Perceived Susceptibility to Chronic Kidney Disease among High-risk Patients Seen in Primary Care Practices

  • L. Ebony BoulwareEmail author
  • Kathryn A. Carson
  • Misty U. Troll
  • Neil R. Powe
  • Lisa A. Cooper
Original Article



Patients’ views of their risk for the development or progression of chronic kidney disease (CKD) are poorly characterized.


To assess perceived risk and concern regarding CKD development or progression among high-risk patients seen in primary care, identify predictors of perceptions, and correlate perceptions with adherence to high blood pressure management.


Cross-sectional study of 195 patients enrolled in a randomized controlled trial on hypertension management in 40 Maryland primary care practices.


We assessed independent predictors (sociodemographics, health literacy, clinical presence of CKD, co-morbid conditions, and health behaviors) of perceived susceptibility (assessed via questionnaire) and adherence (assessed via Hill-Bone blood pressure adherence scale) in multivariable analyses.


In this hypertensive majority African American (63%) population, many participants had uncontrolled blood pressure (44%) or diabetes (42%). Few (20%) felt “very likely” to develop CKD and one third (33%) were “very concerned” about developing CKD. Participants who were female and had low health literacy had lower perceived susceptibility to CKD compared to males and those with higher health literacy. Race and diabetes were also associated with perceived susceptibility. Greater perceived susceptibility was associated with poorer blood pressure management adherence scores.


Many high-risk patients have low perceived susceptibility to CKD. Poor blood pressure therapy adherence scores among those with greatest perceived susceptibility suggest fatalistic attitudes about CKD. If our findings are confirmed in larger studies, interventions targeting patient perceptions of CKD risk and other attitudes associated with these perceptions could impact adherence to therapies and health outcomes.


chronic kidney disease attitudes perceived susceptibility adherence primary care 



Grant #1K23DK070757 from the National Institute of Diabetes and Digestive and Kidney Diseases and Contract #200609197 from Amgen (Dr. Boulware); Grant #K240502643 from National Institute of Diabetes and Digestive and Kidney Diseases (Dr. Powe) and Foundation for Informed Medical Decision Making (Dr. Powe); Grants# R01HL69403 and K24HL083113 from the National Heart Lung and Blood Institute and Contract #200609197 from Amgen (Dr. Cooper)


Dr. Boulware participated in the conceptualization, funding, performance, and analysis of the study; Mrs. Carson participated in the performance and analysis of the study; Ms. Troll participated in the analysis of the study; Dr. Powe participated in the conceptualization, funding, and analysis of the study; Dr. Cooper participated in the conceptualization, funding, performance, and analysis of the study.

Conflict of Interest

None disclosed.


