Predictors of the quality of life of older people with heart failure recruited from primary care

Abstract

Background: current understanding of quality of life in heart failure is largely derived from clinical trials. Older people, women and those with co-morbidities are underrepresented in these. Little is known about factors predictive of quality of life amongst older people with heart failure recruited from community settings. Objective: to identify factors predictive of quality of life amongst older people recruited from community settings. Design: prospective questionnaire survey. Setting: general practice surgeries located in four areas of the UK: Bradford, Barnsley, East Devon and West Hampshire. Subjects: a total of 542 people aged >60 years with heart failure. Methods: participants completed a postal questionnaire, which included a disease-specific measure (Kansas City Cardiomyopathy Questionnaire), a generic quality-of-life measure (SF-36) and sociodemographic information. Results: a multiple linear regression analysis identified the following factors as predictive of decreased quality of life: being female, being in New York Heart Association (NYHA) functional class III or IV, showing evidence of depression, being in socioeconomic groups III–V and experiencing two or more co-morbidities. Older age was associated with decreased quality of life, as measured by a generic health-related quality-of-life tool (the SF-36 mental and physical health functioning scales) but not by a disease-specific tool (the Kansas City Cardiomyopathy Questionnaire). Conclusion: findings from the study suggest that quality of life for older people with heart failure can be described as challenging and difficult, particularly for women, those in a high NYHA class, patients showing evidence of depression, patients in socioeconomic groups III–V, those experiencing two or more co-morbidities and the ‘oldest old’. Such information can help clinicians working with older people identify those at risk of reduced quality of life and target interventions appropriately.