Global Trends in Bariatric Surgery for the Treatment of Metabolic Syndrome: A Bibliometric and Visualization Analysis
摘要
Metabolic syndrome (MetS) is characterized by a cluster of cardiovascular risk factors, including central obesity, insulin resistance, hypertension, and dyslipidemia. Since Reaven first proposed the concept of “Syndrome X,” despite slight variations in diagnostic criteria among organizations such as the WHO, IDF, and NCEP-ATP III, central obesity has been consistently regarded as a core diagnostic component. Bariatric surgery is an effective intervention for the treatment of refractory obesity, with commonly performed procedures including Roux-en-Y gastric bypass (RYGB), adjustable gastric banding (AGB), sleeve gastrectomy (SG), and biliopancreatic diversion (BPD). Studies have demonstrated that bariatric surgery improves insulin resistance, secretory function, and glucose metabolism—thereby alleviating symptoms of metabolic syndrome—through both weight-dependent and weight-independent mechanisms acting on multiple tissues, including the gut and liver. With the rising prevalence of obesity, the significant role of bariatric surgery in improving obesity and metabolic syndrome has garnered increasing research attention, reflected by the annual growth in related publications.
MethodsBased on the Web of Science database, this study employed bibliometric and visualization analyses using VOSviewer and CiteSpace software to systematically examine the global research trends, hot topics, and knowledge structure related to bariatric surgery and metabolic syndrome from January 2014 to March 2025.
ObjectiveTo elucidate the developmental dynamics and emerging frontiers in this field, providing theoretical insights and decision-making support for future research.
ConclusionGlobal research on bariatric surgery and metabolic syndrome has been increasing, with a gradual shift from surgical outcomes toward metabolic mechanisms and personalized treatments. Key research hotspots include gut hormones, bile acids, and microbiota, while emerging trends focus on long-term management and AI-based prediction. This study provides a comprehensive overview that may inform future research directions and support evidence-based clinical decision-making. This study was limited by the use of a single database (Web of Science) and a restricted time frame.