Influence of Diabetes-Related Support on Aerobic Activity Among Older African Americans With Type 2 Diabetes

Abstract

The objective of this study was to examine the influence of diabetes-related support in promoting aerobic activity in a sample of older African Americans. A secondary data analysis was conducted based on a diabetes self-management study of community-dwelling older African Americans. Logistic regression was conducted to examine the influence of diabetes-related support on aerobic activity. The final model demonstrated that there was a strong relationship between having diabetes-related support and aerobic activity, odds ratio =6.56, 95% confidence interval [2.14, 20.11]. The final model also demonstrated a significant influence based on the total number of chronic health conditions on aerobic activity, odds ratio = 0.63, 95% confidence interval [0.498, 0.802]. Findings suggest that older African Americans with Type 2 diabetes and other chronic health conditions may engage in physical activity if they have diabetes-related support from their family and friends.

Keywords

African Americans physical activity diabetes support older adults

Introduction

Physical activity in advanced age has been shown to be beneficial, especially in the prevention of chronic diseases, such as metabolic coronary heart disease (Villareal et al., 2006) and Type 2 diabetes (Demakakos, Hamer, Stamatakis, & Steptoe, 2010). Physical activity among older adults has also been shown to promote psychological well-being (Lampinen, Heikkinen, Kauppinen, & Heikkinen, 2006) and improve quality of life (Awick et al., 2015). The federal government recommends adults achieve a minimum of 150 min of physical activity a week in the form of moderate-intensity aerobic activity or moderate- and vigorous-intensity aerobic activity (U. S. Department of Health and Human Services [HHS], 2008); however, most older adults do not meet the recommended levels for physical activity. According to the Federal Interagency Forum on Aging-Related Statistics (FIFA-RS, 2016), only 12% of older adults met the federal guidelines for physical activity. Although physical activity decreases with age, non-Hispanic Blacks are less likely than non-Hispanic Whites to meet the physical activity recommendations, 9% compared with 13% (FIFA-RS, 2016).

Research on older African Americans and physical activity suggests that support from family and friends may facilitate physical activity (Belza et al., 2004; Matthews et al., 2010). For example, Belza et al. (2004) identified support from family and friends as a consistent theme among physically active older African Americans. In their study, a participant reported that an adult child provided a pedometer as a way of demonstrating support, and another participant reported a friend helped to motivate her to walk. Similarly, Harvey and Alexander (2012) found that older adults who received social support from friends were more likely to engage in physical activity. However, there is some evidence that when exploring facilitators and barriers to physical activity among older adults, family and friends may yield both positive and negative influences. For example, Gallant, Spitze, and Prohaska (2007) examined the influence of family and support networks on chronic illness management among a diverse sample of older adults. They found that family and friends yielded both positive and negative influences on physical activity. Equally important, the researchers found that physical activity was less likely to be discussed or promoted compared with other chronic illness management strategies, such as medication management and dietary activities.

In addition to support from family and friends, older African Americans report that support from their pastors and church family facilitate physical activity (Bopp et al., 2007; Sebastião, Ibe-Lamberts, Bobitt, Schwingel, & Chodzko-Zajko, 2014). For example, Bopp et al. (2007) found that older African American men and women reported that having physical activity programs located within their church would help to facilitate physical activity engagement.

From a population health perspective, Type 2 diabetes is not just an individual chronic condition; it is a costly chronic condition that affects individuals, families, and communities. Type 2 diabetes is a chronic condition that can be influenced by numerous factors within and outside of an individual’s environment, such as social support (Bowen et al., 2015; Fitzpatrick & Hills-Briggs, 2017), spirituality and religiosity (Leach & Schoenberg, 2008), geographic location (Christine et al., 2015), and health policy (Webster, 2010).

It is important to consider various multilevel factors in the management of Type 2 diabetes; by doing so, the focus of care management shifts attention from the individual. Therefore, we approached this study through the conceptual framework of the social determinants of health (SDOH). The World Health Organization (2018) describes the SDOH as “the environmental conditions in which individuals are born, live, learn, work, play, worship, and age that can affect a wide range of health, functioning, and quality-of-life outcomes and risks” (para. 1). The SDOH conceptual framework has been used to conceptualize the numerous ways by which social determinants contribute to population health disparities. We specifically focused on the influence of diabetes-related support. Thus, the objective of this study was to examine the influence of diabetes-related support in promoting aerobic activity in a sample of community-dwelling older African Americans with a self-reported diagnosis of Type 2 diabetes.

