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

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.