THE EFFECTS OF A SIX WEEK WALKING INTERVENTION ON
CARDIOMETABOLIC RISK FACTORS AND MENTAL WELLBEING IN EAST
STROUDSBURG UNIVERSITY STUDENTS AND STAFF

By
Natalie R. Turbett, B.S.
East Stroudsburg University of Pennsylvania

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master
of Science in Exercise Science to the office of Graduate and Extended Studies of East
Stroudsburg University of Pennsylvania

August 6, 2021

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ABSTRACT
A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master
of Science in Exercise Science to the office of Graduate and Extended Studies of East
Stroudsburg University of Pennsylvania.
Student’s Name: Natalie R. Turbett, B.S.
Title: The Effects of a Six Week Walking Intervention on Cardiometabolic Risk Factors
and Mental Well Being in East Stroudsburg University of Pennsylvania Students and
Staff
Date of Graduation: August 6, 2021
Thesis Chair: Emily Sauers, Ph.D.
Thesis Member: Shawn Munford, Ph.D.
Thesis Member: Chad Witmer, Ph.D.

Abstract
Less than half of the U.S. adults meet the current exercise recommendations for
cardiorespiratory exercise. Exercise has been shown to positively impact cardiometabolic
risk factors and mental well-being in adults. However, there is currently limited research
on the impacts of a walking intervention on cardiometabolic risk factors and mentalwellbeing. The aim of this study was to investigate the effects of six-week moderateintensity walking intervention on cardiometabolic disease risk factors and mental
wellbeing in East Stroudsburg University students and staff. The participants were
involved in three separate lab sessions to test cardiometabolic risk factors and mentalwellbeing scores. The participants were involved in a six-week walking intervention
prescribed at individual moderate heart rate intensities. Results from the study showed
that there were no significant changes among all the variables tested. Despite these
findings, it is still suggested that adults should obtain 150 minutes of moderate intensity
aerobic exercise per week.

TABLE OF CONTENTS
LIST OF TABLES ........................................................................................................... VI
LIST OF FIGURES ......................................................................................................... VII
Chapter
I.

INTRODUCTION .......................................................................................1
Health Benefits of Regular Exercise and Physical Activity ........................1
The Effect of Exercise and Physical Activity
on Mental-Wellbeing ...................................................................................2
Sedentary Time ............................................................................................3
Purpose of the Study ....................................................................................4
Hypotheses ...................................................................................................4
Operational Definitions ................................................................................5
Limitations and Delimitations......................................................................6

II.

LITERATURE REVIEW ............................................................................8
Cardiometabolic Disease Improvement with Increased Exercise and
Physical Activity and Reduced Sedentary Time ..........................................8
Mental Wellbeing Improvement with Increased Exercise and
Physical Activity .......................................................................................13

IV

III.

METHODOLOGY ...................................................................................18
Subject Recruitment ..................................................................................18
Equipment ..................................................................................................18
Laboratory Data Collection .......................................................................20
Data Analysis .............................................................................................24

IV.

RESULTS .................................................................................................27
Subject Demographics and Subject Dropout .............................................27

V.

DISCUSSION AND CONCLUSION ......................................................41
Subject Compliance ...................................................................................42
Anthropometric Adaptations .....................................................................42
Cardiovascular Adaptations .......................................................................44
Blood Assay Adaptations ...........................................................................46
Mental-Wellbeing Adaptations ..................................................................48
Conclusion .................................................................................................49

APPENDICES .......................................................................................................51
REFERENCES .....................................................................................................59

V

LIST OF TABLES
● Table 1. Intervention Compliance..........................................................................28
● Table 2. Descriptive Statistics
and Significance for Cardiovascular Variables......................................................33
● Table 3. Descriptive statistics and significance
for measured blood assays .....................................................................................34

VI

LIST OF FIGURES
● Figure 1. Methodology Flowchart ........................................................................26
● Figure 2. Body Mass Measurements for the
three laboratory sessions ........................................................................................29
● Figure 3. Body Fat Measurements for the
three laboratory sessions ........................................................................................30
● Figure 4. Body Mass Index measurements for the
three laboratory sessions ........................................................................................31
● Figure 5. Waist and Hip Circumference measurements for the
three laboratory sessions ........................................................................................32
● Figure 6. Generalized Anxiety Disorder Scores ....................................................36
● Figure 7. Perceived Stress Scores ..........................................................................37
● Figure 8. Body Image Scores .................................................................................38
● Figure 9. General Self-Efficacy Scores .................................................................40

VII

CHAPTER I
INTRODUCTION
Health Benefits of Regular Exercise and Physical Activity
Known benefits to regular exercise and increased physical activity for
cardiometabolic disease reduction and improved mental wellbeing are widely accepted.
However, children, adolescents, and adults throughout the United States do not meet the
current recommendations for exercise. According to the Center for Disease Control, 53.5
% of adults aged 18 and older meet the recommendations for aerobic exercise and only
23.2 % meet the aerobic and muscle-strengthening guidelines (Center for Disease
Control, 2020). With less than half of U.S. adults meeting exercise guidelines, there are
concerns about the effects of prolonged sitting time on risk factors and chronic diseases.
Research shows that prolonged sitting time is relevant to being overweight and obese in
children, adolescents, and adults (Mussi et al., 2017).
The health benefits of regular exercise and physical activity are widely known for
all individuals, but benefits are profound for individuals with cardiometabolic risk factors
(Herbert et al., 2020). According to the American College of Sports Medicine (ACSM)
exercise can modify cardiometabolic risk factors resulting in reduced resting and
submaximal exercising heart rate, lowered systolic and diastolic blood pressure during
submaximal exercise and at rest, reduced triglycerides, improved body composition,
1

decreased blood glucose, and increased high-density lipoproteins (American College of
Sports Medicine, 2018). Other benefits to chronic exercise are lower rates of
cardiovascular disease, strokes, type 2 diabetes, and an overall decrease in morbidity and
mortality (American College of Sports Medicine, 2018).
Aerobic exercise (e.g., walking, running, cycling, swimming, treadmill)
frequencies, intensities, and time recommendations for risk reduction were put forth by
the World Health Organization (WHO) and ACSM. Healthy individuals should engage in
150 minutes of moderate-intensity aerobic exercise for 30 minutes per day, for 5 days a
week or 75 minutes of vigorous-intensity aerobic exercise for 20 minutes per day, 3 times
a week (World Health Organization 2010; American College of Sports Medicine, 2018).
The American college of Sports Medicine defines moderate intensity as 40 to 59% of
HRR and vigorous intensity as 60 to 84% of HRR (2018). The recommendations put
forth internationally are recommended to maintain weight, improve cardiovascular
fitness, and reduce weight gain.
The Effect of Exercise and Physical Activity on Mental Wellbeing
The benefits of regular, aerobic exercise extend beyond just physical benefits.
Mental Well-Being is an umbrella term that encompasses psychological, mental,
cognitive, and affective factors that enhance or impair the functioning of a person
(Herbert, et al., 2020). ACSM also states that anxiety and depression are decreased with
regular aerobic exercise (American College of Sports Medicine, 2018). With regular
participation in exercise, self-reported anxiety was decreased independent of gender, age,
and physical health status (Herbert et al., 2020). Perceived psychological stress in both
males and females is also reduced with exercise, although the intensity, type, and

2

duration of exercise are unclear for maximal benefits (Herbert et al., 2020). Self-efficacy
and self-concept are also positively affected by regular exercise participation (Evans et
al., 2017). Body image, defined as the internal representation of a persons’ outer
appearance, is also affected with regular exercise in both males and females (Campbell
and Hausenblas, 2009). Typical interventions for negative body image are cognitive,
behavioral, and educational therapy. These therapies can often be time-consuming and
costly, so exercise is another treatment option for body satisfaction improvement.
Exercise intervention can positively influence body satisfaction in select groups of
people. People that are motivated for fitness and health reasons had low levels of body
dissatisfaction post-exercise sessions (Fuller-Tyszkiewicz et al., 2013). However, higher
rates of body dissatisfaction can be present in people that are appearance and weightmotivated following an exercise session (Fuller-Tyszkiewicz et al., 2013).
Sedentary Time
Despite known benefits to regular exercise and physical activity, increased time
spent sedentary is still a behavior adopted across the lifespan. On average, the American
adult spends approximately 7.7 hours a day sedentary (Ford and Casperson, 2012).
Recent research has suggested that increased time spent sedentary is a health risk,
irrespective of physical activity time (Solbraa et al., 2015). Prolonged sitting time is
associated with increased weight and obesity, BMI, waist circumference, blood pressure,
and cardiovascular morbidity (Mussi et al., 2017; Luke et al., 2011). Increased sedentary
time can be attributed to technological advancements replacing labor-intensive jobs,
increased time spent in automobiles, sedentary occupations, and increased access to smart
devices (televisions, phones, tablets, etc.).