Methods

Study Design and Participants

Upon approval of the institutional review board at the University of Alabama at Birmingham (Protocol # E160623005), a secondary data analysis was conducted using data from a study about diabetes self-management in a sample of community-dwelling African Americans 65 years of age and older with a self-reported diagnosis of Type 2 diabetes. Briefly, in the original study, participants were recruited across five counties in central Alabama from community-based organizations, such as Black churches and Black-owned businesses. Participants were screened for eligibility over the telephone, which included screening for cognitive impairment. Eligible participants were interviewed in their homes or a private location of their choosing.

The current analyses focused on the relationship between self-report of diabetes-related support and aerobic activity. In the original study (McCaskill, Bolland, Burgio, & Leeper, 2015), participants were asked to answer 25 dichotomous questions about support related to the management of Type 2 diabetes. The questions were developed based on the American Diabetes Association’s (2012, 2015) standards of care in the management of Type 2 diabetes in older adults.

Outcome Variable

Aerobic activity was the outcome variable. Participants were asked to answer the following dichotomous question: “I walk or do other aerobic exercise for 30 minutes at least five times a week.” Aerobic activity was coded as either 0 for no aerobic activity and 1 for yes aerobic activity. The question was selected through a thorough process that included assessments for face validity and content validity, as well as two rounds of cognitive interviews and pilot testing (McCaskill, Bolland, Burgio, & Leeper, 2015).

Independent Variable

Diabetes-related support was the independent variable. Participants were asked to answer the following dichotomous question: “I get help with my sugar diabetes from my family and friends.” Diabetes-related support was coded as either 0 for no diabetes-related support and 1 for yes diabetes-related support. The same process for the aerobic activity question was conducted to ensure face validity and content validity for the diabetes-related support question (McCaskill, Bolland, Burgio, & Leeper, 2015).

Covariates

Marital status was recoded from four categories (never married, married, separated or divorced, and widowed) to two categories (married and not married). The income variable was recoded from 10 categories to 2 categories ($15,000 or less or more than $15,000), which was based on poverty guidelines at the time of the original study (HHS, 2012). The number of years since diagnosis of Type 2 diabetes and the number of chronic health conditions were also entered as covariates. Chronic health conditions were measured using the physical health section of the Duke Older Americans Resources and Services multidimensional functional assessment questionnaire (Fillenbaum, 1981). This instrument was chosen due to demonstrated reliability and validity for use among older African Americans (Fillenbaum & Smyer, 1981).

Missing Data

Missing data were handled based on listwise deletion. Therefore, the one missing value for income resulted in one entire case being excluded from the logistic regression analysis.

Statistical Analysis

All data analyses were performed using SPSS (version 23) (IBM Corp., 2012). For descriptive purposes, chi-square tests of independence were performed to examine relationships between aerobic activity and gender, income, education, and marital status. Independent samples t tests were conducted to compare aerobic activity based on age and mean number of chronic health conditions. Logistic regression analysis was conducted to examine the influence of diabetes-related support on aerobic activity. Education was dropped from the analyses because of correlation with income. Diabetes-related support was entered as the independent variable in Block 1. Age, gender, income, and marital status were entered as covariates in Block 2. The number of years diagnosed with Type 2 diabetes and total number of chronic health conditions were entered into the model as covariates in Block 3. Aerobic activity was entered as the outcome variable.

Results

There were 125 African Americans in the sample. Participants were 65 to 94 years old (M =72.8, SD = 5.71). The majority of participants were female (81%). The number of years living with a Type 2 diabetes diagnosis ranged from less than 30 days to 56 years (M = 13.6, SD = 11.1). For additional characteristics of the sample, see Table 1. In addition to self-reported Type 2 diabetes, participants reported a range of 1 to 11 chronic health conditions (M = 4.90, SD = 2.10). The majority of participants reported diagnoses of hypertension (91.2%) and arthritis (74.4%).

