Body-mass index trajectories from childhood to mid-adulthood and their sociodemographic predictors: Evidence from the International Childhood Cardiovascular Cohort (i3C) Consortium. (June 2022)

• Record Type: Journal Article
• Authors: Cleland, Verity; Tian, Jing; Buscot, Marie-Jeanne; Magnussen, Costan G.; Bazzano, Lydia; Burns, Trudy L.; Daniels, Stephen; Dwyer, Terence; Hutri-Kahonen, Nina; Ikonen, Johanna; Jacobs, David; Juonala, Markus; Prineas, Ronald; Raitakari, Olli; Sinaiko, Alan; Steinberger, Julia; Urbina, Elaine M.; Woo, Jessica G.; Venn, Alison
• Is Part Of: EClinicalMedicine. Volume 48(2022)
• Publication Date: 2022-06
• Subjects: Body mass index -- Trajectory -- Childhood -- Adulthood -- Cohort study -- Predictor; Medicine -- Research -- Periodicals; Medical policy -- Periodicals; Clinical Medicine; Health Policy; Public Health; Medical policy; Medicine -- Research; Periodical; Electronic journals; Periodicals; 613
• DOI: 10.1016/j.eclinm.2022.101440
• Languages: English
• ISSNs: 2589-5370

Abstract

Summary: Background: Understanding lifecourse trajectories of body-mass index (BMI) is important for identifying groups at high risk of poor health and potential target points for intervention. This study aimed to describe BMI trajectories from childhood to mid-adulthood in four population-based cohorts established in the 1970s and 1980s and to identify childhood sociodemographic factors related to trajectory membership. Methods: Between Dec 17, 1970 and Dec 15, 1994, data were collected at the first visit from 9830 participants from the International Childhood Cardiovascular Cohort (i3C) Consortium, which includes participants from Australia (1985), Finland (1980) and the USA (1970–1994). Participants had at least three measures of height and weight, including one in childhood (6–18 years) and one in adulthood (>18 years), and were aged 30–49 years at last measurement. Latent Class Growth Mixture Modelling was used to identify lifecourse BMI trajectory groups and log multinomial regression models were fit to identify their childhood sociodemographic predictors. Findings: Five consistent BMI trajectory groups were identified amongst the four cohorts: persistently low (35.9–58.6%), improving from high (0.7–4.8%), progressing to moderate (9.3–43.7%), progressing to high (1.1–6.0%), and progressing to very high (0.7–1.3%). An additional three BMI trajectory groups were identified in some, but not all, cohorts: adult onset high (three cohorts; 1.8–20.7%), progressing to moderate-high (two cohorts; 5.2–13.8%), and relapsing yo-yoers (alternating upward and downward; one cohort; 1.3%). In pooled analyses, each predictor variable in childhood, including age, gender, parental education and race, was associated with increased likelihood of belonging to the most (e.g., improving from high) and least (e.g., progressing to very high) favourable BMI trajectory groups, suggesting a U-shaped (or inverse U-shaped) pattern of association. Interpretation: Five consistent BMI trajectory groups were identified across four cohorts from Australia, Finland, and the USA, mainly across two eras of birth. While most participants remained on a persistently low trajectory (50%), many demonstrated worsening BMI trajectories (47%), with only few demonstrating improving trajectories (<5%). Age, gender, parental education, and race appear to be important predictors of BMI trajectory group membership and need consideration in preventive and management strategies. Funding: This study was supported by funding from the National Institutes of Health, National Heart, Lung and Blood Institute (grant number R01 HL121230).