Skip to main content

Advertisement

Log in

Mobile Health Technology Can Objectively Capture Physical Activity (PA) Targets Among African-American Women Within Resource-Limited Communities—the Washington, D.C. Cardiovascular Health and Needs Assessment

  • Published:
Journal of Racial and Ethnic Health Disparities Aims and scope Submit manuscript

Abstract

Background

Little is understood about using mobile health (mHealth) technology to improve cardiovascular (CV) health among African-American women in resource-limited communities.

Methods

We conducted the Washington, D.C. CV Health and Needs Assessment in predominantly African-American churches in city wards 5, 7, and 8 with the lowest socioeconomic status based on community-based participatory research (CBPR) principles. The assessment measured CV health factors: body mass index (BMI), fasting blood glucose and cholesterol, blood pressure, fruit/vegetable (F/V) intake, physical activity (PA), and smoking. Participants were trained to use a PA monitoring wristband to measure 30 days of PA, wirelessly upload the PA data to hubs at the participating churches, and access their data from a church/home computer. CV health factors were compared across weight classes.

Results

Among females (N = 78; 99 % African-American; mean age = 59 years), 90 % had a BMI categorized as overweight/obese. Across weight classes, PA decreased and self-reported sedentary time (ST) increased (p ≤ 0.05). Diastolic blood pressure and glucose increased across weight classes (p ≤ 0.05); however, cholesterol, glucose, and BP were near intermediate CV health goals.

Conclusions

Decreased PA and increased ST are potential community intervention targets for overweight and obese African-American women in resource-limited Washington D.C. areas. mHealth technology can assist in adapting CBPR intervention resources to improve PA for African-American women in resource-limited communities.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, Cushman M, et al. Heart disease and stroke statistics—2015 update: a report from the American Heart Association. Circulation. 2015;131:e29–322.

    Article  PubMed  Google Scholar 

  2. Holland AT, Zhao B, Wong EC, Choi SE, Wong ND, Palaniappan LP. Racial/ethnic differences in control of cardiovascular risk factors among type 2 diabetes patients in an insured, ambulatory care population. J Diabetes Complications. 2013;27:34–40.

    Article  PubMed  Google Scholar 

  3. Powell-Wiley TM, Ayers C, Agyemang P, Leonard T, Berrigan D, Ballard-Barbash R, et al. Neighborhood-level socioeconomic deprivation predicts weight gain in a multi-ethnic population: longitudinal data from the Dallas Heart Study. Prev Med. 2014;66:22–7.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Boggs DA, Ban Y, Palmer JR, Rosenberg L. Higher diet quality is inversely associated with mortality in African-American women. J Nutr. 2015;145:547–54.

    Article  CAS  PubMed  Google Scholar 

  5. Carson JA, Michalsky L, Latson B, Banks K, Tong L, Gimpel N, et al. The cardiovascular health of urban African Americans: diet-related results from the Genes, Nutrition, Exercise, Wellness, and Spiritual Growth (GoodNEWS) trial. J Acad Nutr Diet. 2012;112:1852–8.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Lloyd-Jones DM, Hong Y, Labarthe D, Mozaffarian D, Appel LJ, Van Horn L, et al. Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association’s strategic Impact Goal through 2020 and beyond. Circulation. 2010;121:586–613.

    Article  PubMed  Google Scholar 

  7. DeHaven MJ, Ramos-Roman MA, Gimpel N, Carson J, DeLemos J, Pickens S, et al. The GoodNEWS (Genes, Nutrition, Exercise, Wellness, and Spiritual Growth) Trial: a community-based participatory research (CBPR) trial with African-American church congregations for reducing cardiovascular disease risk factors—recruitment, measurement, and randomization. Contemp Clin Trials. 2011;32:630–40.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Pearson TA, Palaniappan LP, Artinian NT, Carnethon MR, Criqui MH, Daniels SR, et al. American Heart Association Guide for Improving Cardiovascular Health at the Community Level, 2013 update: a scientific statement for public health practitioners, healthcare providers, and health policy makers. Circulation. 2013;127:1730–53.

