author: westlie, mariah j. title: the correlation between ... · between family income and obesity...
TRANSCRIPT
1
Author: Westlie, Mariah J. Title: The Correlation between Childhood Obesity and Socioeconomic Status
The accompanying research report is submitted to the University of Wisconsin-Stout, Graduate
School in partial completion of the requirements for the
Graduate Degree/Major: MS Food and Nutritional Sciences
Research Adviser: Ann Parsons, Ph.D.
Submission Term/Year: Summer 2012
Number of Pages: 54
Style Manual Used: American Psychological Association, 6th edition
X I understand that this research report must be officially approved by the Graduate
School and that an electronic copy of the approved version will be made available
through the University Library website
X I attest that the research report is my original work (that any copyrightable
materials have been used with the permission of the original authors), and as such, it
is automatically protected by the laws, rules, and regulations of the U.S. Copyright
Office.
X My research adviser has approved the content and quality of this paper.
Student:
Westlie, Mariah J. 8/22/2012
Adviser:
Ann Parsons, Ph.D. 8/22/2012
This section to be completed by the Graduate School
This final research report has been approved by the Graduate School.
Director, Office of Graduate Studies:
2
Westlie, Mariah J. The Correlation between Childhood Obesity and Socioeconomic Status
Abstract
As a state dedicated to the health of its children and adolescents, the South Dakota
Department of Health 2020 Plan contains an objective of childhood obesity being equal to or less
than 14% (Biskeborn, Buhler, Cushing, Gildemaster, & Christensen, 2012). However, according to a
recent National Health and Nutrition Examination Survey (NHANES), 31.9% of U.S. children
between the ages of 2 and 19 are overweight or obese (Williamson et al., 2009). The objective of
this study was to determine if any relationship existed between childhood obesity and a low
socioeconomic status. Anthropometric measurements of school-aged children as well as National
School Lunch Program enrollment data were obtained from the South Dakota Department of Health
in the spring of 2012. A variety of statistical analyses were performed. From the correlational
analysis, a moderate positive relationship was found (r= +.385, p<.05, Pearson Correlation) between
childhood weight status and enrollment in the national school lunch program. Results indicated that
childhood obesity is a problem in both genders and many different ethnicities in the state of South
Dakota. From these results we conclude that a low socioeconomic status may influence the weight
of a child. This is most likely due to many internal and external factors.
3
The Graduate School University of Wisconsin Stout
Menomonie, WI
Acknowledgments
I would like to thank my thesis adviser, Dr. Ann Parsons, for dedicating her valuable time
and expertise to the completion of my thesis project; I would not have been able to complete
this project without all of her patience, encouragement, and guidance. I would also like to
thank my food and nutrition professors for giving me a great education and experience
throughout my graduate school career, and lastly, I would like to thank all my close family and
friends for the unlimited support and assistance that I obtained from them in the years of my
ongoing education.
4
Table of Contents
Chapter I: Introduction ................................................................................................................... 8
Statement of the Problem .................................................................................................. 8
Purpose of the Study......................................................................................................... 11
Research Objectives .......................................................................................................... 11
Definition of Terms ........................................................................................................... 11
Assumptions and Limitations ............................................................................................ 12
Chapter II: Literature Review ........................................................................................................ 13
Definition of Childhood Obesity ....................................................................................... 13
Occurrence ........................................................................................................................ 14
Risk Factors ....................................................................................................................... 15
Health Detriment .............................................................................................................. 18
Chapter III: Methodology .............................................................................................................. 19
Introduction ...................................................................................................................... 19
Data from the South Dakota Department of Health ........................................................ 19
Data from the National School Lunch Program ................................................................ 20
Data Analysis ..................................................................................................................... 21
Limitations......................................................................................................................... 22
Chapter IV: Results ........................................................................................................................ 25
Introduction ...................................................................................................................... 25
Demographic Data ............................................................................................................ 25
Gender Data ...................................................................................................................... 27
5
Age Data ............................................................................................................................ 28
Regional Data .................................................................................................................... 29
National School Lunch Program Data ............................................................................... 29
Chapter V: Results and Discussions .............................................................................................. 32
Conclusions ....................................................................................................................... 32
Discussion.......................................................................................................................... 34
Recommendations ............................................................................................................ 35
References .................................................................................................................................... 37
Appendix A: Directions for Completing Height and Weights Data Sheet ..................................... 39
Appendix B: Participating Schools ................................................................................................ 43
Appendix C: Schools Participating in Height and Weight Survey, 2010-2011 .............................. 52
Appendix D: South Dakota Education Service Agencies Region Map .......................................... 52
Appendix E: BMI-for-Age Growth Charts ...................................................................................... 53
6
List of Figures
Figure 1: South Dakota School Demographics .............................................................................. 25
Figure 2: Average BMI Differences among Race .......................................................................... 26
Figure 3: Overweight and Obese Body Mass Index for Age ......................................................... 29
Figure 4: Correlational Analysis of Percent Eligible for Free and Reduced Priced Meals Vs.
Occurrence of Overweight & Obesity by Region .......................................................................... 31
7
List of Tables
Table 1: Classification of Weight Status Based on Percentile Ranking ......................................... 22
Table 2: Overweight & Obese Body Mass Index by Race ............................................................. 27
Table 3: Weight Status by Gender ................................................................................................ 28
Table 4: Overweight & Obese Body Mass Index for Age .............................................................. 29
Table 5: Overweight & Obese Body Mass Index by Region .......................................................... 30
Table 6: Percent Eligible for Free & Reduced Price Meals, by Region .......................................... 30
8
Chapter I: Introduction
Statement of the Problem
Childhood obesity is a significant health problem that has been growing exponentially in
the United States in recent years, and current studies have concluded that there is a strong
correlation between childhood obesity and low socioeconomic status. As a state dedicated to
the health of its public including children and adolescents, the South Dakota Department of
Health 2020 objective of childhood obesity should be about equal to or less than 14%. In 2010
the percentage of obesity in children was 15.2% (Biskeborn, Buhler, Cushing, Gildemaster, &
Christensen, 2012). According to a recent National Health and Nutrition Examination Survey
(NHANES), 31.9% of U.S. children between the ages of 2 and 19 are overweight or obese, and
often children who are overweight or obese at a young age will reach adulthood at an
unhealthy weight (Williamson, Champagne, Han, Harsha, Corby, Newton, 2009). This epidemic
is not only affecting the United States but other developed countries as well including the
Middle East, Central Europe, and Eastern Europe. For example, Saudi Arabia and Iran are
among the top seven countries with the highest prevalence of childhood obesity with 16% of
their population of adolescent girls having BMI rankings in the 85th-95th percentile, a number
comparable to the 16.8% of adolescent girls in the United States (Pourhassan & Najafabadi,
2009). Globally, since 2010 the number of overweight children (under the age of five) has
grown to an estimated 43 million, while 35 million of these children live in developed countries
(World Health Organization, 2011). With this trend continuing in recent years, it is likely that
obesity in children will continue to grow exponentially.
9
Childhood obesity is considered a serious medical condition that occurs when a child is
above the normal body mass index for his/her weight and age (Mayo Clinic Staff, 2012a).
Childhood obesity is not only detrimental to the child’s health but it can also lead to abnormal
growth and maturation. If a child is overweight or obese, they are at a significant risk of
developing more serious health conditions including type 2 diabetes, heart disease,
hypertension, and even musculoskeletal disorders (Babey, Hastert, Wolstein, & Diamant, 2010).
A low socioeconomic status within families may correlate with childhood obesity. According to
the American Journal of Public Health, “Cross-sectional data have shown an inverse relationship
between family income and obesity prevalence among children and adolescents, although
some studies suggest that relationship differs according to race/ethnicity and gender” (Babey et
al., 2010, p.2507). This contributing factor of a low income can have a negative effect on both
the child’s diet and nutrition knowledge which can lead to overweight and obesity at an early
age. Family and school life both play a major role; if children are raised in poverty, they are less
likely to have access to healthy food, less likely to have the knowledge of good nutrition, have
an increasingly sedentary lifestyle, and also have less influence from their parents on healthy,
home-cooked meals.
Even in the last few years while rates of childhood obesity has increased, the magnitude
of income disparity in the U.S. population continued to rise as well. In 2001, the prevalence of
obesity was 70% higher in adolescents whose family incomes were below the federal poverty
line than those whose incomes were 300% above the poverty level (Babey et al., 2010). Poverty
is an especially important factor to consider when dealing with childhood obesity because there
are many risk factors that are associated with poverty that can have a strong negative influence
10
on a child’s well-being and health. Risk factors that stem from poverty and a low socioeconomic
status include (but are not limited to) instability, poor housing quality, family turmoil,
inadequate meal times, nutritionally low and calorie dense foods, lack of education, poor sleep
habits, and sedentary activity (Wells et al., 2010). However, the extent and time to which a
child remains at poverty level may influence their weight and health not only as a child but also
into adulthood.
