Addressing health disparities among different demographic groups is a key challenge in public health. Despite many efforts, there is still a gap in understanding how these disparities unfold over time. Our paper focuses on this overlooked longitudinal aspect, which is crucial in both clinical and public health settings. In this paper, we introduce a longitudinal disparity decomposition method that decomposes disparities into three components: the explained disparity linked to differences in the exploratory variables' conditional distribution when the modifier distribution is identical between majority and minority groups, the explained disparity that emerges specifically from the unequal distribution of the modifier and its interaction with covariates, and the unexplained disparity. The proposed method offers a dynamic alternative to the traditional Peters-Belson decomposition approach, tackling both the potential reduction in disparity if the covariate distributions of minority groups matched those of the majority group and the evolving nature of disparity over time. We apply the proposed approach to a fetal growth study to gain insights into disparities between different race/ethnicity groups in fetal developmental progress throughout the course of pregnancy.

翻译：解决不同人口群体间的健康差异是公共卫生领域的关键挑战。尽管已有多项努力，但对于这些差异如何随时间演变的理解仍存在空白。本文聚焦于这一被忽视的纵向维度，该维度在临床和公共卫生实践中均至关重要。我们提出一种纵向差异分解方法，将差异分解为三个组成部分：由两组（多数群体与少数群体）调节变量分布相同时解释变量条件分布差异所导致的解释性差异；因调节变量分布不均及其与协变量交互作用而特异性产生的解释性差异；以及未解释性差异。该方法为传统的Peters-Belson分解方法提供了动态替代方案，既处理少数群体协变量分布与多数群体一致时差异可能减少的问题，也应对差异随时间演变的特性。我们将所提方法应用于一项胎儿生长研究，以深入理解整个孕期不同种族/民族群体在胎儿发育进程中的差异。