Popp Collin J, Wang Chan, Berube Lauren, Curran Margaret, Hu Lu, Pompeii Mary Lou, Barua Souptik, Li Huilin, St-Jules David E, Schoenthaler Antoinette, Segal Eran, Bergman Michael, Sevick Mary Ann
Department of Population Health, New York University Langone Health, 180 Madison Ave, New York, NY 10016, USA.
Public Health Nutrition Program, Department of Epidemiology, NYU School of Global Public Health, 708 Broadway, New York, NY 10003, USA.
Nutrients. 2025 Jun 30;17(13):2178. doi: 10.3390/nu17132178.
: 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. : 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 () or a personalized nutrition diet leveraging a machine learning algorithm (). 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. : A total of 155 participants (: n = 84 vs. : 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/m). In both arms, higher baseline self-efficacy for weight loss was a predictor of weight-loss success. Participants with a higher BMI ( < 0.0001) in the arm and those who were older ( < 0.0001) in the arm were more likely to achieve successful weight loss. : Future weight-loss interventions may consider providing tailored behavioral support for individuals based on weight-loss self-efficacy, BMI, and age.
这项二次分析的目的是确定在个性化营养干预中与更高减肥成功率相关的基线特征。对一项为期6个月的行为咨询随机临床试验中葡萄糖代谢异常和肥胖的成年人的数据进行了分析。参与者被随机分为两种热量限制饮食:低脂饮食()或利用机器学习算法的个性化营养饮食()。分别使用梯度提升机方法,通过重复100次的五折交叉验证,确定每个研究组中预测6个月时成功减肥(≥5%)的基线变量(即年龄、减肥自我效能)。共有155名参与者(:n = 84 vs. :n = 71)提供了数据(均值[标准差]:年龄,59 [10]岁;66.5%为女性;56.1%为白人;体重指数(BMI),33.4 [4.6] kg/m)。在两个组中,更高的减肥基线自我效能是减肥成功的一个预测因素。组中BMI较高的参与者(< 0.0001)和组中年龄较大的参与者(< 0.0001)更有可能实现成功减肥。未来的减肥干预措施可能会考虑根据减肥自我效能、BMI和年龄为个体提供量身定制的行为支持。