Reducing Chronic Disease Health Disparities in the Deep South

Expanding Our Cancer Prevention and Control Infrastructure to Reduce Cancer and Other Chronic Disease Health Disparities in the Deep South

The study is a gardening intervention among 150 older cancer survivors and individuals living with chronic disease (cardiovascular disease and diabetes) in the states of Alabama and Mississippi. This program focuses on 15 counties where a Community Health Advisor training program is in place (Bullock, Calhoun, Dallas Madison, Marengo, Monroe, Sumter, Talladega, Walker Counties in Alabama and Boliver, Granada, Humphrey, Panola, Sunflower, and Yazoo Counties in Mississippi). Participants are paired with Cooperative Extension certified Master Gardeners to plant a vegetable garden at their place of residence (the intervention). Baseline, midpoint, and 1 year follow up will occur. Previous pilot work provides an established relationship with the Cooperative Extension as well as training mechanisms for the Master Gardeners.

Based on the investigator's previously successful gardening interventions that paired cancer survivors with Cooperative Extension Master Gardeners (MG) since 2011, now proposed; a sample of 150 older individuals living with chronic diseases in 15 counties in Alabama and Mississippi. The purpose of this larger study is to determine the efficacy of a gardening intervention that would pair older cancer survivors and individuals living with chronic disease (heart disease and diabetes) (≥ 65 years of age) with master gardeners. Vegetable gardens will be established at participants' homes, and a yearlong intervention involving bimonthly contact between participants and MGs to plan and plant gardens, check plant status, harvest, and rotate plantings will be conducted. It is hypothesized that this intervention will significantly improve fruit and vegetable consumption, physical activity, quality of life and physical functioning. Outcomes: Outcomes will be measured by the number of participants recruited, improvements in physical functioning, physical performance (senior fitness battery and grip strength), physical activity, health-related quality of life, reassurance of worth, and self-efficacy of gardening. Additional outcomes are blood pressure, BMI, waist circumference, lipid, glucose, and HbA1c. Background: There are roughly 15 million cancer survivors in the US, comprising 4% of the populace. The number of cancer survivors is skyrocketing due to a confluence of the following factors: 1) Americans are aging; 2) cancer is an age-related disease (>60% of cancer survivors are age 65+), and 3) improvements in early detection and treatment have resulted in many common cancers having 5-year cure rates that surpass 90%. Rising numbers of cancer survivors represent good news, but over $130 billion annually is needed to address their long-term health and psychosocial needs. Compared to others, cancer survivors are at higher risk for other cancers, cardiovascular disease, osteoporosis, and diabetes. The accelerated functional decline also is a major problem for cancer survivors, especially those who are older. Baker et al. found that compared to age-matched controls, cancer cases (n=45,494) had significantly lower physical and social functioning, vitality, mental health, and health-related quality of life (HRQoL) (p<0.001). The results of others are similar and suggest that cancer survivors face functional decline that threatens their ability to live independently, posing a burden to themselves, their families and the health care system. Thus, cancer survivorship is claimed as a national priority, and there is a call for interventions that target markedly vulnerable subsets. Prior interventions to improve physical activity (PA) and diet quality (DQ) has proven effective in improving functional status and other health outcomes in cancer survivors. The 2 largest randomized controlled trials (RCTs) to date aimed at physical function, RENEW (Reach-out to ENhancE Wellness, n=641) and Project LEAD (Leading the way in Exercise and Diet, n=182), were led by Demark-Wahnefried (PI) and tested home-based interventions. Both RCTs resulted in significant improvements in DQ, PA and physical function, with few adverse events and low rates of attrition, but there was little capacity for dissemination once funding ended. Thus, the investigators have sought to develop interventions that build on existing programs and that have a high likelihood of translation into the community. The proposed intervention relies on (a) the extant infrastructure of the Alabama Cooperative Extension, (b) our collaborative pilot studies with Master Gardeners (MGs), (c) our data that show that gardening consists of low-to-moderate PA that combines aerobic and strength training activities associated with improved health, and (d) new observational data published in 2012 that show that gardeners have significantly better gait speed, balance, and significantly fewer chronic conditions, functional limitations and falls. MG Programs exist in land grant universities in all 50 United States. Certified MGs complete > 100 hrs. of instruction and community service (CS) and 25 hrs./year of CS to maintain active status. In surveying 184 MGs in AL, it was found that 71% were "extremely interested" in mentoring a cancer survivor on vegetable gardening for their CS, and an extra 26% stated that "they were interested and wanted to learn more." Thus, the project is of great interest and builds on an extant infrastructure for sustainability. Ultimately, this intervention could be disseminated to states with 3 growing seasons and adapted to colder weather in those with 2 growing seasons. The intervention also could be adapted for persons with other types of chronic diseases in which physical functioning and lifestyle behaviors are key. Finally, this project is significant because the intervention has great potential for sustainability since gardening: (a) involves many activities which prevent satiation common with other forms of exercise; (b) provides a sense of achievement and zest for life that come from nurturing and observing new life and growth, and (c) imparts natural prompts since plants require regular care (watering) and attention (harvesting) and serve as continual and dynamic behavioral cues.

The study is a gardening intervention among 150 older cancer survivors and individuals living with chronic disease (cardiovascular disease and diabetes) in the states of Alabama and Mississippi. This program focuses on 15 counties where a Community Health Advisor training program is in place (Bullock, Calhoun, Dallas Madison, Marengo, Monroe, Sumter, Talladega, Walker Counties in Alabama and Boliver, Granada, Humphrey, Panola, Sunflower, and Yazoo Counties in Mississippi). Participants are paired with Cooperative Extension certified Master Gardeners to plant a vegetable garden at their place of residence (the intervention). Baseline, midpoint, and 1 year follow up will occur. Previous pilot work provides an established relationship with the Cooperative Extension as well as training mechanisms for the Master Gardeners.

