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  • Title: Predictors of the quality of life of older people with heart failure recruited from primary care.
    Author: Gott M, Barnes S, Parker C, Payne S, Seamark D, Gariballa S, Small N.
    Journal: Age Ageing; 2006 Mar; 35(2):172-7. PubMed ID: 16495294.
    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.
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