Address Obesity to Reduce Cancer Risk and Health Disparities in Rural Ohio
Phase: NA
Conditions: Obesity-Related Malignant Neoplasm
Sponsor: Ohio State University Comprehensive Cancer Center

 
 
 
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The Ohio State University Comprehensive Cancer Center 
Addressing Obesity to Reduce Cancer Risk and Health Disparities in Rural Ohio:  
Home-based Exercise in Rural Ohio (HERO) Study 
 
 
 
Investigators 
 
Brian C. Focht, PhD, FACSM, CSCS 
Professor, Kinesiology  
Vice Chair, Department of Human Sciences 
The Ohio State University 
 
Phone: 614-292-2165 
Email: focht.10@osu.edu  
 
 
 
 
 
Electra Paskett, Ph.D.  
Professor and Chair, Division of Cancer Prevention 
and Control, Department of Medicine 
Associate Director for Population Sciences 
Comprehensive Cancer Center 
The Ohio State University 
 
Phone: 614-293-3917 
Fax: 614-293-5611 
Email: electra.paskett@osumc.edu 
 
 
 
 
Project Staff 
Xiaochen Zhang, MB, MPH, PhD (c) 
Division of Population Sciences  
Comprehensive Cancer Center  
Phone: 614-366-4751 
Fax: 614-293-5611 
Email: Xiaochen.Zhang2@osumc.edu 
 
 
 
 
 
 
Victoria R. DeScenza 
Department of Human Sciences 
The Ohio State University 
Email: descenza.1@osu.edu   
 
 
Jessica Bowman, MS 
Department of Human Sciences 
The Ohio State University 
Email: bowman.1396@osu.edu 
 
Zachary L. Chaplow, MS, CSCS, EP-C 
Department of Human Sciences 
The Ohio State University 
Email: chaplow.1@osu.edu   
 
 
 
Consultant 
Steve Heymsfield, MD 
Department of Metabolism & Body Composition 
Pennington Biomedical 
Email: Steven.Heymsfield@pbrc.edu 
 
 
Kathryn Dispennette, MS 
Department of Human Sciences 
The Ohio State University 
Email: dispennette.2@osu.edu  
 
 
 
 
 
 
 
 
 
 

 
 
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Table of Contents 
A 
PROJECT OVERVIEW .................................................................................................................. 4 
A.1     Title ......................................................................................................................................... 4 
A.2 
Overview .................................................................................................................................. 4 
A.3 
Specific Aims ........................................................................................................................... 4 
B 
BACKGROUND AND RATIONALE ............................................................................................... 5 
B.1 
Literature Review/Current State of Knowledge ........................................................................ 5 
B.1.a 
 Magnitude of the problem ................................................................................................. 5 
B.1.b 
 Obesity and cancer .......................................................................................................... 5 
B.1.c 
Weight loss and cancer risk .............................................................................................. 6 
B.1.d 
 Weight loss in rural populations ........................................................................................ 6 
B.1.e   A Point-of-care Approach to Assess Body Composition and Cancer Risk in Rural 
Populations .................................................................................................................................... 7 
B.2 
Preliminary Studies .................................................................................................................. 7 
C 
RESEARCH DESIGN AND METHODS ......................................................................................... 8 
C.1  Overall strategy. ....................................................................................................................... 8 
C.2 
Research Team ....................................................................................................................... 8 
C.2.a  Research role and responsibilities ..................................................................................... 8 
C.2.b  Research team training ..................................................................................................... 8 
C.3 
Study Population ...................................................................................................................... 9 
C.3.a  Rural Ohio ......................................................................................................................... 9 
C.3.b 
Eligibility Criteria ................................................................................................................ 9 
C.3.c 
Recruitment ..................................................................................................................... 10 
C.3.d 
Randomization ................................................................................................................ 10 
C.3.e 
Informed consent process ............................................................................................... 10 
C.4 
Weight Loss Intervention ....................................................................................................... 10 
C.4.a 
Overview ......................................................................................................................... 10 
C.4.b 
Dietary Component ......................................................................................................... 11 
C.4.c 
Physical activity component ............................................................................................ 11 
C.4.d 
Behavioral component ..................................................................................................... 12 
C.5 
Active Control Group .............................................................................................................. 12 
C.6 
Covid-19 Safety Protocols and Planning ................................................................................ 12 
C.7 
Assessment ........................................................................................................................... 13 
C.7.a 
Primary Outcome: feasibility and acceptability ................................................................ 13 
C.7.b 
Secondary Outcome Assessment ................................................................................... 13 
8. 
Physical fitness ................................................................................................................... 15 
C.9. Timeline ................................................................................................................................... 15 
C.10. Potential problems and alternative strategies ........................................................................ 15 

 
 
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C.10.a. Recruitment ..................................................................................................................... 15 
C.10.b. Intervention ..................................................................................................................... 16 
C.10.c. Assessment ..................................................................................................................... 16 
D 
DATA HANDLING AND ANALYSES ........................................................................................... 16 
D.1. Outcome Analysis Plan .......................................................................................................... 16 
D.1.1. Primary outcome ............................................................................................................. 16 
D.1.2. Secondary outcome ........................................................................................................ 16 
D.2.  Data Management ................................................................................................................ 16 
D.3. Record Retention ................................................................................................................... 17 
E 
HUMAN SUBJECTS .................................................................................................................... 17 
E.1 
Anticipated Risks ................................................................................................................... 17 
E.2 
Benefits of participation .......................................................................................................... 18 
E.3 
Adverse events ...................................................................................................................... 18 
E.3.a 
Severity ........................................................................................................................... 18 
E.3.b 
Association ...................................................................................................................... 18 
E.3.c 
Documentation ................................................................................................................ 19 
E.3.d 
Reporting ......................................................................................................................... 19 
E.4 
Confidentiality ........................................................................................................................ 19 
F. Ethical and Regulatory Considerations ........................................................................................... 19 
F.1 
Institutional Review Board ..................................................................................................... 19 
F.2 
Informed Consent .................................................................................................................. 19 
F.3 
Compliance Monitoring .......................................................................................................... 20 
F.4 
Data and Safety Monitoring Plan ........................................................................................... 20 
G.  LITERATURE CITED .................................................................................................................. 22 
 
 
 

 
 
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A 
PROJECT OVERVIEW 
A.1     Title  
Addressing Obesity to Reduce Cancer Risk and Health Disparities in Rural Ohio: Home-based Exercise in 
Rural Ohio (HERO) Study 
 
A.2 
Overview 
Home-based Exercise in Rural Ohio (HERO) is a single-blind, 2-arm randomized controlled pilot weight loss trial 
designed to establish the feasibility of a 15-week telephone-based weight loss intervention with tailored 
strategies for rural populations with a novel point-of-care approach to assess body composition, lipid profiles, 
and inflammatory markers. Up to 50 overweight or obese rural Ohio residents will be randomly assigned to a 15-
week telephone-based weight loss (n=30) or an active control group (up to 20). We will utilize a novel, portable 
3D optical imaging technology to overcome the lack of access to body composition measures through DXA. 
Together with lipid profiles measured by Cholestech LDX and inflammation markers measured by fasting blood 
draw, this study will establish a practical point-of-care approach to assess disease risk factors that could be 
implemented in rural community settings. Upon completion of this study, we will determine the feasibility and 
preliminary efficacy of a 15-week telephone-based exercise and diet intervention for weight loss and 
improvements in body composition and inflammation biomarkers among overweight and obese rural residents. 
Studying the dose-response relationship will allow us to understand the therapeutic effect of weight loss 
interventions and cancer risk, which has the potential to identify optimal lifestyle modifications to reduce obesity-
related cancer disparities. Findings from our study would provide evidence of the efficacy and therapeutic effect 
of weight loss interventions in cancer prevention in rural populations.  
 
A.3 
Specific Aims 
Obesity is the leading preventable cause of cancer. Obesity significantly elevates risk for cancers of the breast, 
colon and rectum, endometrium, liver, pancreas, and nine other sites. Residents of rural areas are considered 
medically underserved, with less access to quality healthcare and fewer health resources. Rural populations 
experience higher rates of obesity, obesity-related comorbidities and mortality, and higher cancer incidence and 
mortality compared to residents of urban areas. Obesity and poor health behaviors are major contributors to 
health disparities in rural populations. Lifestyle interventions that combine physical activity and a healthy diet for 
weight loss have favorable impacts on weight, body composition, and inflammatory markers. These outcomes 
are consistent with hypotheses from observational studies that physical activity and weight loss potentially 
attenuate the negative effects of obesity and reduce cancer risk. Although evidence-based weight loss programs 
have been implemented and showed health benefits, these programs focused on health-promoting resources 
available in urban areas. Generalizing such programs to rural populations is not feasible due to the limited access 
to recreation facilities, availability of healthy food, and the burden of travel. Additionally, rural residents differ from 
urban counterparts in terms of barriers, self-efficacy, and social support for health behaviors due to their unique 
personal (e.g., family roles, living priorities) and environmental (e.g., limited resources for self-health) factors. 
Therefore, the development of tailored lifestyle interventions to meet the specific needs of rural populations can 
facilitate the improvement of health behaviors and ultimately reduce cancer-related health disparities. 
To achieve our long term goal of integrating lifestyle modifications to reduce cancer risk and related disparities 
for rural populations, understanding the underlying biological mechanism of weight loss, body composition, and 
inflammation is critical. However, empirical evidence documenting the efficacy of lifestyle weight loss 
interventions in rural populations is limited. Among completed or recently awarded trials (as of January 2020), 
none measured body composition and inflammation markers. Estimating the effect of lifestyle interventions on 
weight loss, body composition, and disease risk factors (inflammatory markers, lipid profiles) in rural populations 
is essential for the design and implementation of evidence-based approaches on a larger scale.  
This study will recruit up to 50 obese rural Ohio residents and randomly assigned to a 15-week telephone-based 
weight loss (n=30) or an active control group (up to 20). The study objective is to determine the feasibility and 
preliminary efficacy of a 15-week telephone-based weight loss intervention on weight, body composition, and 
inflammatory markers, with tailored strategies and group messages to address barriers, self-efficacy, and social 
support for rural Ohio populations. We will utilize a novel and applicable point-of-care approach to assess body 

 
 
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composition, lipid profiles, and cancer risk factors in rural community settings. The Specific Aims for this study 
are: 
1. To determine the feasibility and acceptability of a 15-week telephone-based weight loss intervention 
among obese rural residents.  
We hypothesize that 80% of obese rural residents who participate in the study will complete the assigned 
intervention (feasibility), and 80% of the participants in the intervention group will engage in at least 75% 
of the weekly telephone counseling session (acceptability). During the 15-week weight loss intervention, 
we anticipate the minimal occurrence of intervention-related adverse events. 
 
2. To estimate the preliminary efficacy of the lifestyle modifications on weight loss, body composition (fat 
mass, fat percentage), inflammatory biomarkers (IL-6, TNF-α, and CRP), and other disease risk factors 
(lipid profiles).  
We hypothesize that the lifestyle intervention will result in substantial improvements in weight loss, fat 
mass, fat percentage, IL-6, TNF-α, CRP, and lipid profiles (with moderate effect size), compared to the 
active control group.   
 
