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Intentional and unintentional non-adherence in hypertension: psychometric validation, adherence–complexity phenotyping and causal mediation analysis from the VATAHTA Study

Hypertension Research (2025)Cite this article

Abstract

Non-adherence to antihypertensive therapy remains a major barrier to blood pressure (BP) control globally. The behavioural distinction between intentional (INA) and unintentional non-adherence (UNA) is underexplored in low- and middle-income countries. We aimed to validate the Spanish MMAS-8, identify adherence–complexity phenotypes, and assess the mediating role of adherence between regimen complexity and BP control. In this multicenter, cross-sectional study (2022–2024), 1144 hypertensive patients from Argentina were evaluated. Adherence was assessed using the Spanish MMAS-8. Psychometric validation included Cronbach’s alpha and principal component analysis. INA and UNA were classified by domain-based response patterns. K-means clustering was applied to MMAS-8 items and regimen complexity (number of drugs, daily doses). Mediation analysis tested the indirect effect of adherence. The MMAS-8 showed acceptable reliability (α = 0.78) and a unidimensional structure. Full adherence was observed in 41.1%. Among non-adherent patients, 38.5% were INA, 33.6% UNA, and 27.9% mixed. Four phenotypes were identified: (1) high adherence/low complexity; (2) very low adherence/simple regimens; (3) moderate adherence/intermediate complexity; (4) low adherence/high complexity. Adherence significantly mediated the effect of complexity on BP control (β = 0.004; p < 0.001), while the direct effect was non-significant. Compared with phenotype 1, phenotype 2 showed 58% lower odds of control (OR 0.42; 95% CI 0.29–0.61) and phenotype 4 showed 32% lower odds (OR 0.68; 95% CI 0.49–0.94). The Spanish MMAS-8 is valid for this population. Adherence–complexity phenotypes reflect structural and behavioural barriers. Tailored interventions should address INA and UNA using adherence profiling, fixed-dose combinations, and social support.

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References

  1. Mills KT, Stefanescu A, He J. The global epidemiology of hypertension. Nat Rev Nephrol. 2020;16:223–37.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Risk NCD. Factor Collaboration (NCD‑RisC). Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis. Lancet. 2021;398:957–80.

    Google Scholar 

  3. Gagliardi J, Miranda N, Calandrelli M, Nasca R, Giorgi M, Gutierrez L, et al. Prevalence, awareness, treatment and control of hypertension in Argentina: results of the RENATA‑2 study. J Hum Hypertens. 2018;32:773–80.

    Google Scholar 

  4. Delucchi AM, Majul CR, Vicario A, Cerezo GH, Fábregues G, Marín MJ, et al. National Registry of Hypertension (RENATA‑1): epidemiological characteristics of hypertension in Argentina. Rev Argent Cardiol. 2017;85:340–6.

    Google Scholar 

  5. Ordúñez P, Campbell N, Giraldo G, Angell S, Lombardi C, Brettler J, et al. Effective approaches to hypertension control in Latin America and the Caribbean, 2014-20: a review. Rev Panam Salud Publica. 2022;46:e75.

    Google Scholar 

  6. Wald DS, Law M, Morris JK, Bestwick JP, Wald NJ. Combination therapy versus monotherapy in reducing blood pressure: meta-analysis of 42 trials. Am J Med. 2009;122:290–300.

    Article  PubMed  Google Scholar 

  7. Salam A, Kanukula R, Atkins E, Wang X, Islam S, Kishore SP, et al. Efficacy and safety of dual or multiple fixed‑dose combination therapies for hypertension. JAMA. 2019;322:2211–9.

    Google Scholar 

  8. Thom S, Poulter N, Field J, Patel A, Burnier M, Prabhakaran D, et al. Effects of a fixed‑dose combination strategy on adherence and blood pressure: the UMPIRE study. Lancet. 2013;381:1413–22.

    Google Scholar 

  9. Peixoto AJ, Krieger EM, Marín MJ, Alfie J, Gutierrez L, Fábregues G, et al. Joint consensus on fixed‑dose combinations in hypertension. Rev Fed Arg Cardiol. 2021;50:155–9.

    Google Scholar 

  10. Rojas C, Toledo A, Martín‑Sánchez G, Espeche W, Salazar MR, Aizpurúa M, et al. Evaluación de acceso a medicamentos antihipertensivos en Argentina. Salud Colectiva. 2022;18:e3895.

    Google Scholar 

  11. Morisky DE, Ang A, Krousel-Wood M, Ward HJ. Predictive validity of a medication adherence measure in an outpatient setting. J Clin Hypertens. 2008;10:348–54.

    Article  Google Scholar 

  12. Krousel-Wood M, Islam T, Webber LS, Re RN, Morisky DE, Muntner P. New medication adherence scale versus pharmacy fill rates in seniors with hypertension. Am J Manag Care. 2009;15:59–66.

