer, Story, Hannan, 
Tharp, & Rex, 2003). In this study, there was no statistically significant differences 
between BMI and physical activity levels (vigorous p = 0.6765 and moderate  
p = 0.2590), when all other variables were deleted and vigorous and moderate physical 
activity levels and BMI were analyzed. The United States Department of Health and 
Human Services (2000) recommends < 3 days per week for the criteria as not being 
vigorously physically active, and > 3 days per week as the criteria for being vigorously 
physically active. For moderately physically active the Untied States Department of 
Health and Human (2000) services recommends > 5 days per week and < 5 day per week 
is considered to not be moderately physically active.  
 The third factor explored in this study was fruit and vegetable consumption. 
According to the United States Department of Agriculture (USDA, 1995) Food Guide 
Pyramid guidelines for fruit and vegetable consumption, adolescents should consume 2?4 
servings per day of fruits and 3?5 servings per day of vegetables (Dixon, Cronin, & 
Krebs-Smith, 2001). Adolescents would need to consume a minimum of 5 fruits and 
vegetable servings a day to meet a minimum of USDA requirements. Many youth engage 
in unhealthy dieting practices and have erratic eating patterns that include high intakes of 
fast foods and other foods high in fat and sugar, as well as, low intakes of fruits and 
 77
vegetables, and calcium rich foods (Neumark-Sztainer, Story, Resnick, & Blum, 1996). 
While the USDA Food Guide Pyramid recommends three to five servings of vegetables 
per day and two to four servings of fruits, only one in five children consumes five or 
more servings of fruits and vegetables daily (Dixon, Cronin, Krebs-Smith, 2001). Studies 
to date show a lack of concern for healthy eating on the part of young people and little 
normative support for healthy eating (Croll, Neumark-Sztainer, & Story, 2001). Eating 
behaviors are central to an adolescent?s physical development and health. In this study, 
there was no statistically significant differences between obesity and fruit and vegetable 
consumption (p = 0.6943), when all other variables were deleted and BMI and fruit and 
vegetable consumption were analyzed. 
 
Limitations 
 Many different hypotheses exit to delineate the various possible reasons for these 
results. The small sample size of Alabama adolescents in this study (N = 1088) may have 
been a limiting factor. A study by Dietz and Gortmaker (1985), and the National 
Longitudinal Study of Adolescent Health (Gordon-Larsen, McMurray, & Popkin, 1999) 
all included large nationally representative samples of adolescents 6600 and 14,000 
respectively. 
 The physical activity measure for this study may not provide reliable and valid 
data for use with adolescents. Adolescents have been shown to under and over estimate 
the amount of exercise in which they participate (U. S. Department of Health and Human 
Services, 2001). Self-report of physical activity levels may not be an accurate tool for 
measuring physical activity levels for adolescents.  
 78
Adolescents, as an age group, tend to underreport their dietary intake (U.S. 
Department of Health and Human Services, 2001); a more accurate way of measuring 
fruit and vegetable consumption should be considered. This measure with adolescents 
may not be an accurate tool for self-report of fruit and vegetable consumption.  
Self reported height and weight was used to calculate body mass index (BMI), 
expressed as body weight in kilograms divided by the square of height in meters (kg/m2). 
To receive a more accurate BMI for this age group, body composition, using calipers by a 
trained individual, should be considered.  
 
Recommendations 
1. Future research should focus on a larger sample of adolescents. This study 
included 1088 Alabama adolescents, 752 White and 224 Black adolescents. Despite the 
highly complex sampling strategy used to achieve a representative sample of the US 
population, the actual samples sizes become quite small when Youth Risk Behavior 
Survey data are stratified by race, gender, and grade in school. 
2. Additional objective methods to measure the number of hours of television 
viewing may reduce subjective bias. Pairing parental report with adolescent self-report or 
requiring subjects to use television timers are two examples. 
3. Adolescents as an age group tend to underreport their dietary intake (U. S. 
Department of Health & Human Services, 2001); so a more accurate way of measuring 
dietary intake should be developed for this group. A daily log for an extended period of 
time pairing parental report with adolescent self-report would be a consideration. 
 79
4. The use of a trained evaluator to assess activity level frequency, intensity 
and duration of activity levels. Adolescents as an age group tend to over-report the 
amount of physical activity they participate in (U. S. Department of Health & Human 
Services, 2001).  
5. As contemporary United States adolescents become more physically 
inactive, the goal of physical education in schools also needs to be reassessed. According 
to the Center for Disease Control (2004) there is only one state that requires physical 
education every day for all students.  
6. The Youth Risk Behavior Surveys serve many purposes, in light of the 
looming public heath crisis of obesity; the scope of these surveys may need to be 
expanded to encompass public health issues related to overweight adolescents. For 
instance, as Type 2 diabetes is seen in increasing numbers in children and adolescents, 
diabetes might be tracked as part of the surveillance. 
7. Future research may consider comparing different regions within the 
United States (i.e., South to North, East to West).  
8. Comparing the Alabama YRBS data to the national YRBS data could 
provide a valuable educational tool. Awareness of the magnitude of this epidemic is 
critical to correcting and preventing obesity in the future.   
9. Using the YRBS data, look at trends for Alabama, which could provide 
valuable data for areas needing special attention.  
10. From the YRBS survey take out the eleven questions used and conduct a 
survey with these questions only rather than giving the 87 items questionnaire.  
 80
 
 
 
 
 
 
 
 
 
REFERENCES 
 
A C Nielson Company. (1989). Nielson report on television. Northbrook, IL: Nielson 
Media Research. 
American College of Sports Medicine. (2001). Appropriate intervention strategies for 
weight loss and prevention of weight regain in adults. Medicine and Science in 
Sports and Exercise, 22(12), 2145?2156. 
American Diabetes Association Consensus Statement. (2000). Type 2 diabetes in children 
and adolescents. Diabetes Care, 23, 381?389. 
American Dietetic Association. (1999). Position of the American Dietetic Association: 
Dietary guidance for healthy children aged 2 to 11 years. American Dietetic 
Association Journal of the American Dietetic Association, 99(1), 93?101. 
