1. Investigatingthe relationship between subjective and
objectiveexertion during a cardiovascularfitness test
in minority obese youth
Florida International University Department of Dietetics and Nutrition
Major Nutrition Project
Marissa Menendez
Major Professor: Dr. Kathryn Brogan
Statistician: Dr. Angela Tiura
December 5, 2014

2. 2
Introduction
There is sufficient evidence indicating the need for obesity prevention and treatment
programs in American youth.1,2 In the last thirty years, overall rates of obesity among
adolescents aged 12– 19 years have more than tripled, from 5% to 18%. Rates of obesity are as
high as 21% among non-Hispanic black adolescents.3 Although still unclear, the increased
prevalence in obesity of African American adolescents can be explained, at least partially, by
lower levels of physical activity (PA).1 Additionally, for weight loss programs, physical
activity is a recommended key component to be used in conjunction with dietary and lifestyle
changes.4,5,6
Physical activity can be defined as engaging in bodily movements that increase the heart
rate and breathing difficulty. The Physical Activity Guidelines for Americans recommend
adolescents (12-17 years old) participate in  60 minutes of moderate-to-vigorous intensity PA
per day and most of this time should be spent in aerobic activity. Included within the daily one
hour or more of physical activity, at least three days per week should be vigorous intensity.7
Moderate intensity is objectively defined as 50-70% and vigorous intensity as 70-85% of an
individual’s age predicted heart rate maximum (HR max) value.7
One study utilizing accelerometers to track physical activity in United States youth, found
only 42 % of children are achieving moderate-to-vigorous physical activity levels of 60
minutes 5 days a week, but during adolescence these levels drastically plummet to as low as
8%.8,9 Additionally, results from the Youth Risk Behavior Surveillance reveal a considerably
low prevalence of adolescents engaging in at least 60 minutes of daily physical activity across
the country, ranging from 19.7% - 38.5% with a median of 25.4%.2 Furthermore, physical
activity levels are higher in males (36.6%) compared to females (17.7%) and also higher in

3. 3
white males (37.5%) and females (18.7%) compared to black males (37.2%) and females
(16.0%).2 Furthermore, physical inactivity during adolescence is a strong predictor of sedentary
adulthood.10
Substantial data reveals that participation in moderate to vigorous physical activity can lead
to a variety of physical and mental health benefits in children and adolescents. 4,11,12 These
potential benefits include decreased body mass index (BMI),12,13 body fat percentage,13 waist
circumference12,14 and stress/pain perceptions11 and improved obesity related conditions,12
depressive symptoms,11 sleep patterns,11 physical competence,15 body satisfaction,15
cardiovascular fitness16 and exercise tolerance.16
To ensure that youth are achieving the physical activity recommendations and reaping the
numerous benefits of physical activity, the intensity of exercise needs to be measured.
Intensities of physical activities can be measured objectively and subjectively. A relative,
objective measure of exercise intensity utilizes a heart rate monitor via a chest strap and wrist
watch (optional) to track exercise intensities. 17,18,19 The corresponding percentages of age
predicted heart rate maximum values, moderate-vigorous intensities of 60-80%, can be
regulated individually.17 Rate of perceived exertion (RPE) is a subjective measure of exercise
intensity, commonly using Borg’s 6-20 scale of RPE with 6 identified as no exertion at all and
20 classified as extremely hard/maximal exertion.17 RPE has the potential benefit of safely
facilitating exercise training, by regulating exercise intensities in non-clinical or home-based
settings, which normally lack the capability of monitoring objective exertion (e.g. heart
rate).20,17
Children and adolescents vary widely in their abilities to rate their perceived exertions
during physical activity and therefore may over-or-under-estimate their actual exertion during

4. 4
moderate-to-vigorous PA.21 This discrepancy may have detrimental implications for youth
when implementing physical activity recommendations and self-reporting physical activity.
There are a myriad of variables, which could affect the ability of adolescents to accurately
estimate their physical activity exertion levels including: age, gender, body mass index (BMI),
body fat percentage, waist circumference, presence of co-morbidities and prior exercise
experiences.2,22,23,24
The purpose of this literature review is to explore the literature pertaining to African
American adolescent obesity rates and physical activity levels, compared to other ethnicities.
Secondly, this review will examine regulation of moderate-to-vigorous physical activity in
youth and investigate the variables affecting the relationship between subjective and objective
exertion. The following research questions will be explored:
1. Do African American adolescents have higher obesity rates and lower physical activity
levels compared to other ethnic groups?
2. How is moderate-to-vigorous intensity and rate of perceived exertion regulated in children
and adolescents performing physical activity?
3. Is there a relationship between Borg’s Scale of Rate of Perceived Exertion and heart rate in
adolescents performing physical activity?
4. What variables affect the relationship between subjective exertion (Borg’s Scale of RPE) and
objective exertion (heart rate) in youth and adults performing the Chester step test?
Methodology
This literature review sought to include studies focused on the following topics:
adolescent/minority health status, adolescent obesity (BMI, body fat percentage), adolescent
co-morbidities affecting health, physical activity of adolescents, exercise intensity, adolescent

5. 5
subjective and objective exertion and the Chester step test. This review aimed to include mostly
studies based on adolescents; however children and adult population studies were included if
the available data was inadequate. Adolescence is defined as the age range between 12 to 19
years old.3
The exploration and examination of research was accomplished May 2014 through July 2014
using various databases including: FIU Library E-Journal catalog, ScienceDirect,
Medline/Pubmed and Google Scholar. The following search terms were used to select the
pertinent articles: “adolescent health status/obesity, ” “African American adolescent
health/obesity” OR “minority adolescent health/obesity, ” “African American health
problems/issues,” “adolescent physical activity statistics” OR “physical activity of
adolescents,” “exercise intensity,” “subjective and objective exertion,” “rate of perceived
exertion,” “adolescent subjective and objective exertion,” “adolescent subjective and objective
exertion AND age, gender, BMI, body fat percentage, waist circumference and the presence of
co-morbidities,” and “Chester step test.”
Literature Review
Adolescent Health Status and Obesity
Body mass index and body fat percentage are commonly measured and compared to
normative age and gender specific charts to determine adolescent obesity status. Ogden et. al
used NHANES data from 1999-200 and 2010-2011 to investigate trends in obesity and body
mass index (BMI) in male and female children and adolescents using a large representative
sample, which emphasized a significant increase in obesity in males (2-19 yrs. old) and BMI of
adolescent males, but not in females.3 Two studies and the youth risk behavior surveillance
were reviewed, which focused on adolescent obesity, BMI and body fat percentage.2,25,26 Non-

