A review of the scope of BMI latent class trajectory analysis in children and adolescents

Abstract Objective To review the related research on latent class trajectory analysis (LCTA) of body mass index (BMI) in children and adolescents, and to clarify the LCTA of BMI method, evaluation index, change trajectory and related influencing factors, so as to provide basis for early weight management. Methods Based on the scoping review framework of Arksey and O'Malley, we systematically searched PubMed, Web of Science, Embase, The Cochrane Library, Chinese Biomedical Literature Database (CBM), Wanfang, VIP, and China National Knowledge Infrastructure (CNKI) from inception to June 17, 2025. Two researchers independently screened the literature and extracted information. Results A total of 24 articles were included, published from 2007 to 2025, with a median sample size of 1744 cases. Among the trajectory analysis methods, the group-based trajectory model (GBTM) was the most widely used (58.3%), followed by the growth mixture model (GMM) (25.0%). The main software platforms used were Mplus (29.2%), SAS (20.8%) and Stata (20.8%). In terms of model evaluation indicators, Bayesian Information Criterion (BIC) and Average Posterior Probability (Ave PP) are the most frequently used, accounting for 87.5% and 58.3% respectively. The number of BMI trajectories identified in the included studies ranged from 2 to 7, of which 4 trajectories were the most common (54.2%). Although there are differences in trajectory naming, most studies (> 80%) have identified a class of 'low-level-stable' normal weight trajectories as the main development type, accounting for about 40%-70% of the population. Conclusions Through trajectory recognition, the longitudinal trend of BMI can be displayed and relevant influencing factors can be identified. These findings may inform early weight management research and practice. Future research should further standardize the model evaluation criteria and reporting process to enhance the comparability between studies.

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Publication Details

Journal
Discover Pediatrics
Published
2026-10-09
DOI
https://doi.org/10.1007/s44571-026-00007-3
Primary Topic
Obesity, Physical Activity, Diet
Type
article
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article

A review of the scope of BMI latent class trajectory analysis in children and adolescents

Xiayan Yang, Yajiao Gu, Li Li, Diwen Yu
Discover Pediatrics
Obesity, Physical Activity, Diet
article

A review of the scope of BMI latent class trajectory analysis in children and adolescents

Xiayan Yang, Yajiao Gu, Li Li, Diwen Yu
article en

Abstract

Abstract Objective To review the related research on latent class trajectory analysis (LCTA) of body mass index (BMI) in children and adolescents, and to clarify the LCTA of BMI method, evaluation index, change trajectory and related influencing factors, so as to provide basis for early weight management. Methods Based on the scoping review framework of Arksey and O'Malley, we systematically searched PubMed, Web of Science, Embase, The Cochrane Library, Chinese Biomedical Literature Database (CBM), Wanfang, VIP, and China National Knowledge Infrastructure (CNKI) from inception to June 17, 2025. Two researchers independently screened the literature and extracted information. Results A total of 24 articles were included, published from 2007 to 2025, with a median sample size of 1744 cases. Among the trajectory analysis methods, the group-based trajectory model (GBTM) was the most widely used (58.3%), followed by the growth mixture model (GMM) (25.0%). The main software platforms used were Mplus (29.2%), SAS (20.8%) and Stata (20.8%). In terms of model evaluation indicators, Bayesian Information Criterion (BIC) and Average Posterior Probability (Ave PP) are the most frequently used, accounting for 87.5% and 58.3% respectively. The number of BMI trajectories identified in the included studies ranged from 2 to 7, of which 4 trajectories were the most common (54.2%). Although there are differences in trajectory naming, most studies (> 80%) have identified a class of 'low-level-stable' normal weight trajectories as the main development type, accounting for about 40%-70% of the population. Conclusions Through trajectory recognition, the longitudinal trend of BMI can be displayed and relevant influencing factors can be identified. These findings may inform early weight management research and practice. Future research should further standardize the model evaluation criteria and reporting process to enhance the comparability between studies.

Discover PediatricsVol. 1(1)
Hangzhou Normal University (CN), Affiliated Hospital of Hangzhou Normal University (CN)
Openalex Percentile: Top 10%
Obesity, Physical Activity, Diet
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A review of the scope of BMI latent class trajectory analysis in children and adolescents — Xiayan Yang, Yajiao Gu, et al. · Discover Pediatrics (2026) | TGRS Research Map | TGRS