Promoting Intergenerational Health in Rural Kentuckians With Diabetes (PIHRK'D) (PIHRK'D)

Addressing Intergenerational Obesity and Promoting Healthy Eating and Physical Activity Among Individuals [PIHRK'D] Living With Diabetes in Rural Kentucky

The goal of this feasibility study is to use family units as support to promote nutrition and physical activity of individuals with type 2 diabetes. The main question it aims to answer is: • How does the family structure impact the health of its members living with type 2 diabetes? Participants will be asked to; Tell us about their access to food sources and places in the community to engage in physical activity. A nutrition and physical activity plan will be developed for participants and their families to use for 6 months.

BACKGROUND Obesity is a notable public health problem: According to the Center for Disease Control, over 40% of the population in the United States suffers from obesity (Hales et al, 2020). Furthermore, obesity is the second leading cause of deaths in the United States (Swift et al, 2014) and is associated with a significant increase in mortality and decrease in life expectancy of 5-10 years (Fruh, 2017). Factors such as genetics, sedentary lifestyle, and diet have been shown to contribute to obesity (Okobi et al., 2021). Specifically, the prevalence of obesity is remarkably higher or those living in rural communities (34.2%) than those living in urban communities (28.7%; Okobi et al, 2021). In Kentucky, the impact of obesity is devastating, especially in rural communities. The overall state prevalence of obesity for adults in Kentucky is 36.6% and those rates can reach 46.6% in rural communities (America's Health Rankings, 2020). Obesity and poor health outcomes among rural residents are related to unideal engagement in healthy lifestyle behaviors like nutritious eating and physical activity. Factors that contribute to the suboptimal lifestyle behaviors of residents in rural communities include limited personal and community resources and particular cultural norms and practices. The high rates of obesity are particularly of concern because of its association with an increased risk of cardiovascular disease, type 2 diabetes mellitus (T2DM), obstructive sleep apnea as well as cognitive function (Imes & Burke, 2014). T2DM and obesity have a compounding effect on health disparities in rural communities in Kentucky: Type 2 diabetes mellitus (T2DM) is a persistent public health condition with 34.1 million U.S. adults affected (Centers for Disease Control and Prevention [CDC], 2020). Moreover, geographic disparities exist with some population segments such as rural-dwelling Americans experience greater vulnerability to this condition. For instance, the prevalence of diagnosed T2DM is 17% higher in rural residents compared to their urban counterparts (Massey et al., 2010). The prevalence of T2DM in Kentucky's rural counties can reach 23%, compared to the overall state prevalence of 10.6% (Kentucky Cabinet for Health and Family Services, 2020). Moreover, in Kentucky, obesity rates are among the highest in the nation with approximately 36.5% of adults classified as obese, 13.3% diagnosed with type 2 diabetes, 40.9% with hypertension, 37.9% with high cholesterol, while only 15.3% meet physical activity recommendations, and 4.7% meet fruit and vegetable consumption recommendations (America's Health Rankings, 2020). The burden of T2DM and obesity is evident across the lifespan: As obesity prevalence continues to increase in the US population, the effect of obesity has been focused on younger generations. Approximately 24% of adolescent ages 10 to 17 are classified as obese in Kentucky, placing the state number 1 in youth obesity (State of Childhood Obesity, 2020). The increased prevalence of obesity can be associated with youth-onset T2DM indicated by a 95.3% increase from 2001 to 2017 (Lawrence et al, 2021). Moreover, the prevalence of T2DM increases with age and an estimated 25% of older adults (≥ 65 years) have T2DM (Kirkman et al, 2012). The increased prevalence in T2DM among older adults is consistent with the increased prevalence of T2DM where an estimated one-third of older adults are obese (Kritchevsky, 2018). Even though residents in rural Kentucky communities are disproportionally affected by obesity and T2DM, they have less access to health care and reside in suboptimal environments, resulting in poorer health behaviors and outcomes. In addition, cultural norms and beliefs in these areas may further complicate these factors and their perception of the significance of preventative behaviors like health eating and physical activity in health outcomes. The environment and behavior are possible contributors to intergenerational obesity and diabetes in rural Kentucky communities: The literature indicates that patterns of obesity can be seen within families. These patterns are thought to be due to the environments where people live, work, and play (Albuquerque et al, 2017). Specifically, negative environmental factors (e.g., food deserts/healthy food options, lack of greenspace) that contribute to poor health choices (e.g., high food consumption, sweet beverages, lack of exercise; Albuquerque et al, 2017). These environmental factors influence individuals' relationships with food within the family unit. Individuals raised in homes where unhealthy relationships with food have been developed are more likely to repeat these behaviors; thus, increasing the potential for weight gain and obesity