Structural
State-Level Weight Stigma: A novel measure using Project Implicit data and case-study application Alexis Miranda* Alexis Miranda Brittany Charlton Colleen Reynolds Bryn Austin Ariel Beccia
Objective: The importance of studying root causes of health inequities (e.g., structural racism) is established, yet few studies have explored the health effects of structural forms of weight stigma on health. Our objective was to develop a measure of weight stigma at the state level and perform an illustrative case study using preterm birth, an outcome known to be associated with other systems of oppression like racism. Methods: Using data from Project Implicit, a nonprofit that administers implicit association tests to help identify implicit bias, we compiled several individual-level indicators of weight stigma into a composite score and categorized states according to their level of weight stigma, based on quartiles of the state-level average. Case study data were drawn from the longitudinal Growing Up Today Study; participants were followed beginning in 1996 and a lifetime pregnancy history was assessed in 2019. We fit unadjusted logistic regression analyses with generalized estimating equations to account for clustering by multiple births to estimate associations between state-level weight stigma and preterm birth. Results: Individuals residing in states with the highest quartile of weight stigma score (Q4) had 1.49-times the odds of preterm birth compared to those living in the lowest quartile of weight stigma score (95% CI: 1.00, 2.22). The predicted probability of preterm birth in the lowest exposure quartile (Q1) is 0.070; 0.058 for those in Q2; 0.062 for those in Q3; 0.10 for those in Q4. Conclusions: Findings from this study suggest that weight stigma at the state level may be associated with preterm birth. We have demonstrated the effective use of this novel measure and the relative ease in which it can be applied to future studies of weight stigma and health. Future work should examine cumulative exposure to weight stigma over the life-course and consider additional methods to operationalize this exposure in conjunction with individual-level measures.