We will be tracking the interaction with community master gardeners and study participants using REDCap questionnaires. Information gathered will include: Number of participants recruited Number of visits (total) Number of completed visits (within the window) Number of completed visits (outside of window)

The investigators will be administering the EATS survey to all participants designed to measure the intake of fruits and vegetables and has been used widely to track changes in fruit and vegetable intake in specific population groups. This screener termed the By Meal version, asks about usual intakes of fruits and other vegetables by the time of day. Participants list how many servings they eat, an algorithm converts the totals into an average per day; then this average is used to estimate the intake of each participant throughout the study.

For this data point, we will administer the Reassurance of Worth instrument (Revised Social Provision Scale [SPS10]): This instrument posits that social support is defined in terms of its function, namely, social provisions. This theory considers the functions of social relationships across specific social roles (e.g., romantic partner, spouse, family members, friends, colleagues, etc.), especially when individuals face critical life-changing events. Social ties provide social support and that specific social ties might meet individuals' different social support needs or might influence individuals to offer social support. The scale is as follows: Strongly Disagree Disagree Agree Strongly Agree 1 2 3 4 SPS-10 can be a useful clinical and research tool to assess perceived social support not only in perinatal and pae-diatric settings, but also in general medical and mental health settings

We will administer the self-efficacy for gardening: This investigator-created screener is designed to gather information on the degree to which participants feel confident working in their own garden. Questions are centered on: 1.) time spent in the garden, 2.) did participants partake in gardening with anyone else, 3.) and whether or not gardening influenced participants to eat more vegetables.

We will administer the EATS screener: This assessment tool was designed to measure intake of fruits and vegetables and has been used widely to track changes in fruit and vegetable intake in specific population groups. There are two versions of this screener. This version, termed the By Meal version, asks about usual intakes of fruits and other vegetables by time of day. The other version, termed the All-Day version, asks about usual intakes of all items. Both are machine scan-able. Goal achievement is based on an increase of ≥1 serving/ day of Fruits and vegetables assessed via the EATS score pre-and post-program intervention.

Goal achievement based on an increase of ≥5 points on the SF36 Physical Function subscale (PFSS) The SF36 PFSS is a 10-item subscale assessing general physical function and is valid and reliable for use in healthy and chronically-ill adults. Internal consistency is excellent: α=0.89 to 0.92. It has published norms, is sensitive to change, and has performed well in our past studies; we have found it free of ceiling effects.

Goal achievement is based on an improvement in > 4 of 6 performance tests Senior Fitness Test Battery tests several physical function domains: lower and upper body strength (30-second chair stand, arm curl), endurance (2-minute step test), flexibility (chair sit and-reach, back scratch), agility/dynamic balance (8-ft Get Up & Go), and gait speed (8-foot walk); the test battery provides an objective measure of physical function, is sensitive to change, not associated with ceiling effects, and has normative scores. Additional test include grip strength, objectively measured via dynamometer (disability and functional limitation predictor).

SF12 Health Related Quality of Life Index The SF12 Health-Related Quality of Life Index (HRQoL) will provide a global measure of HRQoL, and each of the eight subscales will be explored separate (i.e. Physical functioning, Role-physical, Bodily pain, General health, Vitality, Social functioning, Role-emotional, Mental heat). Internal consistency and reliability for all eight subscales is high, ICC ranging from 0.78 to 0.93. HRQoL weights to create Quality Adjusted Life Years (QALYs) from the SF12 will be done using methods of Brazier & colleagues.

One of six subscales of the Revised Social Provision Scale, this measure will be used to assess the psychosocial benefits of gardening. Several gardening studies have reported enhanced self-esteem, increased independence, and increased zest for life associated with gardening. Reliability estimates range from 0.60 to 0.70. Social Support and Eating Habits (10 items) and Exercise Surveys (13 items): This has been widely used in diverse samples and has strong psychometric properties (α=.70), surveys will be adapted for gardening using identical anchors

This is the organizing concept in Social Cognitive Theory and is defined as people's beliefs in their capability to organize and execute courses of action to deal with prospective situations. Self-efficacy beliefs are domain-specific; thus, within the context of this study, self-efficacy is survivors' beliefs in their ability to meet the challenges of maintaining a successful vegetable garden.

Goal achievement based on an increase of ≥30 minutes/week of moderate to vigorous activity assessed via Godin Leisure Time Activity Questionnaire. Self-reported physical activity will be provided using the Godin Leisure Time Activity Questionnaire, a validated and sensitive tool that captures physical activities.

Participants will be weighed (to the nearest 0.1 kg) at each assessment (baseline and 1-year) while wearing light clothing without shoes using a professional digital scale regularly calibrated to current standards.

Participants' height (to the nearest 0.1 cm) will be measured without shoes using a tape measure. Height will be measured only at the baseline.

Using weight and height data described above, BMI will be calculated using the equation BMI = weight (kg)/height (m2).

Waist circumference will be measured (to the nearest 0.5cm) at the end of normal expiration on base skin at the belly button using a constant-tension spring-loaded tape device. Measures will be taken in a private room rather than in a larger group setting. A privacy screen or curtain will be used when a larger room must be subdivided for the assessments.

Participant blood pressure (BP) will be measured by trained staff using a calibrated automatic sphygmomanometer. Arm circumference will be measured to determine the proper size arm cuff, to avoid over- or under-estimation of the true BP. Participants will be asked to sit with both feet flat on the floor and to rest without talking for five minutes before measurement. BP will be measured twice according standard NHLBI protocols. The two measurements will be averaged.

A blood sample will be collected by trained phlebotomists to process lipid profile [including total cholesterol (TC), High Density Lipoprotein cholesterol (HDL-C), triglycerides and Low Density Lipoprotein cholesterol (LDLC)], glucose and Hemaglobin A1c (HbA1C). Samples will be stored in a cooler for transport back to lab (UAB or community location) for processing. At the lab, plasma and/or serum will be aliquoted into 0.5 ml cryovials and stored on in -80 degree freezer until analyses. Lipids, glucose, and HbA1C will be analyzed in the UAB Diabetes Research Core laboratory. (Overnight fasting is required).

