Quality of Life, Perceptions of Health and IIIness, and Complementary Therapy Use Among People with Type 2 Diabetes and Cardiovascular Disease.

CARDIOVASCULAR disease treatment; TYPE 2 diabetes treatment; EDUCATIONAL attainment; ALTERNATIVE medicine; ATTITUDE (Psychology); CHI-squared test; COMPARATIVE studies; CONFIDENCE intervals; DISEASES; EMPLOYMENT; EPIDEMIOLOGY; GOODNESS-of-fit tests; HEALTH attitudes; HEALTH status indicators; HELP-seeking behavior; MARITAL status; POSTAL service; QUALITY of life; QUESTIONNAIRES; RESEARCH funding; SELF-evaluation; SURVEYS; T-test (Statistics); WORLD Wide Web; COMORBIDITY; LOGISTIC regression analysis; DATA analysis; WELL-being; DATA analysis software; DESCRIPTIVE statistics

AUSTRALIA; VICTORIA

Objectives: To explore perceptions of health and illness, and the use of complementary and alternative medicine (CAM), among people with type 2 diabetes and/or cardiovascular disease (CVD), and relate these to quality of life. Design: A self-administered survey was delivered by mail and internet. The questionnaire was designed from data generated from qualitative research and other sources, to collect information on health-status, CAM use, and health and illness perceptions. Quality of life was compared among participants using Assessment of Quality of Life (AQoL-4D). Subjects: Adults with type 2 diabetes and/or CVD residing in Victoria, Australia, whether or not they used CAM therapies as well as conventional medical treatment. Outcome measures: Comparisons were made of AQoL-4D utility scores, demographic, health and wellbeing status, care-seeking and health management behaviors, and behavioral and illness perception variables. A range of descriptive statistical and predictive modeling techniques were used to assess significant associations ( p<0.01) between CAM-user and non-user populations. Results: From a sample of 2766 people, 45.1% had used CAM in the past 12 months and the remainder had never used CAM; ages ranged from 20-96 years. CAM-users tended to report lower (worse) quality of life measures than non-users, and a greater number of chronic conditions in addition to diabetes and CVD. Despite this, CAM-users reported their illness perception and behavioral change more positively than non-users. There was little difference between CAM and non-users in use of prescription medications despite CAM-users greater disease burden. Conclusion: Higher CAM use and low quality of life appear to reflect comorbidity and poor general health. Greater evidence is needed of how CAM use might support chronic illness prevention and complement chronic disease management, with important policy implications concerning the integration of CAM therapies with mainstream health services. [ABSTRACT FROM AUTHOR]

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