Uncovering the Hidden Magnitude of Within-Race/Ethnicity Skin Tone Inequality

Decades of research have linked skin tone to meaningful inequalities in health and social outcomes among individuals in the same self-identified racial/ethnic group. Yet efforts to document and understand within-race/ethnicity skin tone stratification have been hampered by a fundamental data problem: in most social surveys and biomedical databases, skin tone is either not collected or measured imprecisely using coarse categories based on a single observer’s judgment. In this study, we begin by conducting an online survey to quantify the reliability of existing interviewer-rated skin tone measures. Then, using elastic net regression, we build a genomic prediction model for skin tone among Black and Hispanic participants in the Add Health study, with the goal of improving the accuracy and availability of skin tone measurement in admixed populations. Finally, we use these DNA-based skin tone measures in two longitudinal studies to explore within-race/ethnicity skin tone inequality in contemporary America. Predicted skin tone yields substantially steeper gradients in socioeconomic status and racial classification, indicating that interviewer-rated measures meaningfully understate the degree of social stratification operating within racialized groups. Our results suggest that genetically derived skin tone predictions represent a promising new tool for advancing research on colorism – and, via the ancestry disequilibrium regression framework we introduce, a path toward identifying the causal effects of skin tone.