Importance: Neighborhood environment is an important factor associated with population disparities in obesity. However, few studies have examined whether and in what ways long-term trajectories of neighborhood conditions may be associated with weight outcomes. Moreover, there is a lack of research focusing on multidimensional and nuanced measures that make distinctions between multiple types of neighborhood change (eg, gentrification vs overall growth). Objective: To examine the association between long-term neighborhood economic trajectories and changes in weight status among Black and White adults residing in predominantly low-income communities in the southeastern US. Design, Setting, and Participants: This study was a longitudinal analysis of participants in the Southern Community Cohort Study. Five types of neighborhood economic trajectories (stability, growth, displacement, abandonment, and poverty concentration) were measured using data from the US Census and the American Community Survey from 2000 to 2016. Data were analyzed from December 12, 2021, to July 16, 2022. A total of 33621 Black and White adults in the southeastern US were included in the analytic sample. Exposure: Neighborhood economic trajectory. Main Outcomes and Measures: Substantial weight gain and substantial weight loss (ie, gaining or losing ≥10% of baseline weight) between baseline (March 2002 to September 2009) and follow-up (November 2008 to January 2013) periods were assessed using self-reported information. Results: Among 33 621 participants, the mean (SD) age was 53.4 (8.8) years; 22 116 participants (65.8%) were women, 21 782 (64.8%) were Black, and 11 839 (35.2%) were White. Compared with residents in neighborhoods with stable trajectories, those in neighborhoods with growth trajectories that did not displace original residents were less likely to experience substantial weight gain (odds ratio [OR], 0.75; 95% CI, 0.58-0.97), whereas those in neighborhoods with poverty concentration trajectories were more likely to experience substantial weight gain (OR, 1.08; 95% CI, 1.00-1.17). These patterns appeared stronger among Black participants (eg, substantial weight gain in poverty concentration group: OR, 1.10 [95% CI, 1.00-1.22]; in growth group: OR, 0.76 [95% CI, 0.56-1.02]) compared with White participants (eg, substantial weight gain in poverty concentration group: OR, 1.03 [95% CI, 0.90-1.18]; in growth group: OR, 0.84 [95% CI, 0.52-1.36]). Differences in patterns were also observed among men (eg, substantial weight gain in poverty concentration group: OR, 1.02 [95% CI, 0.88-1.17]; in growth group: OR, 0.58 [95% CI, 0.35-0.96]) compared with women (eg, substantial weight gain in poverty concentration group: OR, 1.12 [95% CI, 1.02-1.23]; in growth group: OR, 0.83 [95% CI, 0.62-1.12]). However, none of the interaction terms between Black vs White participants and men vs women were statistically significant. Neighborhood trajectory was not associated with substantial weight loss (poverty concentration group: OR, 1.00 [95% CI, 0.93-1.09]; abandonment group: OR, 1.01 [95% CI, 0.84-1.15]; displacement group: OR, 1.04 [95% CI, 0.83-1.23]; growth group: OR, 0.88 [95% CI, 0.69-1.12]). Conclusions and Relevance: In this cohort study, neighborhood economic trajectories were associated with weight gain. These findings highlight the importance of using more nuanced and multidimensional measures of neighborhood change in public health research..