A blood sample will be collected by trained phlebotomists to process lipid profile [including total cholesterol (TC), High Density Lipoprotein cholesterol (HDL-C), triglycerides and Low Density Lipoprotein cholesterol (LDLC)], glucose and Hemaglobin A1c (HbA1C). Samples will be stored in a cooler for transport back to lab (UAB or community location) for processing. At the lab, plasma and/or serum will be aliquoted into 0.5 ml cryovials and stored on in -80 degree freezer until analyses. Lipids, glucose, and HbA1C will be analyzed in the UAB Diabetes Research Core laboratory. (Overnight fasting is required).

A blood sample will be collected by trained phlebotomists to process lipid profile [including total cholesterol (TC), High Density Lipoprotein cholesterol (HDL-C), triglycerides and Low Density Lipoprotein cholesterol (LDLC)], glucose and Hemaglobin A1c (HbA1C). Samples will be stored in a cooler for transport back to lab (UAB or community location) for processing. At the lab, plasma and/or serum will be aliquoted into 0.5 ml cryovials and stored on in -80 degree freezer until analyses. Lipids, glucose, and HbA1C will be analyzed in the UAB Diabetes Research Core laboratory. (Overnight fasting is required).

A blood sample will be collected by trained phlebotomists to process lipid profile [including total cholesterol (TC), High Density Lipoprotein cholesterol (HDL-C), triglycerides and Low Density Lipoprotein cholesterol (LDLC)], glucose and Hemaglobin A1c (HbA1C). Samples will be stored in a cooler for transport back to lab (UAB or community location) for processing. At the lab, plasma and/or serum will be aliquoted into 0.5 ml cryovials and stored on in -80 degree freezer until analyses. Lipids, glucose, and HbA1C will be analyzed in the UAB Diabetes Research Core laboratory. (Overnight fasting is required).

Inclusion Criteria: Men and women diagnosed with a cancer of favorable prognosis (localized and regional staged female breast, and prostate cancers; localized colon & rectum, uterine cervix & corpus, kidney/renal pelvis, non-Hodgkin lymphoma, oral cavity/pharynx, and esophagus cancers; and in situ bladder cancer); and have no medical conditions that would preclude gardening or the consumption of a diet high in fruits and vegetables (e.g., pharmacologic doses of warfarin) -In addition, men and women living who are medically stable, but managing chronic disease (cardiovascular disease and/ or diabetes) are eligible. We will include individuals who: (1) are diagnosed with a loco-regionally staged cancer associated with an 80% or greater 5-year survival rate (localized and regional staged female breast, and prostate cancers; localized colon & rectum, uterine cervix & corpus, kidney/renal pelvis, non-Hodgkin lymphoma, oral cavity/pharynx, and esophagus cancers; and in situ bladder cancer) (2) diagnosed with diabetes or cardiovascular disease (3) reside in the 15 counties; (4) completed primary curative cancer treatments, i.e., surgery, chemotherapy or radiation therapy; (5) are at least 65 years of age; (6) are at higher risk of functional decline (≥ 2 physical function (PF) limitations as defined by the SF12PF subscale); (7) currently eat less than 5 servings of fruits and vegetables (F/V)/ day; (8) exercise less than 150 minutes/ week; (9) speak and write in English (some of our scales are not validated in other populations/languages); and (10) are willing to participate in the follow-up assessments; (11) competent to provide informed consent; (12) Access to a phone and/ or email and internet We will exclude individuals who: (1) are not competent due to mental health or other very serious comorbid conditions (e.g., severe orthopedic conditions or scheduled for a hip or knee replacement with 6 months, paralysis, unstable angina or who have experienced a myocardial infarction, congestive heart failure or pulmonary conditions that require hospitalization or oxygen within 6 months, stroke, degenerative neurological conditions, unstable angina (UA), percutaneous coronary intervention (PCI)/coronary artery bypass grafting (CABG), severe valve disease or New York Heart Association (NYHA_ class III-IV heart failure); (2) have any medical condition substantially limiting moderate physical activity; (3) currently taking pharmacologic doses of warfarin (does not include doses taken to maintain a port); (4) do not reside in a location that can accommodate 4 or more Earthboxes or 1-raised bed (4'x 8'), and that get at least 4 hours of sun a day; (5) do not have running water; (6) have recent experience with vegetable gardening, e.g. planted a vegetable garden within the past year; (7) have a history of lymphedema flares, axillary node dissection of 10 or more lymph nodes per side; (8) life expectancy of less than 1 year ; (9) Untreated cardiac conditions including complex congenital heart disease, or untreated complex arrhythmias; or (10) Current substance abuse

Only aggregated, de-identified data will be retained. Currently, there is no plan to share this data outside of the immediate investigative team.

Partridge EE, Fouad MN, Hinton AW, Hardy CM, Liscovicz N, White-Johnson F, Higginbotham JC. The deep South network for cancer control: eliminating cancer disparities through community-academic collaboration. Fam Community Health. 2005 Jan-Mar;28(1):6-19. doi: 10.1097/00003727-200501000-00004.

Lisovicz N, Johnson RE, Higginbotham J, Downey JA, Hardy CM, Fouad MN, Hinton AW, Partridge EE. The Deep South Network for cancer control. Building a community infrastructure to reduce cancer health disparities. Cancer. 2006 Oct 15;107(8 Suppl):1971-9. doi: 10.1002/cncr.22151.

Centers for Disease Control and Prevention. Prevalence of Diagnosed Diabetes - 2013. https://www.cdc.gov/diabetes/data/statistics-report/diagnosed.html2018.

Castle PE, Gage JC, Partridge EE, Rausa A, Gravitt PE, Scarinci IC. Human papillomavirus genotypes detected in clinician-collected and self-collected specimens from women living in the Mississippi Delta. BMC Infect Dis. 2013 Jan 7;13:5. doi: 10.1186/1471-2334-13-5.

Castle PE, Rausa A, Walls T, Gravitt PE, Partridge EE, Olivo V, Niwa S, Morrissey KG, Tucker L, Katki H, Scarinci I. Comparative community outreach to increase cervical cancer screening in the Mississippi Delta. Prev Med. 2011 Jun;52(6):452-5. doi: 10.1016/j.ypmed.2011.03.018. Epub 2011 Apr 8.