3

University students compromise a unique subgroup within the United States
population where sedentary time is prevalent. Sedentary time is a health issue due to time
spent sitting in classes or while completing academic assignments. College students are
presented with a pivotal time in their life where physical activity and exercise behaviors
are developed (Mussi et al., 2017). Sedentary behaviors adopted in college carry over into
adulthood, increasing the risk of being overweight and obese. Further, a study from 2018
found that University students have increased exposure to screen time and high use of the
internet, exposing students to more sedentary time (Franco et al., 2018). With less than
half of the adult American population meeting exercise guidelines and sedentary time
being harmful to health, promotion of increased exercise and physical activity, as well as
reducing sedentary time for cardiometabolic health and mental wellbeing in college aged
individuals should be investigated.
Purpose of the Study
The aim of this study was to investigate the effects of six-week moderate-intensity
walking intervention on cardiometabolic disease risk factors and mental wellbeing in East
Stroudsburg University Students and Staff.
Hypotheses
It was hypothesized that there would be an improvement in the subjects’
cardiometabolic risk factors and mental well-being following the 6-week walking
intervention. For the anthropometric data it was hypothesized that waist circumference
and hip circumference would reduce significantly, and body fat percentage would reduce
significantly. According to the previous research it is hypothesized that weight and body
mass index would not significantly change. For the cardiovascular variables it was

4

hypothesized that systolic blood pressure and diastolic blood pressure would both
significantly reduce at a resting level, as well as resting heart rate. It was hypothesized for
the blood assays that total cholesterol, low density lipoprotein, triglycerides, and blood
glucose would significantly decrease. For the high-density lipoprotein levels, it was
hypothesized that there would be a significant increase.
For the Mental-Wellbeing scores it was hypothesized that there would be a
significant reduction in Generalized Anxiety Scores and perceived stress scores. General
self-efficacy scores and body image scores were hypothesized to significantly increase.
Operational Definitions
● Anthropometrics: Subject height measured in cm, weight (WT) in kg, body mass
index (BMI) in kg/m2, body fat percentage (BF%), waist circumference (WC) in
cm, and hip circumference (HC) in cm.
● Cardiovascular Risk Factors: Resting heart rate (RHR) measured in bpm, resting
systolic blood pressure (SBP) measured in mmHg, and resting diastolic blood
pressure (DBP) measured in mmHg.
● Blood Assay Risk Factors: Fasted total cholesterol (TC) in mg/dL, low-density
lipoprotein (LDL) in mg/dL, high-density lipoprotein (HDL) in mg/dL,
triglycerides (TG) in mg/dL, and blood glucose (BG) in mg/dL.
● Mental Wellbeing: Subject self-reported stress, anxiety, self-efficacy, and body
image.
o Stress: The Perceived Stress Scale (PSS) is a 10-item scale, 1-4 Likert
Scale utilized to determine perceived psychological stress (Cohen et al.,
1988).

5

o Anxiety: The Generalized Anxiety Disorder (GAD) questionnaire is a
seven-question 0-4 Likert scale used to determine symptoms of GAD
(Spitzer et al., 2006).
o Self-Efficacy: The General Self-Efficacy Scale (GSE) is a 10-item scale
used for self-reported self-efficacy (Schwarzer and Jerusalem, 1995).
o Body Image: The Body Image Questionnaire-NL (DBIQ-NL) is a 37-item
nonclinical Likert scale from 1 to 5 on self-reported body image
(Scheffers et al., 2017).
● Currently Sedentary: Not participating in at least 30 minutes of moderate-intensity
physical activity on at least three days/week for at least three months.
● Currently Active: ACSM recommendations of 150 minutes per week at a
moderate intensity.
● Moderate Intensity: 40 to 59% of heart rate reserve (HRR). Utilize HRmax of
220-age for calculation and RHR from lab assessment.
● Walking Intervention: Six weeks, five times per week, for 30 minutes at 40 to
59% of HRR.
Limitations and Delimitations
The first limitation to this study was the sample size. Only ten subjects were
recruited and nine completed the intervention. If a study were completed in the future
with similar methodology to this one, a larger sample size should be used. In relation to
the sample, the sample was not homogenous, which can be seen through the large
differences in the standard deviations from the anthropometric variables of height and
weight measured. In the future a study should be conducted where the subjects are

6

randomly assigned to a walking intervention where there are no differences in the groups
anthropometric data. Another limitation was that a physical activity screen questionnaire
was not utilized to determine if the subjects were being truthful about their cardiovascular
activity prior to the intervention. The information about the inclusion criteria for physical
activity was included in the initial recruitment process but was not actually screened.
There is a potential that the subjects recruited were already participating in
cardiorespiratory exercise. An assessment which was intended to be utilized in this study
was a baseline data analysis of steps and active time compared to during the intervention.
A baseline data session was unable to be completed due to restrictions for bringing
subjects into the laboratory due to COVID-19 and not getting the fitness trackers shipped
to the university in time for the entire study to be completed by the end of the Spring
2021 semester. Another limitation was some of the assessment tools that were utilized.
BF% was measured using BIA, which can be impacted by hydration status (American
College of Sports Medicine, 2018). The subjects were reminded to hydrate the night
before their lab sessions to ensure they were hydrated, however that does not guarantee
euhydration. In the future, a test that is more valid and reliable should be utilized such as
air displacement plethysmography. Lastly, as seen through the HR compliance in the
sessions, walking may not be advised as a moderate intensity exercise for people aged 40
and younger. Rather, walking can be incorporated into a reduction of sedentary time and
low intensity activity which can contribute to total daily energy expenditure.

7

CHAPTER 2
LITERATURE REVIEW
Cardiometabolic Disease Improvement with Increased Exercise and Physical
Activity and Reduced Sedentary Time
Exercise training impacts cardiometabolic risk factors in males and females over a
broad age range. A study in 2019 conducted a randomized controlled trial on sedentary,
middle-aged adults to determine if exercise training impacted cardiometabolic risk
(Amaro-Gahete et al., 2019). 71 middle-aged males and females (40-65) were randomly
assigned to 4 different treatment groups. The first group was no exercise, the control
group. Subjects were instructed to not change any physical activity or dietary habits for
the 12 weeks. The second group was training based on physical activity
recommendations. Subjects were asked to complete 150 min per week at 60-65% of their
HRR using a cycle ergometer, treadmill, or elliptical ergometer. Participants also
completed two full-body resistance training sessions per week for 60 minutes. The third
group was high intensity interval training (HIIT) where they completed two training
sessions a week. The first training session was a long session of 40-65 minutes per week
at 95% of VO2 max. The second session, the short interval, was circuit-based weight
training circuit where the subjects wanted to reach 6-9 on perceived exertion on a 0-10
scale. The fourth group was HIIT plus whole-body electrostimulation (EMS). The
8

HIIT+EMS group followed the same HIIT procedure but incorporated the EMS training
of 15-20 Hz in the long interval and 35-75 Hz in the short interval. Cardiometabolic risk
scores were calculated for all four groups over the course of the 12-week program.
Weight, BMI, waist circumference, body composition, blood pressure and fasted blood
samples were all measured. The cardiometabolic risk was scored using the International
Diabetes Federation. There was a significant reduction in cardiometabolic risk for all the
groups compared to the control group (Amaro-Gahete et al., 2019). HDL levels
increased, total cholesterol decreased, and blood pressure decreased in the physical
activity group (Amaro-Gahete et al., 2019). Insulin sensitivity was significantly different
from the control group to the physical activity group with sensitivity increasing (AmaroGahete et al., 2019). The group that experienced the greatest reduction in cardiometabolic
risk was the HIIT+EMS group (Amaro-Gahete et al., 2019). As lean body mass
increased, cardiometabolic risk factors decreased (Amaro-Gahete et al., 2019).
HIIT+EMS may be the most effective training for improving cardiometabolic risk
compared to HIIT or physical activity (Amaro-Gahete et al., 2019).
Physical activity volume and intensity are important factors for cardiometabolic
risk for factor reduction. Increased physical activity time is known to improve resting and
submaximal blood pressure, resting and submaximal exercise heart rate, total cholesterol,
and total triglyceride levels (Sumner et al., 2020). Walking-based physical activity can be
an advantage because it is a modality that can be easily incorporated and is widely
available to people (Sumner et al., 2020). To determine the effects of volume and
intensity stepping activity on cardiometabolic risk factors, 2686 people were invited to
take part in an accelerometer-based study in Singapore. Of 2686 invited, 635 completed