B 
BACKGROUND AND RATIONALE  
B.1 
Literature Review/Current State of Knowledge   
Rural residents experience obesity-related disparities, including high rates of obesity, obesity-related 
comorbidities, cancer incidence, and premature mortality. Although evidence-based weight loss interventions 
have demonstrated health benefits in clinical settings, utilizing the same strategies may not be feasible and 
effective for rural populations due to their unique characteristics. This study aims to determine the feasibility and 
preliminary efficacy of a 15-week telephone-based lifestyle intervention combining exercise and diet for weight 
loss and improvement in body composition and inflammation biomarkers in overweight and obese rural 
populations. 
 
This project is well-aligned with the mission of the American Institute for Cancer Research (funding agency) and 
its special Cancer Prevention Research Priority as it will address how lifestyle modifications (physical activity 
and dietary restriction) can reduce cancer risk (e.g., inflammation biomarkers) through improvements in weight 
and body composition in rural populations. The following sections summarize the obesity problem in rural 
populations, past studies examining obesity, weight loss, and cancer risks, and the novelty of utilizing a point-of-
care approach to assess body composition and cancer risk factors in rural populations.   
 
B.1.a Magnitude of the problem 
Health disparities in rural populations are significant. About 97% of the U.S land is located in rural counties, and 
60 million Americans live in these areas (1). Residents in rural areas are considered underserved populations 
with lower access and fewer resources to health care, and experience higher rates of obesity, obesity-related 
comorbidities and mortality, and higher cancer incidence and mortality, compared to residents in urban areas (2-
5). Although many of the social determinants of health (e.g., low income/education, lack of health insurance) are 
linked to health disparities, obesity and poor health behaviors are the major modifiable contributors to health 
disparities in rural populations (6-10). Developing effective strategies to provide weight loss programs to promote 
healthy behaviors and reduce obesity-related cancer risk in rural populations is an important public health priority. 
 
B.1.b Obesity and cancer 
Obesity is the leading preventable cause of cancer (11). Each year more than 1,600,000 people are diagnosed 
with cancer and more than 600,000 people will die from cancer in the U.S (12). Approximately 40% of cancer 
cases and 14-20% of cancer-specific deaths are attributed to overweight and obesity (13). Obesity leads to 
abnormal and excessive adiposity accumulation, which negatively impacts metabolic and inflammatory 
processes that promote cell growth, carcinogenesis, and tumor promotion (14-18). Additionally, the dysfunctional 
adipose tissue promotes tumor progression and metastasis (17, 19). Due to these unfavorable physiological 
modifications, obesity elevates the risk of 13 cancers (17, 20-23).  

 
 
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Obesity-related inflammation is linked to elevated cancer risk, independent of obesity itself (24). The 
accumulation of adipose tissue due to obesity produces pro-inflammatory cytokines such as interleukin 6 (IL-6), 
tumor necrosis factor-alpha (TNF-α), and C-reactive protein (CRP), which subsequently affect multiple systemic 
processes and promotes various aspects of tumor growth, development, and metastasis (25). IL-6, a cytokine 
that produced up to 35% by adipose tissue, is involved in the development and growth of a variety of cancers 
through the STAT3 pathway by promoting cancer cell proliferation, survival, migration, and angiogenesis (26-
28). Elevated IL-6 is observed in several cancers (e.g., breast, colon, gastrointestinal tract, lung, ovary) and is 
correlated with cancer prognosis (29-35). TNF-α controls inflammatory cell proliferation and mediates many 
aspects of the inflammatory process, such as regulating cytokines, 
chemokines, adhesions, and pro-angiogenic activities (36, 37). Similar 
to IL-6, TNF-α stimulates proliferation, survival, migration, and 
angiogenesis in most cancer cells, leading to tumor promotion (38). 
CRP, an acute-phase protein produced in the liver and controlled by IL-
6 and TNF-α, is a stable downstream marker of systemic inflammation 
(39-41). Circulating CRP is positively associated with risks of cancers 
in the breast, colon, liver, lung, bladder, kidney, endometrium, and 
ovary (42-47). The dysregulation of these cytokines leads to 
inflammation in both local (tissue) and global (circulating in serum) 
levels, which promotes tumor growth (48).   
 
B.1.c Weight loss and cancer risk 
Weight loss may reverse obesity-related metabolic imbalances and 
chronic inflammation (49-54). Obesity-related cancer risk could be 
reduced in response to weight loss as a result of improved inflammatory 
profile (55) (Figure 1). Accumulating evidence indicates that a period 
of weight loss improves obesity-related inflammation markers, such as 
IL-6, TNF-α, and CRP (56-62). While increasing physical activity level 
alone could lead to a substantial decrease in TNF-α, lifestyle 
interventions that combine physical activity and dietary modification can 
produce a 24-31% decrease in TNF-α, 34-44% decrease in CRP, and 33-62% in IL-6 (58-62). Lifestyle weight 
loss interventions provide additional metabolic benefits on insulin, lipid profiles, and improvements in body 
composition (63-67). These outcomes are consistent with the hypotheses that weight loss, physical activity, and 
healthy diet may potentially attenuate the negative effects of obesity and reduce cancer risk and premature 
mortality (68-70).  
 
B.1.d Weight loss in rural populations  
Evidence-based lifestyle weight loss interventions have been implemented and demonstrated favorable results 
in clinical settings targeting populations with various diseases (e.g., cancer, type II diabetes, hypertension) (71-
82). These programs focused on and utilized resources in urban areas. To utilize the same intervention strategies 
from these programs may not be feasible and effective for rural populations to lose weight due to their unique 
personal (e.g., family roles, living priorities) and environmental (e.g., limited resources) factors (83-85). Barriers 
to healthy diet and the lack of recreation facilities explain variations in health behaviors in rural populations. 
These populations also have lower self-efficacy in healthy diet and exercise (i.e., belief of the ability to eat 
healthy/exercise when there are barriers), and minimal social support from family and friends to promote healthy 
lifestyle (83-85). Individuals with lower self-efficacy and social support are less likely to overcome barriers to 
achieve improvement in health behaviors (86). Self-efficacy and social support are critical in successful weight 
loss efforts by supporting the expectation, setting goals, establishing healthy dietary habits, increasing daily 
physical activity, and persistence in overcoming barriers (87, 88). However, tailored strategies to improve self-
efficacy and social support for rural populations are understudied. Moreover, although remotely accessible 
interventions are suggested to achieve more weight loss with better cost-effectiveness than face-to-face 
interventions in rural areas (89, 90), web-based interventions have not provided clinically meaningful weight loss 
(91). Therefore, the proposed study, HERO, will include a telephone-based weight loss intervention, specifically 
focused on improving self-efficacy and increasing social support to help rural populations overcome barriers, 

 
 
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improve healthy diet and physical activity, and maintain a healthy weight, with the goal of reducing obesity-
related cancer risk and health disparities.   
 
B.1.e  A Point-of-care Approach to Assess Body Composition and Cancer Risk in Rural 
Populations 
The significance of the HERO study is enhanced by the potential to develop a more applicable point-of-care 
approach to assess body composition, lipid profiles, and cancer risk factors in rural populations, in addition to 
translating an evidence-based lifestyle program with the integration of tailored strategies. Body mass index (BMI) 
is limited as a measure of adiposity, as it does not truly reflect body fat and fat distribution (92).  Measures of 
body fat are more relevant to assessing cancer risk, as adiposity deposition is associated with inflammation and 
carcinogenesis (93, 94). Dual-energy X-ray absorptiometry (DXA) is a standard measure of body composition 
that provides estimates of fat, bone, and bone-free lean mass (95). DXA-derived fat mass is positively associated 
with risk of breast cancer, independent of BMI and other risk factors (96-99). Rural populations may differ from 
the general population in the physiological response to lifestyle interventions due to variations in perceived 
stress, depressive symptoms, and other life stressors. However, among the handful of lifestyle weight loss 
interventions in rural populations, completed or recently awarded trials, none measured body composition (91, 
100). This might be due to the access burden of standard measurement of body composition (e.g., DXA) in rural 
community settings. In order to provide body composition measures for rural populations, the HERO study will 
use a novel, portable 3-Dimension (3D) Body Scanner, Styku S100 (Styku LLC, Los Angeles, CA), to assess 
body measurements, including fat mass and fat percentage, in rural community-settings. Together with lipid 
profile measured by finger stick and inflammatory markers measured by fasting blood draw, the proposed study 
will provide preliminary data from a lifestyle weight loss intervention on weight, body composition, and 
inflammatory markers in rural populations. We will estimate the preliminary efficacy of lifestyle modification on 
weight loss, body composition, and inflammatory markers among overweight/obese rural residents. Findings 
from the HERO study will serve as preliminary data for a large-scale randomized controlled trial to quantify the 
therapeutic effect of weight loss interventions and cancer risk in rural populations, with the goal to identify optimal 
lifestyle modifications to reduce obesity-related cancer disparities. 
 
B.2 
Preliminary Studies  
Previous weight loss interventions conducted by the P.I., Dr. Focht, 
have focused on disease prevention and health promotion in 
various populations. The current and previous NIH funded 
randomized controlled weight loss trials (Comprehensive Lifestyle 
Intervention 
Program 
for 
Knee 
Osteoarthritis 
Patients, 
R01AG050725; Feasibility of An Exercise and Dietary Intervention 
in Men on Prolonged Androgen Deprivation Therapy, IDEA-P trial; 
R03CA16296901) have demonstrated a strong interdisciplinary 
team with extensive experience in design/delivery of weight loss 
program (Figure 2). The Co-I of this proposed project, Dr. Electra 
Paskett, is a nationally recognized investigator in health disparities. 
Her research with underserved populations established the 
expertise and capability to conduct studies in disease prevention, 
health disparities, and improving access in underserved areas, 
including a faith-based weight loss program in Appalachian states 
(The Walk by Faith Trial; U54 CA153604) and the Rural Interventions for Screening Effectiveness (RISE; R01 
CA196243). The RISE Project recruited 1039 participants from rural Ohio and Kentucky who had complete data 
on height and weight and agreed to be contacted about opportunities for future research. About 573 of them live 
in northwest rural Ohio, and 330 had a BMI≥ 25 kg/m2. We anticipate at least 40% of these participants would 
be willing to participate in this study.     
 

 
 
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C 
RESEARCH DESIGN AND METHODS  
C.1  
Overall strategy.   
This study is a single-blind, 2-arm randomized controlled pilot study designed to determine the feasibility and 
preliminary efficacy of a 15-week telephone-based weight loss in obese rural populations. Up to 50 obese rural 
Ohio residents will be randomly assigned to a 15-week telephone-based weight loss group (n=30) or active 
control group (up to 20). The primary outcome of this trial is the feasibility of a 15-week telephone-based weight 
loss intervention. The exploratory outcomes include changes in weight, body composition, lipid profiles, and 
inflammatory markers (CRP, IL-6, and TNF-α). Exploring the efficacy of the telephone-based intervention on 
weight loss, body composition, lipid profiles, and inflammatory markers will provide preliminary effect estimates 
for future larger-scale randomized controlled trial in rural populations. 
 
C.2 
Research Team 
C.2.a  Research role and responsibilities 
Overall study responsibility belongs to Drs. Focht and Paskett, Co-PIs of the study (Table 1). Dr. Focht and his 
research team will be responsible for day-to-day study oversight including obtaining regulatory approval, 
screening/recruiting participants, obtaining informed consent, conducting in-person assessments, deliver 
intervention, and data management activities. Dr. Paskett will be responsible for the refining the study materials 
and supervising the recruitment process. Dr. Heymsfield will serve as the team consultant to provide expertise 
on body composition assessment using the 3-D body scanner.  
 