Litton AG, Castle PE, Partridge EE, Scarinci IC. Cervical cancer screening preferences among African American women in the Mississippi Delta. J Health Care Poor Underserved. 2013 Feb;24(1):46-55. doi: 10.1353/hpu.2013.0017.

Scarinci IC, Garcia FA, Kobetz E, Partridge EE, Brandt HM, Bell MC, Dignan M, Ma GX, Daye JL, Castle PE. Cervical cancer prevention: new tools and old barriers. Cancer. 2010 Jun 1;116(11):2531-42. doi: 10.1002/cncr.25065.

Scarinci IC, Litton AG, Garces-Palacio IC, Partridge EE, Castle PE. Acceptability and usability of self-collected sampling for HPV testing among African-American women living in the Mississippi Delta. Womens Health Issues. 2013 Mar-Apr;23(2):e123-30. doi: 10.1016/j.whi.2012.12.003. Epub 2013 Feb 12.

Carroll WR, Foushee HR Jr, Hardy CM, Floyd T, Sinclair CF, Scarinci I. Tobacco use among rural African American young adult males. Otolaryngol Head Neck Surg. 2011 Aug;145(2):259-63. doi: 10.1177/0194599811404968. Epub 2011 Apr 26.

Sinclair CF, Foushee HR, Pevear JS 3rd, Scarinci IC, Carroll WR. Patterns of blunt use among rural young adult African-American men. Am J Prev Med. 2012 Jan;42(1):61-4. doi: 10.1016/j.amepre.2011.08.023.

Sinclair CF, Foushee HR, Scarinci I, Carroll WR. Perceptions of harm to health from cigarettes, blunts, and marijuana among young adult African American men. J Health Care Poor Underserved. 2013 Aug;24(3):1266-75. doi: 10.1353/hpu.2013.0126.

Partridge EE, Hardy CM, Baskin ML, Fouad M, Willis L, James G, Wynn T. Shifting Community-Based Participatory Infrastructure from Education/Outreach to Research: Challenges and Solutions. Prog Community Health Partnersh. 2015;9 Suppl(Suppl):33-9. doi: 10.1353/cpr.2015.0019.

Pekmezi D, Ainsworth C, Holly T, Williams V, Benitez T, Wang K, Rogers LQ, Marcus B, Demark-Wahnefried W. Rationale, design, and baseline findings from a pilot randomized trial of an IVR-Supported physical activity intervention for cancer prevention in the Deep South: the DIAL study. Contemp Clin Trials Commun. 2017 Dec;8:218-226. doi: 10.1016/j.conctc.2017.10.008. Epub 2017 Nov 2.

Robinson JC, Carson TL, Johnson ER, Hardy CM, Shikany JM, Green E, Willis LM, Marron JV Jr, Li Y, Lee CH, Baskin ML. Assessing environmental support for better health: active living opportunity audits in rural communities in the southern United States. Prev Med. 2014 Sep;66:28-33. doi: 10.1016/j.ypmed.2014.05.021. Epub 2014 Jun 2.

Ard JD, Carson TL, Shikany JM, Li Y, Hardy CM, Robinson JC, Williams AG, Baskin ML. Weight loss and improved metabolic outcomes amongst rural African American women in the Deep South: six-month outcomes from a community-based randomized trial. J Intern Med. 2017 Jul;282(1):102-113. doi: 10.1111/joim.12622. Epub 2017 May 17.

Hood CM, Gennuso KP, Swain GR, Catlin BB. County Health Rankings: Relationships Between Determinant Factors and Health Outcomes. Am J Prev Med. 2016 Feb;50(2):129-35. doi: 10.1016/j.amepre.2015.08.024. Epub 2015 Oct 31.

Roth GA, Dwyer-Lindgren L, Bertozzi-Villa A, Stubbs RW, Morozoff C, Naghavi M, Mokdad AH, Murray CJL. Trends and Patterns of Geographic Variation in Cardiovascular Mortality Among US Counties, 1980-2014. JAMA. 2017 May 16;317(19):1976-1992. doi: 10.1001/jama.2017.4150.

Mokdad AH, Dwyer-Lindgren L, Fitzmaurice C, Stubbs RW, Bertozzi-Villa A, Morozoff C, Charara R, Allen C, Naghavi M, Murray CJ. Trends and Patterns of Disparities in Cancer Mortality Among US Counties, 1980-2014. JAMA. 2017 Jan 24;317(4):388-406. doi: 10.1001/jama.2016.20324.

National Cancer Institute. State Cancer Profiles, 2011-2015. Accessed Februrary 28, 2019 at http://statecancerprofiles.cancer.govn.d.

Centers for Disease Control and Prevention. National Center for Chronic Disease Prevention and Health Promotion. Chronic Disease Indicators (CDI) Data [online]. [accessed Mar 11, 2019]. URL: https://nccd.cdc.gov/cdi. 2016.

Braveman P, Egerter S, Williams DR. The social determinants of health: coming of age. Annu Rev Public Health. 2011;32:381-98. doi: 10.1146/annurev-publhealth-031210-101218.

