thesis on diabetes prevention

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Prevention of Type 2 Diabetes by Lifestyle Changes: A Systematic Review and Meta-Analysis

Affiliations.

1 Institute of Public Health and Clinical Nutrition, School of Medicine, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland. [email protected].
2 Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Centre, St. Michael's hospital, Toronto, ON M5B 1W8, Canada. [email protected].
3 Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A1, Canada. [email protected].
4 Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Centre, St. Michael's hospital, Toronto, ON M5B 1W8, Canada. [email protected].
5 Physicians Committee for Responsible Medicine, Washington, DC 20016, USA. [email protected].
6 Institute for Clinical and Experimental Medicine, 140 21 Prague, Czech Republic. [email protected].
7 Department of Clinical Medicine and Surgery, Federico II University, 80138 Naples, Italy. [email protected].
8 Department of Endocrinology and Internal Medicine, Aarhus University Hospital, 8200 Aarhus N, Denmark. [email protected].
9 German Institute of Human Nutrition Potsdam-Rehbrücke, Clinical Nutrition-DZD, Arthur-Scheunert-Allee 114-116, D-14558 Nuthetal, Germany. [email protected].
10 Department of Endocrinology, Charité University Medicine, Diabetes and Nutrition, Campus Benjamin Franklin, Hindenburgdamm 30, D-12203 Berlin, Germany. [email protected].
11 German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany. [email protected].
12 Diabetes Center, 2nd Department of Internal Medicine, Medical School, National and Kapodistrian University of Athens, Hippokration General Hospital of Athens, 157 72 Athens, Greece. [email protected].
13 Human Nutrition Unit, University Hospital of Sant Joan de Reus, Department of Biochemistry and Biotechnology, Faculty of Medicine and Health Sciences, Institut d'Investigació Sanitària Pere Virgili, Rovira i Virgili University, 43201 Reus, Spain. [email protected].
14 Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, 28029 Madrid, Spain. [email protected].
15 Institute of Public Health and Clinical Nutrition, School of Medicine, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland. [email protected].
16 Department of Medicine, Endocrinology and Clinical Nutrition, Kuopio University Hospital, 70210 Kuopio, Finland. [email protected].
17 Toronto 3D Knowledge Synthesis and Clinical Trials Unit, Clinical Nutrition and Risk Factor Modification Centre, St. Michael's hospital, Toronto, ON M5B 1W8, Canada. [email protected].
18 Department of Nutritional Sciences, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A1, Canada. [email protected].
19 Division of Endocrinology and Metabolism, Department of Medicine, St. Michael's Hospital, Toronto, M5B 1W8 ON, Canada. [email protected].
20 Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, M5B 1T8 ON, Canada. [email protected].
PMID: 31683759
PMCID: PMC6893436
DOI: 10.3390/nu11112611

Prevention of type 2 diabetes (T2D) is a great challenge worldwide. The aim of this evidence synthesis was to summarize the available evidence in order to update the European Association for the Study of Diabetes (EASD) clinical practice guidelines for nutrition therapy. We conducted a systematic review and, where appropriate, meta-analyses of randomized controlled trials (RCTs) carried out in people with impaired glucose tolerance (IGT) (six studies) or dysmetabolism (one study) to answer the following questions: What is the evidence that T2D is preventable by lifestyle changes? What is the optimal diet (with a particular focus on diet quality) for prevention, and does the prevention of T2D result in a lower risk of late complications of T2D? The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach was applied to assess the certainty of the trial evidence. Altogether seven RCTs (N = 4090) fulfilled the eligibility criteria and were included in the meta-analysis. The diagnosis of incident diabetes was based on an oral glucose tolerance test (OGTT). The overall risk reduction of T2D by the lifestyle interventions was 0.53 (95% CI 0.41; 0.67). Most of the trials aimed to reduce weight, increase physical activity, and apply a diet relatively low in saturated fat and high in fiber. The PREDIMED trial that did not meet eligibility criteria for inclusion in the meta-analysis was used in the final assessment of diet quality. We conclude that T2D is preventable by changing lifestyle and the risk reduction is sustained for many years after the active intervention (high certainty of evidence). Healthy dietary changes based on the current recommendations and the Mediterranean dietary pattern can be recommended for the long-term prevention of diabetes. There is limited or insufficient data to show that prevention of T2D by lifestyle changes results in a lower risk of cardiovascular and microvascular complications.

Keywords: complications; diet; lifestyles; prevention; type 2 diabetes.

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Conflict of interest statement