    Article  PubMed  Google Scholar 

  9. Marcus BH, Bock BC, Pinto BM, Forsyth LH, Roberts MB, Traficante RM. Efficacy of an individualized, motivationally-tailored physical activity intervention. Ann Behav Med. 1998;20:174–80.

    Article  CAS  PubMed  Google Scholar 

  10. Baruth M, Sharpe PA, Parra-Medina D, Wilcox S. Perceived barriers to exercise and healthy eating among women from disadvantaged neighborhoods: results from a focus groups assessment. Women Health. 2014;54:336–53.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Unertl KM, Schaefbauer CL, Campbell TR, Senteio C, Siek KA, Bakken S, et al. Integrating community-based participatory research and informatics approaches to improve the engagement and health of underserved populations. J Am Med Inform Assoc. 2015.

  12. US Centers for Disease Control and Prevention (CDC). 2014. Washington DCBrfsssq.

  13. Yingling LR, Brooks AT, Wallen GR, Peters-Lawrence M, McClurkin M, Cooper-McCann R, et al. Community engagement to optimize the use of web-based and wearable technology in a cardiovascular health and needs assessment study: a mixed methods approach. JMIR mHealth uHealth. 2016;4:e38.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Chobanian AV BG, Black HR, Cushman WC, Green LA, Izzo JL, Jones DW, et al. Seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure. Hypertension. 2003.

  15. National Heart L, and Blood Institute Expert Panel. [Accessed April 3, 2011];Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults. Available at: http://www.nhlbi.nih.gov/guidelines/obesity

  16. Frieden TR. Forward: CDC health disparities and inequalities report—United States, 2011. MMWR Suppl. 2011;60:1–2.

    Google Scholar 

  17. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in body mass index among US children and adolescents, 1999–2010. JAMA. 2012;307:483–90.

    Article  PubMed  Google Scholar 

  18. Mielke Jr PW, Berry KJ. The Terpstra-Jonckheere Test for ordered alternative values; randomized probability values. Percept Mol Skills.2009; 91:447–50.

  19. Ammerman A, Corbie-Smith G, St George DM, Washington C, Weathers B, Jackson-Christian B. Research expectations among African American church leaders in the PRAISE! project: a randomized trial guided by community-based participatory research. Am J Public Health. 2003;93:1720–7.

  20. Sloane DC, Diamant AL, Lewis LB, Yancey AK, Flynn G, Nascimento LM, et al. Improving the nutritional resource environment for healthy living through community-based participatory research. J Gen Intern Med. 2003;18:568–75.

  21. Abebe NA, Capozza KL, Des Jardins TR, Kulick DA, Rein AL, Schachter AA, et al. Considerations for community-based mhealth initiatives: insights from three beacon communities. Journal of Medical Internet Research. 2013;15:e221.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Wilmot KA, O’Flaherty M, Capewell S, Ford ES, Vaccarino V. Coronary heart disease mortality declines in the United States from 1979 through 2011: evidence for stagnation in young adults, especially women. Circulation. 2015;132:997–1002.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Blackwell DL, Lucas JW, Clarke TC. Summary health statistics for U.S. adults: national health interview survey, 2012. Vital Health Stat 10. 2014;1–161.

  24. Nabel EG. Heart disease prevention in young women: sounding an alarm. Circulation. 2015;132:989–91.

    Article  PubMed  Google Scholar 

  25. Thorndike AN, Mills S, Sonnenberg L, Palakshappa D, Gao T, Pau CT, et al. Activity monitor intervention to promote physical activity of physicians-in-training: randomized controlled trial. PLoS One. 2014;9:e100251.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Case MA, Burwick HA, Volpp KG, Patel MS. Accuracy of smartphone applications and wearable devices for tracking physical activity data. JAMA. 2015;313:625–6.

    Article  CAS  PubMed  Google Scholar 

  27. Whitt-Glover MC, Keith NR, Ceaser TG, Virgil K, Ledford L, Hasson RE. A systematic review of physical activity interventions among African American adults: evidence from 2009 to 2013. Obesity reviews. 2014;15 Suppl 4:125–45.

