Background <p>Multiracial adults represent a growing U.S. population but are often grouped together or reassigned to single-race categories in public health research, when they are included in analysis at all. Aggregation obscures subgroup variation and limits opportunities for targeted prevention.</p> Methods <p>We analyzed 2014–2023 California Behavioral Risk Factor Surveillance System data (<i>n</i> = 100,177) to estimate prevalence of 28 chronic disease and aging-related risk factors across racial and ethnic groups, including disaggregated Multiracial subgroups. We classified participants based on all self-identified races, limited aggregatation to subgroups with <i>N</i> &lt; 50, and standardized prevalence by age and sex using 2020 California population distributions. Survey-weighted methods produced prevalence estimates, relative standard errors, and subgroup comparisons.</p> Results <p>Multiracial subgroups had the highest prevalence for 24 of 28 outcomes. Prevalence differences across Multiracial subgroups also exceeded 20 percentage points for nearly half of all outcomes. American Indian or Alaska Native-Black and Hispanic-Black-White adults showed the greatest burden of chronic disease, poor general health, and disability in the sample. In contrast, while several Asian Multiracial subgroups (e.g., Asian-Black, Asian-Native Hawaiian or Pacific Islander) had the lowest prevalence across multiple domains, Asian-White adults were not consistently the healthiest Multiracial subgroup.</p> Discussion <p>Health outcomes for Multiracial adults do not follow a fixed hierarchy; subgroup position varies across domains. Wide variation is masked by common aggregation practices, leading to missed opportunities to identify and support high-burden subgroups. Surveillance systems should expand capacity to collect and report disaggregated race and ethnicity data to strengthen prevention efforts.</p>