Identifying and Monitoring Chronic Disease Disparities By Income and Race/Ethnicity Using the Health Disparities Calculator (HD*calc)

BACKGROUND:  Public health practitioners in Colorado are working to ensure health equity throughout the state. The identification, measurement, and monitoring of health disparities is a priority at state and local public health agencies. To improve measurement of chronic disease disparities, we assessed the utility of a publicly available software, the Health Disparities Calculator (HD*calc) produced by the National Cancer Institute (NCI) and the Surveillance, Epidemiology, and End Results Program (SEER). We applied the software to measure disparities in adult prevalence of health behaviors and conditions by income and race/ethnicity.  

METHODS:  Colorado Behavioral Risk Factor Surveillance System (BRFSS; 2000-2014) data were used to estimate prevalence of health behaviors and conditions by demographic factors. Body mass index (BMI) was calculated from self-reported height and weight to determine obesity (BMI≥30kg/m²). Current smoking was defined as ever smoking 100+ cigarettes and now smoking at least “some days”. Income was categorized as <$35,000, $35,000-$49,999, or $50,000+. Racial/ethnic categories were limited to White, Black, or Hispanic. Due to methodological changes to BRFSS, trends pre- and post-2011 were interpreted with caution. Prevalence estimates were calculated in three-year overlapping intervals using SAS and inputted into HD*calc to generate 11 summary measures of disparity. Trend analysis was conducted using Joinpoint software. 

RESULTS:  Obesity prevalence increased during 2000-2010 and then stabilized during 2011-2014. Prevalence decreased with increasing income, and prevalence in the middle-income group approached that of the low-income group since 2010. Absolute and relative income disparities decreased in recent years, but the trends were not statistically significant. Similar nonsignificant trends of disparity indices were found for obesity by race/ethnicity despite a consistently greater burden among Black and Hispanic adults compared with White adults. Current smoking prevalence decreased with increasing income. The overall prevalence decreased during 2000-2014 with the largest decrease among the high-income group, while income-based disparities significantly increased over the same period. Trends in racial/ethnic disparities by smoking status were nonsignificant despite higher smoking prevalence among minorities compared with Whites.   

CONCLUSIONS:  HD*calc can be used to measure and monitor disparities over time. We observed disparities in the prevalence of obesity and current smoking by income and race/ethnicity during the past 15 years. The obesity disparities were found to be statistically stable over this period while the current smoking disparities by income have increased. These findings support decisions to target public health interventions to lower income adults and minorities at high risk for obesity, smoking, and related chronic diseases.