JSS serves on the board of, and has received a grant through, his institution from the International Nut and Dried Fruit Council and the Eroski Foundation. He serves on the Executive Committee of the Instituto Danone Spain and on the Scientific Committee of the Danone International Institute. He has received research support from the Instituto de Salud Carlos III, Spain; the Ministerio de Educación y Ciencia, Spain; the Departament de Salut Pública de la Generalitat de Catalunya, Catalonia, Spain; and the European Commission. Further research support has come from the California Walnut Commission, Sacramento CA, USA; the Patrimonio Comunal Olivarero, Spain; the La Morella Nuts, Spain; and Borges S.A., Spain. He reports receiving consulting fees or travel expenses from Danone; California Walnut Commission, the Eroski Foundation, the Instituto Danone–Spain, Nuts for Life, Australian Nut Industry Council, Nestlé, Abbot Laboratories, and Font Vella Lanjarón. He is on the Clinical Practice Guidelines Expert Committee of the European Association for the study of Diabetes (EASD) and has served on the Scientific Committee of the Spanish Food and Safety Agency, and the Spanish Federation of the Scientific Societies of Food, Nutrition and Dietetics. He is an Executive Board Member of the Diabetes and Nutrition Study Group [DNSG] of the EASD. JLS has received research support from the Canadian Foundation for Innovation, Ontario Research Fund, Province of Ontario Ministry of Research and Innovation and Science, Canadian Institutes of health Research (CIHR), Diabetes Canada, PSI Foundation, Banting and Best Diabetes Centre (BBDC), American Society for Nutrition (ASN), INC International Nut and Dried Fruit Council Foundation, National Dried Fruit Trade Association, The Tate and Lyle Nutritional Research Fund at the University of Toronto, The Glycemic Control and Cardiovascular Disease in Type 2 Diabetes Fund at the University of Toronto (a fund established by the Alberta Pulse Growers), and the Nutrition Trialists Fund at the University of Toronto (a fund established by an inaugural donation from the Calorie Control Council). He has received in-kind food donations to support a randomized controlled trial from the Almond Board of California, California Walnut Commission, American Peanut Council, Barilla, Unilever, Unico/Primo, Loblaw Companies, Quaker, Kellogg Canada, and WhiteWave Foods. He has received travel support, speaker fees and/or honoraria from Diabetes Canada, Mott’s LLP, Dairy Farmers of Canada, FoodMinds LLC, International Sweeteners Association, Nestlé, Pulse Canada, Canadian Society for Endocrinology and Metabolism (CSEM), GI Foundation, Abbott, Biofortis, ASN, Northern Ontario School of Medicine, INC Nutrition Research & Education Foundation, European Food Safety Authority (EFSA), Comité Européen des Fabricants de Sucre (CEFS), and Physicians Committee for Responsible Medicine. He has or has had ad hoc consulting arrangements with Perkins Coie LLP, Tate & Lyle, and Wirtschaftliche Vereinigung Zucker e.V. He is a member of the European Fruit Juice Association Scientific Expert Panel. He is on the Clinical Practice Guidelines Expert Committees of Diabetes Canada, European Association for the study of Diabetes (EASD), Canadian Cardiovascular Society (CCS), and Obesity Canada. He serves or has served as an unpaid scientific advisor for the Food, Nutrition, and Safety Program (FNSP) and the Technical Committee on Carbohydrates of the International Life Science Institute (ILSI) North America. He is a member of the International Carbohydrate Quality Consortium (ICQC), Executive Board Member of the Diabetes and Nutrition Study Group (DNSG) of the EASD, and Director of the Toronto 3D Knowledge Synthesis and Clinical Trials foundation. His wife is an employee of Sobeys Inc. TAK has received research support from the Canadian Institutes of Health Research (CIHR) and an unrestricted travel donation from Bee Maid Honey Ltd. He was an invited speaker at a Calorie Control Council annual general meeting for which he received an honorarium. No competing interests were declared by the other authors (MU, EV, HK, AAR, KH, AP, AT, US).

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Diabetes prevention through a public health strategy

Masters Thesis
Cruz, Cristina
Emetu, Roberta
Forster, Myriam
Rainisch, Bethany
Health Sciences
California State University, Northridge
Community Health Education
nutrition education
Dissertations, Academic -- CSUN -- Health Science.
public health
prediabetes
2021-08-09T20:09:53Z
http://hdl.handle.net/10211.3/221289
by Cristina Cruz

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Diabetes Mellitus II Screening and Prevention Research Paper

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Introduction

Condition and screening, epidemiology of condition, methodology, critical analysis.

Today, master’s-prepared nurses should be ready to help patients by following doctors’ prescriptions, maintaining a treatment plan, cooperating with family members, and educating. However, in addition to the steps taken after the disease is diagnosed, preventive screening guidelines are required in many clinical areas. The awareness of epidemiology allows nurses to understand the causes and progress of a condition and offer interventions to predict complications. In the United States, as well as across the globe, diabetes is a serious chronic disease that affects human life quality and has no cure. According to the Centers for Disease Control and Prevention (CDC, 2020), diabetes is the seventh leading cause of death and a common vision disability cause in 12% of the US population. Regarding the offered sources and knowledge about this condition, nurses must support their patients and encourage screening based on credible guidelines. The US Preventive Services Task Force (USPSTF, 2021) recommends screening for type 2 diabetes and preventive interventions for obese or overweight adults aged 35 to 70. This paper aims to evaluate recommendations, review diabetes epidemiology, and analyze the methods to prove a moderate net benefit of the guideline.