US Burden of Disease Collaborators; Mokdad AH, Ballestros K, Echko M, Glenn S, Olsen HE, Mullany E, Lee A, Khan AR, Ahmadi A, Ferrari AJ, Kasaeian A, Werdecker A, Carter A, Zipkin B, Sartorius B, Serdar B, Sykes BL, Troeger C, Fitzmaurice C, Rehm CD, Santomauro D, Kim D, Colombara D, Schwebel DC, Tsoi D, Kolte D, Nsoesie E, Nichols E, Oren E, Charlson FJ, Patton GC, Roth GA, Hosgood HD, Whiteford HA, Kyu H, Erskine HE, Huang H, Martopullo I, Singh JA, Nachega JB, Sanabria JR, Abbas K, Ong K, Tabb K, Krohn KJ, Cornaby L, Degenhardt L, Moses M, Farvid M, Griswold M, Criqui M, Bell M, Nguyen M, Wallin M, Mirarefin M, Qorbani M, Younis M, Fullman N, Liu P, Briant P, Gona P, Havmoller R, Leung R, Kimokoti R, Bazargan-Hejazi S, Hay SI, Yadgir S, Biryukov S, Vollset SE, Alam T, Frank T, Farid T, Miller T, Vos T, Barnighausen T, Gebrehiwot TT, Yano Y, Al-Aly Z, Mehari A, Handal A, Kandel A, Anderson B, Biroscak B, Mozaffarian D, Dorsey ER, Ding EL, Park EK, Wagner G, Hu G, Chen H, Sunshine JE, Khubchandani J, Leasher J, Leung J, Salomon J, Unutzer J, Cahill L, Cooper L, Horino M, Brauer M, Breitborde N, Hotez P, Topor-Madry R, Soneji S, Stranges S, James S, Amrock S, Jayaraman S, Patel T, Akinyemiju T, Skirbekk V, Kinfu Y, Bhutta Z, Jonas JB, Murray CJL. The State of US Health, 1990-2016: Burden of Diseases, Injuries, and Risk Factors Among US States. JAMA. 2018 Apr 10;319(14):1444-1472. doi: 10.1001/jama.2018.0158.

Henley SJ, Anderson RN, Thomas CC, Massetti GM, Peaker B, Richardson LC. Invasive Cancer Incidence, 2004-2013, and Deaths, 2006-2015, in Nonmetropolitan and Metropolitan Counties - United States. MMWR Surveill Summ. 2017 Jul 7;66(14):1-13. doi: 10.15585/mmwr.ss6614a1.

Moy E, Garcia MC, Bastian B, Rossen LM, Ingram DD, Faul M, Massetti GM, Thomas CC, Hong Y, Yoon PW, Iademarco MF. Leading Causes of Death in Nonmetropolitan and Metropolitan Areas- United States, 1999-2014. MMWR Surveill Summ. 2017 Jan 13;66(1):1-8. doi: 10.15585/mmwr.ss6601a1. Erratum In: MMWR Morb Mortal Wkly Rep. 2017 Jan 27;66(3):93.

US Department of Agriculture: Economic Research Service. Rural-Urban Continuum Codes. https://www.ers.usda.gov/data-products/rural-urban-continuum-codes/n.d.

US Department of Health and Human Services. State Cancer Profiles: Age-Adjusted Mortality Rates by Cancer Site (2011-2015). In: National Cancer Institute, ed. https://statecancerprofiles.cancer.gov/index.htmln.d.

Centers for Disease Control and Prevention. Compressed Mortality File 1999-2016 on CDC WONDER Online Database. http://wonder.cdc.gov/cmf-icd10.html2017.

Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System Survey Data. In: US Department of Health and Human Services, ed.2015.

Roland KB, Milliken EL, Rohan EA, DeGroff A, White S, Melillo S, Rorie WE, Signes CC, Young PA. Use of Community Health Workers and Patient Navigators to Improve Cancer Outcomes Among Patients Served by Federally Qualified Health Centers: A Systematic Literature Review. Health Equity. 2017 May 1;1(1):61-76. doi: 10.1089/heq.2017.0001. eCollection 2017.

Kim K, Choi JS, Choi E, Nieman CL, Joo JH, Lin FR, Gitlin LN, Han HR. Effects of Community-Based Health Worker Interventions to Improve Chronic Disease Management and Care Among Vulnerable Populations: A Systematic Review. Am J Public Health. 2016 Apr;106(4):e3-e28. doi: 10.2105/AJPH.2015.302987. Epub 2016 Feb 18.

Fisher EB, Boothroyd RI, Elstad EA, Hays L, Henes A, Maslow GR, Velicer C. Peer support of complex health behaviors in prevention and disease management with special reference to diabetes: systematic reviews. Clin Diabetes Endocrinol. 2017 May 25;3:4. doi: 10.1186/s40842-017-0042-3. eCollection 2017.

Hardy CM, Wynn TA, Huckaby F, Lisovicz N, White-Johnson F. African American community health advisors trained as research partners: recruitment and training. Fam Community Health. 2005 Jan-Mar;28(1):28-40. doi: 10.1097/00003727-200501000-00006.

Hinton A, Downey J, Lisovicz N, Mayfield-Johnson S, White-Johnson F. The community health advisor program and the deep South network for cancer control: health promotion programs for volunteer community health advisors. Fam Community Health. 2005 Jan-Mar;28(1):20-7. doi: 10.1097/00003727-200501000-00005.

Lisovicz N, Wynn T, Fouad M, Partridge EE. Cancer health disparities: what we have done. Am J Med Sci. 2008 Apr;335(4):254-9. doi: 10.1097/maj.0b013e31816a43ad. No abstract available.

Morales M. Health Literacy Research Methods: A Pilot Study Investigation With Adult Beginning Readers. International Journal of Qualitative Methods 2017;16:1609406917709913.

Greenhalgh T, Robert G, Macfarlane F, Bate P, Kyriakidou O. Diffusion of innovations in service organizations: systematic review and recommendations. Milbank Q. 2004;82(4):581-629. doi: 10.1111/j.0887-378X.2004.00325.x.

Navarro AM, Raman R, McNicholas LJ, Loza O. Diffusion of cancer education information through a Latino community health advisor program. Prev Med. 2007 Aug-Sep;45(2-3):135-8. doi: 10.1016/j.ypmed.2007.05.017. Epub 2007 Jun 2.

Bluethmann SM, Mariotto AB, Rowland JH. Anticipating the "Silver Tsunami": Prevalence Trajectories and Comorbidity Burden among Older Cancer Survivors in the United States. Cancer Epidemiol Biomarkers Prev. 2016 Jul;25(7):1029-36. doi: 10.1158/1055-9965.EPI-16-0133.