Table 1.

Demographic Characteristics of Participants (N= 125).

Variable	N (%)
Gender
Female	101 (80.8)
Male	24 (19.2)
Education
High school graduate or less	69 (55.2)
Some college or college graduate	56 (44.8)
Marital status
Not married	96 (76.8)
Married	29 (23.2)
Annual household income
Less than $15,000	71 (56.8)
More than $15,000	54 (43.2)

Fifty-eight participants (46.4%) reported aerobic activity at least five times per week. Participants reporting aerobic activity less than five times a week reported more chronic health conditions (M = 6.60, SD = 2.10), compared with participants reporting regular aerobic activity (M = 5.10, SD = 1.74, t = 4.30, df = 121.60, p = .000). There was no significant difference in age by aerobic activity group. Table 2 provides the percentage of participants who reported diabetes-related support and aerobic activity, as well as the relationships of aerobic activity to various demographics (all of which were not statistically significant, p > .05).

Table 2.

Self-Report of Aerobic Activity on Demographics and Diabetes-Related Support.

	Aerobic activity (%)	χ²	p *
Gender		3.09	.063
Female	42.6
Male	62.5
Education		.126	.723
High school or less	32.0
More than high school	26.0
Income		.495	.587
$15,000 and less than	43.7
More than $15,000	50.0
Marital status		.430	.531
Not married	44.8
Married	51.7
Diabetes-related support		8.09	.005**
Yes	53.1
No	77.8

Note. Used the first category as the reference category except for gender.

*Fisher’s exact test.

**p value significant at .05 level (two tailed).

Logistic regression analyses were conducted to determine the influence of diabetes-related support on self-report of aerobic activity. A test of the full model against a constant only model was statistically significant, indicating that diabetes-related support, while controlling for age, gender, income, and marital status, reliably distinguished between individuals reporting aerobic activity five times a week and individuals reporting aerobic activity less than five times a week (χ² = 10.84, p < .001, df = 1).

The model explained 32% (Nagelkerke’s R² of .322) of the variance in self-reported aerobic activity and correctly classified 70.2% of cases (Table 3). The Wald criterion demonstrated that diabetes-related support was uniquely associated with aerobic activity (odds ratio [OR] = 6.56), p < .001 with 95% confidence interval [2.14, .20.11]. The ORs for diabetes-related support indicated that when holding other variables constant, participants who self-reported having diabetes-related support had approximately seven times greater odds of reporting regular aerobic activity than participants who reported no diabetes-related support.

Table 3.

Final Logistic Regression Model Predicting Aerobic Activity.

Variables	B	Wald χ²	Odds ratio	p	95% CI
Diabetes-related support	1.882	10.485	6.563	<.001*	[2.142, 20.112]
Age	.017	.205	1.017	.650	[.945, 1.095]
Gender	.598	1.209	1.818	.272	[.626, 5.279]
Income	.160	.111	1.174	.739	[.331, 2.190]
Marital status	.058	.010	1.059	.919	[.347, 3.233]
Years Type 2 diabetes	–.032	2.227	.969	.136	[.929, 1.010]
Total chronic health conditions	–.459	14.206	.632	<.001*	[.498, .802]

Note. CI = confidence interval.

*p significant at .05 level (two tailed).

The number of reported chronic health conditions was also uniquely associated with aerobic activity (OR = 0.63, p < .001 with 95% confidence interval [.498, .802]). The OR for the number of reported chronic health conditions indicated that when holding diabetes-related support constant, as the number of chronic health conditions increased, the odds of self-report of aerobic activity decreased. For an increase of one chronic health condition, participants were only 63% as likely to report aerobic activity.

Discussion

The analyses examined the influence of diabetes-related support on self-report of aerobic activity in a sample of community-dwelling older African Americans with Type 2 diabetes. We approached this study through the conceptual framework of the SDOH (World Health Organization, 2018), drawing attention to the role of diabetes-related support. We acknowledge that diabetes-related support is not the only contributing factor for promoting self-report of aerobic activity among older African Americans. However, we do contend that the conceptual framework of SDOH allows us to consider the environment in which older African Americans live and interact to receive diabetes-related support.

