Group‐based trajectory modeling of body mass index and body size over the life course: A scoping review. (29th September 2020)

• Record Type: Journal Article
• Authors: De Rubeis, Vanessa; Andreacchi, Alessandra T.; Sharpe, Isobel; Griffith, Lauren E.; Keown‐Stoneman, Charles D. G.; Anderson, Laura N.
• Is Part Of: Obesity science and practice. Volume 7:Number 1(2021)
• Page Start: 100
• Page End: 128
• Publication Date: 2020-09-29
• Subjects: body weight -- growth mixture modeling -- latent class growth analysis -- life course; Obesity -- Periodicals; 616.398005
• DOI: 10.1002/osp4.456
• Languages: English
• ISSNs: 2055-2238

Abstract

Abstract: Background: Group‐based trajectory modeling has been applied to identify distinct trajectories of growth across the life course. Objectives of this study were to describe the methodological approaches for group‐based modeling of growth across the life course and to summarize outcomes across studies. Methods: A scoping review with a systematic search of Medline, EMBASE, CINAL, and Web of Science was conducted. Studies that used a group‐based procedure to identify trajectories on any statistical software were included. Data were extracted on trajectory methodology, measures of growth, and association with outcomes. Results: A total of 59 studies were included, and most were published from 2013 to 2020. Body mass index was the most common measure of growth ( n = 43). The median number of identified trajectories was 4 (range: 2–9). PROC TRAJ in SAS was used by 33 studies, other procedures used include TRAJ in STATA, lcmm in R, and Mplus. Most studies evaluated associations between growth trajectories and chronic disease outcomes ( n = 22). Conclusions: Group‐based trajectory modeling of growth in adults is emerging in epidemiologic research, with four distinct trajectories observed somewhat consistently from all studies. Understanding life course growth trajectories may provide further insight for population health interventions.