Abstract
Background/Objectives:
Dietary weight loss interventions have heterogeneous outcomes in long-term studies, with many participants regaining part or all of the lost weight. Growth mixture modelling is a novel analytic approach that can be used to identify different trajectories of weight change during a trial rather than focussing on the total amount of weight lost.
Subjects/Methods:
Data were pooled from two 12-month dietary weight loss studies where no significant difference was detected between the treatment and control arms, thus allowing analysis independent of treatment. The data set included 231 subjects (74.5% female), with a mean weight loss of 6.40 kg (4.96). Growth mixture models were used to identify participants with similar trajectories of change in body mass index (BMI).
Results:
Three subgroups were identified. A rapid and continuing BMI loss over the study period (rapid, n=53), a rapid initial weight loss in the first 3 months with a slowing rate over the remaining 9 months (maintainers, n=146) and those with an initial loss trajectory, which slowed and began to increase at 9 months (recidivists, n=53). Age (s.d.) and BMI (s.d.) were significantly different between the three groups (rapid 53 years (7), 28.99 kg/m2 (3.30); maintainers 47 years (9), 30.90 kg/m2 (2.95); recidivists 44 years (7), 34.84 kg/m2 (1.92), both P<0.001).
Conclusions:
Older subjects with lower BMIs were more likely to have a rapid and continuing weight loss in a 1-year dietary-based weight loss intervention. Different interventional approaches may be necessary for different ages and baseline BMIs and stratification prior to randomisation may be necessary to prevent confounding in weight loss trials.
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Acknowledgements
Funding for the studies was provided by the Australian National Health and Medical Research Council (Project Grant Number 514631) and by Horticulture Australia Limited using the vegetable levy and matched funding from the Australian Government.
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Batterham, M., Tapsell, L. & Charlton, K. Baseline characteristics associated with different BMI trajectories in weight loss trials: a case for better targeting of interventions. Eur J Clin Nutr 70, 207–211 (2016). https://doi.org/10.1038/ejcn.2015.45
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DOI: https://doi.org/10.1038/ejcn.2015.45
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