throughout the lifespan. The confluence of behaviors and environment and their effect on gene expression, known as epigenetics, provides some explanation to obesity in certain populations. Similar to the patterns found for obesity, T2DM has been linked to genetics. Many of those living with T2DM have at least one family member who was also affected, exhibiting a pattern of inheritance. In addition, the risk of developing T2DM is 40% if one parent has T2DM and 70% if both parents have been diagnosed (Ali, 2013). Familial links to diabetes via certain genes/genetic factors and epigenetic changes have been noted. However, those changes are mostly attributed to the environment and individuals' behaviors. Specifically, T2DM has been linked to risk factors such as unhealthy eating, sedentary lifestyle, and stress (Ali, 2013). Though gene expression modifications occur via epigenetics, those changes can be reversible through environment and behavior modifications. Family-based interventions can be used to promote health in rural communities: With an estimated 5.9 million intergenerational families (e.g., grandparents, parents, grandchildren ≤18 years; America's Fact Finder, 2017), it is imperative that we understand how this family structure impacts the health of its members. This type of family unit is particularly of interest in rural Appalachia since families provide influence cultural health beliefs and health behaviors. In addition to intergenerational households, families in rural Kentucky live on the same piece of land called hollows-land between two mountains. Family-centered behaviors (Demir & Bektas, 2017; Fiese et al, 2015) have long-standing been shown to have positive, health-promoting benefits on nutrition and health outcomes (Schor, 1995). As disease management predominately occurs within the home, utilization of family-based interventions related to adult chronic diseases have been associated with positive health-related outcomes (Baig et al., 2015; Martire & Helgeson, 2017; Weihs et al., 2002). Secure, supportive, relationships with individuals of support, including family or close friends, improve personal management of these conditions. Thus, developing an intervention that mitigates social environment factors that hinder proper nutrition and physical activity. The burden of T2DM and obesity can be mitigated through common self-care activities, specifically healthy eating and physical activity: Healthy eating habits and physical activity are vital for those suffering from obesity and/or T2DM. There is strong evidence supporting the benefits in reducing long-term weight gain with healthy dietary patterns like consuming higher amounts of fruits and vegetables (Bhupathiraju & Hu, 2016). Healthy eating habits are an important factor in T2DM prevention and management and can improve insulin sensitivity and glycemic control, which can help improve overall quality of life and lifestyle improvement (Anders & Schroeter, 2015). Physical activity is associated with numerous health benefits, specifically in reducing the risk of developing obesity and T2DM. An abundance of evidence from prospective cohort studies and randomized clinical trials indicate that physical activity and an active lifestyle are vital complements in weight management by increasing total energy expenditure, reducing fat mass, maintenance of lean body mass, and improving metabolic rate (Strasser, 2013). The combination of increased physical activity and healthy eating has been shown to be more effective than either alone. Both nutritional changes and increased physical activity are factors contributing to weight loss, which is an important aspect of obesity and T2DM management to improve health outcomes and reduce long-term health complications (Strasser, 2013). However, residents of rural Appalachian communities report inadequate diet and physical activity behaviors, and experience poorer health outcomes than the rest of the nation (Hoogland et al, 2019). Residents of rural Kentucky communities consistently report poor diet and low levels of physical activity as key health concerns, and data has shown that it is less common for residents living in rural areas to consume the recommended weekly servings of fruits and vegetables compared to nonrural residents (Hoogland et al, 2019). APPROACH The proposed project is informed by the National Framework for Health Equity and Well Being (Burton et al., 2021), which was recently developed by the Cooperative Extension Service. This framework explicitly acknowledges the multiple levels of influence on health outcomes and the role of Cooperative Extension Service as a mitigator of community-level health inequities. The framework acknowledges factors that contribute to health inequities at various societal levels, including root causes of structural inequity; norms, policies, and practices; and social determinants of health. As individuals flow through multiple sectors of environments that they live in, each has a direct influence individually and collectively. For the proposed grant, we will focus on how county-level Extension agents (federally funded program) can be used to mitigate health disparities that contribute to intergenerational obesity and T2DM management in rural Kentucky. Community-level factors also impact health outcomes such as lack of access to healthy, affordable food, as well as availability of health-related resources. Community assets will be gathered using subjective and objective community audits and assessed