A New Tool for Handling Multiracial and Multi-Identity Data in Health Research

When surveys ask about race or ethnicity, a growing number of Americans select more than one category. The multiracial population now represents over 10% of the U.S. population and is the fastest growing racial group in the country. Yet researchers routinely collapse these individuals into an “other race” category for statistical analysis, rendering specific subgroups invisible. This brief introduces CATAcode, a free software tool that helps researchers systematically explore, document, and prepare check-all-that-apply demographic data for statistical modeling. In a demonstration with over 8,000 high school students, CATAcode revealed 85 distinct racial identity combinations from just eight response options. The tool shows how coding decisions dramatically affect representation. In one dataset, standard approaches identified only 12 Native American participants, while a priority approach increased that number to 128. The analysis shows that even seemingly small methodological choices can mean the difference between communities being statistically invisible or present in findings.