Lipoprotein(a) distribution across race/ethnicity and its association with mortality outcomes in NHANES III (1988-1994) with follow up to 2019

Introduction Lipoprotein(a) [Lp(a)] is now widely recognised as an independent risk factor for cardiovascular outcomes and mortality but evidence on race/ethnicity-specific differences in Lp(a) concentrations and risk thresholds remains inconsistent. This study examines whether the association between Lp(a) and all-cause and cardiovascular mortality differs by race/ethnicity. Methods We analysed a nationally representative cohort of U.S. adult from NHANES III with mortality follow-up through 2019. Participants were stratified into three race/ethnicity groups: non-Hispanic White, non-Hispanic Black, and Mexican-American. Associations between Lp(a) and mortality outcomes were estimated using multivariable Cox and Fine-Gray competing risk models. Results A total of 50,519,751 survey-weighted records were included. Mean follow-up was 22.6 years with an estimated 17,793,340 all-cause deaths and 5,762,320 cardiovascular deaths. Median Lp(a) concentrations were higher among non-Hispanic Black participants (36 mg/dL, IQR 22-66) than non-Hispanic White (12 mg/dL, IQR 3-30) and Mexican-American (8 mg/dL, IQR 2-22) participants. In the non-Hispanic Black group 26.7% had Lp(a) 50-75 mg/dL and 15.0% had Lp(a) >75 mg/dL. Mexican American participants with Lp(a) >75 mg/dL had a higher risk of cardiovascular mortality that persisted after multivariable adjustment (sHR 2.93, 95% CI 1.01–8.56, p-value 0.049). Among non-Hispanic Black participants, higher Lp(a) was linked to all-cause and cardiovascular mortality in unadjusted models but not after adjustment. No significant association was detected in non-Hispanic White participants. Conclusion Lp(a) distributions and their relationship with clinical outcomes vary by race/ethnicity. Our findings suggest that prognostic thresholds for Lp(a) may differ across groups, supporting the need to define and validate race/ethnicity-specific cut-offs that best predict cardiovascular outcomes and improve risk stratification.