Although the literature is replete with research on social support in the management of chronic health conditions, there is an absence in the literature of a standard definition for diabetes-related support, which we define as instrumental, emotional, spiritual, social, or financial support related to the management of Type 2 diabetes. Given the extensive familial and fictive kin networks often associated with African Americans (Spruill, Coleman, Powell-Young, Williams, & Magwood, 2014), it is important to recognize that diabetes-related support can come from family members, friends, as well as clergy. For examples, an older African American with Type 2 diabetes may receive encouragement from a family member or friend to walk together on a regular basis to manage blood sugar and promote cardiovascular health; a son may purchase blood sugar test strips for his mother, or a pastor may offer support through regular prayer. When encouraging older African Americans with Type 2 diabetes to engage in regular physical activity, physicians and other health-care providers should consider the potential influence of supportive relationships on diabetes self-care (Brundisini, Vanstone, Hulan, DeJean, & Giacomini, 2015). Future research should include an examination of the individual characteristics of support-providers and their effect on all aspect of diabetes self-care.

Our findings suggest that participants who reported having diabetes-related support were more likely to self-report aerobic activity, compared with participants who reported not having diabetes-related support. This finding is important because of our efforts to define and measure diabetes-related support among older African Americans with a self-reported diagnosis of diabetes. It is plausible that diabetes-related support from family and friends offers older African Americans with Type 2 diabetes a degree of accountability. Diabetes-related support may also indicate to older African Americans that family and friends care about their health and well-being. This finding is also important because it adds to our understanding about the potential influence of diabetes-related support on the overall management of Type 2 diabetes among older African Americans (Chesla et al., 2004; Vaccaro, Exebio, Zarini, & Huffman, 2014).

A sizeable percentage of participants reported being physically active, and all participants reported multiple chronic health conditions that could negatively influence their ability to maintain physical activity. However, research indicates that older African Americans are willing to engage in physical activity if their chronic health conditions are well managed (Frosch, Rincom, Ochoa, & Mangione, 2010; Tang, Brown, Funnell, & Anderson, 2008) and if they receive support from family and friends (Belza et al., 2004; Frosch et al., 2010; Harvey & Alexander, 2012; Matthews et al., 2010). Although previous research suggests that medically underserved adults may be willing to exercise regardless of chronic health conditions (Frosch et al., 2010; Schrop et al., 2006; Tang et al., 2008), our findings indicate that the number of chronic health conditions negatively influenced the self-report of aerobic activity. Even though our results suggest contradictory findings, for participants in our study, the types of chronic conditions and the severity of the chronic conditions may yield considerable influence on physical activity in addition to diabetes-related support.

We also found that participants reported higher levels of aerobic activity (46.2%), compared with other older residents of Alabama (35.1%; Centers for Disease Control and Prevention [CDC], 2013). This finding is interesting because physical activity levels are low among older African Americans in Alabama (CDC, 2013) and throughout the United States (FIFA-RS, 2016). The high level of aerobic activity reported among participants may be the result of a mostly urban sample. In general, older adults who live in urban neighborhoods with mostly African Americans report more physical activity than rural older adults with majority European Americans (Armstrong-Brown, Eng, Powell Hammond, Zimmer, & Bowling, 2015). In addition, urban residents are more likely than rural residents to have access to exercise facilities (Parks, Housemann, & Brownson, 2003; Wilcox, Castro, King, Housemann, & Brownson, 2000). Another factor that possibly influenced the high level of self-reported aerobic activity participation may have to do with the high number of participants that were recruited from senior centers with physical activity programs.

We found that age was not a significant predictor of self-report of aerobic activity. This finding was surprising because older adults are among the least physically active population compared with other groups of adults, especially those 75 years and older (Schoenborn, Adams, & Pergoy, 2013). According to national statistics, when a person reaches age 75 years, physical activity decreases to 24.3%, compared with 55% among adults 18 to 24 years of age (Schoenborn et al., 2013). Unfortunately, being physically inactive in advanced age can negatively affect diabetes management (Demakakos et al., 2010), psychological well-being (Lampinen et al., 2006), and quality of life (Awick et al., 2015; Brown et al., 2004; Lampinen et al., 2006). However, walking is a safe and low-cost alternative to physical inactivity. Community-based approaches that have included walking, such as the CDC’s Racial and Ethnic Approaches to Community Health, have demonstrated success among African American adults of all ages (Miles, Kruger, Liaso, Carlson, & Fulton, 2011).