9

the study. Participants were male and female with an average age of 48.4 years. Body
mass index (BMI), height and weight, waist circumference, systolic (SBP) and diastolic
blood pressure (DBP), fasted cholesterol, and fasted glucose were all recorded.
Participants had to wear the accelerometer for seven consecutive days for their usual
routine, excluding bathing, sleeping, and swimming. When looking at step volume lower
triglyceride levels were statistically significant (Sumner et al., 2020). Lower BMI, waist
circumference, SBP, and DBP, as well as fasted blood glucose were seen with 30 minute
and 60-minute step cadences (Sumner et al., 2020). Inactive time was statistically
significant with a higher DBP. Overall, the results from the study found that step intensity
was associated with a greater reduction in risk factors compared to step volume (Sumner
et al., 2020).
A reduction in sedentary time may be just as important as increased exercise and
physical activity for all-cause mortality and cardiometabolic health (Mussi et al., 2017).
In 2017 a cross-sectional study was completed by Mussi et al. to identify the sitting time
cutoff point for overweight, obesity, abdominal obesity, and lipid disorders in university
students. The sample was 137 females attending a University in Brazil studying nursing.
Students that participated in the study were approached in a class where the objectives
and procedures were introduced by the researchers. The students voluntarily joined the
study and were evaluated on sitting time, blood assays, and anthropometric
measurements. Time spent seated was recorded using a series of questions that students
responded to with a time. These questions related to activities that are typically spent
seated such as class attendance, academic tasks, time spent on the cellphone, time spent
watching television, etc. The blood assays measured total cholesterol, low-density

10

lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides. Anthropometric
measurements recorded were BMI, weight, waist circumference (WC), and height.
Results from the study showed that 8 hours a day of sedentary time is a discriminator for
abdominal obesity in undergraduate nursing students (Mussi et al., 2017). Sitting time
during the week or weekend was not statistically significant for lipid disorders (Mussi et
al., 2017).
Accumulation of 10,000 steps has become a number that people should aim to
reach every day, which is based on epidemiological studies which report that reaching
10,000 steps a day may reduce SDP and DBP in postmenopausal women (Tully and
Cupples, 2011). However, the effects of reaching 10,000 steps per day in university
students are not as researched. In 2011 a stepping intervention was prescribed to 12
students attending Queen’s University. The participants completed an activity
questionnaire to indicate willingness to participate in the program. Then, seven days
before the trial subjects were allocated randomly into a 10,000 group or a control group.
The measurements of height, body mass, waist and hip circumferences, aerobic fitness,
BP, and HR were obtained pre intervention and post intervention. The intervention was 6
weeks in length. Results from the study found that there were no significant differences
pre-intervention in step count (Tully and Cupples, 2011). All the participants in the
10,000-step group significantly increased their daily step count, with adherence to the
program being 84.8% (Tully and Cupples, 2011). After the six-week intervention, there
was also a significant drop in SBP and DBP (Tully and Cupples, 2011). Data from the
study suggests that pedometer intervention may be suitable in university students to

11

increase step count for modifying later in life cardiovascular risk (Tully and Cupples,
2011).
Walking is a readily accessible mode of moderate intensity physical activity for
almost all population types (Murphy et al., 2002). Current studies demonstrate that
regular walking is associated with a lower risk of coronary events and type 2 diabetes
(Murphy et al., 2002). Long bouts of walking and short bouts of walking can increase
aerobic fitness in obese and overweight populations (Murphy et al., 2002). The purpose
of this study was to determine if short, intermittent bouts of walking could elicit similar
improvements in aerobic fitness, cardiovascular risk, and psychological health. Subjects
in the study were assigned to a crossover design so that each subject would undergo a
long bout and short bout of walking. Each program had the subjects walk at 70 – 80% of
the predicted maximal heart rate for a total of 30 minutes, 5 days a week. In the long bout
program, the subjects completed the 30 minutes in one session while the other short bout
design was 10 minutes of walking separated by > 3 hrs. There was a wash-out period of
two weeks where afterward the subjects switched protocol. Measurements were recorded
at baseline, after the first program, before the second program, and after the second
program. The blood samples were obtained 2 days after each training program. 32
middle-aged subjects were recruited that were sedentary and did not have any known
cardiovascular disease or orthopedic limitations. Waist and hip circumference, skinfold
for body fatness, resting arterial blood pressure, blood samples (HDL and total
cholesterol), and a field walking VO2 max test were completed prior to the interventions
and post interventions. The subject’s mood was assessed, barriers to exercise scale, and
perceived self-efficacy were measured. Results from the study showed that subjects

12

assigned to the short/long intervention undertook more walking, but it was not
statistically significant (Murphy et al., 2002). There were no significant changes in body
mass (Murphy et al., 2002). Body fat percentage, waist, and hip circumference, and
diastolic blood pressure decreased significantly with both programs. Predicted VO2 max
increased significantly with both programs, but subjects in the short/long showed greater
increases (Murphy et al., 2002). Total cholesterol, triglycerides, and HDL concentrations
increased significantly in both interventions (Murphy et al., 2002). There was no
statistical significance in mood state from either program, but subjects did report greater
confidence in walking (Murphy et al., 2002). Perceived barriers to physical activity,
effort, time, obstacles, and health decreased with both programs, but was only significant
for the effort barrier (Murphy et al., 2002). Results from the study showed that
accumulating 30 minutes of brisk walking is effective in increasing aerobic fitness,
improving blood lipid profiles, and enhancing psychological well-being (Murphy et al.,
2002).
Mental Wellbeing Improvement with Increased Exercise and Physical Activity
Exercise can also affect mental wellbeing positively. Mental wellbeing
encompasses self-reported anxiety, perceived psychological stress, self-efficacy, and
body image. A study done in 2020 by Herbert et al., investigated the effects of regular
physical activity on mental wellbeing and a short-term weekly aerobic exercise
intervention for mental wellbeing. The randomized control trial was completed either in a
laboratory or online. There were two groups’ subjects were randomly assigned to: online
pilot study or laboratory study. One group (n=74) had male and female subjects. The
subjects were randomly assigned to an exercise intervention or an expressive writing

13

intervention. In the exercise group, for six weeks the subjects completed a low to
moderate intensity aerobic exercise session two times per week in their own home.
Participants were provided with two exercise programs in the format of videos and tables.
The sessions lasted 16 minutes. For the expressive writing group, the subjects were
prescribed 6 weeks of expressive writing, twice a week. This group also tracked changes
in mental wellbeing. Expressive writing was chosen as the other intervention because of
previous demonstration in studies that expressive writing can be beneficial for mental
wellbeing. The subjects wrote about distressing weekly events for approximately 15
minutes, twice a week. The second group (n=30) was all females, and the subjects
completed the aerobic exercise sessions in a laboratory for 2 weeks. Self-reported
depression, anxiety, perceived stress, body dissatisfaction, and quality of life were
measured. All the participants received two different video recordings of the exercise
program. For the online group after the intervention, participants assigned to the exercise
intervention group had a decrease in self-reported depressive symptoms (Herbert et al.,
2020). State anxiety was marginally increased but there were no significant changes in
trait anxiety (Herbert et al., 2020). Perceived stress was also significantly changed across
time and group with the aerobic exercise group decreasing significantly (Herbert et al.,
2020). Quality of life was not impacted in either group (Herbert et al., 2020). Exercise
and body dissatisfaction were significantly affected over time with both groups
decreasing (Herbert et al., 2020). The results from this study concluded that physical
activity and regular aerobic exercise for 6 weeks are beneficial for reducing subclinical
depressive symptoms and perceived stress among university students. Exercise

14

interventions should be incorporated into daily university schedules as an intervention for
subclinical depression and perceived stress (Herbert et al., 2020).
Both low-intensity and moderate-intensity exercise are effective at reducing
general anxiety and anxiety sensitivity (O’Neill and Dogra, 2020). However, there is not
a lot known about anxiety levels in individuals with asthma and exercise at a higher
intensity. The purpose of the study was to determine if a 6-week HIIT intervention would
reduce anxiety among adults with asthma and whether sex would influence the reduction
(O’Neill and Dogra, 2020). Participants completed a 6 week, 3 times a week HIIT
protocol on a cycle ergometer. The session started with a 5-minute warm-up followed by
10% at peak power output for a minute and then 90% at peak power output for one
minute. This was repeated 10 times. Participants were aged 18-44 years old and were
male and female. The Anxiety Sensitivity Index (ASI), Body Sensations Questionnaire,
and Generalized Anxiety Disorder scale were used to determine anxiety among the
participants. For asthma related anxiety an open visual scale was utilized. PreIntervention to post-intervention the peak power output improved (O’Neill and Dogra,
2020). The total ASI was improved as well as the Body Sensations Questionnaire
(O’Neill and Dogra, 2020). The VAS measurements did not change from pre-intervention
to post-intervention (O’Neill and Dogra, 2020). There were also no significant reactions
between sex and any anxiety outcomes (O’Neill and Dogra, 2020). Results overall
showed that 15% of participants experienced a clinically meaningful improvement in
anxiety sensitivity from the HIIT intervention (O’Neill and Dogra, 2020).
Broadly, exercise is known to improve psychological wellbeing (Evans et al.,
2017). Anxiety and depressive symptoms are reduced, and quality of life is improved.