6. 6
Hispanic white, non-Hispanic black and Mexican American male and female children and
adolescents were included in the large sample size of cross-sectional analyses of NHANES
data.25,26 Age and gender specific body fat percentages and growth curves demonstrate more
value compared to BMI, showing boys body fat peaking at age 11 and girls body fat increasing
throughout adolescence to an average of 17% and 27.8% at 18 years old, respectively.26
Therefore, along with BMI, body fat percentage should also be taken into account when
analyzing obesity status in children and adults.
To evaluate adolescent health status, common indicators for examination include:
abdominal obesity (waist circumference), insulin resistance, blood pressure and triglyceride
levels. Guijarro de Armas et al., utilizing a descriptive study, reported 80% of obese male and
female adolescents were found to have 1 or 2 metabolic syndrome components and 19.6% (1 in
5) had 3 or more components and also were diagnosed with metabolic syndrome. Abdominal
obesity was most the most prevalent metabolic syndrome component, followed by hypertension
and hypertriglyceridemia. Obesity and insulin resistance were significantly higher in
adolescents with more metabolic syndrome criteria.27 Spolidoro et. al focused on the relevance
of waist circumference as an early indicator of overweight, metabolic syndrome and
cardiovascular risk factors, in male and female youth participating in a cohort study. Waist
circumference, strongly correlated with body mass index, and was found to be a useful
screening tool for metabolic syndrome and cardiovascular disease risk in children and
adolescents.28
Minority Adolescent Health and Obesity
African American adolescent males have higher rates of obesity, compared to other ethnic
groups. The Center for Disease Control (CDC) used a 3 stage cluster sample design and school-

7. 7
based youth risk behavior survey to collect data on a very large sample size of male and female
white, black and Hispanic high school students.2 Results showed 13.7% of 9-12th grade high
school students are obese, furthermore the prevalence was highest among males (16.6%)
compared to females (10.8%) and black females (16.7%) compared to Hispanic (11.2%) and
white females (9.7%).2
By the same token, black adolescents are at an increased risk of hypertension, diabetes,
HIV infections and mortality from cardiovascular disease. The CDC Health Disparities and
Inequalities Report, obtained to describe health outcomes in specific population groups, found
hypertension to be most prevalent in non-Hispanic blacks (42%) compared to non-Hispanic
whites (28.8%). Estimated HIV infection diagnoses rates in individuals  13 years old, is
highest among blacks/African Americans compared to other ethnic groups. The age-adjusted
prevalence of medically diagnosed diabetes in people  18 years old is highest among blacks
(11.0), compared to white (7.0) and Hispanic (10.7) individuals. Men have a higher mortality
rate than women attributable to coronary heart disease, additionally, black women and men are
more likely to expire from stroke and heart disease compared to white individuals.29
Analyzing data from NHANES 1999-2010, including 40.9% Non-Hispanic blacks, youth
with physical and psychiatric disabilities were more likely to be obese, less likely to be
physically active and had higher continuous metabolic syndrome scores compared to
adolescents without disabilities. Lower physical activity levels and higher BMI percentile were
associated with higher continuous metabolic syndrome scores in adolescents with disabilities.30
Sarafrazi et al. declares 30% of children and adolescents aged 8–15 years in the United States
misperceive their weight status, which is more common among boys (32.3%) than girls
(28.0%). One third of non-Hispanic black (34.4%) and Mexican-American (34.0%) children

8. 8
and adolescents misperceive their weight status compared with 27.7% non-Hispanic whites.
Seventy-one percent of overweight girls, 81% of overweight boys, 36% of obese girls and 48%
of obese boys regard themselves as being at a proper weight.25 Therefore, both genders of
overweight and obese adolescents have difficulty identifying an appropriate weight for
themselves,25 which could transcend into inaccurate estimations of moderate-to-vigorous
intensity physical activity.
Adolescent Physical Activity and Exercise Intensity
Given that moderate-to-vigorous intensity physical activity levels decrease during
adolescence,2,8,9 it is important to examine the physical activity patterns and associated
intensities of exercise in this age group, to gain further understanding of the possible benefits
and barriers to achieving the daily recommendations. Three studies and the CDC youth risk
behavior surveillance were reviewed to explore adolescent physical activity and exercise
intensity.2,11,15,16 All three studies included males and females11,15,16 with ages ranges from 18-
22,5 15-18,15 and 13-1716 years old and small (42, 36)11,16 to medium sample sizes (551).15
None of the studies occurred in the United States, but instead in Switzerland,11 Poland15 and
Brazil.16 Two studies investigated the physical and mental health benefits of vigorous physical
activity in normal weight young adults,11,15 one utilizing a cross-sectional analysis11 and the
other a longitudinal prospective design.15 The third study, a randomized controlled design,
sought to evaluate the effects of a 12 week aerobic physical exercise program on
cardiorespiratory and metabolic responses in overweight adolescents using a submaximal cycle
ergometer incremental test.16
Two studies investigated the benefits of vigorous physical activity,11,15 with one asserting
that participants performing additional vigorous intensity exercise three times per week for 20

9. 9
minutes perceive less stress, experience fewer depressive symptoms, report less pain, suffer
from fewer subjective sleep complaints and spend a higher percentage of time in REM sleep.11
The second study established that leisure time vigorous physical activity improved lung
function in late adolescent females and late adolescent males have higher levels of physical
competence, general appearance evaluation and body satisfaction, which predicted vigorous
physical activity.15 Silva et al. deduced that exercise performed at lactate threshold (LT) and
onset of blood lactate accumulation (OBLA) training intensities (heavy domain) prompted
significant changes in the aerobic and metabolic (HR improvement) capacities of overweight
adolescents, improving their exercise tolerance.16
The Center for Disease Control (CDC) analyzed the youth risk behavior surveillance and
reported 15.2% of the 9-12th grade students do not participate in at least one day of physical
activity for 60 minutes. The prevalence of having been physically active at least 60 minutes per
day on five or more days was higher among older age groups (12th grade), amongst white
(50.1%) than black (41.0%) and Hispanic (44.7%) students, higher among white female
(40.5%) and Hispanic female (35.4%) than black female (29.3%) students, and higher among
white males (59.6%) than black (53.3%) and Hispanic males (54.4%).2 With these studies
taken together, although normal weight adolescents participate in physical activity more often
than their over weight peers, both genders regardless of weight status can acquire substantial
benefits from moderate-to-vigorous intensity physical activity.
Adolescent Subjective and Objective Exertion
There is limited research investigating the regulation of subjective and objective exertion in
United States adolescents, coupled with a lack of studies explicitly analyzing exertion levels in
African American youth. Additionally, non-Hispanic black adolescents are more likely to

10. 10
misperceive their weight status,25 which could translate into an increased probability of them
over-or-under estimating their physical activity exertion levels. Five studies were examined to
assess adolescent perceived and objective exertion. Four of the studies included children and
adolescents with ages ranging from 8-1821,2212-1318 and 8-12 years old,23 while one study
included only children aged 9-11 years old.19 All of the studies included males and females, but
resided in various locations including Canada,21,22 Australia,18 Hong Kong19 and Buffalo, New
York.23 Four studies had a small sample size of 79,21,22 37,18 3223 and one study had a medium
sample size of 21019 youth. Two of the studies utilized the Dalhousie Dyspnea/Perceived
Exertion scales as well as the Borg CR-10 scale during incremental cycle ergometer testing of
youth who are healthy and those with asthma and cystic fibrosis.21,22 Two studies used heart
rate biofeedback via Polar heart rate monitors in physical education classes18,19 to evaluate
children’s ability to identify time spent in moderate to vigorous physical activity18 and to
investigate if the heart rate biofeedback promotes an increase in physical activity.19 One study
used Cart and Load Effort Rating RPE scale and heart rate monitoring during continuous cycle
ergometer exercise below and above ventilatory threshold to assess the validity of this scale on
separate exercise days.23
Two studies utilized the Dalhousie Dyspnea and Perceived Exertion and Borg CR-10
scales.21,22 One confirmed good correlations in both scales in perceived leg exertion versus
work and dyspnea versus ventilation, along with children preferring the Dalhousie pictorial
scale compared to Borg’s scale to rate leg exertion and dyspnea.21 In the second study, children
demonstrated a wide range of variation in their ability to rate their perceived exertion,
exhibiting diverse functional relationships between work capacity and rate of perceived
exertion, while younger children generally having lower RPE ratings compared to older