Limitations

There were some limitations associated with our findings. The cross-sectional nature of our data allows us to examine relationships between variables, but not infer causation. Also, generalizability is limited because participants were recruited across five counties in central Alabama from community-based organizations, such as Black churches and Black-owned businesses, which limits generalizability to broader populations. There is potentially a difference between diabetes-related support and general social support. We are unable to determine without additional study if indeed both constructs differ. In addition, we were unable to assess the providers of the diabetes-related support. It is possible that support-providers and their relationship with support-recipients may influence various aspects of diabetes-related support, including physical activity.

Our analyses were based on participants’ self-report data from a secondary analysis. Perhaps objective measures of aerobic activity and verification of Type 2 diabetes and other chronic health conditions may have strengthened our findings. However, previous researchers have reported on the validity and reliability of self-report of physical activity measures compared with objective measures of physical activity (Harada, Chiu, King, & Stewart, 2001), as well as self-report of chronic conditions compared with medical chart review, with promising results (Kriegsman, Penninx, Van Eijk, Boeke, & Deeg, 1996).

Conclusions

To the best of our knowledge, our study was the first of this kind to examine the potential influence of diabetes-related support on community-dwelling older African Americans with Type 2 diabetes. To further our understanding in this area, research is needed to determine if diabetes-related support differs significantly from social support. This could be accomplished through qualitative methods, such as cognitive interviews and focus groups that explore diabetes-related support from the perspective of older African Americans with Type 2 diabetes, and quantitative methods. Based on the qualitative results, a quantitative diabetes-related support measure could be developed and compared with a social support measure for divergent validity.

In addition to developing a measure to assess diabetes-related support, it is equally important to remember that physical activity is important to the successful management of Type 2 diabetes (American Diabetes Association, 2018). While there may be challenges to prescribing physical activity to older African Americans with Type 2 diabetes, physicians and other health-care providers should be willing to prescribe exercise, regardless of age and health status (Elsawy & Higgins, 2010; HHS, 2008).

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported through a fellowship in advanced geriatrics, Birmingham/Atlanta Geriatric Research, Education, & Clinical Center (GRECC). The content is solely the responsibility of the authors and does not necessarily represent the official views of the U.S. Department of Veterans Affairs.

Author Biographies

Gina M. McCaskill is a post-doctoral scholar with the Birmingham VA Medical Center, Birmingham/Atlanta Geriatric Research, Education, and Clinical Center (GRECC), Birmingham VA Medical Center. She studies health disparities, quality of life, and physical activity in older veterans with chronic conditions.

Pamela G. Bowen is an assistant professor, junior nurse researcher, and a seasoned certified family nurse practitioner interested in building a program of research focused on increasing physical activity in African American older adults who are predominantly low-income with obesity-related chronic illnesses, such as hypertension, diabetes, arthritis, and heart disease.

Loretta T. Lee is an assistant professor at the University of Alabama at Birmingham (UAB) and a family nurse practitioner. Her primary goal is to advance scientific knowledge regarding diabetes self-management for older adults, with a particular emphasis on ensuring that culturally and ethnically appropriate intervention strategies are used to eliminate racial health disparities.

Kathryn L. Burgio is a behavioral psychologist, professor of medicine in the Division of Gerontology, Geriatrics and Palliative Care, and Founding Director of the UAB Continence Program. She is also Associate Director for Research at the Birmingham/Atlanta Geriatric Research, Education, and Clinical Center at the Birmingham VA Medical Center.

James Leeper is a professor in the department of community medicine and population health and the Director of Education. He teaches courses in biostatistics, serves on dissertation committees, and is a Rural Medicine clerkship director for the Rural Medical Scholars Program in addition to other activities.

