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Association between polypharmacy and health-related quality of life among US adults with cardiometabolic risk factors

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Abstract

Purpose

There are known associations between cardiometabolic risk factors and polypharmacy; however, there is no evidence about how polypharmacy among adults with cardiometabolic risk factors impacts their health-related quality of life (HRQoL). The main objective of this study was to assess the association between polypharmacy and HRQoL among adults with cardiometabolic risk factors living in the USA.

Methods

Individuals age ≥ 18 years with at least one of the three cardiometabolic risk factors (diabetes, hyperlipidemia, and hypertension) were identified from the Medical Expenditure Panel Survey 2015 data. We defined polypharmacy as use of at least five classes of prescription medications. Physical component summary (PCS) and mental component summary (MCS) were obtained from the 12-item Short-Form Health Survey version 2 to measure HRQoL. We conducted adjusted ordinary least-square regressions to determine the association between polypharmacy and HRQoL.

Results

We identified 7621 (weighted N = 80 million) adults with at least one cardiometabolic risk factors of whom 46.9% reported polypharmacy. Polypharmacy was noted in 29.7% of those with hypertension, whereas 82.4% of those with all the three cardiometabolic risk factors had polypharmacy. The unadjusted mean PCS and MCS scores for those with polypharmacy were lower than those without polypharmacy. In the multivariable regressions, we found that adults with polypharmacy had significantly lower PCS scores (β = − 4.27, p < 0.0001) compared to those without polypharmacy, while the MCS scores between those with and without polypharmacy were no longer significantly different.

Conclusion

Surveillance of use of concurrent prescription medications is warranted so as to improve physical functioning in this vulnerable group.

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References

  1. Agency for Healthcare Research and Quality. (2019). Medical Expenditure Panel Survey. MEPS Topics: Priority Conditions-General. Updated April 2019. Retrieved August 3, 2019, from https://meps.ahrq.gov/data_stats/MEPS_topics.jsp?topicid=41Z-1.

  2. American Heart Association. (2005). Heart Disease and Stroke Statistics-2005 Update. Dallas, TX: American Heart Association.

    Google Scholar 

  3. Kahn, R., Buse, J., Ferrannini, E., & Stern, M. (2005). The metabolic syndrome: Time for a critical appraisal: Joint statement from the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care,28, 2289–2304.

    Article  Google Scholar 

  4. Ford, E. S. (2005). Risks for all-cause mortality, cardiovascular disease, and diabetes associated with the metabolic syndrome: A summary of the evidence. Diabetes Care,28, 1769–1778.

    Article  Google Scholar 

  5. Center for Disease Prevention and Control Division of Diabetes Translation. US Diabetes Surveillance System. Long-term trends in diabetes 2017. Retrieved August 3, 2019, from https://www.cdc.gov/diabetes/statistics/slides/long_term_trends.pdf.

  6. Carroll, M. D., Fryar, C. D., & Kit, B. K. (2015). Total and high-density lipoprotein cholesterol in adults: United States, 2011-2014. NCHS Data Brief, No. 226. Hyattsville, MD: National Center for Health Statistics.

  7. Zhang, Y., & Moran, A. E. (2017). Trends in the prevalence, awareness, treatment, and control of hypertension among young adults in the United States, 1999 to 2014. Hypertension,70(4), 736–742.

    Article  CAS  Google Scholar 

  8. Sullivan, P. W., Ghushchyan, V., & Ben-Joseph, R. H. (2008). The effect of obesity and cardiometabolic risk factors on expenditures and productivity in the United States. Obesity,16(9), 2155–2162.

    Article  Google Scholar 

  9. Guyatt, G. H., Feeny, D. H., & Patrick, D. L. (1993). Measuring health-related quality of life. Annals of Internal Medicine,118, 622–629.

    Article  CAS  Google Scholar 

  10. Dominick, K. L., Ahern, F. M., Gold, C. H., & Heller, D. A. (2002). Relationship of health-related quality of life to healthcare utilization and mortality among older adults. Aging Clinical and Experimental Research,14(6), 499–508.

    Article  Google Scholar 

  11. DeSalvo, K. B., Bloser, N., Reynolds, K., He, J., & Muntner, P. J. (2006). Mortality prediction with a single general self-rated health question: A meta-analysis. Journal of General Internal Medicine,21(3), 267–275.

    Article  Google Scholar 

  12. Sullivan, P. W., Ghushchyan, V., Wyatt, H. R., Wu, E. Q., & Hill, J. O. (2007). Impact of cardiometabolic risk factor clusters on health-related quality of life in the US. Obesity,15(2), 511–521.

    Article  Google Scholar 

  13. Mitchell, P. M., Al-Janabi, H., Richardson, J., Iezzi, A., & Coast, J. (2015). The relative impacts of disease on health status and capability wellbeing: a multi-country study. PLoS ONE,10(12), e0143590.