11. 11
children.22 Two studies utilizing HR monitors for biofeedback found contrasting results.18,19
Conley et al. claims HR biofeedback did not improve children’s ability to identify time spent in
moderate to vigorous physical activity,18 while McManus et al. concluded heart-rate monitor
feedback increased overall activity and percentage of time spent in vigorous physical activity,
although this increase was not maintained long-term after biofeedback removal.19 Barkley and
Roemmich found boys to have a higher VO2 peak than girls and observed a moderate
relationship between HR and CALER RPE (r=0.30), hence the RPE ratings increased with
exercise intensities, demonstrating a positive association with heart rate.23 Taken together,
these studies reveal that children and adolescents struggle to accurately identify and regulate
their time spent in moderate and vigorous physical activity, regardless of heart biofeedback and
subjective exertion scale.
Chester Step Test
There is a lack of research evaluating the Chester step test parameters in adolescents. Adults
have repeatedly been selected as the population of choice in Chester step test studies, therefore,
uncertainty still exists regarding the variables that affect the ability of children and adolescents
to accurately rate their perceived exertion and its relationship to heart rate values. Four studies
were reviewed to obtain suitable Chester step test information.12,13,33,34 All four studies included
a male and female adult population with mean ages 23,31 22.4,17 69.9,24 30.6.14 years old.
Seventeen year old university students were included in two studies17,31 and 18 year old
adolescents were included in three studies.17,14,31 Mean BMI values included normal and
overweight ranges: 23.3,17 24.7,14 25.9.24 Three studies took place in the United Kingdom17,14,31
and one in Brazil.24 The Chester step test protocols slightly varied in all four studies,17,14,31,24
with only one study analyzing the effects of static and passive arm actions.31 Three studies

12. 12
initiated Chester step test stage 1 at 15 steps/minute (0.30 cm step height), increased 5
steps/minute at the end of each 2 minute (up to 5 stages)31,17 and terminated the test at 80% HR
max or RPE of 14 (Borg’s 6-20)33 and 80% HR max and RPE of 15 (Borg’s 6-20).17,14 Another
study in COPD patients utilized the standard 5 stage Chester step test protocol with a 20 cm
step and a modified Borg’s scale, which terminated the test either by the patient (because of leg
fatigue and/or dyspnea) or by the physiotherapist as a result of the patient’s inability to
maintain the prescribed cadence for 15 seconds.24
Elliott et al. analyzed Chester step test arm movements, finding that although active arm
action lead to a seven beats per minute (bpm) HR increase across all Chester step test stages, it
did not significantly impact the predicted VO2 max.31 Buckley et al. results show age estimated
HR max significantly overestimated actual HR max of five bpm and the RPE and % HR max
(actual) correlation improved with a second Chester step test trial. At stage I, the average RPE
was 9 (57% HR Max) and RPE increased with each successive stage, elevating to an RPE of 14
(81% HR Max) by stage IV. At all Chester step test stages in trial 2, RPE:% HR max
coefficients were significant with the highest correlations at Chester step test stages III (r =
0.78) and IV (r=0.84).17 Sykes et al. found the Chester step test duration spanned four to ten
minutes, dependent on individual fitness levels of the adults. Several of the fitter participants
were able to successfully complete all five stages, whereas those less fit only completed two
stages and had to stop the Chester step test because their heart rate reached the 80% age
predicted maximum.14
A third study in overweight COPD patients showed that the Chester step test is significantly
correlated with FEV1 (lung function) 6-min walk distance, peak work load during cycling
ergometry, and number of steps and peak heart rate (r=0.55). Similar results were found

13. 13
between Chester step trials for HR and SpO2 (breathing efficiency and blood transport) at each
stage and at peak exercise. Ninety-seven percent (thirty-one) of the older adults completed stage
I, 59% (nineteen) completed stage II, 22% (seven) completed stage III and only one adult
completed stage IV and the first minute of the final stage V. Thirty-eight percent of the older
adults had their test interrupted because of they were unable to maintain the cadence and 63%
asked to stop the test as a result of dyspnea and leg fatigue. Hence, the Chester step test is
reproducible in COPD patients but a reduction in the workload and initial cadence of the test is
necessary.24 Among males and females of all adult age groups and fitness levels, the Chester
step test accurately predicts aerobic capacity (VO2 max), demonstrating a high correlation and
good test-retest repeatability.14
Summary of Evidence/Significance
Although recent data indicates over 18% of adolescents (12-19 years old) are obese,3 over
nine million children and adolescents misperceive their weight status which is most common
amongst boys, non-Hispanic blacks, overweight, obese and low-income youth.25 On the whole,
weight management interventions including a combination of physical activity, nutrition
education and behavior counseling have achieved successful outcomes in overweight and obese
adolescents,13,32 with early treatment intervention further improving success.6
Overall, the prevalence of participation in the recommended 60 minutes of daily physical
activity is higher in males, white ethnicity and at older ages.2 Moderate-to-vigorous intensity
physical activity can potentially decrease BMI,12,13 body fat percentage,13 waist
circumference,12,13 amidst improving cardiovascular fitness,16 exercise tolerance16 and obesity
related conditions such as hypertension,12 hypertriglyceridemia,12 impaired glucose tolerance12
and sleep apnea5. Heart rate-RPE data taken during the Chester step test reliably represents

14. 14
relative exercise intensity (%VO2max) for males and females of all age groups and fitness
levels,17,14 demonstrating most accuracy when intensities are >65% HR max or >50% VO2 max
and a practice trial of the Chester step test is performed first.17 Children and adolescents
demonstrate a large span of variation in their abilities to rate their perceived exertions during
exercise.22 Identifying time spent in moderate-to-vigorous physical activity remains a complex
task for children and adolescents, even with personalized biofeedback from heart rate
monitors.18,19 Many children and adolescents lack the prior experiences and PA perceptions to
accurately gauge the varying amounts of perceived exertion at different intensities of
exercise.22
Strengths of this literature review include: representation of a broad range of ethnicities from
different parts of the world, together with data on males, females and adolescents of different
ages, fitness levels and health statuses. This review does have several limitations. Firstly, broad
age ranges of youth and adults,21,14,22 limits the generalization of findings to all adolescents 12-
16 years old. The data are limited by the nature of the self-reporting of physical activity as well
as surveys2 and questionnaires5 used in several studies. Small sample sizes were also prevalent.
11,16,17,31 Difficulty in obtaining accurate skin fold measurements in obese individuals possibly
led to body fat percentage and composition calculation errors.26 Lastly, the Chester step test
studies varied the test protocols, did not include any African Americans or adolescents/children
younger than 17 years old, or a specific obese/overweight population,17,14,31,24 which restricts
the general applicability of the findings.
The purpose of the ensuing study is to investigate the relationship between subjective and
objective exertion during the Chester step test in African American adolescents with obesity
(AAAO). The information generated from this study will enhance the understanding of the