at the participant level using social network analysis. Societal level factors include social norms and cultural health beliefs that impact health decision-making within the community, particularly families/households. Participants will be recruited on a staggered basis from 2 rural counties in Kentucky. Recruitment will be conducted via Extension Offices, word-of-mouth, social media, UK Healthcare outpatient clinics (e.g., internal medicine, family medicine, endocrinology) as well as UK's Barnstable Brown Diabetes and Obesity Center. Once enrolled, participants will be screened by the RD to confirm obesity/overweight, T2DM diagnosis, and identify each participants' placement within the Transtheoretical Model (Six Stages of Change): pre-contemplation, contemplation, preparation, action, maintenance, or relapse. Enrollment Stage of Change will be used to develop appropriate goals for each participant. Beyond the primary enrolled participant in the study, members of the household will be invited to attend meetings with the RD and Dining with Diabetes program sessions. Aim 1: Use social network analysis to describe (a) community assets (e.g., access to healthy eating and ways to participate in physical activity) and (b) intergenerational links to obesity and diabetes (e.g., parent, sibling, child). Social network analysis will be used to map food sources and food assistance (e.g., supermarket, convenience store, fast food, food pantries), including the types of food offered and frequency of engagement with food sources. Similar methods will be used to identify areas/places within the community that could be used to engage in physical activities (e.g., gym, community center, green space, walking trails). A network map will be developed per household to be used to develop a tailored program that that is feasible and accessible to overweight/obese individuals living with diabetes and members of their household. Participants will be asked to provide the following information on up to 5 immediate family members: age; sex; education level; relationship (e.g., spouse, child, sibling, parent); whether that individual is overweight/obese; and current T2DM diagnosis status (e.g., no diagnosis, diagnosed by a healthcare provider, told by a healthcare provider to be prediabetic). Additional information will be gathered regarding the interconnectedness (e.g., person 1 and person 3 are siblings) of the known relationships between family members. Aim 2: Develop a household-specific nutrition and physical activity plan. A 6-month nutrition and physical activity intervention will be implemented with eligible, enrolled, Kentucky residents focused on leveraging household/familial social networks. Medical nutrition therapy will be used within a household to tailor healthy eating and physical activity. The 4-week Dining with Diabetes Program will be used to supplement medical nutrition therapy. The participant will be engaged to take someone from their household with them to the Dining with Diabetes sessions to promote and reinforce healthy lifestyle choices. At the baseline study visit, the research coordinator will provide a study overview and conduct consent. After consent has been obtained, the research coordinator will collect demographics, baseline clinical outcomes, validated surveys, and social network data for the perceived community resources and family characteristics. The research coordinator will conduct an objective community assessment and provide that information as well as the perceived community assets data to the dietitian to be used as part of the medical nutrition therapy. The research coordinator will collect relevant clinical measures, specifically blood pressure, HbA1c, and lipid panel, and validated surveys at baseline and 3- and 6-months post-intervention. The dietitian will schedule and complete the first session medical nutrition therapy within 2 weeks of baseline data collection and will continue to conduct medical nutrition therapy monthly for 6 months. The dietitian will also collect relevant clinical measures, specifically blood pressure, HbA1c, and lipid panel, and validated surveys at 3 and 6 months during the intervention period. Aim 3: Determine the preliminary effectiveness of a tailored nutrition and physical activity for those living within the household. Data will be collected at five times per participant throughout the intervention. Data collection time points will include baseline and twice during the 6 months intervention period (3 and 6 months) and then again at 3 months and 6 months post-intervention. To evaluate feasibility of the proposed intervention, we will use guiding questions (Orsmond & Cohn, 2015) that address the following: evaluation of recruitment capability and resulting sample characteristics, evaluation and refinement of data collection procedures and outcomes measures, evaluation of acceptability and suitability of intervention and study procedures, evaluation of resources and ability to manage and implement the study and intervention, and preliminary evaluation of participant responses to interventions. Acceptability of community health workers will be assessed using a previously published assessment of community health workers (Islam et al., 2017). This assessment measures attributes, such as the participants perception of cooperative extension agents and a registered dietician to address health concerns, respect and dignity, honesty, interpersonal relationships, and assistance with changing behaviors.

