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Updated: May 16, 2026

Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
BMI growth channel transitions predict underweight and overweight outcomes in young adults
Mariane Helen De Oliveira1, Iolanda Karla Santana Dos Santos2, Camila Medeiros da Silva Mazzeti3
1Boston College, School of Social Work, Chestnut Hill, MA, USA.
Abstract:
This study examined the association between transitions in BMI growth channel (BMI-GC) and the odds of underweight and overweight in young adulthood. Data were drawn from 2,759 participants in the Young Lives study (YL) and 2,782 participants in the National Longitudinal Survey of Youth 1997 (NLSY97). Normal Weight (NW) subsamples, consisting of 1,922 participants from YL and 1,477 from NLSY97, were selected for sensitivity analyses. Individual BMI-GC trajectories were estimated using linear mixed-effects models, and classified into four groups: Stable, Crossing Upwards, Crossing Downwards, and Fluctuating. Associations between BMI-GC groups and underweight and overweight at age 22 were assessed using logistic regression models. Compared to the Stable group, participants in the Crossing Downwards group had higher odds of being underweight in YL (OR: 2.62; 95%CI: 1.95-3.54), whereas those in the Crossing Upwards group had higher odds of overweight in YL (OR: 3.96 (95%CI: 2.61-5.99)) and in NLSY97 (OR: 2.55 (95%CI: 1.95-3.33)). In sensitivity analysis (NW subsamples), Crossing Downwards remained associated with underweight in YL (OR: 1.75; 95%CI: 1.23-2.48), and Crossing Upwards remained associated with overweight in both cohorts (OR: 1.95; 95%CI: 1.14-3.34 in YL and OR: 1.67; 95%CI: 1.00-2.78 in NLSY97). Crossing BMI-GC was associated with both underweight and overweight outcomes, including among participants with normal weight during childhood and adolescence. These findings highlight the importance of BMI-GC in weight assessments, offering a more nuanced understanding of growth trajectories and emphasizing the need to move beyond BMI categories alone to predict long-term nutritional risks.
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