Global studies of the impact of maternal obesity on child gut microbiota: a bibliometric analysis (2010–2026)

Introduction Maternal overweight/obesity and excessive weight gain during pregnancy are increasingly studied in relation to the offspring's gut microbiota. However, the bibliometric structure and thematic development of this area have not been sufficiently characterized. The aim of this study was to map publication dynamics, scientific impact, collaboration patterns, and conceptual themes in the literature. Methods A literature search was conducted in the Scopus and Web of Science Core Collection databases through June 14, 2026. After filtering by document type and language, 408 records were exported. In EndNote, 168 duplicates were removed, leaving 240 unique records for screening. 89 publications met the selection criteria. Bibliometric analysis was conducted using Bibliometrics 5.5.0 and Biblioshiny in R 4.6.0. Author Keywords were aligned using a stop-word list and a thesaurus, and co-occurrence, thematic mapping, Trend Topics, and multiple correspondence analysis were performed. Results The final corpus included 89 papers published between 2010 and 2026, drawn from 66 sources, comprising 41 articles and 48 reviews. The annual growth rate was 10.58%, and the international co-authorship rate was 23.6%. Keyword analysis identified three main co-occurrence clusters, encompassing maternal obesity, the pregnancy/newborn microbiome, and feeding/delivery-related factors. The thematic map highlighted maternal obesity–microbiome–newborn and infant gut microbiota–early life as core themes, and breastfeeding–delivery mode–cesarean section as a well-developed theme. The Multiple Correspondence Analysis (MCA) revealed four conceptual groups: maternal obesity and early development, nutrition, mode of delivery, and methodological/anthropometric factors. Conclusion The field of research is expanding but remains thematically heterogeneous. Future studies should prioritize standardized longitudinal designs, repeated microbiome sampling, multi-omics approaches, and interventional studies with adequate statistical power. These results provide a basis for determining future research priorities without inferring causal or clinical effects.