Traditional pairwise meta-analysis (PMA) is a very useful method that pools evidence from one study design type if appropriate; its widespread use in nutrition research is an important phenomenon. Recently, a promising method for more advanced evidence-synthesis, called network meta-analysis (NMA), was introduced. NMA is an extension of PMA that enables simultaneous comparison of multiple interventions. NMA combines direct evidence (i.e., trials comparing 2 interventions directly) and indirect evidence (i.e., from a connected route via ≥1 comparators, e.g. placebo) in a network of studies. NMAs have the potential to advance knowledge in the field of nutrition as they provide insights that cannot be obtained by individual 2-arm randomized controlled trials or PMA. Thus, in this perspective paper, we aim to summarize the current (methodologic) status of published NMAs in nutrition research and emphasize advances and strengths in comparison with traditional PMA through specific examples, and highlight potential pitfalls and limitations. NMA is an emerging methodology in the field of nutrition research. A PubMed search identified only 23 nutrition research-related NMAs published since the inception of journals up to January 8, 2019 (61% of them published since 2017), compared with >5000 published PMAs. Moreover, we aim to highlight the scientific concepts and standards through the use of the following NMA example: "Which type of oils/solid fats offers the greatest impact on blood lipids?" In this regard, we discuss intervention definitions, transitivity/similarity, statistical methods, description and visualization of results, inconsistency, ranking, dissemination bias, assessing the certainty of evidence by Grading of Recommendations Assessment, Development and Evaluation, and reporting guidelines. We expect that rigorously conducted NMAs based on high-quality systematic reviews will become the new evidence synthesis benchmark in nutrition research. However, caution is warranted because abuse and misinterpretations of PMA and NMA findings could hamper the scientific field and possibly decision-making regarding public policy.