title: Comparison of a single global item and an index of a multi-item health status measure among persons with and without diabetes in the US.
abstract: This study examined the hypothesis that a single global item can be substituted for an index of a multi-item assessment and lead to equivalent interpretative outcomes. Substitutability would be demonstrated if: (1) the two measures were strongly correlated, and regression analysis showed that the same variables accounted for variation in each measure, and (2) difference scores between multi-item and global scores were close to zero and remained so as socio-demographic and co-morbid conditions varied. A multi-item assessment was constructed by mapping items from the NHANES I Epidemiologic Follow-up Study (NHEFS), using available data for persons with and without diabetes, onto the health-status classification system of the Health Utilities Index Mark 1 (HUI), creating the NHEFS-HUI. NHEFS-HUI data, when correlated to the self-assessed health status (SAHS) item, revealed a coefficient of 0.55. Regression analyses identified 9 of 14 variables contributed to the variability of each health status index, but differences existed in which variables were significant for which measure. Five of the possible 14 difference scores for persons with diabetes and non-diabetics approached zero. Persons with diabetes had lower NHEFS-HUI scores than non-diabetics. These data were considered insufficient for demonstrating substitutability. Suggestions were made on how optimal substitutability could be achieved.
authors.affiliation: The Johns Hopkins School of Medicine, USA. ibarofsky@adelphia.net
authors.forename: I
authors.initials: I
authors.lastname: Barofsky
authors.forename: P
authors.initials: P
authors.lastname: Erickson
authors.forename: M
authors.initials: M
authors.lastname: Eberhardt
mesh_terms: D000328:Adult; D000368:Aged; D003920:Diabetes Mellitus; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D016018:Least-Squares Analysis; D008297:Male; D008875:Middle Aged; D009749:Nutrition Surveys; D011788:Quality of Life; D012044:Regression Analysis; D014481:United States