Body Satisfaction
Running head: BODY SATISFACTION
Temporal Trends in Body Satisfaction and Weight Controlling Behaviors
Among US High School Students 1999-2007
Andrea E. Kirby
Vanderbilt University
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Body Satisfaction
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Table of Contents
Table of Contents ............................................................................................................................ 2
Abstract ........................................................................................................................................... 4
Temporal Trends in Body Dissatisfaction and Weight Controlling Behaviors .............................. 5
Spread and Internalization of the “Thin Ideal” ........................................................................... 5
Harm of Body Dissatisfaction ..................................................................................................... 5
Poor Nutrition ......................................................................................................................... 5
Unnecessary Restriction.......................................................................................................... 6
Eating Disorders...................................................................................................................... 6
Depression............................................................................................................................... 7
Economic Costs ...................................................................................................................... 7
Background ................................................................................................................................. 8
Prevalence ............................................................................................................................... 8
Women at Risk........................................................................................................................ 9
Body Distortion as a Measure of Body Dissatisfaction ........................................................ 10
Limitations of Current Literature .......................................................................................... 10
Rationale for Approach ............................................................................................................. 11
Questionnaire ........................................................................................................................ 11
Large, Representative Sample of Adolescents ...................................................................... 11
Long Time Span to Analyze Change Over Time.................................................................. 12
Specific Aims ............................................................................................................................ 12
Method .......................................................................................................................................... 14
Overview ................................................................................................................................... 14
Participants ............................................................................................................................ 14
YRBSS Data Sets .................................................................................................................. 14
YRBSS Sampling Methods....................................................................................................... 15
Sampling ............................................................................................................................... 15
Weighting .............................................................................................................................. 16
Response Rates ..................................................................................................................... 16
Data Collection ..................................................................................................................... 17
Data Processing ..................................................................................................................... 17
Study Variables ......................................................................................................................... 17
Demographic Variables ........................................................................................................ 17
Key Variables........................................................................................................................ 18
Derived Variables ................................................................................................................. 19
Weight control factors....................................................................................................... 19
Weight satisfaction............................................................................................................ 20
Design ....................................................................................................................................... 21
Data Preparation.................................................................................................................... 21
Data Analysis ........................................................................................................................ 21
Results ........................................................................................................................................... 23
Sample Description ................................................................................................................... 23
Models................................................................................................................................... 26
Change Over Time ................................................................................................................ 27
Hypothesis one: increase in body dissatisfaction over time. ............................................ 27
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Hypothesis two: decrease in healthy behaviors & increase in extreme behaviors over
time. .................................................................................................................................. 28
Gender and Ethnicity Differences ......................................................................................... 30
Hypothesis three: greater body dissatisfaction and weight control behaviors among
females. ............................................................................................................................. 30
Hypothesis four: greater body dissatisfaction and weight control behaviors among
Caucasians......................................................................................................................... 34
Relationship between Body Dissatisfaction and Weight Control Behavior ......................... 38
Hypothesis five: positive association between body dissatisfaction and weight control
behaviors. .......................................................................................................................... 38
Hypothesis six: greater prevalence of body dissatisfaction and weight control behaviors
among older adolescents. .................................................................................................. 39
Discussion ..................................................................................................................................... 44
Major Findings .......................................................................................................................... 44
Limitations ................................................................................................................................ 46
Implications............................................................................................................................... 47
Future Research ........................................................................................................................ 48
References ..................................................................................................................................... 50
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Abstract
Background: Dissatisfaction with the size, weight, and shape of one’s body contributes to the
risk of developing an eating disorder. Body dissatisfaction appears common among adolescents,
but there is little information available on changes in prevalence over time.
Purpose: We aim to study temporal changes in body dissatisfaction and eating disordered
behavior between 1999 and 2007 and their relationship in high school aged youth.
Methods: The National Youth Risk Behavior Survey (YRBS) data sets were downloaded from
the Centers for Disease Control and Prevention (CDC) for the years 1999, 2001, 2003, 2005, and
2007. A pooled data set of variables common across the years was created (n= 64,270).
Hypothesis: We hypothesize that the prevalence of body dissatisfaction and weight control
behaviors will increase over time. We predict prevalence differences based on gender, ethnicity,
and age. We also predict a correlation between body dissatisfaction and weight control
behaviors.
Data Analysis: The YRBS uses a multistage probability sampling design. We conducted
univariate descriptive analysis with SPSS using case weights and multivariate hierarchical
hypothesis testing with AM Statistical Software, which takes into account correlated errors
within sampling units and utilizes design weights.
Results: Consistency of body satisfaction and weight control behaviors was found over time.
White adolescents and females seem at high risk of body dissatisfaction and eating disorder
behavior. Body dissatisfaction and extreme weight control behaviors were positively related and
fairly stable across age.
Implications: Future research should study younger populations to improve understanding of
etiology and effectiveness of body dissatisfaction and eating pathology preventions.
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Temporal Trends in Body Dissatisfaction and Weight Controlling Behaviors
Spread and Internalization of the “Thin Ideal”
Body dissatisfaction—unhappiness with one’s size, shape, or weight—pervades Western
culture and appears to be spreading. Alongside the spread of body dissatisfaction, the “thin ideal”
of women has also developed. Internalization of the “thin ideal” occurs when an individual
adopts a cultural ideal of thinness and accepts it as his/her personal standard. Because culture has
such a great influence on body image (Dolan, Birtchnell, & Lacey, 1987), the cultural spread of
the “thin ideal” and its internalization present a threat to well-being (Austin & Smith, 2008). The
problem of body dissatisfaction is associated in the development of eating disorders (Stice &
Shaw, 2002), leading to death and economic burdens. Furthermore, “given the recent widespread
dissemination of this message in the media, it is unclear what the cumulative effect of this
message may be on psychological functioning and weight control practices” (Roehrig,
Thompson, & Cafri, 2008). Therefore, additional research is needed to grasp the scope of the
spread of the “thin ideal” and its impact on weight controlling behaviors.
Harm of Body Dissatisfaction
Poor Nutrition
One of the implications of the spread of the “thin ideal” may be body dissatisfaction,
which correlates with poor quality of food intake. Specifically among adolescents, an age group
that tends to lack appropriate knowledge of nutritional needs (Nelson, Lytle, & Pasch, 2009),
poor body image plays a strong role in poor nutrition. Among children dissatisfied with their
bodies, boys tended to cut out desserts, girls tended to eat less meats and carbohydrates (such as
French fries and potato chips), and neither ate more fruits and vegetables (Middleman, Vazquez,
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& Durant, 1998). In Middleman, Vazquez, and Durant’s study, “feeling too fat,” the main reason
cited for weight-loss attempts, tended to result in a restrictive eating style. Predominately seen in
females, this severely restrictive eating style fails to supply the nutrients, vitamins, and energy
necessary for optimal growth and development in adolescence (Wahl, 1999).
Unnecessary Restriction
Another unhealthy behavior associated with body dissatisfaction is unnecessary food
restriction. Female dieters are more likely to inaccurately estimate their weight, weigh more, and
perceive themselves as heavier than non-dieters, thereby contributing to more dieting (MossavarRahmani, Pelto, Ferris, & Allen, 1996). Furthermore, increased dieting behavior predicts the
development of both sub-threshold eating disorders and eating disorders. This finding led Stice
and Shaw to conclude that body dissatisfaction can lead to dieting, which can lead to eating
disorders (2002). For example, restrictive eating in which hunger cues are denied and meals are
skipped may lead to overeating, binge eating, and/or weight gain (Spear, 2006). Thus, body
dissatisfaction that results in restrictive eating has many potentially harmful effects.
Eating Disorders
The most severe complication of body dissatisfaction is arguably the development of
eating disorders, which can be fatal (Howlett, McClelland, & Crisp, 1995). Body dissatisfaction
was the greatest single predictor within the eating disorder inventory for the development of
partial syndrome eating disorder within a 4-year period among the high school females that
Stanford University of Medicine followed (Killen et al., 1996). This supports a link between
body dissatisfaction (and weight concerns in general) and later development of partial syndrome
eating disorder (a particularly strong link given that this study was prospective and done over 4
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years). Accordingly, body dissatisfaction, which is a precursor and risk factor for the
development of eating disorders, can lead to the severe health complications that are seen in
eating disorders. These include a range of health problems, such as osteopenia, osteoporosis,
impaired pregnancy and child rearing ability among women (Treasure & Szmukler, 1995), dental
deterioration, gastric or esophageal rupture (Rome & Ammerman, 2003), and even premature
death (Sullivan, 1995).