Type 2 diabetes is a condition for analysis, and screening tests, like fasting plasma glucose, HbA1C, and an oral glucose tolerance test, for patients of a particular group are recommended. The USPSTF (2021) defines screening for prediabetes and type 2 diabetes as Grade B because there is a high certainty of moderate net benefit. Diabetes is a long-lasting health condition characterized by problems turning food into energy (CDC, 2020). The body does not produce enough insulin because of a poorly working pancreas, and high blood sugar levels stay in the system, provoking heart disease and vision loss. These physiological changes provoke increased thirst, hunger, urination, and fatigue. Although particular groups (Blacks, Asians, and Native Americans) are at a higher risk for diabetes, such factors as age (older adults), physical activity, obesity, sleep quality, and smoking are still critical (Ismail et al., 2021). Recommendations for screening for type 2 diabetes every three years have been changed to underline age and weight characteristics: adults aged between 35 and 70 who are overweight or obese (USPSTF, 2021). Weight risk assessment and glucose measurement are the two reasonable steps for modern populations to consider.

Despite the level of obtained knowledge and care quality, it is not always possible to predict diabetes progress in a population. Healthcare providers, researchers, and educators prefer to address recent epidemiological studies. Epidemiology is the study of the determinants and distribution (prevalence) of health conditions in a specific population group (Ahlbom, 2020). There are many statistical terms to include in the epidemiological evaluation of diabetes, and the current project focuses on sex, age, and racial factors. The estimated prevalence of diagnosed diabetes in males is larger than in females: 11% (745,000) and 9.5% (738,000), respectively (CDC, 2020). The number of Americans older than 65 years is higher compared to other age groups, including about 15.9 million seniors (American Diabetes Association [ASA], 2022). Addressing racial differences, the ASA (2022) offers the following numbers: 14.5% of American Indians (the larger trend) and 7.4% of non-Hispanic white (the less trend). In 2019, 87,647 death certificates were reported in the United States and 282,801 certificates globally, with diabetes as an underlying cause (ASA, 2022; CDC, 2020). These numbers cannot be ignored to prove the importance of early symptom detection and prevention.

As an independent group of experts in preventing medicine, the USPSTF aims to develop the best methodology processes to maintain the population’s well-being. It consists of five major steps: nominations review, research draft, public comments review, evidence review, and final recommendations (USPSTF, 2021). The same stages are followed in this section of the paper to discuss how to screen and prevent diabetes. Regarding the prevalence of diabetes among adults and insignificant changes in gender differences, it is correct to choose people aged 35-70 years for examination (ASA, 2022; CDC, 2020; Ismail et al., 2021; USPSTF, 2021). One of the first tasks is to inform people from the chosen age group about the risks of diabetes and the necessity of diagnosing this condition at an early stage. However, people usually need more facts to understand the threat, and the recognition of additional factors is required. In this case, obesity is a critical risk factor for diabetes. Ismail et al. (2021) conclude that diabetes risks in elderly people (both men and women) are higher compared to other age statistical groups. Older adults face severe challenges in dealing with diabetes-related complications.

People share common opinions about the importance of managing diabetes to avoid lethal outcomes. They are aware that a healthy lifestyle and dietary habits contribute to diabetes prevention. Still, not many people follow recommendations and neglect physical activities. Ismail et al. (2021) identify physical inactivity as an independent risk factor for type 2 diabetes as it decreases insulin sensitivity and increases beta-cells loss. Considering these findings and the USPSTF guideline, diabetes prevention starts with improving human weight characteristics. Thus, the screening measures based on age and obesity (overweight) in both genders, even if there are no clear symptoms of diabetes, can be proved.

There are three main aspects in the USPSTF guideline recommendation: a specific population, the importance of screening, and the development of preventive interventions. The population characteristics are age (35-70 years), Body Mass Index (more than 25 with an exception for Asians – BMI can be more than 25), and race (American Indians, Blacks, Hawaiians, Hispanics, and Asians) (USPSTF, 2021). The screening type includes measuring fasting plasma glucose (HbA1C) level or an oral glucose tolerance test (USPSTF, 2021). The interval obtained among adults would be at least three years, even if the previous blood glucose levels were normal (USPSTF, 2021). Several recommendations are necessary to help asymptomatic individuals understand what changes are reasonable. First, behavioral weight loss allows people to prevent diabetes-related morbidity. Second, smoking cessation is suggested because nicotine reduces muscle glucose intake and promotes insulin resistance (Ismail et al., 2021). Finally, people with diabetes experience fatigue and get tired very quickly. Thus, decreased sleep quality is associated with low oxygen and a high possibility of inflammation. Sleep improvement should not be ignored in preventing diabetes among people of all races, ages, and genders.

In recent literature, it is possible to find additional recommendations on how to prevent diabetes and what screening methods are effective for particular population groups. In many developing countries, healthcare providers do not get access to reliable resources to protect people against chronic diseases. For example, in Iran, only half of the diabetic people are aware of their condition, and a new diabetes screening program has been implemented by the Iranian ministry of health (Kianpour et al., 2021). In addition to the age and weight characteristics, local recommendations include a family history of diabetes or gestational diabetes (Kianpour et al., 2021). Patients need to fast for about eight hours before the day they have a diagnostic appointment. If the fast blood glucose test results are higher than 126 mg/dl, additional tests are required to identify the stage of diabetes (Kianpour et al., 2021). Family history plays an important role in identifying diabetes at an early stage, but the USPSTF guideline omits this point in its program.

