195113 Creating and Using the CDC HRQOL Healthy Days Index with Fixed Option Survey Response Options

Wednesday, November 11, 2009: 11:30 AM

Keith Zullig, MSPH, PhD , Community Medicine, West Virginia University, Morgantown, WV
J. Wanzer Drane, PE, PhD , Professor Emeritus, Department of Epidemiology and Biostatistics, University of South Carolina School of Public Health, Columbia, SC
Background: Health-related quality of life (HRQOL) measures used on interview-based BRFSS and NHANES surveys track HP 2010 objectives. “Healthy Days” are calculated by adding the number of poor physical and mental health days and subtracting the total from 30 days. However, the question becomes how to calculate this index with fixed response option surveys (e.g., ‘0 days', ‘1-2 days', ‘3-5 days', etc.)?

Hypotheses: Hypotheses examined that computing the index was possible with forced responses and that significant HRQOL differences with demographic and risk behavior variables would be observed.

Methods: Using the 1997 South Carolina YRBS and a 2007 university dataset, variables were first created based on the averages within each response option from the healthy index items (i.e. the middle value of each one of the ranges). Since each index item produced its own mean and standard deviation (SD), producing a day range from –30 to 30, adjusted command statements forced overall healthy days into a 0 to 30 range allowing an overall good health days (GHDs) mean and SD calculation possible.

Results: The coding for 4 poor physical health days (PPHDs) and 4 poor mental health days (PMHDs) was: IF (PPHDs=4 AND PMHDs < 4) OR (PPHDs < 4 AND PMHDs = 4) THEN BHDs (bad health days)=4. If a respondent reported 1.5 PMHDs and 4 PPHDs, they were assigned 4 BHDs, or 26 GHDs, the greater of the two values.

Conclusions: This “Healthy Days” calculation is confirmed by discerning significant quality of life differences among selected variables.

Learning Objectives:
1. To evaluate whether computing a healthy days index was possible with forced response option survey data. 2. To demonstrate that the computed index would be able to differentiate quality of life differences with selected demographic and risk behavior variables

Keywords: Methodology, Behavioral Research

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: Both authors jointly conceptualized and executed the study.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.