A comparison of the four healthy days measures (HRQOL-4) with a single measure of self-rated general health in a population-based health survey in New York City

• Main Authors: Sarah E. Dumas, Tenzin Yangchen Dongchung, Michael L. Sanderson, Katherine Bartley, Amber Levanon Seligson
• Format: Article
• Language: English
• Published: BMC 2020-09-01
• Series: Health and Quality of Life Outcomes
• Subjects: Health-related quality of life; Self-rated general health; Healthy days measures; Population-based health surveys; Predictive power
• Online Access: http://link.springer.com/article/10.1186/s12955-020-01560-4

Abstract Background Data on health-related quality of life (HRQOL) can be used to track health disparities, assess the impact of chronic diseases, and predict mortality. The Centers for Disease Control and Prevention’s “Healthy Days Measures” (HRQOL-4) assesses four key domains: self-rated general health, physical health, mental health, and activity limitations. The domains are not easily combined to summarize overall HRQOL, and some evidence suggests that self-rated general health may be an adequate proxy indicator for overall HRQOL. This study compares self-rated general health as a solitary measure of HRQOL with two summary indices of the HRQOL-4 as a predictor of adverse health conditions in a representative sample of adult New York City residents. Methods The 2017 NYC Social Determinants of Health survey implemented by the New York City Department of Health and Mental Hygiene collected data from a representative sample of New Yorkers (n = 2335) via phone, mail, and web. We compared the information criteria and predictive power of self-rated general health with two alternative summary indices of the HRQOL-4 in predicting self-reported health conditions (hypertension, diabetes, obesity, non-specific psychological distress, and a summary indicator for at least one those four morbidities). Results Overall, 19.1% (95% CI: 16.9, 21.5) of respondents reported that they had fair or poor general health. Self-rated general health was significantly associated with days of poor physical health, poor mental health, and activity limitations (p < 0.001 for each). While the Akaike and Bayesian information criteria suggested that the summary indices of the HRQOL-4 produced marginally better models for predicting adverse health conditions, self-rated general health had slightly higher predictive power than did the summary indices in all models of physical health outcomes as measured by Tjur’s pseudo-R2 and the area under the curve. Conclusion We found very small differences between self-rated general health and the summary indices of the HRQOL-4 in predicting health conditions, suggesting self-rated general health is an appropriate proxy measure of overall HRQOL. Because it can be measured with a single question rather than four, it might be the most simple, efficient, and cost-effective method of summarizing HRQOL in large population-based surveys.