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Bariatric Surgery

Predictors of weight loss after bariatric surgery—a cross-disciplinary approach combining physiological, social, and psychological measures

Abstract

Background

Bariatric surgery leads to a substantial weight loss (WL), however, a subset of patients undergoing surgery fails to achieve adequate WL. The reason for the individual variation in WL remains unexplained. Using an exploratory cross-disciplinary approach, we aimed to identify preoperative and early postoperative factors explaining the variation in WL after bariatric surgery.

Methods

Sixty-one subjects were recruited. Eighteen subjects did not receive surgery and three subjects dropped out, leaving a total sample of 40 subjects. Physiological, social, and psychological data were collected before and 6 months after surgery. All variables were analyzed in combination using a least absolute shrinkage and selection operator (LASSO) regression to explain the variation in WL 18 months after Roux-en-Y gastric bypass (n = 30) and sleeve gastrectomy (n = 10).

Results

Mean WL was 31% (range: 10–52%). The following preoperative factors predicted 59% of the variation in WL: type of surgery (14%), diabetes status (12%), economic resources (9%), sex (7%), binge eating disorder (7%), degree of depression (5%), household type (3%), and physical activity (1%). Including information on early responses after surgery increased the ability to predict WL to 78% and was explained by early WL (47%), changes in energy density of food consumed from a buffet meal (9%), changes in glicentin (5%), degree of depression (5%), sex (5%), type of surgery (2%), economic resources (2%), and changes in drive for thinness (1%).

Conclusions

Using a cross-disciplinary approach, a substantial part of the individual variation in WL was explained by a combination of basic patient characteristics, psychological profile, and social conditions as well as physiological, psychological and behavioral responses to surgery. These results suggest that patient characteristics collected in a cross-disciplinary approach may help determine predictors for less successful WL after bariatric surgery. If verified in larger cohorts this may form the basis for individualized postoperative support to optimize WL outcome.

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Fig. 1: Overview of the study design.
Fig. 2: Weight loss 18 months after bariatric surgery.

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Acknowledgements

We wish to thank the staff at Bariatric Clinic, Køge Hospital, Denmark, the kitchen and laboratory staff and master’s students at the Department of Nutrition, Exercise and Sports, University of Copenhagen, Denmark, and Eva Pacini at the Department of Psychology, University of Copenhagen, Denmark, for helping with recruitment and data collection. Furthermore, we wish to thank Lene Stevner at the Department of Nutrition, Exercise and Sports, University of Copenhagen, for support with the protocol. A special thanks to all the participants in the GO Bypass study.

Funding

This study was carried out as part of the research program “Governing Obesity” funded by the University of Copenhagen Excellence Programme for Interdisciplinary Research (www.go.ku.dk). Additional funding was obtained from the Danish Diabetes Academy supported by the Novo Nordisk Foundation, the Lundbeck Foundation, and the Aase and Ejnar Danielsens Foundation.

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Correspondence to Anders Sjödin.

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Conflict of interest

CWlR is supported by grants from Science Foundation Ireland (ref. 12/YI/B2480), Health Research Board (USIRL-2016–2), and the Irish Research Council during the conduct of the study. Furthermore, CWlR reported being on the advisory boards for Novo Nordisk and GI Dynamics, receiving a research grant from AnaBio, receiving honoraria for lectures and advisory work from Eli Lily, Johnson and Johnson, Sanofi Aventis, Astra Zeneca, Janssen, Bristol-Myers Squibb, and Boehringer-Ingelheim, and reported shares in Keyron. The other authors have declared that no conflict of interest exists.

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Nielsen, M.S., Christensen, B.J., Schmidt, J.B. et al. Predictors of weight loss after bariatric surgery—a cross-disciplinary approach combining physiological, social, and psychological measures. Int J Obes 44, 2291–2302 (2020). https://doi.org/10.1038/s41366-020-0576-9

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