Efficacy of behavioral interventions in managing gestational weight gain (GWG): A component network meta-analysis

Abstract

Objective: To identify the most effective behavioral components within lifestyle interventions to optimize gestational weight gain (GWG) to inform guidelines, policy and translation into healthcare. Methods: Behavioral components were identified from study level data of randomized antenatal lifestyle interventions using a behavioral taxonomy framework and analyzed using component network meta-analysis (NMA). The NMA ranked behavioral combinations hierarchically by efficacy of optimizing GWG. Direct and estimated indirect comparisons between study arms (i.e., control and intervention) and between different component combinations were estimated to evaluate component combinations associated with greater efficacy. Results: Overall, 32 studies with 11,066 participants were included. Each intervention contained between 3 and 7 behavioral components with 26 different behavioral combinations identified. The majority (n = 24) of combinations were associated with optimizing GWG, with standard mean differences (SMD) ranging from —1.01 kg (95% CI —1.64 to —0.37) and —0.07 kg (—0.38 to 0.24), compared with controls. The behavioral cluster identified as most effective, included components of goals, feedback and monitoring, natural consequences, comparison of outcomes, and shaping knowledge (SMD —1.01 kg [95% CI —1.64 to —0.37]). Conclusion: Findings support the application of goal setting, feedback and monitoring, natural consequences, comparison of outcomes, and shaping knowledge as essential, core components within lifestyle interventions to optimize gestational weight gain.