15. 15
ability of adolescents to closely correspond their daily physical activities with moderate-to-
vigorous exercise intensities using Borg’s 6-20 rate of perceived exertion scale. Adolescents
who are able to successfully associate their subjective and objective exertion may be better able
to properly regulate their exercise intensities during various physical activities and effectively
achieve the physical activity recommendations. Nutrition professionals have the responsibility
to assist youth in accurately identifying MVPA and closely matching subjective and objective
exertion, to successfully overcome this barrier to achieving physical activity goals.33 Registered
dietitians (RDs) and dietetic technicians registered (DTRs) are in need of adequate
training/skills for the challenges of child-obesity epidemic: assessment of body size,
nutrition/dietary concerns, knowledge of weight management strategies and PA
recommendations.34
Below are the specific aims and hypotheses for the study.
Specific Aim 1: To describe the subjective exertion (Borg’s Scale of RPE) and objective
exertion (heart rate) in AAAO performing the Chester step test.
Specific Aim 2: To investigate the relationship between subjective exertion (Borg’s Scale of
RPE) and objective exertion (heart rate) in AAAO performing the Chester step test.
Hypothesis 2: A weak relationship exists between subjective exertion and objective exertion in
AAAO performing the Chester Step test.
Specific Aim 3: To examine the effects of the age, gender, weight, BMI, body fat percentage,
waist circumference and the presence of co-morbidities, on subjective exertion (Borg’s Scale of
RPE) and objective exertion (heart rate) in AAAO performing the Chester step test.

16. 16
Hypothesis 3: Older youth, males, and youth with lower BMI, body fat percentage, waist
circumference and fewer co-morbidities, will have a stronger relationship between subjective
and objective exertion during the Chester step test.
Methods
Parent Study
A secondary analysis was completed using data from the FIT Families Project: Interventionist
Procedures for Adherence to Weight Loss Recommendations in Black Adolescents Phase 2.
This study utilized nutrition, physical activity and behavioral interventions over a seven month
program duration with the purpose of refining intervention protocols to maximize AAAO and
family adherence to recommendations for behavior changes in eating and physical activity.35
All data in the parent study was de-identified and was provided to the investigator in a
password encrypted flash drive in an excel database. The data had been previously collected
and is reported with patient IDs (PIDs) to ensure confidentiality.35 The investigator had no
knowledge of the participants’ identities. The Institutional Review Board at Florida
International University approved the progression of this study on July 11, 2014.
Participants
One hundred and eighty-one African American obese adolescents and their caregivers,
residing in Detroit, Michigan participated in the parent study. Obesity was defined as a BMI 
95th percentile for age and gender. Informed consent and youth assent was obtained before the
initiation of the study. At baseline, data were collected via questionnaires, anthropometrics were
measured and the participating adolescents performed a Chester step test to assess their
cardiovascular fitness.35

17. 17
Chester step test
All baseline Chester step tests were completed in the adolescents’ homes.40 The Chester step
test comprised five levels/stages of two-minute intervals, utilizing guided verbal instructions and
a pre-recorded metronome tempo that began at 15 steps/minute and increased five steps/minute
with each successive stage increase.17,14,35 Materials needed for the Chester step test included:
30cm step, iPod, external speaker, RPE Scale, ePulse Heart Rate Monitor and data
collection/results sheet. In preparation for the Chester step test, the participant’s name and age
was written on the sheet. Using the formula, 220 – age in years, the HR max and 80% HR max
were calculated:
Age 12: HR max = 208 bpm; 80% HR max = 166 bpm; Age 13: HR max = 207 bpm; 80% HR
max = 166 bpm; Age 14: HR max = 206 bpm; 80% HR max = 165 bpm; Age 15: HR max = 205
bpm; 80% HR max = 164 bpm; Age 16: HR max = 204 bpm; 80% HR max = 163 bpm.
These values were entered at the top of the graph sheet and two horizontal lines were drawn on
the graph to illustrate the values. Prior to setting up the step test equipment, the research
associate asked the adolescent where he/she would be most comfortable performing the step
test. It was recommended that the Chester step test be completed in an area with minimal
distractions and interruptions from other family members that may be in the home.35
The research associate first explained the posted Borg’s 6-20 Rate of Perceived Exertion
scale to the adolescent. A rating of 6-8 indicates “very, very light exertion,” 9-10 “very light,”
11-12 “fairly light,” 13-14 “moderately hard,” 15-16 “hard,” 17-18 “very hard,” 19 “very, very
hard,” and 20 signifying “exhaustion.” Next, the adolescent was assisted in placing the ePulse
heart rate monitor in the appropriate area. The strap was looped through the buckle, around the
arm and back on itself; then tightened to fit snug. Since the ePulse was designed to be worn on

18. 18
either forearm, the research associate placed it on whichever forearm allows him/her to read the
display easily. The display was placed on the inner forearm and the sensor on the upper outer
arm. The ePulse was clicked on and the adolescent sat quietly for 15-20 seconds until a blue
light came on at the bottom of the display. This light indicated that ePulse had locked onto the
heart rate and the adolescent can begin activity. The baseline heart rate was recorded on the
data collection sheet before the adolescent began stepping.35
The Chester step test stepping technique (whole foot should be firmly placed on the 30
cm step and the leg should be fully straightened) was demonstrated and explained before the
start of the test. The adolescent was informed that he/she could change their lead leg. It was
explained that the first rate is very slow and controlled and they should attempt to keep the
correct rhythm as the tempo increases. The CD was turned on and the adolescent was asked to
listen to the instructions. After the first stage, the heart rate displayed on the ePulse was
recorded and also the vocalized rate of perceived exertion from the adolescent. A mean stable
heart rate value was recorded during the last few seconds of each level, as well as the rate of
perceived exertion. Providing the heart rate was below 80% HR Max and RPE below 14, the
adolescent continued on to the next stage. The test continued until the target 80% HR max was
reached or exceeded and/or the adolescent reported an RPE of 14 (moderately hard).35
Statistical Analysis
The secondary analysis of this study used only baseline Chester step test data from the parent
study for 178 adolescents. Three adolescents were excluded from the analysis due to missing
data. All of the statistical analyses were performed with SPSS version 21.0 software and
statistical significance was set at p  0.05. The Chester step test variables obtained and

19. 19
analyzed included: fitness rating, aerobic capacity (mlO2/kg/min) level completed, heart rate at
completed step level and rate of perceived exertion at completed step level.
Graphical analysis was used to obtain the aerobic capacity and fitness rating of the
adolescents performing the Chester step test. First, the heart rate at each of the completed level
levels was plotted on a graph and a line was drawn to best fit the data points. The line was
further extended to cross the adolescent’s HR max for their age. A vertical line was dropped
down from this intersection to the correlated predicted aerobic capacity. The norms for aerobic
capacity table, for gender and age, was used to classify the predicted aerobic capacity by
matching it to the corresponding fitness rating category including: excellent (1), good (2),
average (3), below average (4), poor (5).35
Data were checked for normality using histogram plots and all data on participant
characteristics were normally distributed except for heart rate at completed step level was
skewed to the right towards higher heart rate values. Descriptive statistics (minimum,
maximum range, mean, standard deviation) were employed to describe variables of the sample
population including: age, gender, weight, BMI, waist circumference, presence of co-
morbidities and body fat percentage. In addition, skewness and kurtosis were used in
conjunction with the descriptive statistics to describe objective (heart rate) and subjective
exertion (RPE) for adolescents who reached each stage. Frequency distributions were also
utilized to examine the causes for stopping the Chester step test at different levels and among
various ages.
Linear regression and one-way analysis of covariance (ANOVA) analyzed the relationship
between HR and RPE and obtained the overall significance between objective and subjective
exertion. The independent variable (predictor) was HR value at completed step level and the