  1. 1.
    Coresh J, Selvin E, Stevens LA, et al. Prevalence of chronic kidney disease in the United States. JAMA. 2007;298(17):2038–47.CrossRefPubMedGoogle Scholar
  2. 2.
    Shlipak MG, Sarnak MJ, Katz R, et al. Cystatin C and the risk of death and cardiovascular events among elderly persons. N Engl J Med. 2005;352(20):2049–60.CrossRefPubMedGoogle Scholar
  3. 3.
    Sarnak MJ, Katz R, Stehman-Breen CO, et al. Cystatin C concentration as a risk factor for heart failure in older adults. Ann Intern Med. 2005;142(7):497–505.PubMedGoogle Scholar
  4. 4.
    Haroun MK, Jaar BG, Hoffman SC, Comstock GW, Klag MJ, Coresh J. Risk factors for chronic kidney disease: a prospective study of 23,534 men and women in Washington County, Maryland. J Am Soc Nephrol. 2003;14(11):2934–41.CrossRefPubMedGoogle Scholar
  5. 5.
    Jee SH, Boulware LE, Guallar E, Suh I, Appel LJ, Miller ER 3rd. Direct, progressive association of cardiovascular risk factors with incident proteinuria: results from the Korea Medical Insurance Corporation (KMIC) study. Arch Intern Med. 2005;165(19):2299–304.CrossRefPubMedGoogle Scholar
  6. 6.
    Hostetter TH, Lising M. National kidney disease education program. J Am Soc Nephrol. 2003;14(7 Suppl 2):S114–116.CrossRefPubMedGoogle Scholar
  7. 7.
    NKDEP Urges Primary Care for People with CKD. NIH Publication No. 08-4531 [ Accessed August, 2009]
  8. 8.
    Peralta CA, Hicks LS, Chertow GM, et al. Control of hypertension in adults with chronic kidney disease in the United States. Hypertension. 2005;45(6):1119–24.CrossRefPubMedGoogle Scholar
  9. 9.
    Pathman DE, Konrad TR, Freed GL, Freeman VA, Koch GG. The awareness-to-adherence model of the steps to clinical guideline compliance. The case of pediatric vaccine recommendations. Med Care. 1996;34(9):873–89.CrossRefPubMedGoogle Scholar
  10. 10.
    Kirkman MS, Williams SR, Caffrey HH, Marrero DG. Impact of a program to improve adherence to diabetes guidelines by primary care physicians. Diabetes Care. 2002;25(11):1946–51.CrossRefPubMedGoogle Scholar
  11. 11.
    Cooper LA, Roter DL, Bone LR, et al. A randomized controlled trial of interventions to enhance patient-physician partnership, patient adherence and high blood pressure control among ethnic minorities and poor persons: study protocol NCT00123045. Implement Sci. 2009;4:7.CrossRefPubMedGoogle Scholar
  12. 12.
    Davis TC, Crouch MA, Long SW, et al. Rapid assessment of literacy levels of adult primary care patients. Fam Med. 1991;23(6):433–5.PubMedGoogle Scholar
  13. 13.
    Kim MT, Hill MN, Bone LR, Levine DM. Development and testing of the Hill-Bone Compliance to High Blood Pressure Therapy Scale. Prog Cardiovasc Nurs. 2000;15(3):90–6.CrossRefPubMedGoogle Scholar
  14. 14.
    Chobanian AV, Bakris GL, Black HR, et al. The seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003;289(19):2560–72.CrossRefPubMedGoogle Scholar
  15. 15.
    Expert Panel on the Identification E, Treatment of Overweight in A. Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: executive summary. Am J Clin Nutr. 1998;68(4):899–917.Google Scholar
  16. 16.
    Zhang J, Yu KF. What’s the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA. 1998;280(19):1690–1.CrossRefPubMedGoogle Scholar
  17. 17.
    Huber PJ. The Behavior of Maximum Likelihood Estimates under Nonstandard Conditions. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability. Berkeley, CA: University of California Press;1967:221–3.Google Scholar
  18. 18.
    White H. A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica. 48:817–30.Google Scholar
  19. 19.
    Williams RL. A note on robust variance estimation for cluster-correlated data. Biometrics. 2000;56:645–6.CrossRefPubMedGoogle Scholar
  20. 20.
    Rogers WH. Regressions standard errors in clustered samples. Stata Tech Bull. 1993;13:19–23.Google Scholar
  21. 21.
    Coresh J, Byrd-Holt D, Astor BC, et al. Chronic kidney disease awareness, prevalence, and trends among U.S. adults, 1999 to 2000. J Am Soc Nephrol. 2005;16(1):180–8.CrossRefPubMedGoogle Scholar
  22. 22.
    Waterman AD, Browne T, Waterman BM, Gladstone EH, Hostetter T. Attitudes and behaviors of African Americans regarding early detection of kidney disease. Am J Kidney Dis. 2008;51(4):554–62.CrossRefPubMedGoogle Scholar
  23. 23.
    National Kidney F. Annual data report: Kidney Early Evaluation Program. American Jounal of Kidney Diseases. 2003;42(5):Supplement 4.Google Scholar
  24. 24.
    Lea JP, McClellan WM, Melcher C, Gladstone E, Hostetter T. CKD risk factors reported by primary care physicians: do guidelines make a difference? Am J Kidney Dis. 2006;47(1):72–7.CrossRefPubMedGoogle Scholar
  25. 25.
    Boulware LE, Troll MU, Jaar BG, Myers DI, Powe NR. Identification and referral of patients with progressive CKD: a national study. Am J Kidney Dis. 2006;48(2):192–204.CrossRefPubMedGoogle Scholar