Monthly in-home MNT will be conducted by the RD for members of the household but will be tailored for the participant with diabetes for 6 months. Dietary counseling will be focused on living with diabetes, appropriate food choices, glycemic control, and importance of weight management. To enhance participant buy-in and sustainability, the RD will utilize Motivational Interviewing (MI) principles to work with participants to improve self-efficacy of behavior change and set Specific, Measurable, Achievable, Relevant, and Time-Bound (SMART) goals each month. Also, participants will enroll in the group facilitated Dining with Diabetes program with the option to bring one member of their social to their local Cooperative Extension offices. Dining with Diabetes is an interactive 4-session program that includes direct education on healthy eating, food preparation strategies, physical activity, emotional health, identifying complications of diabetes, and problem-solving skills.

Medical Nutrition therapy is an intervention that will be administered to the participants for 6 months.

Diabetes knowledge of the participants will be assessed using a validated Diabetes Knowledge Questionnaire (DKQ). It targets knowledge deficits which can be related to measurable outcomes, false statements or those known to be common and/or serious misconceptions (Garcia et al, 2001).

Diabetes self-management/self-efficacy will be assessed using the Diabetes Empowerment Scale. Diabetes Empowerment Scale is a 23-item scale that measures diabetes-related psychosocial self-efficacy with an overall Cronbach's uses 3 subscales: Managing the Psychosocial Aspects of Diabetes, Assessing Dissatisfaction and Readiness to Change, and Setting and Achieving Diabetes Goals (Anderson et al, 2000)

The Diabetes Distress Scale (DDS) is a 17-item scale that measures patient concerns about disease management, support, emotional burden and access to care. The response scale for each question ranges from "1" (not a problem) to "6" (a very serious problem). An average score of greater than or equal to 3 indicated moderate distress and discriminated between high and low distressed groups (Fisher et al, 2008)

Inclusion Criteria: must be diagnosed with type 2 diabetes must be from rural Kentucky must be living in rural Kentucky for at least 1 year Exclusion Criteria: potential participants without consent

The participants have been informed that their personal data will not be shared, and their confidentiality will be kept.

Albuquerque D, Nobrega C, Manco L, Padez C. The contribution of genetics and environment to obesity. Br Med Bull. 2017 Sep 1;123(1):159-173. doi: 10.1093/bmb/ldx022.

Ali O. Genetics of type 2 diabetes. World J Diabetes. 2013 Aug 15;4(4):114-23. doi: 10.4239/wjd.v4.i4.114.

Anders S, Schroeter C. Diabetes, diet-health behavior, and obesity. Front Endocrinol (Lausanne). 2015 Mar 16;6:33. doi: 10.3389/fendo.2015.00033. eCollection 2015.

Anderson RM, Funnell MM, Fitzgerald JT, Marrero DG. The Diabetes Empowerment Scale: a measure of psychosocial self-efficacy. Diabetes Care. 2000 Jun;23(6):739-43. doi: 10.2337/diacare.23.6.739.

Baig AA, Benitez A, Quinn MT, Burnet DL. Family interventions to improve diabetes outcomes for adults. Ann N Y Acad Sci. 2015 Sep;1353(1):89-112. doi: 10.1111/nyas.12844. Epub 2015 Aug 6.