Table 1. Research Role and Responsibilities 
Research Role 
 
Responsibilities 
Investigators 
Dr. Focht (PI) 
Dr. Paskett (Co-PI) 
Oversee study progress 
Project manager 
Xiaochen Zhang 
Obtain regulatory approval, screen and recruit 
participants, obtain informed consent, schedule 
and deliver intervention, and manage data 
collection and analysis 
Health coaches 
Zachary Chaplow, Victoria 
DeScenza, Alyssa Dispennette, 
and other OSU Kinesiology 
students with training in exercise 
physiology and behavioral changes 
and experience in weight loss trials 
Screen and recruit participants, obtain informed 
consent, and deliver intervention (go through the 
exercises, provide behavioral change techniques 
and strategies, and moderate group messages) 
Other research 
staff 
Jessica Bowman and other OSU 
Kinesiology staff/students with 
training in exercise physiology and 
experience in weight loss trials 
Screen and recruit participants, obtain informed 
consent, conduct in-person assessments 
Dietitian  
OSU staff with background in 
nutrition  
Provide dietary counselling to participants when 
needed 
Consultant  
Dr. Steve Heymsfield (from 
Pennington Biomedical) 
Consult on body composition measures using 3D 
body scanner  
 
C.2.b  Research team training 
Prior to the initiation of the project, all research staff will receive standardized training to ensure that the activities 
of the study are conducted in a uniform, safe, confidential and secure manner. All research staff will attend a one 
hour long training using slides and manuals developed for prior studies and will be modified for the current study. 
Contents covered in the training session will include: 1) overview of study objectives; 2) description of study 
groups and interventions; 3) protection of human  subjects,  HIPAA,  and  confidentiality  issues;  4)  cultural  
sensitivity;  5)  roles  and  responsibilities; 6)  documentation  and  reporting  requirements;  7)  data  monitoring  

 
 
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and  quality  assurance  procedures; 8) handling problems/questions during recruitment/data collection; 9) 
effective communication techniques; and 10) use of the REDCap for data entry.  
 
The success of a weight loss intervention is dependent upon the health coaches’ ability to communicate with a 
wide range of people and in the culturally accepted vernacular. Personal skills such as the ability to be 
empathetic, patient, and caring are important when it comes to helping participants understand and comply with 
behavioral changes. Health coaches trained by Dr. Focht in exercise physiology and behavioral change, and 
have experience in weight loss trials will deliver the intervention to participants. All health coaches will take a 
refresher training before study started. The refresher training will include information about concept and 
strategies of behavioral intervention, principle and goals of physical activity and dietary modification, and ways 
to overcome barriers to behavioral change. Health coaches will also be trained in communication, consistency, 
and collaboration in the rural community and cultural setting. 
 
In addition to the one-hour training, research staff will be trained using standard protocols for assessments, 
including measuring weight, height through scales, body composition via 3D body scanner, and timed fitness 
performance. In terms of colleting blood samples, research staff will be trained to use finger stick using 
Cholestech LDX. Only research staff who are certified phlebotomists will conduct blood draw. Following the 
training session, research staff will role-play and receive feedback until they have reached 100% compliance 
with recruitment, assessment, and data collection integrity. 
 
C.3 
Study Population 
C.3.a  Rural Ohio  
Within Ohio, 50 of the total 88 counties (56.8%) are considered rural according to Rural-Urban Continuum Codes 
(RUCC). These counties have a population of about 2.3 million, most of whom are Caucasian. Our study will 
target adults 20-64 years old who reside in rural Ohio counties. We will enroll up to 50 adults 20-64 years of age 
in the designated counties.  
 
C.3.b Eligibility Criteria 
Inclusion Criteria: 1) BMI≥ 25kg/m2; 2) Age ≥20 years and <65 years; 3) Not currently participating in any weight 
loss intervention or meeting the 2018 Physical Activity Guidelines for Americans (150 min/week of moderate-
intensity exercise or 75 min/week of vigorous exercise); 4) Ability to walk two city blocks (about 400 steps) 
comfortably; and 5) Ability to speak and read English. 
 
Exclusion Criteria: 1) Prior cancer diagnosis (except non-melanoma skin cancer) or severe medical conditions 
such as unstable cardiovascular disease or digestive disorders that would preclude physical activity and dietary 
intervention; 2) pregnant or nursing women (if one becomes pregnant over the course of the study, she will be 
asked to report to research staff); and 3) unable to give informed consent. 
 
Potential participants will be screened for eligibility by phone or online survey. To determine whether an 
interested individual should consult with his or her physician before beginning an exercise program, potential 
participants who self-reported to have pre-existing health conditions (e.g., heart problems, insulin-dependent 
diabetes, poorly controlled blood pressure, other severe disease) will be asked to obtain medical clearance 
before enrollment. For potential participants who self-reported any health condition that may preclude them from 
the exercise/dietary modification (e.g., poorly controlled blood pressure, insulin-dependent diabetes, any heart 
disease, or any other severe disease), we will ask their permission to contact to their physicians to obtain medical 
clearance. Their physicians must fax, email or mail a medical clearance form (see 10. Medical Clearance Form) 
to OSU by baseline assessment so that the individual can participate in the study. If physicians indicated the 
participant is not eligible for our study, we will contact the participants by phone/email to inform their ineligibility 
(see 1d. Not eligible from physician clearance). 
 
Eligible participants will be grouped by their residency locations (e.g., county, geographic region) to schedule in-
person assessments (baseline and 15-week). To optimize retention and maintain data fidelity, all assessments 

 
 
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will be obtained on-site at community locations (e.g., library, Area Health Education Center) close to participants' 
homes by trained study staff. 
 
C.3.c Recruitment 
We will recruit up to 50 overweight/obese rural residents through social media (i.e., Facebook), flyers, and a list 
of participants from a previous study (The RISE Project). We anticipate to screen 9-15 individuals per week and 
recruit 4-5 participants per month. 
 
C.3.d Randomization  
Participants will be randomized to either the weight loss intervention group (Telephone-based health counselling) 
or the active control group (Health education) using block randomization in 4-5 waves. Every 6-12 participants 
consented and enrolled, one wave will be formed. For each wave, participants will be assigned to either weight 
loss (n=30) or active control group (up to 20 participants).  
 
C.3.e Informed consent process 
After confirming eligibility for the trial, each participant will be given a unique study number. The research staff 
(see table 1 for details) will explain all aspects of the study in lay language and answer all the candidate’s 
questions regarding the study.  The individual will be asked to provide written informed consent to participate in 
the study. If an eligible participant refuses to provide written consent, the research staff will not proceed with the 
baseline assessment. The research staff will follow talking points that will outline all of the requirements of the 
study and will cover the content of the informed consent form. The participants will be given a copy of the 
informed consent document for their records and afforded the opportunity to ask questions and have them 
answered to their satisfaction. Once the individual fully understands each element of the consent and the study, 
including the purpose, requirements, risks, confidentiality, right to withdraw, and contact person, then he/she will 
be asked to provide consent. The screening process will take approximately 5 minutes, and the informed consent 
process could take up to 15 minutes to complete. 
 
The consent process will be documented in detail including any questions asked by the individuals and the 
responses provided by research staff. The research staff will date and sign the documentation. In addition, the 
time the consent process began and ended will also be documented. Prior to the beginning the baseline 
assessment, participants will be asked once again if they understand the requirements of the study and if they 
wish to continue. Any subsequent changes to the informed consent process will be submitted to the OSU IRB 
for approval prior to activation. 
 
Participants assigned to the weight loss group will notify the research study staff of any pre-existing medical 
conditions, including injuries and recent surgeries, at baseline before they start the weight loss intervention and 
will inform the research study staff should they experience any medical problems, including injuries, over the 
course of the weight loss program. Their responses at baseline and throughout the weight loss intervention will 
be recorded on an Adverse Events Log.  
 
C.4 
Weight Loss Intervention 
C.4.a Overview 
The proposed weight loss intervention is a 15-week telephone-
based, multi-component approach adapted from the Healthy 
Living and Eating Program  (73), which was designed for 
cancer patients. We will modify the program from the in-person 
group sessions to a remotely accessible telephone-based 
intervention to reduce the burden of travel for rural populations 
and transform the program from a cancer patient’s focus to one 
of a general population with obesity. Participants randomized 

 
 
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to the weight loss group will receive weekly telephone sessions led by health coaches with a background in 
exercise physiology and behavioral weight loss interventions for 15 weeks to achieve a 7% weight loss goal. 
Participants will be encouraged to lose weight through a modest restriction in caloric intake (500-1000kcal/day) 
that gradually progresses towards a personalized, target daily caloric intake goal (1200-1800 kcal/day) and 
concomitant increase in energy expenditure via physical activity including aerobic exercise and resistance 
training (Table 2). Participants will be asked to self-monitor dietary intake and physical activity through a paper 
food log or MyFitnessPal on a daily basis. They will also receive a lifestyle modification manual (will be submitted 
in the first amendment) based on the Health Living and Eating Program and the Look AHEAD study to guide 
behavioral changes with weekly goals  (73, 101).  
 
C.4.b Dietary Component 
During the weekly telephone session, participants will receive dietary recommendations tailored to their current 
weight and weight loss target. The specific dietary objectives will be consistent with recommendations from the 
American Institute of Cancer Research (AICR)  (102). The AICR nutrition guidelines were selected to be 
implemented in the dietary portion of the intervention because: a) of their value for offsetting adverse changes 
in body weight, body composition, and metabolic and inflammatory markers; b) they are the most 
comprehensive, scientifically-based cancer prevention guidelines available; and c) the education materials 
available from AICR in support of their guidelines are clear, easy-to-follow and very consumer-friendly.   
 
The dietary intervention encourages reductions in portion size and caloric and fat consumption together with a 
gradual transition from an animal-based diet to a more plant-rich diet while still incorporating animal foods, 
including milk and meat, with an emphasis on monitoring food proportion and portion size. Specifically, the dietary 
component includes: 1) reduction in energy intake by 500-1000 kcal per day; 2) reduction in total fats to 25-30%, 
saturated fats to 7%, and protein to 15% of total calories; 3) increase in fruit and vegetable consumption to 5 
servings per day; 4) intake of 3 or more servings per day of whole grains and a gradual increase to at least 25 
grams of dietary fiber per day, and 5) increase water intake.  
 
The weekly intervention on dietary intake will use a motivational interviewing approach.  This technique has been 
extensively used in substance abuse counseling and recently, has been applied to diet-related behavior change. 
Motivational interviewing has been demonstrated to be an effective communication method to promote behavior 
change in various populations  (103, 104). Additionally, participants will receive tailored dietary strategies built 
upon many of the cognitive-behavioral self-management techniques utilized in the behavioral exercise 
counseling component, including self-monitoring, building self-efficacy, goal setting, and anticipating and 
overcoming barriers to dietary behavior change. Dietary consultations will be provided by a registered dietitian 
to participants, as needed.  
 
C.4.c Physical activity component 
A combination of home-based aerobic and resistance exercise will be described through a lifestyle modification 
manual and telephone counseling. The goal of physical activity will be to achieve 150-200 min/week moderate-
intensity aerobic physical activity and 2-3 sessions/week resistance training. The aerobic physical activity 
consists of gradually progressing from 10-30 minutes of exercise on most, if not all days of the week, with a 
primary focus placed upon brisk walking as the primary accessible mode of aerobic exercise for each participant. 
However, participants are encouraged to engage in their preferred choice of exercise mode that they are able 
and willing to perform including brisk walking, running, or cycling. The home-based resistance exercise involves 
performing 1-3 sets of 8RM-12RM repetitions of various exercises (e.g., sit-to-stand, standing leg curl, seated 
leg extension, chest press, lateral raise, bent-over row, straight-arm pulldown, arm curl, triceps pushdown, and 
chair abdominal curls) using body weights and resistance bands (see exercise manual). All exercise 
prescriptions were appropriately modified for safe and effective home-based exercise.  
 