Olivio J. Clay is an associate professor at the UAB, department of psychology. His research focuses on addressing issues related to successful aging. He is particularly interested in several aspects of aging, including racial/ethnic disparities in health, family caregiving, social support, health care access and utilization, cognition, and mobility.

References

American Diabetes Association. (2012). Standards of medical care in diabetes—2012. Diabetes Care, 35(Suppl. 1), S11–S63. doi:10.2337/dc12-5011

American Diabetes Association. (2015). Standards of medical care in diabetes—2015: Summary of revisions. Diabetes Care, 38(Supp. 1), S1–S90. Retrieved from http://professional.diabetes.org/admin/UserFiles/0%20-%20Sean/Documents/January%20Supplement%20Combined_Final.pdf

American Diabetes Association. (2018). Standards of medical care in diabetes—2018. Diabetes Care, 41(Supp. 1), S1–S52. Retrieved from http://care.diabetesjournals.org/content/diacare/suppl/2017/12/08/41.Supplement_1.DC1/DC_41_S1_Combined.pdf

Armstrong-Brown

Eng

Powell Hammond

Zimmer

Bowling

J. M.

(2015). Redefining racial residential segregation and its association with physical activity among African Americans 50 years and older: A mixed methods approach. Journal of Aging and Physical Activity, 23(2), 237–246. doi:1123/japa.2013-0069

Awick

E. A.

Wójcicki

T. R.

Olson

E. A.

Fanning

Chung

H. D.

Zuniga

, . . . McAuley

(2015). Differential exercise effects on quality of life and health-related quality of life in older adults: A randomized controlled trial. Quality of Life Research, 24(2), 455–462. doi:10.1007/s11136-014-0762-0

Belza

Walwick

Shiu-Thornton

Schwartz

Taylor

LoGerfo

(2004). Older adult perspectives on physical activity and exercise: Voices from multiple cultures. Preventing Chronic Disease, 1(4), 1–12. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1277949/pdf/PCD14A09.pdf

Bopp

Lattimore

Wilcox

Laken

McClorin

Swinton

, . . . Bryant

(2007). Understanding physical activity participation in members of an African American church: A qualitative study. Health Education Research, 22(6), 815–826. doi:10.1093/her/cyl149

Bowen

P. G.

Clay

O. J.

Lee

L. T.

Vice

Ovalle

Crowe

(2015). Associations of social support and self-efficacy with quality of life in a sample of older adults with diabetes. Journal of Gerontological Nursing, 41, 21–29. doi:10.3928/00989134-20151008-44

Brown

D. W.

Brown

D. R.

Heath

G. W.

Balluz

Giles

W. H.

Ford

E. S.

Mokdad

A. H.

(2004). Associations between physical activity dose and health-related quality of life. Medicine & Science in Sports & Exercise, 36, 890–896. doi:10.1249/01.MSS.0000126778.77049.76

10.

Brundisini

Vanstone

Hulan

DeJean

Giacomini

(2015). Type 2 diabetes patients’ and providers’ differing perspectives on medication nonadherence: A qualitative meta-synthesis. BMC Health Services Research, 15, 516. doi:10.1186/s12913-015-1174-8

11.

Centers for Disease Control and Prevention. (2013). The state of aging and health in America 2013. Atlanta, GA: Author and U. S. Department of Health and Human Services. Retrieved from http://www.cdc.gov/features/agingandhealth/state_of_aging_and_health_in_america_2013.pdf

12.

Chesla

C. A.

Fisher

Mullan

J. T.

Skaff

M. M.

Gardiner

Chun

(2004). Family and disease management in African-American patients with type 2 diabetes. Diabetes Care, 27, 2850–2855.

13.

Christine

P. J.

Auchincloss

A. H.

Bertoni

A. G.

Carnethon

M. R.

Sánchez

B. N.

Moore

, . . . Diez Roux

A. V.

(2015). Longitudinal associations between neighborhood physical and social environments and incident type 2 diabetes mellitus: The Multi-Ethnic Study of Atherosclerosis (MESA). JAMA Internal Medicine, 175(8), 1311–1320. doi:10.1001/jamainternmed.2015.2691

14.

