Application of Network Meta-Analysis in The Field of Physical Activity and Health Promotion: A Case Study

Abstract

Continued advancement in the field of kinesiology and health promotion relies heavily on the synthesis of rigorous quantitative scientific evidence. As such, meta-analyses of randomized controlled trials have led to a better understanding of what intervention strategies are superior (i.e., produce the greatest effects) in physical activity-based health behavior change interventions. Indeed, standard meta-analytic approaches have allowed researchers in the field to synthesize relevant experimental evidence using pairwise procedures which produce reliable estimates of the homogeneity, magnitude, and potential biases in the observed effects. However, pairwise meta-analytic procedures are only capable to discerning differences in effects between a select intervention strategy and a select comparison condition or control condition. In order to maximize the impact of physical activity interventions on health-related outcomes, it is necessary to establish evidence concerning the comparative efficacy of all relevant physical activity intervention strategies. The development of network meta-analysis (NMA)—most commonly used in medical-based clinical trials—has allowed for the quantification of indirect comparisons, even in the absence of direct, head-to-head trials. Thus, it stands to reason that NMA can be applied in the physical activity and health promotion research to identify the best intervention strategies. Given this analysis technique is novel and largely unexplored in the field of kinesiology and health promotion, care must be taken in its application to ensure reliable estimates and discernment of the effect sizes between interventions. Therefore, the purpose of this study is to first comment on the potential application and importance of NMA in the field of kinesiology and health promotion, then describe how to properly and effectively apply this technique using a specific case study evaluating the effects of different lifestyle interventions on children’s body composition, and lastly suggest important considerations for its appropriate application in this field. In this paper, overviews of the foundations of NMA and commonly used approaches for conducting NMA are provided, followed by assumptions of NMA, opportunities and challenges in NMA, and a case study example of the development and conduct of an NMA, as well as the interpretation of the analysis results. The case study collect original data from published randomized controlled studies investigating on some type of intervention on variables including body mass index (BMI), BMI z-score (BMIz), and body fat percentage, divided the used intervention into ten categories in total, from simple single intervention to multiple components mixed intervention (more than three), and used pre-processed data to carry out network meta-analysis. Results of analysis using mean difference (SD) between baseline and immediate post-intervention data showed that PA intervention ranked top two of the most effective approaches among other types of lifestyle interventions in all three variables, suggesting that promoting PA participation is crucial in children’s health status and childhood obesity control. While based on the analysis using combined original pre-and-post data (SE), multiple component interventions were predicted to be the best ranked intervention approach among all ten types of intervention, indicating that taking care of more aspects in children’s lifestyle may also result in an important impact for children to keep healthy and fit.