During the telephone counseling in the first two weeks, health coaches will go through the exercises described 
in the lifestyle modification manual with each participant, and if needed, modifications of the exercises will be 
provided. Participants will be provided an exercise manual and access to online YouTube videos (as another 
option) that demonstrate safe, effective techniques for each of the prescribed exercises, provide examples for 

 
 
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alternative exercise options, and provide simple tips for proper exercise form. These videos have been 
successfully implemented to facilitate home-based exercise in prior lifestyle interventions led by the investigative 
team. Each week participants will gradually increase their exercise duration and intensity in increments of 10-30 
min until attaining the target physical activity volume goal. 
C.4.d Behavioral component 
Each week, participants will receive a 30-45 minute telephone counseling session that provides behavioral 
change techniques tailored to rural populations using the contemporary principles of cultural-tailoring and Social 
Cognitive Theory  (105), and focus on motivation, relapse prevention, emotional distress, time management, and 
overcoming barriers. Each session will include a review of the previous week’s activity, planned weekly lessons, 
dietary and exercise goals for the subsequent week, and strategies tailored to each participant to improve self-
efficacy, social support, and overcome barriers. Additionally, group messages following the weekly telephone 
counseling is integrated with the behavioral component to promote independent adherence to lifestyle 
modification.  
 
Participants will also receive a physical activity tracker (e.g., Fitbit) and a weight scale. Participants will learn 
how to use the Fitbit and will wear it during the entire study period. Participants will learn how to conduct self-
measurements and record body weight each week, as well as set up MyFitnessPal (or using paper log) to self-
monitor dietary intake and physical activity throughout the 15-week study period.  
 
The objective of the behavioral component is to promote increased self-efficacy and social support for lifestyle 
modifications and gradually facilitate participants’ transition toward successful independent self-regulation of a 
healthy diet and physical activity. The behavioral component focuses upon the acquisition and practice of self-
regulatory skills in conjunction with a continuous problem-solving model of behavior change to empower 
participants to exert greater control over their behavior, cognition, and environment. The behavioral component 
is designed to: a) increase health knowledge of the benefits of physical activity and dietary modifications; b) 
enhance self-efficacy and positive outcome expectancies through the promotion of a series of successful 
experiences in changing exercise and eating behavior; and c) improving self-regulation of exercise and eating 
behaviors through the use of goal-setting, self-monitoring, stimulus control, cognitive restructuring, and barrier 
problem-solving strategies. The efficacy of this approach for promoting adoption and maintenance of exercise 
and dietary behavior change has been demonstrated in prior randomized controlled trials that Dr. Focht has 
served as principal and co-investigator on other studies  (106-109). 
 
C.5 
Active Control Group 
At the beginning of the study, participants randomized to the active control arm will receive education brochures 
(will be submitted in the first amendment) describing the American Institute for Cancer Research physical activity 
and dietary guidelines. Participants will be asked to meet the 2018 Physical Activity Guidelines for Americans 
(150 min/week of moderate-intensity exercise or 75 min/week of vigorous exercise), and increase fruit and 
vegetable intake, reduce fat intake, reduce sugary drink, increase consumption of whole grain, and increase 
water intake. An exercise manual with access Online YouTube videos (as another option) will be available as 
examples for proper exercise form for strength training. We will also encourage them to self-monitor weight, 
dietary intake, and physical activity through MyFitnessPal or paper log. To achieve the retention and provide 
motivation and strategies for behavioral change in the active control group, participants will receive a Fitbit and 
the lifestyle modification manual at the end of the study. 
  
C.6 
Covid-19 Safety Protocols and Planning 
In order to minimize risk of exposure in research activities conducted during the COVID-19 pandemic, we will be 
using multiple strategies that align with OSU Office of Research recommendations included in the Staged 
Reopening Plan guidance including: a) Promote healthy hygiene practices including frequent and thorough hand 
washing and hand sanitizer; b) Maintain recommended social distancing during all in-person research 
assessments; c) Limit personnel to no more than 1 person per 150 sq ft; d) Staggered scheduling of research 
staff and assessment visits will be enacted to maintain social distancing protocols; e) Assessment visits will be 
scheduled in a manner that limits the amount of time spent on campus or in the field to absolute minimum needed 

 
 
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to accomplish research and continue to work remotely as much as possible. In this regard, during the ongoing 
pandemic, in-person contacts are limited to outcome assessments which significantly reduces time spent in the 
labs and/or field settings by participants and personnel. Self-report measures will be completed via virtual and/or 
mail to reduce in-person contact time; f) PPE including masks, face shields, and gloves will be worn during 
contact to limit risk of virus spread; Homemade or cloth masks are accepted; g) Use of a Daily symptom log for 
all participants and personnel- fever of 100.4 over the past 24 hours, symptoms related to COVID, or suspect 
they may have been exposed within the recent 14 days should stay home and call PCP; h) Clean and disinfect 
using approved disinfectant cleaners for all lab/office surfaces that require contact (desk, keyboard, ipads, doors, 
etc) before and after each required activity in assessment visits ; i) Personnel must remove one glove when 
opening doors, pushing elevator buttons, etc to avoid cross contamination; j) Our designated investigative team 
will coordinate all scheduling and oversight of research activities in consultation with PI (Dr. Brian Focht) to 
reduce overlap of researchers in a given space; j) Log time of entry, time of departure, and temperature; and k) 
Participants will not have anyone accompany them to assessments unless they require assistance. 
 
C.7 
Assessment  
Outcome assessments will be obtained at baseline and 15 weeks later at in-person visits by research staff 
blinded to treatment group assignment. All outcome assessments will be conducted at a community center or 
public location convenient to the participant. Each outcome measure will be collected through paper or online 
survey (through REDCap) and stored in REDCap (Research Electronic Data Capture).  
C.7.a Primary Outcome: feasibility and acceptability 
Completion rate and participation of the weekly telephone counseling session will be measured to evaluate the 
feasibility and acceptability of the 15-week telephone-based weight loss intervention. 
 
C.7.b Secondary Outcome Assessment 
Self-reported questionnaires and objective measures by research staff will be used (Table 3). 
 
Table 3. Assessment Approach 
 
Assessment 
Approach 
Time 
Weight, height 
Research staff using weight scale 
2 mins 
Body composition 
Research staff using Styku 3D body scanner 
10 mins 
Hydration status 
Research staff using urine specific gravity 
3 mins 
Lipid: Total cholesterol (TC), triglycerides 
(TG), high-density lipoprotein cholesterol 
(HDL-C), and low-density lipoprotein 
cholesterol (LDL-C) 
Research staff (with training) using Cholestech 
LDX 
3 mins 
Inflammatory markers: C-reactive protein 
(CRP), Interleukin (IL)-6, TNF-α 
Research staff (certified phlebotomists) 
conducting blood draw 
5 mins 
Objectively measured physical activity 
Participants will wear ActivPAL for 7 days 
-- 
IPAQ Leisure-Time Exercise 
Questionnaires  
Self-reported via paper or online survey 
5 mins 
Diet diary (developed by NCI) 
Self-reported via paper for 7 days 
-- 
Healthy eating and weight SE 
questionnaires 
Self-reported via paper or online survey 
5 mins 
Multi-dimensional Self-Efficacy scales 
Self-reported via paper or online survey 
5 mins 
Social Support Inventory for Physical 
Activity 
Self-reported via paper or online survey 
5 mins 
Social Support Inventory for Healthy eating Self-reported via paper or online survey 
5 mins 
Physical Fitness 
Research staff (with training) using standard 
protocols 
15 mins 

 
 
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1. Anthropometric assessment 
Body weight (kg) and height (cm) will be measured to calculate BMI (kg/m2).  
 
2. Body composition 
Fat mass (kg), fat%, lean mass (kg), lean% will be measured using a 3-Dimension (3D) Body Scanner, Styku 
S100 (Styku LLC, Los Angeles, CA). The Styku S100 scanner uses an infrared camera built into a tower and a 
rotating platform to capture body circumference and 
volumes. Participants will stand on the platform with their 
arms positioned in the A-pose and then will be rotated 
clockwise. The Styku S100 scanner uses Microsoft Kinect 
Fusion software to recognize body landmarks, which are 
used to calculate and visualize various body measurements  
(110). The Styku S100 scanner produced reliable 
measures of body composition compared with dual-energy 
X-ray absorptiometry (Figure 3). Most importantly, the 
Styku S100 scanner is feasible to use in rural community-
settings because of its portable size and ease of 
assembling (Figure 4).  
 
3. Hydration 
Proper hydration is critical for collecting blood samples through finger stick and venipuncture. In 
addition, inflammatory markers are sensitive to hydration status. Therefore, to ensure proper 
hydration, participants will be asked to consume 2 cups of water the night before the assessment and 
another 2 cups the morning of the assessment. Urine samples will be checked for urine-specific 
gravity (USG) using a refractometer. A USG<1.025 indicates euhydration.   
 
4. Lipid profile 
Total cholesterol (TC), triglycerides (TG), high-density 
lipoprotein cholesterol (HDL-C), and low-density lipoprotein 
cholesterol (LDL-C) will be obtained by fasting capillary 
blood sampling from fingerstick and analyzed using 
Cholestech LDX (Hayward, CA). The Cholestech LDX has 
demonstrated the accuracy and precision to assess blood 
lipid  (111, 112). It is a point-of-care assessment to screen 
abnormal blood lipid in clinical, community, and other health 
promotion settings  (113, 114). The Cholestech LDX 
provides lipid profiles result within 5 minutes, which will 
allow research staff and participants to receive results at the 
same visits.  
 
5. Inflammatory markers 
All participants will undergo a fasting (≥6 hr) blood draw (50mL per assessment). Plasma samples will be stored 
at -80°C until assayed. C-reactive protein (CRP) concentration (ng/L), Interleukin (IL)-6 concentration (pg/mL), 
and TNF-α will be quantified with electrochemiluminescent multiplex immunoassay platform (Meso Scale 
Discovery, MSD).  
 
6. Physical activity 
Objectively-determined minutes of PA participation will be assessed and  The ActivPAL captures free-living 
sedentary and ambulatory PA and is well-established as one of the most accurate wearable activity monitors  

 
 
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(115). The monitor will be set to collect PA data using the manufacturer settings and is affixed to the midline of 
patients’ right thigh in a waterproof pouch allowing for continuous wear time. Participants will be provided verbal 
and written instructions on how to wear the ActivPAL and wear the monitor 24 hours per day for the 7 consecutive 
days following the completion of the study assessment visits. In the event of wear time problems, patients must 
have at least 10 hours per day of wear time on 4 days of the week (including at least 1 weekend day) for a valid 
assessment. Monitors will be returned to trial staff via U.S. postal service.  
 
Participants will also complete self-reported Leisure-Time Exercise Questionnaires  (116) in the 1st and 15th 
week. 
7. Dietary intake 
All participants will complete 7-day food checklist for at the 1st and 15th week. This food checklist was developed 
by the National Cancer Institutes that comprised of a list of foods. Over the course of a day, participant makes a 
check beside a food each time she or he eats it. It yields estimates of macro nutrient intake, as well as intake by 
specific food groups. Participants in the weight loss intervention will also be encouraged to complete daily food 
log using MyFitnessPal (or paper log) during the trial. The food log and weekly summary of caloric and 
macronutrient intake will be regularly monitored by the trial’s staff and registered dietitian to track adherence.  
 