    Article  PubMed  Google Scholar 

  28. Coughlin SS, Smith SA. A review of community-based participatory research studies to promote physical activity among African Americans. Journal of the Georgia Public Health Association. 2016;5:220.

    PubMed  PubMed Central  Google Scholar 

  29. Parker VG, Coles C, Logan BN, Davis L. The LIFE project: a community-based weight loss intervention program for rural African American women. Family & community health. 2010;33:133.

    Article  Google Scholar 

  30. Ries A, Blackman L, Page R, Gizlice Z, Benedict S, Barnes K, et al. Goal setting for health behavior change: evidence from an obesity intervention for rural low-income women. Rural and remote health. 2014;14.

  31. Wilcox S, Parrott A, Baruth M, Laken M, Condrasky M, Saunders R, et al. The faith, activity, and nutrition program: a randomized controlled trial in African-American churches. American journal of preventive medicine. 2013;44:122–31.

    Article  PubMed  Google Scholar 

  32. Zoellner J, Connell CL, Santell R, Fungwe T, Strickland E, Avis-Williams A, et al. Fit for life steps: results of a community walking intervention in the rural Mississippi Delta. Progress in Community Health Partnerships: Research, Education, and Action. 2007;1:49–60.

    Article  Google Scholar 

  33. Burke LE, Ma J, Azar KM, Bennett GG, Peterson ED, Zheng Y, et al. Current science on consumer use of mobile health for cardiovascular disease prevention: a scientific statement from the American Heart Association. Circulation. 2015;132:1157–213.

    Article  PubMed  Google Scholar 

  34. Eysenbach G. The law of attrition. J Med Internet Res. 2005;7:e11.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Lapan S, Quartaroli M. Research essentials: An introduction to design and practices. 2009.

    Google Scholar 

  36. Kumanyika SKW-GM, Haire-Joshu D. What works for obesity prevention and treatment in black Americans? Research directions. Obes Rev. 2014;15 Suppl 4:204–12.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

We would like to acknowledge the participating church communities for warmly welcoming our research team and providing feedback from preliminary stages. Additionally, we acknowledge the D.C. CHOC for their contribution, as without their insightful recommendation, this project would not have come to fruition. Funding for TP-W, LY, and VM is provided through the Division of Intramural Research of the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH). Funding for CA is provided through a professional services contract (contract #HHSN268201300173P) through the Division of Intramural Research of NHLBI at NIH. Funding for ST and JA-B is provided through the Office of Intramural Training and Education of the National Institutes of Health (NIH). Funding for GW and AT-B is provided through the Clinical Center, NIH. Funding for MP-L is provided through Division of Intramural Research - Hematology Branch, National Heart Lung and Blood Institute, NIH. Funding for DS is provided through the Office of Behavioral and Social Sciences Research (OBSSR) of the Office of the Director of the National Institutes of Health (NIH). We would also like to acknowledge the work on this project by Mr. Praduman Jain and colleagues from Vignet Corporation through use of their Precision Medicine Initiative (PMI) toolkit under contract #HHSN268201400023P. The PMI toolkit enables custom mHealth programs for data collection, population, surveillance, interactive informed consent, assessments, remote monitoring, CBPR, consumer engagement, interventions, motivations, and behavior change. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to T. M. Powell-Wiley.

Ethics declarations

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Conflict of Interest

All authors declare that they have no conflict of interest.

Funding

This study was funded by the National Heart, Lung, and Blood Institute (grant number ZIA HL006168).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Thomas, S., Yingling, L., Adu-Brimpong, J. et al. Mobile Health Technology Can Objectively Capture Physical Activity (PA) Targets Among African-American Women Within Resource-Limited Communities—the Washington, D.C. Cardiovascular Health and Needs Assessment. J. Racial and Ethnic Health Disparities 4, 876–883 (2017). https://doi.org/10.1007/s40615-016-0290-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40615-016-0290-4

Keywords

Navigation