15

Varied intensities, frequencies, and modalities have been studied to determine the effect
of mental wellbeing. The purpose of the study from Evans et al., in 2017 was to
determine how different dimensions of exercise are associated with psychological wellbeing among healthy, physically active adults participating in self-selected exercise
(Evans et al., 2017). Frequency, duration, and intensity over 2 months were tracked and
related to mental health outcomes. Depressed mood, anxiety, quality of sleep, ability to
concentrate, alertness, sense of confidence, satisfaction with weight, perceived physical
fitness, appetite, stress experience, and satisfaction with physical shape and appearance
were measured. 173 adults completed the study and were recruited over posted
announcements. The participants recorded for 8 weeks their exercise diary with
frequency, duration, intensity, and omitted workouts. The psychological wellbeing was
measured using a 0-10 Likert Scale at the end of the week. Exercise frequency improved
8 of the 11 psychological variables (quality of sleep, ability to concentrate, alertness,
sense of confidence, satisfaction with physical shape and appearance) (Evans et al.,
2017). Exercise duration improved depressed mood and anxiety. There was a difference
among males and females, too, with increased duration showing lower ratings of
depressed mood and anxiety among only males (Evans et al., 2017). Exercise intensity
improved 8 out of the 11 variables (all except anxiety, satisfaction with weight, and
amount of stress experienced). There were also significant gender differences. Males had
lower ratings of depressed mood interaction with increased intensity. Exercise omissions
negatively impacted 10 of the 11 variables, exception of weight (Evans et al., 2017).
There were also significant gender differences with males only having detrimental
impacts on the ability to concentrate, alertness, perceived physical fitness, and appetite

16

(Evans et al., 2017). Overall, higher-intensity exercise is associated with improvements in
cognition and mood, as well as increased appetite and quality of sleep (Evans et al.,
2017).

17

CHAPTER 3
METHODOLOGY
Subject Recruitment
Subjects were recruited from East Stroudsburg University graduate and
undergraduate programs that had face-to-face instruction for the Spring 2021 semester.
The subjects were sent an email regarding the study information. To participate in the
study, the subjects had to meet the inclusion criteria of sedentary or not being physically
active based on ACSM recommendations. Subjects were included if they were not
currently getting 150 minutes of moderate-intensity aerobic activity within one week.
Any resistance training that a subject was participating in was not included in the 150
minutes of moderate intensity training. Participants were aged 18 to 40 years old and
both males and females were recruited. ESU faculty and staff were also recruited via
email, utilizing the same recruitment process as ESU students.
Equipment
● Surgilance One Touch Safety Lancets (Medi purpose, 2017, United States)
● PTS Diagnostics CardioChek PA Analyzer (PTS Diagnostics, 2021, Indiana,
United States)
● PTS Diagnostics Lipid Panels (PTS Diagnostics, 2021, Indiana, United States)

18

● PTS Collect Capillary Tubes (PTS Diagnostics, 2021, Indiana, United States)
● Omni Trust Powder Free Latex Examination Gloves (Omni International Corp,
2021 New Hampshire, United States)
● Clorox Bleach Disinfecting Wipes (The Clorox Company, 2021, California,
United States)
● Hydrox Isopropyl Alcohol 99% (Med Lab Supply, 2021, Florida, United States)
● Element Non-Woven Gauze Sponges (McKesson, 2021, Texas, United States)
● Lifescan Ultra 2 Blood Glucose Meter (Lifescan, 2021, Pennsylvania, United
States)
● One-Touch Ultra Glucose Test Strips (Lifescan, 2021, Pennsylvania, United
States)
● Detecto Adult Mechanical Stadiometer (Detecto, 2021, Missouri, United States)
● Befour PS- 6600 ST Portable Digital Scale (Befour, 2021, Wisconsin, United
States)
● Baseline Evaluation Instruments 60-inch Gulick Tape (Baseline Evaluation
Instruments, 2021, New York, United States)
● Omron HBF- 306 C Bioelectrical impedance Analysis (Omron Healthcare, 2006,
Illinois, United States)
● Omron BP7200 5 Series Automatic Blood Pressure Cuff (Omron Healthcare,
2019, Illinois, United States)
● Fitbit Inspire 2 Heart Rate Monitor (Google, 2019, China)
● American Sociological Association Perceived Stress Scale
● GAD-7 Scale

19

● Generalized Self-Efficacy Scale
● DBIQ Scale
● PPE: Face Shield, Face Masks, and Laboratory Coats
Laboratory Data Collection
Once recruited, the subjects were asked to set up a time for their first laboratory
session to collect baseline data. 12 hours prior to their first lab session all subjects were
instructed to complete a 12 hour fast and to abstain from physical activity for 12 hours.
The subjects were instructed that they could drink water for the 12 hours leading up to the
fasted tests. They were also instructed to bring along a light snack and water for the
following morning. Once in the lab for the first baseline session a standard PAR-Q
(Appendices) and informed consent were given to the subjects to complete the subjects
were given time to read the PAR-Q and informed consent and were asked by the
researcher if they had any questions. The total time for the study was explained to the
subjects, which was eight weeks. There was one week prior for baseline data collection,
6-weeks for intervention, and one-week post- intervention data collection.
Once the PAR-Q and informed consent was completed, data collection began.
The subjects were instructed to sit in a chair for five minutes without movement, using
their phone, or talking to other people. Once the five minutes was complete, the Omron
Automatic Blood Pressure cuff was used to measure RHR and BP. The left arm was used
for every subject, and they were instructed to rest their left arm on the table. The cuff was
placed along the upper arm by the brachial artery with a supinated palm.
Anthropometric data of height (cm) and weight (cm) were measured to track
changes in weight and for changes in BMI. Guidelines for height and weight
20

measurement followed the current ACSM recommendations. Height was measured using
a Detect Stadiometer and weight was measured with the Befour Digital Scale. BMI
(kg/m2) and BF% were calculated using the BIA. The practitioner entered the age, sex,
activity level, and height/weight. Once all the information was entered the subjects were
instructed to hold out the machine using both hands and gently press down onto the silver
bars on the side until the readings for both measurements appeared. Lastly for
anthropometrics WC and HC were recorded. A Gulick Tape and tensiometer were used to
measure WC and HC. Three measurements were taken for each circumference and
followed ACSM recommendations.
Once all the anthropometric data was collected, the blood assay measurements
were recorded. The laboratory table was disinfected, and the subjects were asked to sit
down. The researcher asked for the non-dominant hand to clean off the fingertips with
rubbing alcohol and gauze. The first and second fingers were predominantly used,
although for some subjects the third and fourth fingers were cleaned. A one-touch lancet
was used to prick the finger. The lancet was pushed into the lateral or medial side of the
bed of the finger. BG was measured first using the OneTouch glucometer and test strips.
If necessary, a second finger prick was performed to record TC, HDL, and TG levels.
The CardioChek machine and pipe were used to measure fasted HDL, LDL, and TG
levels.
Next, all the mental wellbeing scales were completed. They were completed after
the blood measurements so that any anxiety or stress about the fingerpick would not alter
the mental wellbeing data. Self-reported anxiety, stress, self-efficacy, and body image
scale were completed by the subjects in person so that the researchers were available to

21

answer questions. These four scales used were not diagnostic scales and data from the
four scales was only utilized to track changes in mental wellbeing from the walking
intervention. The GAD-7 was used as a validated scale to assess symptoms of generalized
anxiety (Spitzer et al., 2006). The GAD-7 was a 7 question, Likert scale of 0 (not at all
sure) to 3 (nearly every day). A score of 5, 10, and 15 were the cutoff points for mild,
moderate, and severe anxiety. These anxiety classifications were not used to diagnose any
of the subjects but rather to monitor if there were any changes in anxiety scores at each
lab visit. The PSS was used to measure the perception of stress. The PSS is a validated
scale on how people measure the degree to which one’s life is stressful (Cohen et al.,
1988). The PSS was 10 questions in length and based on a 0 (never) to 4 (very often)
scale. Questions four, five, seven, and eight were reverse scored. All the scores were then
totaled from each column and added together for the total score. A higher score indicated
higher perceived stress. The GSE was used as a validated questionnaire to measure selfefficacy and was 10 questions in length based on a 1 (not at all true) through 4 (exactly
true) Likert scale (Schwarzer and Jerusalem, 1995). Scores from each column were
combined for a total score from 10 to 40, with a higher score indicating higher selfefficacy. The DBIQ Scale was a 35 question, validated scale to measure self-reported
body image. A modified version of the DBIQ, the DBIQ-NL was utilized to assess body
image. The modified version was a validated and reliable scale that was used in a nonclinical setting for body image (Scheffers et al., 2017). 24 questions were included that
focus on self-aggrandizement and vitality. Questions about sexual fulfillment and
physical contact were omitted for 24 questions total. Responses were scored on a 5-point
(1= not at all agree, 5= fully agree) Likert scale. Questions two, three, six, fifteen,

22

eighteen, twenty-three, and twenty-six were reverse scored. Self-aggrandizement and
vitality were calculated separately for a total body image score. A higher DBIQ score
indicates a better-perceived body image. The researcher did all the scoring, and the
subjects were only instructed to read the statements on each scale and write down the
associated number from each scale.
Once the baseline data collection was completed the walking intervention was
prescribed to the subjects. The subjects were asked not to change any of their other
current activities and to maintain their current diet. The walking intervention was a
prescribed 30 minutes of walking 5 times a week, for 6 weeks. The intensity of the
walking was at moderate intensity, which was 40 to 59% of HRR. Maximal HR (MHR)
was based on the age-predicted maximal heart rate formula (APMHR) of 220-age. RHR
was based on the number from the Automatic Omron BP cuff. For the entire eight weeks,
each subject was given a Fitbit Inspire 2 to measure compliance to the walking protocol.
The subjects were asked to record their 30 minutes of walking on the Fitbit Inspire 2 and
sync their information with the Fitbit application on their cell phone. Time and HR from
the walking sessions was recorded in the Fitbit application. The Fitbit trackers were given
to the subjects at the first laboratory session. Instructions for wearing the Fitbit monitor
were based on Sumner et al., study where the monitor was removed for charging,
showering, and swimming activities only (2020). Instructions on how to wear the monitor
were from Fitbit manufacturer recommendations for placement. The monitor was to be
worn on the top of a selected wrist with the back of the watch should be in contact with
the skin for optimal tracking (Fitbit, 2020).

