Evaluating buffering effects for social determinants of health and type 2 diabetes in the All of Us Research Program.

INTRODUCTION

Social determinants of health (SDOH) play a strong role in influencing type 2 diabetes (T2D) risk. Certain protective SDOH have been demonstrated to mitigate or buffer against the positive associations between risk-associated SDOH and poor health outcomes, though such buffering effects have only been evaluated among a limited range of SDOH and outside the context of T2D. This study aims to assess potential buffering effects among SDOH associated with T2D case status.

METHODS

The study population was constructed from Research Program data. Survey data were used to derive composite metrics measuring 10 different SDOH. Logistic regression models modeling T2D case status as a function of each SDOH were used to designate each as either a T2D risk-associated or protective factor. Interaction models were used to measure potential buffering effects between T2D risk-associated and protective factors.

RESULTS

The main study population consists of 215,270 participants. All ten SDOH were significantly associated with T2D. Social support and neighborhood cohesion emerged as T2D protective factors, with the rest being classified as risk-associated factors for T2D. A single buffering effect was observed between social support and stress (β = 0.43, p <0.05) (95% CI, -0.84 to -0.01). Reverse buffering effects were observed between neighborhood cohesion and discrimination, food insecurity, and individual-level socioeconomic deprivation (SED). Reverse buffering effects were also observed between social support and food insecurity, individual-level SED, and spirituality.

CONCLUSIONS

The buffering effect observed between social support and stress on T2D is consistent with previous findings. The reverse buffering effects observed in interactions between certain SDOH factors suggest that some risk-associated SDOH may weaken the potential benefits of certain protective SDOH. Interventions aimed at alleviating adverse socioeconomic conditions may have a compounding effect on reducing T2D risk by enabling communities to benefit from T2D protective factors.