In comparison, developed countries like Sweden improve their diabetes prevention programs at community and facility levels. According to Timm et al. (2020), such screening methods help cover more unfavorable risk profiles, with special attention to men for achieving a gender balance in interventions. In addition, the Stockholm diabetes program identifies a socioeconomic risk factor and proves its contribution to diabetes progress (Timm et al., 2020). In the United States, the differences in family incomes are mentioned as the determinants of human health. Still, in the USPSTF recommendations, no attention is paid to this population recommendation.

In general, screening for diabetes is an important step in maintaining human well-being and public health, as it is the only way to identify asymptomatic people who might have this disease. The USPSTF guideline recommendations underline the necessity of taking one of the offered tests and diagnosing if the result is positive. The decision to pay attention to individuals of a particular age range (35-70 years) and a specific physical condition (BMI more than 25) is properly evidenced. There are many risk factors for type 2 diabetes, but obesity and physical inactivity remain the two critical facts that cannot be ignored. Finally, the threat of diabetes continues to grow with age, and older adults may benefit from the offered screening system classified as Grade B and use the offered preventive strategies to improve their health.

Ahlbom, A. (2020). Epidemiology is about disease in populations . European Journal of Epidemiology, 35 (12), 1111-1113. Web.

American Diabetes Association. (2022). Statistics about diabetes . ADA. Web.

Centers for Disease Control and Prevention. (2020). National diabetes statistics report 2020 estimates of diabetes and its burden in the United States [PDF file]. Web.

Ismail, L., Materwala, H., & Al Kaabi, J. (2021). Association of risk factors with type 2 diabetes: A systematic review . Computational and Structural Biotechnology Journal, 19 , 1759-1785. Web.

Kianpour, F., Fararouei, M., Hassanzadeh, J., Mohammadi, M., & Dianatinasab, M. (2021). Performance of diabetes screening tests: An evaluation study of Iranian diabetes screening program . Diabetology & Metabolic Syndrome, 13 (1). Web.

Timm, L., Harcke, K., Karlsson, I., Sidney Annerstedt, K., Alvesson, H. M., Stattin, N. S., Forsberg, B. C., Östensond, C. G., & Daivadanam, M. (2020). Early detection of type 2 diabetes in socioeconomically disadvantaged areas in Stockholm – Comparing reach of community and facility-based screening . Global Health Action, 13 (1). Web.

US Preventive Services Task Force. (2021). USPSTF recommendations development process . USPSTF. Web.

US Preventive Services Task Force. (2021). Screening for prediabetes and type 2 diabetes: US preventive services task force recommendation statement . JAMA, 326 (8), 736-743. Web.

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IvyPanda. (2024, June 29). Diabetes Mellitus II Screening and Prevention. https://ivypanda.com/essays/diabetes-mellitus-ii-screening-and-prevention/

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IvyPanda . (2024) 'Diabetes Mellitus II Screening and Prevention'. 29 June.

IvyPanda . 2024. "Diabetes Mellitus II Screening and Prevention." June 29, 2024. https://ivypanda.com/essays/diabetes-mellitus-ii-screening-and-prevention/.

1. IvyPanda . "Diabetes Mellitus II Screening and Prevention." June 29, 2024. https://ivypanda.com/essays/diabetes-mellitus-ii-screening-and-prevention/.

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IvyPanda . "Diabetes Mellitus II Screening and Prevention." June 29, 2024. https://ivypanda.com/essays/diabetes-mellitus-ii-screening-and-prevention/.

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Perceived Benefits and Barriers of a Community-Based Diabetes Prevention and Management Program

This study examined the perceptions of benefits of and barriers to participating in a community-based diabetes program to improve program effectiveness. The Diabetes Prevention and Management (DPM) program was a twenty-two session, 1-year program, modeled after the evidence-based National Diabetes Prevention Program and AADE7 Self-Care Behaviors framework. Community-based participatory research approach was used to culturally tailor the curriculum. Participants included overweight or obese adults with dysglycemia. A benefits and barriers survey was developed to gather information on participants’ perception of the program, as well as information on demographics and health literacy levels. Eighty-nine adults participated in the DPM program (73% females; 62% diabetic; 77% had adequate health literacy); 79% of participants completed the benefits and barriers survey. Principal component analysis indicated two components representing benefits (Cronbach’s α = 0.83) and barriers (α = 0.65). The majority perceived high benefits and low barriers to program participation; benefits included helpful interaction with health coach or program leader (73%), improved lifestyle modification (65%) due to the program, and satisfaction with the program (75%). Open-ended questions confirmed themes related to benefits of program participation, suggestion for programmatic improvements as well as barriers to participation. Participant feedback could be used to guide interventions and tailor future program implementation.

1. Introduction

Diabetes affects 30.3 million Americans (9.4% of the population) and contributes to early morbidity and mortality [ 1 ]. In addition, 84.1 million Americans or 33.9% have prediabetes [ 1 ]. Diabetes is especially prevalent in Appalachian areas [ 2 ], particularly West Virginia, the only all-Appalachian state. West Virginia (WV) has one of the highest rates of diabetes (15.3%) and pre-diabetes (35%) among the 53 US states and territories [ 3 , 4 ]. This may be due in part to the majority of the residents residing in rural areas (WV is the 3rd most rural state in the country) [ 5 ] and low socioeconomic status, considering that diabetes is highest among individuals who earn a household income of less than $15,000 per year, and that 17.9% of West Virginians are below the poverty level [ 6 ]. Other factors that contribute to the high rate of diagnosed and undiagnosed diabetes and pre-diabetes in WV include geography, lack of access to quality care, the aging population, and the Appalachian culture of fatalism [ 7 ]. In addition, healthy lifestyle practices are also poor; obesity, physical inactivity, and smoking are major contributing factors to diabetes [ 1 ]. Importantly, if not properly managed, dysglycemia (individuals with diabetes and pre-diabetes) can lead to a variety of severe complications, including but not limited to heart disease, stroke, hypertension, blindness and eye problems, kidney disease, nervous system disease, and amputation [ 8 ]. In WV, diabetes-related diseases such as heart disease, hypertension and stroke are the number 1, 2 and 5 causes of death, respectively [ 4 ].