Depression
Depression, both clinical and sub-clinical, is another potential consequence of eating
disorders. The presence of eating disorder during adolescence predicts an increased risk for later
development of depression, but depression does not significantly predict later development of
eating disorders (Marmorstein, von Ranson, Iacono, & Malone, 2008). Unfortunately,
Marmorstein, von Ranson, Iacono, and Malone did not directly test the causal relationship
between eating disorder and development of depression. Also, a predominately Caucasian
sample may threaten the external validity of their study. However, the study’s epidemiological
nature and longitudinal data strengthen its conclusions, which converge with other research. For
example, Stice and Bearman also found that body dissatisfaction and eating disorders predict
later development of depressive symptoms, particularly in adolescent females (2001).
Economic Costs
Body dissatisfaction also places a substantial economic burden on those directly and
indirectly affected by it. In Germany in 1995, the economic cost of anorexia nervosa alone was
estimated to be 65,000,000 euros, and 10,000,000 euros for bulimia nervosa (Simon, Schmidt, &
Pilling, 2005). These estimates include health costs, such as inpatient treatment, clinical therapy,
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and doctor appointments. Insurance companies and welfare programs often contribute to the
costs associated with these disorders, affecting society at large. Most figures underestimate the
costs of body dissatisfaction that sometimes develops into disordered eating, thus the true cost of
body dissatisfaction to society is likely larger than most realize. Between poor nutrition,
unnecessary dietary restriction, and the development of mental disorders, the consequences of
body dissatisfaction can be severe on individuals that it directly affects, as well as a society that
carries the economic burden of associated disorders.
Background
Body dissatisfaction, the negative subjective evaluation of one’s body, is a substantial
health concern that faces the world today. While the spread and potential harm of body
dissatisfaction is well documented in the literature (Grogan, 1999), the onset and temporal trends
of body dissatisfaction are comparatively understudied. Accompanying the growth of body
dissatisfaction is the growth of obesity (Anderson, Eyler, Galuska, Brown, & Brownson, 2002)
(Flegal, Carroll, Kuczmarski, & Johnson, 1998), eating disorders (Keski-Rahkonen et al., 2007),
and related premature death due to chronic illness among the adult population (Agras, 2001).
Research into body dissatisfaction and its consequences among adolescents indicates that body
dissatisfaction is prevalent and problematic. However, more research among adolescent
populations is necessary to understand the onset, temporal trends, and strategies for the
prevention of body dissatisfaction.
Prevalence
The rising rates of eating disorders, of which body dissatisfaction is a precursor, among
adults further emphasizes the need for additional research in the area. In the United Kingdom the
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incidence rate of anorexia nervosa rose from 4.2 per 100,000 people in 1993 to 4.7 per 100,000
people in 2000 (Hoek, 2006). This incidence rate provides more information on the growth of
anorexia nervosa among the population than its prevalence rate and emphasizes the continued
growth and spread of eating disorders. However, because anorexia nervosa is chronic and
difficult to treat, incident rates may lead some to underestimate the prevalence of eating
disorders. Although anorexia nervosa is more fatal than bulimia nervosa, bulimia nervosa is
more prevalent. Estimates suggest that 13.5 per 100,000 adult females develop bulimia nervosa
every year (Hoek, 2006). These rates are commonly accepted as underestimates of the actual
prevalence of eating disorders, and therefore new research is necessary to gain a more accurate
picture of the prevalence of eating disorders and its related precursors (such as body
dissatisfaction). Furthermore, these estimations focus on adult populations and tend to overlook
the development of eating disorders among adolescents.
Women at Risk
Literature also suggests that women are at greater risk for body dissatisfaction, which
translates into increased risk for eating disorders (Fairburn & Harrison, 2003). Not only are
women more likely to dislike a particular body part, but also they are more likely to overestimate
perceived weight (an established predictor of anorexia nervosa) and be dissatisfied with their
current weight (Dolan et al., 1987). The implication that women are at a greater risk for body
dissatisfaction than their male counterparts is strong. Interestingly, Dolan et al. also attribute this
trend, and the withdrawal of 6 women from the study upon learning that their weight would be
measured, to society’s “thin ideal” of women (Dolan et al., 1987). Although the more in-depth
assessments used in the study improve the quality of its measurements, it also harms the quality
of the study. For instance, Dolan could only manage 100 participants in the study. Such a small
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sample size hinders the internal validity of the study, and therefore creates a need for larger
sample sizes that are more likely to accurately represent the population.
Body Distortion as a Measure of Body Dissatisfaction
While not perfect, body image “distortion” is a useful operational definition of body
dissatisfaction for studies on a larger scale. Research indicates that body image distortion among
people with eating disorders is not an issue of perceptual deficit, but likely a cognitive process
(Cash & Deagle, 1997). Perhaps so-called body distortion is intentional, or at least has some
utility for those who adopt it. (Overestimation of normal body weight may serve as a greater
motivator to lose unwanted weight than an accurate estimation, whereas underestimation of
overweight may reinforce a desire to avoid exertion often required to lose weight.) Although
some ambiguity remains around body image distortion and its mechanism in poor body image, it
can be a useful indicator of body dissatisfaction (Brug, Wammes, Kremers, Giskes, & Oenema,
2006). More research into the predictive validity of body image distortion for body
dissatisfaction may prove its utility in prevention studies among typical populations.
Limitations of Current Literature
While literature has provided insightful indicators of risk factors for body dissatisfaction
and eating disorders that can be aimed at prevention, current literature has failed to fully address
the needs to study adolescent populations, use large sample sizes, and analyze trends over time.
Research is heavily weighted on adult populations, rather than adolescent populations, in which
eating disorders develop and onset at higher rates (Diagnostic and Statistical Manual of Mental
Disorders, 2000). There is also a lack of recent research on large sample sizes, covering multiple
ethnicities and regions within the United States. However, the most palpable gap in the literature
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is a trend analysis of body dissatisfaction and related behaviors across multiple years. This study
aims to fill in these gaps.
Rationale for Approach
Questionnaire
This observational study utilized the questionnaire approach, because it provides insight
into the emotions, attitudes, and beliefs of a participant that form his/her body image, as well as
demographics associated with body dissatisfaction. A national survey of overweight and obese
women concluded that body dissatisfaction predicts weight loss efforts better than actual body
mass index (Anderson et al., 2002). Questionnaires, such as this one, allow for greater sampling
sizes and may also generate more discussion and leads for areas of research, but lack causal
conclusions. For instance, Anderson and colleagues were able to conclude that weight loss
efforts and body dissatisfaction are correlated, but a directionality problem remains: which one
promotes the development of the other? Despite a few drawbacks, the questionnaire approach is
effective for investigating body satisfaction (which is largely an internal construct), obtaining
large sample sizes to improve validity, and generating research leads.
Large, Representative Sample of Adolescents
The growing rates of body dissatisfaction, behaviors symptomatic of eating disorder,
and—predictably—eating disorders among adolescents are alarming. For example, 57% of
females and 31% of males in their senior year of high school reported eating disordered behavior
(such as binge eating or unhealthy efforts to lose weight like taking diet pills, intentionally
skipping meals, fasting, smoking cigarettes, and purging) in the 1998 Minnesota Student Survey
(Croll, Neumark-Sztainer, Story, & Ireland, 2002). These high rates of behavior, which are
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precursory to and evident of eating disorders among adolescents, suggest that body
dissatisfaction does not suddenly spring up in adulthood, but rather develops earlier. Therefore,
further research on the onset, trends, and causes of body dissatisfaction among young
adolescents needs to be performed. A limitation of the Minnesota study is that the sample was
limited to students in Minnesota. Thus, new research should use nationally representative
samples in order to improve external validity and large sample sizes to improve internal validity.
Long Time Span to Analyze Change Over Time
The rise in eating disorder behavior among adolescents is dangerous, harmful, and
requires society’s immediate attention (Forman-Hoffman, 2004). Forman-Hoffman
commendably used the Youth Risk Behavior Survey from 1999 for her data, making her sample
more representative of adolescents living in the United States and her conclusions more easy to
generalize to the United States healthcare and education systems than Croll, Neumark-Sztainer,
Story, and Ireland’s study (2002). However, the survey from 1999 now seems outdated. Thus a
more recent survey would be more relevant and useful for assessing the current condition of
body dissatisfaction and eating disorder behavior among adolescents. Additionally, analyzing
several surveys over time would provide insight into any trends and patterns in body
dissatisfaction and disordered eating, as well as minimize error due to extrapolation.
