Using item response theory to analyze the relationship between health-related quality of life and health risk factors.

Many researchers have presented results of the relationships between health-related quality of life (HRQOL) indicators (outcomes) and health risk factors using either linear or logistic regression modeling. We combined the results of multiple HRQOL models by using item response theory (IRT) to assess the association between multiple correlated HRQOL indicators and multiple demographic and health risk variables as predictors. The data source for the study was Rhode Island's 2004 Behavioral Risk Factor Surveillance System, which had a sample of 3,999 adults aged 18 years or older. We developed a single model for overall HRQOL by using IRT to assess the association between HRQOL indicators and multiple demographic and health risk variables as predictors. The strongest predictors for overall poor HRQOL were lower income, inability to work, unemployment, smoking, lack of exercise, asthma, obesity, and disability. IRT may serve as a solution for modeling multiple correlated outcomes in epidemiology. Application of IRT to epidemiologic data can help identify at-risk subgroups for targeted interventions.