Dysglycemia presents a significant challenge for individuals, communities, and healthcare systems due to increased risk for disease and comorbid conditions associated with health care costs [ 9 , 10 , 11 ]. Medical expenditure was 2.3 times higher for individuals with diabetes than without and healthcare costs associated with diabetes was $245 billion in 2012 [ 12 ]. Hence, prevention and education efforts are currently focused on preventing or delaying the early onset of diabetes and its complications. Prevention is one of the most effective public health strategies for reducing the prevalence of diabetes and improving successful disease self-management. Previous evidence-based lifestyle programs, such as the Diabetes Prevention Program (DPP) [ 13 ], Da Qing Study [ 14 ], Swedish Malmo Study [ 15 ], Finnish Diabetes Prevention Study [ 16 ], and United Kingdom Prospective Diabetes Study [ 17 ], have shown that diet, physical activity, and behavior modifications can combat the rising number of individuals with prediabetes; lifestyle modification is also a critical component of diabetes self-management [ 18 ].

While the translation of lifestyle interventions is often recommended for reducing the risk for diabetes and its complications, adequate dissemination of diabetes prevention and management programs in WV (e.g., the DPP, WV Dining with Diabetes program, Chronic Disease Self-Management Program (CDSMP), and Diabetes Self-Management Program (DSMP), and Diabetes Self-Management Education) is less than desired [ 19 ]. Understanding the perceived benefits and barriers of participation is critical if we are to improve prevention efforts in WV communities. Rigorous and supportive research on factors that motivate or deter individuals with dysglycemia to participate in lifestyle interventions is currently lacking in this medically underserved state. Furthermore, very little diabetes research has shown adequate dissemination, the use of qualitative techniques, or the understanding of the underlying benefits and barriers involved with lifestyle programming.

Examining the role of benefits and barriers is important in understanding the effectiveness of community-based diabetes programs. Hence, the purpose of this exploratory study was to develop an instrument for assessing the benefits of a community-based diabetes prevention and management (DPM) program. These results can be used to tailor the curriculum for Appalachian culture, and can help with accessibility to diabetes programs in community settings, which may represent a novel way of improving and implementing effective programs in WV. Furthermore, results from this research can be used to tailor new and available programs for improved program adherence, utilization, and behavior changes as well as increase health provider referrals to lifestyle programs in West Virginia communities.

The purpose of the study was to: (1) Determine the participants’ perceived barriers for engaging in the DPM program; (2) Determine the benefits of program participation; and (3) Assess the satisfaction with various components of the program (if any).

2. Experimental Section

2.1. data source, eligibility and recruitment.

The original data source was the Diabetes Prevention and Management (DPM) program from 2014 through 2016. The DPM was implemented in twenty-two sessions over 12 months in two Appalachian churches, and was modeled after the evidence-based National DPP and modified to include diabetes management sessions using the American Association of Diabetes Educators Self-Care Behaviors framework (AADE7) [ 13 , 20 ]. The program emphasizes goal-setting and self-monitoring to make lasting improvements in nutrition and physical activity; moderate weight loss; building self-efficacy and social support for sustainable lifestyle changes; and overcoming barriers to maintaining weight-loss and lifestyle changes [ 21 , 22 ]. Specifically, program sessions included, but were not limited to, the following information: healthy eating, physical activity, stress management, keys to eating out, mindful eating, problem solving and medication adherence. Program participants could attend all program sessions, and those who missed a session had the opportunity to review a closed YouTube channel that had the program session recordings. The DPM program utilized a prospective study design to evaluate the delivery of an evidence-based, non-pharmacological, behavioral lifestyle intervention. Individuals who were at risk of developing diabetes (i.e., prediabetes stage) or were diagnosed with diabetes, based on survey screening questions or fasting blood glucose, were recruited for the study. Eligible individuals had to be aged 18 years or older, with a BMI of equal to or greater than 25 kg/m 2 , and had to be motivated to meet the Surgeon General’s recommended physical activity of at least 150 min per week. Potentially eligible participants were recruited from the greater Morgantown and Charleston, WV areas using convenience and snowball sampling due to the nature of the program. These two areas have several hospitals, Federally Qualified Health Centers, free clinics, churches and other community-based organizations (e.g., Young Men’s Christian Association) from which participants were successfully recruited for the program. Participants were also recruited through community advertisements such as flyers, church bulletins, email lists, and community presentations. The study protocol was approved by West Virginia University Institutional Review Board.