8. Self-Efficacy and Social Support 
Participants will be asked to complete self-reported Healthy Weight and Eating Self-Efficacy, Multi-dimensional 
Self-Efficacy scales  (117-119), as well as adapted Social Support Inventory for Physical Activity (SSPA) and 
Eating Habits (SSEH) questionnaires  (120, 121).  
 
9. Physical fitness 
Participants will be asked to complete valid and reliable timed performance-related mobility tasks, such as 400-
meter walk and lift and carry task  (122-125). These assessments at baseline will serve as a reference to tailor 
exercise counseling for each participant.  
 
C.9. Timeline 
Database development and personnel training will 
occur in the first 2 months of Year 1 (Table 4). 
Participant recruitment, with a target accrual of 4-5 
participants per month, will begin month 3 of Year 1 
and continue through month 7 of year 2. The 
intervention data collection will begin in Month 4 of 
Year 1 and end in month 10 of Year 2. The remaining 
3 months of Year 2 will be used for data analyses, 
presentations, and manuscript preparation and 
provide flexibility in the event of unexpected barriers 
encountered during data collection.  
 
C.10. Potential problems and alternative strategies 
C.10.a. Recruitment 
Rural residents may experience the burden of travel, limited affordable healthy food options, and fewer exercise 
facilities. We opted to use a telephone-based weight loss intervention to reduce the burden of travel to a face-
to-face program. Our research team has been successful in conducting studies in rural populations, which allows 
us to contact participants from previous research (RISE) to achieve our recruitment goal. Although RISE 
participants are all women, we anticipate enrolling men by other recruitment approaches, such as community 
events. As the primary aim of the proposed study is the feasibility, not generalizability, the representation of 
participants’ sex is not our focus.  

 
 
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C.10.b. Intervention 
We have access to an in-house registered dietitian who will provide participants with resources and strategies 
to optimize their food selections and improve dietary intake as needed. If, during the 15-week intervention, 
participants experience barriers to exercise facilities, we would expand exercise options, including an exercise 
manual with home-based alternative exercises, and access to online YouTube videos (as another option), to 
allow participants to utilize more resources to complete the moderate-intensity exercises.  
C.10.c. Assessment 
We considered using a standard measure of body composition using Dual-energy X-ray absorptiometry (DXA) 
but opted not to as this is likely to add the burden of travel to facilities equipped with DXA. However, we will 
assess body composition using a 3-D Styku body scanner, which is portable to rural community-settings and can 
provide valid and reliable data on body composition. Together with using Cholestech LDX to evaluate 
participants’ lipid profiles, the proposed study is innovative to test new point-of-care approaches to assess 
disease risk factors in rural populations. 
 
D 
DATA HANDLING AND ANALYSES  
D.1. 
Outcome Analysis Plan 
D.1.a Primary outcome 
The feasibility of completing the study is defined as the percentage of enrolled participants who complete the 
study. If we observe an 80% completion rate in the weight loss intervention group (n=30), the 85%, 90%, and 
95% confidence intervals (CIs) for the completion rate would be (69.5, 90.5), (68.0, 92.0), and (65.7, 94.3), 
respectively. If the true completion rate is 80%, we have 95% power to rule out the unacceptable 50% completion 
rate with 95% confidence (one-sided).  
 
The acceptability of the weight loss intervention is the percentage of participants in the weight loss intervention 
group who engage at least 75% of the weekly telephone counseling session. Intervention-related adverse 
events, satisfactory, and other feasibility assessments, such as the percent of initial contact to enrollment, 
reasons for consent refusal, barriers to adherence to weekly goals, and reasons for drop-out will also be 
assessed. 
 
D.1.b Secondary outcome 
Significance test for the preliminary efficacy of the lifestyle intervention will quantify the difference in means using 
repeated measures analysis of variance (ANCOVA) statistical model to adjust baseline values and control for 
the effect of age. The sample size of 30 participants in the weight loss group and at least 15 in the active control 
group is feasible to recruit for a pilot/preliminary efficacy study that accounts for a projected attrition rate of 20% 
yet also still provides adequate power to detect meaningful, moderate to large effect size (0.54-0.72) on weight 
loss, body composition, inflammatory markers, and lipid profiles.  
 
Analyses will be conducted using the intention to treat principle with last value carried forward approach used to 
account for data missing due to participant attrition. Exploratory analyses will compare outcomes including weight 
loss, changes in body composition, changes in physical activity and dietary intake, changes in lipid profiles and 
inflammatory biomarkers between the telephone-based weight loss group and the active control group. We will 
also examine whether social support and self-efficacy changes among participants from the weight loss group. 
These exploratory analyses will provide effect size estimates to inform the development of a large-scale phase 
II randomized controlled lifestyle weight loss intervention trial.  
 
D.2. 
 Data Management  
As mentioned above, we will use REDCap as our data entry system. It will be used to store the baseline and 
follow-up questionnaires, will work directly with the OSU CCTS Research Informatics Services Core and will be 

 
 
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used as a central location for data processing and management. Vanderbilt University, with collaboration from a 
consortium of institutional partners (including OSU) and the NIH National Center for Research Resources, has 
developed a software toolset and workflow methodology for electronic collection and management of research 
and clinical trial data. REDCap data collection projects rely on a thorough study-specific data dictionary defined 
in an iterative self-documenting process by all members of the research team with planning assistance from the 
CCTS Research Informatics Services Core. As part of the data dictionary development process, individual fields 
can be denoted as “identifiers”. When exporting a de-identified dataset, these variables are omitted. Additionally, 
the data export tool also allows shifting of dates for a limited data set export. REDCap provides a secure, web-
based application that is flexible enough to be used for a variety of types of research, provides an intuitive 
interface for users to enter data and has real time validation rules (with automated data type and range checks) 
at the time of entry. It offers easy data manipulation with audit trails and ad hoc reporting functionality for 
reporting, monitoring and querying patient records, and an automated export mechanism to common statistical 
packages (SPSS, SAS, Stata, R/S-Plus). REDCap is 21 CRF Part 11 capable. Currently, REDCap installations 
support electronic signatures by positively identifying the user through a unique username and password 
combination. The provisioning of accounts and user access to specific database (s) is integrated with the OSU 
Medical Center LDAP authentication service, and the provisioning of access and specific user rights are 
managed by CCTS staff.  
 
Each participant will be assigned a unique study ID (SID) when first recruited that will follow their electronic 
information in REDCap, throughout the study. Each participant will have their own folder that will contain a copy 
of their consent documentation form, any paper format self-reported questionnaires or assessments, Medical 
Clearance (if any), and any letters sent to the participant. The folders will be stored in locked filing cabinets in a 
locked office. No information about a study participant will be given to third parties unless that subject has given 
written or witnessed consent to do so.  
Information will be obtained and maintained on all individuals screened for this study.  If available we will keep 
demographic data on those individual who are ineligible and eligible but refuse.  The data will be used to ensure 
that we do not contact individuals who are ineligible for the study or who have told us they do not want to 
participate in the study.  The data will also be used to characterize/compare this group individual to those who 
are eligible and agree to participate; it is important to determine if those who are ineligible and especially those 
who refuse to participate, are in way inherently different from the women who participate in the study.   
 
D.3. 
Record Retention 
All research records (including identifying information) will be maintained until data analysis and all manuscripts 
have been completed, or for the length of time designated by the institutional requirement and the NCI and AICR.  
Paper records will be maintained in a secured storage facility and electronic data will be stored in a password 
protected database until is appropriate to destroy the data.  The IRB at OSU, the NCI, and AICR will be notified 
of our intent to destroy the data. If required by NCI or AICR, de-identified data may be shared with the NCI and 
AICR and their data repositories. 
 
E 
HUMAN SUBJECTS  
E.1 
Anticipated Risks 
There are minimal risks associated with completing the objective and self-report measures for this study. Possible 
psychological risks may occur in that some individuals may experience some guilt or embarrassment in objectively 
measured body composition and self-reporting low levels of motivation or intention to exercise. Embarrassment or 
discomfort could occur from certain baseline or follow-up survey questions, but participants are able to skip any 
questions that they do not wish to answer. Risks anticipated with receiving the intervention materials (brochures, 
telephone-based counseling) or encouraging participants to promote healthy lifestyle are minimal. There are minor 
risks associated with venipuncture (taking blood from a vein) including mild discomfort or bruising.  Less commonly, 
a small clot, swelling of the vein, infection, or bleeding may occur at the site of puncture. 
 
There is the possibility of muscle soreness from increased physical activity. The muscle soreness may last several 
days after each exercise session, but it is not likely to be severe enough to limit activities of daily living. There is 

 
 
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also a risk of muscle injury, which may require medical attention, may take several months to heal, and may limit 
activities of daily living for a period of days, weeks, or months. Participants will be informed that there is an 
increased risk with starting a physical activity program and be advised of all of the potential risks.  Additionally, Dr. 
Focht and research staff with training in exercise physiology and behavioral changes will be directly involved in 
conducting physical fitness tests and delivering exercise components.   
 
There is a slight risk of breach of confidentiality, but steps are in place to protect participants' personal information. 
Electronic data will be stored behind a firewall and accessed only by study staff through password-protected 
computers. Paper-based data will be stored in a locked cabinet within a locked file room. 
 
Collectively, the participants will be assuming no more than minimal risk in completing the assessment protocol 
and the minimal risk inherent to completing the assessments will be mitigated via stringent pre-test medical 
screening and during testing supervision. 
 
E.2 
Benefits of participation   
Participants may gain awareness of healthy eating and physical activity from evidence-based program. 
Participants in the telephone-based counseling group will receive a physical activity tracker (e.g., Fitbit) at the 
beginning of the study, and weekly telephone-based weight loss counselling for 15 weeks. Participants in the 
active control group will also receive a physical activity tracker and lifestyle modification manual at the end of the 
study. All participants will receive regular body weight, body composition, and blood tests for lipid profiles and 
inflammatory biomarkers free of charge. 
 
E.3 
Adverse events 
Adverse events, including any unfavorable and unintended sign (e.g., abnormal laboratory finding or symptom) 
will be collected as they occur, regardless of whether it is considered related to the weight loss intervention. 
Musculoskeletal injuries and previously undocumented major medical events incurred during the intervention will 
be systematically collected on all participants during the study period using standardized forms from our prior 
work. Patients will have instructions to contact the PI or their primary health providers to discuss and manage 
any possible side effects. The PI, study coordinator should immediately be contacted in the event such a problem 
arises.   
E.3.a Severity 
1) Serious adverse event:  Any adverse event that is fatal or life threatening, is permanently disabling, requires 
inpatient hospitalization or prolongs hospitalization, or results in a congenital anomaly or birth defect; 
2) Life-threatening event:  Any adverse event in which the subject is at immediate risk of death from the reaction 
as it occurs; does not include a reaction that, if it occurs in a more serious form, might cause death; 
3) Unexpected event:  Any adverse event that is not identified in nature, severity, or frequency in the investigator 
brochure, study protocol, consent form, or IND application; or the event is more serious than anticipated. 
 