    PubMed  PubMed Central  Google Scholar 

  13. Romero C, Marín MJ, Alfie J, Gutierrez L, Acevedo M, Fábregues G, et al. Validación de escalas de adherencia en pacientes hipertensos: revisión sistemática. Hipertens Riesgo Vasc. 2022;39:20–28.

    Google Scholar 

  14. Renna N, Salazar MR, Martín-Sánchez G, Toledo A, Gagliardi J, Bendersky M, et al. Adherencia, combinaciones fijas y factores socioeconómicos en hipertensión: hallazgos del estudio VATAHTA. Rev Fed Arg Cardiol. 2024;51:18–25.

    Google Scholar 

  15. Vrijens B, De Geest S, Hughes DA, Przemyslaw K, Demonceau J, Ruppar T, et al. A new taxonomy for describing and defining adherence to medications. Br J Clin Pharm. 2012;73:691–705.

    Article  Google Scholar 

  16. Gellad WF, Grenard JL, Marcum ZA. A systematic review of barriers to medication adherence in the elderly: looking beyond cost and regimen complexity. Am J Geriatr Pharmacother. 2011;9:11–23.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Jin J, Sklar GE, Min Sen Oh V, Chuen Li S. Factors affecting therapeutic compliance: a review from the patient's perspective. Ther Clin Risk Manag. 2008;4:269–86.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Cooper C, Booth A, Gill P, Lacey T. A taxonomy of adherence interventions: a systematic review and synthesis of meta-analyses. Patient Educ Couns. 2021;104:2990–3002.

    Google Scholar 

  19. World Health Organization. Adherence to long-term therapies: evidence for action. Geneva: WHO; 2003.

  20. Castellano JM, Sanz G, Peñalvo JL, Bansilal S, Fernández-Ortiz A, Alvarez L, et al. A polypill strategy to improve adherence: results from the FOCUS trial. J Am Coll Cardiol. 2014;64:2071–82.

    Article  PubMed  Google Scholar 

  21. Burnier M, Egan BM. Adherence in hypertension. Circ Res. 2019;124:1124–40.

    Article  PubMed  CAS  Google Scholar 

  22. Kronish IM, Ye S. Adherence to cardiovascular medications: lessons learned and future directions. Prog Cardiovasc Dis. 2013;55:590–600.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Chow CK, Redfern J, Hillis GS, Thakkar J, Santo K, Hackett ML, et al. Effect of lifestyle-focused text messaging on risk factor modification in patients with coronary heart disease: a randomized clinical trial. JAMA. 2015;314:1255–63.

    Article  PubMed  CAS  Google Scholar 

  24. Lee JK, Grace KA, Taylor AJ. Effect of a pharmacy care program on medication adherence and persistence, blood pressure, and low-density lipoprotein cholesterol: a randomized controlled trial. JAMA. 2006;296:2563–71.

    Article  PubMed  CAS  Google Scholar 

  25. Marcolino MS, Oliveira JAQ, Ribeiro ALP, Alkmim MBM, Aquino EC, Côrtes MF, et al. Telemedicine application in the care of diabetes patients: systematic review and meta-analysis. PLoS One. 2013;8:e79246.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Ihm SH, Kim KI, Kim CH, Cho EJ, Kim M, Yoo B, et al. Blood pressure control and medication adherence among patients with hypertension and cognitive impairment in Korea. Hypertens Res. 2019;42:1545–53.

    Google Scholar 

  27. Al-Ghurair SA, Hughes CA, Simpson SH, Guirguis LM. A systematic review of patient self-reported barriers of adherence to antihypertensive medications. Curr Hypertens Rep. 2012;14:431–41.

    Google Scholar 

  28. Nieuwlaat R, Wilczynski N, Navarro T, Hobson N, Jeffery R, Keepanasseril A, et al. Interventions for enhancing medication adherence. Cochrane Database Syst Rev. 2014;2014:CD000011.

  29. Menckeberg TT, Bouvy ML, Bracke M, Kaptein AA, Leufkens HG, Raaijmakers JA, et al. Beliefs about medicines predict refill adherence to inhaled corticosteroids. J Psychosom Res. 2008;64:47–54.

    Article  PubMed  Google Scholar 

  30. Poon EG, Keohane CA, Yoon CS, Ditmore M, Bane A, Levtzion-Korach O, et al. Effect of bar-code technology on the safety of medication administration. N Engl J Med. 2010;362:1698–707.

    Article  PubMed  CAS  Google Scholar 

  31. Burnier M. Medication adherence and persistence as the cornerstone of effective antihypertensive therapy. Am J Hypertens. 2006;19:1190–6.

    Article  PubMed  Google Scholar 

  32. Patel P, Ordunez P, DiPette D, Escobar MC, Hassell T, Wyss R, et al. Improved blood pressure control to reduce cardiovascular disease morbidity and mortality: the Standardized Hypertension Treatment and Prevention Project. J Clin Hypertens. 2016;18:1284–94.