    Article  Google Scholar 

  14. Jorgensen, T., Johansson, S., Kennerfalk, A., Wallander, M. A., & Svardsudd, W. K. (2001). Prescription drug use, diagnoses, and healthcare utilization among the elderly. Annals of Pharmacotherapy,35(9), 1004–1009.

    Article  CAS  Google Scholar 

  15. Linjakumpu, T., Hartikainen, S., Klaukka, T., Veijola, J., Kivela, S. L., & Isoaho, R. (2002). Use of medications and polypharmacy are increasing among the elderly. Journal of Clinical Epidemiology,55(8), 809–817.

    Article  Google Scholar 

  16. Bedell, S. E., Jabbour, S., Goldberg, R., et al. (2000). Discrepancies in the use of medications, their extent and predictors in an outpatient practice. Archives of Internal Medicine,160(14), 2129–2134.

    Article  CAS  Google Scholar 

  17. Pantalone, K. M., Hobbs, T. M., Wells, B. J., Kong, S. X., Kattan, M. W., Bouchard, J., et al. (2015). Clinical characteristics, complications, comorbidities and treatment patterns among patients with type 2 diabetes mellitus in a large integrated health system. BMJ Open Diabetes Research and Care,3, e000093.

    Article  Google Scholar 

  18. Ventura, H. O., & Lavie, C. J. (2016). Impact of comorbidities in hypertension. Current Opinion in Cardiology,31(4), 374–375.

    Article  Google Scholar 

  19. Iglay, K., Hannachi, H., Joseph Howie, P., et al. (2016). Prevalence and co-prevalence of comorbidities among patients with type 2 diabetes mellitus. Current Medical Research and Opinion,32(7), 1243–1252.

    Article  Google Scholar 

  20. Park, C., Fang, J., Hawkins, N. A., & Wang, G. (2017). Comorbidity status and annual total medical expenditures in US hypertensive adults. American Journal of Preventive Medicine,53(6), S172–S181.

    Article  Google Scholar 

  21. Vyas, A., Pan, X., & Sambamoorthi, U. (2012). Chronic condition clusters and polypharmacy among adults. International Journal of Family Medicine,2012, 193168.

    Article  Google Scholar 

  22. Abolhassani, N., Castioni, J., Marques-Vidal, P., Vollenweider, P., & Waeber, G. (2017). Determinants of change in polypharmacy status in Switzerland: the population-based CoLaus study. European Journal of Clinical Pharmacology,73, 1187–1194.

    Article  Google Scholar 

  23. Fincke, B. G., Miller, D. R., & Spiro, A. (1998). The interaction of patient perception of overmedication with drug compliance and side effects. Journal of General Internal Medicine,13(3), 182–185.

    Article  CAS  Google Scholar 

  24. Henderson, J. A., Buchwald, D., & Manson, S. M. (2006). Relationship of medication use to health-related quality of life among a group of older American Indians. Journal of Applied Gerontology,25(1), 89S–104S.

    Article  Google Scholar 

  25. Clearya, K. K., & Howell, D. M. (2007). Prescription medication use and health-related quality of life in rural elderly. Physical & Occupational Therapy in Geriatrics,26(2), 63–81.

    Article  Google Scholar 

  26. Montiel-Luque, A., Nunez-Montenegro, A. J., Martin-Aurioles, E., et al. (2017). Medication-related factors associated with health-related quality of life in patients older than 65 years with polypharmacy. PLoS ONE,12(2), e0171320.

    Article  Google Scholar 

  27. Bonfiglio, V., Umegaki, H., & Kuzuya, M. (2019). Potentially inappropriate medications and polypharmacy: A study of older people with mild cognitive impairment and mild dementia. Journal of Alzheimer’s Disease Preprint,71(3), 889–897.

    Article  CAS  Google Scholar 

  28. Midao, L., Giardini, A., Menditto, E., Kardas, P., & Costa, E. (2018). Polypharmacy prevalence among older adults based on the survey of health, ageing and retirement in Europe. Archives of Gerontology and Geriatrics,78, 213–220.

    Article  Google Scholar 

  29. Rodrigues, M. C., & Oliveira, C. D. (2016). Drug-drug interactions and adverse drug reactions in polypharmacy among older adults: An integrative review. Revista Latino-Americana de Enfermagem,24, e2800.

    PubMed  PubMed Central  Google Scholar 

  30. Rosenberg, J., Rochon, P. A., & Gill, S. S. (2014). Unveiling a prescribing cascade in an older man. Journal of the American Geriatrics Society,62(3), 580–581.

    Article  Google Scholar 

  31. Rollason, V., & Vogt, N. (2003). Reduction of polypharmacy in the elderly. A systematic review of the role of the pharmacist. Drugs Aging,20, 817–832.

