Behavior, Psychology and Sociology

Weight variability during self-monitored weight loss predicts future weight loss outcome

Abstract

Background

Obesity treatments often do not produce long-term results. It is therefore critical to better understand biological and behavioral correlates or predictors of future weight change.

Objective

We tested the hypothesis that greater weight variability, independent of total body weight change, during early weight loss would predict degree of long-term success.

Subjects/Methods

We included 24,009 American users of the Withings smart scale with over a year’s worth of self-monitored weight data. Multilevel modeling was used to calculate weight variability as the root mean square error around participants’ weight trajectory regression line, using weekly average weights from the first 12 weeks of weight loss. Linear regressions were then used to examine whether weight variability predicted weight change from week 12 to week 48, 72, and 96.

Results

Greater weight variability predicted less weight loss/more weight regain at week 48 (b ± SE: 1.18 ± 0.17, p < 0.001), week 72 (b ± SE: 1.45 ± 0.21, p < 0.001), and week 96 (b ± SE: 1.45 ± 0.23, p < 0.001), controlling for baseline BMI and overall weight change during the first 12 weeks. An interaction effect was found between weight variability and baseline BMI such that the relationship between weight variability and later weight change was stronger in individuals with lower baseline BMI.

Conclusions

This study found that in a large population sample, weight variability early on during weight loss significantly predicted longer term weight loss outcomes. The results provide further support that weight variability be considered an important predictor of future weight change. Research is needed to understand the mechanisms underlying this effect.

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Fig. 1: Mean weight over time.
Fig. 2: Examples of individual regression curves used to calculate RMSE (weight variability), independent of weight trajectory.
Fig. 3: Baseline BMI significantly moderated the relationship between weight variability and future weight change from weeks 12 to 48.

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Acknowledgements

We would like to thank the Withings company, employees and users for sharing the data with us.

Disclosure

Dr. Wilkinson is an employee of Novo Nordisk Inc.

Author information

Correspondence to Leora Benson.

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The authors declare that they have no conflict of interest.

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Benson, L., Zhang, F., Espel-Huynh, H. et al. Weight variability during self-monitored weight loss predicts future weight loss outcome. Int J Obes (2020). https://doi.org/10.1038/s41366-020-0534-6

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