Demakakos

Hamer

Stamatakis

Steptoe

(2010). Low-intensity physical activity is associated with reduced risk of incident type 2 diabetes in older adults: Evidence from the English Longitudinal Study of Ageing. Diabetologia, 53, 1877–1885. doi:10.1007/s00125-010-1785-x

15.

Elsawy

Higgins

K. E.

(2010). Physical activity guidelines for older adults. American Academy of Family Physicians, 81(1), 55–59. Retrieved from http://www.aafp.org/afp/2010/0101/p55.pdf

16.

Federal Interagency Forum on Aging-Related Statistics. (2016). Older Americans 2012: Key indicators of well-being. Washington, DC: Government Printing Office. Retrieved from https://agingstats.gov/docs/LatestReport/Older-Americans-2016-Key-Indicators-of-WellBeing.pdf

17.

Fillenbaum

G. G.

(1981). Multidimensional functional assessment of older adults: The duke older Americans resources and services procedures. Hillsdale, NJ: Lawrence Erlbaum Associates.

18.

Fillenbaum

G. G.

Smyer

M. A.

(1981). The development, validity, and reliability of the OARS Multidimensional Functional Assessment Questionnaire. Journal of Gerontology, 36(4), 428–434. doi:10.1093/geronj/36.4.428

19.

Fitzpatrick

S. L.

Hill-Brigs

(2017). Strategies for sustained weight management. Perspectives from African American patients with type 2 diabetes. Diabetes Educator, 43(3), 304–310. doi:10.1177/014521717699071

20.

Frosch

D. L.

Rincon

Ochoa

Mangione

C. M.

(2010). Activating seniors to improve chronic disease care: Results from a pilot intervention study. Journal of the American Geriatric Society, 58(10), 1496–1503. doi:10.1111/j.1532-5415.2010.02980.x

21.

Gallant

M. P.

Spitze

G. D.

Prohaska

T. R.

(2007). Help or hindrance? How family and friends influence chronic illness self-management among older adults. Research on Aging, 29, 375–409. doi:10.1177/0164027507303169

22.

Harada

N. D.

Chiu

King

A. C.

Stewart

A. L.

(2001). An evaluation of three self-report physical activity instruments for older adults. Medicine & Science in Sports & Exercise, 33, 962–970. Retrieved from http://ovidsp.tx.ovid.com/

23.

Harvey

Alexander

(2012). Perceived social support and preventive health behavioral outcomes among older women. Journal of Cross-Cultural Gerontology, 27(3), 275–290. doi:10.1007/s10823-012-9172-3

24.

IBM

Corp.

(2012). IBM SPSS Statistics for Windows (Version 21.0) [Computer software] . New York, NY: IBM.

25.

Kriegsman

D. M. W.

Penninx

B. W. J. H.

Van Eijk

J. T. M.

Boeke

A. J. P.

Deeg

D. J. H.

(1996). Self-reports and general practitioner information on the presence of chronic diseases in community-dwelling elderly. A study of agreement and determinants of disagreement. Journal of Clinical Epidemiology, 12, 1407–1417. doi:10.1016/S0895-4356(96000274-0

26.

Lampinen

Heikkinen

R. L.

Kauppinen

Heikkinen

(2006). Activity as a predictor of mental well-being among older adults. Aging & Mental Health, 10(5), 454–466. doi:10.1080/13607860600640962

27.

Leach

C. R.

Schoenberg

N. E.

(2008). Striving for control: Cognitive, self-care, and faith strategies employed by vulnerable Black And White older adults with multiple chronic conditions. Journal of Cross-Cultural Gerontology, 23, 377–399. doi:10.1007/s10823008-9086-2

28.

Matthews

A. E.

Laditka

S. B.

Laditka

J. N.

Wilcox

Corwin

S. J.

Liu

, . . . Logsdon

R. G.

(2010). Older adults’ perceived physical activity enablers and barriers: A multicultural perspective. Journal of Aging and Physical Activity, 18, 119–140. doi:10.1123/japa.18.2.119

29.

McCaskill, G. M., Bolland, K. A., Burgio, & K. L., Leeper, J. (2015). Development and validation of a diabetes self-management instrument for older African-Americans. Social Work in Health Care, 55(5), 381–394. doi:10.1080/00981389.2015.1129012.

