Beyond Social Determinants: Empirically Identifying Indigenous Determinants of Health In AI/an Communities

Background and Purpose

American Indian and Alaska Native (AI/AN) populations experience persistent health inequities shaped by structural racism, socioeconomic marginalization, and ongoing settler colonial processes. While social determinants of health (SDOH) frameworks have advanced understanding of these inequities, they often fail to capture Indigenous-specific determinants such as cultural continuity, relationality, and community connectedness. Emerging scholarship calls for the empirical identification and measurement of Indigenous determinants of health to better reflect Indigenous conceptualizations of well-being. Guided by Public Health Critical Race Praxis (PHCRP) and Indigenous health frameworks, this study aims to identify and quantitatively examine Indigenous determinants of health using data from the Native American COVID-19 Alliance (NACA) Needs Assessment. This study further assesses how these determinants relate to health outcomes during the COVID-19 pandemic and could inform future interventions that address SDOH

Methods

This study uses cross-sectional data from the NACA Needs Assessment, a national survey of AI/AN adults conducted in 2021 (N = 8,718). Health outcomes include self-rated health (ordinal), mental health indicators (binary/ordinal), substance use (binary/count), and unmet healthcare need (binary). A theoretically informed variable mapping process is used to operationalize Indigenous determinants of health across three domains: (1) structural conditions (e.g., financial hardship, employment disruption, healthcare access barriers), (2) relational and community contexts (e.g., social support, household composition), and (3) cultural and protective factors (e.g., cultural engagement, identity, resilience). Analyses include descriptive statistics and exploratory factor analysis to identify underlying constructs, followed by multivariable regression models (ordinal logistic, Poisson regression with robust standard errors, and negative binomial regression, as appropriate). Sequential modeling assesses the relative contributions of each domain to health outcomes, and stratified analyses examine heterogeneity across demographic and socioeconomic groups.

Results

Preliminary findings suggest that Indigenous determinants of health are multidimensional and extend beyond conventional SDOH measures. Structural conditions are significantly associated with poorer self-rated health, increased mental health burden, and greater unmet healthcare needs. Relational and community factors, particularly social support, are associated with improved health outcomes across domains. Cultural and protective factors emerge as distinct contributors to health, demonstrating independent associations with mental health and self-rated health outcomes. Factor-analytic results indicate that the cultural, relational, and structural domains represent empirically distinguishable constructs, supporting the conceptualization of Indigenous determinants of health as a multidimensional framework.

Conclusions and Implications

This study advances social work and public health research by empirically identifying and operationalizing Indigenous determinants of health within a large national dataset. Findings underscore the importance of moving beyond conventional SDOH frameworks to incorporate culturally and relationally grounded determinants that reflect Indigenous experiences. Implications include the need for measurement development, culturally responsive interventions, and policy approaches that address structural inequities while supporting Indigenous strengths. This work contributes to growing evidence base for Indigenous-informed quantitative methodologies and offers a framework for advancing health equity in AI/AN communities.