E.3.b Association 
1) Definitely Related:  An adverse event that has a timely relationship to the administration of the study 
intervention and follows a known pattern of response for which no alternative cause is present;  
2) Probably Related: An adverse event that has a timely relationship to the administration of the study 
intervention and follows a known pattern of response, but for which a potential alternative cause may be present;  
3) Possibly Related: An adverse event that has a timely relationship to the administration of the study 
intervention, follows no known pattern of response, but a potential alternative cause does not exist;  
4) Unrelated:  An adverse event for which there is evidence that it is definitely related to a cause other than the 
study intervention; in general, no timely relationship to the administration of the drug/procedure exists, or if so, 
the event does not follow a pattern of response and an alternative cause is present. 
 

 
 
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E.3.c Documentation 
The adverse event form will be used by study staff to report injuries or other adverse events reported by 
participants throughout the study. The patient will be observed and monitored carefully until the condition 
resolves, stabilizes, or its cause is identified.  All adverse events, including laboratory abnormalities, will be 
followed up according to good medical practices. Information to be recorded includes: 1) specific type of reaction; 
2) duration of reaction; 3) severity/grade of reaction according to the NCI Common Terminology Criteria for 
Adverse Events v4.0 (CTCAE); 4) suspected cause of the reaction (i.e. possibly or probably related to one of the 
following: study treatment, progression of disease, concurrent medications, concurrent illness, or other factors); 
5) changes made in the administration of the study intervention and other actions taken to alleviate the clinical 
event; and 6) patient’s response to medical interventions. 
E.3.d Reporting 
In accordance with IRB guidelines, serious adverse events will be reported within 10 days of the investigator’s 
or research staff members’ learning of the event to OSU IRB. OSU IRB Event Reports should be submitted 
through BuckIRB at: http:/orrp.osu.edu/irb/buck-IRB/. Events resulting in temporary or permanent interruption of 
study activities by the investigator or sponsor to avoid potential harem to subjects should be reported within 48 
hours whenever possible. 
 
All events that may represent unanticipated problems involving risks to subjects or others will be promptly 
reported (as described above), regardless of whether they occur during or after the study, or involve a subject 
who has withdrawn from or completed study participation. If changes to the research or consent process are 
proposed as a result of the event, or if additional information will be provided to current and/or past participants, 
a protocol amendment will be submitted for IRB review. 
 
Related events involving risk but not meeting the prompt reporting requirements will be reported to the IRB in 
summary form at the time of continuing review.  
 
E.4 
Confidentiality  
Participants enrolled the study will be assigned to a study ID. Individuals will not be identified by name or by any 
other personal identifying information in reports, or publications resulting from this study. All information will 
remain de-identified. Thus, risk of disclosure of confidential medical information will be essentially nonexistent. 
Additionally, all data will be number coded and stored in a password protected files and a locked research office 
that can only be accessed by the research staff. These procedures have been successfully used to protect 
confidentiality in our prior studies. 
Study patients may voluntarily withdraw at any time from the protocol. The reasons for discontinuation of the 
study will be documented in the patient record and data collection forms. A letter to the PI in writing  
 
F. Ethical and Regulatory Considerations 
F.1 
Institutional Review Board 
Prior to initiating the research project and conducting any research project activities the PI will obtain written 
approval to conduct the research project from the appropriate institutional regulatory bodies. Should changes to 
the research project protocol become necessary, the PI will submit protocol amendments in writing to the IRB 
for approval prior to implementation.    
 
F.2 
Informed Consent 
As noted in section 3.2.3, consent will be sought and obtained via phone and verbal consent process completed 
prior to initiating any research project procedures. Each element of the consent will be verbally explained to the 
potential participant. The woman will be given an opportunity to ask questions and have the questions answered 
to her satisfaction. Once the individual understands each element of the verbal consent, including the purpose, 
requirements, benefits, risks, confidentiality, right to withdraw, and contact person, then and only then will it will 

 
 
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be documented that the individual consented to participate in the study.  
 
F.3 
Compliance Monitoring 
In accordance with IRB guidelines, the study program will be reviewed by the IRB every 12 months or less.  
Deviations from the protocol must be documented in the medical record and reported immediately to the PI. 
Deviations that meet the criteria for Immediate Event Reporting (http://orrp.osu.edu/irb/event/index.cfm) such as 
those that increase risks to subjects and/or compromise scientific integrity will be reported immediately to the 
IRB.   
 
F.4 
Data and Safety Monitoring Plan 
We have developed a Data and Safety Monitoring Plan for this study. The purpose of the data and safety 
monitoring plan is to ensure the safety of participants, the validity and integrity of data, and the appropriate 
termination of studies for which significant benefits or risks have been uncovered or when it appears that the 
study cannot be concluded successfully. Risks associated with participation in research must be minimized to 
the extent practical and the method and degree of monitoring should be commensurate with risk. The essential 
elements of the Data and Safety Monitoring Plan include: 
1. 
Monitoring the progress of the study and the safety of participants; 
2. 
Plans for assuring compliance with requirements regarding the reporting of adverse events (AE); 
3. 
Plans for assuring that any action resulting in a temporary or permanent suspension of the study is 
reported to the appropriate agencies; and 
4. 
Plans for assuring data accuracy and protocol compliance. 
 
Prior to the initiation of the project, all project staff will receive standardized training to ensure that the activities 
of the study are conducted in a uniform, safe, confidential and secure manner. A tracking system will be put in 
place to document data collection activities, and reports will be generated on a weekly and monthly basis to 
monitor the study activities (Table 5). Meetings will take place on a monthly basis to monitor the activities of the 
project and to continually reassess the progress of the project including assessments of data quality, timeliness, 
participant recruitment, accrual, retention and monitoring of the risk versus benefits throughout the study period.  
 
Table 5. The frequency of data review  
Data Type 
Frequency of Review 
Subject accrual (adherence to protocol regarding demographics, 
inclusion/exclusion) 
Monthly 
Adverse event rates (injuries, symptom changes requiring altered exercise 
prescription) 
Monthly 
Compliance to treatment, dropout rates 
Twice per month 
 
All AEs will be reported according to the policy outlined by the OSU Institutional Review Board (IRB). The 
appropriate forms will be completed and sent in accordance to the timeline set forth by the IRB.  All AEs will be 
reported to and reviewed by the study team. The research project manager will conduct a 10% eligibility 
verification.  If a violation is noted, the research manager will document the violation and inform the project 
investigators of the matter. The appropriate action will be taken to rectify the violation and to determine what or 
if any corrective actions need to take place. All protocol violations will be documented and reported to the IRB.  
Also, any privacy violations will be reported to the IRB and the institutional privacy office. All privacy violations, 
adverse events, and protocol violations will be reported to and reviewed by the principal investigators (Dr. Brian 
Focht) and the research team, who will be responsible for reporting to the appropriate regulatory bodies at OSU.  
 
The IRB will be provided feedback more frequently if there should be any adverse events or other 
recommendations. The investigators are responsible for reporting to the NCI and AICR project director any action 
resulting in temporary or permanent suspension of the research project at OSU. These actions will be reported 
to the NCI and AICR program director within 72 hours of notification.  All documents or correspondence that are 
generated in the course of correcting or appealing the suspension status must also be forwarded to the program 

 
 
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director within 72 hours of it being presented to the institutional body that put for the directive to temporarily or 
permanently suspend the research project.  During this time no research project activities can occur.  
 
The principal investigators are responsible for submitting reports; annual reports will be sent to the OSU IRB, 
and as required by the NCI and AICR project offices. Information included in the reports will include the number 
of individuals enrolled in the study, dropout rates and any protocol deviations. 
 
 

 
 
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G. 
 LITERATURE CITED 
1. 
Bureau UC. New census data show differences between urban and rural populations.  2016. 
2. 
Befort CA, Nazir N, Perri MG. Prevalence of obesity among adults from rural and urban areas 
of the United States: findings from NHANES (2005‐2008). The Journal of Rural Health 2012;28 
(4):392-7. 
3. 
Cossman JS, James WL, Cosby AG, et al. Underlying causes of the emerging nonmetropolitan 
mortality penalty. American Journal of Public Health 2010;100 (8):1417-9. 
4. 
Harris JK, Beatty K, Leider J, et al. The double disparity facing rural local health departments. 
Annual review of public health 2016;37:167-84. 
5. 
Zhang X, Holt JB, Lu H, et al. Neighborhood commuting environment and obesity in the United 
States: An urban–rural stratified multilevel analysis. Preventive medicine 2014;59:31-6. 
6. 
Martin SL, Kirkner GJ, Mayo K, et al. Urban, rural, and regional variations in physical activity. 
The Journal of Rural Health 2005;21 (3):239-44. 
7. 
Health US. 2011: With Special Feature on Socioeconomic Status and Health.  2012. 
8. 
Hartley D. Rural health disparities, population health, and rural culture. American Journal of 
Public Health 2004;94 (10):1675-8. 
9. 
Meit M, Knudson A, Gilbert T, et al. The 2014 update of the rural-urban chartbook. Bethesda, 
MD: Rural Health Reform Policy Research Center 2014. 
10. 
Downey LH. Rural populations and health: Determinants, disparities, and solutions. Preventing 
chronic disease 2013;10. 
11. 
Ligibel JA, Alfano CM, Courneya KS, et al. American Society of Clinical Oncology position 
statement on obesity and cancer. Journal of clinical oncology 2014;32 (31):3568. 
12. 
Society AC. Cancer facts & figures 2016. Atlanta, GA: American Cancer Society, 2016. 2012. 
13. 
Steele CB, Thomas CC, Henley SJ, et al. Vital signs: trends in incidence of cancers associated 
with overweight and obesity—United States, 2005–2014. MMWR Morbidity and mortality weekly 
report 2017;66 (39):1052. 
14. 
Guilherme A, Virbasius JV, Puri V, et al. Adipocyte dysfunctions linking obesity to insulin 
resistance and type 2 diabetes. Nature reviews Molecular cell biology 2008;9 (5):367. 
15. 
Arita Y, Kihara S, Ouchi N, et al. Paradoxical decrease of an adipose-specific protein, 
adiponectin, in obesity. Biochemical and biophysical research communications 1999;257 (1):79-
83. 
16. 
Donohoe CL, Doyle SL, Reynolds JV. Visceral adiposity, insulin resistance and cancer risk. 
Diabetology & metabolic syndrome 2011;3 (1):12. 
17. 
Hursting SD, DiGiovanni J, Dannenberg AJ, et al. Obesity, energy balance, and cancer: new 
opportunities for prevention. Cancer prevention research 2012;5 (11):1260-72. 
18. 
Bray G, Kim K, Wilding J, et al. Obesity: a chronic relapsing progressive disease process. A 
position statement of the World Obesity Federation. Obesity Reviews 2017;18 (7):715-23. 
19. 
Iyengar NM, Hudis CA, Dannenberg AJ. Obesity and cancer: local and systemic mechanisms. 
Annual review of medicine 2015;66:297-309. 
20. 
Lauby-Secretan B, Scoccianti C, Loomis D, et al. Body fatness and cancer—viewpoint of the 
IARC Working Group. New England Journal of Medicine 2016;375 (8):794-8. 
21. 
Bhaskaran K, Douglas I, Forbes H, et al. Body-mass index and risk of 22 specific cancers: a 
population-based cohort study of 5· 24 million UK adults. The Lancet 2014;384 (9945):755-65. 
22. 
Mantovani A. Cancer: inflaming metastasis. Nature 2009;457 (7225):36. 
23. 
Hursting SD, Berger NA. Energy balance, host-related factors, and cancer progression. Journal 
of Clinical Oncology 2010;28 (26):4058. 
24. 
Calle EE, Kaaks R. Overweight, obesity and cancer: epidemiological evidence and proposed 
mechanisms. Nature Reviews Cancer 2004;4 (8):579-91. 
25. 
Deng T, Lyon CJ, Bergin S, et al. Obesity, inflammation, and cancer. Annual Review of 
Pathology: Mechanisms of Disease 2016;11:421-49. 