2.2. Benefits and Barriers Survey

Benefits and barriers were assessed using a 33-item survey questionnaire developed by the researchers. The survey examined participants’ perception of benefits of and barriers to participation in the DPM program. The survey questions sought information on the following: barriers to engaging in the program, benefits reported for program participation, satisfaction with various components of the program (if any), and demographic information of the participants (medical history, family history of disease, health literacy, and physical health and mental health wellbeing). In addition, individuals had the opportunity to respond, using open-ended questions, on specific benefits and barriers, provide suggested improvements for the program, and identify the most interesting components that may lead to improvement of community-based diabetes lifestyle programs.

We used a modified Centers for Disease Control clinical data form to identify the medical history of diseases, including prediabetes, diabetes and heart disease [ 23 ]. Self-rated general health status was measured by questions modified from the WV Ruby Memorial Hospital Health Questionnaire; the question asked, “Compared to other people, how do you rate your physical health?”, with response choices ranging from 1 to 5, where 1 = Poor and 5 = Excellent [ 24 ]. Self-rated mental health was measured by the question “Compared to other people, how do you rate your mental health?”, with response ranging from 1 to 5, where 1 = Poor and 5 = Excellent. In addition, health literacy was measured by three validated questions developed by Chew et al.: (1) “If you need to go to the doctor, clinic or hospital, how confident are you in filling out forms by yourself?”; (2) “How often do you have someone (family member or staff at the clinic or hospital) help you read health or medical forms?”; and (3) “How often do you have problems learning about your medical condition because of trouble understanding written health information?” [ 24 , 25 ]. Response options ranged from 1 to 5 for each question, where 1 = Not at all confident or Always and 5 = Extremely confident or Never. Thus, higher scores indicate adequate health literacy.

The remainder of the survey questions were developed and modified from two reliable and valid surveys which were the Community Health Awareness of Diabetes (CHAD) and the Summary of Diabetes Self-Care Activities (SDSCA) measure, along with previous lifestyle programming experience [ 26 , 27 ]. These specific questions identified the benefits and barriers of the diabetes program. The benefits and barriers program questions used Likert response items (1 = Not applicable, 2 = Strongly Disagree, 3 = Disagree, 4 = Neutral, 5 = Agree, and 6 = Strongly agree) and an open-ended format. The survey was reviewed by the program staff (Investigators and Health Coaches) to ensure response time, readability, and applicability. Participants were asked to complete the survey without interaction with their peers in order to reduce bias. Confidentiality was assured by using their participant ID number. The questionnaire was completed at 6 months and at the end of the program; however, the last data point was used to assess the participants’ perception. All participants were English-speaking individuals and were able to read and write in English, a norm in WV. However, study personnel assisted those participants who had questions and/or needed clarification while completing the survey.

2.3. Statistical Analyses

Data were analyzed using SPSS (IBM, Armonk, NY, USA) All data was double entered and compared for missingness. While 89 participants (unduplicated) were enrolled in the DPM program, the current analyses included 70 participants with complete data. Descriptive characteristics for the total sample are provided. Cronbach’s alpha of this new scale was used to assess reliability or internal consistency, and principal component analysis (PCA) with a varimax rotation was conducted to examine the factorial structure of the constructs, with eigenvalues greater than 1. An eigenvalue of 1 or greater indicates that the factor possesses at least as much total variance as is contained in a single item. PCA was computed by correlating the score for each scale item with the total score for each observation, and by comparing that to the variance for all individual item scores. Model refinement and assessment were carried out iteratively. Following the PCA, findings were quantified and assessed through descriptive analyses. Additionally, the open-ended format for some questions allowed triangulation of the quantitative and qualitative feedback on participants’ perceived program benefits and barriers.

3.1. Demographics

Table 1 presents descriptive statistics on the total sample, which included 89 unduplicated participants. Participants were primarily female (73%) and aged 20 to 83 years (mean age = 58.51 ± 0.26 years). The majority (62%) of the participants with diabetes were of low socioeconomic status, had a college degree or higher (69.7%) and an average income (45% < $50,000). Both newly diagnosed and those with longer duration of diabetes were enrolled for the intervention program; the mean number of years with diabetes reported was 19 ± 13.5 years, and no significant difference was found between the two groups. Furthermore, two-thirds reported that they were currently married (63%) and had family members living in their household (mean = 1.24 ± 0.30).

Descriptive statistics of categorical and continuous, demographic variables.

Variable	Categories		Percent (%)/Mean ± SD
Sex	Female	65	73
Sex	Male	24	27
Marital Status	Not Currently Married	27	30.3
Marital Status	Currently Married	56	62.9
Education	High School or Some College	23	25.8
Education	College Degree or Higher	62	69.7
Income	≤$50,000	40	44.9
Income	≥$50,000	27	30.3
Diabetes Status	Prediabetes	34	38.2
Diabetes Status	Diabetes	55	61.8
Age		89	58.5
Household Size		66	1.24
Benefits		70	5.45
Barriers		70	4.31

With respect to participants who had a genetic predisposition to diabetes; 64% indicated a family history, and over half (56%) knew someone who had been diagnosed with heart disease. Likewise, hypertension (55%) and high cholesterol (54%) were major comorbidities for this study sample. However, over 50% of participants self-rated their overall physical and mental health status to be good or excellent, and more than 77% of participants had adequate health literacy.