Benjamini Y., Hochberg Y. (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 289-300

Bhupathiraju SN, Hu FB. Epidemiology of Obesity and Diabetes and Their Cardiovascular Complications. Circ Res. 2016 May 27;118(11):1723-35. doi: 10.1161/CIRCRESAHA.115.306825.

Chapman-Novakofski K, Karduck J. Improvement in knowledge, social cognitive theory variables, and movement through stages of change after a community-based diabetes education program. J Am Diet Assoc. 2005 Oct;105(10):1613-6. doi: 10.1016/j.jada.2005.07.010.

Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, Ekelund U, Yngve A, Sallis JF, Oja P. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003 Aug;35(8):1381-95. doi: 10.1249/01.MSS.0000078924.61453.FB.

Demir D, Bektas M. The effect of childrens' eating behaviors and parental feeding style on childhood obesity. Eat Behav. 2017 Aug;26:137-142. doi: 10.1016/j.eatbeh.2017.03.004. Epub 2017 Mar 22.

Fisher L, Glasgow RE, Mullan JT, Skaff MM, Polonsky WH. Development of a brief diabetes distress screening instrument. Ann Fam Med. 2008 May-Jun;6(3):246-52. doi: 10.1370/afm.842.

Fruh SM. Obesity: Risk factors, complications, and strategies for sustainable long-term weight management. J Am Assoc Nurse Pract. 2017 Oct;29(S1):S3-S14. doi: 10.1002/2327-6924.12510.

Garcia AA, Villagomez ET, Brown SA, Kouzekanani K, Hanis CL. The Starr County Diabetes Education Study: development of the Spanish-language diabetes knowledge questionnaire. Diabetes Care. 2001 Jan;24(1):16-21. doi: 10.2337/diacare.24.1.16. Erratum In: Diabetes Care 2001 May;24(5):972.

Griffie D, James L, Goetz S, Balotti B, Shr YH, Corbin M, Kelsey TW. Outcomes and Economic Benefits of Penn State Extension's Dining With Diabetes Program. Prev Chronic Dis. 2018 May 3;15:E50. doi: 10.5888/pcd15.170407.

Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of Obesity and Severe Obesity Among Adults: United States, 2017-2018. NCHS Data Brief. 2020 Feb;(360):1-8.

Hood KK, Hilliard M, Piatt G, Ievers-Landis CE. Effective strategies for encouraging behavior change in people with diabetes. Diabetes Manag (Lond). 2015;5(6):499-510.

Hoogland AI, Hoogland CE, Bardach SH, Tarasenko YN, Schoenberg NE. Health Behaviors in Rural Appalachia. South Med J. 2019 Aug;112(8):444-449. doi: 10.14423/SMJ.0000000000001008.

Kirkman MS, Briscoe VJ, Clark N, Florez H, Haas LB, Halter JB, Huang ES, Korytkowski MT, Munshi MN, Odegard PS, Pratley RE, Swift CS. Diabetes in older adults. Diabetes Care. 2012 Dec;35(12):2650-64. doi: 10.2337/dc12-1801. Epub 2012 Oct 25. No abstract available.

Kritchevsky SB. Taking Obesity in Older Adults Seriously. J Gerontol A Biol Sci Med Sci. 2017 Dec 12;73(1):57-58. doi: 10.1093/gerona/glx228. No abstract available.

Lawrence JM, Divers J, Isom S, Saydah S, Imperatore G, Pihoker C, Marcovina SM, Mayer-Davis EJ, Hamman RF, Dolan L, Dabelea D, Pettitt DJ, Liese AD; SEARCH for Diabetes in Youth Study Group. Trends in Prevalence of Type 1 and Type 2 Diabetes in Children and Adolescents in the US, 2001-2017. JAMA. 2021 Aug 24;326(8):717-727. doi: 10.1001/jama.2021.11165. Erratum In: JAMA. 2021 Oct 5;326(13):1331.