Low socioeconomic status and poverty are not only risk factors for childhood obesity
but for adult obesity as well. In recent findings, it has been found that children who grew up
overweight or obese at a low socioeconomic status are more likely to create bad nutrition
habits and lack proper nutrition knowledge when they are older, which in turn exacerbates
their health problems and makes potentially life threatening and chronic conditions. In order to
demonstrate the claim that childhood socioeconomic status influences adulthood health and
BMI, a recent study published data supporting this theory. According to the American Journal of
Public Health, as childhood socioeconomic status decreased the body mass index as well as
waist-to-hip ratio increased significantly at age 26 years in both men and women. The article
continued further by stating 80% of women who grew up within a low socioeconomic
household were overweight or obese at adulthood compared to that of 40% from a higher
childhood socioeconomic status (Wells, Evans, Beavis, & Ong, 2010).
The health and well-being of a child is strongly influenced by the socioeconomic status
to which they were raised in, and in order to intervene on this growing epidemic, these
problems need to be addressed. Although a low socioeconomic status may prove to be a
disadvantage, parents/guardians should still be able to have access to the proper tools,
11
resources, and knowledge in their community for their children to be raised in a healthy home
environment. It is always important when intervening on childhood obesity to make sure that
intervention strategies are always culturally appropriate as well as appropriate for the current
socioeconomic conditions of the target population (Pourhassan & Najafabadi, 2009).
Purpose of the Study
The purpose of this study was to determine whether or not poverty is correlated to
childhood obesity and BMI index of children located within the state of South Dakota. Data was
obtained from the South Dakota Department of Health during the spring of 2012; this data was
then correlated with participation in the National School Lunch Program from the school year
2010/2011.
Research Objectives
This study will attempt to determine if a correlation exists between:
Childhood obesity and low socioeconomic status.
This study will attempt to determine if there is a change:
In the occurrence of overweight and obese children in South Dakota between the years
2010 and 2011.
Definition of Terms
The following terms are defined in order to receive a clear understanding of this study.
Body Mass Index: Abbreviated as BMI, body mass index is defined as a measure of
body weight relative to height. The ratio of the weight of the body in kilograms to the
square of height in meters (BMI = (weight in kg)/ [height (m)]2) (Centers for Disease Control
and Prevention, 2011b)
12
Healthy weight: For children, a healthy weight is a weight that is between the 5th and
85th percentile for the correct age and gender. (Centers for Disease Control and Prevention,
2011b 11).
High Risk Group: Comprises children and adolescents with a body mass index above the
85th percentile based on corresponding age and gender (Viewegg, Johnston, Lanier,
Fernandez, & Pandurangi, 2007). Thus, for children, those who are classified as overweight
or obese are in the high risk group.
Obese: In children, obesity is defined as a BMI that is equal to or greater than the 95th
percentile for age and gender (Centers for Disease Control and Prevention, 2011b).
Overweight: In children, overweight is defined as a BMI that is between the 85th and
95th percentile for age and gender (Centers for Disease Control and Prevention, 2011b).
Socioeconomic Status: Is defined and conceptualized as social standing or class of an
individual or group, this is measured as a combination of education, income, and occupation
(APA, 2011).
Assumptions and Limitations
In this study, it is assumed that anthropometric collecting techniques that were used for
measuring the children were made both with reliability and validity.
There are a few potential limitations to this study. Limitations of this study include the
variety sample population of this study. The population of South Dakota is unique due to the
fact that there are more Native Americans present in the population than many other states;
thus generalizing this data to all states across the United States could result in a skewed
perception of data.
13
Chapter II: Literature Review
The following chapter will begin with a synopsis of childhood obesity including
definition, risk factors, occurrences, and health detriments. It will further continue to overview
the occurrences of childhood obesity from those with poor socioeconomic status, and why this
might occur.
Definition
Obesity in adults is defined as a body mass index (BMI) of 30 or higher. BMI in adults is
often used as the determining factor when it comes to a set weight versus height ratio because
it correlates to a person’s total amount of body fat (Centers for Disease Control and Prevention,
2012). However, in children, BMI is age and gender specific, and is commonly referred to as
“BMI-for-age”. For children, BMI is plotted upon the CDC BMI-for-age growth chart (according
to gender) in order to obtain a percentile ranking, this percentile indicates the child’s BMI
relative to children of the same gender and age(Appendix E) (Centers for Disease Control and
Prevention, 2011b). Currently, “BMI-for-age” remains as the most common measure to use in
assessing a child’s weight status because it is inexpensive and non-invasive when compared to
other body fat measures (Centers for Disease Control and Prevention, 2011b). The rankings for
weight status are as follows: underweight is below the 5th percentile, healthy weight is
between the 5th and 85th percentile, overweight is between 85th and 95th percentile, and
obesity is equal to or greater than the 95th percentile (Centers for Disease Control and
Prevention, 2011b). If a child is in the overweight or obese category (higher than the 85th
percentile), medical professionals define them as “high risk” (Vieweg et al., 2007).
14
Occurrence
Childhood obesity has become one of the fastest growing epidemics in many developed
countries, and a recent estimate has found that around 17.6% of children in the United States
are obese, and that 70% of obese children will grow into obese adults (Pourhassan &
Najafabadi, 2009). The prevalence of obesity in children in developed countries has continued
to rise steadily since 1971 (with variability in some countries), and the highest prevalence of
childhood obesity remains in regions of the world such as North America, the Middle East,
Central Europe, and Eastern Europe (Pourhassan & Najafabadi, 2009). In the United states,
results from the National Health and Nutrition Examination Survey (NHANES) showed that
among pre-school age children (aged 2-5) rates of obesity more than doubled from 5% to 10.4%
between 1976-1980 and 2007-2008 (Centers for Disease Control and Prevention 2011a). These
rates of obesity also increased from 6.5% to 19.6% in 6-11 year olds, and 5% to 18.1% in 12-19
year olds, during the same time period (Centers for Disease Control and Prevention 2011a).
These staggering statistics are still continuing to grow and it has many medical professionals
fearing the worst for our future generations. Adolescents who are obese, or who are at high
risk for becoming obese are more likely to become obese as adults. According to the Center of
Disease Control, “…approximately 80% of children who were overweight at aged 10–15 years
were obese adults at age 25 years...and if overweight begins before 8 years of age, obesity in
adulthood is likely to be more severe” (Centers for Disease Control and Prevention 2011a, p.1).
The National Health Examination Survey (NHES) and the National Health and Nutrition
Examination Survey (NHANES) support this claim on childhood obesity because it is apparent
from the data in past and recent surveys that the obesity has nearly tripled in the past 50 years
15
(Centers for Disease Control and Prevention, 2012). In a past NHANES surveys from 2003-2004
and 2005-2006, there showed no significant changes on the prevalence of obesity in children
and adolescents; however, the current NHANES reports from 2010-2011 show that nearly
18.7% of children aged from 6-19 years old were obese a significant increase from 2003. Lastly,
the most current the data from the NHANES reports shows that 19.6% of children aged 6-11,
and 18.1% of individuals 12-19 years old were considered obese (Biskeborn, et al., 2012). Obese
children are at a much greater risk than their normal weight counterparts for many health
problems during their youth and adulthood if the weight problem is never resolved.
Risk Factors
Risk factors for childhood obesity are often varied and can be attributed to many
different internal and external factors in the child’s life. One of the major risk factors that make
a child susceptible to becoming overweight or obese is diet. A diet high in fat, high in refined
carbohydrates, and low in fruits, vegetables, and fiber can work in combination with other risk
factors to increase the vulnerability of becoming overweight or obese (Mayo Clinic Staff,
2012d). Several other risk factors include lack of exercise, family history and environment,
psychological state, and socioeconomics (Mayo Clinic Staff, 2012d).
