Patterns of Weight Change Trajectories and Treatment Response in an Integrated Adult Primary Care Weight Management Practice

Anita Ganti; Shanna Tucker; Afua Takyi; Musarrat Nahid; Alexa Bickhart; Debra Katz-Feigenbaum; Erica Phillips

doi:10.1002/osp4.70045

Patterns of Weight Change Trajectories and Treatment Response in an Integrated Adult Primary Care Weight Management Practice

Obes Sci Pract. 2025 Jan 13;11(1):e70045. doi: 10.1002/osp4.70045. eCollection 2025 Feb.

Authors

Anita Ganti¹, Shanna Tucker², Afua Takyi³, Musarrat Nahid¹, Alexa Bickhart⁴, Debra Katz-Feigenbaum⁴, Erica Phillips¹

Affiliations

¹ Division of General Internal Medicine Weill Cornell Medicine New York New York USA.
² Department of Medicine NYU Grossman School of Medicine New York New York USA.
³ Comprehensive Weight Control Center Weill Cornell Medicine New York New York USA.
⁴ Outpatient Nutrition, Diabetes Education and Breastfeeding Support Services NewYork-Presbyterian Hospital New York New York USA.

Abstract

Introduction: Given the significant interindividual variable responses to interventions for obesity, the early identification of factors associated with a differential in weight loss would benefit real-world approaches in clinical practice.

Objective: This study evaluated the factors associated with individual variability in response to enrolling in a weight management program integrated into an academic-based primary care practice.

Methods: Data were retrospectively collected and analyzed for patients referred to a primary care-based weight management practice between 2012 and 2020. A mixed-model, semi-parametric group-based modeling approach was used to identify group membership and explore weight change trajectories over 18 months, as measured by the percent of initial body weight loss and the probability of losing at least 5% of initial body weight (IBW).

Results: Three hundred ninety-three patients were included in the study; the median age was 53 years, 84% female, 40% self-identified as non-Hispanic Black, and about one-third white. Among those, 374 had sufficient follow-up data for group-based modeling. Four groups were identified and named: "Weight Gainers" added 1.3% of IBW; "Initial Resistors" lost 6.7% of IBW; "Early Maintainers" lost 7.1% of IBW; and "Steady Achievers" lost 15% of IBW. Weight change in all groups was over 18 months. The probability of losing 5% IBW was described by three groups: "Minimal Late Responders," "Moderate Responders," and "High Early Responders." Younger age, non-Hispanic Black race, fewer follow-up visits, and lower proportion prescribed two or more anti-obesity medications (AOMs) simultaneously were associated with a lower probability of achieving 5% IBW.

Conclusions: Compared to the other groups, Weight Gainers and Minimal Late Responders had a distinct trajectory associated with two modifiable factors: the number of treatment visits and AOMs. Tailored interventions targeting these factors early may increase the probability of meaningful weight loss.