Andersen, R. E., Crespo, C. J., Bartlett, S. J., Cheskin, L. J., & Pratt, M. (1998). 
Relationship of physical activity and television watching with body weight and 
level of fatness among children: Results from the third national health and 
nutritional examination survey. Journal of the American Medical Association, 
279(12), 938?942. 
Arias, E., Anderson, R. N., Kung, H-C., Murphy, S. D., & Kochanek, K. S. (2003). 
Deaths: Final data for 2001. National Vital Statistics Report, 52, 1?100. 
 81
Aristimuno G. G., Foster, T. A., Voors, A. W., Srinivasan, S. R., Berenson, G. S. (1984). 
Influence of persistent obesity in children on cardiovascular risk factors: The 
Bogalusa Heart Study. Circulation, 69(5), 895?904. 
Arluk, S., Branch, J. D., Swain, D. P., & Dowling, E. A. (2003). Childhood obesity?s 
relationship to time spent in sedentary behavior. Military Medicine, 168(7), 583?
586. 
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. 
Englewood Cliffs, NJ: Prentice-Hall. 
Bandura, A. (1989). Regulation of cognitive processes thought perceived self-efficacy. 
Development Psychology, 25, 729?735. 
Battle, E. K., & Brownell, K. D. (1996). Confronting a rising tide of eating disorders and 
obesity: Teatment vs. prevention and policy. Addict Behaviors, 21, 755?765. 
Berkey, C. S., Rockett, H. R., & Field, A. E. (2000). Activity, dietary intake and weight 
changes in a longitudinal study of preadolescent and adolescent boys and girls. 
Pediatrics, 105, 56?64. 
Berkowitz, R. I., & Stunkard, A. J. (2002). Development of childhood obesity. In T. A. 
Wadden & A. J. Stunkard (Eds.), Handbook of obesity treatment. New York: 
Guilford Press. 
Best, J. W., & Kahn, J. V. (1993). Research in education. Boston, MA: Allyn & Bacon. 
Bloomgarden, Z. T. (2002). New insights in obesity. Diabetes Care, 25(4), 789?795. 
Bouchard C. (1991). Is weight fluctuation a risk factor? New England Journal of 
Medicine, 324(26), 1887?1888. 
 82
Bouchard C. (1997). Genetics of human obesity: Recent results form linkage studies. 
Journal of Nutrition, 127, 1887S?1890S. 
Boynton-Jarrett, R., Thomas, T. N., Peterson, K. E., Wiecha, J., Sobol, A. M., & 
Gortmaker, S. L. (2003). Impact of television viewing patterns on fruit and 
vegetable consumption among adolescents. Pediatrics, 112(6), 1321?1326. 
Brener, N. D., Billy, J. O., & Grady, W. R. (2003). Assessment of factors affecting the 
validity of self reported health risk behavior among adolescents: Evidence from 
the scientific literature. Journal of Adolescent Health, 33, 436?457. 
Brener, N. D., Collins, J. L., Kann, L., Warren, C. W., & Williams, B. I. (1995). 
Reliability of the youth risk behavior survey questionnaire. American Journal of 
Epidemiology, 141(6), 575?580. 
Brener, N. D., Kann, L., McManus, T., Kinchen, S. A., Sundberg, E. C., & Ross, J. G. 
(2002). Reliability of the 1999 Youth Risk Behavior Survey Questionnaire. 
Journal of Adolescent Health, 31, 336?342. 
Briefel, R. R., Sempos, C. T., McDowell, M. A., Chien, S., & Alaimo, K. (1997). Dietary 
methods research in the third national health and nutrition examination survey: 
Underreporting of energy intake. American Journal of Clinical Nutrition, 65, 
1203S?1209S. 
Bullen, B. A., Reed, R. B., & Mayer, J. (1964). Physical activity of obese and non-obese 
adolescent girls appraised by motion picture sampling. American Journal of 
Clinical Nutrition, 15, 211?223. 
Burns, C. M., Richman, R., & Caterson, I. D. (1987). Nutrition knowledge in obese and 
overweight. International Journal of Obesity, 11, 485?492. 
 83
Calle, E. E., Thun, M. J., & Petrelli, J. M. (1999). Body mass index and mortality in a 
prospective cohort of U.S. adults. New England Journal of Medicine, 341(15), 
1097?105. 
Caspersen, C. J., & Merritt, R. K. (1995). Physical activity trends among 26 states, 1986?
1990. Medical Science of Sports Exercise, 124, 1878S?1885S. 
Centers for Disease Control and Prevention (CDC). (1994). Prevalence of overweight 
among adolescents ? United States 1988?1991. Morbidity and Mortality Weekly 
Report, 43(44), 818?821. 
Centers for Disease Control and Prevention (CDC). (1996). Guidelines for school health 
programs to promote lifelong healthy eating. Morbidity and Mortality Weekly 
Report: Recommendation and Reports, 45(RR-9), 1?41. 
Centers for Disease Control and Prevention (CDC). (1996). Surgeon general?s report on 
physical activity and health. The Journal of the American Medical Association, 
276, 522. 
Centers for Disease Control and Prevention (CDC). (1996). Youth risk behavior 
surveillance ? United States, 1995. Morbidity and Mortality Weekly Report, 45, 
1?63. 
Centers for Disease Control and Prevention (CDC). (1997). Guidelines for school and 
community programs to promote lifelong physical activity among young people. 
Morbidity and Mortality Weekly Report, 46(No. RR-6), 1?36. 
Centers for Disease Control and Prevention (CDC). (2000). CDC surveillance 
summaries. Morbidity and Mortality Weekly Report (MMWR), 49, No. SS-5. 
 84
Centers for Disease Control and Prevention (CDC). (2001). School health programs and 
policies study: A summary report. Journal of School Health, 71(7), 249?350. 
Centers for Disease Control and Prevention (CDC). (2002). Active community 
environments. Retrieved October 18, 2004 from http://www.cdc.gov/nccdphp/ 
dnpa/aces.htm 
Centers for Disease Control and Prevention (CDC). (2004). Methodology of the Youth 
Risk Behavior Surveillance System. Morbidity and Mortality Weekly Report. 53 
(No. RR12), 1?13.  