The United States has rapidly become a more technologically diverse nation, and with
new technology often times exercise and physical activity is forgotten by the wayside. In recent
years, children have experienced a significant decrease in their physical activity and exercise,
while sedentary behaviors including TV watching and computer gaming have increased (Bellows
& Roach, 2010). Children between the ages of 8 and 18 are averaging 3 hours per day involved
with technology-related sedentary activities including television, video games, DVDS, and
16
movies (Bellows & Roach, 2010). Thus, extracurricular activities such as sports and outside play
time are becoming minimal in many children’s lives. The Colorado State University Extension
further explains the negative impact of technology-related sedentary activities on the increased
occurrence of childhood obesity,
Several studies have found a positive association between time spent watching
television and prevalence of overweight in children. Sedentary behavior, and specifically
television viewing, may replace time children spend in physical activities, contribute to
increased calorie consumption through excessive snacking and eating meals in front of
the television, influence children to choose high-calorie, low-nutrient foods through
exposure to food advertisements, and decrease children’s metabolic rate (Bellows &
Roach, 2010, p.1).
Family life also has a large impact on a child’s health and weight status because
overweight or obese children often come from an overweight or obese household (Mayo Clinic
Staff, 2012d). It is more likely when children have this background that they be more
susceptible to gain excess weight due to an environment with calorie dense foods and low
physical activity (Mayo Clinic Staff, 2012d). Children are not always capable of procuring and
making their own meals, and if the parents/guardians are supplying the household with calorie
dense foods, then that is what the child will eat. Behaviors such as these in family households
can contribute to weight gain in children as well as the entire family (Mayo Clinic Staff, 2012d).
Another major risk factor involved in a child’s weight is psychological state, some
children, like adults, will use food as a cure to their problems; other children may eat because
17
of boredom, stress, or high running emotions. Often, these behaviors are similar in the child’s
parents or guardians (Mayo Clinic Staff, 2012d).
Finally, and the focus of this thesis, is that socioeconomic status contributes to a child’s
weight. Low socioeconomic status, in itself may influence a variety of factors than can
contribute to an overweight child. Data published in the Southern Medical Journal elaborates
on these potential factors that may affect the occurrence of overweight and obese with
socioeconomic status, factors including:
…health insurance; neighborhood and personal safety; local schools and their resources;
local food stores and the extent to which they carry health foods; the price of food;
private and public transportation; proclivity to watch television and participate in other
sedentary activities; subsidized local, state, and federal programs; and access to gyms
and health clubs. (Vieweg et al., 2007, p.11).
In this same study, over a 7 year period, BMI percentile in children (with a beginning average
age of 8.8 years) increased significantly due to socioeconomic status. As an entire group, the
overweight prevalence increased from 31% to 40%, but when analyzing the status of children
with low socioeconomic status, overweight prevalence jumped from 37% to 67%, which
suggests a strong correlation between weight status and socioeconomic status (Vieweg et al.,
2007). The CDC also stated, “One of 7 low-income, preschool-aged children is obese… the
prevalence of obesity in low-income two to four year-olds increased from 12.4% in 1998 to
14.5% in 2003” (CDC, 2011a, p.1). Socioeconomic status along with other serious risk factors
can be major determinants to whether or not a child may become overweight or obese at a
young age.
18
Health Detriment
Obese and overweight children are starting to experience health consequences at an
earlier age than those in any other decade, and have to deal with conditions, that until now
were only affecting adults. Childhood obesity is a condition that can have severe consequences
on a child both physically and mentally. Physically, obese children are at an increased risk for
many diseases including cardiovascular disease, which encompasses high cholesterol levels,
high blood pressure, and abnormal glucose intolerance (Centers for Disease Control and
Prevention, 2011b). In a random, population-based sample of 5-17 year old children, 70% of
obese children were suffering from at least one cardiovascular disease symptom, while 39% of
obese children suffered from 2 or more (Centers for Disease Control and Prevention, 2011b).
Other health risks that may occur as a result from childhood obesity include: asthma, fatty liver,
sleep apnea, and type 2 diabetes mellitus (Centers for Disease Control and Prevention, 2011b).
Health complications that stem from childhood obesity are often associated with a shorter life
span and can greatly affect the outcome of a child’s life (Choudary, Donnelly, Racadio, & Strife,
2007).
In order to increase life expectancy of children and improve their quality of life and
health conditions, it is of increasing importance to slow and prevent the epidemic of childhood
obesity that arise from potential risk factors such as socioeconomic status. Overweight and
obese children not only will have a poor quality of life at a younger age, but will also experience
these ailments and diseases into prolonged life.
19
Chapter III: Methodology
Introduction
Data in this thesis was collected previously; the following chapter includes an overview
of the methods and data collection techniques that were used by the South Dakota Department
of Health completed in the school year 2010/2011. Before data analysis was started, approval
was necessary from the UW-Stout Institutional Review Board (IRB). The chapter will also include
methods of data analysis, correlational tests of significance that were performed, and finally
the limitations to the study’s methodology.
Data from the South Dakota Department of Health
The existing data that was received from the South Dakota Department of Health for
analysis in this thesis included both public and private schools located within South Dakota
(Appendix B). All data was received anonymously. The sample population that was analyzed is
school aged children, grades 1-5 (ages 5-11), both male and female, the majority Caucasian.
Data that was used in this study were the anthropometric measurements of the children, this
was assumed to be collected using methods, techniques, and tools that were pre-approved and
overseen by a medical professional (i.e.: school nurse). The sample form used for data
collection can be found in the Appendix A. Measures taken on the children included weight,
and height.
Data obtainment took place in spring 2012. The intention of data obtainment was to
first receive permission from The South Dakota Department of Health to analyze their
preexisting data, including both anthropometric measurements of their children as well as their
National School Lunch Program participation. The data set for 2010-2011 academic year from
20
the South Dakota Department of Health included over 49,000 students. The data set for the
2009/2010 academic year included over 40,000 students. The data from each student collected
by the South Dakota Department of Health included school name, county, education region,
date of birth, height, weight, gender, and ethnicity. From the National School Lunch Program
data set, the data that was collected by the DOH included school district, school name, site
enrollment, and percent of students eligible for free and reduced priced meals. The South
Dakota Department of Health followed specific guidelines for data collection (Appendix A). The
following text summarizes the data collection methods utilized by the South Dakota
Department of Health:
The Coordinated School Health Program sent letters to all South Dakota school health
and physical education teachers and school nurses requesting that schools share their
height and weight data with the DOH. Copies of this letter were also sent electronically
to superintendents and building principals. Data collection instructions on the correct
way to measure children and forms to submit data were posted on the project
website...School participation in the data collection effort is voluntary and there is no
payment for submitting data. South Dakota completed this project for the thirteenth
time during the 2010-2011 school year (Biskeborn, et al, 2011).
Data from National School Lunch Program
“In South Dakota, the Child and Adult Nutrition Services is responsible for administering
the U.S. Department of Agriculture’s Food and Nutrition Services and Food Distribution Division
Programs” (Biskeborn, et al, 2011). The programs that this department is responsible for
includes: summer food service, child and adult care food, team nutrition activities, commodity
21
supplemental food program, USDA food distribution for child nutrition programs, the
emergency food assistance program, fresh fruit and vegetable program, special milk,
reauthorization, and lastly the National School Lunch and School breakfast program (Biskeborn,
et al, 2011).The National School Lunch Program (NSLP) is a federally assisted meal program that
is able to operate both within public and non-profit private schools as well as licensed and
accredited residential child care institutions (Biskeborn, et al, 2011). The National School Lunch
Program provides nutritionally balanced, low-cost or free lunches to children each school day,
however, in order to determine eligibility for low-cost or free lunches; specific requirements
must be met (such as income). The data that was received from the South Dakota DOH on the
NSLP enrollment was able to provide a resource for an estimate of socioeconomic status for
students enrolled in both public and private institutions. The percent of students enrolled in the
NSLP was based on percent enrolled by region. In order to properly assess the children’s
socioeconomic status, the preexisting data from the DOH was analyzed from the school’s 2010
enrollment of the National School Lunch Program. Participation within this program indicated
the student’s socioeconomic status, and provided a correlation for the anthropometric
measurements of the children.
Data Analysis
Once the data from the DOH and NSLP had been received it was then compiled together
into a larger data base in order to ensure proper organization and data analysis. From the given
height and weight of the students, BMI was then calculated using the appropriate equation
placed into an Excel spreadsheet. This metric equation that was used to calculate the BMI of
the children was (weight (kg)/ [height(m)]2 (CDC, 2009a), this value was then plotted on the
22
Center for Disease Control and Prevention (CDC) BMI-for-age and gender charts to determine
the percentile of each child (Appendix E). Each child was classified into one of four categories
based on the percentile determined (Table 1). For further analysis on the National School Lunch
Program data, the schools were broken down into corresponding education regions and
correlated with the occurrence of overweight and obesity. Analyses and statistics were run on
both the anthropometric measurements of the children and the National School Lunch Program
enrollment; this included descriptive statistics as well as a Pearson’s r correlational test for
significance. The program used for statistical analysis was the Statistical Program for Social
Sciences (SPSS), version 17.0. Error bars on graphs represent the SEM.