Specific Aims
This study aims to address how body dissatisfaction has changed in the past 10 years
among high school students in the United States and examine corresponding trends in weight
control efforts. Based on risk factors indicated in previous research, gender, ethnicity, and age,
differences were analyzed, as well as the relationship between body dissatisfaction and eating
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disorder behavior. Ultimately, this study tackles the theory that external situations influence
internalized cognitions and attitudes (such as body dissatisfaction), which predict behavior (such
as eating disorder behavior). Research hypotheses include:
1. Increased body dissatisfaction over time
2. Decrease in healthy behaviors (such as nutritional food intake and moderate exercise) and
increase in extreme weight control behaviors over time
3. Greater body dissatisfaction and weight control behaviors among females
4. Greater body dissatisfaction and weight control behaviors among Caucasians
5. Positive association between body dissatisfaction and weight control behaviors
6. Greater prevalence of body dissatisfaction and weight control behaviors among older
adolescents
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Method
Overview
Participants
The population of interest was all high school students in the United States. Participants,
ranging from ages 12 to 18 and of various ethnicities, were randomly selected for sampling.
YRBSS Data Sets
This study used preexisting data from the national Youth Risk Behavior Surveillance
System (YRBSS), which the Center for Disease Control and Prevention (CDC) developed to
assess the occurrences of health risk behaviors among high school students on an ongoing basis.
Data was collected from high school students across the United States based on student
responses to a questionnaire. The 1999 YRBS was the result of an extensive update of previous
versions of the YRBS in which 11 questions were deleted and 16 questions added (to ensure that
behaviors most closely related to mortality risk, and for which effective interventions have been
established, were included). Of particular importance to the study of body dissatisfaction were
the additions of self-reported weight and height to the questionnaire in 1999. Thus, this study
analyzed data from the 1999 YRBS to the most recent 2007 YRBS. The questionnaire was given
to test sites in the form of a booklet, which computers scanned to determine student responses
and ensure consistency. The national survey contained multiple-choice questions in 6 categories
of health behavior with 5-8 additional questions pertaining to health (that do not fall into one of
the 6 categories). An example question follows:
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Which of the following are you trying to do about your weight?
A. Lose weight
B. Gain weight
C. Stay the same weight
D. I am not trying to do anything about my weight.
Overall, the YRBSS has been found to be reliable. However, a version of the
questionnaire from 1999 had ten questions with questionable test-retest reliability (Brener et al.,
2002). Nevertheless, YRBS self-report responses, particularly among high school-age
adolescents, are considered valid (Brener, Billy, & Grady, 2003). For example, after completing
the YRBSS twice in two weeks, 2,965 students were weighed and measured to determine the
validity of self-reported weight and height. Although the CDC study found that the self-reports
were very reliable, it also found that students tended to underreport their weight by 3.5 pounds
and over-report their height by 2.7 inches (Brener, McManus, A., Lowry, & Wechsler, 2003).
While not perfect, it appears that the YRBSS is a fairly reliable and valid tool for measuring
health risks and behaviors associated with body dissatisfaction and disorder eating.
YRBSS Sampling Methods
Sampling
The YRBSS employed three-stage cluster sampling. First, sixteen strata were formed
from the 50 states and the District of Colombia based on metropolitan statistical area and
minority populations to ensure representative samples. Then the primary sampling units, which
are about the size of a large county, were randomly selected from these strata. The second stage
of sampling selected private and public schools of varying sizes. To ensure similar sample sizes,
individual classrooms were selected for the third stage of sampling.
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Weighting
Individual cases were weighted based on sex, ethnicity, and grade to ensure that the
sample was representative of students in 9th through 12th grade in the United States. For instance,
because black and Hispanic students were over-sampled to ensure accurate assessment of a
smaller subset of the population, weighting corrected for this over-sampling. This was done
through an iterative process in which extreme sampling weights were trimmed, resulting in an
overall sample that was representative of the population of high school students in the United
States on the basis of sex, ethnicity, and grade (Potter, 1990). In addition to over-sampling,
weighting also helped to correct for non-response.
Response Rates
The YRBSS sampled without replacement, which prevented non-measurable bias due to
non-response from entering the sample. As can be seen in Table 1, student response rates were
higher than school response rates over all five years studied. The mean school response rate was
78%, whereas the mean student response rate was 84%. Therefore, the mean overall response
rate was 66%. Ultimately, non-response might have introduced some bias into the data.
Table 1
Response Rates
Year
Response Rate
School
Student
Overall
1999
77%
86%
66%
2001
75%
83%
63%
2003
81%
83%
67%
2005
78%
86%
67%
2007
81%
84%
68%
Mean
78%
84%
66%
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Data Collection
Participant welfare and consistency were stressed throughout data collection. Parental
permission for data collection was obtained for each participating student according to local
guidelines. Therefore, according to local guidelines, permission from participants’ parents was
established either actively (prior to participation) or passively (after participation). Students
voluntarily participated in completing the survey during a class period. Using cover sheets for
responses on answer sheets or standard booklets and sealing recorded responses after
questionnaire completion ensured student privacy. To ensure consistency in the process of data
collection, trained data collectors visited students’ schools to explain the study using a
standardized script and distribute the questionnaires.
Data Processing
After data was collected, the ORC Macro (a research and information technology firm)
and the CDC processed the data. ORC Macro scanned the raw data and then sent it to the CDC to
be compiled it into one data set. The CDC used SAS and Visual Basic to run quality control on
the data (looking for missing responses, logical inconsistency between responses, and responses
that are out-of range). Questionnaires with less than twenty acceptable responses after logical
editing were removed from the data set. The CDC then returned the cleaned data set to the ORC
Macro for weighting.
Study Variables
Demographic Variables
A list of each demographic variable and how they were operationalized follows.
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
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BMI: Students were asked how tall they are and how much they weigh without their
shoes on. From these responses, body mass index in kilograms per square meter (kg/M2)
was calculated using SPSS.

Age: Students were asked whether they were 12 or younger, 13, 14, 15, 16, 17, or 18 or
older.

Grade: Students were asked their current grade and provided the options: 9th, 10th, 11th,
12th, or other or ungraded.

Gender: Students were asked to indicate whether they were male or female.

Ethnicity: Students reported their ethnicity from these options: Indian/ Alaska Native,
Asian, Black or African American, Hispanic, Latino, native Hawaiian or Pacific Islander,
White, or Multiple- Hispanic, or Multiple-Non-Hispanic. Based on the distribution of the
results, the data were condensed into 4 categories: non-Hispanic white, non-Hispanic
black, Hispanic, and multiple or other.
Key Variables
Main study variables varied from the year of data collection to self-description of weight
and weight control variables. A list of each key variable and how they were operationalized
follow.

Year: The year variable describes the year the data was collected for the national survey,
which takes place every other year.

Describe Weight: Students were asked how they describe their weight and given the
options: very underweight, slightly underweight, about right, slightly overweight, or very
overweight.
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
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Exercise: Exercising to control weight is operationalized as a positive response to
exercising within the past thirty days to lose or maintain current weight.

Diet: A positive response to eating less food, lower calorie food, or food low in fat in the
past thirty days in order to lose or maintain current weight was considered dieting.

Fast: Fasting was operationalized as a positive response to not eating for 24 hours or
longer within the past thirty days in order to lose or prevent gaining weight.

Diet Pills: A positive response to taking diet pills, powders, or liquids without a doctor’s
approval in order to lose weight or prevent weight gain within the past thirty days was
categorized as taking diet pills.

Purge: Purging was operationalized as a positive response to vomiting or taking laxatives
to lose or maintain current weight within the past thirty days.
Derived Variables
Weight control factors.
Due to the large amount of behavior variables, they were reduced to a smaller set of
scores. A factor analysis of these variables was performed using principal components with
varimax rotation. The result was three factors, which are presented in Table 2. Factor one
represents healthy food intake consisting of fruit, potatoes, carrots, and other veggies. Factor two
represents vomiting/ laxative use, diet pill use, and fasting and is named extreme weight control
behaviors. Finally, the third factor, weight loss strategies, consisted of exercising and dieting to
lose weight. Factor scores were computed for all cases on each of the three factors. These factor
scores are uncorrelated and represent three independent dimensions of eating behavior.
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Table 2
Eating Behavior Factor Scores
Variable
Other vegetables 4-6 times a week
Carrots 4-6 times a week
Fruits 4-6 times week
Potatoes 4-6 times a week
Vomit/laxative use for weight control
Diet pills for weight control
Fasting for weight control
Exercise for weight control
Diet for weight control
Factors
Healthy
Extreme Weight
Food
Control Behaviors
0.686
-0.661
-0.638
-0.586
--0.759
-0.711
-0.681
-----
Weight Loss
Strategies
-------0.844
0.785
Weight satisfaction.
