Skip Navigation
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

National Institute of Environmental Health Sciences

Use this QR code to view the newest version of this document
Use this QR code to view the newest version of this document

Your Environment. Your Health.

Publication Detail

Title: The role of body mass index at diagnosis of colorectal cancer on Black-White disparities in survival: a density regression mediation approach.

Authors: Devick, Katrina L; Valeri, Linda; Chen, Jarvis; Jara, Alejandro; Bind, Marie-Abèle; Coull, Brent A

Published In Biostatistics, (2022 Apr 13)

Abstract: 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. It has also been established that body mass index (BMI) is a 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 differences in BMI are partially responsible for observed racial/ethnic disparities in survival for CRC patients. This article 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. Our density mediation approach can be utilized to estimate natural direct and indirect effects in the general causal mediation setting under stronger assumptions. We perform a simulation study 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 when BMI is a mediator variable. When applied to motivating data from the Cancer Care Outcomes Research and Surveillance (CanCORS) Consortium, our approach suggests the proposed intervention is potentially beneficial for elderly and low-income Black patients, yet harmful for young or high-income Black populations.

PubMed ID: 32968805 Exiting the NIEHS site

MeSH Terms: Aged; Bayes Theorem; Body Mass Index; Colorectal Neoplasms*/diagnosis; Humans; Socioeconomic Factors; United States

Back
to Top