Table 1: Classification of Weight Status Based on Percentile Ranking Weight Status Percentile
Underweight <5th percentile
Normal Weight 5th≤85th percentile
Overweight 85th<95th percentile
Obese ≥95th percentile
Limitations
The major limitation in this study was the diversity of the participants—the majority
population of South Dakota is Caucasian with a large minority of Native Americans (~10%) and
because obesity and poverty seem to be closely related with race and ethnicity, generalizing
this data to all populations across the United States may result in a skewed perception of data
(if the population is largely different). The preexisting data that was taken from the South
Dakota Department of Health also included limitations that might affect the data analysis:
Data quality has been determined to be within acceptable standard deviation but has
the following limitations: First, schools voluntarily submitted height and weight data
23
from across the state, but no attempt was made to obtain a representative sample.
However, school personnel collected data for 35.2 percent of the state’s students from
193 schools. While American Indian students comprise 15.8 percent of the South Dakota
enrollment population, they represent 10.1 percent of the students surveyed. Second,
the data was filtered and the following types of records were removed: data that had
biologically implausible results, entries where all essential data elements were not
completed, and duplicate records. After removing the above cases, the sample size was
49,146 students and 193 schools for analysis. Third, while the instructions included the
type of equipment and technique that schools should use, there is no assurance that
school personnel always followed the instructions. The DOH provided balance-beam
scales and wall-mounted measuring boards to schools to help improve the quality of
data. While it is not known what training persons who obtained the measurements had,
it is known that school nurses or school health and physical education teachers obtained
or supervised the data collected. Fourth, South Dakota’s height data are of acceptable
quality, however, worldwide measurements of height tend to be of marginal quality.
There could be several possible reasons for this including the use of measuring
equipment that did not allow accurate heights to be obtained. This can occur when the
person doing the measuring is shorter than the person being measured. Those who
measure adolescents may need to stand on a step stool or a chair to have their eye level
above the child’s head. In addition, if the measuring stick on a standing scale was used,
the children would be inaccurately reported as shorter than they are. South Dakota
should be aware of this problem when determining heights. This may be solved now as
24
adolescent height is more normal but this may explain the high level of short stature for
the 1998-1999 school year (Biskeborn, et al, 2011).
25
Figure 1: South Dakota School Demographics
White Non-Hispanic
American Indian/Alaska Native
Hispanic
Black Non-Hispanic
Other
Not Specified
Asian
Hawaiian/Pacific Islander
Chapter IV: Results
This chapter will include results based on gender, ethnicity, age, and school location and
a detailed analysis of the National School Lunch Program that has been correlated with the
2010-2011 South Dakota public school anthropometric measurements.
Demographic Data
49,791 students were surveyed and measured within the South Dakota public and
private school system for their anthropometric measurements. Of the students measured, 79%
were White non-Hispanic, 10% were American Indian/ Alaska Native, 3% were Hispanic, 3%
were Black non-Hispanic, 2% were ‘other’, 1% were Asian, 1% were Hawaiian/Pacific Islander,
and 1% were ‘not specified’ (Figure 1). Within the large population of these students there
were differences found between the student’s BMI and their ethnicity/race (Figure 2). The
average BMI among the different races of the students ranged from 18.4-21.1 with a standard
26
margin of error at .238. The highest average BMI belonging to the Black Non-Hispanic sample
population with an average of 21.1 (+/-.12); Hawaiian/Pacific Islanders with an average of 20.7
(+/-.37); Hispanic with an average of 20.5 (+/-.18); ‘other’ with an average of 19.4 (+/-.56);
White non-Hispanic with an average of 19.4 (+/-.15); American Indian/Alaskan Native with an
average of 19.1(+/-.11); Asian with an average of 18.9 (+/-.23); and lastly ‘not specified’ with an
average of 18.4 (+/-.19)(Figure 2). A one-way ANOVA was used to determine the significance of
this data, and from this test it was found that the differences between groups was found
significant with a p-value =.042 (p<.05).
Table 2 indicates that the most frequent occurrence of overweight (85th≤95th
percentile), in accordance to race, was found within the American Indian/Alaska Native
category, followed by ‘not specified’, ‘other’, and White non-Hispanic with 19.4%, 17.1%,
16.8%, & 15.5% respectively (Table 2).
Similarly, the most frequent occurrence of obese children (>95th percentile) was also
found within the American Indian/Alaska Native population with a 26.9% occurrence, followed
15 16 17 18 19 20 21 22
Not Specified
Asian
American Indian/Alaska Native
White Non-Hispanic
Other
Hispanic
Hawaiian/Pacific Islander
Black Non-Hispanic
Figure 2: Average BMI Differences Among Race
Average BMI
27
by ‘not specified’, ‘other’, and White non-Hispanic with 20.5%, 18.7%, and 13.2%, respectively.
With a combined total of overweight and obese children in the categories of White non-
Hispanic, American Indian/Alaska Native, ‘other’, and ‘not specified’ (not taking the other
ethnic groups into consideration) the occurrence of overweight and obese children surveyed
within this South Dakota population exceeds 30%.
Table 2: Overweight and Obese Body Mass Index by Race
Race Number of Students
Underweight Normal Weight
Overweight Obese
White non-Hispanic
38,708 1,510 (3.9%)
26,089 (67.4%)
6,000 (15.5%)
5,109 (13.2%)
American Indian/Alaska Native
4,830 87 (1.8%)
2,507 (51.9%)
937 (19.4%)
1,299 (26.9%)
Other 4,576 384 (8.4%)
2,567 (56.1%)
769 (16.8%)
856 (18.7%)
Unknown/Not Specified
696 32 (4.6%)
402 (57.8%)
119 (17.1%)
143 (20.5%)
Total 48,810*
2,013 (4.1%)
31,565 (64.7%)
7,825 (16.0%)
7,407 (15.2%)
Values in parenthesis are percent of total within that ethnic group *This value is different from the original value of 49,146 because Hispanic, Black Non-Hispanic,
Asian, & Hawaiian/Pacific Islander categories are omitted, for statistical purposes.
Gender Data
Next, in respect to gender, the sample population consisted of 48% males and 52%
females, and within these two groups, differences were also found among the South Dakota
students. These differences showed the frequency of overweight and obese in both genders as
well as a variety of ages. Table 3, summarizes the amount of overweight and obese body mass
index by gender (utilizing data from 2009/2010 and then comparing it to that of 2010/2011) in
both female and male participants. From 2010 to 2011, the female’s overweight and obese
body mass index decreased from 16.7% and 16.0% to 16.1% and 15.2%, respectively; the male’s
28
overweight and obese body mass index decreased from 16.7% and 17.3% to 16.1% and 16.0%,
respectively.
Table 3: Weight Status by Gender
Total Female Male
2010/2011: Underweight
Normal weight
Overweight
Obese
Total
2025
(4.1%) 31,737 (6.5%) 7,912
(16.1%) 7,470
(15.2%)
49,146
474
(2.0%) 16,036 (67.6%) 3,795
(16.0%) 3,416
(14.4%)
23,721
539
(2.1%) 16,725 (65.8%) 4,093
(16.1%) 4,068
(16.0%)
25,425
2009/2010: Underweight
Normal weight
Overweight
Obese
Total
1630
(4.0%) 25,926 (63.3%) 6,838
(16.7%) 6,551)
(16.0%)
40,945
424
(2.1%) 13,134 (66.6%) 3,296
(16.7%) 2,881
(14.6%)
19,735
477
(2.2%) 13,522 (63.8%) 3,542
(16.7%) 3,669
(17.3%)
21,210
Values in parenthesis are percent of total.
Age Data
Table 4 illustrates data found from anthropometric measurements regarding BMI-for-
age statistics for South Dakota students. The data shows age groups 5-8 and 9-11, as that is
defined as ‘childhood’. This table indicates that both of these age groups in South Dakota have
a larger occurrence of overweight and obesity than what is desired from the South Dakota
Department of Health (≤14%). The percent of obese children aged 5-8 years in 2010 was 13.0%
29
and the percent of obese children aged 9-11 years was 16.3%; with a total combined value of
14.5% (Table 4). Figure 3 illustrates a more visual representation of Table 4 for the occurrence
of overweight and obese students organized by age. It is important to note an overall
increasing trend in the occurrence of overweight and obese students as they progress in age.