Additionally, the rate of program completion for participants was 82%. Dropout was defined as those participants who informed the team that they were withdrawing from the study or when they were unable to be contacted after missing a scheduled assessment and/or follow-up phone calls. Attendance was taken at every educational session. Several individuals started the program, but dropped out in the first 4 weeks due to instrumental reasons such as changes in health and mobility, competing family responsibilities, transportation issues, change in job, etc. Based on attendance, taken at every educational session, the average number of sessions attended was 75% (or 14 sessions). No significant difference was noted based on diabetes and pre-diabetes status.

3.2. Reliability of Scale

PCA identified clustering of five constructs as follows: screening/risk, location, fasting blood work, benefits and barriers. The two factors of importance for this study were benefits and barriers; eight questions loaded for benefits and five questions loaded for barriers. The benefits and barriers components were then placed in a two-component PCA analysis to further assess reliability of the scale, which is presented in Table 2 . With the two-component PCA analysis, the overall Cronbach’s alpha reliability for the benefits component was 0.827 and 0.645 for barriers. These two factors accounted for 15.3 (benefits) and 21.3 (barriers) of the variance for the total sample. Questions relating to diabetes screening/risk, fasting blood work and location were excluded from the final PCA analysis for this study.

Two-factor PCA reliability statistics of benefits and barriers scale.

Variable	Cronbach’s Alpha	Mean	Variance	Standard Deviation	of Items
Barriers	0.645	21.5	21.3	4.62	5
Benefits	0.827	43.6	15.3	3.91	8

For the main variables (benefits, barriers), the mean response was 43.6 ± 3.91 and 21.5 ± 4.62, respectively. The mean scores for these two constructs indicated high benefits and low barriers with the DPM program. DPM program aided in implementing lifestyle changes for participants and educational sessions provided a positive experience for support, discussion and learning opportunities. The benefit item-mean scores ranged from 5.03 to 5.64 on a 1–6 scale ( Table 3 ). Overall, perceived barriers to program participation and engagement was low (range = 3.76 to 4.69) and therefore included minimal areas of improvement. Most individuals were satisfied with the program and improvement in lifestyle behaviors, and this suggests that individuals rated the individual benefits and barriers items positively. Specifically, individuals with prediabetes (mean = 5.43 ± 0.528) and diabetes (mean = 5.48 ± 0.399) scored benefits positively as well.

Benefits and barriers items (benefits n = 69, barriers n = 70).

Benefit/Barrier	Item	Mean	Standard Deviation
Benefit	The health coach or program leader was encouraging or helpful	5.61	0.623
Benefit	The program materials/demonstrations were informative	5.64	0.514
Benefit	I changed my lifestyle as a result of the program	5.03	0.923
Benefit	I will discuss my program results with my health provider	5.45	0.697
Benefit	I will discuss my results with my family and/or friends	5.29	0.842
Benefit	The program helped me understand the risks associated with diabetes and/or its complications	5.49	0.797
Benefit	The program helped me understand how to prevent and/or manage diabetes	5.46	0.759
Benefit	Overall, I was satisfied with the program	5.64	0.568
Barrier	Transportation was a barrier for me	4.69	1.27
Barrier	The weather kept me from attending some program sessions	4.33	1.40
Barrier	My health status kept me attending some program sessions	4.53	1.29
Barrier	My work kept me from attending some program sessions	4.24	1.55
Barrier	Family activities kept me from attending some program sessions	3.76	1.64
Barrier	Family activities kept me from attending some program sessions	3.76	1.64

3.3. Survey Results

3.3.1. benefits and barriers.

Over 70% indicated that the interaction with their personal health coach or program leaders, as well as program materials/demonstrations, were helpful and informative. The program was successful in helping 65% of individuals to modify their health behavior and make positive lifestyle changes as a result of the program. In addition, 70% used the results of blood tests completed during the program to discuss with their healthcare provider and family/friends. The majority (74%) of participants indicated that the program helped them understand the risks associated with dysglycemia and how to prevent/manage diabetes. Overall, about 75% of respondents were satisfied with the program. Specifically, transportation was not identified as a barrier for the majority of participants. While some educational sessions were done during winter months, over half of the individuals (53%) reported they did not miss a session due to weather and work priorities, family activities and personal health issues did not deter their attendance.

3.3.2. Other Constructs

As mentioned previously, the constructs that were excluded from the two-construct PCA were screening/risk, location and fasting bloodwork. Among these were some interesting conclusions that helped confirm the assumption of high benefits and low barriers. For example, over half (71%, 66%) of the participants had been screened for diabetes and had been informed of their risk for diabetes by their health provider. Approximately 69% of respondents indicated that the church location used for program implementation was convenient. Furthermore, fasting blood work done at the churches during weekend mornings was not challenging for approximately 71% of individuals; over half of participants (54%) felt comfortable giving blood. The benefits and barriers constructs correlated significantly with participant’s self-rated physical health ( r = 0.29, p = 0.015 & r = 0.366, p = 0.002, respectively) indicating individuals with good health perceived greater program benefits and lower barriers to participation. Interestingly, adequate health literacy was not associated with either benefits and barriers of the program.

