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The Role of Body Mass Index at Diagnosis of Colorectal Cancer on Black-White Disparities in Survival: A Density Regression Mediation Approach (306669)
*Katrina L Devick, Mayo ClinicLinda Valeri, Columbia Mailman School of Public Health
Jarvis Chen, Harvard T.H. Chan School of Public Health
Alejandro Jara, Pontificia Universidad Católica de Chile
Marie-Abèle Bind, Harvard University
Brent A Coull, Harvard T.H. Chan School of Public Health
Keywords: Accelerated failure time model, Cancer health disparities, Causal inference, Dependent Dirichlet process, Nonparametric Bayesian, Stochastic Interventions
The study of racial/ethnic inequalities in health is important to reduce the uneven burden of disease. In the case of colorectal cancer (CRC), disparities in survival among non-Hispanic Whites and Blacks are well documented, and mechanisms leading to these disparities need to be studied formally. Body mass index (BMI) is a well-established risk factor for developing CRC, and recent literature shows BMI at diagnosis of CRC is associated with survival. Since BMI varies by racial/ethnic group, a question that arises is whether disparities in BMI is partially responsible for observed racial/ethnic disparities in CRC survival. This paper presents new methodology to quantify the impact of the hypothetical intervention that matches the BMI distribution in the Black population to a potentially complex distributional form observed in the White population on racial/ethnic disparities in survival. We perform a simulation that shows our proposed Bayesian density regression approach performs as well as or better than current methodology allowing for a shift in the mean of the distribution only, and that standard practice of categorizing BMI leads to large biases.