Individuals reside within communities influenced by various social determinants impacting health, which may harmonize or conflict at individual and neighborhood levels. While some experience concordant circumstances, discordance is prevalent, yet poorly understood due to the lack of a universally accepted method for quantifying it. This paper proposes a methodology to address this gap.

We propose a systematic approach to operationalize concordance and discordance between individual and neighborhood social determinants, using household income (HHI) (continuous) and race/ethnicity (categorical) as examples for individual social determinants. We demonstrated our method with a small dataset that combines self-reported individual data with geocoded neighborhood level. We anticipate that the risk profiles created by either self-reported individual data or neighborhood-level data alone will differ from patterns demonstrated by typologies based on concordance and discordance.

In our cohort, it was revealed that 20% of patients experienced discordance between their HHIs and neighborhood characteristics. Additionally, 38% reside in racially/ethnically concordant neighborhoods, 23% in discordant ones, and 39% in neutral ones.

Our study introduces an innovative approach to defining and quantifying the notions of concordance and discordance in individual attributes concerning neighborhood-level social determinants. It equips researchers with a valuable tool to conduct more comprehensive investigations into the intricate interplay between individuals and their environments. Ultimately, this methodology facilitates a more accurate modeling of the true impacts of social determinants on health, contributing to a deeper understanding of this complex relationship.