A new variable, Weight Satisfaction Index (WSI), was used as an indication of body
dissatisfaction. Before constructing the WSI value, the self-reported body mass index
(kilograms/ meters squared) variable was standardized based on age and gender (ZBMI). WSI
was constructed to represent the deviation of actual ZBMI from the average of one of five groups
based on self-rating of weight. Thus, in order to obtain the WSI variable 0.32 was added to the
ZBMI of people who rated themselves as very underweight and 0.49 was added to the ZBMI of
people who rated themselves as slightly underweight. People who described themselves as just
about right in terms of weight had 0.25 subtracted from their ZBMI. The ZBMI of those who
placed themselves in the slightly overweight category decreased by 1.18, whereas it decreased by
1.78 for those falling into the very overweight self-description category to obtain WSI. Thus, a
low number means that an individual is thinner than the average person with the same body
weight self-rating. In this construction of body satisfaction, a low number indicates
dissatisfaction with body weight. A high number indicates a person heavier than the average
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person who gave a particular body weight rating, and thus has relative body satisfaction. Such
manipulations were done to compare weight perception while taking into account ZBMI, and
thus better measure body satisfaction.
Design
We obtained the YRBSS data for this correlational observation study. The study design is
repeated cross-sections of American high school students in years 1999, 2001, 2003, 2005, and
2007. Self-report data in the form of survey responses from different students was used to
analyze the relationships between demographics, attitudes, and self-reported behaviors related to
body dissatisfaction and weight control behaviors.
Data Preparation
The cleaned data sets were downloaded from the CDC website and analyzed to determine
consistent variables over the years of interest. The years to be studied were selected based on the
data they provided in relation to the research questions. The five selected datasets were merged
into one large dataset and checked again for errors. Coding of variables, such as labeling
unnamed variables in the data sets for years 2001 and 2003, simplified data analysis.
Furthermore, recoding of any divergent variables made the variables of interest consistent across
the years. For instance, the Hispanic and Latino categories in the year 2007 data for the ethnicity
variable were merged into one category to better coincide with earlier data.
Data Analysis
Finally the data was analyzed. SPSS, a computer program, was used to perform
descriptive statistics on sample characteristics (demographic variables) and key variables to
assess participant attitudes and behavior by year. All SPSS analyses used the case weights.
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Secondly, multivariate hypothesis testing was performed with AM Statistical Software on
variables that measure body dissatisfaction and weight control behaviors. Use of AM Statistical
Software yielded accurate estimates of variability rather than underestimates of variability due to
created correlated errors within clustered sampling units (Bell-Ellison & Kromrey, 2007). Such
statistical programs that yield accurate estimates of variability and incorporate sample weights
lead to appropriate analysis using complex data from sample surveys. Each hypothesis was
examined with hierarchical regression analysis. For instance, to analyze change in body
satisfaction over time, linear regressions were done first with ethnicity, gender, and grade
variables to control for demographic variables and then the year variable was added to the
equation to test the first hypotheses via the change in R-squared. Beta weights were also
analyzed to determine whether the relationship was positive or negative.
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Results
Sample Description
The demographics were relatively comparable across the sampled data. The distribution
of the demographic variables (see Table 3) was similar to the distribution of the key variables
(see Table 4). The year 1999 has the most data, but all years have a relatively similar and
sufficient amount of data to address the research questions. Body mass index remained fairly
constant across the years with a very slight increase, so it should not have confounded the data.
While the collected data concentrated on students from ages 15 to 17, it was fairly evenly
distributed across 9th through 12th grade. The trends also remained constant across the 8 years.
Additionally, the sampling of males and females remained at a roughly 1:1 ratio across all 8
years, so gender should not have confounded the results either.
However, a larger amount of people identifying themselves as other or mixed ethnicity
(15.6%) was sampled in 1999 compared to the other years. If ethnicity has a strong influence on
body dissatisfaction and eating disorder related behavior, then this might have confounded
results based on trends over time. However, weighting likely reduced potential confounding.
Furthermore, heavy sampling from minority populations enabled the answering of questions
related to ethnicity, and was therefore desirable. Ultimately, the size and distribution of the data
appears to be robust enough to address the research questions.
Table 3 presents the frequency and percent of collected data for each studied year
according to demographic variables. The mean and standard deviation were given for the body
mass index and WSI variables, because they are continuous variables.
Body Satisfaction
24
Table 3
Frequency & Percent of Collected Data for Demographic Variables by Year
1999
Variable
BMI
WSI
2001
Year
2003
2005
2007
Age
<12
13
14
15
16
17
> 17
Total
M
23.02
-0.078
Freq.
1
10
1347
3532
4027
3452
2062
14431
SD
4.69
0.8169
%
0.0%
1.0%
9.3%
24.5%
27.9%
23.9%
14.3%
M
22.85
-0.102
Freq.
2
11
1388
3186
3203
2948
1789
12527
SD
4.54
0.8168
%
0.0%
0.1%
11.1%
25.4%
25.6%
23.5%
14.3%
M
23.19
-0.016
Freq.
5
6
1501
3371
3468
3130
1710
13191
SD
4.56
0.7994
%
0.0%
0.0%
11.4%
25.6%
26.3%
23.7%
13.0%
M
23.43
-0.002
Freq.
3
13
1324
3433
3399
3071
1792
13035
SD
4.79
0.7919
%
0.0%
0.1%
10.2%
26.3%
26.1%
23.6%
13.7%
M
23.42
0.016
Freq.
7
8
1405
3290
3316
3047
1743
12816
SD
4.76
0.7932
%
0.1%
0.1%
11.0%
25.7%
25.9%
23.8%
13.6%
Grade
9th
10th
11th
12th
Other
Total
4023
3743
3446
3167
7
14386
28.0%
26.0%
24.0%
22.0%
0.0%
3732
3144
2855
2756
7
12494
29.9%
25.2%
22.9%
22.1%
0.1%
3729
3508
3113
2810
6
13166
28.3%
26.6%
23.6%
21.3%
0.0%
3694
3411
3052
2855
8
13020
28.4%
26.2%
23.4%
21.9%
0.1%
3609
3359
3032
2792
3
12795
28.2%
26.3%
23.7%
21.8%
0.0%
7383
7048
51.2%
48.8%
6094
6433
48.6%
51.4%
6801
6389
51.6%
48.4%
6595
6440
50.6%
49.4%
6507
6309
50.8%
49.2%
8765
1969
1440
2257
14431
60.7%
13.6%
10.0%
15.6%
8550
1526
1449
1002
12527
68.3%
12.2%
11.6%
8.0%
8078
1833
2215
1064
13190
61.2%
13.9%
16.8%
8.1%
8109
1841
1888
1197
13035
62.2%
14.1%
14.5%
9.2%
7776
1869
2070
1101
12816
60.7%
14.6%
16.2%
8.6%
Gender
Male
Female
Total
Ethnicity
White
Black
Hispanic
Other
Total
Table 4 displays the key variables and the frequency and percent of the data for each
year. As can be seen in Table 4, while 1999 has slightly more data than the following years, all
the years have enough data points to find significant differences between the years. The rate of
self-descriptions of underweight appears to slightly decrease over the years. Although some of
the percentages of weight control behaviors are relatively small, the amount of data is still high
enough to make meaningful conclusions. For instance, only 4.4% of the students reported
purging in 2007, but the data frequency of 607 is substantive enough to address research
Body Satisfaction
25
questions. Overall the data are fairly consistent and well distributed over the 8 years, despite a
few trends over the years in the data. Ultimately, there is enough data for all variables across all
8 years to warrant their study.
Body Satisfaction
26
2005
2007
Table 4
Frequency & Percent of Collected Data for Key Variables by Year
1999
Variable
Describe
Weight
Freq.
Very
Under
Slightly
Under
About
Right
Slightly
Over
Very
Over
Total
Year
2003
2001
%
Freq.
%
Freq.
%
Freq.
%
Freq.