Miller KD, Siegel RL, Lin CC, Mariotto AB, Kramer JL, Rowland JH, Stein KD, Alteri R, Jemal A. Cancer treatment and survivorship statistics, 2016. CA Cancer J Clin. 2016 Jul;66(4):271-89. doi: 10.3322/caac.21349. Epub 2016 Jun 2.

Roy S, Vallepu S, Barrios C, Hunter K. Comparison of Comorbid Conditions Between Cancer Survivors and Age-Matched Patients Without Cancer. J Clin Med Res. 2018 Dec;10(12):911-919. doi: 10.14740/jocmr3617w. Epub 2018 Oct 30.

Bennett JA, Winters-Stone KM, Dobek J, Nail LM. Frailty in older breast cancer survivors: age, prevalence, and associated factors. Oncol Nurs Forum. 2013 May 1;40(3):E126-34. doi: 10.1188/13.ONF.E126-E134.

Ronning B, Wyller TB, Jordhoy MS, Nesbakken A, Bakka A, Seljeflot I, Kristjansson SR. Frailty indicators and functional status in older patients after colorectal cancer surgery. J Geriatr Oncol. 2014 Jan;5(1):26-32. doi: 10.1016/j.jgo.2013.08.001. Epub 2013 Aug 30.

Baker F, Haffer SC, Denniston M. Health-related quality of life of cancer and noncancer patients in Medicare managed care. Cancer. 2003 Feb 1;97(3):674-81. doi: 10.1002/cncr.11085.

Demark-Wahnefried W, Clipp EC, Lipkus IM, Lobach D, Snyder DC, Sloane R, Peterson B, Macri JM, Rock CL, McBride CM, Kraus WE. Main outcomes of the FRESH START trial: a sequentially tailored, diet and exercise mailed print intervention among breast and prostate cancer survivors. J Clin Oncol. 2007 Jul 1;25(19):2709-18. doi: 10.1200/JCO.2007.10.7094.

Demark-Wahnefried W, Morey MC, Clipp EC, Pieper CF, Snyder DC, Sloane R, Cohen HJ. Leading the Way in Exercise and Diet (Project LEAD): intervening to improve function among older breast and prostate cancer survivors. Control Clin Trials. 2003 Apr;24(2):206-23. doi: 10.1016/s0197-2456(02)00266-0.

Morey MC, Snyder DC, Sloane R, Cohen HJ, Peterson B, Hartman TJ, Miller P, Mitchell DC, Demark-Wahnefried W. Effects of home-based diet and exercise on functional outcomes among older, overweight long-term cancer survivors: RENEW: a randomized controlled trial. JAMA. 2009 May 13;301(18):1883-91. doi: 10.1001/jama.2009.643.

Park SA, Shoemaker CA, Haub MD. A preliminary investigation on exercise intensities of gardening tasks in older adults. Percept Mot Skills. 2008 Dec;107(3):974-80. doi: 10.2466/pms.107.3.974-980.

Blair CK, Morey MC, Desmond RA, Cohen HJ, Sloane R, Snyder DC, Demark-Wahnefried W. Light-intensity activity attenuates functional decline in older cancer survivors. Med Sci Sports Exerc. 2014 Jul;46(7):1375-83. doi: 10.1249/MSS.0000000000000241.

Chen TY, Janke MC. Gardening as a potential activity to reduce falls in older adults. J Aging Phys Act. 2012 Jan;20(1):15-31. doi: 10.1123/japa.20.1.15.

Desmond R, Jackson BE, Hunter G. Utilization of 2013 BRFSS Physical Activity Data for State Cancer Control Plan Objectives: Alabama Data. South Med J. 2015 May;108(5):290-7. doi: 10.14423/SMJ.0000000000000282.

Kerr J, Marshall S, Godbole S, Neukam S, Crist K, Wasilenko K, Golshan S, Buchner D. The relationship between outdoor activity and health in older adults using GPS. Int J Environ Res Public Health. 2012 Dec;9(12):4615-25. doi: 10.3390/ijerph9124615.

Kerr J, Sallis JF, Saelens BE, Cain KL, Conway TL, Frank LD, King AC. Outdoor physical activity and self rated health in older adults living in two regions of the U.S. Int J Behav Nutr Phys Act. 2012 Jul 30;9:89. doi: 10.1186/1479-5868-9-89.

Sommerfeld AJ, Waliczek TM, Zajicek JM. Growing Minds: Evaluating the Effect of Gardening on Quality of Life and Physical Activity Level of Older Adults. 2010;20:705.

Aziz NM, Rowland JH. Cancer survivorship research among ethnic minority and medically underserved groups. Oncol Nurs Forum. 2002 Jun;29(5):789-801. doi: 10.1188/02.ONF.789-801.

Kaur JS, Coe K, Rowland J, Braun KL, Conde FA, Burhansstipanov L, Heiney S, Kagawa-Singer M, Lu Q, Witte C. Enhancing life after cancer in diverse communities. Cancer. 2012 Nov 1;118(21):5366-73. doi: 10.1002/cncr.27491. Epub 2012 Mar 20.

Campbell MK, Demark-Wahnefried W, Symons M, Kalsbeek WD, Dodds J, Cowan A, Jackson B, Motsinger B, Hoben K, Lashley J, Demissie S, McClelland JW. Fruit and vegetable consumption and prevention of cancer: the Black Churches United for Better Health project. Am J Public Health. 1999 Sep;89(9):1390-6. doi: 10.2105/ajph.89.9.1390.

Campbell MK, Motsinger BM, Ingram A, Jewell D, Makarushka C, Beatty B, Dodds J, McClelland J, Demissie S, Demark-Wahnefried W. The North Carolina Black Churches United for Better Health Project: intervention and process evaluation. Health Educ Behav. 2000 Apr;27(2):241-53. doi: 10.1177/109019810002700210.

Demark-Wahnefried W, McClelland JW, Jackson B, Campbell MK, Cowan A, Hoben K, Rimer BK. Partnering with African American churches to achieve better health: lessons learned during the Black Churches United for Better Health 5 a day project. J Cancer Educ. 2000 Fall;15(3):164-7. doi: 10.1080/08858190009528686.