23

The subjects were asked to return to the lab two more times. Once after
completing session 15 at the end of week three and again after completing session 30 at
the end of week six. The previously mentioned lab tests were completed at these two lab
sessions A follow up email was sent to each subject outlining information on how to wear
the Fitbit, record sessions, and information about the study. The contact information of
the primary researcher was also given to each subject at the baseline session. At the end
of the six-week session, the subjects returned their Fitbits to the researcher and were
given instructions on how to download excel files from the past two months off the Fitbit
website. The subjects emailed the Fitbit excel files to the researcher, which the researcher
then used for data analysis.
At the first laboratory session the subjects were verbally informed to not change
any dietary habits and at each follow up session a verbal check was completed with each
subject that there were no dietary changes. A verbal check in was also completed at each
session regarding if there were any changes to exercise beyond the study intervention. If
the subjects confirmed there were any changes in diet or exercise, the intervention was
stopped for that individual participant.
Data Analysis
Data was recorded on Microsoft Excel 2016 or placed into a binder for the study.
Once all the data was collected from the subjects the data was reorganized in Microsoft
Excel to calculate means, standard deviations, and delta scores. Data analysis was broken
up into four different categories for each variable tested: anthropometrics, cardiovascular,
blood assays, and mental wellbeing. WT, BF%, BMI, WC, and HC were organized under
the anthropometrics category. SBP, DBP, and RHR were organized under the

24

cardiovascular category. TC, LDL, HDL, TG, and BG were all categorized within blood
assays. Lastly, each of the four scales was organized under the mental wellbeing section.
IBM SPSS Version 27 was used for data analysis. A one-way repeated measures
ANOVA was calculated for each variable, comparing participants' baseline week, week
three, and week six of testing. Each variable was tested at an alpha of .05 and a
confidence interval of 95% of the mean. A paired samples t-test was run using SPSS to
determine if there were differences in HR compliance from weeks one to three versus
weeks three to six. The paired samples t-test was tested at a .05 alpha level and 95%
confidence interval of the mean. Total compliance was determined by counting the total
number of walks that the participants completed compared to the total number of walks
(30) that should have been completed. The total walks completed was then divided by 30
walks to give a compliance percentage. The same process was used for the total six
weeks but instead using the prescribed HR zones. The HR from each recorded session
was looked through by the researcher and any walks not within the HR zone were not
counted towards intervention compliance.
During the first week, one participant did not fill out the DBIQ correctly, so this
data was not utilized for the mean score calculation for the DBIQ in the first lab session.
At week three of the study, two subjects had to quarantine so data was unable to be
collected for those two subjects at week three. One subject did not have their blood
triglyceride, HDL, and LDL levels recorded because of almost passing out in the first
baseline session. These three variables were not recorded from this subject again for
weeks three and six.

25

Figure 1. Methodology Flowchart

26

CHAPTER IV
RESULTS
Subject Demographics and Subject Dropout
A total of 10 subjects were recruited via email. There were three undergraduate
students, four graduate students, and three faculty initially recruited. Two undergraduate
students, four graduate students, and three faculty members completed the full duration of
the intervention. Four males and six females were initially recruited for the study via
email. Four males and five females completed the six-week intervention. The mean age
of the subjects was 24.78 + 2.99 years, and the mean height was 175.10 + 8.33 cm.

27

Table 1
Intervention Compliance
Walking Compliance
% Total Walks
% Walks within HR
zones
% Walks within HR
zones weeks 1 to 3
% Walks within HR
zones weeks 3 to 6

Mean and STDEV
94.815 + 6.479
57.415 + 37.949

p-value

65.643 + 39.753

.124

57.661 + 38.137

.124

Note. Compliance with the walking intervention is displayed in Table 1. The mean and
standard deviation are shown for the total % of walks out of 30 that all the subjects
completed. The walks within the prescribed HR zones are also shown. Compliance for
the walks within the HR zones is also presented as percentages out of the 30 walks that
were completed. The compliance was also broken up into weeks one to three compared to
weeks three to 6. A paired samples t-test was run using SPSS to determine if there were
any differences in HR compliance in weeks one to three versus three to six. A p-value of
.124 showed that there was no difference in HR compliance during the walks between the
two sets of weeks.

28

Figure 2
Body Mass measurements for the three laboratory sessions

Note. The mean scores for changes in weight over the course of the three lab sessions are
presented above. The mean weight from the first session was 85.392 ± 22.997 kg, 79/177
± 8.204 kg at the second session, and 85.277 ± 22.908 kg in the final session. A one-way
ANOVA test was utilized to test for differences in the means between weeks one to three,
three to six, and one to six. A p-value of .831 revealed that there was no difference in
weight between the three sessions.

29

Figure 3
Body Fat Percentage measurements for the three lab sessions

Note. The BF% for each week of testing is displayed above in figure 2. The mean BF%
from week one was 27.133 ±6.624, 26.443 ± 6.847 % in week 3, and 26.6778 ± 6.957%
in week six. A one-way ANOVA test was utilized to see if there were any differences in
the mean BF% for each week of testing. A p-value of .979 revealed that there was no
difference in body fat % between weeks one to three, three to six, and one to six.

30

Figure 4
Body Mass Index measurements for the three laboratory sessions

Note. The mean scores for BMI are displayed in figure 4 for each lab session. The mean
BMI from week one was 27.611 ± 5.377 kg/m2, 26.343 ± 5.009 kg/m2 in week 3, and
27.622 ± 5.261 kg/m2 in the sixth week. A one-way ANOVA was run to determine if
there were any differences in the subjects BMI measurements for each lab session. A pvalue of .862 showed that there was no difference in BMI between each lab session.

31

Figure 5
Waist and Hip Circumference measurements for the three laboratory sessions

Note. The mean measurement for WC and HC are presented in figure 5. The mean WC in
week one was 92.257 ± 18.961 cm, 85.233 ± 14.685 cm in week three, and 88.586 ±
18.099 cm in week six. For the HC, the mean measurement for week one was 92.257 ±
18.961 cm, 85.233 ± 14.685 cm in week three, and 88.596 ± 19.099 cm in week six. A
one-way ANOVA test was used to calculate any differences between each lab session.
For the WC, a p-value of .751 revealed that there was no difference in the measured WC
between each lab session. For the HC, a p-value of .751 also showed that there were no
differences in the measured hip circumference for each lab session.

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Table 2
Descriptive Statistics and Significance for Cardiovascular Variables

Variable
SBP
(mmHg)
DBP
(mmHg)

RHR (bpm)

Week
1
3
6
1
3
6
1
3
6

Mean and Stdev
122.777 + 10.662
122.222 + 11.773
122.480 + 15.449
69 + 8.154
73.850 + 9.063
71 + 8.306
66.666 + 7.123
68.571 + 8.580
71.444 + 9.976

Sig
0.996

0.532

0.510

Note. The mean and standard deviation are shown for SBP, DBP, and RHR from each lab
session. The significance is also displayed for each variable. For the SBP there was a
mean change of -2.875 ± 12.988 mmHg from week one to week six. The DBP had a
mean change of 1.375 ± 8.86 mmHg from the week one lab session to the last lab visit.
The RHR had a change of 4.75 ± 10.209 bpm from week one to week 6. A one-way
ANOVA was used to calculate any changes in cardiovascular adaptations for the walking
intervention. For the SBP a p-value of .996 showed that there was no difference in SBP
from pre- to post-intervention. For the DBP a p-value of .532 also showed that there was
no difference from pre-intervention to post-intervention. A calculated p-value of .510 for
the RHR also showed that there was no difference in RHR for week one to week six of
the intervention.

