OBJECTIVES: This study aims to understand ethnic group disparities in health outcomes by examining health-related quality of life (HRQoL), work productivity loss, and resource use.   METHODS: The data came from the 2013 US National Health and Wellness Survey, a representative, cross-sectional general health survey (N=75,000). Respondents were categorized into ethnic groups based on self-reported race and Hispanic origin questions: White (n=57,916), Black (n=7,855), Hispanic/Latino (n=6,192), Asian (n=3,792), Other/Multi-ethnic (n=2,534). Differences were examined for HRQoL (SF-36v2: mental and physical component summary (MCS, PCS) and SF-6D (health utility) scores), productivity loss (Work Productivity and Activity Impairment questionnaire), and resource use in the past 6 months. Initial analyses used one-way ANOVAs and multivariable generalized linear models were used to control for demographic and health characteristics (e.g., income) to examine the unique effect associated with ethnicity. RESULTS: Preliminary comparisons revealed White respondents had the highest MCS scores (Mean=49.41) and health utility scores (M=0.74) whereas Hispanic/Latinos and Other had the lowest MCS (M=46.13, M=46.74, respectively) and health utility (M=0.71, M=0.70) scores (all ps<.05). Asian respondents had the highest PCS scores (M=52.20) with Other having the lowest (M=49.19; p<.05). Overall, White respondents had less work productivity loss (M=14.17%) and activity impairment (M=22.22%) than Hispanic/Latino (work productivity loss M=22.30% and activity impairment M=24.41%) or Other (work productivity loss M=19.06% and activity impairment M=26.20%; all ps<.05). Relative to Hispanics, White respondents reported less ER visits (M=0.19 vs. 0.34) and hospitalizations (M=0.11 vs. 0.23; all ps<.05). Adjusted models lessened many of these differences, often likening White respondents to those of ethnic minority groups. CONCLUSIONS: Initial analyses showed White respondents had higher HRQoL, less work and activity impairment, and lower resource use. However, after controlling for confounders, many of those differences were minimized indicating that factors other than ethnicity may more strongly influence health outcomes such as income.