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Content

Short-term weight trajectories and long-term weight outcomes from a lifestyle intervention in real-world clinical practice.

Description

Romanelli RJ, Sudat S, Huang Q, Ma J, Venditti EM, Greenwood DA, Pressman AR, Azar KMJ., Transl Behav Med. pii: ibz118. doi: 10.1093/tbm/ibz118. [Epub ahead of print], 2019 Aug 01

Investigators

Kristen Azar, R.N., BSN, MSN/MPH, Investigator, Sylvia Sudat, PhD

Abstract

Centers for Disease Control and Prevention aligned lifestyle change programs are effective in promoting weight loss among those with elevated cardiometabolic risk; yet, variability in weight outcomes among participants is high. Little is known about heterogeneity of short-term weight changes among participants in real-world clinical practice.

We sought to identify short-term weight trajectory clusters among lifestyle change program participants in real-world clinical practice and to examine the relationship between cluster membership and long-term weight outcomes.

We identified participants from the electronic health records (2010-2017) with weight measured ≤30 days prior to program initiation (baseline) and in four intervals (3-week segments) in the 12 weeks after baseline. Clustering analysis was performed to identify distinct trajectories in percent weight change over 12 weeks. Cluster-specific differences in weight change at 12 and 52 weeks were assessed.

Among 1,148 participants, across 18 clinic sites, three clusters were identified: minimal-to-no weight loss (MWL), delayed-minimal weight loss (DWL), and steady-moderate weight loss (SWL), corresponding to mean weight changes of 0.4%, -2.3%, and -4.8% at 12 weeks follow-up, respectively. Mean weight changes were 0.4%, -1.8%, and -5.1% for MWL, DWL, and SWL clusters, respectively, at 52 weeks follow-up, which correlated in direction and magnitude with short-term weight changes.

Clustering analysis reveals heterogeneous, short-term weight trajectories among lifestyle change program participants in real-world clinical practice. Given the relationship between the magnitudes of short- and long-term weight change, individual participant weight trajectories may be useful in identifying potential non-responders in need of adjunctive or alternative therapy.

Pubmed Abstract

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Associated Topics

  • Diabetes, Insulin Resistance and Metabolic Syndrome
  • Medical Informatics
  • Obesity

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