33

Table 3
Descriptive statistics and significance for measured blood assays
Variable
TC (mg/dL)

TG (mg/dL)
HDL
(mg/dL)
LDL
(mg/dL)

BG (mg/dL)

Week
1
3
6
1
3
6
1
3
6
1
3
6
1
3
6

Mean and Stdev
160.125 + 42.367
161.167 + 32.676
173.500 + 26.645
107.250 + 39.881
73.666 + 23.720
97.875 + 27.126
54.500 + 19.603
55.333 + 13.276
55.625 + 14.802
88.625 + 34.070
77.830 + 44.090
89.180 + 20.858
91.333 + 10.988
83.428 + 6.477
89.111 + 6.622

Sig
0.706

0.165

0.990

0.532

0.191

Note. The descriptive statistics and significance for the blood assays are presented in
table 4. The means and standard deviations from weeks one, three, and six are displayed
for TC, TG, HDL, LDL, and BG. For the TC there was a mean change of 13.375 ±
39.813 from week one to week six. The TG levels had a mean change of -9.375 ± 43.996
from the first to the last lab visit. The HDL levels had a calculated mean change of 1.125
± 16.89 from week one to week six. The calculated LDL levels change 9.625 ± 36.578
from the first to the last lab visit. BG measurements had a mean change of -3.125 ±
11.813 from week one to week 6. For each variable, a one-way ANOVA was used to
calculate differences in week one, three, and week six mean scores. For TC, a p-value of
.706 determined there was no difference in the mean TC from each lab session. A
calculated p-value of .165 for the TG also determined that there was no difference in the

34

TG level from each lab session. For HDL levels, the calculated p-value was .990 showing
that there was no difference between each lab session for the HDL levels. A calculated pvalue of .532 for the LDL also revealed that there were no differences between each lab
session. For the BG, a p-value of .191 showed that there was no difference in BG levels
from each lab visit.

35

Figure 6
Generalized Anxiety Disorder Scores

Note. The mean scores and standard deviation for the results from the GAD-7 are
presented in figure 6 above. The mean GAD score from the first lab session was 5.5 ±
5.7532, 5.833 ± 5.947 at week three, and 4.750 ± 4. 8917 in the sixth week. A mean delta
score of -0.75 ± 3.37 was calculated from week one to week six. A one-way ANOVA
was calculated to determine if there were any differences in the recorded anxiety scores
from each lab visit. A p-value of .951 showed that there was no difference in anxiety
scores that were reported from each lab session.

36

Figure 7
Perceived Stress Scores

Note. The mean scores and standard deviation for the results from the PSS are displayed
in figure 7 above. The mean PSS score from week one was 13.125 ± 8.167, 12.333 ±
5.854 for the third week, and 12.250 ± 5.339 for the sixth week. For the PSS, there was a
mean calculated change of -0.875 ± 9.775 from week one to week six. A one-way
ANOVA was calculated to determine if there were any differences in the recorded
perceived stress scores from each lab visit. A calculated p-value of .903 showed that there
was no difference in perceived stress scores that were reported from each lab session.

37

Figure 8
Body Image Scores

Note. A total body image score is represented in figure 8 above from the breakdown of
DBIQ (V) and DBIQ (A). The mean score from the DBIQ (V) and DBIQ (A) was added
together to calculate a mean DBIQ score. Reported values were calculated from each lab
session. The total DBIQ score from week one was 72.143 ± 11.596, 97.500 ± 9.376 for
week three, and 78.625 ± 23.537 for week six. There was a total mean change of 15.5 ±
23.537 for the total DBIQ score from week one to week six. The DBIQ (V) mean score
from week one was 28/143 ± 6.962, 31.333 ± 3.011 in week three, and 32 ± 3.703 in the
sixth week. DBIQ (A) mean scores were initially measured at 44 ± 9.398, 48.167 ± 9.347
in week three, and 46.625 ± 11.275 for the sixth week. The total mean change for the
total DBIQ score came from an increase in the mean DBIQ (V) score of 7.375 ± 11.8676
and from the DBIQ (A) change of 8.125 ± 12.088. A one-way ANOVA was calculated
on the DBIQ (V), DBIQ (A), and total DBIQ score to determine if there were any
differences in the scores from each lab session. A calculated p-value of .350 for the
DBIQ (V) and a calculated p-value of .761 revealed that there were no differences in the
38

associated scores between each lab session. A p-value of .492 showed that there was no
difference in the total DBIQ score from each lab visit.

39

Figure 9
General Self- Efficacy Scores

Note. The reported scores from the GSE scale are shown in figure 9 from each lab visit.
The initial measurement from the GSE mean score was 34 ± 3.891, 34.167 ± 2.927 in
week three, and 34.500 ± 3.024 in the sixth week. The total change from week one to
week six was 0.5 ± 2.563 for GSE. A one-way ANOVA was run to determine if there
were any differences in week one to three, three to six, and one to six in reported selfefficacy. A calculated p-value of .942 determined that there was no difference in reported
self-efficacy from each lab visit.

40

CHAPTER V
DISCUSSION AND CONCLUSION
Students in a University setting spend time sedentary for completion of
assignments and for class time (Mussi et al., 2017). This time spent sedentary,
irrespective of physical activity time, is associated with increased weight, BMI, obesity,
waist circumference, blood pressure, and cardiovascular morbidity (Mussi et al., 2017).
Studies have shown that increase step count and moderate intensity walking interventions
have positively impacted SBP, DBP, BF%, WC, and HC (Murphy et al, 2002; Tully and
Cupples et al., 2011). In addition to cardiometabolic risk factors, mental-wellbeing can
also be positively impacted through increased exercise and physical activity. Studies have
shown that body dissatisfaction, subclinical depressive symptoms, and perceived stress
can be reduced through increased exercise and physical activity (Herbert et al., 2020).
This present study aimed to investigate if a six-week walking intervention would
positively impact cardiometabolic risk factors and mental-wellbeing in university
students and staff.

41

Subject Compliance
Table 1 displays the compliance from the involved subjects for the entire sixweek walking intervention. Within the six weeks of the intervention each subject should
have completed a total of 30 walks. The compliance to the total number of walks was
94.815 + 6.479 %, which is consistent, and slightly higher, than a step count intervention
from 2011 that had an adherence rate of 84.8% (Tully and Cupples, 2011). However,
when breaking down the compliance by the prescribed HR intensities there was only
57.415 ± 38 % for the entire six weeks. When broken down further into the first three
weeks the compliance at the HR intensities was 65.643 ± 39.753 % and 57.661 ±
38.137% from the last three weeks. A study from Murphy et al., had a compliance rate of
88.2 ± 1.1 % and 91.3 ± 4.1 % for the two walking interventions included in their study
(2002). However, that compliance to their intervention was related to time and not HR
intensities. Presently, a study could not be identified in relation to compliance in a
walking intervention with prescribed HR at a moderate intensity.
Anthropometric Adaptations
The present WT results are consistent with previous studies. Table 4 (Appendices)
and Figure 2 overview the descriptive statistics for WT. The subjects involved in the
study had a weight of 85.392 + 22.996 kg at the week one session, 79.171 + 21.705 kg at
week three, and 85.276 + 22.907 and week six session for a total change in weight from
week one to three of -0.12 + 1.04. This small change in weight was determined to not be
significant for this sample of participants. A walking intervention from 2002 also found
that in middle aged adults there were no significant changes in body mass after the
walking intervention (Murphy et al., 2002). The current findings for BF% are shown in

42

table 4 and figure 3. The changes in BF% from this study are not consistent with previous
research on a six-week walking intervention. At the first laboratory session the BF% was
27.133 + 6.623 %, 26.442 + 6.847 % in the third week, and 26.677 + 6.956 at the sixth
week for a total change of -0.46 + 3.50 from week one to week six. The previous study
found significant reductions in BF% with their prescribed walking intervention (Murphy
et al., 2002). The first BMI measurement for all the subjects was 27.611 + 5.376, kg/m² at
week three it was 26.342 + 5.009 kg/m², and 27.622 + 5.260 kg/m² at the sixth week. The
total change in BMI was 0.01 + 0.38 kg/m² from the first to the last session. These
changes in BMI are consistent with a previous study that a walking intervention does not
significantly impact BMI (Murphy et al, 2002). According to ACSM, the BMI scores
obtained from this study would classify the subjects on average in the overweight
category (ACSM, 2018). Data from the WC and HC changes are displayed in Table 4 and
Figures 4 and 5. WC was measured at 92.257 + 18.961 cm at the first session, 85.233 +
14.884 cm in the third week, and 88.595 + 18.088 cm at the final session for a total
change of -3.66 + 4.21 cm from week one to week six. The HC was measured at 92.256 +
18.961 cm at week one, 88.233 + 14.684 cm at the third week, and 88.595 + 18.099 cm at
the sixth week for a total change of -1.97 + 4.51 cm from the first to last session. These
changes were determined to not be significant for measured WC and HC. These findings
do not agree with previous research that WC and HC should decrease significantly
following a six-week walking intervention (Murphy et al., 2002).
These inconsistent findings could be explained by low compliance to moderate
HR intensities. Since the overall compliance to the moderate HR intensities for the entire
six weeks was 57.415 ± 37.949, there is a potential that there was not enough stress

