George Rust1,2, Shun Zhang3, Zhongyuan Yu4, Lee Caplan5, Sanjay Jain6, Turgay Ayer7, Luceta McRoy8, Robert S Levine9. 1. Department of Behavioral Sciences and Social Medicine, Florida State University College of Medicine, Tallahassee, FL. 2. Department of Community Health And Preventive Medicine, Morehouse School of Medicine, Atlanta, Georgia. 3. Statistics and Methodology Department, NORC at the University of Chicago, Chicago, Illinois. 4. School of Systems and Enterprises, Stevens Institute of Technology, Hoboken, New Jersey. 5. Deparment of Community Health and Preventive Medicine, Morehouse School of Medicine, Atlanta, Georgia. 6. Department of Medicine, Morehouse School of Medicine, Atlanta, Georgia. 7. Department of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia. 8. School of Business and Management, Southern Adventist University, Collegedale, Tennessee. 9. Department of Family and Community Medicine, Baylor College of Medicine, Houston, Texas.
Abstract
BACKGROUND: Although colorectal cancer (CRC) mortality rates are declining, racial-ethnic disparities in CRC mortality nationally are widening. Herein, the authors attempted to identify county-level variations in this pattern, and to characterize counties with improving disparity trends. METHODS: The authors examined 20-year trends in US county-level black-white disparities in CRC age-adjusted mortality rates during the study period between 1989 and 2010. Using a mixed linear model, counties were grouped into mutually exclusive patterns of black-white racial disparity trends in age-adjusted CRC mortality across 20 three-year rolling average data points. County-level characteristics from census data and from the Area Health Resources File were normalized and entered into a principal component analysis. Multinomial logistic regression models were used to test the relation between these factors (clusters of related contextual variables) and the disparity trend pattern group for each county. RESULTS: Counties were grouped into 4 disparity trend pattern groups: 1) persistent disparity (parallel black and white trend lines); 2) diverging (widening disparity); 3) sustained equality; and 4) converging (moving from disparate outcomes toward equality). The initial principal component analysis clustered the 82 independent variables into a smaller number of components, 6 of which explained 47% of the county-level variation in disparity trend patterns. CONCLUSIONS: County-level variation in social determinants, health care workforce, and health systems all were found to contribute to variations in cancer mortality disparity trend patterns from 1990 through 2010. Counties sustaining equality over time or moving from disparities to equality in cancer mortality suggest that disparities are not inevitable, and provide hope that more communities can achieve optimal and equitable cancer outcomes for all. Cancer 2016;122:1735-48.
BACKGROUND: Although colorectal cancer (CRC) mortality rates are declining, racial-ethnic disparities in CRC mortality nationally are widening. Herein, the authors attempted to identify county-level variations in this pattern, and to characterize counties with improving disparity trends. METHODS: The authors examined 20-year trends in US county-level black-white disparities in CRC age-adjusted mortality rates during the study period between 1989 and 2010. Using a mixed linear model, counties were grouped into mutually exclusive patterns of black-white racial disparity trends in age-adjusted CRC mortality across 20 three-year rolling average data points. County-level characteristics from census data and from the Area Health Resources File were normalized and entered into a principal component analysis. Multinomial logistic regression models were used to test the relation between these factors (clusters of related contextual variables) and the disparity trend pattern group for each county. RESULTS: Counties were grouped into 4 disparity trend pattern groups: 1) persistent disparity (parallel black and white trend lines); 2) diverging (widening disparity); 3) sustained equality; and 4) converging (moving from disparate outcomes toward equality). The initial principal component analysis clustered the 82 independent variables into a smaller number of components, 6 of which explained 47% of the county-level variation in disparity trend patterns. CONCLUSIONS: County-level variation in social determinants, health care workforce, and health systems all were found to contribute to variations in cancer mortality disparity trend patterns from 1990 through 2010. Counties sustaining equality over time or moving from disparities to equality in cancer mortality suggest that disparities are not inevitable, and provide hope that more communities can achieve optimal and equitable cancer outcomes for all. Cancer 2016;122:1735-48.
Authors: Joedrecka S Brown Speights; Samantha Sittig Goldfarb; Brittny A Wells; Leslie Beitsch; Robert S Levine; George Rust Journal: Am J Public Health Date: 2017-03-21 Impact factor: 9.308
Authors: Luceta McRoy; Josué Epané; Zo Ramamonjiarivelo; Ferhat Zengul; Robert Weech-Maldonado; George Rust Journal: Cancer Causes Control Date: 2021-10-27 Impact factor: 2.506
Authors: Samantha S Goldfarb; Kelsey Houser; Brittny A Wells; Joedrecka S Brown Speights; Les Beitsch; George Rust Journal: PLoS One Date: 2018-07-31 Impact factor: 3.240
Authors: Michael Hendryx; Lucia Guerra-Reyes; Benjamin D Holland; Michael Dean McGinnis; Emily Meanwell; Susan E Middlestadt; Karen M Yoder Journal: BMJ Open Date: 2017-10-11 Impact factor: 2.692