Centers for Disease Control and Prevention (CDC), National Center for Health Statistics. 
(1999). NCHS Health E-Stats: Prevalence of overweight among children and 
adolescents: United States, 1999. Retrieved October 1, 2004 from 
http://www.cdc.gov/nchs/products/pubs/pubd/hestats/overwwght00.htm  
Centers for Disease Control and Prevention (CDC), National Center for Health Statistics. 
(2003). CDC growth charts: United States. Retrieved February 1, 2004 from 
http://www.cdc.gov/growthcharts. 
Centers from Disease Control and Prevention (CDC) Press Release. (1999). Prevalence 
of overweight among children and adolescents: United States. Retrieved February 
7, 2004 from http://www.cdc.gov  
Chakravarthy, M. V., & Booth, F. W. (2003). Inactivity and inaction: We can?t afford 
either. Archives of Pediatrics and Adolescent Medicine, 157, 8.  
Charney, E., Goodman, H. C., McBride, M., Lyon, B., & Pratt, R. (1976). Childhood 
antecedents of adult obesity: Do chubby infants become obese adults? New 
England Journal of Medicine, 295, 6?9. 
 85
Chirico, A. M., & Stunkard, A. J. (1963). Physical activity and human obesity. New 
England Journal of Medicine, 263(19), 935?940. 
Christakis, D. A., Zimmerman, F. J., DiGiuseppe, D. L., & McCarty, C. A. (2004). Early 
television exposure and subsequent attentional problems in children. Pediatrics, 
113(4), 708?713. 
Chodorow, N. (1978). The reproduction of mothering. Los Angeles, CA: University of 
California Press. 
Cohen, J. (1985). Obesity: A review. Journal of Consulting and Clinical Psychology, 
59(1), 115?125. 
Committee on Diet and Health, Food and Nutrition Board. (1989). Diet and health: 
Implications for reducing chronic disease risk. Washington, DC: National 
Academy Press. 
Crespo, C. J., Smit, E., Troiano, R. P., Bartlett, S. J., Macera, C. A., Anderson, R. E. 
(2001). Television watching, energy intake, and obesity in US children: Results 
from the third National Health and Nutrition Examination Survey, 1988?1994. 
Archives of Pediatric Adolescent Medicine, 155, 360?365. 
Croll, J. K., Neumark-Sztainer, D., & Story, M. (2001). Healthy eating: What does it 
mean to adolescents? Journal of Nutrition Education, 33(4), 193?199. 
Deckelbaum, R. J., & Williams, C. L. (2001). Childhood obesity: The health issue. 
Obesity, 9(Suppl 4), 239S?243S. 
DeLany, J. (1998). Role of energy expenditure in the development of pediatric obesity. 
American Journal of Clinical Nutrition, 68, 950S?955S. 
 86
Dennison, B., Staus, J., Mellits, E., & Charney, E. (1988). Childhood physical fitness 
test: Predictor of adult physical activity levels? Pediatrics, 82, 324?330.  
Dennison, B. A., Russo, T. J., Burdick, P. A., & Jenkins, P. L. (2004). An intervention to 
reduce television viewing by preschool children. Archives of Pediatrics and 
Adolescent Medicine, 158(2), 170?176. 
Dietz, W. H. (1987). Childhood obesity. Annals of the New York Academy of Sciences, 
499, 47?55. 
Dietz, W. H. (1991). Physical activity and childhood obesity. Nutrition, 7, 295?296. 
Dietz, W. H. (1998). Health consequences of obesity in youth: Childhood predictors of 
adult disease. Pediatrics, 101(suppl 3, pt 2), 518?525. 
Dietz, W. H., Bland, M. G., Gortmaker, S. L., Molloy, M., & Schmid, T. L. (2002). 
Policy tools for the childhood obesity epidemic. The Journal of Law, Medicine 
and Ethics, 30(3), 83?87. 
Dietz, W. H., & Gortmaker, S. L. (1985). Do we fatten our children at the television set? 
Obesity and television viewing in children and adolescents. Pediatrics, 75(5), 
807?812. 
Dietz, W. H., & Gortmaker, S. L. (1993). TV or not TV: Fat is the question [editorial]. 
Pediatrics, 91, 499?500. 
Dietz, W. H., & Gortmaker, S. L. (2001). Preventing obesity in children and adolescents. 
Annual Review of Public Health, 22, 337?353. 
Dietz WH, Strasburger VC. (1991). Children, adolescents, and television. Current 
Problems in Pediatrics, 21, 8?31. 
 87
DiPietro, L., Mossberg, H-O., & Stunkard, A. J. (1994). A 40-year history of overweight 
children in Stockholm: Life-time overweight morbidity, and mortality. 
International Journal of Obesity and Related Metabolic Disorders, 18, 585?590. 
Dixon L. B., Cronin F. J., & Krebs-Smith S. M. (2001). Let the pyramid guide your food 
choices: Capturing the total diet concept. Journal of Nutrition, 131, 461S?472S. 
DuRant, R. H., Baranowski, T., Johnson, M., & Thompson, W. O. (1994). The 
relationship among television watching, physical activity, and body composition 
of young children. Pediatrics, 94, 449?455. 
Epstein, L. H., & Goldfield, G. S. (1999). Physical activity in the treatment of childhood 
overweight and obesity: current evidence and research issues. Medicine Science of 
Sports Exercise, 31(11 supl), S5532?S559.  
Epstein, L. H., Paluch, R. A., Gordy, C. C., & Dorn, J. (2000). Decreasing sedentary 
behaviors in treating pediatric obesity. Archives of Pediatrics and Adolescent 
Medicine, 154, 220?226. 
Erikson, E. H. (1963). Childhood and society (2
nd
 ed.). New York: Norton. 
Erikson, E. H. (1968). Identity, youth and crisis. New York: Norton. 
Everett, S. A., Kann, L., McReynolds, L. (1997). The youth risk behavior surveillance  
system: Policy and program applications. The Journal of School Health, 67, 333?
335. 