    Article  Google Scholar 

  33. Cutler RL, Fernandez-Llimos F, Frommer M, Benrimoj C, Garcia-Cardenas V. Economic impact of medication non-adherence by disease groups: a systematic review. BMJ Open. 2018;8:e016982.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Rajpura J, Nayak R. Medication adherence in a sample of elderly suffering from hypertension: evaluating the influence of illness perceptions, treatment beliefs, and illness burden. J Manag Care Pharm. 2014;20:58–65.

    PubMed  Google Scholar 

  35. Omboni S, Caserini M. Telemedicine and M-health in hypertension management: technologies. Appl Clin Evid High Blood Press Cardiovasc Prev. 2019;26:359–66.

    Google Scholar 

  36. Logan AG, Irvine MJ, McIsaac WJ, Tisler A, Ross H, Easty A, et al. Effect of home blood pressure telemonitoring with self-care support on uncontrolled systolic hypertension in diabetics. Hypertension. 2012;60:51–57.

    Article  PubMed  CAS  Google Scholar 

  37. Kjeldsen SE, Lund-Johansen P, Nilsson PM, Mancia G. Unattended versus attended blood pressure measurement: implications for clinical practice. Curr Hypertens Rep. 2014;16:508.

    Google Scholar 

  38. Redon J, Olsen MH, Cooper RS, Zurriaga O, Martinez-Beneito MA, Laurent S, et al. Hypertension in patients with diabetes: global perspectives and current management. Cardiovasc Diabetol. 2006;5:26.

    Google Scholar 

  39. Ribeiro AG, Ribeiro SM, Dias CM, Franceschini SD, Priore SE, Peluzio MCG. Nonadherence to antihypertensive medication: validation of a new tool in a Brazilian population. Arq Bras Cardiol. 2014;103:389–98.

    Google Scholar 

  40. Wald DS, Morris JK, Wald NJ. Randomized polypill crossover trial in people aged 50 and over. PLoS One. 2012;7:e41297.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Horne R, Weinman J, Barber N, Elliott RA, Morgan M. Concordance, adherence and compliance in medicine taking. London: NCCSDO; 2005.

  42. Bailey SC, Oramasionwu CU, Wolf MS. Rethinking adherence: a health literacy–informed model of medication self-management. J Health Commun. 2013;18:20–30.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Osterberg L, Blaschke T. Adherence to medication. N Engl J Med. 2005;353:487–97.

    Article  PubMed  CAS  Google Scholar 

  44. Khatib R, Schwalm JD, Yusuf S, Haynes RB, McKee M, Khan M, et al. Patient and healthcare provider barriers to hypertension awareness, treatment and follow up: a systematic review and meta-analysis. J Hypertens. 2014;32:1921–34.

    Google Scholar 

  45. Egan BM, Zhao Y, Axon RN. US trends in prevalence, awareness, treatment, and control of hypertension, 1988–2008. JAMA. 2010;303:2043–50.

    Article  PubMed  CAS  Google Scholar 

  46. Kronish IM, Rieckmann N, Halm EA, Shimbo D. Chronic disease self-management and adherence to antihypertensive medication in older adults: a population-based survey. Med Care. 2009;47:521–6.

    Google Scholar 

  47. Morisky DE, DiMatteo MR. Improving the measurement of self-reported medication nonadherence: response to authors. J Clin Epidemiol. 2011;64:255–7.

    Article  PubMed  Google Scholar 

  48. Niiranen TJ, Johansson JK, Reunanen A, Jula AM. Optimal threshold for diagnosing hypertension with ambulatory blood pressure monitoring: predictive value for cardiovascular events. Hypertension. 2013;62:698–703.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Cardiology, Hospital Español de Mendoza, Mendoza, Argentina

    Nicolás F. Renna, Jesica M. Ramirez & Matias F. Arrupe

  2. Area of Physiopathology, Department of Pathology, UNCuyo–IMBECU–CONICET, Mendoza, Argentina

    Nicolás F. Renna

  3. Department of Internal Medicine, Hospital Central de Mendoza, Mendoza, Argentina

    Jesica M. Ramirez

  4. Adherence. Long Beach, Long Beach, CA, USA

    Philip Magueflor Morisky

  5. University of La Verne, College of Business, La Verne, CA, USA

    Philip Magueflor Morisky

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  1. Nicolás F. Renna
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Correspondence to Nicolás F. Renna.

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Conflict of interest

The Morisky Medication Adherence Scale (MMAS) is copyrighted by Adherence, which licenses its use for research and commercial purposes. PM oversees the implementation and licensing of the scale. Any fees collected support the advancement of adherence research and patient-centred interventions. This financial interest has been disclosed and managed in accordance with institutional guidelines. The authors affirm that these relationships have not influenced the design, conduct, or reporting of this study, and that the scientific integrity of the work remains uncompromised.

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Renna, N.F., Ramirez, J.M., Arrupe, M.F. et al. Intentional and unintentional non-adherence in hypertension: psychometric validation, adherence–complexity phenotyping and causal mediation analysis from the VATAHTA Study. Hypertens Res (2025). https://doi.org/10.1038/s41440-025-02427-1

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