43

placed onto the cardiovascular system to elicit adaptations in BF%, WC, and HC. A
previous study mentioned that changes in BF%, HC, and WC that were identified in their
study could lower the risk of cardiovascular disease (Murphy et al., 2002). Additionally,
kilocalorie expenditure could have been impacted if the subjects were not reaching the
moderate heart rate intensity that was initially prescribed. Higher heart rate intensities
yield higher kilocalorie burn and can ultimately contribute to a reduction in body mass
and body fat percentage (Falcone et al., 2015).
Cardiovascular Adaptations
The adaptations in the SBP from this study is not consistent with a previous study
that a six-week walking intervention should reduce SBP (Tully and Cupples, 2011).
Table 2 shows the results from the cardiovascular adaptations. At the beginning of the
intervention in the first week SBP was measured to be 122.77 ± 10.662 mmHg. In the
third week the SBP was 122.222 ± 11.773 mmHg and in the sixth week it was measured
at 122.48 ± 15.499 mmHg for a total not significant change of -2.875 ± 12.988 mmHg.
SBP in this study was also inconsistent with the previously mentioned study that SBP
decreased following the 10,000-step intervention (Tully and Cupples, 2011). At the
beginning of this study the DBP was 69 mmHg ± 8.154 mmHg. The measured DBP in
week three was 73.85 mmHg ± 9.063 and in the sixth week it was 71 ± 8.306 mmHg with
a total not significant change of 1.375 ± 8.863 mmHg. The study from Tully and Cupples
also found a significant decrease in DBP following the 10,000 steps intervention. RHR
was measured at 66.666 ± 7.123 bpm in the first week, 68.571 ± 8.58 bpm in the third
week, and 71.444 ± 9.976 bpm in the sixth week for a total change in RHR of 4.75 ±

44

10.209 bpm. This study does not agree with previous research that RHR is reduced with
an increase in physical activity and exercise (Sumner et al., 2020).
The inconsistent findings could again be attributed to the overall compliance to
the walking intervention. With better compliance to the HR intensities prescribed from
ACSM, there may have been more stress placed on the cardiovascular system which
would elicit a reduction in SBP, DBP, and RHR. In addition to the stress placed on the
cardiovascular system exercising at the moderate heart rate intensity or higher heart
intensity yields in a higher number of kilocalories being expended to complete an
exercise bout (Falcone et al., 2015). When more calories are expended within a session
there will be a greater reduction in body mass (Falcone et al., 2015). The initial
measurement for the SBP was on average classified as elevated according to newest
guidelines released from the American College of Cardiology and the American Heart
Association (AHA, 2021). However, SBP reading from this study was not near the
ACSM risk factor of >140 mmHg. DBP was also below the risk factor category of >90
mmHg with the initial measurement at 69 mmHg. This group started out even below the
risk factor stratification level which could be another reason why there were no
significant changes which occurred.
Another explanation as to why there were not any changes could be explained by
the subjects did not reach 10,000 steps each day. The step count data was unable to be
used as the subjects did not keep the tracker on the entire day, so it could not be
determined in total step count significantly changed. When comparing to Tully and
Cupples study, the subjects increased their total step count to 10,000 steps and saw
significant changes (2011). ACSM identifies 0 to 5000 steps as sedentary, 5,000 to

45

7,4999 steps as low active, 7,5000 to 9,999 as somewhat active, 10,000 to 12,500 as
active, and 12,500 or more as highly active (American College of Sports Medicine,
2011). If the subjects only activity for the day was the walking intervention their step
count could still be identified as low activity or sedentary, which could further explain a
lack of significant changes.
Blood Assay Adaptations
Table 3 displays the blood assay adaptations that occurred over the course of the
intervention. The changes which occurred in this study are not consistent with previous
findings that a six-week walking intervention significantly reduces TC, HDL levels, and
TG levels (Murphy et al., 2002). In the present study, the TC was initially measured at
160.125 ± 42.367 mg/dL, 161.167 ± 32.676 mg/dL in the third week, and 173.5 ± 26.645
in the final lab session for a total not significant change of 13.375 ± 39.8135 mg/dL from
week one to week six. TG levels were initially measured at 107.25 ± 39.881 mg/dL in the
first session, 73.66 ± 23.72 mg/dL in the third week, and 97.875 ± 27.126 mg/dL in the
final week. The total change for the TG levels was -9.375 ± 43.996 mg/dL, which were
not significant changes. The HDL levels were measured at 53.333 ± 19.603 mg/dl in the
first lab session, 55.333 ± 13.276 mg/dL in the second lab session, and 55.625 ± 14.802
in the last lab session. The total change of the HDL levels was 1.125 ± 16.89 mg/dL,
which were not significant changes. At the beginning of the intervention the LDL was
88.625 ± 34.07 mg/dL, 77.73 ± 44.09 mg/dL at the second lab session, and 89.18 ±
20.858 mg/dL in the final lab session for a total not significant change of 9.625 ± 36.578
mg/dL. Lastly, the initial measurement for the BG was 91.333 ± 10.988 mg/dL in the first
week, 83.428 ± 6.477 mg/dL in the third week, and 89.111 ± 6.622 mg/dL in the final

46

week. There was a total change of -3.125 ± 11.813 mg/dL from week one to week six
which were not significant.
A possible explanation for a lack of changes in the blood measurements may stem
from that the initial measurements for all the blood measurements could not be classified
as a risk factor as they fell below the ACSM negative risk factor stratification. For TC to
be considered a risk factor it needs to be > 200 mg/dL, and the participants initial TC
started at 160.125 mg/dL. The HDL levels were above the risk factor of < 40 mg/dL
measured at 55.33 mg/dL, meaning this was not a negative risk factor to initially start the
intervention. The LDL levels were also below the risk factor of > 130 mg/dL being
initially measured at 77.83 mg/dL. There was an increase in LDL from the first week of
testing to the last week of testing, but it was not a significant change. This increase in
LDL levels could potentially be explained by if the subjects were not truthful about their
diets and changed their eating behavior’s part way through the study. One article from
2002 highlights that if dietary changes occurred during the intervention, it would be
likely that carbohydrates would be decreased and fats would be increased to improve
health (Murphy et al., 2002). If the subjects did modify their diets in this way, it would
reflect a decrease in HDL cholesterol and an increase in TG and LDL levels (Murphy et
al., 2002). TG levels were also below the risk factor of >150 mg/dl with the initial
measurement being 107.25 mg/dL. Lastly, for metabolic health BG was initially
measured at 91.33 mg/dL, which is also below the ACSM risk factor of >100 mg/dL. A
study that was done in 2017 found that three weeks of uphill or downhill walking when
adjusted for total energy expenditure significantly improved pre-diabetic male’s oral
glucose tolerance test (Philippe et al., 2017). Additionally, since the compliance to the

47

HR zones was 57.415 ± 37.949 % for this group of subjects this could explain why there
were no significant changes which occurred.
Mental-Wellbeing Adaptations
Figure 6 shows the GAD-7 scores from the three separate lab sessions. The
measured GAD score in week one was 4.889 ± 5.667, 5.00 ± 5.859 in the third week,
4.222 ± 4.841 in the sixth week. There was a total not significant change of -0.75 ± 3.370
from week one to week six. The GAD-7 results from this study are consistent with
previous research that low to moderate intensity exercise twice a week in college students
does not significantly impact self-reported trait anxiety (Herbet et al., 2020). However, a
study from 2017 found that increased exercise intensity does positively impact perceived
anxiety (Evans et al., 2017). Figure 7 presents the PSS scores from each session. The
score from week one was 12.444 ± 7.970, 12.857 ± 5.520 in the third week, 11.444 ±
5.547 in the sixth week for a total not significant change of -0.875 ± 9.775 from the first
lab session to the last lab session. The findings from this current study are currently
inconsistent when comparing to previous research. Previous findings showed that low to
moderate intensity exercise does significantly improve perceived stress among college
students (Herbert et al., 2020). Another study found that increased exercise intensity also
significantly improves perceived stress, anxiety, and depressive symptoms (Evans et al.,
2017). Figure 8 displays the scores for the DBIQ total score, DBIQ (V), and DBIQ (A)
from each laboratory visit. The measured DBIQ in week one 72.000 ± 10.714, 76.714 ±
11.294 in the third week, and 78.555 ± 11.938 in the sixth week for a total not significant
change of 15.5 ± 23.537. The measured DBIQ (V) from week one was 28.250 ± 6.453,
29.714 ± 5.089 in the third week, 31.888 ± 3.480 in the sixth week. The DBIQ (A) from