Fagot-Campagna, A., Saadinem, J. B., Flegal, K. M., Beckles, G. A. (2001). Diabetes, 
impaired fasting glucose, and elevated hbA1c in U.S. adolescents: The third 
national health and nutrition examination survey. Diabetes Care, 24, 834?837. 
 88
Faigenbaum, A. (1998). Fundamental fitness in children: recommendation for keeping 
kids health and fit. American College of Sports Medicine Health and Fitness 
Journal, 2, 18?22. 
Faith, M. S., Pietrobelli, A., Nenez, C., Heo, M., Heymsfield, S. B., & Allison, D. B. 
(1999). Evidence for independent genetic influences on fat mass and body mass 
index in a pediatric twin sample. Pediatrics, 104, 61?67. 
Feldman, D. E., Barnett, T., Shrier, I., Rossignol, M., & Abenhaim, L. (2003). Is physical 
activity differentially associated with different types of sedentary pursuits? 
Archives of Pediatrics & Adolescent Medicine, 157, 797?802. 
Felts, M., Tavasso, D., Chenier, T., & Dunn, P. (1992). Adolescents? perceptions of 
relative weight and self-reported weight loss activities. The Journal of School 
Health, 62(8), 372. 
Flegal, K. M., Carroll, M. D., Kuczmarski, R. J., & Johnson, C. L. (1998). Overweight 
and obesity in the United States: Prevalence and trends. The International Journal 
of Obesity, 22, 23. 
Flegal, K. M., Carroll, M. D., Ogden, C. L, & Johnson, C. L. (2002). Prevalence and 
trends in obesity among US adults, 1999?2000. Journal of the American Medical 
Association, 288, 1723?1727. 
Fontaine, K. R., Redden, D. T., Wang, C., Westfall, A.O., & Allison, D. B. (2003). Years 
of life lost due to obesity. Journal of the American Medical Association, 289, 
187?193. 
Foreyt, J. P. (1987). Issues in the assessment and treatment of obesity. Journal of 
Consulting and Clinical Psychology, 55(5), 677?684. 
 89
Foreyt, J. P., & Cousins, J. H. (1989). Obesity. In E. Mash & R. Barbley (Eds.), 
Treatment of childhood disorders (pp. 405?422). New York: Guilford Press.  
Ford, E., & Mokdad, A. H. (2001). Fruit and vegetable consumption and diabetes 
mellitus incidence among U.S. adults. Preventive Medicine, 32, 33?39. 
Francis, C., Bope, A., MaWhinney, S., Czajka-Narins, D., & Alford, B. (1999). Body 
composition, dietary intake, and energy expenditure in nonobese, prepubertial 
children of obese and non obese biological mothers. American Dietetic 
Association Journal of the American Dietetic Association, 99, 58?65. 
Freedman, D. C., Dietz, W. H., Scinivasan, S. R, & Berenson, G. S. (1999). The relation 
of overweight to cardiovascular risk factors among children and adolescents: The 
Bogalusa Heart Study. Pediatrics, 101, 518?525. 
Freedman, D. S., Dietz, W. H., Srinivasan, S. R., & Berenson, G. S. (1999). The relation 
of overweight to cardiovascular risk factors among children and adolescents: The 
Bogalusa Heart Study. Pediatrics, 103, 1175?1182. 
Freedman, D. S., Khan, L. K., Dietz, W. H., Srinivasan, S. R., & Berenson, G. S. (2001). 
Relationship of childhood obesity to coronary heart disease risk factors in 
adulthood: The Bogalusa Heart Study. Pediatrics, 108(3), 712?718. 
Freedman, D. S., Shear, C. L., Burke, G. L., Srinivasan, S. R., Webber, L. S., Harsha, D. 
W. (1987). Persistence of juvenile-onset obesity over eight years: The Bogalusa 
Heart Study. American Journal of Public Health, 77, 588?592. 
French, S. A., Story, M., Neumark-Sztainer, D., Fulkerson, J. A., & Hannan, P. (2001). 
Fast food restaurant use among adolescents: Associations with nutrient intake, 
 90
food choices and behavioral and psychosocial variables. International Journal of 
Obesity, 25, 1823?1833. 
Freud, S. (1954). Collected works, standard edition. London: Hogarth Press. 
Freud, S. (1961). Some psychical consequences of the anatomical differences between 
the sexes. In J. Strachey (Ed.), Standard edition of the complete psychological 
works of Sigmund Freud (Vol. 19). London: Hogart Press. 
Fried, E., & Nestle, M. (2002). The growing political movement against soft drinks in 
schools. Journal of the American Medical Association, 288, 2181?2182. 
Fruhbeck, G. (2000). Childhood obesity: Time for action, not complacency. British 
Medical Journal, 320, 328?329. 
Gam, S. M. (1995). Continuities and changes in fatness from infancy through adulthood. 
Current Problems in Pediatrics, 15, 1?47. 
Gazzaniga, J., & Burns, T. (1993). Relationship between diet composition and body 
fatness, with adjustment for resting energy expenditure and physical activity, in 
preadolescent children. American Journal of Clinical Nutrition, 58, 21?28. 
Giammattei, J., Blix, G., Marshak, H. H., Wollitzer, A. O., & Pettitt, D. J. (2003). 
Television watching and soft drink consumption. Archives of Pediatrics and 
Adolescent Medicine, 157(9), 882?886. 
Gifford, K. D. (2002). Dietary fats, eating guides, and public policy: History, critique, 
and recommendations. American Journal of Medicine, 113(suppl 9B), 89S?106S. 
Gilligan, C. (1988). Adolescent development reconsidered. In C. Gilligan, J. V. Ward, J. 
M. Taylor, & B. Bardige (Eds.), Mapping the moral domain. Cambridge, MA: 
Harvard University Press.  
 91
Gilligan, C., & Attanucci, J. (1988). Two moral orientations: Gender differences and 
similarities. Merrill-Palmer Quarterly, 34, 223?237. 
Glaser, N. S. (1997). Non-insulin-dependent diabetes mellitus I childhood and 
adolescence. Pediatric Clinics of North America, 44, 307?337. 
Glass, G. V., & Hopkins, K. D. (1996). Statistical methods in education and psychology. 
(3rd ed.). Boston: Allyn and Bacon.  