    Article  Google Scholar 

  32. Wise, J. (2013). Polypharmacy: A necessary evil. BMJ,347, f7033.

    Article  Google Scholar 

  33. Agency for Healthcare Research and Quality. Medical Expenditure Panel Survey, HC-181: 2015 Full Year Consolidated Data File; 2017. Retrieved July 17, 2019, from https://meps.ahrq.gov/data_stats/download_data/pufs/h181/h181doc.pdf.

  34. Medical Expenditure Panel Survey Clinical Classification Code to ICD-9-CM Code Crosswalk. Retrieved September 30, 2019, from https://meps.ahrq.gov/data_stats/download_data/pufs/h180/h180doc.pdf.

  35. Ware, J., Jr., Kosinski, M., & Keller, S. D. (1996). A 12-item short-form health survey: Construction of scales and preliminary tests of reliability and validity. Medical Care,34, 220–233.

    Article  Google Scholar 

  36. Ware, J. Jr, Kosinski, M., Turner-Bowker, D. M., & Gandek, B. SF-12v2: How to score version 2 of the SF-12 health survey (with a supplement documenting version 1). Lincoln, RI: QualityMetric Inc.

  37. Masnoon, N., Shakib, S., Kalisch-Ellett, L., & Caughry, G. E. (2017). What is polypharmacy? A systematic review of definitions. BMC Geriatrics,17(1), 230.

    Article  Google Scholar 

  38. Mizokami, F., Koide, Y., Noro, T., & Furuta, K. (2012). Polypharmacy with common diseases in hospitalized elderly patients. The American Journal of Geriatric Pharmacotherapy,10(2), 123–128.

    Article  Google Scholar 

  39. Indu, R., Adhikari, A., Maisnam, I., Basak, P., Sur, T. K., & Das, A. K. (2018). Polypharmacy and comorbidity status in the treatment of type 2 diabetic patients attending a tertiary care hospital: An observational and questionnaire-based study. Perspectives in Clinical Research,9(3), 139–144.

    Article  Google Scholar 

  40. Hays, R. D., & Morales, L. S. (2001). The RAND-36 measure of health-related quality of life. Annals of Medicine,33, 350–357.

    Article  CAS  Google Scholar 

  41. Henderson, J. A., Buchwald, D., & Manson, S. M. (2006). Relationship of medication use to health-related quality of life among a group of older American Indians. J Appl Gerontol,25(1), 89S–104S.

    Article  Google Scholar 

  42. Franic, D. M., & Jiang, J. Z. (2006). Potentially inappropriate drug use and health-related quality of life in the elderly. Pharmacotherapy,26(6), 768–778.

    Article  Google Scholar 

  43. Kadam, U. T. (2011). Potential health impacts of multiple drug prescribing for older people: A case-control study. British Journal of General Practice,61(583), 128–130.

    Article  Google Scholar 

  44. Stewart, S. T., Woodward, R. M., & Cutler, D. M. A proposed methods for monitoring US population health: Linking symptoms, impairments, chronic conditions, and health ratings. In NBER Working Paper Series. National Bureau of Economic Research, Cambridge, Massachusetts, USA.

  45. Magaziner, J., Cadigan, D. A., Fedder, D. O., & Hebel, J. R. (1989). Medication use and functional decline among community-dwelling older women. Journal of Aging Health,1, 470–484.

    Article  Google Scholar 

  46. Verdoorn, S., Kwint, H., Blom, J. W., Gussekloo, J., & Bouvy, M. L. (2019). Effects of a clinical medication review focused on personal goals, quality of life, and health problems in older persons with polypharmacy: a randomized controlled trial (DREAMeR-study). PLoS Medicine,16(5), e1002798.

    Article  Google Scholar 

  47. Choe, H. M., Farris, K. B., Stevenson, J. G., et al. (2012). Patient-centered medical home: developing, expanding, and sustaining a role for pharmacists. American Journal of Health System Pharmacy,69(12), 1063–1071.

    Article  Google Scholar 

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Funding

This study was not funded by any grant.

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Authors and Affiliations

  1. Department of Pharmacy Practice, College of Pharmacy, University of Rhode Island, 7 Greenhouse Road, Kingston, RI, 02881, USA

    Ami Vyas, Frisca Kang & Marilyn Barbour

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  1. Ami Vyas
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Correspondence to Ami Vyas.

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This study involved secondary database analysis of a publicly available database, and hence, this study was deemed to be exempt from ethical approval by our institution.

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Vyas, A., Kang, F. & Barbour, M. Association between polypharmacy and health-related quality of life among US adults with cardiometabolic risk factors. Qual Life Res 29, 977–986 (2020). https://doi.org/10.1007/s11136-019-02377-5

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