Application of Latent Class Analysis to Identify Behavioral Patterns of Response to Behavioral Lifestyle Interventions in Overweight and Obese Adults.
Sommaire de l'article
Examining responders and non-responders to behavioral lifestyle interventions among overweight/obese adults with additional comorbidities may aid in refining and tailoring obesity treatment.
The purpose of this study is to demonstrate the use of latent class analysis to identify patterns of response to behavioral lifestyle interventions based on adherence to diet and exercise recommendations.
Repeated measures latent class analysis was applied to two clinical trial datasets, combination of two active interventions in the PREMIER Trial (n = 501) and phase 1 of the Weight Loss Maintenance Trial (WLM; n = 1685), to identify patterns of response to behavioral lifestyle interventions. Treatment response was based on adherence to daily recommendations for fruit/vegetable, fat, saturated fat, sodium, and exercise at baseline and 6 months.
In PREMIER, three distinct latent classes emerged: responders (45.9 %), non-responders (23.6 %), and early adherers (30.5 %). Responders and Early Adherers had greater weight loss at 6 and 18 months and were more likely to meet behavioral recommendations at 18 months than Non-responders. For WLM, there were four latent classes: partial responders (16 %), non-responders (40 %), early adherers (2 %), and fruit/veggie only responders (41 %). Non-responders in WLM had significantly less weight loss at 6 months compared to that of the other three latent classes.
Latent class analysis is a useful method to apply to clinical trial data to identify distinct patterns of response to behavioral interventions. Overweight/ obese participants who respond to behavioral lifestyle treatment (i.e., meet behavioral recommendations) have significantly greater weight loss than that of participants who do not make behavioral changes.