The Future of Social Determinants of Health: Addressing Structural Inequities
The discourse surrounding **Social Determinants of Health (SDOH)** has evolved significantly, moving beyond individual-level factors to a deeper understanding of the structural forces that shape health outcomes. Historically, research has focused on proximate determinants such as access to healthy food, education, and income. While these remain crucial, a growing consensus emphasizes the need to look further upstream, recognizing that systemic inequities and structural oppression are fundamental drivers of population health.
Structural oppression encompasses interconnected systems of discrimination across various societal domains—educational, economic, social, political, criminal-legal, and healthcare. These systems create and perpetuate the relational subordination of socially disadvantaged groups, reinforcing discriminatory beliefs and uneven resource distribution. Examples include structural racism, structural sexism, and other forms of systemic bias that manifest in drastic inequities within institutional arrangements. The future of SDOH research and intervention lies in comprehensively addressing these complex, multilevel, multifaceted, interconnected, systemic, and intersectional forms of oppression.
Advancing our understanding of these structural drivers requires innovative approaches to measurement and data infrastructure. A key recommendation is to utilize interdisciplinary structural theories to guide the development of robust, valid measures of structural oppression. This involves acknowledging that oppression operates at macro (e.g., state-level policies), meso (e.g., organizational practices), and micro (e.g., internalized ideologies) levels. Furthermore, structural oppression is multifaceted, embedded within various institutions, and interconnected, meaning that inequities in one domain often reinforce those in others, such as racial residential segregation impacting education, employment, and healthcare access.
To accurately capture these complex phenomena, future studies should operationalize structural forms of oppression using theory-driven empirical measures. This includes employing latent variable approaches, which are well-suited for minimizing measurement error and modeling unobserved, complex systems like structural racism and sexism. Incorporating legal, cultural, and ideological measures of structural oppression will provide a more comprehensive understanding of its pervasive influence. Additionally, investigating the geography of structural oppression—identifying ‘hot spots’ of discriminatory environments—is crucial for targeted interventions. Examining social pathways and biological mechanisms connecting structural oppression to health will further illuminate the causal links.
Ultimately, a national publicly available, user-friendly data infrastructure on contextual measures of structural oppression is essential. This infrastructure would facilitate mandated publicly funded research to analyze health inequities in relation to structural conditions and deposit data in a central repository. Such efforts would move beyond individual-level solutions, fostering systemic changes that reduce health inequities and improve overall population health. By focusing on the wider set of forces and systems shaping the conditions of daily life, we can work towards a more equitable and healthier future for all.