ArticleHealth technology assessment (Winchester, England)2025
Dismantling behavioural weight management interventions: component network meta-analysis of randomised controlled trials and real-world services.
Article in Health technology assessment (Winchester, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Behavioural weight management interventions are complex interventions having several coexisting components designed to facilitate weight loss. Existing evidence has shown behavioural weight management interventions to be effective; however, the magnitude of weight loss varies among programmes. There is value in understanding whether differences in the intervention components influence the overall effectiveness of the interventions. The current study is the first attempt to explore the effects of individual components of interventions using data from both randomised controlled trials and real-world services based in the United Kingdom. Objective: To deconstruct behavioural weight management interventions into constituent components and identify the effectiveness of individual components for weight loss. Design: A component network meta-analysis of data from randomised controlled trials and real-world services. Setting: Real-world services and randomised controlled trials based in the United Kingdom for weight management in adults. Participants: Adults over 18 years of age, living in the United Kingdom and attending behavioural weight management interventions in the real world ( Main outcome measure: Mean change in weight after 12 weeks of active weight loss sessions. Methods: Bayesian two-staged component network meta-analysis using an additive model. Results: In the analysis of randomised controlled trials, significant weight loss was associated with components tailoring (mean difference -5.54 kg; 95% credible interval -7.72 to -3.35), flexibility in attendance (mean difference -3.18 kg; 95% credible interval -4.29 to -2.07) and multimodal referral (mean difference -2.57 kg; 95% credible interval -4.89 to -0.25). In real-world services, the components associated with significant weight loss included multimodal referral (mean difference -2.01, 95% credible interval -2.13 to -1.88), personalised dietary advice (mean difference -1.22, 95% credible interval -1.33 to -1.11), flexibility (mean difference -0.41, 95% credible interval -0.47 to -0.35) and in-person delivery (mean difference -0.45, 95% credible interval -0.52 to -0.38). However, co-design (mean difference 3.46 kg; 95% credible interval 2.12 to 4.82) in randomised controlled trials, and added extras (mean difference 0.99 kg; 95% credible interval 0.88 to 1.10) and tailoring (mean difference 0.33 kg; 95% credible interval 0.27 to 0.40) in real-world services, were not shown to be effective in short-term weight loss. Conclusions: The findings from this study highlight the importance of understanding the impact of intervention components such as accessibility, flexibility, tailoring and dietary advice and in-person delivery in weight loss at 12 weeks. Future research should consider exploring the component interactions and long-term weight loss for improved understanding and developing effective programmes. Funding: This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number NIHR129523.
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