20. 20
dependent variable (outcome) was RPE at completed step level. Multiple linear regression and
ANOVA were conducted to examine the interaction effects of the moderator variables age,
gender, BMI, waist circumference, presence of co-morbidities and body fat percentage, on HR
(objective exertion) and RPE (subjective exertion) at completed step level. RPE at completed
step level was labeled as the dependent variable and the independent variables were comprised
of the HR at completed step level combined with: age, gender, BMI, waist circumference,
presence of co-morbidities and body fat percentage (moderator variableXHR). Standardized
regression coefficients (Beta) were used to compare the relative strengths of the predictor
(independent) and outcome variables (dependent) in the regression model, examining which
independent variables (HRXmoderator variables) had a significant effect on the dependent
variable (RPE). The simple slopes test, with 2 way standardized plot form, deciphered the
variations in the relationship between body fat percentage, HR and RPE.
Results
Descriptive statistics
One hundred and eighty-one African American adolescents, 122 (67.4%) girls and 59 (32.6%)
boys, were initially enrolled in the parent study, FIT Families Project.35 Descriptive statistics
from the 178 youth completing the Chester step test is presented in Table 1.Co-morbidities of
obesity (diagnoses of diabetes, hypertension, asthma and sleep apnea) were found in 49.7% of
the population. On average, the adolescents completed 1.98 (SD = 0.770) of the Chester step test
stages, with their mean heart rate at 157.99 bpm (SD = 17.393) and RPE of 14.69 (SD = 2.051).
The Chester step test was valid, with no reason for concern (M = 1.01, SD = 0.078).

21. 21
Table 1: Descriptive Statistics, Participant Population
n Mean SD Minimum Maximum
Age (years) 181 13.8 1.4 12 16
Average
Weight (lbs)
181 230 51.1 133 451
BMI (kg/m2) 181 38.2 7.5 25.7 60.5
Waist circ.
(in.)
181 43.9 6.5 32.0 66.0
Body fat % 179 48.0 7.3 29.7 65.6
In analyzing the overall frequency of causes for stopping the Chester step test (Figure 1), it
is evident that more than half (54.5%) of the adolescents halted the test as a result of their RPE
being  14 (Borg’s 6-20 RPE scale) and 16.9% of adolescents stopped because their HR reached
 80% of their age predicted HR max. Less than a quarter (23.4%) of adolescents had to stop the
test because their RPE was  14 and heart rate reached 80% of their age predicted HR max,
leaving only 5.1% quitting because of neither heart rate nor RPE. Twelve year olds had the
highest frequency of stopping because of RPE (65.9%) and fifteen year old adolescents had the
lowest frequency of stopping for RPE (43.6%), but the highest frequency for ending because
both their HR and RPE reached the allowable thresholds for the Chester step test. Adolescents at
age fourteen were the group that most frequently terminated the Chester step test as a result of
reaching 80% HR max values (31.3%).

22. 22
Figure 1: Frequency of Causes for Stopping CST at all ages 12-16: Stages/Levels 1-5
Of the 47 (26%) adolescents who stopped the Chester step test at Stage 1, after only two
minutes of stepping, 70% of them halted the test because their RPE reached  14 and 9%
because both HR and RPE reached the designated threshold of 80% HR Max and  14,
respectively. Over half of the 178 participants (n = 93, 52%) terminated the Chester step test at
stage 2, after 4 minutes of stepping, most commonly because of their RPE elevating to  14.
Almost one third of the adolescents (29%) had a HR value and RPE that both matched the
established thresholds for terminating the test. Results indicated only 17% of adolescents had to
stop the test because their HR reached  80% HR Max.
Thirty-three adolescents completed the Chester step test at stage 3, with 55% because of RPE
and 30% because their HR and RPE both reached the cut-off values for test termination. This
left only 12% stopping because of HR and 3% because of neither HR nor RPE. Four adolescents
(ages 13, 14, and two 15 years old) successfully completed stage 4, 8 minutes of stepping. Half
of them stopped because of RPE, leaving one quarter each because of HR reaching  80% HR
max and both HR and RPE reaching termination values. Only one obese adolescent, age 12, was
55%
17%
23%
5%
Frequency of Causes for Stopping
CST at all ages 12-16: Levels 1-5
RPE
HR
Both
Neither

23. 23
able to successfully complete all five stages of the Chester step test. The HR of this adolescent
(169 bpm) surpassed the 80% HR max of 166 bpm but the RPE of 12 remained below the
threshold, signifying a “fairly light” rate of perceived exertion.
The linear regression model summary demonstrates that HR at completed step level
(independent variable) is able to predict 1.8% of the variance in RPE at completed step level
(dependent variable) values (R=0.134, R2=0.018, Adjusted R=0.012). A one standard deviation
increase in HR at completed step level leads to a 0.134 decrease in RPE at completed step level,
although HR is not a statistically significant predictor of RPE (p = 0.075, β = -0.134). (Table 2).
Table 2: Multiple RegressionAnalysis
 SE  t p-value
Constant 17.177 1.4 12.270 0.000
HR at
completed
step level
-0.016 0.009 -0.134 -1.790 0.075
Table 3: ANOVAa
Sum of
Squares
dF Mean Square F p-value
Regression 13.313 1 13.313 3.205 0.075b
Residual 731.069 176 4.154
Total 744.382 177
a. Dependent Variable: RPE Rate of perceived exertion at completed step level
b. Independent Variable (Predictor): HR Heart rate at completed step level (constant)
The ANOVA analysis reveals a trend towards a weak (marginal) relationship exists between
HR at completed step and RPE at completed step level (F(1, 176) = 3.205, p = 0.075) (Table 3).
ANOVA and multiple regression model analysis affirms age, gender, BMI, waist circumference
and presence of co-morbidities do not significantly affect the relationship between HR at

24. 24
completed step level and RPE at completed step level. Body fat was the only variable that
significantly moderates the relationship between HR and RPE at completed step level
(Regression: β = 0.170, p = 0.025; ANOVA: F(3,172) = 3.335, MSE = 13.607, p = 0.021) (Table
14 and Table 15, respectively). A one standard deviation increase in HR at completed step level
interacting with body fat (bodyfatXhr) leads to a 0.170 increase in RPE at completed step level
(β = 0.170) (Table 4).
Table 4: Multiple RegressionModel Summary
Variables R R2 Adjusted
R2
SE  t p-value
Age 0.135 0.018 0.001 2.049 -0.019 -0.246 0.806
Gender 0.144 0.021 0.004 2.047 -0.057 -0.549 0.584
BMI 0.178 0.032 0.015 2.035 0.107 1.359 0.176
Waist
Circumference
0.181 0.033 0.016 2.034 0.087 1.124 0.263
Co-
morbidities
0.150 0.023 0.006 2.045 0.030 0.284 0.777
Body fat % 0.234 0.055 0.038 2.020 0.170 2.255 0.025
The two-way standardized plot and simple slopes test revealed that among adolescents with
higher percent body fat, the higher the actual heart rate, the higher the RPE score (t=2.154, p =
0.033). Conversely, among adolescents with lower percent body fat, the higher the actual heart
rate, the lower the RPE score (t=-2.355, p = 0.020) (Table 5).

