Erica I Lubetkin1, Haomiao Jia, Peter Franks, Marthe R Gold. 1. Department of Community Health and Social Medicine, Sophie Davis School of Biomedical Education/CUNY Medical School, New York, NY 10031, USA. lubetkin@med.cuny.edu
Abstract
INTRODUCTION: Health-related quality of life (HRQL) measures are used increasingly in evaluations of clinical and population-based outcomes and in economic analyses. We investigate the influence of demographic, socioeconomic, and chronic disease factors on the HRQL of a representative U.S. sample. METHODS: We examined data from 13,646 adults in the 2000 Medical Expenditure Panel Survey, a nationally representative sample of the U.S. general population, who completed a self-administered questionnaire containing the EQ-5D, a preference-based measure. We assessed the relationships between EQ-5D scores and sociodemographic variables, including age, sex, race/ethnicity, income and education, and six common chronic conditions. RESULTS: In fully adjusted models, EQ-5D scores decreased with increasing category of age and were lower for persons with a lower income and educational attainment as well as each of the six conditions. Although the EQ-5D scores were lower for females and Whites compared with Blacks such differences were not of a magnitude considered to be clinically important. CONCLUSIONS: In the U.S., sociodemographic factors and clinical conditions are strongly associated with scores on the EQ-5D. Population health studies and risk-adjustment models should account and adjust for these factors when assessing the performance of health programs and clinical care.
INTRODUCTION: Health-related quality of life (HRQL) measures are used increasingly in evaluations of clinical and population-based outcomes and in economic analyses. We investigate the influence of demographic, socioeconomic, and chronic disease factors on the HRQL of a representative U.S. sample. METHODS: We examined data from 13,646 adults in the 2000 Medical Expenditure Panel Survey, a nationally representative sample of the U.S. general population, who completed a self-administered questionnaire containing the EQ-5D, a preference-based measure. We assessed the relationships between EQ-5D scores and sociodemographic variables, including age, sex, race/ethnicity, income and education, and six common chronic conditions. RESULTS: In fully adjusted models, EQ-5D scores decreased with increasing category of age and were lower for persons with a lower income and educational attainment as well as each of the six conditions. Although the EQ-5D scores were lower for females and Whites compared with Blacks such differences were not of a magnitude considered to be clinically important. CONCLUSIONS: In the U.S., sociodemographic factors and clinical conditions are strongly associated with scores on the EQ-5D. Population health studies and risk-adjustment models should account and adjust for these factors when assessing the performance of health programs and clinical care.
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