ABSTRACT: Highlights • Rurality was not significantly associated with BMI percentiles.• Suburban adolescents had significantly different dietary behaviors.• Being non-Hispanic black was a predictor of BMI and obesity-related risk factors.• Low household income was a predictor of BMI and obesity-related risk factors.• Additional obesity research using a three-category rurality classification is needed. Data from the nationally representative 2014 Family Life, Activity, Sun, Health, and Eating (FLASHE) study was examined to identify differences in adolescent Body Mass Index (BMI) and obesity-related behaviors by rurality status (i.e., urban, suburban, rural) while accounting for relevant demographics (i.e., sex, race/ethnicity, household income). This secondary, cross-sectional analysis included 1,353 adolescents. Analyses included descriptive statistics, one-way analysis of variance, Chi-squared tests, and multiple linear regression models (reported significance level p < 0.05). Rurality was not associated with BMI when controlling for demographics. However, relative to rural adolescents, suburban adolescents had significantly higher junk food, sugar-sweetened beverages (SSB), sugary food (all β=+0.2, p ≤ 0.001), and fruit/vegetable intake (β=+0.1, p ≤ 0.05). Compared to Non-Hispanic White adolescents, Non-Hispanic Black adolescents had significantly higher BMI (β=+4.4, p ≤ 0.05), total sedentary time (β=+4.1, p ≤ 0.001), junk food, SSB, and sugary food intake (all β=+0.2, p ≤ 0.05). Relative to their lower-income household counterparts, adolescents from higher-income households had significantly lower BMI (β = -9.7, p ≤ 0.001), junk food (β = -0.2, p ≤ 0.05), and SSB intake (β = -0.5, p ≤ 0.001). Contrary to literature, rurality was not a significant predictor of adolescent BMI. While suburban status was significantly associated with several diet-related risk factors, it was not in the direction anticipated. Being non-Hispanic Black and from a low-income household had the greatest influence on adolescent BMI. Findings highlight the importance of using a three-category classification for rurality.