25. 25
Table 5: 2-Way Standardized Plot
Discussion
This is the first study to investigate the relationship between subjective and objective exertion
during a cardiovascular fitness test in AAAO. Although the Chester step test of cardiovascular
fitness has only been validated in the adult population,17,14,31,24 it was selected for this study
because of several reasons. In the parent study (FIT Families Project), the baseline Chester step
test of cardiovascular fitness warranted the utilization of a test that was cost effective, portable
and practical, along with being safe to use in the homes of the all of the adolescents. This
research (utilizing a 30 cm step) 35 and several other studies confirmed that the Chester step
test, with options of 15, 20, 25 or 30 cm steps, can be adapted to suit people with a wide range
of ages, abilities and conditions; providing an easily standardized and safely controlled tool to
assess aerobic fitness under a range of intensities below maximum heart rate values. 17,14,31,24
In previous studies, Borg’s 6-20 rate of perceived exertion scale has been frequently
implemented, in conjunction with age predicted heart rate maximum values, as a subjective
measure of rating perceived pain, fatigue and effort during the Chester step test,21,17,14,31 but the
16
16.2
16.4
16.6
16.8
17
17.2
17.4
17.6
17.8
18
Low HR High HR
RPE
Low % Body Fat
High % Body
Fat

26. 26
populations only included adults  18 years old. A few studies with children have used other
subjective measures of assessing exercise exertion including: Borg’s CR-10 scale,21 Dalhousie
Dyspnea pictorial scales21 and CALER RPE scale.23 The CALER RPE scale was found to be a
valid indictor of the exercise intensities of 8-12 year old children on separate cycle ergometer
sessions.23 Additionally, although Borg’s CR-10 and Dalhousie Dyspnea scales resulted in
parallel subjective ratings in both children and adolescents with cystic fibrosis or asthma, the
youth preferred the Dalhousie pictorial scales.21 After taking these previous studies into
account, it is evident that although Borg’s scale of RPE has been the most extensively utilized
and studied subjective rating scale for the Chester step test, although other scales may be more
effective in grasping the ability of adolescents to accurately estimate their subjective
(perceived) exertion levels by adding correlating pictures.21,23,31,24
In accordance with Buckley et al. and Elliott et al., this study designated the Chester step
test termination cut-off values at 80% HR max and RPE of 14,35,17,23while one other Chester
step test study implemented values of 80% HR max and RPE of 15,14 which may more closely
correlate to a “moderately hard” perceived exertion in the adolescent population.
The results from this study indicated a trend towards a weak (marginal) relationship
(F=3.205, p = 0.075, Beta = -0.134) between subjective and objective exertion during the
Chester step test in AAAO. In concurrence with other studies on youth performing
cardiovascular fitness tests, this study demonstrated that adolescents vary in their capacity to
closely correlate their rate of perceived exertion (Borg’s 6-20 RPE scale) and their objective
exertion when performing the Chester step test.21,22,23 Less than 25% of the 178 total
participants in this study, terminated the Chester step test because they reached BOTH ≥ 80%
HR Max and RPE ≥14. This population is more likely to over estimate than underestimate their

27. 27
exertion levels during the Chester step test. The 15 year-old adolescents were the age group
with the highest percentage reaching their cut-off 80% HR max and RPE 14, but this did not
signify enhanced cardiovascular fitness or progression to advanced Chester step test stages,
compared to other age groups.
For children and adolescents, the complexity of rating their perceived exertions in
accordance with their objective exertions, could involve a multitude of factors. Although the
African American adolescent population has the highest prevalence of obesity compared to
other ethnicities and age groups, the youth risk factor behavior surveillance also reveals that
physical activity, of 60 minutes five or more days a week, is lowest in this population group,
comparatively.2 Therefore, the adolescents in this study likely lack adequate prior experiences
of physical activity and perceptions of various exercise intensities. Unfortunately, this gap
could lead to the inability of AAAO to identify time spent in moderate-to-vigorous intensity
physical activities and self-regulate their exercise intensities when participating in different
physical activities varying in type and duration.21,18,22
The Chester step test protocol in this study was valid, leaving no reason for concern. Sykes
and Roberts found that a single Chester step test can give a valid estimate of aerobic fitness
level in males and females of varied ages, but it is not recommended to obtain exact measures
of aerobic capacity.14 Similary, Buckley et al. confirmed the HR and RPE attained during the
Chester step test are valid and reliable representations of relative exercise intensity, but this
only holds true at intensities >50% HR Max or >65% VO2 max and following a practice
Chester step test trial.17 Although Alves de Camargo et al. found the Chester step test to be
reproducible on separate occasions, it was very short in duration (2 stages), hence the initial
cadence and progressive steps increments in each stage seemed to be too extensive for the

28. 28
COPD patients.24 The mean age (13.8 years) of the participants in this study was substantially
younger and mean BMI (38.2 kg/m2) significantly higher than the participants in the
comparable studies employing the Chester step test, which makes it challenging to directly
compare the results of this study in AAAO to other Chester step test results.
Furthermore, 26% (47) of the adolescents in this study only completed stage 1 (2 minutes)
of the Chester step test, compared to 97% of older adults with COPD.24 Comparatively, only
2% (4) of total population of obese adolescents in this study (n=178) were able to successfully
proceed to Chester step test stage 4 and only one person completed stage 5, similar to only one
(3%) COPD patient proceeding past stage 3.24 Research evidence reveals that normal weight
adults are able to progress further through the Chester step test stages,17,14 unlike the AAAO
(n=140, 79%) in this study who had considerable difficulty moving past only four minutes of
stepping (stage 2), similar to overweight COPD patients.24 Taken together, regardless of
normal, overweight or obese weight statuses, individuals with enhanced cardiovascular fitness
are generally more equipped to exercise for a longer duration during the Chester step test.
It was hypothesized that the moderator variables age, gender, BMI, body fat percentage and
waist circumference would affect the relationship between subjective and objective exertion in
AAAO performing the Chester step test at baseline. As a result of statistical significance
lacking, this hypothesis is rejected for age, gender, BMI, waist circumference and presence of
co-morbidities. Although results of the youth risk factor surveillance reveal that the prevalence
of  60 minutes of physical activity on at least five days/week is higher among adolescent boys
compared to girls and of younger high school students (9th and 10th grade),2 the results of this
study did not support this information. Taking into account that NHANES, National Youth
Fitness Survey 2012 and the youth risk factor behavior surveillance results revealing that obese