Martire LM, Helgeson VS. Close relationships and the management of chronic illness: Associations and interventions. Am Psychol. 2017 Sep;72(6):601-612. doi: 10.1037/amp0000066.

Massey, C.N., Appel, S.J., Buchanan, K.L., et al. (2010) Improving Diabetes Care in Rural Communities: An Overview of Current Initiatives and a Call for Renewed Efforts. Clinical Diabetes, 28, 20-27. http://dx.doi.org/10.2337/diaclin.28.1.20

Mayberry LS, Berg CA, Greevy RA Jr, Wallston KA. Assessing helpful and harmful family and friend involvement in adults' type 2 diabetes self-management. Patient Educ Couns. 2019 Jul;102(7):1380-1388. doi: 10.1016/j.pec.2019.02.027. Epub 2019 Mar 1.

Misra R, Fitch C. A model exploring the relationship between nutrition knowledge, behavior, diabetes self-management and outcomes from the dining with diabetes program. Prev Med. 2020 Dec;141:106296. doi: 10.1016/j.ypmed.2020.106296. Epub 2020 Oct 23.

Okobi OE, Ajayi OO, Okobi TJ, Anaya IC, Fasehun OO, Diala CS, Evbayekha EO, Ajibowo AO, Olateju IV, Ekabua JJ, Nkongho MB, Amanze IO, Taiwo A, Okorare O, Ojinnaka US, Ogbeifun OE, Chukwuma N, Nebuwa EJ, Omole JA, Udoete IO, Okobi RK. The Burden of Obesity in the Rural Adult Population of America. Cureus. 2021 Jun 20;13(6):e15770. doi: 10.7759/cureus.15770. eCollection 2021 Jun.

Rollnick S, Butler CC, Kinnersley P, Gregory J, Mash B. Motivational interviewing. BMJ. 2010 Apr 27;340:c1900. doi: 10.1136/bmj.c1900. No abstract available.

Schmitt A, Gahr A, Hermanns N, Kulzer B, Huber J, Haak T. The Diabetes Self-Management Questionnaire (DSMQ): development and evaluation of an instrument to assess diabetes self-care activities associated with glycaemic control. Health Qual Life Outcomes. 2013 Aug 13;11:138. doi: 10.1186/1477-7525-11-138.

Schor EL. The influence of families on child health. Family behaviors and child outcomes. Pediatr Clin North Am. 1995 Feb;42(1):89-102. doi: 10.1016/s0031-3955(16)38910-6.

Sherbourne CD, Stewart AL. The MOS social support survey. Soc Sci Med. 1991;32(6):705-14. doi: 10.1016/0277-9536(91)90150-b.

Strasser B. Physical activity in obesity and metabolic syndrome. Ann N Y Acad Sci. 2013 Apr;1281(1):141-59. doi: 10.1111/j.1749-6632.2012.06785.x. Epub 2012 Nov 21.

Swift DL, Johannsen NM, Lavie CJ, Earnest CP, Church TS. The role of exercise and physical activity in weight loss and maintenance. Prog Cardiovasc Dis. 2014 Jan-Feb;56(4):441-7. doi: 10.1016/j.pcad.2013.09.012. Epub 2013 Oct 11.

van Dijk SJ, Molloy PL, Varinli H, Morrison JL, Muhlhausler BS; Members of EpiSCOPE. Epigenetics and human obesity. Int J Obes (Lond). 2015 Jan;39(1):85-97. doi: 10.1038/ijo.2014.34. Epub 2014 Feb 25.

Weihs, K., Fisher, L., & Baird, M. (2002). Families, health, and behavior: A section of the commissioned report by the Committee on Health and Behavior: Research, Practice, and Policy Division of Neuroscience and Behavioral Health and Division of Health Promotion and Disease Prevention Institute of Medicine, National Academy of Sciences. Families, Systems, & Health, 20(1), 7-46. https://doi.org/10.1037/h0089481

Centers for Disease Control and Prevention. National diabetes statistics report 2020: Estimates of diabetes and its burden in the United States. 2020.

National Institute for Diabetes and Digestive and Kidney Diseases. (2016). Diabetes diet, eating, and physical activity