Table 4: Overweight and Obese Body Mass Index for Age
Age (years) Number of Students Underweight Normal Overweight Obese
5-8 17,998 684 (3.8%)
12,293 (68.3%)
2,682 (14.9%)
2,339 (13.0%)
9-11 15,717 550 (3.5%)
10,012 (63.7%)
2,593 (16.5%)
2,562 (16.3%)
Total 33,715 1,234 (3.7%)
22,305 (66.2%)
5,275 (15.7%)
4,901 (14.5%)
Regional Data
In reference to Appendix D, South Dakota is divided into 6 different geographical regions
which have been numbered 1, 2, 3, 5, 6, & 7(there is no region 4). Table 5 shows the highest
combined occurrence of overweight and obese in region 5 at 40.0% followed by region 6 at
37.1%, region 1 at 33.3%, region 7 at 29.4%, region 2 at 27.7%, and lastly region 3 at 21.0%.
0.00%
5.00%
10.00%
15.00%
20.00%
Overweight Obese
Figure 3: Overweight and Obese Body Mass Index by Age
5-8
9-11
30
Table 5: Overweight and Obese Body Mass Index by Regions
Region Number of Students
Underweight/Normal Weight Combined
Overweight Obese
1 10,639 7,096 (66.7%)
1,830 (17.2%)
1,713 (16.1%)
2 19,681 14,229 (72.3%)
2,913 (14.8%)
2,539 (12.9%)
3 5,091 4,020 (79.0%)
957 (18.8%)
114 (2.2%)
5 1,491 894 (59.9%)
253 (17.0%)
344 (23.1%)
6 2,944 1,852 (62.9%)
553 (18.8%)
539 (18.3%)
7 9,300 6,565 (70.6%)
1,386 (14.9%)
1,349 (14.5%)
Total 49,146 33,763 (68.7%)
7,913 (16.1%)
7,470 (15.2%)
Values in parenthesis indicate percent of total.
National School Lunch Program Data
Table 6 illustrates the percent of students eligible for free and reduced priced meals by
region. The results showed that the percent eligible for free and reduced meals for all regions is
at an average of around 37.97%, which is more than 1/3 of all students in South Dakota that
received free or reduced cost meals in 2010-2011 school year. The region in which the most
Table 6: Percent Eligible for Free and Reduced Price meals by Region Region Region Enrollment Number eligible for
free and reduced meals
Percent eligible for free and reduced price
meals
1 14,551 4,576.9 31.45%
2 34,272 11,615.7 33.89%
3 8,889 4,089.7 46.01%
5 2,709 1,667.6 61.55%
6 3,738 1,598.8 42.77%
7 19,505 8,217 42.13%
Total 83,664 31,765.6 37.97%
31
students are receiving assistance from the NSLP in respective order is region 5, region 3, region
6, region 7, region 2, and finally region 1.The range between the highest participation region (5)
and the lowest participation region (1) was nearly two fold.
Figure 4 is one of the most important figures to this research, as it correlates the
National School Lunch Program enrollment by region in South Dakota with that region’s specific
overweight and obese combined occurrences. After running a Pearson’s Correlation test
between these two variables the Pearson’s r-value is +.385 at a confidence level of .05,
indicating a moderate positive correlation. As the percent of students who are eligible for free
and reduced priced meals increases so does the occurrence of overweight and obesity of South
Dakota students.
1
2
3
5
6 7
y = 0.5992x + 0.2413 R² = 0.1484
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
0.00% 10.00% 20.00% 30.00% 40.00% 50.00%
Pe
rce
nt
Elig
ible
fo
r N
SLP
Percent Occurrence of Overweight & Obesity
Figure 4: Correlational Analysis of Percent Eligible for Free and Reduced Priced Meals Vs. Occurence of Overweight & Obesity by Region
3
32
Chapter V: Conclusions and Discussions
This chapter will begin with the conclusions made from the results; then followed by a
discussion comparing and contrasting the results, and lastly it will end with recommendations
for the future.
Conclusions
It was found that Native Americans, around 10% of the sample population in South
Dakota, showed a more frequent occurrence of being overweight or obese, in comparison to
the other races. In respect to gender, significant differences were found among the South
Dakota participants; males in the population had a higher occurrence of obesity when
compared to females, and in comparison from previous data collected in 2009/2010 by the
South Dakota Department of Health, the occurrence of overweight and obese in both male and
female students decreased in 2010/2011. According to the data analyzed, both age groups of 5-
8 and 9-11 in South Dakota have an issue with the occurrence of overweight and obesity with a
higher combined total occurrence than the South Dakota’s healthy kids 2020 objective of ≤14%.
The results for body mass index by regions of South Dakota show that the highest combined
occurrence of overweight and obesity was found in region 5, followed by region 3, region 6,
region 1, region 7, and lastly region 2. It should be noted that region 2 was the only region that
was considered significantly below the state’s confidence interval rate of 14.9% while regions 3,
5, and 6 were significantly higher than the state rate. Lastly, the data analysis on the National
School Lunch Program showed that more than 1/3 of all students surveyed were eligible for
free and reduced meals, which was a similar figure for the occurrence of overweight and obese
children. The region in which the most students are receiving assistance from the NSLP in
33
respective order is region 5, region 3, region 6, region 7, region 2, and finally region 1. The
range between the highest participation region and the lowest participation was nearly two
fold. After running a Pearson’s Correlation test between these two variables (occurrence of
overweight and obesity vs. enrollment in NSLP) the Pearson’s r-value (+.385) indicated a
moderate positive correlational relationship. The correlation is said to have a moderate
positive relationship because the value falls between +.30-.39 (Pearson’s r Correlation, 2012).
While the Pearson’s r value indicates a moderate positive relationship between childhood
obesity and socioeconomic status it must be noted that correlation does not provide causation,
but the data does provide valuable insight on this relationship. As the percent of students that
are eligible for free and reduced priced meals increases as does the occurrence of overweight
and obesity of South Dakota students.
From the results presented in the previous section of this thesis, it can be concluded
that childhood obesity is a significant problem in the South Dakota population; affecting both
males and females and also many different ethnicities alike. The results can also conclude that
families with a low socioeconomic status are more likely to experience being overweight or
obese in childhood, which may be a result of several factors including poor diet, lack of
exercise, family history and environment, and psychological impact. According to the South
Dakota Department of Health;
Childhood overweight and child obesity is a multi-faceted problem that should be
addressed by promoting healthy eating and increasing physical activity and decreasing
inactivity. While it will take South Dakotans working together to overcome this
34
increasing problem, schools can play a key role in providing education and healthy
environments (Biskeborn, et al, 2011, p. 13).
Discussion
The results of this study are consistent with the epidemic of overweight and obesity
affecting children across the entire USA and developed countries alike, and the conclusions
made in regard to this thesis are similar to the conclusions made by the CDC. Recently, the CDC
reported that around 17% of children nationwide are obese, and that this percentage has
increased exponentially in the past decades (Centers for Disease Control and Prevention, 2010).
In children aged from 6-11 the amount of obesity from 1976-2008 has increased by 13.1%, a
rising trend that proves to be problematic (Centers for Disease Control and Prevention, 2010).
Another finding that was consistent with current research is that socioeconomic status may
contribute to a child’s weight. A low socioeconomic status encompasses several factors that can
contribute to an overweight child, factors outlined by The Southern Medical Journal include
(but are not limited to): health insurance, local schools, local food stores, public transportation,
participation in sedentary activities, and subsidized local, state, and federal programs (Vieweg
et al., 2007). In agreement with The Southern Medical Journal, The CDC also reports that a low
socioeconomic status may influence a higher BMI in children; in a low socioeconomic
environment, one in seven low-income, preschool-aged children is obese, and the prevalence
of obesity in low-income toddlers has increased markedly from the year 1998 to 2003 at an
occurrence 12.4% in 1998 to 14.5% in 2003 (Centers for Disease Control and Prevention, 2010).
Being overweight or obese as a child can not only be detrimental to the mental and emotional
health of child but physically as well. Obese and overweight children experience more severe
35
health problems at a younger age than the majority of their normal weight peers. Ailments that
affect overweight and obese children include but are not limited to cardiovascular diseases,
type 2 diabetes mellitus, asthma, sleep apnea, and a fatty liver. From these diseases and
ailments overweight and obese children will not only have a poor quality of life at a younger
age but will continue to struggle with this issue into their adult life.
Recommendations
While prevention of childhood obesity should be the ultimate goal for healthcare
providers, families, and schools, the United States still needs to recognize that children are
individuals, and that each child may need a specific plan of care, taking into context all the
factors to why and how the child is at risk or has become overweight or obese. The South
Dakota schools, as well as schools across the United States are encouraged to work with their
local doctors and health representatives to define when and how referrals for evaluation and
intervention should be made on students that are at risk for becoming overweight or obese.