%
398
2.6%
343
2.6%
379
2.6%
278
2.0%
272
2.0%
2136
14.0%
1771
13.2%
1967
13.3%
1661
12.1%
1599
11.6%
8201
53.7%
7302
25.8%
8059
54.6%
7498
54.5%
7769
56.3%
3866
25.3%
3464
25.8%
3714
25.2%
3688
26.8%
3542
25.7%
657
15258
4.3%
566
13446
4.2%
629
14748
4.3%
630
13755
4.6%
612
13794
4.4%
Present
Absent
Total
8640
6554
15194
56.9%
43.1%
7776
5650
13426
57.9%
42.1%
8415
6511
14926
56.4%
43.6%
8254
5473
13727
60.1%
39.9%
8288
5431
13719
60.4%
39.6%
Present
Absent
Total
5904
9263
15167
38.9%
61.1%
5548
7768
13316
41.7%
58.3%
5945
8799
14744
40.3%
59.7%
5538
8179
13717
40.4%
59.6%
5455
8279
13734
39.7%
60.3%
Present
Absent
Total
1850
13368
15218
12.2%
87.8%
1750
11567
13317
13.1%
86.9%
1898
12856
14754
12.9%
87.1%
1659
11638
13297
12.5%
87.5%
1597
11636
13233
12.1%
87.9%
Present
Absent
Total
1071
14127
15198
7.0%
93.0%
1215
12236
13451
9.0%
91.0%
1246
13576
14822
8.4%
91.6%
862
12877
13739
6.3%
93.7%
793
12542
13335
5.9%
94.1%
Present
Absent
Total
714
14474
15188
4.7%
95.3%
714
12699
13413
5.3%
94.7%
857
13940
14797
5.8%
94.2%
639
13053
13692
4.7%
95.3%
607
13128
13735
4.4%
95.6%
Exercise
Diet
Fast
Pills
Purge
Models
Hierarchical linear regression and beta weights were used to test the six hypotheses. The
first table for each hypothesis test displays the hierarchical regression analysis (with the variables
added to the regression equation in the first column and the subsample size (n) in the next). The
coefficient of alienation is “k,” and “F” tests for the significance of the hypothesis that R2 change
Body Satisfaction
27
is equal to 0. (The program only provides R2 to 3 decimal places.) For each hypothesis test, two
analyses were done. First, a regression was done using the control variables. Then the variable
critical to the hypothesis test was added. From the two R2 values, we computed R2 change and
used Excel to calculate the significance of R2 change.
Change Over Time
Hypothesis one: increase in body dissatisfaction over time.
Tables 5 and 6 show results for the hypothesis that body dissatisfaction will increase over
time. As can be seen in Table 5, when race, grade, gender, and ZBMI were controlled, the year
added no contribution to the regression equation for WSI. The R2 change value was 0.00000.
Table 5
Weight Satisfaction Index Over Time
Model
Race, grade, gender
ZBMI
Year
n
R2
k
64,000
64,000
64,000
5
7
8
R2 change
0.083
0.674
0.674
F
-0.59100
0.00000
p
-56110.80267
0.00000
-0.0000
1.0000
Table 6 shows a slight increase in WSI over time (p<0.006). Hypothesis one is not
supported since there was a small, but significant, improvement in body satisfaction over time.
Table 6
Weight Satisfaction Index Over Time
Parameter Name
Constant
White
Black
Hispanic
Sex
Grade
ZBMI
Year
MSE
Estimate
SE
-0.669
0.015
0.172
0.030
0.254
-0.019
0.626
0.003
0.211
t
0.016
0.011
0.012
0.013
0.006
0.003
0.004
0.001
--
p > |t|
-42.643
1.386
13.926
2.349
40.716
-7.643
172.078
2.756
--
0.000
0.167
0.000
0.020
0.000
0.000
0.000
0.006
--
Body Satisfaction
28
Hypothesis two: decrease in healthy behaviors & increase in extreme behaviors over
time.
Results of the hypothesis that healthy food consumption would decrease over time are
displayed in Tables 7 and 8. This hypothesis failed to be confirmed with an R2 change of 0.00000
when year was added to the regression equation (see Table 7).
Table 7
Healthy Food Consumption Over Time
Model
Ethnicity, gender, grade
ZBMI
Year
n
R2
k
64,000
64,000
64,000
4
5
7
R2 change
0.013
0.013
0.013
-0.00000
0.00000
F
p
-0.00000
0.00000
-1.0000
1.0000
Table 8 indicates a slight decrease in consumption of healthy food over time (p>0.014) in
accordance with the hypothesis. However, the small R2 change value shows that support for this
hypothesis is weak.
Table 8
Healthy Food Consumption Over Time
Parameter Name
Constant
Black
Hispanic
Other Ethnicity
Grade
Gender
ZBMI
Year
MSE
Estimate
SE
-0.031
-0.259
-0.091
0.069
-0.016
0.115
0.005
-0.009
0.991
t
0.028
0.018
0.021
0.026
0.006
0.013
0.006
0.004
--
p > |t|
-1.116
-14.679
-4.402
2.631
-2.846
9.129
0.857
-2.469
--
0.266
0.000
0.000
0.009
0.005
0.000
0.393
0.014
--
Tables 9 and 10 show results for extreme weight control variables. R2 was significant, but
small, 0.1% of the variance.
Body Satisfaction
29
Table 9
Extreme Weight Control Behaviors Over Time
Model
Ethnicity, gender, grade
ZBMI
Year
n
k
64,000
64,000
64,000
R2
4
0.033
5
0.042
6
0.043
R2 change
F
-0.00900
0.00100
p
-13712.78571
1488.18605
-0.0000
0.0000
As can be seen in Table 10, there was a slight decrease in extreme weight control
behaviors from 1999 to 2007, which disconfirms predictions (p>0.005).
Table 10
Extreme Weight Control Behaviors Over Time
Parameter Name
Constant
Black
Hispanic
Other Ethnicity
Grade
Gender
ZBMI
Year
MSE
Estimate
SE
0.470
-0.034
0.037
0.028
0.021
-0.383
0.098
-0.010
0.975
t
0.032
0.017
0.020
0.028
0.005
0.014
0.006
0.004
--
14.725
-2.064
1.856
1.024
3.868
-27.849
15.619
-2.837
--
p > |t|
0.000
0.040
0.065
0.307
0.000
0.000
0.000
0.005
--
Tables 11 and 12 display results for the hypothesis that moderate weight loss strategies
will decrease over time. Disconfirming the hypothesis, Table 11 shows that the year variable
contributed nothing (R2=0.00000) to the regression equation.
Table 11
Exercise & Diet Over Time
Model
Ethnicity, gender, grade
ZBMI
Year
n
k
64,000
64,000
64,000
R2
4
0.068
5
0.164
6
0.164
R2 change
-0.09600
0.00000
F
p
-37459.31707
0.00000
-0.0000
1.0000
Table 12 shows no significant decrease in exercise and diet behavior over time (p>0.761).
This fails to confirm the second hypothesis that healthy weight control behaviors would decrease
Body Satisfaction
30
over time. Ultimately, there is little support for the second hypothesis. Weight control variables
were fairly stable over time.
Table 12
Exercise & Diet Over Time
Parameter Name
Constant
Black
Hispanic
Other Ethnicity
Grade
Gender
ZBMI
Year
MSE
Estimate
SE
0.830
-0.383
-0.077
-0.051
-0.015
-0.546
0.317
-0.001
0.845
t
p > |t|
0.031
0.018
0.017
0.025
0.006
0.014
0.006
0.003
--
27.191
-21.105
-4.517
-2.033
-2.419
-39.002
56.072
-0.305
--
0.000
0.000
0.000
0.043
0.016
0.000
0.000
0.761
--
Gender and Ethnicity Differences
Hypothesis three: greater body dissatisfaction and weight control behaviors among
females.
Tables 13 and 14 show results of the prediction that females will have higher rates of
body dissatisfaction than males. As seen in Table 13, gender aided in predicting WSI
(R2=0.02400), in accordance with expected results.
Table 13
WSI by Gender
Model
Ethnicity, grade
ZBMI
Year
Gender
n
R2
k
64,000
64,000
64,000
64,000
4
5
7
8
R2 change
0.028
0.649
0.650
0.674
-0.62100
0.00100
0.02400
F
p
-61232.13097
98.44769
2278.57567
-0.0000
0.0000
0.0000
As predicted, Table 14 indicates greater weight satisfaction among males than females
(p>0.006).
Body Satisfaction
31
Table 14
WSI by Gender
Parameter Name
Constant
Black
Hispanic
Other Ethnicity
Grade
ZBMI
Year
Gender
MSE
Estimate
SE
-0.654
0.157
0.015
-0.015
-0.019
0.626
0.003
0.254
0.211
t
p > |t|
0.013
0.008
0.013
0.011
0.003
0.004
0.001
0.006
--
-50.435
19.994
1.174
-1.386
-7.643
172.078
2.756
40.716
--
0.000
0.000
0.242
0.167
0.000
0.000
0.006
0.000
--
Tables 15 and 16 show results of the hypothesis that females will more frequently
consume healthy foods than males. Gender slightly contributed (R2 change=0.013) to the
regression equation (Table 15).