Blair CK, Madan-Swain A, Locher JL, Desmond RA, de Los Santos J, Affuso O, Glover T, Smith K, Carley J, Lipsitz M, Sharma A, Krontiras H, Cantor A, Demark-Wahnefried W. Harvest for health gardening intervention feasibility study in cancer survivors. Acta Oncol. 2013 Aug;52(6):1110-8. doi: 10.3109/0284186X.2013.770165. Epub 2013 Feb 26.

Bandura A. Social foundations of thought and action. Englewood Cliffs, NJ: Princeton Hall International; 1986.

Bandura A. Human agency in social cognitive theory. Am Psychol. 1989 Sep;44(9):1175-84. doi: 10.1037/0003-066x.44.9.1175.

Bandura A. Health promotion by social cognitive means. Health Educ Behav. 2004 Apr;31(2):143-64. doi: 10.1177/1090198104263660.

Sterling SR, Bertrand B, Judd S, Baskin ML. Nut Intake among Overweight and Obese African-American Women in the Rural South. Am J Health Behav. 2016 Sep;40(5):585-93. doi: 10.5993/AJHB.40.5.5.

Tran KM, Johnson RK, Soultanakis RP, Matthews DE. In-person vs telephone-administered multiple-pass 24-hour recalls in women: validation with doubly labeled water. J Am Diet Assoc. 2000 Jul;100(7):777-83. doi: 10.1016/S0002-8223(00)00227-3.

Demark-Wahnefried W, Clipp EC, McBride C, Lobach DF, Lipkus I, Peterson B, Clutter Snyder D, Sloane R, Arbanas J, Kraus WE. Design of FRESH START: a randomized trial of exercise and diet among cancer survivors. Med Sci Sports Exerc. 2003 Mar;35(3):415-24. doi: 10.1249/01.MSS.0000053704.28156.0F.

Bieri JG, Brown ED, Smith JC. Determination of individual carotenoids in human plasma by high performance liquid chromatography. J Liq Chromatogr 1985;8:473-84.

Gamboa-Pinto AJ, Rock CL, Ferruzzi MG, Schowinsky AB, Schwartz SJ. Cervical tissue and plasma concentrations of alpha-carotene and beta-carotene in women are correlated. J Nutr. 1998 Nov;128(11):1933-6. doi: 10.1093/jn/128.11.1933.

Stewart AL, Mills KM, King AC, Haskell WL, Gillis D, Ritter PL. CHAMPS physical activity questionnaire for older adults: outcomes for interventions. Med Sci Sports Exerc. 2001 Jul;33(7):1126-41. doi: 10.1097/00005768-200107000-00010.

Stewart AL, Verboncoeur CJ, McLellan BY, Gillis DE, Rush S, Mills KM, King AC, Ritter P, Brown BW Jr, Bortz WM 2nd. Physical activity outcomes of CHAMPS II: a physical activity promotion program for older adults. J Gerontol A Biol Sci Med Sci. 2001 Aug;56(8):M465-70. doi: 10.1093/gerona/56.8.m465.

Cyarto EV, Marshall AL, Dickinson RK, Brown WJ. Measurement properties of the CHAMPS physical activity questionnaire in a sample of older Australians. J Sci Med Sport. 2006 Aug;9(4):319-26. doi: 10.1016/j.jsams.2006.03.001. Epub 2006 Apr 19.

Demark-Wahnefried W, Clipp EC, Morey MC, Pieper CF, Sloane R, Snyder DC, Cohen HJ. Lifestyle intervention development study to improve physical function in older adults with cancer: outcomes from Project LEAD. J Clin Oncol. 2006 Jul 20;24(21):3465-73. doi: 10.1200/JCO.2006.05.7224.

Demark-Wahnefried W, Morey MC, Sloane R, Snyder DC, Miller PE, Hartman TJ, Cohen HJ. Reach out to enhance wellness home-based diet-exercise intervention promotes reproducible and sustainable long-term improvements in health behaviors, body weight, and physical functioning in older, overweight/obese cancer survivors. J Clin Oncol. 2012 Jul 1;30(19):2354-61. doi: 10.1200/JCO.2011.40.0895. Epub 2012 May 21.

Snyder DC, Morey MC, Sloane R, Stull V, Cohen HJ, Peterson B, Pieper C, Hartman TJ, Miller PE, Mitchell DC, Demark-Wahnefried W. Reach out to ENhancE Wellness in Older Cancer Survivors (RENEW): design, methods and recruitment challenges of a home-based exercise and diet intervention to improve physical function among long-term survivors of breast, prostate, and colorectal cancer. Psychooncology. 2009 Apr;18(4):429-39. doi: 10.1002/pon.1491.

Welk GJ, Almeida J, Morss G. Laboratory calibration and validation of the Biotrainer and Actitrac activity monitors. Med Sci Sports Exerc. 2003 Jun;35(6):1057-64. doi: 10.1249/01.MSS.0000069525.56078.22.

Welk GJ, Schaben JA, Morrow JR Jr. Reliability of accelerometry-based activity monitors: a generalizability study. Med Sci Sports Exerc. 2004 Sep;36(9):1637-45.

Freedson PS, Melanson E, Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc. 1998 May;30(5):777-81. doi: 10.1097/00005768-199805000-00021.

Lyden K, Kozey SL, Staudenmeyer JW, Freedson PS. A comprehensive evaluation of commonly used accelerometer energy expenditure and MET prediction equations. Eur J Appl Physiol. 2011 Feb;111(2):187-201. doi: 10.1007/s00421-010-1639-8. Epub 2010 Sep 15.

Sloane R, Snyder DC, Demark-Wahnefried W, Lobach D, Kraus WE. Comparing the 7-day physical activity recall with a triaxial accelerometer for measuring time in exercise. Med Sci Sports Exerc. 2009 Jun;41(6):1334-40. doi: 10.1249/MSS.0b013e3181984fa8.