29. 29
boys and girls were less physically active overall and our study’s participants having BMI and
waist circumference means both  95th percentile on CDC growth charts, it was hypothesized
that these two obesity criteria would affect the relationship between HR and RPE at completed
step level. Contrary to our hypothesis, BMI and waist circumference did not affect the
relationship between subjective and objective exertions.
Body fat percentage (95th percentile) was in fact the only variable to moderate the
relationship between HR at completed step level and RPE at completed step level. Results of
this study demonstrated that amidst adolescents with higher body fat percentage, as their actual
heart rate increased, their RPE value also increased. Conversely, among adolescents with lower
body fat percentages, as their actual heart rate continued to increase, their RPE values
decreased. There is a lack of evidence-based research investigating the effect of body fat
percentage on the relationship between HR and RPE, and no studies have yet examined this
relationship in the Chester step test of cardiovascular fitness. In a study with healthy young
adults, Buckley et al. demonstrated that different training statuses of the participants could
affect the HR and RPE relationship.17 One possible explanation of these results could relate to
fitness levels and prior physical activity experiences of the adolescents. Those who have a
substantial amount of experiences with exercise and elevated cardiovascular fitness, some
exhibiting an obese BMI but lower body fat percentages as in this study, might be more likely
to continue stepping to achieve a greater proportion of their HR max and be able to effectively
counter the simultaneous increase in RPE parallel to HR, with increasing workload. By the
same token, in a study investigating subjective exertion (RPE) in obese adults, Gondoni et al.,
reported that Borg’s RPE scale was negatively correlated to exercise intensity (METs) and
duration of exercise leading to an estimated 20% overestimation of exertion intensity.36

30. 30
As additional limitations to this study, it is important to keep in mind the specific study
population of adolescents with obesity of African American descent in Detroit, Michigan area,
lacking a control group to compare HR and RPE values of the Chester step test. Therefore, the
results of the study can only be generalized to AAAO. Furthermore, the nature of the secondary
analysis of the Chester step test baseline data from the parent study did not allow a direct
interaction with the study participants. For these reasons, causal relationships between the
moderator variables, (age, gender, BMI, waist circumference, presence of co-morbidities and
body fat percentage) HR and RPE at completed CST levels, cannot be established.
The unfamiliarity with Chester step test at baseline, without a trial run, could have resulted
in adolescents ineffectively rating their perceived exertion. Other possible sources of error in
the Chester step test which could have affected the study results include: prediction of HR Max
from the formula 220-age,14 inaccurate reading14 and recording of HR,14 variance in
active/passive arm movements31 and the adolescents’ abilities to maintain the correct stepping
tempo and technique.14 An existing limitation of this study is the insufficient data on the
medications that the adolescents in this study were taking. Medications such as beta blockers
could prevent the heart from increasing at the same rate as the exercise intensity, possibly
leading to higher RPE numbers reported, incongruent to lower heart rate values at the same
workload.37
Conclusions
The Chester step test provided a valid and reliable tool that proved to be a portable, cost-
effective and easily standardized measure of assessing the cardiovascular fitness of adolescents
with obesity, under a range of intensities below maximum values, in the home setting. The
AAAO in this study varied in their capacity to closely correlate their rates of perceived exertion

31. 31
(subjective) and heart rate values (objective). Over 50% of the adolescents in this study
terminated the Chester step test because their RPE reached the allowable threshold (14) even
though their heart rate was below the 80% HR max cut-off value. Therefore, the AAAO were
more likely to over estimate than underestimate their exertion levels during the Chester step
test. Moreover, it is consistent with other research, that the adolescents in this study would have
increasing difficulty conceptualizing a moderately hard (Borg’s 13-14) level of perceived
exertion with a minimal foundation of physical activity experiences, which could help to
explain the overall overestimation of exercise exertion during Chester step test stages 1-4, in all
age groups (12-16 yrs.). As previously hypothesized, the study results indicated that HR and
RPE at completed Chester step test level were marginally related (weak) and body fat
percentage was the only variable to significantly moderate this relationship. Adolescents need
to be well trained to identify their exercise intensities to appropriately self-regulate their PA to
achieve recommended guidelines of ≥ 60 minutes of MVPA daily, including VPA ≥ 3 days per
week.7
Implications for Dietetic Practice
Weight management interventions combining physical activity, dietary intake/nutrition
education, behavior counseling and caregiver engagement have achieved successful outcomes
in overweight and obese adolescents.13,32,34 Nutrition professionals have the active role and
responsibility to utilize nutrition and physical activity recommendations to promote and
maintain optimum health throughout the lifecycle. As outlined in the Academy of Nutrition and
Dietetics recent position practice paper, registered dietitians are leaders in research and practice
in chronic disease prevention and health promotion. In dietetic practice, RDs and DTRs should
be providing updated physical activity knowledge and appropriate skills according to national

32. 32
physical activity guidelines for individuals of various age groups, health statuses and cultures.34
Future Research
Of utmost importance is to investigate the PA knowledge/skills of nutrition professionals
and implementation strategies of the youth physical activity recommendations (e.g. utilization
of the AND PA toolkit for RDs). Effective, culturally targeted, lifestyle interventions and long-
term training programs for adolescents with obesity that combine physical exercise, nutrition
education and behavior therapy are recommended, but few have been fully implemented and
evaluated to assess their success in weight management and other positive outcomes.38
Furthermore, studies with culturally targeted long-term interventions, especially in the
disproportionally affected groups of youth,38 are needed to examine the key components to
successfully transition from HR mediated feedback to self-regulation of varying exercise
intensities.19 Taken that research has shown youth to prefer pictorial perceived exertion scales
versus number and corresponding description scales, future studies should investigate the
validity and efficacy of Dalhousie pictorial scales in children and adolescents of various ethnic
groups.21
Future studies should focus on assessing the heart rate-RPE reliability and transferability to
various modes of activity.17 Similarly, this is especially true for the African American youth
who are overweight and obese, as there is a lack of evidenced-based literature measuring heart
rate and RPE for different types and intensities of exercise. Additional research should
investigate the effects of age, gender, BMI, waist circumference, co-morbidities, body fat
percentage and prior exercise experiences on RPE and HR during different physical activities
in youth.

33. 33
References
1. Baskin ML, Ahluwalia HK, Resnicow K. Obesity intervention among African-American
children and adolescents. Pediatr Clin North Am. 2001;48(4):1027-1039.
2. Kann L, Kinchen S, Shanklin SL et al. Youth risk behavior surveillance — United States,
2013. MMWR. 2014;63(4):35-36.
3. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in body mass
index among US children and adolescents. JAMA. 2012;307:483-490.
4. Evans RK, Franco RL, Stern M, et al. Evaluation of a 6-month multi-disciplinary healthy
weight management program targeting urban, overweight adolescents: Effects on physical
fitness, physical activity, and blood lipid profiles. International Journal of Pediatric Obesity.
2009;4:130-133.
5. Naar-King S, Ellis D, Kolmodin K, et al. A randomized pilot study of multisystemic therapy
targeting obesity in African-American adolescents. Journal of Adolescent Health.
2009;45(4):417-419.
6. Baxter KA, Ware RS, Batch JA, Truby H. Predicting success: Factors associated with weight
change in obese youth undertaking a weight management program. Obesity Research &
Clinical Practice. 2013;7(2):e147-e154.
7. Physical Activity Guidelines Advisory Committee: Physical activity guidelines advisory
committee report. U.S. Department of Health and Human Services.
http://www.health.gov/PAGuidelines/Report/pdf/CommitteeReport.pdf. Published 2008.
Accessed June 9, 2014.
8. Physical Activity Guidelines for Americans Midcourse Report Subcommittee of the
President’s Council on Fitness, Sports & Nutrition. Physical Activity Guidelines for Americans
Midcourse Report: Strategies to Increase Physical Activity Among Youth. Washington, DC:
U.S. Department of Health and Human Services, 2012.
http://www.health.gov/paguidelines/midcourse/pag-mid-course-report-final.pdf. Accessed
September 5, 2014.
9. Troiano RP, Berrigan D, Dodd KW, et al. Physical activity in the United States measured by
accelerometer. Med Sci Sports Exerc. 2008;40(1): 181-8.
10. Alfano, CM, Klesges, RC, Murray, DM, Beech, BM, & McClanahan, BS. History of sport
participation in relation to obesity and related health behaviors in women. Preventive Medicine.
2002;34(1):82-89.
11. Gerber M, Brand S, Herrmann C, Colledge F, Holsboer-Trachsler E, Pühse U. Increased
objectively assessed vigorous-intensity exercise is associated with reduced stress, increased
mental health and good objective and subjective sleep in young adults. Physiol Behav.