Table 15
Healthy Food Intake by Gender
Model
Ethnicity, grade
ZBMI
Year
Gender
n
R2
k
64,000
64,000
64,000
64,000
4
5
7
8
R2 change
0.009
0.009
0.010
0.013
-0.00000
0.00100
0.00300
F
p
-0.00000
6399.10000
14766.92308
-1.0000
0.0000
0.0000
In contrast to predictions, Table 16 shows that males more frequently consumed healthy
foods on a weekly basis than females (p>0.000). These results disconfirm the hypothesis that
females more frequently engage in weight control behaviors than males.
Body Satisfaction
32
Table 16
Healthy Food Intake by Gender
Parameter Name
Constant
Black
Hispanic
Other Ethnicity
Grade
ZBMI
Year
Gender
MSE
Estimate
SE
-0.031
-0.259
-0.091
0.069
-0.016
0.005
-0.009
0.115
0.991
t
p > |t|
0.028
0.018
0.021
0.026
0.006
0.006
0.004
0.013
--
-1.116
-14.679
-4.402
2.631
-2.846
0.857
-2.469
9.129
--
0.266
0.000
0.000
0.009
0.005
0.393
0.014
0.000
--
In Tables 17 and 18 the findings of the hypothesis that extreme weight control behaviors
will be more common among females. Table 17 shows that gender contributed to the regression
equation (R2 change=0.03600) while controlling for ethnicity, grade, and ZBMI. This supports
the third hypothesis.
Table 17
Extreme Weight Control Behaviors by Gender
Model
Ethnicity, grade
ZBMI
Year
Gender
n
R2
k
64,000
64,000
64,000
64,000
4
5
7
8
R2 change
0.001
0.007
0.007
0.043
-0.00600
0.00000
0.03600
F
p
-54851.14286
0.00000
53573.02326
-0.0000
1.0000
0.0000
Table 18 confirms expected greater frequency of extreme weight control behaviors
among females compared to males (p>0.000).
Body Satisfaction
33
Table 18
Extreme Weight Control Behaviors by Gender
Parameter Name
Constant
Black
Hispanic
Other Ethnicity
Grade
ZBMI
Year
Gender
MSE
Estimate
SE
0.470
-0.034
0.037
0.028
0.021
0.098
-0.010
-0.383
0.975
t
p > |t|
0.032
0.017
0.020
0.028
0.005
0.006
0.004
0.014
--
14.725
-2.064
1.856
1.024
3.868
15.619
-2.837
-27.849
--
0.000
0.040
0.065
0.307
0.000
0.000
0.005
0.000
--
Tables 19 and 20 show results for diet and exercise by gender. As expected, Table 19
indicates that gender contributed significantly to the regression equation for predicting diet and
exercise, accounting for 7.3% of the variance.
Table 19
Diet & Exercise by Gender
Model
Ethnicity, grade
ZBMI
Year
Gender
n
R2
k
64,000
64,000
64,000
64,000
4
5
7
8
R2 change
0.010
0.091
0.091
0.164
-0.08100
0.00000
0.07300
F
p
-56960.80220
0.00000
28483.35366
-0.0000
1.0000
0.0000
As seen in Table 20, females also reported higher frequency of diet and exercise than
males (p>0.000). This confirms the third hypothesis that greater rates of body dissatisfaction and
weight control behaviors will be present among females than males.
Body Satisfaction
34
Table 20
Diet & Exercise by Gender
Parameter Name
Constant
Black
Hispanic
Other Ethnicity
Grade
ZBMI
Year
Gender
MSE
Estimate
SE
0.830
-0.383
-0.077
-0.051
-0.015
0.317
-0.001
-0.546
0.845
t
p > |t|
0.031
0.018
0.017
0.025
0.006
0.006
0.003
0.014
--
27.191
-21.105
-4.517
-2.033
-2.419
56.072
-0.305
-39.002
--
0.000
0.000
0.000
0.043
0.016
0.000
0.761
0.000
--
Hypothesis four: greater body dissatisfaction and weight control behaviors among
Caucasians.
Tables 21 and 22 show results of the hypothesis that WSI will be greatest among
Caucasians. With R2 change=0.00400, ethnicity adds to the predictive value of the regression
equation in accordance with the hypothesis (as can be seen in Table 21).
Table 21
WSI by Ethnicity
Model
Gender, grade
ZBMI
Year
Ethnicity
n
R2
k
64,000
64,000
64,000
64,000
4
5
7
8
R2 change
0.060
0.670
0.670
0.674
0.61000
0.00000
0.00400
F
p
58262.28358
0.00000
379.7626113
0.0000
1.0000
0.0000
Table 22 shows that students identifying themselves as black tend to have greater body
satisfaction than those identifying themselves as white (p>0.000). This confirms the hypothesis.
However, when white students were compared to Hispanic students and those of other
ethnicities, no significant results were found to confirm the hypothesis that higher body
dissatisfaction would be present among white students.
Body Satisfaction
35
Table 22
WSI by Ethnicity
Parameter Name
Constant
Gender
Grade
ZBMI
Year
Black
Hispanic
Other Ethnicity
MSE
Estimate
SE
-0.654
0.254
-0.019
0.626
0.003
0.157
0.015
-0.015
0.211
t
p > |t|
0.013
0.006
0.003
0.004
0.001
0.008
0.013
0.011
--
-50.435
40.716
-7.643
172.078
2.756
19.994
1.174
-1.386
--
0.000
0.000
0.000
0.000
0.006
0.000
0.242
0.167
--
Tables 23 and 24 show healthy food intake by ethnicity. Ethnicity slightly added to the
regression equation for healthy food intake with R2 change=0.00800 (Table 23), which supports
the hypothesis that healthy food intake will be greater among Caucasians than other ethnicities.
Table 23
Healthy Food Intake by Ethnicity
Model
Gender, grade
ZBMI
Year
Ethnicity
n
R2
k
64,000
64,000
64,000
64,000
4
5
7
8
R2 change
0.004
0.004
0.005
0.013
-0.00000
0.00100
0.00800
F
p
-0.00000
12798.20000
39378.46154
-1.0000
0.0000
0.0000
Table 24 shows that compared to white students, black and Hispanic students were less
likely to eat healthy food in support of the hypothesis (p>0.000). In contrast to the hypothesis,
students of other ethnicities were more likely to eat healthy food (p>0.009). Thus, support for the
hypothesis is weak at best.
Body Satisfaction
36
Table 24
Healthy Food Intake by Ethnicity
Parameter Name
Constant
Gender
Grade
ZBMI
Year
Black
Hispanic
Other Ethnicity
MSE
Estimate
SE
-0.031
0.115
-0.016
0.005
-0.009
-0.259
-0.091
0.069
0.991
t
p > |t|
0.028
0.013
0.006
0.006
0.004
0.018
0.021
0.026
--
-1.116
9.129
-2.846
0.857
-2.469
-14.679
-4.402
2.631
--
0.266
0.000
0.005
0.393
0.014
0.000
0.000
0.009
--
Tables 25 and 26 display results of the hypothesis that extreme weight control behaviors
are most prevalent among Caucasians. Disconfirming the hypothesis, Table 25 shows that
ethnicity added no significant contribution to predicting extreme weight control behaviors (R2
change=0.00000).
Table 25
Extreme Weight Control Behavior by Ethnicity
Model
Gender, grade
ZBMI
Year
Ethnicity
n
R2
k
64,000
64,000
64,000
64,000
4
5
7
8
R2 change
0.033
0.042
0.043
0.043
-0.00900
0.00100
0.00000
F
p
-13712.78571
1488.16279
0.00000
-0.0000
0.0000
1.0000
However, white students were more likely to engage in extreme weight control behaviors
(p>0.040), as seen in Table 26. This offers very weak support for the fourth hypothesis.
Additionally, results for other minorities were not statistically significant.
Body Satisfaction
37
Table 26
Extreme Weight Control Behavior by Ethnicity
Parameter Name
Constant
Gender
Grade
ZBMI
Year
Black
Hispanic
Other Ethnicity
MSE
Estimate
SE
0.470
-0.383
0.021
0.098
-0.010
-0.034
0.037
0.028
0.975
t
p > |t|
0.032
0.014
0.005
0.006
0.004
0.017
0.020
0.028
--
14.725
-27.849
3.868
15.619
-2.837
-2.064
1.856
1.024
--
0.000
0.000
0.000
0.000
0.005
0.040
0.065
0.307
--
Tables 27 and 28 show results for moderate weight control behaviors by gender. As seen
in Table 27, the R2 change for ethnicity was 0.01600. This supports the hypothesis that
Caucasians are more likely to engage in weight control behaviors than other ethnicities.
