Purpose: Investigations into rural tobacco-related disparities in the U.S. are hampered by the lack of a standardized approach for identifying the rurality-and, consequently, the urbanicity-of an area. Therefore, the purpose of this study was to compare the most common urban/rural definitions (Census Bureau, OMB, RUCA, and Isolation) and determine which is preferable for explaining the geographic distribution of several tobacco-related outcomes (behavior, receiving a doctor's advice to quit, and support for secondhand smoke policies). Methods: Data came from The Current Population Survey Tobacco Use Supplement. For each tobacco-related outcome, one logistic regression was conducted for each urban/rural measure. Models were then ranked according to their ability to explain the data using Akaike information criterion (AIC). Results: Each definition provided very different estimates for the prevalence of the U.S. population that is considered "rural" (e.g., 5.9% for the OMB, 17.0% for the Census Bureau). The OMB definition was most sensitive at detecting urban/rural differences, followed by the Isolation scale. Both these measures use strict, less-inclusive criteria for what constitutes "rural." Conclusions: Overall, results demonstrate the heterogeneity across urban/rural measures. Although findings do not provide a definitive answer for which urban/rural definition is the best for examining rural tobacco use, they do suggest that the OMB and Isolation measures may be most sensitive to detecting many types of urban/rural tobacco-related disparities. Caveats and implications of these findings for rural tobacco use disparities research are discussed. Efforts such as these to better understand which rural measure is appropriate for which situation can improve the precision of rural substance use research.
Purpose: Investigations into rural tobacco-related disparities in the U.S. are hampered by the lack of a standardized approach for identifying the rurality-and, consequently, the urbanicity-of an area. Therefore, the purpose of this study was to compare the most common urban/rural definitions (Census Bureau, OMB, RUCA, and Isolation) and determine which is preferable for explaining the geographic distribution of several tobacco-related outcomes (behavior, receiving a doctor's advice to quit, and support for secondhand smoke policies). Methods: Data came from The Current Population Survey Tobacco Use Supplement. For each tobacco-related outcome, one logistic regression was conducted for each urban/rural measure. Models were then ranked according to their ability to explain the data using Akaike information criterion (AIC). Results: Each definition provided very different estimates for the prevalence of the U.S. population that is considered "rural" (e.g., 5.9% for the OMB, 17.0% for the Census Bureau). The OMB definition was most sensitive at detecting urban/rural differences, followed by the Isolation scale. Both these measures use strict, less-inclusive criteria for what constitutes "rural." Conclusions: Overall, results demonstrate the heterogeneity across urban/rural measures. Although findings do not provide a definitive answer for which urban/rural definition is the best for examining rural tobacco use, they do suggest that the OMB and Isolation measures may be most sensitive to detecting many types of urban/rural tobacco-related disparities. Caveats and implications of these findings for rural tobacco use disparities research are discussed. Efforts such as these to better understand which rural measure is appropriate for which situation can improve the precision of rural substance use research.
Authors: Megan E Roberts; Nathan J Doogan; Allison N Kurti; Ryan Redner; Diann E Gaalema; Cassandra A Stanton; Thomas J White; Stephen T Higgins Journal: Health Place Date: 2016-04-22 Impact factor: 4.078
Authors: N J Doogan; M E Roberts; M E Wewers; C A Stanton; D R Keith; D E Gaalema; A N Kurti; R Redner; A Cepeda-Benito; J Y Bunn; A A Lopez; S T Higgins Journal: Prev Med Date: 2017-03-16 Impact factor: 4.018
Authors: Frances A Stillman; Erin Tanenbaum; Mary Ellen Wewers; Devi Chelluri; Elizabeth A Mumford; Katherine Groesbeck; Nathan Doogan; Megan Roberts Journal: Prev Med Date: 2018-09-24 Impact factor: 4.018
Authors: Sara E Watson; Paul Smith; Jessica Snowden; Vida Vaughn; Lesley Cottrell; Christi A Madden; Alberta S Kong; Russell McCulloh; Crystal Stack Lim; Megan Bledsoe; Karen Kowal; Mary McNally; Lisa Knight; Kelly Cowan; Elizabeth Yakes Jimenez Journal: Clin Transl Sci Date: 2022-01-21 Impact factor: 4.438