3.3.3. Open-Ended Responses

The themes that emerged related to barriers of the program were health status, work, travel and family activities. To improve the program, the participants suggested to offer more sessions, provide more recipes, more food demonstrations, and guest speakers. Some of the benefits of the program were awareness of food intake, knowledge about disease and tools to control weight, social support and encouragement. Along with the benefits, most participants thought the guest speakers, tracking, and self-motivation presentations were the most interesting parts of the program. Specific benefits and barriers items are provided in Table 4 .

Benefits and barriers themes from open-ended responses.

Benefits	Barriers
Awareness of disease	Craving at work
Encouragement/motivation	Family responsibilities
Recipes	Travel activities
Lifestyle changes	Church activities
Support/relationship building	Health
Knowledge	Length of questionnaires
Reduction in medications	One meeting time
Weight loss
Lower blood pressure

4. Discussion

This research study examined the factors that motivated or deterred participants’ active participation, as well as suggestions for improvements. Overall, the participants had a positive impression, due to helpful and informative interactions with health coaches and program leaders and improved knowledge and skills for successful lifestyle changes as a result of the program. However, scheduling conflicts with work, travel and family activities were noted as barriers to participation. Therefore, understanding participant perceptions to barriers are critical for addressing concerns for the program.

Health behavior theories cite several factors in behavioral determination that can explain or predict a specific behavior change [ 28 ]. An individual’s perception can be positive or negative, based on the perceived benefits and barriers before a behavior takes place. For example, an individual will most likely choose a behavior that has the most benefits, especially if the benefits outweigh the barriers [ 29 ]. In particular, the health promotion model suggests that engaging in a behavior is dependent on the results of the actions whether it be benefits or barriers. Benefits and barriers can be directly or indirectly motivational to an individual when it comes to behavioral change [ 30 ]. Perhaps, directly could be by personal experiences and indirectly might be the result of a previous event. Consequently, prediction of the barriers or costs related to a behavior can in turn affect the intention to engage in a behavior or their level of performance with a behavior [ 31 ]. For behavior change, barriers can directly create an obstacle prior to engaging or indirectly through decrease in commitment.

Our results concur with prior studies that highlight the fact that program satisfaction is based on high benefits and low barriers. Interestingly, participants self-rated their health as good or excellent despite their current chronic condition(s) and a genetic predisposition to chronic diseases (based on their family history). Additionally, participants reported adequate literacy levels and socioeconomic status than most areas of WV and were confident in reading and understanding information about their health and disease condition. The program participants were similar in demographic characteristics (age, income, geographical area) to the state, but were more educated (70% with Bachelor’s degree) and had a higher percent of females [ 32 ]. Hence, our study population was representative of the state; the majority of WV counties are rural (ranging from 4–9 in Rural-Urban Commuting Area codes (RUCA)) with our study sample including participants from counties mostly rural (3–6 in RUCA codes) [ 33 ].

The program length of one-year was not regarded as a barrier, as has been reported for the National Diabetes Prevention Program, and participants conveyed the satisfaction resulting from peer and program support as they could share their feelings, issues and struggles in a non-judgmental environment, foster peer support and encouragement, and accountability from Health Coaches [ 34 ]. The benefits of the long-term program format also allowed for incremental behavioral change and continuous feedback and support for behavior modification. Program location, transportation, weather, work priorities, and family activities did not pose a barrier and participants were enthusiastic to come for the educational sessions. Given the benefits of the program, 75% reported their overall satisfaction with participating in the DPM program.

Despite the positive feedback received on the program, there were some limitations with this study. For example, all study variables were self-reported and could have led to measurement error and misclassification bias. Specifically, determination of benefits and barriers scores were based on a self-report measure that was developed for this study. In addition, the study is limited by the small sample size and missingness in the data.

Our findings provide evidence that the DPM program is successful in helping individuals with dysglycemia to make positive lifestyle changes and self-manage their chronic conditions. Hence, the use of Health Coaches and community-based models such as the DPM program can be successful and sustainable in WV. However, while the overall benefits were identified, suggestions for improvements such as to offer more sessions, provide recipes, food demonstrations, and bringing experts can be used to tailor future diabetes prevention and management programs.

5. Conclusions

Findings highlight two implications for public health. First, there is a general lack of participant perceptions of community-based diabetes programs, and this study fills a gap in diabetes intervention research in Appalachia, especially in WV. Second, participation in the DPM program improved lifestyle modification while allowing for interventions to become more tailored to the community’s needs. By identifying these benefits and barriers, the program effectiveness can be improved resulting in a better quality of life for WV communities.

Acknowledgments

This work was supported by grants from the Eye Foundation of America, Rotary Club International, Claude Worthington Benedum Foundation, Women of WVU, and the WVU Clinical Translational Science Institute. Statistical advice was sought from Christa Lilly of WVU School of Public Health, Department of Biostatistics.

Author Contributions

We declare that we have participated in the manuscript development; and approved the final version. Samantha Shawley-Brzoska and Ranjita Misra helped to develop the study design, acquisition of data, analysis and interpretation of data, critical revision of manuscript for important intellectual content, administrative, technical, or material support, and study supervision. Both authors had full access to the data and take responsibility for the integrity of the data, accuracy of the data analyses and interpretation of the results, and the content in the final submission.

Conflicts of Interest

The authors declare no conflict of interest.

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