Table 27
Diet & Exercise by Ethnicity
Model
Gender, grade
ZBMI
Year
Ethnicity
n
R2
k
64,000
64,000
64,000
64,000
4
5
7
8
R2 change
0.058
0.148
0.148
0.164
-0.09000
0.00000
0.01600
F
p
-38914.66216
0.00000
6242.926829
-0.0000
1.0000
0.0000
Table 28 indicates that white students were more likely to diet and exercise than black
students (p>0.000), Hispanic students (p>0.000), and students of other ethnicities (p>0.043).
This confirms the hypothesis that diet and exercise behaviors are greatest among white students.
Body Satisfaction
38
Table 28
Diet & Exercise by Ethnicity
Parameter Name
Constant
Gender
Grade
ZBMI
Year
Black
Hispanic
Other Ethnicity
MSE
Estimate
SE
t
0.830
-0.546
-0.015
0.317
-0.001
-0.383
-0.077
-0.051
0.845
p > |t|
0.031
0.014
0.006
0.006
0.003
0.018
0.017
0.025
--
27.191
-39.002
-2.419
56.072
-0.305
-21.105
-4.517
-2.033
--
0.000
0.000
0.016
0.000
0.761
0.000
0.000
0.043
--
Relationship between Body Dissatisfaction and Weight Control Behavior
Hypothesis five: positive association between body dissatisfaction and weight control
behaviors.
Tables 29 and 30 show the relationship between WSI and weight control behaviors.
Given that R2 change=0.0000 with the addition of the year variable to the regression equation, as
seen in Table 29, it appears that the relationship between WSI and weight control behaviors was
stable over time. Table 29 also indicates the presence of a relationship between WSI and weight
control behaviors (R2 change=0.01700). This supports the hypothesis that as body dissatisfaction
increases weight control behaviors will also increase.
Table 29
Relationship between WSI & Weight Control Behaviors
Model
Ethnicity, gender, grade
ZBMI
Year
Weight Control
n
R2
k
64,000
64,000
64,000
64,000
5
7
8
13
0.083
0.674
0.674
0.6910
R2 change
-0.59100
0.00000
0.01700
F
p
-56110.80267
0.00000
1574.16064
-0.0000
1.0000
0.0000
Body Satisfaction
39
As seen in Table 30, there is a positive association between WSI and healthy food intake
in contrast to prediction (p>0.026). Table 30 also shows a negative association between extreme
weight control behaviors and diet and exercise as expected (p>0.000).
Table 30
Relationship between WSI & Weight Control Behaviors
Parameter Name
Constant
Black
Hispanic
Other Ethnicity
Gender
Grade
ZBMI
Year
Healthy Food Intake
Extreme Weight Control
Diet & Exercise
MSE
Estimate
SE
t
-0.550
0.014
0.124
0.008
0.001
0.009
-0.019
0.011
0.181
0.007
-0.020
0.003
0.660
0.004
0.003
0.001
0.007
0.003
-0.054
0.005
-0.096
0.004
0.199
--
-40.284
15.401
0.162
-1.733
26.209
-7.831
161.120
2.379
2.240
-11.893
-23.683
--
p > |t|
0.000
0.000
0.871
0.084
0.000
0.000
0.000
0.018
0.026
0.000
0.000
--
Hypothesis six: greater prevalence of body dissatisfaction and weight control behaviors
among older adolescents.
Tables 31 and 32 show results for the hypothesis that body dissatisfaction will be greater
among older adolescents than younger adolescents. As seen in Table 31, age accounted slightly
for WSI (R2 change=0.00100), which confirms the hypothesis.
Table 31
WSI by Age
Model
Ethnicity, gender
ZBMI
Year
Age
n
R2
k
64,000
64,000
64,000
64,000
4
6
7
8
R2 change
0.078
0.673
0.674
0.675
-0.59500
0.00100
0.00100
F
p
-56575.39376
94.94214
94.80000
-0.0000
0.0000
0.0000
When the beta weights displayed in Table 32 are taken into account, a negative
association between WSI and age seems apparent (p>0.000). Given the small R2 change value,
Body Satisfaction
this offers little support to the hypothesis that weight dissatisfaction is greater among older
adolescents.
Table 32
WSI by Age
Parameter Name
Constant
Black
Hispanic
Other Ethnicity
Gender
ZBMI
Year
Age
MSE
Estimate
SE
-0.587
0.158
0.015
-0.016
0.257
0.626
0.003
-0.023
0.211
t
p > |t|
0.016
0.008
0.013
0.011
0.006
0.004
0.001
0.002
--
-36.847
20.241
1.181
-1.461
41.561
171.562
2.570
-10.148
--
0.000
0.000
0.239
0.145
0.000
0.000
0.011
0.000
--
Tables 33 and 34 show results of the hypothesis that healthy food intake increases with
age. In contrast to prediction, Table 33 shows that age did not contribute to the regression
equation for healthy food intake (R2 change=0.00000).
Table 33
Healthy Food Intake by Age
Model
Ethnicity, gender
ZBMI
Year
Age
n
R2
k
64,000
64,000
64,000
64,000
4
6
7
8
R2 change
0.012
0.012
0.013
0.013
-0.00000
0.00100
0.00000
F
p
-0.00000
4922.384615
0.00000
-1.0000
0.0000
1.0000
Table 34 shows no statistically significant relationship between age and healthy food
intake (p>0.81). This fails to support the hypothesis.
40
Body Satisfaction
41
Table 34
Healthy Food Intake by Age
Parameter Name
Constant
Black
Hispanic
Other Ethnicity
Gender
ZBMI
Year
Age
MSE
Estimate
SE
-0.025
-0.258
-0.089
0.070
0.116
0.006
-0.009
-0.009
0.991
t
p > |t|
0.036
0.018
0.021
0.026
0.013
0.006
0.004
0.005
--
-0.704
-14.641
-4.286
2.696
9.154
0.877
-2.430
-1.755
--
0.482
0
0
0.008
0.000
0.381
0.016
0.081
--
Tables 35 and 36 show extreme weight control variables by age. Table 35 indicates a
slight contribution (R2 change=0.00200) of age to predicting extreme weight control behaviors,
which supports the sixth hypothesis.
Table 35
Extreme Weight Control Behaviors by Age
Model
Ethnicity, gender
ZBMI
Year
Age
n
R2
k
64,000
64,000
64,000
64,000
4
6
7
8
R2 change
0.033
0.042
0.042
0.044
-0.00900
0.00000
0.00200
F
p
-13712.5714
0.00000
2908.63636
-0.0000
1.0000
0.0000
Table 36 shows that as age increased, the frequency of students using extreme weight
control behaviors increased (p>0.0000). This confirms the hypothesis that extreme weight
control behaviors will increase with age.
Body Satisfaction
Table 36
Extreme Weight Control Behaviors by Age
Parameter Name
Constant
Black
Hispanic
Other Ethnicity
Gender
ZBMI
Year
Age
MSE
Estimate
SE
0.350
-0.035
0.039
0.029
-0.387
0.099
-0.010
0.035
0.974
t
p > |t|
0.040
0.017
0.020
0.027
0.014
0.006
0.004
0.005
--
8.661
-2.134
1.955
1.049
-28.271
16.033
-2.777
6.682
--
0.000
0.034
0.052
0.295
0.000
0.000
0.006
0.000
--
Tables 37 and 38 show results of the hypothesis that rates of diet and exercise are
positively associated with age. As seen in Table 37, age did not significantly contribute to
predicting diet and exercise (R2 change =0.00000). This disconfirms the hypothesis.
Table 37
Diet & Exercise by Age
Model
Ethnicity, gender
ZBMI
Year
Age
n
R2
k
64,000
64,000
64,000
64,000
4
6
7
8
R2 change
0.066
0.164
0.164
0.164
-0.09800
0.00000
0.00000
F
p
-38239.12195
0.000
0.000
-0.0000
1.0000
0.0000
Disconfirming the hypothesis, Table 38 shows that younger adolescents appear to diet
and exercise slightly more than older adolescents (p>0.001).
42
Body Satisfaction
Table 38
Effect of Age on Diet & Exercise
Parameter Name
Constant
Black
Hispanic
Other Ethnicity
Gender
ZBMI
Year
Age
MSE
Estimate
SE
0.881
-0.381
-0.076
-0.050
-0.544
0.316
-0.001
-0.018
0.845
t
0.037
0.018
0.017
0.024
0.014
0.006
0.003
0.005
--
p > |t|
23.926
-21.052
-4.496
-2.050
-39.010
55.849
-0.338
-3.320
--
0.000
0.000
0.000
0.042
0.000
0.000
0.736
0.001
--
43
Body Satisfaction
44
Discussion
Major Findings
Table 39 offers an overview of the results from each hypothesis. After the hypothesis is
stated in the second column, the level to which significant results confirm or disconfirm the
hypothesis is presented to the right. Finally, a brief conclusion is shown that corresponds to each
hypothesis.