34. 34
2014;135(0):17-24.
12. Reinehr T, Kleber M, Toschke AM. Lifestyle intervention in obese children is associated
with a decrease of the metabolic syndrome prevalence. Atherosclerosis. 2009;207(1):174-180.
13. Reinehr T, Schaefer A, Winkel K, Finne E, Toschke AM, Kolip P. An effective lifestyle
intervention in overweight children: Findings from a randomized controlled trial on “Obeldicks
light”. Clinical Nutrition. 2010;29(3):331-336.
14. Sykes K, Roberts A. The Chester step test—a simple yet effective tool for the prediction of
aerobic capacity. Physiotherapy. 2004;90(4):183-188.
15. Luszczynska A, Abraham C. Reciprocal relationships between three aspects of physical self-
concept, vigorous physical activity, and lung function: A longitudinal study among late
adolescents. Psychol Sport Exerc. 2012;13(5):640-648.
16. Silva DAS, Petroski EL, Pelegrini A, Guglielmo LGA. Effect of physical exercise on the
cardiorespiratory response in overweight adolescents. Turkish Journal of Endocrinology and
Metabolism. 2012;16:14-18.
17. Buckley JP, Sim J, Eston RG, Hession R, Fox R. Reliability and validity of measures taken
during the chester step test to predict aerobic power and to prescribe aerobic exercise. Br J
Sports Med. 2004;38:197-205.
18. Conley MM, Gastin PB, Brown H, Shaw C. Heart rate biofeedback fails to enhance
children's ability to identify time spent in moderate to vigorous physical activity. Journal of
Science and Medicine in Sport. 2011;14(2):153-158.
19. McManus AM, Masters RSW, Laukkanen RMT, Yu CCW, Sit CHP, Ling FCM. Using
heart-rate feedback to increase physical activity in children. Prev Med. 2008;47(4):402-408.
20. Morris M, Lamb K, Cotterrell D, Buckley J. Predicting maximal oxygen uptake via a
perceptually regulated exercise test (PRET). Journal of Exercise Science & Fitness.
2009;7(2):122-128.
21. Pianosi PT, Huebner M, Zhang Z, McGrath PJ. Dalhousie dyspnea and perceived exertion
scales: Psychophysical properties in children and adolescents. Respiratory Physiology &
Neurobiology. 2014;199(0):34-40.
22. Huebner M, Zhang Z, Therneau T, McGrath P, Pianosi P. Modeling trajectories of perceived
leg exertion during maximal cycle ergometer exercise in children and adolescents. BMC
Medical Research Methodology. 2014;14(4):1-9.
23. Barkley JE, Roemmich JN. Validity of a pediatric RPE scale when different exercise
intensities are completed on separate days. Journal of Exercise Science & Fitness. 2011;9(1):
52-57.

35. 35
24. Alves de Camargo A, Justino T, Silva de Andrade CH, Malaguti C, Dal Corso S. Chester
step test in patients with COPD: Reliability and correlation with pulmonary function test results.
Respiratory Care. 2011;56(7):995-1001.
25. Sarafrazi N, Hughes J, Borrud L, Burt V, Paulose-Ram R. Perception of weight status in
U.S. children and adolescents aged 8–15 years, 2005–2012. NCHS data brief. 2014(158):1-8.
26. Laurson KR, Eisenmann JC, Welk GJ. Body fat percentile curves for U.S. children and
adolescents. Am J Prev Med. 2011;41(4S2):S87-S92.
27. Guijarro de Armas MaG, Monereo Megías S, Merino Viveros M, Iglesias Bolaños P, Vega
Piñero B. Prevalence of metabolic syndrome in a population of obese children and adolescents.
Endocrinología y Nutrición (English Edition). 2012;59(3):155-159.
28. Spolidoro JV, Pitrez Filho ML, Vargas LT, et al. Waist circumference in children and
adolescents correlate with metabolic syndrome and fat deposits in young adults. Clinical
Nutrition. 2013;32(1):93-97.
29. Freidman TR et al. CDC Health Disparities and Inequalities Report – United States 2011.
MMWR. 2011;60(Suppl):1.
30. Kim Y, Conners RT, Hart PD, Kang Y, Kang M. Association of physical activity and body
mass index with metabolic syndrome among US adolescents with disabilities. Disability and
Health Journal. 2013;6(3):253-259.
31. Elliott D, Abt G, Barry T. The effect of an active arm action on heart rate and predicted
VO2max during the Chester step test. Journal of Science and Medicine in Sport. 2008;11(2):
112-115.
32. Covelli MM. Efficacy of a school-based cardiac health promotion intervention program for
African-American adolescents. Applied Nursing Research. 2008;21(4):173-180.
33. Fitzgerald N., Slawson D. Practice paper of the Academy of Nutrition and Dietetics: The
Role of Nutrition is Health Promotion and Chronic Disease Prevention. J Acad Nutr Diet.
2013:1-13.
34. Hoelscher DM, Kirk S, Ritchie L, Cunningham-Sabo L. J Acad Nutr Diet. Position of the
Academy of Nutrition and Dietetics: Interventions for the Prevention and Treatment of Pediatric
Overweight and Obesity. 2013;113(10):1375-1394.
35. Naar-King S, Ellis D, Idalski Carcone A, Templin T, Jacques-Tiura AJ, Brogan K, et al.
Sequential multiple assignment randomized trial (SMART) to construct weight loss interventions
for African American adolescents. Journal of Clinical Child and Adolescent Psychology.
Forthcoming.

36. 36
36. Gondoni LA, Nibbio F, Caetani G, et al. What are we measuring? Considerations on
subjective ratings of perceived exertion in obese patients for exercise prescription in cardiac
rehabilitation programs. International Journal of Cardiology. 2010;140(2):236-238.
37. Tabet JY, Meurin P, Teboul F, et al. Determination of exercise training level in coronary
artery disease patients on β blockers. European Journal of Cardiovascular Prevention &
Rehabilitation. 2008;15(1):67-72.
38. Zoorob R, Buchowski MS, Beech BM, et al. Healthy families study: Design of a childhood
obesity prevention trial for Hispanic families. Contemporary Clinical Trials. 2013;35(2):108-
121.