• Yongwen Jiang and Jana Earl Hesser.
• Center for Health Data and Analysis, Rhode Island Department of Health, Providence, Rhode Island, USA. Yongwen.Jiang@health.ri.gov
• Health Qual Life Out. 2008 Jul 11; 6: 49.

BackgroundHealth-related quality of life (HRQOL) has become an important consideration in assessing the impact of chronic disease on individuals as well as in populations. HRQOL is often assessed using multiple indicators. The authors sought to determine if multiple indicators of HRQOL could be used to characterize patterns of HRQOL in a population, and if so, to examine the association between such patterns and demographic, health risk and health condition covariates.MethodsData from Rhode Island's 2004 Behavioral Risk Factor Surveillance System (BRFSS) were used for this analysis. The BRFSS is a population-based random-digit-dialed telephone survey of adults ages 18 and older. In 2004 RI's BRFSS interviewed 3,999 respondents. A latent class regression (LCR) model, using 9 BRFSS HRQOL indicators, was used to determine latent classes of HRQOL for RI adults and to model the relationship between latent class membership and covariates.ResultsRI adults were categorized into four latent classes of HRQOL. Class 1 (76%) was characterized by good physical and mental HRQOL; Class 2 (9%) was characterized as having physically related poor HRQOL; Class 3 (11%) was characterized as having mentally related poor HRQOL; and Class 4 (4%) as having both physically and mentally related poor HRQOL. Class 2 was associated with older age, being female, unable to work, disabled, or unemployed, no participation in leisure time physical activity, or with having asthma or diabetes. Class 3 was associated with being female, current smoking, or having asthma or disability. Class 4 was associated with almost all the same predictors of Classes 2 and 3, i.e. older age, being female, unable to work, disabled, or unemployed, no participation in leisure time physical activity, current smoking, with having asthma or diabetes, or with low income.ConclusionUsing a LCR model, the authors found 4 distinct patterns of HRQOL among RI adults. The largest class was associated with good HRQOL; three smaller classes were associated with poor HRQOL. We identified the characteristics of subgroups at higher-risk for each of the three classes of poor HRQOL. Focusing interventions on the high-risk populations may be one approach to improving HRQOL in RI.

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