Gordon-Larsen, P., McMurray, R. G., & Popkin, B. M. (1999). Adolescent physical 
activity and inactivity vary by ethnicity: The National Longitudinal Study of 
Adolescent Health. Journal of Pediatrics, 135, 301?306. 
Goran, M. I., & Treuth, M. S. (2001). Energy expenditure, physical activity, and obesity 
in children. Pediatric Clinic North America, 48(4), 931?953. 
Gortmaker, S. L., Dietz, W. H., & Cheung, L. W. Y. (1990). Inactivity, diet, and the 
fattening of America. American Dietetic Association Journal of the American 
Dietetic Association, 90(9), 1247?1252. 
Gortmaker, S. L., Dietz, W. H., Sobol, A. M., & Wehler, C. A. (1987). Increasing 
pediatric obesity in the United States. American Journal of Diseases of Children, 
141, 535?540. 
Gortmaker, S. L., Must, A., Sobol, A. M., Peterson, K., Colditz, G. A., & Dietz, W. H. 
(1996). Television viewing as a cause of increasing obesity among children in the 
United States, 1986?1990. Archives of Pediatric Adolescent Medicine, 150, 356?
362. 
 92
Guo, S. S., & Chumlea, W. C. (1999). Tracking of body mass index in children in 
relation to overweight in adulthood. American Journal of Clinical Nutrition, 70, 
145S?148S. 
Guo, S. S., Roche, A. F., Chumlea, W. C., Gardner, J. R., & Siervogel, R. M. (1994). The 
predictive value of childhood body mass index values for overweight at age 35 
years. American Journal of Clinical Nutrition, 59, 810?819. 
Guo, S. S., Wu, W., Chumlea, W. C., & Roche, A. F. (2002). Predicting overweight and 
obesity in adulthood from body mass index values in childhood and adolescence. 
American Journal of Clinical Nutrition, 76, 653?658. 
Gutin, B., & Manos, T. M. (1993). Physical activity in the prevention of childhood 
obesity. Annals of the New York Academy of Sciences, 699, 115?126. 
Hall, G. S. (1904). Adolescence: Its psychology and its relations to physiology, 
anthropology, sociology, sex, crime, religion, and education (Vol. 1). New York: 
Appleton-Century-Crofts. 
Hammerberg, D. D. (1992). The association between television viewing and related video 
activities, physical activity level, and weight in obese and non-obese fourth grade 
children. Unpublished doctoral dissertation, University of Denver, Denver, CO. 
Harsha, D. W. (1995). The benefits of physical activity in childhood. American Journal 
of Medical Science, 23(suppl 1), S109?113. 
Havighurst, R. J. (1972). Developmental tasks and education. New York: David McKay. 
Hill, J., & Throwbridge, F. (1998). The cause and health consequences of obesity in 
children and adolescents. Pediatrics, 101, 497?575. 
 93
Himes, J. H., & Dietz, W. H. (1994). Guidelines for overweight in adolescent 
preventative services: Recommendations from an expert committee. The Expert 
Committee on Clinical Guidelines for Overweight in Adolescent Preventative 
Services. American Journal of Clinical Nutrition, 59, 307. 
Hinkle, D. E., Wiersma, W., & Jurs, S. G. (1994). Applied statistics for the behavioral 
sciences (3rd ed.). Boston: Houghton Mifflin. 
Horney, K. (1967). Feminine psychology. New York: Norton.  
Hosmer, D. W., Jr., & Lemeshow, S. (1989). Applied logistic regression. New York: 
John Wiley & Sons. 
Hu F. B., Leitzamlam, M. F., Stampfer, M. J., Coldditza, G. A., Williet, W. C, & Rimm, 
E. B. (2001). Physical activity and television watching in relation to risk for type 
2 diabetes mellitus in men. Archives in International Medicine, 161, 1542?1548. 
Hu, F., Manso, J. E, & Willett, W. C. (2001). Types of dietary fat and risk of coronary 
heart disease: A critical review. Journal of the American College of Nutrition, 20, 
5?19. 
Jacobson, M. (1998). Liquid candy: How soft drinks are harming America?s health. 
Center for Science and the Public Interest web site. October 1998. Available at: 
http://www.cspinet.org/sodapop/liquid_candy.htm. Accessed January 29, 2004. 
Jeffery, R. W., & French, S. A. (1998). Epidemic obesity in the United States: Are fast 
foods and television viewing contributing? American Journal of Public Health, 
88(2), 277?280. 
 94
Jette, M., Berry, W., & Pearlman, L. (1977). The effects of an extracurricular physical 
activity program on obese adolescents. Canadian Journal of Public Health, 68, 
39?42. 
Johnston, F. E. (1985). Health implication of childhood obesity. Annual of Internal 
Medicine, 101, 497?505. 
Johnston, L. D., O?Malley, P., & Bachman, J. (2002). National survey results on drug use 
from the monitoring the future study of secondary school students. Bethesda: MD: 
National Institute on Drug Abuse. 
Kennedy, C. (2000). Television and young Hispanic children?s health behaviors. 
Pediatric Nursing, 26(3), 283?294. 
Kennedy, C. M., Strzempki, F., Danford, C., & Kools, S. (2002). Children?s perceptions 
of TV and health behaviors effects. Journal of Nursing Scholarships, 34(3), 289?
294. 
Kimm, S. Y. S., & Obarzanek, E. (2002). Childhood obesity: A new pandemic of the new 
millennium. Pediatrics, 110(5), 1003?1007. 
Kinsey, J. D. (1994). Food and families? socioeconomic status. Journal of Nutrition, 124, 
1878S?1885S. 
Klesges, R. C., Klesges, L. M., Eck, L. H., & Shelton, M. L. (1995). A longitudinal 
analysis of accelerated weight gain in preschool children. Pediatrics, 95, 126?
132. 
Kleinbaum, D. G. (1994). Logistic regression: A self-learning text. New York: Springer-
Verlag. 
 95
Kolbe, L. J., Kann, L., & Collins, J. L. (1993). Overview of the youth risk behavior 
surveillance system. Public Health Report, 108(Suppl 1), 2?10. 
