Baseline Characteristics of Weight-Loss Success in a Personalized Nutrition Intervention: A Secondary Analysis

Background/Objectives: The aim of this secondary analysis is to determine the baseline characteristics that are associated with a higher likelihood of weight-loss success in a personalized nutrition intervention. Methods: Data were analyzed in adults with abnormal glucose metabolism and obesity from a 6-month behavioral counseling randomized clinical trial. Participants were randomized to two calorie-restricted diets: a low-fat diet (Standardized) or a personalized nutrition diet leveraging a machine learning algorithm (Personalized). The gradient boosting machine method was used to determine the baseline variables (i.e., age, weight-loss self-efficacy) that predicted successful weight loss (≥5%) at 6 months in each study arm separately, using repeated five-fold cross-validation with 100 repetitions. Results: A total of 155 participants (Personalized: n = 84 vs. Standardized: n = 71) contributed data (mean [standard deviation]: age, 59 [10] y; 66.5% female; 56.1% White; body mass index (BMI), 33.4 [4.6] kg/m²). In both arms, higher baseline self-efficacy for weight loss was a predictor of weight-loss success. Participants with a higher BMI (p < 0.0001) in the Standardized arm and those who were older (p < 0.0001) in the Personalized arm were more likely to achieve successful weight loss. Conclusions: Future weight-loss interventions may consider providing tailored behavioral support for individuals based on weight-loss self-efficacy, BMI, and age.