Table 39
Overview of Majors Findings
Number
1
Hypothesis
Increase in BD over time
Degree of Support
Slight increase in WSI over time
2
Decrease in healthy
behaviors and increase in
unhealthy behaviors over
time
3
Greater BD and WCB
among females
4
Greater BD and WCB
among Caucasians
5
Positive association
between BD and WCB
6
Greater BD and WCB
among older adolescents
Slight decrease in healthy food intake
over time, slight decrease in extreme
WCB over time, and no significant
decrease in moderate weight loss
strategies over time
Greater BD, extreme WCB, and weight
loss strategies among females, but
greater healthy food intake among
males
Slightly greater BD among white
students than black students, very weak
support for white students engaging in
extreme WCB more than black
students, and slightly greater incidence
of diet and exercise among white
students
Slight negative relationship between
BD and healthy food intake contrasts
with positive relationship between BD
extreme WCB, diet, and exercise
Slightly greater BD and extreme WCB
among older adolescents offers little
support, which contrasts with very
slightly greater diet and exercise among
younger adolescents
Conclusion
BD appears fairly stable from
1999 to 2007
WCB appear fairly stable from
1999 to 2007
Presence of BD and behaviors
explicitly targeted at weight loss
are more common among
females
BD and WCB may be slightly
greater among white students
when compared to black
students
BD appears to be positively
associated with behaviors
explicitly targeted at weight loss
BD and WCB appear to be
present at roughly similar rates
among high school students of
all ages
Note. BD = body dissatisfaction; WCB = weight control behaviors.
Over time there was a slight decrease in healthy food intake as predicted, however in
contrast to predictions there was a slight increase in WSI and a slight decrease in extreme weight
control behaviors over time. Effect sizes were extremely small (with time accounting for no
Body Satisfaction
45
more than 0.1% of the variance of all the regression equations). Thus, body satisfaction and
weight control behaviors appear fairly stable from 1999 to 2007. This converges with Cash,
Morrow, Hrabosky, and Perry’s findings (2004) that body satisfaction improved among nonblack
and black females in the mid-nineties and male body dissatisfaction was fairly stable from 1983
to 2001, as well as Rozin, Trachtenberg, & Cohen’s study (2001).
In confirmation of hypothesis three, males tended to have a higher WSI than females who
more frequently engaged in extreme weight control behaviors, diet, and exercise than males.
These results are in accord with Dolan and colleagues' study (1987) and a study that found
greater body dissatisfaction and weight loss measures among high school females (Paxton, S. J.,
et al., 1991). More males consumed healthy food than females in contrast to expectations, but
consistent with another study (Neumark-Sztainer, D., et al., 2006). However, this result may
reflect greater caloric intake among males (Rolls, Fedoroff, & Guthrie, 1991), rather than a
higher ratio of healthy to unhealthy food intake.
Black students appeared more satisfied with their body weight than white students, who
more frequently engaged in weight control behaviors than black students as predicted. Such
findings are consistent with previous literature that suggests greater prevalence of dieting (White,
Kohlmaier, Varnado-Sullivan, & Williamson, 2003) and disordered eating behavior (StreigelMoore, et al., 2000) among white females than black females. These body satisfaction
differences might also be interpreted as a reflection of black females’ apparent greater flexibility
in construction of body image ideals (Parker, Nichter, Nichter, Vuckovic, Sims, &
Ritenbaugh,1995), which may allow for greater accommodation of overweight bodies more
common among black females (Yun et al., 2006).
Body Satisfaction
46
Disconfirming the hypothesis that WSI is positively associated with weight control
behaviors, a positive association between body satisfaction and healthy food consumption was
found. However, a negative association between WSI and extreme weight control behaviors,
diet, and exercise confirmed this hypothesis. Given these results, it seems probable that healthy
food consumption (as indexed in this study) may not be usefully conceptualized as a weight
control behavior. Perhaps black students’ tendency to eat less healthy food than white students is
a result of socioeconomic disparities (Drewnowski, 2004), which are reflected in higher rates of
adiposity (Shrewsbury & Wardle, 2008), rather than relatively greater body satisfaction. If this is
the case, then this study’s results may be interpreted as consistent with findings of positive
association between body dissatisfaction and weight control efforts (Stice & Shaw, 2002),
(Killen et al., 1996).
Finally, as expected, older adolescents were barely more likely to have a lower WSI and
engage in extreme weight control behaviors. This converges with findings of consistent body
image across grade (Talamayan, Springer, Kelder, Gorospe, & Joye, 2006), life span
(Tiggemann, 2004), and age (Stevens & Tiggemann, 1988), as well as higher prevalence of selfreported disordered eating behaviors among older adolescent females (Jones, Bennett, Olmsted,
Lawson, & Rodin, 2001). Yet, in contrast to the hypothesis that older adolescents would have
higher rates of body dissatisfaction and weight control behaviors, younger adolescents dieted and
exercised more than older adolescents.
Limitations
There are several limitations to this study. One of the biggest limitations is that it is solely
based on collected survey data. This results in construction of ZBMI from adolescents’ selfreports, which have been shown to overestimate height and underestimate weight (Brener,
Body Satisfaction
47
McManus, Lowry, & Wechsler, 2003). Second, the unconventional variable used to measure
body satisfaction, WSI, has not been used or substantiated in other studies. The WSI variable
also fails to take into account participants, such as prepubescent males, who may weigh less than
their desired weight and experience body dissatisfaction due to perception of being underweight.
This limits the confidence of conclusions in regard to body dissatisfaction that can be drawn
from this study. Additionally, interaction effects were not included. Therefore, we might have
missed an interaction between gender and ethnicity. Last, no “causal claims” can be made from
the results of this study, as it lacks any experimental manipulation.
Implications
Most of the literature on trends in body dissatisfaction seem to indicate its growth over
time, as indicated by a meta-analysis of 222 studies (Feingold & Mazzella, 1998). However,
results from this study suggest relative constancy in body satisfaction, as well as weight control
behaviors, among adolescents in more recent years. Perhaps body satisfaction, and accordingly
weight control behaviors, has stabilized in recent years. While this might be taken as an
indication of improvement in combating body dissatisfaction and eating pathology, their
apparent firmness and staying power ought to also be stressed. Renewed effort to reduce body
dissatisfaction and disordered eating is necessary.
This study shows the prevalence of body dissatisfaction across ethnically and regionally
diverse adolescents in the United States, providing a better understanding a representative
sample of United States high school students. It also confirms previous findings that females and
white people are at high risk for body dissatisfaction and extreme weight control behaviors.
Additionally, greater prevalence of body dissatisfaction than extreme weight control
behaviors among adolescents and the positive association between body dissatisfaction and
Body Satisfaction
48
extreme weight control behaviors appear to be consistent with the conceptualization of body
dissatisfaction as a potential precursor to eating pathology. Therefore, findings from this study
might lend some support to a pathway model of the development of eating disorders in which
body dissatisfaction is key (Stice & Shaw 2002).
Finally, body dissatisfaction and weight control behaviors appear to present at roughly
similar rates across high school students of different ages. This consistency may suggest that
body dissatisfaction generally develops prior to the time that adolescents reach high school.
Therefore, preventive interventions will likely be most effective when they are done before
people reach adolescence.
Future Research
This study allows for several areas of improvement in future research. First, physical
measurement of participant height and weight, rather than reliance on self-report, may reduce
self-report error and improve the accuracy of body mass index. Measuring body dissatisfaction in
multiple ways, such as the difference between actual weight and ideal weight, the degree of
manipulation to transform an image of perceived body shape to an image of ideal body shape,
and explicit report of satisfaction, would provide more compelling results. Experimental designs
that manipulate body satisfaction may allow for causal claims about the relationship between
body dissatisfaction and eating disorder behavior.
Based on these findings, more research among populations at the age of onset of body
dissatisfaction and disordered eating behaviors seems necessary. For instance, future research
into body dissatisfaction in childhood may lead to greater understanding of the etiology of body
dissatisfaction (Davison, Markey, & Birch, 2003). Ultimately, more quality research into the
Body Satisfaction
49
mechanisms that may lead to disordered eating behavior, such as body dissatisfaction, will likely
improve our understanding and ability to prevent eating pathology and weight problems.
Body Satisfaction
50
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