30.

Miles

I. W.

Kruger

Liaso

Carlson

S. A.

Fulton

J. E.

(2011). Walking increases among African American adults following a community-based physical activity intervention: Racial and ethnic approaches to community health, 2002-2005. Journal of Health Disparities Research and Practice, 5(1), 43–54. Retrieved from http://digitalscholarship.unlv.edu/cgi/viewcontent.cgi?article=1014&context=jhdrp

31.

Parks

S. E.

Housemann

R. A.

Brownson

R. C.

(2003). Differential correlates of physical activity in urban and rural adults of various socioeconomic backgrounds in the United States. Journal of Epidemiology & Community Health, 57, 29–35. doi:10.1136/jech.57.1.29

32.

Schoenborn

C. A.

Adams

P. F.

Peregoy

J. A.

(2013). Health behaviors of adults: United States, 2008-2010. Vital and Health Statistics Series 10(257), 1–184. Retrieved from http://www.cdc.gov/nchs/data/series/sr_10/sr10_257.pdf

33.

Schrop

S. L.

Pendleton

B. F.

McCord

Gil

K. M.

Stockton

McNatt

Gilchrist

V. J.

(2006). The medically underserved: Who is likely to exercise and why? Journal of Health Care for the Poor and Underserved, 17(2), 276–289. doi:10.1353/hpu.2006.0069

34.

Sebastião

Ibe-Lamberts

Bobitt

Schwingel

Chodzko-Zajko

(2014). Employing a participatory research approach to explore physical activity among older African American women. Journal of Aging Research, 2014, 1–8. doi:10.1155/2014/941019

35.

Spruill

I. J.

Coleman

B. L.

Powell-Young

Y. M.

Williams

T. H.

Magwood

(2014). Non-biological (Fictive kin and othermothers): Embracing the need for a culturally appropriate pedigree nomenclature in African-American families. Journal of the National Black Nurses Association, 25(2), 23–30.

36.

Tang

T. S.

Brown

M. B.

Funnell

M. M.

Anderson

R. M.

(2008). Social support, quality of life, and self-care behaviors among African Americans with type 2 diabetes. Diabetes Educator, 34(2), 266–276. doi:10.1177/0145721708315680

37.

U. S. Department of Health and Human Services. (2008). 2008 Physical activity guidelines for Americans: Be active, healthy, and happy (ODPHP Publication No. U0036). Retrieved from http://www.health.gov/paguidelines/pdf/paguide.pdf

38.

U. S. Department of Health and Human Services. (2012). Federal poverty guidelines. Washington, DC. Retrieved from http://aspe.hhs.gov/poverty/12poverty.shtml#guidelines

39.

Vaccaro

J. A.

Exebio

J. C.

Zarini

G. G.

Huffman

F. G.

(2014). The role of family/friend social support in diabetes self-management for minorities with type 2 diabetes. Journal of Nutrition and Health, 2(1), 1–9. doi: 10.12691/jnh-2-1-1

40.

Villareal

D. T.

Miller

B. V., III.

Banks

Fontana

Sinacore

D. R.

Klein

(2006). Effect of lifestyle intervention on metabolic coronary heart disease risk factors in obese older adults. American Journal of Clinical Nutrition, 84(1), 1317–1323. Retrieved from http://ajcn.nutrition.org/content/84/6/1317.full.pdf+html

41.

Webster

N. J.

(2010). Medicare and racial disparities in health: Fee-for-Service versus managed care. The impact of demographics on health and health care: Race, ethnicity and other social factors. Research in the Sociology of Health Care, 28, 47–70. doi:10.1108/S0275-4959(2010)0000028005

42.

Wilcox

Castro

King

A. C.

Housemann

Brownson

R. C.

(2000). Determinants of leisure time physical activity in rural compared with urban older and ethnically diverse women in the United States. Journal of Epidemiology & Community Health, 54, 667–672. Retrieved from https://www-jstor-org.web.bisu.edu.cn/stable/23369268

43.

World Health Organization. (2018). Social determinants of health. Retrieved from http://www.who.int/social_determinants/en/