Kotz, K., & Story, M. (1994). Food advertisements during children?s Saturday morning 
television programming: Are they consistent with dietary recommendations? 
American Dietetic Association Journal of the American Dietetic Association, 94, 
1296?1300. 
Kraak, V., & Pelletier, D. (1998). The influence of commercialism on the food 
purchasing behavior of children and teenage youth. The Family Economic 
Nutritional Review, 11, 15?23. 
Kronenberg, F., Pereira, M. A., & Schmitz, M. K. (2000). Influence of leisure time 
physical activity and television watching on atherosclerosis risk factors in NHLBI 
Family Heart Study. Atherosclerosis, 153, 433?443. 
Kuczmarski, R. J., Flegal, K. M., Campbell, S. M, & Johnson, C. L. (1994). Increasing 
prevalence of overweight among U.S. adults: The National Health Nutrition 
Examination Surveys, 1960 to 1991. The Journal of the American Medical 
Association, 272, 205?221. 
Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago: University of 
Chicago Press. 
LaVecchia, C., & Tavani, A. (1998). Fruit and vegetables, and human cancer. European 
Journal of Cancer Prevention, 7, 3?8. 
Lin, B. H., Guthrie, J., & Blaylock, J. (1996). The diet of America?s children: Influences 
of dining out, household characteristics, and nutrition knowledge. Washington, 
DC: US Department of Agriculture: Economic Number 746 (AER-746).  
 96
Lin, B. H., Guthrie, J., & Frazao, E. (1999). Quality of children?s diets at and away from 
home: 1994?1996. Food Review, 22(1), 2?10. 
Lindquist, C., Gower, B., & Goran, M. (2000). Role of dietary factors and ethnic 
differences in early risk of cardiovascular disease and type 2 diabetes. American 
Journal of Clinical Nutrition, 71, 725?732. 
Lowry, R., Wechsler, H., Kann, L., & Collins, J. (2001). Recent trends in participation in 
physical education among US high school students. Journal of School Health, 71, 
145?152. 
Ludwig, D. S., & Ebbeling, C. B. (2001). Type 2 diabetes mellitus in children: Primary 
care and public health considerations. Journal of the American Medical 
Association, 286, 1427?1430. 
Ludwig, D., Peterson, K., & Gortmaker, S. (2001). Relation between consumption of 
sugar sweetened drinks and childhood obesity: A prospective, observational 
analysis. Lancet, 357, 505?506. 
Lytle, L. A. (2002). Nutritional issues for adolescents. American Dietetic Association 
Journal of the American Dietetic Association, 102(3), S8?S12. 
Maloney, M. J., McGuire, J., Daniels, S. R., & Specker, B. (1989). Dieting behavior and 
eating attitudes in children. Pediatrics, 84(3), 482?489. 
Manos, T. M., Gutin, B., Rhodes, T., Spandorfer, P. R., Jackson, L. W., & Litaker, M. S. 
(1993). Energy expenditure and intake in obese and non-obese African American 
girls. Annals of the New York Academy of Sciences, 699, 275?277. 
 97
Marshall, S. I., Sarkin, J. A., Sallis, J. F., & McKenzie, T. L. (1998). Tracking of health-
related fitness components in youth ages 9 to 12. Medical Science of Sports 
Exercise, 30, 910?916. 
McDowell, M. A., Briefel, R. R., & Alaimo, K. (1994). Energy and macronutrient intakes 
of person ages 2 months and over in the United States: Third National Health and 
Nutrition Examination Survey, phase 1, 1988?1991. Advance Data Vital Health 
Statistics. No. 255. DHHS publications PHS 95?1250. 
Menard, S. (1995). Applied logistic regression analysis. Thousands Oaks, CA: Sage 
Publications. 
Munoz, K. A., Krebs-Smith, S. M., Ballard-Barbash, R., & Cleveland, L. E. (1997). Food 
intakes of U.S. children and adolescents compared with recommendations. 
Pediatrics, 199, 323?329.  
Must, A., Jacques, P. F., Dallal, G. E., Bajema, D. J., & Dietz, W. H. (1992). Long-term 
morbidity and mortality of overweight adolescents: a follow-up of the Harvard 
Growth Study of 1922 to 1935. New England Journal of Medicine, 327, 1350?
1355. 
Must, A., & Strauss, R. S. (1999). Risks and consequences of childhood and adolescent 
obesity. International Journal of Obesity and Related Metabolic Disorders, 
23(Suppl 2), S2?S11, 25, 497?505.  
Nader, P. R. (1993). The Kellogg children?s nutrition survey. American Dietetic 
Association Journal of the American Dietetic Association, 699, 147?153. 
 98
National Center for Health Statistics (NCHS). (2000). Health, United States, 2000 with 
adolescent health chartbook. Retrieved November 2004 from 
http://www.cec.gov/nchs/data/hus/hus00cht.pdf 
Neufeld, N. D., Raffel, L. J., Landon, C., Chen, Y. D., & Vadheim, C. M. (1998). Early 
presentation of type 2 diabetes in Mexican-American youth. Diabetes Care, 21, 
80?86. 
Neumark-Sztainer, D., Story, M., Hannan, P. J., Tharp, T., & Rex, J. (2003). Factors 
associated with changes in physical activity. Archives of Pediatrics and 
Adolescent Medicine, 157, 8. 
Neumark-Sztainer, D., Story, M., Resnick, M., & Blum, R. (1996). Correlates of 
inadequate fruit and vegetable consumption among adolescents. Preventive 
Medicine, 25, 497?503. 
Nieto, F. J., Szklo, M., & Comstock, G. W. (1992). Childhood weight and growth rates as 
predictors of adult mortality. American Journal of Epidemiology, 136(2), 201?
213. 
Obarzanek, E. (1993). Methodological issues in estimating the prevalence of obesity in 
childhood. Annals of the New York Academy of Sciences, 699, 278?279. 
Ogden, C. L., Flegal, K. M., Carroll, M. D., & Johnson, C. L. (2002). Prevalence and 
trends in overweight among U.S. children and adolescents, 1999?2000. Journal of 
the American Medical Association, 288, 1728?1732. 
