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. 2016 Jul 11:14:22.
doi: 10.1186/s12963-016-0091-3. eCollection 2016.

Summarizing health-related quality of life (HRQOL): development and testing of a one-factor model

Shaoman Yin  1 , Rashid Njai  2 , Lawrence Barker  2 , Paul Z Siegel  2 , Youlian Liao  2
Affiliations

Summarizing health-related quality of life (HRQOL): development and testing of a one-factor model

Shaoman Yin et al. Popul Health Metr. .

Abstract

Background: Health-related quality of life (HRQOL) is a multi-dimensional concept commonly used to examine the impact of health status on quality of life. HRQOL is often measured by four core questions that asked about general health status and number of unhealthy days in the Behavioral Risk Factor Surveillance System (BRFSS). Use of these measures individually, however, may not provide a cohesive picture of overall HRQOL. To address this concern, this study developed and tested a method for combining these four measures into a summary score.

Methods: Exploratory and confirmatory factor analyses were performed using BRFSS 2013 data to determine potential numerical relationships among the four HRQOL items. We also examined the stability of our proposed one-factor model over time by using BRFSS 2001-2010 and BRFSS 2011-2013 data sets.

Results: Both exploratory factor analysis and goodness of fit tests supported the notion that one summary factor could capture overall HRQOL. Confirmatory factor analysis indicated acceptable goodness of fit of this model. The predicted factor score showed good validity with all of the four HRQOL items. In addition, use of the one-factor model showed stability, with no changes being detected from 2001 to 2013.

Conclusion: Instead of using four individual items to measure HRQOL, it is feasible to study overall HRQOL via factor analysis with one underlying construct. The resulting summary score of HRQOL may be used for health evaluation, subgroup comparison, trend monitoring, and risk factor identification.

Keywords: Factor analysis; Health-related quality of life; Summary score.

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Figures

Fig. 1
Fig. 1
Final one-factor model for the CDC HRQOL-4, BRFSS 2013. Standardized factor loadings from the latent construct (represented by the large oval) to its measures (represented by rectangles) are shown beside the single-headed arrows. The small ovals represent error variances unexplained by the model. The curved double-headed arrow represents correlations between error variances
Fig. 2
Fig. 2
HRQOL summary score, BRFSS 2013. Histogram shows the distribution of the HRQOL summary score using BRFSS 2013 data set. Larger value means better quality of HRQOL. The “skewed left” distribution suggests that the majority of the population is healthy in terms of HRQOL
Fig. 3
Fig. 3
Trend analysis of overall HRQOL, BRFSS 2001–2010 and 2011–2013. The weighted and age-adjusted HRQOL summary scores were predicated by the model for the 2001–2010 and 2011–2013 periods, respectively. The mean HRQOL summary score for each year is shown from 2001 to 2013. The 2000 US Census population was used for age standardization.
See this image and copyright information in PMC

References

    1. Palermo TM, Long AC, Lewandowski AS, Drotar D, Quittner AL, Walker LS. Evidence-based assessment of health-related quality of life and functional impairment in pediatric psychology. J Pediatr Psychol. 2008;33:983–996. doi: 10.1093/jpepsy/jsn038. - DOI - PMC - PubMed
    1. Revicki DA, Kleinman L, Cella D. A history of health-related quality of life outcomes in psychiatry. Dialogues Clin Neurosci. 2014;16:127–135. - PMC - PubMed
    1. Centers for Disease Control and Prevention. Measuring Healthy Days: Population assessment of health-related quality of life. Atlanta, Georgia: CDC. 2000. https://www.cdc.gov/hrqol/pdfs/mhd.pdf. Accessed Nov 2000.
    1. Hennessy CH, Moriarty DG, Zack MM, Scherr PA, Brackbill R. Measuring health-related quality of life for public health surveillance. Public Health Rep. 1994;109:665–672. - PMC - PubMed
    1. Moriarty DG, Zack MM, Kobau R. The Centers for Disease Control and Prevention's Healthy Days Measures - population tracking of perceived physical and mental health over time. Health Qual Life Outcomes. 2003;1:37. doi: 10.1186/1477-7525-1-37. - DOI - PMC - PubMed