Ware JE, Kosinski M. SF-36® Physical & Mental Health Summary Scales: A manual for users of Version 2 (2nd ed). Lincoln, RI: QualityMetric Inc.; 2007.

Rikli RE, Jones CJ. Development and validation of a functional fitness test for community-residing older adults. J Aging Phys Act 1999;7:129-61.

Rikli RE, Jones CJ. Functional fitness normative scores for community-residing older adults, ages 60-94. J Aging Phys Act 1999;7:162-81.

Rantanen T, Guralnik JM, Foley D, Masaki K, Leveille S, Curb JD, White L. Midlife hand grip strength as a predictor of old age disability. JAMA. 1999 Feb 10;281(6):558-60. doi: 10.1001/jama.281.6.558.

Taekema DG, Gussekloo J, Maier AB, Westendorp RG, de Craen AJ. Handgrip strength as a predictor of functional, psychological and social health. A prospective population-based study among the oldest old. Age Ageing. 2010 May;39(3):331-7. doi: 10.1093/ageing/afq022. Epub 2010 Mar 10.

Bohannon RW. Comfortable and maximum walking speed of adults aged 20-79 years: reference values and determinants. Age Ageing. 1997 Jan;26(1):15-9. doi: 10.1093/ageing/26.1.15.

Studenski S, Perera S, Patel K, Rosano C, Faulkner K, Inzitari M, Brach J, Chandler J, Cawthon P, Connor EB, Nevitt M, Visser M, Kritchevsky S, Badinelli S, Harris T, Newman AB, Cauley J, Ferrucci L, Guralnik J. Gait speed and survival in older adults. JAMA. 2011 Jan 5;305(1):50-8. doi: 10.1001/jama.2010.1923.

Walters SJ, Munro JF, Brazier JE. Using the SF-36 with older adults: a cross-sectional community-based survey. Age Ageing. 2001 Jul;30(4):337-43. doi: 10.1093/ageing/30.4.337.

Brazier JE, Roberts J. The estimation of a preference-based measure of health from the SF-12. Med Care. 2004 Sep;42(9):851-9. doi: 10.1097/01.mlr.0000135827.18610.0d.

Kharroubi SA, Brazier JE, Roberts J, O'Hagan A. Modelling SF-6D health state preference data using a nonparametric Bayesian method. J Health Econ. 2007 May 1;26(3):597-612. doi: 10.1016/j.jhealeco.2006.09.002. Epub 2006 Oct 27.

McCabe C, Brazier J, Gilks P, Tsuchiya A, Roberts J, O'Hagan A, Stevens K. Using rank data to estimate health state utility models. J Health Econ. 2006 May;25(3):418-31. doi: 10.1016/j.jhealeco.2005.07.008. Epub 2006 Feb 24.

Waliczek TM, Sommerfeld AJ, Zajicek JM. Growing Minds: Evaluating the Effect of Gardening on Quality of Life and Physical Activity Level of Older Adults. Horttechnology 2010;20:705-10.

Brown VM, Allen AC, Dwozan M, Mercer I, Warren K. Indoor gardening older adults: effects on socialization, activities of daily living, and loneliness. J Gerontol Nurs. 2004 Oct;30(10):34-42. doi: 10.3928/0098-9134-20041001-10.

Cutrona CE, Russell D. The provisions of social relationships and adaptation stress. In: Jones WH, Perlman D, eds. Advances in personal relationships. Greenwich, CT: JAI Press; 1987:37-67.

Sallis JF, Pinski RB, Grossman RM, Patterson TL, Nader PR. The development of self-efficacy scales for health related diet and exercise behaviors. Health Educ Res 1988;3:283-92.

Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977 Mar;84(2):191-215. doi: 10.1037//0033-295x.84.2.191. No abstract available.

Bandura A. Social foundations of thought and action : a social cognitive theory. Englewood Cliffs, N.J.: Prentice-Hall; 1986.

Christy SM, Mosher CE, Sloane R, Snyder DC, Lobach DF, Demark-Wahnefried W. Long-term dietary outcomes of the FRESH START intervention for breast and prostate cancer survivors. J Am Diet Assoc. 2011 Dec;111(12):1844-51. doi: 10.1016/j.jada.2011.09.013.

Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ; National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003 May 21;289(19):2560-72. doi: 10.1001/jama.289.19.2560. Epub 2003 May 14. Erratum In: JAMA. 2003 Jul 9;290(2):197.

Fisher G, Hyatt TC, Hunter GR, Oster RA, Desmond RA, Gower BA. Effect of diet with and without exercise training on markers of inflammation and fat distribution in overweight women. Obesity (Silver Spring). 2011 Jun;19(6):1131-6. doi: 10.1038/oby.2010.310. Epub 2010 Dec 23.

Fisher G, Hyatt TC, Hunter GR, Oster RA, Desmond RA, Gower BA. Markers of inflammation and fat distribution following weight loss in African-American and white women. Obesity (Silver Spring). 2012 Apr;20(4):715-20. doi: 10.1038/oby.2011.85. Epub 2011 Apr 28.

Institute of Medicine (US) Committee for the Study of the Future of Public Health. The Future of Public Health. Washington (DC): National Academies Press (US); 1988. Available from http://www.ncbi.nlm.nih.gov/books/NBK218218/

Brownson RC, Seiler R, Eyler AA. Measuring the impact of public health policy. Prev Chronic Dis. 2010 Jul;7(4):A77. Epub 2010 Jun 15.

Walter L, Dumke K, Oliva A, Caesar E, Phillips Z, Lehman N, Aragon L, Simon P, Kuo T. From Tobacco to Obesity Prevention Policies: A Framework for Implementing Community-Driven Policy Change. Health Promot Pract. 2018 Nov;19(6):856-862. doi: 10.1177/1524839918760843. Epub 2018 Apr 5.

Weber MD, Simon P, Messex M, Aragon L, Kuo T, Fielding JE. A framework for mobilizing communities to advance local tobacco control policy: the Los Angeles County experience. Am J Public Health. 2012 May;102(5):785-8. doi: 10.2105/AJPH.2011.300586. Epub 2012 Mar 15.