Overton, W. F., Ward, S. L., Noveck, I. A., Black, J., & O?Brien, D. P. (1987). Form and 
content in the development of deductive reasoning. Developmental Psychology, 
23, 22?30. 
 99
Pace, P. J., Webster, J., & Garrow, J. S. (1986). Exercise and obesity. Sports Medicine, 3, 
89?113. 
Perrine, M. W., Peck, R. C., & Fell, J. C. (1988). Epidemiologic perspectives on drunk 
driving. In Surgeon General?s workshop on drunk driving: Background papers 
(pp. 35?76). Washington, DC: U.S. Department of Health and Human Services, 
Public Health Service, Office of the Surgeon General. 
Perusse, L., & Bouchard, C. (2000). Gene-diet interactions in obesity. American Journal 
of Clinical Nutrition, 72(suppl), 1285S?1290S. 
Piaget, J. (1954). The construction of reality in the child. New York: Basic Books.  
Pinhas-Hamiel, O., Dolan, L. M., Daniels, S. R., Staniford, D., Khoury, P. R., & Zeitler, 
P. (1996). Increased incidence of non-insulin dependent diabetes mellitus among 
adolescents. The Journal of Pediatrics, 128, 608?615. 
Power, C., Lake, J. K., & Cole, T. J. (1997). Measurement and long-term health risks of 
child and adolescent fatness. International Journal of Obesity and Related 
Metabolic Disorders, 21, 507?526.  
Public Health Service. (1991). Healthy people 2000: National health promotion and 
disease prevention objectives. Washington, DC: U.S. Department of Health and 
Human Services. 
Raitakari, O. T., Porkka, K. V., Taimela, S., Telama, R., Rasanen, L., & Vikari, J. S. A. 
(1994). Effects of persistent physical activity and inactivity on coronary risk 
factors in children and young adults. American Journal of Epidemiology, 140, 
195?205. 
 100
Reese, H. W., & Overton, W. F. (1970). Models of development and theories of 
development. In L.R. Goulet & P. B. Baltes (Eds.), Lifespan development 
psychology: Research and theory. New York: Academic Press.  
Renaud, S. (2001). Diet and stroke. Journal of Nutritional Health. 5, 167?172. 
Roberts, S. B. (1993). Energy expenditure and the development of early obesity. Annals 
of the New York Academy of Sciences, 699, 18?25. 
Robinson, B. (1995). Television advertising for health. Pediatric Annals, 24(2), 73?78. 
Robinson, T. (1998). Does television cause childhood obesity? Journal of the American 
Medical Association, 279(12), 959?960. 
Robinson, T. N. (1999). Reducing children?s television viewing to prevent obesity: A 
randomized controlled trial. Journal of the American Medical Association, 282, 
1561?1567. 
Robinson, T. N., Wilde, M. L., Navracruz, L. C., Haydel, K. F., & Varady, A. (2001). 
Effects of reducing children?s television and video game use on aggressive 
behavior: A randomized controlled trial. Archives of Pediatrics & Adolescent 
Medicine, 155, 17?23. 
Rocchini, A. P. (2002). Childhood obesity and a diabetes epidemic. New England 
Journal of Medicine, 346, 854?855. 
Rosenbaum, M., Leibel, R. L., & Hirsch, J. (1997). Obesity. New England Journal of 
Medicine, 337, 396?407. 
Sadowsky, H. S., Sawdon, J. M., Scheiner, M. E., & Sticklin, A. M. (1999). Eight weeks 
moderate intensity exercise intervention elicits body composition change in 
adolescents. Cardiopulmonary Physical Therapy Journal. 10, 2. 
 101
Salvaggio, J. L., Bryant, J., (Eds.). (1989). Media use in the information age: Emerging 
patterns of adaptation and consumer use. Hillsdale, NJ: Lawrence Erlbaum. 
Schlosser, E. (2002). Fast food nation. New York: Harper Collins. 
Serdula, N. J., Ivery, D., Coates, R. J., Freedman, D. S., Williamson, D. F., & Byers, T. 
(1993). Do obese children become obese adults? A review of literature. 
Preventive Medicine, 22, 167?177. 
Shah, M., & Jeffrey, R. W. (1991). Is obesity due to overeating and inactivity, or to a 
defective metabolic rate? A review. Annals of Behavioral Medicine, 13(2), 73?81. 
Shannon, B., Peacock, J., & Brown, J. M. (1991). Body fatness, television viewing and 
calorie-intake of a sample of Pennsylvania sixth grade children. Journal of 
Nutritional Education, 23(6), 262?268. 
Shear, C. L., Freedman, D. S., Burke, G. L., Harsha, D. W., Webber, L. S., & Berenson, 
G. S. (1988). Secular trends of obesity in early life: The Bogalusa Heart Study. 
American Journal of Public Health, 78(1), 75?77 
Simons-Morton, G. B., Parcel, G. S., Baranowski, T., Forthofer, R., & O?Hara, N. M. 
(1991). Promoting physical activity and a healthful diet among children: Results 
for a school-based intervention study. American Journal of Public Health, 81(8), 
986?991. 
Skinner, B. F. (1938). The behavior of organisms: An experimental analysis. New York: 
Appleton-Century-Crofts. 
Skinner, B. F. (1953). Science and human behavior. New York: Macmillan. 
Skinner, B. F. (1961). Cumulative record (rev. ed.). New York: Appleton-Century-Crofts.  
 102
Southam, M. A., Kirkley, B. G., Murchison, A., & Berkowitz, R. I. (1984). A summer 
day camp approach to adolescent weight loss. Adolescence, 29(76), 855?868. 
Steinberger, J., Moran, A., Hong, C. P., Jacobs, D. R., & Sinaiko, A. R. (2001). Adiposity 
in childhood predicts obesity and insulin resistance in young adulthood. The 
Journal of Pediatrics, 138, 469?473. 
Steinmetz, K., & Potter, J. (1991). Vegetables, fruit, and cancer. Journal of 
Epidemiology, 2, 325?357. 
Stephens, M. B., Harrison, J. J., Wilson, C., Ringler, R. L., & Robinson, C. (2003). Are 
children of military parents more physically fit than children of civilian parents? 