Recommendations for further research would include an investigation of other states on their
socioeconomic status versus the occurrence of childhood obesity, in order to determine
whether or not a low socioeconomic status is indicative to childhood overweight and obesity
across the nation. A longitudinal survey would also be of benefit in order to follow students
from childhood to young adulthood to see if a low socioeconomic status at a young age
correlates with the occurrence of adulthood obesity. Lastly, an outreach program should be
made for those who are receiving aid form the National School Lunch Program in order to
educate both students and families on the importance of healthy eating while maintaining a
36
budget; having budget friendly healthy alternatives to cheap, convenience, or fast food could
significantly impact the effect of childhood obesity on our nation.
Suggestions for intervention for the prevention and treatment of childhood obesity and
other chronic diseases include increasing the amount of physical activity, decreasing television
viewing, increase fruit and vegetable intake, decrease sweetened beverage intake, decrease
portion sizes, increase breastfeeding, and increase nutrition education in schools both for
families and children. Families regardless of socioeconomic status should be able to provide
their children with healthy food choices for meals and snacks, encouraging children to be
physically active, involving children in selecting and preparing healthful food, involving children
in appropriate activity programs, serving as a role model for children, and limiting television
watching or video games to no more than 2 hours per day (Biskeborn, et al., 2012).
37
References
About BMI for children and teens. Centers for Disease Control and Prevention. (2011, February
15). Retrieved April 10, 2011, from: www.cdc.gov/healthyweight/
Babey, S., Hastert, T., Wolstein, J., & Diamant, A. (2010). Income disparities in obesity trends
among California adolescents. American Journal of Public Health, 100(11), 2149-2155.
Bellows, L., & Roach, J. (2010, May 12). Childhood obesity. Colorado State University Extension.
Retrieved April 11, 2011, from: www.ext.colostate.edu/pubs
Biskeborn, K., Buhler, B., Cushing, C., Gildemaster, M., & Christensen, M. (n.d.). South Dakota
School Height Weight Survey Project. Department of Health. Retrieved July 31, 2012,
from doh.sd.gov/SchoolWeight/
Centers for Disease Control and Prevention. Obesity and overweight for professionals. (2010, June 21).
Retrieved April 25, 2011, from: www.cdc.gov/obesity/defining
Centers for Disease Control and Prevention. Glossary. (2009, June 5). Retrieved April 10, 2011,
from: www.cdc.gov/leanworks/resources
Mayo Clinic Staff. Childhood obesity. (2010, February 9). Retrieved July 31, 2012, from:
www.mayoclinic.com/health/childhood-obesity/DS00698
Mayo Clinic Staff (2010a). Childhood Obesity, Complications, Retrieved July 31, 2012 from
http://www.mayoclinic.comlhealthlchildhoodobesity/DS00698/DSECTION=complication
s
Mayo Clinic Staff. (201 Ob). Childhood Obesity, Definition, Retrieved July 30,2012, from
http://www.mayoclinic.com/heaJthlchildhood-obesity/DS00698
38
Mayo Clinic Staff. (201 Oc). Childhood Obesity. Risk Factors, Retrieved July 30th, 2012, from
http://wwW.mayoclinic.com/healthichildhood-obesity/DS00698/DSECTION=risk-factors
About the National Health and Nutrition Examination Survey. (2012, July 12). Centers for
Disease Control and Prevention. Retrieved August 1, 2012, from
http://www.cdc.gov/nchs/nhanes/about_nh
Pearson’s r Correlation. (n.d.).Instructor’s Resource Guide for the Text. Retrieved July 31, 2012,
from faculty.quinnipiac.edu/libarts/polsci/Statistics.html
Pourhassan, M., & Najafabadi, A. (2009). Survey prevalence and prevention of childhood
obesity. Shiraz E. Medical Journal, 10(3), 126-137.
Socioeconomic status. American Psychological Association (APA) (n.d.). Retrieved April 10,
2011, from: www.apa.org/topics/socioeconomic-status/index.aspx
Vieweg, V., Johnston, C., Lanier, J., Fernandez, A., & Pandurangi, A. (2007). Correlation between
high risk obesity groups and low socioeconomic status in school children. Southern
Medical Journal, 100(1), 8-13.
Wells, N., Evans, G., Beavis, A., & Ong, A. (2010). Early childhood poverty, cumulative risk
exposure, and body mass index trajectories through young adulthood. American Journal
of Public Health, 100(12), 2507-2512.
Williamson, D., Champagne, C., Han, H., Harsha, D., Corby, M., Newton, R., et al. (2009).
Increased obesity in children living in rural communities of Louisiana. International
Journal of Pediatric Obesity, 4(3), 160-165.
World Health Organization. (n.d.). Childhood overweight and obesity. Retrieved April 11, 2011,
from: www.who.int/dietphysicalactivity
39
Appendix A:
Directions for Completing School Heights and Weights Data Sheet
School Name and County: Provide full name of school and county in which school is located.
District Name: Report the name of the school district in which the school is located.
Contact Name and Email: This information is needed in case there are questions about the data.
Provide the name of the contact person and their email address.
School Principal’s Name and Email: This information is needed for contact purposes.
2. Date of Measurement: Complete date using month, day, and year. If data was obtained on
September 20, 2010 enter 09 20 2010. Use a separate page for each day data is collected.
Please send data as obtained rather than wait until the end of the school year to send the
recorded data.
Information on each student measured:
Name of student: Remove this information before submitting the data. It is provided for local
school information only.
4. ID#: Each child measured needs a unique identification number. It can just be numerical
order but three digits should be used (i.e., 001, 002, etc). The number is used for data collection
purposes only. Please do not use an ID number more than once for each school.
5. Sex: Enter sex of student as either 1 (male) or 2 (female).
6. Date of Birth: Record person’s date of birth. If date of birth is May 8, 2000, record as follows:
Month Day Year
0 5 0 8 2 0 0 0
7. Ethnic Origin/Race: Enter each student’s race. Complete this by your observation of the race.
Select one or more of the categories listed below:
1 White, not Hispanic
2 Black, not Hispanic
3 Hispanic
4 American Indian or Alaskan Native
5 Hawaiian or Pacific Islander
40
6 Asian
7 Other
9 Not Specified / Unknown
8. Height: Enter height of individual. Use inches to the nearest 1/8 inch. Do not change
denominator of fraction. Always convert to eighths: 3/4 should be converted to 6/8, 1/4 to
2/8, etc. If height is 45 1/8 inches, record as follows:
4 5 1/8
Allowable entries for numerator of fraction are 0-7. Do not leave blank if zero. Do not use 9 for
an unknown fraction. If height is 62 inches, record as follows:
6 2 0/8
Below is a conversion chart to convert feet and inches to inches. We have added this to the
report form for ease of submitting height in inches, as required.
School personnel should measure height with a metal measuring tape and right-angle
headpiece or full-length measuring board to insure accuracy. Do not use the measuring rod on
the adult balance beam weight scale because it is not accurate. Have individual remove shoes,
heavy outer clothing, hats, and hair barrettes. Procedure:
(1) Have the student stand with his or her back against the wall on a flat floor directly in front of
the measuring tape. The tape should run directly down the center of the back.
(2) Individual should stand with feet slightly apart and the back as straight as possible. The
heels, buttocks, and shoulder blades should touch the wall or surface of the measuring board.
(3) Have individual look straight ahead with head erect but not touching the wall or measuring
board.
(4) Place the headpiece flat against the wall and at a right angle to the head. Lower it until it
firmly touches the crown of the head.
41
(5) Hold the right-angle headpiece steady and have the person move out from under it.
(6) Read the measurement at eye level where the lower edge of the headpiece intersects the
measuring tape.
(7) Repeat the procedure until two measurements agree within 1/4 inch. Record the larger of
the two measurements on the form.
9. Weight: Enter weight of individual. Use pounds to the nearest 1/4 pound. Do not change the
denominator of the fraction. Always convert to fourths (1/2 should be converted to 2/4, 4/16 to
1/4, etc.) For example, if weight is 56 1/2 pounds, record as follows:
0 5 6 2/4
Do not leave numerator of fraction blank if zero. Do not use 9 for unknown fraction unless
pounds are unknown also. For example, 125 pounds is recorded as follows:
1 2 5 0/4
Weight should be taken without shoes or heavy outer clothing. Use adult beam balance scale if
at all possible. Scale needs to be placed on uncarpeted floor if possible for an accurate weight.
Child needs to stand on the center of scale platform and not be touching other objects or
person. Child should be weighed, step off the scale, and then weighed again to ensure an
accurate weight.
