Differences in treatment response to a total diet replacement intervention versus a food-based intervention: A secondary analysis of the OPTIWIN trial

Quantifying the effect of nutritional interventions on metabolic resilience using personalized computational models

The manifestation of metabolic deteriorations that accompany overweight and obesity can differ greatly between individuals, giving rise to a highly heterogeneous population. This inter-individual variation can impede both the provision and assessment of nutritional interventions as multiple aspects of metabolic health should be considered at once. Here, we apply the Mixed Meal Model, a physiology-based computational model, to characterize an individual's metabolic health in silico. A population of 342 personalized models were generated using data for individuals with overweight and obesity from three independent intervention studies, demonstrating a strong relationship between the model-derived metric of insulin resistance (ρ = 0.67, p < 0.05) and the gold-standard hyperinsulinemic-euglycemic clamp. The model is also shown to quantify liver fat accumulation and β-cell functionality. Moreover, we show that personalized Mixed Meal Models can be used to evaluate the impact of a dietary intervention on multiple aspects of metabolic health at the individual level.

Health-Related Quality of Life in Weight Loss Interventions: Results from the OPTIWIN Trial

Obesity is highly prevalent and associated with several adverse outcomes including health-related quality-of-life (HRQoL), work productivity, and activity impairment. The objective of this study is to examine group differences in HRQoL and labor-related health outcomes among participants in the OPTIWIN program, which compared the effectiveness of two intensive behavioral weight loss interventions. Participants (n = 273) were randomized to OPTIFAST^®(OP) or food-based (FB) dietary interventions for 52 weeks. HRQoL and labor-related health outcomes were measured at baseline, week 26, and week 52, using two questionnaires. At baseline, there were no differences between groups on the Impact of Weight on Quality-of-Life Questionnaire (IWQOL-Lite). At week 26, the OP group had statistically significant differences towards better HRQoL for Physical Function, Self-Esteem, and the total score compared with the FB group. At week 52, the OP group showed better HRQoL in the total score (p = 0.0012) and in all but one domain. Moreover, the adjusted change-from-baseline normalized total score at week 52 was −5.9 points (p = 0.0001). Finally, the mean IWQOL-Lite normalized score showed that HRQoL improves by 0.4442 units (p < 0.0001) per kg lost, and that greater weight reduction was positively associated with better HRQoL. No statistically significant group differences were found with the Work Productivity and Activity Impairment (General Health) (WPAI-GH) Questionnaire. HRQoL improves with highly intensive, well-structured weight loss interventions. Greater weight loss lead to larger improvements. The lack of negative effect on productivity and activity suggests that these interventions may be compatible with an active work lifestyle.