 
 
23 
 Version 1. Mar 2021 
26. 
Ghosh S, Ashcraft K. An IL-6 link between obesity and cancer. Frontiers in bioscience (Elite 
edition) 2013;5:461-78. 
27. 
Naugler WE, Karin M. The wolf in sheep's clothing: the role of interleukin-6 in immunity, 
inflammation and cancer. Trends in molecular medicine 2008;14 (3):109-19. 
28. 
Kim JH, Bachmann RA, Chen J. Interleukin‐6 and insulin resistance. Vitamins & Hormones 
2009;80:613-33. 
29. 
Okada S, Okusaka T, Ishii H, et al. Elevated serum interleukin-6 levels in patients with pancreatic 
cancer. Japanese journal of clinical oncology 1998;28 (1):12-5. 
30. 
Nakashima J, Tachibana M, Horiguchi Y, et al. Serum interleukin 6 as a prognostic factor in 
patients with prostate cancer. Clinical cancer research 2000;6 (7):2702-6. 
31. 
Dowlati A, Levitan N, Remick SC. Evaluation of interleukin-6 in bronchoalveolar lavage fluid and 
serum of patients with lung cancer. Journal of Laboratory and Clinical Medicine 1999;134 
(4):405-9. 
32. 
Li Y-Y, Hsieh L-L, Tang R-P, et al. Interleukin-6 (IL-6) released by macrophages induces IL-6 
secretion in the human colon cancer HT-29 cell line. Human immunology 2009;70 (3):151-8. 
33. 
Goydos JS, Brumfield AM, Frezza E, et al. Marked elevation of serum interleukin-6 in patients 
with cholangiocarcinoma: validation of utility as a clinical marker. Annals of surgery 1998;227 
(3):398. 
34. 
Sriuranpong V, Park JI, Amornphimoltham P, et al. Epidermal growth factor receptor-
independent constitutive activation of STAT3 in head and neck squamous cell carcinoma is 
mediated by the autocrine/paracrine stimulation of the interleukin 6/gp130 cytokine system. 
Cancer research 2003;63 (11):2948-56. 
35. 
Giri D, Ozen M, Ittmann M. Interleukin-6 is an autocrine growth factor in human prostate cancer. 
The American journal of pathology 2001;159 (6):2159-65. 
36. 
Wang X, Lin Y. Tumor necrosis factor and cancer, buddies or foes? 1. Acta Pharmacologica 
Sinica 2008;29 (11):1275-88. 
37. 
Balkwill F, Mantovani A. Inflammation and cancer: back to Virchow? The lancet 2001;357 
(9255):539-45. 
38. 
Grivennikov SI, Karin M. Inflammatory cytokines in cancer: tumour necrosis factor and 
interleukin 6 take the stage. Annals of the rheumatic diseases 2011;70 (Suppl 1):i104-i8. 
39. 
Brenner DR, Scherer D, Muir K, et al. A review of the application of inflammatory biomarkers in 
epidemiologic cancer research. Cancer Epidemiology and Prevention Biomarkers 2014;23 
(9):1729-51. 
40. 
Pepys MB, Hirschfield GM. C-reactive protein: a critical update. The Journal of clinical 
investigation 2003;111 (12):1805-12. 
41. 
Black S, Kushner I, Samols D. C-reactive protein. Journal of Biological Chemistry 2004;279 
(47):48487-90. 
42. 
Gunter MJ, Wang T, Cushman M, et al. Circulating adipokines and inflammatory markers and 
postmenopausal breast cancer risk. JNCI: Journal of the National Cancer Institute 2015;107 (9). 
43. 
Erlinger TP, Platz EA, Rifai N, et al. C-reactive protein and the risk of incident colorectal cancer. 
Jama 2004;291 (5):585-90. 
44. 
Heikkilä K, Harris R, Lowe G, et al. Associations of circulating C-reactive protein and interleukin-
6 with cancer risk: findings from two prospective cohorts and a meta-analysis. Cancer causes & 
control 2009;20 (1):15-26. 
45. 
Zeng F, Wei H, Yeoh E, et al. Inflammatory markers of CRP, IL6, TNFα, and soluble TNFR2 and 
the risk of ovarian cancer: a meta-analysis of prospective studies. Cancer Epidemiology and 
Prevention Biomarkers 2016;25 (8):1231-9. 
46. 
Wang T, Rohan TE, Gunter MJ, et al. A prospective study of inflammation markers and 
endometrial cancer risk in postmenopausal hormone nonusers. Cancer Epidemiology and 
Prevention Biomarkers 2011;20 (5):971-7. 

 
 
24 
 Version 1. Mar 2021 
47. 
Toriola AT, Cheng TYD, Neuhouser ML, et al. Biomarkers of inflammation are associated with 
colorectal cancer risk in women but are not suitable as early detection markers. International 
journal of cancer 2013;132 (11):2648-58. 
48. 
Shoelson SE, Herrero L, Naaz A. Obesity, inflammation, and insulin resistance. 
Gastroenterology 2007;132 (6):2169-80. 
49. 
Clément K, Viguerie N, Poitou C, et al. Weight loss regulates inflammation-related genes in white 
adipose tissue of obese subjects. The FASEB Journal 2004;18 (14):1657-69. 
50. 
Nicklas BJ, Ambrosius W, Messier SP, et al. Diet-induced weight loss, exercise, and chronic 
inflammation in older, obese adults: a randomized controlled clinical trial. The American journal 
of clinical nutrition 2004;79 (4):544-51. 
51. 
Lakhdar N, Denguezli M, Zaouali M, et al. Diet and diet combined with chronic aerobic exercise 
decreases body fat mass and alters plasma and adipose tissue inflammatory markers in obese 
women. Inflammation 2013;36 (6):1239-47. 
52. 
Fabian CJ, Kimler BF, Donnelly JE, et al. Favorable modulation of benign breast tissue and 
serum risk biomarkers is associated with> 10% weight loss in postmenopausal women. Breast 
cancer research and treatment 2013;142 (1):119-32. 
53. 
Rapp K, Klenk J, Ulmer H, et al. Weight change and cancer risk in a cohort of more than 65 000 
adults in Austria. Annals of Oncology 2007;19 (4):641-8. 
54. 
Byers T, Sedjo R. Does intentional weight loss reduce cancer risk? Diabetes, obesity and 
metabolism 2011;13 (12):1063-72. 
55. 
Ramos-Nino ME. The role of chronic inflammation in obesity-associated cancers. ISRN oncology 
2013;2013. 
56. 
Nicoletti G, Giugliano G, Pontillo A, et al. Effect of a multidisciplinary program of weight reduction 
on endothelial functions in obese women. Journal of endocrinological investigation 2003;26 
(3):RC5-RC8. 
57. 
Ziccardi P, Nappo F, Giugliano G, et al. Reduction of inflammatory cytokine concentrations and 
improvement of endothelial functions in obese women after weight loss over one year. 
Circulation 2002;105 (7):804-9. 
58. 
StraÎczkowski M, Kowalska I, Dzienis-StraÎczkowska S, et al. Changes in tumor necrosis factor: 
a system and insulin sensitivity during an exercise training program in obese women with normal 
and impaired glucose tolerance. Eur J Endocrin 2001;145:273-80. 
59. 
Tsukui S, Kanda T, Nara M, et al. Moderate-intensity regular exercise decreases serum tumor 
necrosis factor-α and HbA 1c levels in healthy women. International journal of obesity 2000;24 
(9):1207-11. 
60. 
Esposito K, Pontillo A, Di Palo C, et al. Effect of weight loss and lifestyle changes on vascular 
inflammatory markers in obese women: a randomized trial. Jama 2003;289 (14):1799-804. 
61. 
Marfella R, Esposito K, Siniscalchi M, et al. Effect of weight loss on cardiac synchronization and 
proinflammatory cytokines in premenopausal obese women. Diabetes care 2004;27 (1):47-52. 
62. 
Dandona P, Weinstock R, Thusu K, et al. Tumor necrosis factor-α in sera of obese patients: fall 
with weight loss. The Journal of Clinical Endocrinology & Metabolism 1998;83 (8):2907-10. 
63. 
Foster‐Schubert KE, Alfano CM, Duggan CR, et al. Effect of diet and exercise, alone or 
combined, on weight and body composition in overweight‐to‐obese postmenopausal women. 
Obesity 2012;20 (8):1628-38. 
64. 
Imayama I, Ulrich CM, Alfano CM, et al. Effects of a caloric restriction weight loss diet and 
exercise on inflammatory biomarkers in overweight/obese postmenopausal women: a 
randomized controlled trial. Cancer research 2012;72 (9):2314-26. 
65. 
Linkov F, Maxwell GL, Felix AS, et al. Longitudinal evaluation of cancer-associated biomarkers 
before and after weight loss in RENEW study participants: implications for cancer risk reduction. 
Gynecologic oncology 2012;125 (1):114-9. 

 
 
25 
 Version 1. Mar 2021 
66. 
Group LAR. Long term effects of a lifestyle intervention on weight and cardiovascular risk factors 
in individuals with type 2 diabetes: four year results of the Look AHEAD trial. Archives of internal 
medicine 2010;170 (17):1566. 
67. 
Swift DL, Houmard JA, Slentz CA, et al. Effects of aerobic training with and without weight loss 
on insulin sensitivity and lipids. PloS one 2018;13 (5):e0196637. 
68. 
Committee PAGA. Physical activity guidelines advisory committee scientific report. Washington, 
DC: US Department of Health and Human Services 2018;2018:F2-33. 
69. 
Kerr J, Anderson C, Lippman SM. Physical activity, sedentary behaviour, diet, and cancer: an 
update and emerging new evidence. The Lancet Oncology 2017;18 (8):e457-e71. 
70. 
PATEL AV, FRIEDENREICH CM, MOORE SC, et al. American College of Sports Medicine 
roundtable report on physical activity, sedentary behavior, and cancer prevention and control. 
Medicine & Science in Sports & Exercise 2019;51 (11):2391-402. 
71. 
Group LAR. Cardiovascular effects of intensive lifestyle intervention in type 2 diabetes. New 
England journal of medicine 2013;369 (2):145-54. 
72. 
Irwin ML. Weight loss interventions and breast cancer survival: the time is now. American Society 
of Clinical Oncology, 2014. 
73. 
Brown JC, Yung RL, Gobbie-Hurder A, et al. Randomized trial of a clinic-based weight loss 
intervention in cancer survivors. Journal of Cancer Survivorship 2018:1-10. 
74. 
Kramer MK, Kriska AM, Venditti EM, et al. Translating the Diabetes Prevention Program: a 
comprehensive model for prevention training and program delivery. American journal of 
preventive medicine 2009;37 (6):505-11. 
75. 
Group DPPR. The Diabetes Prevention Program (DPP): description of lifestyle intervention. 
Diabetes care 2002;25 (12):2165-71. 
76. 
Sjöström CD, Peltonen M, Wedel H, et al. Differentiated long-term effects of intentional weight 
loss on diabetes and hypertension. Hypertension 2000;36 (1):20-5. 
77. 
Stevens VJ, Obarzanek E, Cook NR, et al. Long-term weight loss and changes in blood 
pressure: results of the Trials of Hypertension Prevention, phase II. Annals of internal medicine 
2001;134 (1):1-11. 
78. 
Blumenthal JA, Sherwood A, Gullette EC, et al. Exercise and weight loss reduce blood pressure 
in men and women with mild hypertension: effects on cardiovascular, metabolic, and 
hemodynamic functioning. Archives of internal medicine 2000;160 (13):1947-58. 
79. 
Ligibel JA, Barry WT, Alfano C, et al. Randomized phase III trial evaluating the role of weight 
loss in adjuvant treatment of overweight and obese women with early breast cancer (Alliance 
A011401): study design. NPJ breast cancer 2017;3 (1):37. 
80. 
Morey MC, Snyder DC, Sloane R, et al. Effects of home-based diet and exercise on functional 
outcomes among older, overweight long-term cancer survivors: RENEW: a randomized 
controlled trial. Jama 2009;301 (18):1883-91. 
81. 
Goodwin PJ, Segal RJ, Vallis M, et al. Randomized trial of a telephone-based weight loss 
intervention in postmenopausal women with breast cancer receiving letrozole: the LISA trial. 
Journal of Clinical Oncology 2014;32 (21):2231-9. 
82. 
Matthews L, Pugmire J, Moore L, et al. Study protocol for the ‘HelpMeDoIt!’randomised 
controlled feasibility trial: an app, web and social support-based weight loss intervention for 
adults with obesity. BMJ open 2017;7 (10):e017159. 
83. 
Johnson ER, Carson TL, Affuso O, et al. Relationship between social support and body mass 
index among overweight and obese African American women in the rural deep South, 2011-
2013. Preventing chronic disease 2014;11:E224-E. 
84. 
O'Brien TR, Jenkins C, Amella E, et al. Perceptions of older rural women using computerized 
programs for weight management. Online Journal of Rural Nursing and Health Care 2014;14 
(2):80-96. 
85. 
Hardin-Fanning F. Adherence to a Mediterranean diet in a rural Appalachian food desert. Rural 
and remote health 2013;13 (2):2293. 