10. Submit data as soon as possible after measurements are taken, though data will be
accepted throughout the school year until the June 15 deadline. Send all data to:
Email: [email protected]
Mail: Carrie Cushing
South Dakota Department of Health
600 E. Capitol
Pierre, SD 57501-2535 Fax: 5605.773.5683
42
Return to: Carrie Cushing Email: Carrie.Cushina®state.sd.us South Dakota Department of Health BOD East C•pl.61 Pierre, SO 57!01
SCHOOL HEIGHTS /WEIGHTS
School Name: -----------------------------------------------------------------------
Coum~ -----------------------------------------------------------------------Oistrict Name: --------------------------------------
Contacl Person: --------------------------------School Principal Name: --------------------------------
Date or Measurements:
MD DAY YEAR
Contact Email: ----------------------
Principal Email: -------------
Name (For your use only - remove lOll Sex DOS (req uired) Race Height Welght Ft. ln. • Inc n FL • In< before submitting} requll"ed inclles 8'i pounds .c~s
mo dav "'"" 3 •• "' s 3 • ., 3 1 . ., • . . "' 3 2• 38 s s • ..
18 /4 3 3 • ,. s •• .. /8 14
3 4 • 40 • 7 • "' 3 5o " s a. !a /8 /4 3 •• 42 • 9 • ..
3 7 • 43 5 10 • 70 /8 /4 3 •• .. 5 11 • 71
/8 /4 3 §. 4S $ 0 • 72 3 10 . 48 • 1 • 73
/8 /4
/8 /4
3 11 • 47 • 2 • 74
' •• .. • 3 • 75 4 i • 49 $ •• 76
/8 /4 4 2 • so • s • n 4 3 • S1 • •• 78
/8 /4 ' 4 • S2 • 7 • 79
/8 /4 ' •• 53 • •• 80 4 •• .. • •• 81
/8 /4 4 7 • 56 6 10 . 82 4 •• .. 8 11 • B3
/8 /4 • 9• 57 1 0 • Ill
/8 /4 4 tO • .. 7 1 • .. 4 n. 59 7 2 • ..
18 /4 18 /4
• •• .. 7 3 • 87 s 1. 81 1 • • .. • 2 • 62 7 •• 89
~ 1=White . not Hispanic 2=Btack. not Hispan.ic 3=Hi:spanic 4=American Indian or AlaSkan Native 5=Ha'lo'l•ailan or Paa'ic Islander 6=Asian 7=0ther 9-=Unknown
For sWdents with more Ulan one race. p&ease indicate eacli race and separa!e with a comma. &!.;. 1=MBB 2=Female
43
Appendix B Participating Schools
School Name, City Education Service Agency Region County
Alcester-Hudson Elementary, Alcester 2 Union
All City Elementary, Sioux Falls 2 Minnehaha
Anne Sullivan Elementary, Sioux Falls 2 Minnehaha
Atall Elementary, Union Center 7 Meade
Axtell Park Middle School, Sioux Falls 2 Minnehaha
Baltic High School, Baltic 2 Minnehaha
Batesland Elementary, Batesland 7 Shannon
Beadle Elementary, Yankton 3 Yankton
Belle Fourche High School, Belle Fourche 7 Butte
Belle Fourche Middle School, Belle Fourche 7 Butte
Black Hawk Elementary, Black Hawk 7 Meade
Blumengard Colony, Faulkton 5 Faulk
Brandon Elementary, Brandon 2 Minnehaha
Brandon Valley Middle School, Brandon 2 Minnehaha
Brentwood Colony, Faulkton 5 Faulk
Bridgewater Elem, Bridgewater 2 Hanson
Brown High School, Sturgis 7 Meade
Buchanan Elementary, Huron 3 Beadle
Burke Schools, Burke 3 Gregory
Camelot Intermediate, Brookings 1 Brookings
Canyon Lake Elementary, Rapid City 7 Pennington
44
CC Lee Elementary, Aberdeen 1 Brown
Central High School, Aberdeen 1 Brown
Challenge Center, Sioux Falls 2 Minnehaha
Chamberlain Elem, Chamberlain 3 Brule
Chancellor Elementary, Chancellor 2 Lincoln
Cleveland Elementary, Sioux Falls 2 Minnehaha
Colman-Egan Schools, Colman 1 Moody
Corral Drive Elementary, Rapid City 7 Pennington
Dakota Middle School, Rapid City 7 Pennington
Dakota Valley Elementary, N. Sioux City 2 Union
Dakota Valley Jr HS, N. Sioux City 2 Union
De Smet Schools, De Smet 1 Kingsbury
Dell Rapids Middle School, Dell Rapids 2 Minnehaha
Discovery Elementary, Sioux Falls 2 Minnehaha
Douglas Middle School, Box Elder 7 Pennington
East Elementary, Spearfish 7 Lawrence
Edison Middle School, Sioux Falls 2 Minnehaha
Elk Point-Jefferson Elementary, Elk Point 2 Union
Elk Point-Jefferson MS, Elk Point 2 Union
Elm Springs Elementary, Wasta 7 Meade
Emery Elementary, Emery 2 Hanson
Enning Elementary, Enning 7 Meade
Estelline Elem, Estelline 1 Hamlin
Ethan Schools, Ethan 3 Davison
45
Eugene Field Elementary, Sioux Falls 2 Minnehaha
Evergreen Colony, Faulkton 5 Faulk
Explorer Elementary, Harrisburg 2 Lincoln
Faith Elementary, Faith 5 Meade
Faulkton Schools, Faulkton 5 Faulk
Fred Assam Elementary, Brandon 2 Minnehaha
Freeman Davis Elem, Mobridge 5 Walworth
Garfield Elementary, Sioux Falls 2 Minnehaha
General Beadle Elementary, Rapid City 7 Pennington
George S. Mickelson Middle School, Brookings 1 Brookings
Georgia Morse Middle School, Pierre 6 Hughes
Gertie Belle Rogers Elementary, Mitchell 3 Davison
Grandview Elementary, Rapid City 7 Pennington
Gregory Schools, Gregory 3 Gregory
Groton Schools, Groton 1 Brown
Hamlin Elementary School, Hayti 1 Hamlin
Harrisburg Middle School, Harrisburg 2 Lincoln
Hartford Elementary, Hartford 2 Minnehaha
Harvey Dunn Elementary, Sioux Falls 2 Minnehaha
Hawthorne Elementary, Sioux Falls 2 Minnehaha
Hayward Elementary, Sioux Falls 2 Minnehaha
Hereford Elementary, Hereford 7 Meade
Highmore-Harrold Elementary, Highmore 6 Hyde
46
Hillcrest Elementary, Brookings 1 Brookings
Holgate Middle School, Aberdeen 1 Brown
Horace Mann Elementary, Rapid City 7 Pennington
Horace Mann Elementary, Sioux Falls 2 Minnehaha
Howard Elementary, Howard 2 Miner
Howard High School, Howard 2 Miner
Howard Junior High School, Howard 2 Miner
Humboldt Elementary, Humboldt 2 Minnehaha
Huron High School, Huron 3 Beadle
Huron Middle School, Huron 3 Beadle
Immaculate Conception, Watertown 1 Codington
Iroquois Schools, Iroquois 1 Kingsbury
Jefferson Elementary, Huron 3 Beadle
Jefferson Elementary, Pierre 6 Hughes
Jefferson Elementary, Sioux Falls 2 Minnehaha
Jefferson Elementary, Watertown 1 Codington
Joe Foss Alternative, Sioux Falls 2 Minnehaha
John F. Kennedy Elementary, Sioux Falls 2 Minnehaha
John Harris Elementary, Sioux Falls 2 Minnehaha
John Paul II Elementary, Mitchell 3 Davison
Journey Elementary, Harrisburg 2 Lincoln
Knollwood Heights Elementary, Rapid City 7 Pennington
Koch Elementary, Milban 1 Grant
47
Lake Preston Elementary, Lake Preston 1 Kingsbury
Laura B. Anderson Elementary, Sioux Falls 2 Minnehaha
Laura Wilder Elementary, Sioux Falls 2 Minnehaha
