Insulin resistance and inflammation predict kinetic body weight changes in response to dietary weight loss and maintenance in overweight and obese subjects by using a Bayesian network approach

Am J Clin Nutr. 2013 Dec;98(6):1385-94. doi: 10.3945/ajcn.113.058099. Epub 2013 Oct 30.


Background: The ability to identify obese subjects who will lose weight in response to energy restriction is an important strategy in obesity treatment.

Objective: We aimed to identify obese subjects who would lose weight and maintain weight loss through 6 wk of energy restriction and 6 wk of weight maintenance.

Design: Fifty obese or overweight subjects underwent a 6-wk energy-restricted, high-protein diet followed by another 6 wk of weight maintenance. Network modeling by using combined biological, gut microbiota, and environmental factors was performed to identify predictors of weight trajectories.

Results: On the basis of body weight trajectories, 3 subject clusters were identified. Clusters A and B lost more weight during energy restriction. During the stabilization phase, cluster A continued to lose weight, whereas cluster B remained stable. Cluster C lost less and rapidly regained weight during the stabilization period. At baseline, cluster C had the highest plasma insulin, interleukin (IL)-6, adipose tissue inflammation (HAM56+ cells), and Lactobacillus/Leuconostoc/Pediococcus numbers in fecal samples. Weight regain after energy restriction correlated positively with insulin resistance (homeostasis model assessment of insulin resistance: r = 0.5, P = 0.0002) and inflammatory markers (IL-6; r = 0.43, P = 0.002) at baseline. The Bayesian network identified plasma insulin, IL-6, leukocyte number, and adipose tissue (HAM56) at baseline as predictors that were sufficient to characterize the 3 clusters. The prediction accuracy reached 75.5%.

Conclusion: The resistance to weight loss and proneness to weight regain could be predicted by the combination of high plasma insulin and inflammatory markers before dietary intervention.

Trial registration: NCT01314690.

Publication types

  • Clinical Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Antibodies, Monoclonal / metabolism
  • Bayes Theorem
  • Biomarkers / blood
  • Biomarkers / metabolism
  • Body Mass Index
  • Caloric Restriction*
  • Female
  • Humans
  • Insulin / blood
  • Insulin Resistance*
  • Interleukin-6 / blood
  • Kinetics
  • Leukocytes / immunology*
  • Male
  • Middle Aged
  • Obesity / diet therapy*
  • Obesity / immunology
  • Obesity / metabolism
  • Obesity / prevention & control
  • Overweight / diet therapy*
  • Overweight / immunology
  • Overweight / metabolism
  • Overweight / prevention & control
  • ROC Curve
  • Secondary Prevention
  • Subcutaneous Fat, Abdominal / immunology*
  • Subcutaneous Fat, Abdominal / metabolism
  • Weight Gain
  • Weight Loss


  • Antibodies, Monoclonal
  • Biomarkers
  • HAM-56 antibody
  • IL6 protein, human
  • Insulin
  • Interleukin-6

Associated data