48

week one was 43.750 ± 8.735, 47.000 ± 9.073 in the third week, and 46.666 ± 10.547 in
the sixth week. This finding is also inconsistent with previous research which showed
that exercise frequency and exercise intensity both improved satisfaction with physical
shape and appearance (Evans et al., 2017). Lastly, GSE is shown in figure 9 with a score
represented from each lab session. The GSE from week one was 33.888 ± 3.655, 34.428
± 2.76 in week three, and 34.222 ± 2.948 in week six. The total difference from week one
to week six for the GSE scores was a not significant change 0.5 ± 2.563. The GSE score
is also inconsistent with previous research which showed that both exercise frequency
and exercise intensity improve perceived self-confidence (Evans et al., 2017).
The inconsistent findings from this present study compared to previous literature
could be explained by the intervention compliance. In the previously mentioned study
from 2017, a moderate exercise intensity to higher exercise intensity showed
improvements in body image and self-efficacy in physically active, older adults (Evans et
al., 2017). For all the subjects involved in the study if the HR was not compliant with the
prescribed intensity it was lower than the moderate HR intensity prescribed.
For the future it is recommended that a larger sample size be obtained.
Additionally, a sample that is homogenous should be gathered to limit huge variability,
which is seen in the present study. A randomized trial with a control group and placebo
group should be implemented to see if there would be any significant changes in step
count from pre-intervention to post-intervention.
Conclusion
This present study sought to determine if a six-week walking intervention in
individuals aged 40 and younger would positively impact cardiometabolic risk factors

49

and mental-wellbeing. Of all the variables measured, none were found to be statistically
significant to positively impact cardiometabolic risk factors and mental-wellbeing.
However, results from this study should not undermine the positive benefits that have
been seen in other studies regarding the benefits of low to moderate intensity exercise on
cardiometabolic risk factors and mental-wellbeing (Herbert et al., 2020; Murphy et al.,
2002; Tully and Cupples, 2011). Universities should still consider the importance of
reducing sedentary time and increasing physical activity and exercise to reduce
cardiometabolic risk factors and improve mental wellbeing in students and staff.

50

APPENDICES
IRB Approval

East Stroudsburg University Institutional Review Board
Human Research Review
Protocol # ESU-IRB-030-2021
Date:

February 9, 2021

To:

Natalie Turbett and Emily Sauers

From: Shala E. Davis, Ph.D., IRB Chair
Proposal Title: “Effects of a Six Week Walking Intervention on Cardiometabolic Risk Factors
and Mental Well-Being in College Aged Individuals”
Review Requested:

Exempted

Expedited X

Full Review

Review Approved:

Exempted

Expedited X

Full Review

FULL RESEARCH
____

Your full review research proposal has been approved by the University IRB (12 months).
Please provide the University IRB a copy of your Final Report at the completion of your
research.

____

Your full review research proposal has been approved with recommendations by the
University IRB. Please review recommendations provided by the reviewers and submit
necessary documentation for full approval.

____

Your full review research proposal has not been approved by the University IRB.
Please review recommendations provided by the reviewers and resubmit.

EXEMPTED RESEARCH
____ Your exempted review research proposal has been approved by the University
IRB (12 months). Please provide the University IRB a copy of your Final Report
at the completion of your research.
____ Your exempted review research proposal has been approved with
recommendations by the University IRB. Please review recommendations
provided by the reviewers and submit necessary documentation for full
approval.
____ Your exempted review research proposal has not been approved by the University
IRB. Please review recommendations provided by the reviewers and resubmit, if
appropriate.
51

EXPEDITED RESEARCH
__X_ Your expedited review research proposal has been approved by the University
IRB (12months). Please provide the University IRB a copy of your Final Report
at the completion of your research.
____ Your expedited review research proposal has been approved with
recommendations by the University IRB. Please review recommendations
provided by the reviewers and submit necessary documentation for full
approval.
____ Your expedited review research proposal has not been approved by the University
IRB. Please review recommendations provided by the reviewers and resubmit, if
appropriate.
________________________________________________________________________
______
Please revise or submit the following:

52

Table 4
Table 4. Descriptive Statistics for Anthropometric Data

N

Mean

Std.
Deviation

Std.
Error

1.00

9

85.392

22.997

3.00

7

79.177

6.00

9

Total

Variable

WT (kg)

BF (%)

BMI
(kg/m²)

WC
(cm)

HC (cm)

95% Confidence
Interval for Mean
Min

Max

103.069

54.100

123.030

59.103

99.252

53.800

121.900

7.636

67.668

102.885

54.300

121.900

21.839

4.368

74.596

92.625

53.800

123.030

27.133

6.624

2.208

22.042

32.225

16.200

39.800

7

26.443

6.847

2.588

20.110

32.775

17.800

38.800

6.00

9

26.678

6.957

2.319

21.330

32.025

16.700

39.300

Total

25

26.776

6.524

1.305

24.083

29.469

16.200

39.800

1.00

9

27.611

5.377

1.792

23.478

31.744

20.400

36.900

3.00

7

26.343

5.009

1.893

21.710

30.976

20.200

35.800

6.00

9

27.622

5.261

1.754

23.579

31.666

20.600

36.500

Total

25

27.260

5.047

1.009

25.177

29.343

20.200

36.900

1.00

9

92.257

18.961

6.320

77.682

106.831

68.930

129.000

3.00

6

85.233

14.685

5.995

69.822

100.644

66.700

106.850

6.00

9

88.596

18.099

6.033

74.683

102.508

66.700

126.750

Total

24

89.128

17.140

3.499

81.890

96.365

66.700

129.000

1.00

9

92.257

18.961

6.320

77.682

106.831

68.930

129.000

3.00

6

85.233

14.685

5.995

69.822

100.644

66.700

106.850

6.00

9

88.596

18.099

6.033

74.683

102.508

66.700

126.750

Total

24

89.128

17.140

3.499

81.890

96.365

66.700

129.000

Lower
Bound

Upper
Bound

7.666

67.715

21.706

8.204

85.277

22.908

25

83.610

1.00

9

3.00

The descriptive statistics for WT, BF percentage, BMI, WC, and HC are shown above.
The mean for each variable is presented for the baseline week, week three of testing, and
week six of testing. The overall mean is also displayed for each variable. For WT the
total change in weight from week one to week 6 was -0.12 ± 1.04. The BF% scores
changed -0.46 ± 3.50 from week one to six. Recorded BMI changed 0.01 ± 0.38 from
week one to week six. The calculated WC changed -3.66 ± 4.21 from the first lab session
to the last lab session. HC changed -1.97 ± 4.51 from week one to week six.
53

PSS Scale

54

DBIQ Scale

55

GAD-7 Scale

GSE Scale

56

Study Invitation
Department of Exercise Science
We invite you to take part in this research study. We would like you to understand why
the research is being done and what it would involve for you. Please take the time to
carefully read through. Thank you for your time and please reach out to the investigator if
interested.
Inclusion Criterion:
- Currently not participating in 150 minutes of moderate intensity aerobic exercise each
week.
-

18 to 40 years old.

-

No known disease (cardiovascular, renal, musculoskeletal, metabolic, etc.).

Purpose of the study:
- Effects of a 6-week Walking Intervention on Cardiometabolic Risk Factors and
Mental Wellbeing in College Aged Individuals and Faculty/Staff at East Stroudsburg
University
What we would like you to do:
-

1-week baseline, walking for six weeks, 1-week post-intervention

-

3 total lab visits: Baseline week, week 3 of intervention, and post-intervention
o Lab visits will be completed in the mornings: approximately 30 minutes
for each lab session

- Intervention: 30 minutes individually prescribed walking to be completed outside of
the laboratory 5 times per week
Contact information:
-

Investigator: Natalie Turbett, nturbett@live.esu.edu

-

Thesis Chair: Dr. Emily Sauers, esauers@esu.edu

IRB approval:
ESU-IRB-030-2021

57

Subject Information Sheet for the Six-Week Intervention
•

Fitbit Wearing Instructions
o Wear the Fitbit for the entire duration of the day

•

•
•
•
•
•

o Can be removed for showering and charging
o Wear to bed (can be removed if it causes discomfort)
o Make sure the Fitbit is placed on the wrist that was selected when setting
up the device
o The back sensor should be in contact with skin
o Make sure the strap is not too loose that the device is sliding up and down
the wrist.
Walking Intervention
o 6 weeks of walking (30 minutes, 5 times a week)
o Can be on weekends or weekdays
o Make sure the device is worn during the walks
o Either use the smart track feature for recording walking workouts or start a
walking workout on the Fitbit app
o Make sure that when walking your heart rate is within the individual
prescribed intensities
o Walks can either be done outside or on a treadmill indoors
Nutrition
o Do not change/modify your current eating behaviors for the duration of
your time included in the study
Exercise
o Do not change/modify your current resistance training
We will ask you to come into the lab two more times to test
Once three weeks into the intervention and once at the end of the intervention
We will try to schedule these on the same day of the week and time as your first
lab session

58

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