LB Williams Elementary, Mitchell 3 Davison
Lead-Deadwood Elem, Deadwood 7 Lawrence
Lennox Elementary, Lennox 2 Lincoln
Lennox Middle School, Lennox 2 Lincoln
Liberty Elementary, Harrisburg 2 Lincoln
Lincoln Elementary, Aberdeen 1 Brown
Lincoln High School, Sioux Falls 2 Minnehaha
Longfellow Elementary, Mitchell 3 Davison
Longfellow Elementary, Sioux Falls 2 Minnehaha
Lowell Elementary, Sioux Falls 2 Minnehaha
Lower Brule Elementary, Lower Brule 6 Lyman
Lower Brule High School, Lower Brule 6 Lyman
Madison Elementary, Huron 3 Beadle
Mark Twain Elementary, Sioux Falls 2 Minnehaha
May Overby Elementary, Aberdeen 1 Brown
McCook Central Elementary, Salem 2 McCook
McCook Central Middle School, Salem 2 McCook
McIntosh Schools, McIntosh 5 Corson
McKinley Elementary, Pierre 6 Hughes
McLaughlin Elementary, McLaughlin 5 Corson
48
McLaughlin High School, McLaughlin 5 Corson
McLaughlin Middle School, McLaughlin 5 Corson
Meadowbrook Elementary, Rapid City 7 Pennington
Medary Elementary, Brookings 1 Brookings
Memorial Middle School, Sioux Falls 2 Minnehaha
Milbank High School, Milbank 1 Grant
Milbank Middle School, Milbank 1 Grant
Mitchell Middle School, Mitchell 3 Davison
Mobridge-Pollock Middle School, Mobridge 5 Walworth
Mobridge Upper Elementary, Mobridge 5 Walworth
North Middle School, Rapid City 7 Pennington
North Park Elementary, Belle Fourche 7 Butte
OM Tiffany Elementary, Aberdeen 1 Brown
Opal Elementary, Opal 7 Meade
Oscar Howe Elementary, Sioux Falls 2 Minnehaha
Patrick Henry Middle School, Sioux Falls 2 Minnehaha
Pearl Creek Colony Elementary, Iroquois 1 Kingsbury
Philip Schools, Philip 7 Haakon
Piedmont/Stagebarn Elementary, Piedmont 7 Meade
Pierre Indian Learning Center, Pierre 6 Hughes
Pinedale Elementary, Rapid City 7 Pennington
Platte-Geddes Elementary, Platte 3 Charles Mix
Platte-Geddes Junior High School, Platte 3 Charles Mix
49
Rapid Valley Elementary, Rapid City 7 Pennington
Redfield Schools, Redfield 1 Spink
Renberg Elementary, Sioux Falls 2 Minnehaha
RF Pettigrew Elementary, Sioux Falls 2 Minnehaha
Robbinsdale Elementary, Rapid City 7 Pennington
Robert Frost Elementary, Sioux Falls 2 Minnehaha
Roosevelt Elementary, Watertown 1 Codington
Roosevelt High School, Sioux Falls 2 Minnehaha
Rosa Parks Elementary, Sioux Falls 2 Minnehaha
Rutland Schools, Rutland 1 Lake
Sacred Heart, Yankton 3 Yankton
Sanborn Central Schools, Forestburg 3 Sanborn
Seton St. Elizabeth, Rapid City 7 Pennington
Simmons Elementary, Aberdeen 1 Brown
Simmons Middle School, Aberdeen 1 Brown
Sioux Valley Elementary, Volga 1 Brookings
Sioux Valley Middle School, Volga 1 Brookings
South Canyon Elementary, Rapid City 7 Pennington
South Middle School, Rapid City 7 Pennington
South Park Elementary, Belle Fourche 7 Butte
South Park Elementary, Rapid City 7 Pennington
Southwest Middle School, Rapid City 7 Pennington
St. Agnes Elementary, Vermillion 2 Clay
50
St. Joseph Elementary, Pierre 6 Hughes
St. Mary’s Schools, Dell Rapids 2 Minnehaha
Sturgis Elementary, Sturgis 7 Meade
Success Academy, Sioux Falls 2 Minnehaha
Summit Oaks, Sioux Falls 2 Minnehaha
Sunny Plains Christian School, Iroquois 1 Kingsbury
TF Riggs High School, Pierre 6 Hughes
Terry Redlin Elementary, Sioux Falls 2 Minnehaha
Thunderbird Colony, Faulkton 5 Faulk
Timber Lake Schools, Timber Lake 5 Dewey
Tiospaye Topa Schools, Ridgeview 5 Dewey
Union Center Elementary, Union Center 7 Meade
Valley View Elementary, Rapid City 7 Pennington
Wagner Community Schools, Wagner 3 Charles Mix
Washington Elementary, Huron 3 Beadle
Washington Elementary, Pierre 6 Hughes
Washington High School, Sioux Falls 2 Minnehaha
Watertown Middle School, Watertown 1 Codington
Webster Elementary, Webster 1 Day
Webster Elementary, Yankton 3 Yankton
West Elementary, Spearfish 7 Lawrence
West Middle School, Rapid City 7 Pennington
White Lake Schools, White Lake 3 Aurora
51
White River Schools, White River 6 Mellette
Whitewood Elementary, Whitewood 7 Meade
Whittier Middle School, Sioux Falls 2 Minnehaha
Williams Middle School, Sturgis 7 Meade
Wolf Creek Elementary, Pine Ridge 7 Shannon
Wolsey/Wessington Schools, Wolsey 3 Beadle
Woodrow Wilson Elementary, Rapid City 7 Pennington
Woonsocket Elementary, Woonsocket 3 Sanborn
Worthing Elementary, Worthing 2 Lincoln
52
Appendix C
Appendix D
South Dakota Education Services Agencies Region Map
53
Appendix E
BMI-for-age Growth Charts
2 to 20 years: Glt1s ~E ----------Stature-for-age 8ftd Weight-ror-age percenllles
to---1-- -i-
•:» Cd~J-~ ::,~;;:~··r::u::.r~~~ i:.J ; jti' t ltl,!l
1 In ~cn~t! · .1"'. ·~ ::s:: :a: -tc-:''
9 !i 10 11 12 13
~w..-.-...... ···"f:-;.A~~!i!J ft~C..-•-*- ·--·
- - '-'"" thilnl:--- -- ..... ~ .. - "-CCOoa. ~q>;,-...u~ .. --
14 15 IE '
R£conn • -----
-
:!~· ..... ,....-:I~J. ~~-~~
~1\1·
:!)Q roiU· :~~ t(:N"
....... :!10 ~
~:I _ ~ :1 :iv
~..:oll -w E
~:lJ• I
G
:!:.!i ~20· H T
-"' .. ~10· ;~~ ,.---
~~!i [tOO•
:~ :'3D
"":~ ·9:1
:lO ra ~..r..n
;'Jir. ~
-::;10!1 ;-.:a
:1s •lO =~~~ tiD .. ll! 15 3)
54
2 10 20 year ! Boys E ______________________ ___
Body mass ndex·lcw-age pere~nlile9 RECOfi • ---
L._• .b I .·!hUrt . ~- tijJ• ~ ~ I""" ~ '""" I ~
f~ ~ ~ 1-
1-.:.s-
II I a.~-
~ I
J.3 -- [; :; ,_ r- -r;:: :;:; :::: 1::: 32 -- r; ~ ~ ::;:: I; :; !"""
"""" """' ' I ~ ~ :; ·- !; · ~ 31 -I ~ ~ I 30-
"nii !;abf'Jtt I r :an C\1 "' t I [!.!IJ) "~ ;= .. \\'1;14 ll( •• J ·~ .. ..,lctt•Ym 29-
IA1J ~a-
-i- -,_ = 1-- "21 - 27-- -~~ I ~ = ,_, ....
... 2!i ~= I ~ "::' • r;o; - ~ - 2!i-...
-..:!5 l.:S-.,.. ,__
- 2 ~ t-
- :!3 :!.3 -
... ~ --= - ~~., --:; - - -- ~ - :; ~
- 1?1 !; 1- ·-·-·-= ~ ·--·-.... r~ -·-.,... ,_ ~ ~ :~ !; I ~ :; ~1 -~
~ ~ ~ -• • !-- -- 29 '""" :?0-
- 1!1 ~ ~.::;;
9 -.s~
- te a-
- li 7-..... -......
'""" - :;; ~.~ ~ ; := ~ ::: r-• Hi iiiio ~~ :~ ;.= ~ ,,=;
""' r- ~ ... : ~ s -
~~ := :; r; :; ~~ - '""" !:; .. 5 !""" ~ ~ s -_, -- l l 3 -
- t ~ 12-- - -1_ ... -- .... tgtm• l .. ..fll • ~ -~ ACiE !YEARS) ·~ !;.;;; l iiii :::
'"" ·~ ~ -~ J ~ 5 s r e g 1n ~ , 1~ ~a 14 ts 16 11 ta G 20
., ,.. ..... ~ ... ~4>~·-c.r.·
---~-et.M -...-.... "' ...