<p>Lifespan inequality is a fundamental marker of population health that has been studied extensively in the last couple of decades. However, little is known about the most important drivers of such inequality and its changes over time. This research note presents a novel method to decompose lifespan inequality in those settings where the population under study is partitioned across several factors <i>simultaneously</i> (e.g., race, sex, ethnicity, education, and so on) and one wants to know which one of them is its most important determinant. Unlike traditional approaches that inspect the influence of each factor on the outcome of interest separately, the proposed method allows determining the contribution of those several factors and their multiple-way interactions to overall lifespan inequality. We illustrate the method using US life tables from 2010 for adults aged 25 and over by sex, race, and educational attainment. In our example, the two- and three-way interactions between factors account for more than 40% of between-group inequality—a sizable quantity that speaks about the non-trivial associations that exist among them. The methods proposed here can be useful in the analysis of inequality in areas going beyond health—for instance, in the broad and expanding field of intersectional inequalities.</p>