Cleland, V and Tian, J and Buscot, M-J and Magnussen, C and Bazzano, LA and Burns, TL and Daniels, SR and Dwyer, T and Jacobs, DR and Juonala, M and Prineas, RJ and Raitakari, O and Sinaiko, AR and Steinberger, J and Urbina, EM and Woo, JG and Venn, AJ, Body mass index trajectories from childhood to adulthood: Evidence from the International Childhood Cardiovascular Cohort (i3C) Consortium, Circulation, pp. 1, Vol 139 (Suppl_1). ISSN 0009-7322 (2019) [Conference Extract]
Methods: Data were from 12,086 participants (45% male) from four cohorts established in Australia, Finland and the US. Participants had ≥3 measures of height and weight, including ≥1 in childhood (6-18 years, mean 9.7 to 11.1 years at first visit) and ≥1 in adulthood (mean 40.0 to 50.9 years at last visit). Latent Class Growth Mixture Modelling estimated BMI trajectory groups. Correlates (age, gender, race, parental education) of BMI trajectories were identified with log multinomial regression.
Results: Mean BMI ranged from 17.8-18.3 kg/m2 at first visit and 26.4-30.2 kg/m2 at last visit. Six BMI trajectories (Figure) were identified in three cohorts: persistently normal (48-57% of participants), improving from high (1-2%), progressing to overweight (30-39%), progressing to obese (1-8%), late onset obese (2-6%), and progressing to severe obesity (1-3%). One cohort had a seventh group: greatly improving (<1%). Women were less likely to progress to overweight and more likely to progress to obese than men. Black participants were at greater risk of progressing to obesity, severe obesity and late onset obesity than white participants. Improving from high BMI was associated with being younger at first visit and lower parental education.
Conclusion: Similar BMI trajectories were identified across cohorts, countries and time, despite different BMI distributions. Females and black Americans were most likely to be of high BMI at the end of follow-up. Few participants (≤2%) improved from high BMI. A better understanding of the factors that influence the highest and improving BMI trajectories may help identify risk reduction strategies.
|Item Type:||Conference Extract|
|Keywords:||obesity, weight, trajectory|
|Research Division:||Biomedical and Clinical Sciences|
|Research Group:||Cardiovascular medicine and haematology|
|Research Field:||Cardiology (incl. cardiovascular diseases)|
|Objective Group:||Evaluation of health and support services|
|Objective Field:||Health inequalities|
|UTAS Author:||Cleland, V (Associate Professor Verity Cleland)|
|UTAS Author:||Tian, J (Dr Jing Tian)|
|UTAS Author:||Buscot, M-J (Dr Marie-Jeanne Buscot)|
|UTAS Author:||Magnussen, C (Associate Professor Costan Magnussen)|
|UTAS Author:||Venn, AJ (Professor Alison Venn)|
|Web of Science® Times Cited:||1|
|Deposited By:||Menzies Institute for Medical Research|
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