  26. 26.
    Davis RE, Dolan G, Thomas S, et al. Exploring doctor and patient views about risk communication and shared decision-making in the consultation. Health Expect. 2003;6(3):198–207.CrossRefPubMedGoogle Scholar
  27. 27.
    Royak-Schaler R, Lemkau JP, Ahmed SM. Discussing breast cancer risk in primary care. J Am Med Womens Assoc. 2002;57(2):115–6.PubMedGoogle Scholar
  28. 28.
    Buchanan AH, Skinner CS, Rawl SM, et al. Patients’ interest in discussing cancer risk and risk management with primary care physicians. Patient Educ Couns. 2005;57(1):77–87.CrossRefPubMedGoogle Scholar
  29. 29.
    National Kidney Disease Education P. Health professionals. Accessed July 17, 2009.
  30. 30.
    Boulware LE. Challenges for public campaigns to improve the health of persons at high risk of developing CKD. Am J Kidney Dis. 2008;51(4):535–8.CrossRefPubMedGoogle Scholar
  31. 31.
    Niederdeppe J, Levy AG. Fatalistic beliefs about cancer prevention and three prevention behaviors. Cancer Epidemiol Biomarkers Prev. 2007;16(5):998–1003.CrossRefPubMedGoogle Scholar
  32. 32.
    Farmer D, Reddick B, D'Agostino R, Jackson SA. Psychosocial correlates of mammography screening in older African American women. Oncol Nurs Forum. 2007;34(1):117–23.CrossRefPubMedGoogle Scholar
  33. 33.
    Russell KM, Perkins SM, Zollinger TW, Champion VL. Sociocultural context of mammography screening use. Oncol Nurs Forum. 2006;33(1):105–12.CrossRefPubMedGoogle Scholar
  34. 34.
    Greiner KA, James AS, Born W, et al. Predictors of fecal occult blood test (FOBT) completion among low-income adults. Prev Med. 2005;41(2):676–84.CrossRefPubMedGoogle Scholar
  35. 35.
    Burkhart PV, Rayens MK. Self-concept and health locus of control: factors related to children’s adherence to recommended asthma regimen. Pediatr Nurs. 2005;31(5):404–9.PubMedGoogle Scholar
  36. 36.
    Cvengros JA, Christensen AJ, Lawton WJ. The role of perceived control and preference for control in adherence to a chronic medical regimen. Ann Behav Med. 2004;27(3):155–61.CrossRefPubMedGoogle Scholar
  37. 37.
    O’Hea EL, Grothe KB, Bodenlos JS, Boudreaux ED, White MA, Brantley PJ. Predicting medical regimen adherence: the interactions of health locus of control beliefs. J Health Psychol. 2005;10(5):705–17.CrossRefPubMedGoogle Scholar
  38. 38.
    Dunbar-Jacob JM, Schlenk EA, Burke LE, Matthews JT. Predictors of patient adherence: patient characteristics. In: Schumamer SA, Schron EB, Ockene JK, McBee WL, eds. The Handbook of Health Behavior Change. 2nd ed. New York: Springer Publishing Company; 1998: 491–511.Google Scholar
  39. 39.
    Glanz K, Lewis FM, Rimer BK. Part Two: Models of Indivudial Health Behavior. Health Behavior and Health Education. Theory, Research and Practice. San Francisco: Jossey-Bass, Inc.; 1997.Google Scholar
  40. 40.
    DiMatteo MR, Haskard KB, Williams SL. Health beliefs, disease severity, and patient adherence: a meta-analysis. Med Care. 2007;45(6):521–8.CrossRefPubMedGoogle Scholar
  41. 41.
    Wilson PW, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97(18):1837–47.PubMedGoogle Scholar
  42. 42.
    Wolf PA, D’Agostino RB, Belanger AJ, Kannel WB. Probability of stroke: a risk profile from the Framingham Study. Stroke. 1991;22(3):312–8.PubMedGoogle Scholar
  43. 43.
    Officers A, Coordinators for the ACRG. Major outcomes in moderately hypercholesterolemic, hypertensive patients randomized to pravastatin vs usual care: the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT-LLT). JAMA. 2002;288(23):2998–3007.CrossRefGoogle Scholar
  44. 44.
    Rahman M, Pressel S, Davis BR, et al. Renal outcomes in high-risk hypertensive patients treated with an angiotensin-converting enzyme inhibitor or a calcium channel blocker vs a diuretic: a report from the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). Arch Intern Med. 2005;165(8):936–46.CrossRefPubMedGoogle Scholar

Copyright information

© Society of General Internal Medicine 2009

Authors and Affiliations

  • L. Ebony Boulware
    • 1
    • 2
    • 4
    Email author
  • Kathryn A. Carson
    • 2
  • Misty U. Troll
    • 1
    • 4
  • Neil R. Powe
    • 1
    • 2
    • 3
    • 4
  • Lisa A. Cooper
    • 1
    • 2
    • 3
    • 4
  1. 1.Division of General Internal Medicine, Department of MedicineJohns Hopkins School of MedicineBaltimoreUSA
  2. 2.Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  3. 3.Department of Health Policy and ManagementJohns Hopkins Bloomberg School of Public HealthBaltimoreUSA
  4. 4.Welch Center for Prevention, Epidemiology and Clinical ResearchJohns Hopkins Medical InstitutionsBaltimoreUSA

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