 
 
26 
 Version 1. Mar 2021 
86. 
Bandura A. Social cognitive theory: An agentic perspective. Annual review of psychology 
2001;52 (1):1-26. 
87. 
Bandura A. Self-efficacy: The exercise of control. Macmillan; 1997. 
88. 
McAuley E, Blissmer B. Self-efficacy determinants and consequences of physical activity. Exerc 
Sport Sci Rev 2000;28 (2):85-8. 
89. 
Porter GC, Laumb K, Michaud T, et al. Understanding the impact of rural weight loss 
interventions: A systematic review and meta‐analysis. Obesity Reviews 2019. 
90. 
Radcliff TA, Bobroff LB, Lutes LD, et al. Comparing costs of telephone vs face-to-face extended-
care programs for the management of obesity in rural settings. Journal of the Academy of 
Nutrition and Dietetics 2012;112 (9):1363-73. 
91. 
Hageman PA, Pullen CH, Hertzog M, et al. Web-Based Interventions Alone or Supplemented 
with Peer-Led Support or Professional Email Counseling for Weight Loss and Weight 
Maintenance in Women from Rural Communities: Results of a Clinical Trial. Journal of obesity 
2017;2017:1602627. 
92. 
Okorodudu D, Jumean M, Montori VM, et al. Diagnostic performance of body mass index to 
identify obesity as defined by body adiposity: a systematic review and meta-analysis. 
International journal of obesity 2010;34 (5):791-9. 
93. 
Jinjuvadia R, Lohia P, Jinjuvadia C, et al. The association between metabolic syndrome and 
colorectal neoplasm: systemic review and meta-analysis. Journal of clinical gastroenterology 
2013;47 (1):33. 
94. 
Pais R, Silaghi H, Silaghi AC, et al. Metabolic syndrome and risk of subsequent colorectal 
cancer. World journal of gastroenterology: WJG 2009;15 (41):5141. 
95. 
Goodpaster BH. Measuring body fat distribution and content in humans. Current Opinion in 
Clinical Nutrition & Metabolic Care 2002;5 (5):481-7. 
96. 
Rohan TE, Heo M, Choi L, et al. Body fat and breast cancer risk in postmenopausal women: a 
longitudinal study. Journal of cancer epidemiology 2013;2013. 
97. 
Iyengar NM, Arthur R, Manson JE, et al. Association of body fat and risk of breast cancer in 
postmenopausal women with normal body mass index: a secondary analysis of a randomized 
clinical trial and observational study. JAMA oncology 2019;5 (2):155-63. 
98. 
Arthur RS, Xue X, Kamensky V, et al. The association between DXA‐derived body fat measures 
and breast cancer risk among postmenopausal women in the Women's Health Initiative. Cancer 
Medicine 2019. 
99. 
Renehan AG, Zwahlen M, Egger M. Adiposity and cancer risk: new mechanistic insights from 
epidemiology. Nature Reviews Cancer 2015;15 (8):484-98. 
100. Ritchie ND, Kaufmann PG, Gritz RM, et al. Presessions to the National Diabetes Prevention 
Program may be a promising strategy to improve attendance and weight loss outcomes. 
American Journal of Health Promotion 2019;33 (2):289-92. 
101. Wadden TA. The look AHEAD study: A description of the lifestyle intervention and the evidence 
supporting it. Obesity 2006;14 (5):737-52. 
102. World Cancer Research Fund. Food, Nutrition and the Prevention of Cancer: A Global 
Perspective. Washington, DC: American Institute for Cancer Research; 2007. 
103. Campbell MK, Carr C, Devellis B, et al. A randomized trial of tailoring and motivational 
interviewing to promote fruit and vegetable consumption for cancer prevention and control. Ann 
Behav Med 2009;38 (2):71-85. 
104. Carels RA, Darby L, Cacciapaglia HM, et al. Using motivational interviewing as a supplement to 
obesity treatment: a stepped-care approach. Health Psychol 2007;26 (3):369-74. 
105. Bandura A. Self-efficacy:  The Exercise of Control. New York: Freeman; 1997. 
106. Focht BC, Brawley L, Rejeski WJ, et al. Effects of lifetime physical activity and traditional 
exercise therapy programs upon health-related quality of life among older adults in cardiac 
rehabilitation. Ann Behav Med 2004;28:52-61. 

 
 
27 
 Version 1. Mar 2021 
107. Focht BC, Garver M, Devor ST, et al. Short-term changes in pedometer-determined physical 
activity in knee osteoarthritis patients: Evidence from the IMPACT-P trial. Medicine and Science 
in Sports and Exercise (in press). 
108. Rejeski WJ, Brawley LR, Ambrosius WT, et al. Older adults with chronic disease: benefits of 
group-mediated counseling in the promotion of physically active lifestyles. Health Psychol 
2003;22 (4):414-23. 
109. Rejeski WJ, Focht BC, Messier SP, et al. Obese, older adults with knee osteoarthritis: weight 
loss, exercise, and quality of life. Health Psychol 2002;21 (5):419-26. 
110. Bourgeois B, Ng B, Latimer D, et al. Clinically applicable optical imaging technology for body 
size and shape analysis: comparison of systems differing in design. European journal of clinical 
nutrition 2017;71 (11):1329-35. 
111. Bard RL, Kaminsky LA, Whaley MH, et al. Evaluation of Lipid Profile Measurements Obtained 
From the Cholestech L· D· X Analyzer. Journal of Cardiopulmonary Rehabilitation and 
Prevention 1997;17 (6):413-8. 
112. Rogers EJ, Misner L, Ockene IS, et al. Evaluation of seven Cholestech LDX analyzers for total 
cholesterol determinations. Clinical chemistry 1993;39 (5):860-4. 
113. Parikh P, Mochari H, Mosca L. Clinical utility of a fingerstick technology to identify individuals 
with abnormal blood lipids and high-sensitivity C-reactive protein levels. American Journal of 
Health Promotion 2009;23 (4):279-82. 
114. Carey M, Markham C, Gaffney P, et al. Validation of a point of care lipid analyser using a hospital 
based reference laboratory. Irish journal of medical science 2006;175 (4):30. 
115. Lyden K, Keadle SK, Staudenmayer J, et al. The activPAL™ accurately classifies activity 
intensity categories in healthy adults. Medicine and science in sports and exercise 2017;49 
(5):1022. 
116. Godin G, Shephard RJ. A simple method to assess exercise behavior in the community. Can J 
Appl Sport Sci 1985;10 (3):141-6. 
117. McAuley E. Self-efficacy and the maintenance of exercise participation in older adults. J Behav 
Med 1993;16 (1):103-13. 
118. Melzack R. The short-form McGill Pain Questionnaire. Pain 1987;30 (2):191-7. 
119. Rodgers WM, Wilson PM, Hall CR, et al. Evidence for a multidimensional self-efficacy for 
exercise scale. Res Q Exerc Sport 2008;79 (2):222-34. 
120. Dunkel-Schetter C, Feinstein L, Call J. UCLA Social Support Inventory (UCLA-SSI). 1986. Los 
Angeles: University of California. 
121. Sallis JF, Grossman RM, Pinski RB, et al. The development of scales to measure social support 
for diet and exercise behaviors. Preventive medicine 1987;16 (6):825-36. 
122. Peters C, Lotzerich H, Niemeier B, et al. Influence of a moderate exercise training on natural 
killer cytotoxicity and personality traits in cancer patients. Anticancer Res 1994;14 (3A):1033-6. 
123. Peters C, Lotzerich H, Niemeir B, et al. Exercise, cancer and the immune response of 
monocytes. Anticancer Res 1995;15 (1):175-9. 
124. Reboussin BA, Rejeski WJ, Martin K, et al. Correlates of satisfaction with body function and 
body appearance in older aged adults:  The activity counseling trial. Psychol Health 
2000;15:239-54. 
125. Rejeski WJ, Ettinger WH, Jr., Schumaker S, et al. Assessing performance-related disability in 
patients with knee osteoarthritis. Osteoarthritis Cartilage 1995;3 (3):157-67. 
121. 
AppalachianRegionalCommission. County economic status designations in the Appalachian region - 
fiscal year 2006, 2007. 
122. 
Abramson R, Haskell J. Encyclopedia of Appalachia. Knoxville: University of Tennessee, 2006. 
123. 
AmericanCancerSociety. Ohio Cancer Facts and Figures, 2003. Special Focus: Ohio Appalachia. Dublin: 
American Cancer Society, Ohio Division, 2003. 
124.  County Cancer Profiles, Ohio Cancer Incidence Surveillance System, Ohio Department of Health, 2008.  

 
 
28 
 Version 1. Mar 2021 
125.  National Institutes of Health. Eating at America’s Table study: quick food scan 2002. 
http://riskfactor.cancer.gov/diet/screeners/fruitveg/allday.pdf.  
126.  J. Shannon, A.R. Kristal, S.J. Curry and S.A. Beresford, Application of a behavioral approach to 
measuring dietary change: The fat- and fiber-related diet behavior questionnaire, Cancer Epidemiol 
Biomarkers Prev 6 (1997), pp. 355–361.  
127.     A.R. Kristal, A.L. Shattuck and H.J. Henry, Patterns of dietary behavior associated with selecting diets 
low in fat: Reliability and validity of a behavioral approach to dietary assessment, J Am Diet Assoc 90 
(1990), pp. 214–220. 
128.    British Columbia Ministry of Health. PAR-Q Validation Report,1978.