Family Medicine, 35(5), 404?407. 
Steptoe, A., & Butler, N. (1996). Sports participation and emotional wellbeing in 
adolescents. Lancet, 347, 1789?1792. 
Story, M., Neumark-Sztainer, D., & French, S. (2002). Individual and environmental 
influences on adolescent eating behaviors. American Dietetic Association, 102(3), 
S40?S51. 
Stubbs, R. J., Prentice, A. M., & James, W. P. (1997). Carbohydrates and human appetite. 
Annual New York Academy of Science, 819, 44?69. 
Sugarman, J. R., White, L. L., & Gilbert, T. J. (1990). Evidence for a secular change in 
obesity, height, and weight among Navajo Indian schoolchildren. American 
Journal of Clinical Nutrition, 52, 960?966. 
Sylper, A. H. (1998). Childhood obesity, adipose tissue distribution, and the pediatric 
practitioner. Pediatrics, 102(1), e4?e19. 
 103
Taras, H., Sallis, J., Patterson, T., Nader, P., & Nelson, J. (1989). Television?s influence 
on children?s diet and physical activity. Developmental and Behavioral 
Pediatrics, 10(4), 176?180. 
Telama, R., Xiaolin, Y., Laakso, L., & Vilkari, J. (1997). Physical activity in childhood 
and adolescence as predictor of physical activity in young adulthood. American 
Journal of Preventive Medicine, 13, 317?323. 
Thakur, N., & D?Amico, F. (1999). Relationship of nutrition knowledge and obesity in  
 adolescence. Family Medicine, 21(2), 122?127. 
Troiano, R. P., & Flegal, K. M. (1998). Overweight children and adolescents: 
Description, epidemiology, and demographics. Pediatrics, 101, 497?504. 
Troiano, R. P., Flegal, K. M., Kuczmarski, R. J., Campbell, S. M., & Johnson, C. L. 
(1995). Overweight prevalence and trends for children and adolescents: The 
National Health Examination Surveys (NHANES), 1963?1991. Archives of 
Pediatrics & Adolescent Medicine, 149, 1085?1091. 
Tucker, L. A. (1986). The relationship of television viewing to physical fitness and 
obesity. Adolescence, 21(84), 797?806. 
Tucker, L., & Bagwell, M. (1991). Television viewing and obesity in adult females. 
American Journal of Public Health, 62(2), 124?137. 
Tucker, L., Selijaas, G., & Hager, R. (1997). Body fat percentage of children varies 
according to their diet composition. American Dietetic Association Journal of the 
American Dietetic Association, 97, 981?986. 
 104
U. S. Department of Agriculture (USDA) and U. S. Department of Health and Human 
Services. (1995). Nutrition and your health: Dietary guidelines for Americans (4
th
 
ed.). Washington, DC: Author.  
U. S. Department of Agriculture (USDA) and U. S. Department of Health and Human 
Services. (2000). Report of the dietary guidelines advisory committee. 
Washington, DC: Author.  
U. S. Department of Health and Human Services. (1988). The surgeon general?s report 
on nutrition and health. Washington, DC: Government Printing Office. 
U. S. Department of Health and Human Services. (1996). Physical activity and health: A 
report of the surgeon general. Atlanta, GA: Centers for Disease Control and 
Prevention, National Center for Chronic Disease Prevention and Health 
Promotion. 
U. S. Department of Health and Human Services. (2000). Physical activity and health: A 
report of the surgeon general. Atlanta, GA: Author.  
U. S. Department of Health and Human Services. (2000) Healthy people 2010: With 
understanding and improving health (2
nd
 ed.). Washington, DC: U.S. Government 
Printing Office.  
U. S. Department of Health and Human Services. (2001). The surgeon general?s call to 
action to prevent and decrease overweight and obesity. Rockville, MD: U.S. 
Department of Health and Human Services, Public Health Service, Office of the 
Surgeon General.  
 105
U. S. Public Health Service. (1988). The surgeon general?s report on nutrition and 
health. Washington, DC: U.S. Department of Health and Human Services, Public 
Health Service (PHS) 88-50210. 
Utter, J., Neumark-Sztainer, D., Jeffery, R., & Story, M. (2003). Couch potatoes or 
french fries: Are sedentary behaviors associated with body mass index, physical 
activity, and dietary behaviors among adolescents? American Dietetic 
Association, 103, 10. 
Vanhala, M., Vanhala, P., Kumpusalo, E., Halonen, P., & Takala, J. (1998). Relation 
between obesity and childhood to adulthood and the metabolic syndrome: 
population based study. British Medical Journal, 317?319. 
Wang, G., & Dietz, W. H. (2002). Economic burden on obesity in youths ages 6 to 17 
years: 1976?1999. Pediatrics, 105, 671?680. 
Wechsler, H., Brener, N., Kuester, S., & Miller, C. (2001). Food service and foods and 
beverages available at school: Results from the School Health Policies and 
Programs Study 2000. Journal of School Health, 71(7), 313?324.  
Whitaker, R. C., Wright, J. A., Pepe, M. S., Seidel, K. D., & Dietz, W. H. (1997). 
Predicting obesity in young adulthood from childhood and parental obesity. New 
England Journal of Medicine, 337, 869?873. 
Williams, C. L., Bollella, M., & Carter, B. J. (1993). Treatment of childhood obesity in 
pediatric practice. Annals of the New York Academy of Sciences, 699, 207?219. 
Wolf, A. M., Gortmaker, S. L., Cheung, L., Gray, H. M., Herzog, D. B., & Colditz, G. A. 
(1993). Activity, inactivity, and obesity: Racial, ethnic, and age differences 
among schoolgirls. American Journal of Public Health, 83(11), 1625?1627. 
 106
Young, T. K., Dean, H. J., Flett, B., & Wood-Steiman, W (2000). Childhood obesity in a 
population at high risk for type 2 diabetes. The Journal of Pediatrics, 128, 263?
267. 
Zakus, G., Chin, M. L., Cooper, H., Makovsky, E., & Merrill, C. (1981). Treating 
adolescent obesity: A pilot project in a school. The Journal of School Health, 
663?666.