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The association between metabolic–body mass index phenotype and risk of gastric cancer: A retrospective cohort study

Miguel VIEIRA and Maria Teresa SILVA

Obesity is a known risk factor for several cancers, but its association with gastric cancer (GC) remains inconsistent.We evaluated the association between metabolic–body mass index (BMI) phenotype and GC incidence in a large population, with a focus on sex and menopausal status, given hormonal influences on cancer risk.This retrospective cohort study used data from the Korean National Health Insurance Service. We included 4,441,403 adults who underwent health screening in 2012 without a prior history of cancer. Participants were classified into four metabolic–BMI phenotypes: metabolically healthy normal weight (MHN), metabolically healthy obesity (MHO), metabolically unhealthy normal weight (MUN), and metabolically unhealthy obesity (MUO). Cox proportional hazards models were used to estimate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for GC risk.During a mean follow-up of 9.0 years, 32,964 individuals (0.7%) developed GC. Compared with MHN, MUN (aHR 1.04, 95% CI 1.01–1.07) and MUO (aHR 1.10, 95% CI 1.07–1.14) were associated with higher GC risk. Among males, risk increased progressively across the MHO, MUN, and MUO groups (aHR 1.16, 95% CI 1.12–1.20 for MUO). Among females, no significant associations were observed before menopause; however, postmenopausal MUO was associated with increased GC risk (aHR 1.11, 95% CI 1.05–1.18). In a sensitivity analysis with a 5-year landmark period, associations were slightly stronger. Stratified analysis showed consistent results across subgroups.This large-scale, nationwide cohort study of over 4.4 million Korean adults provides robust evidence that MUO and MUN are associated with an elevated risk of GC. Notably, we found this risk to be more prominent among males and postmenopausal females, underscoring the influence of metabolic health and hormonal status in GC pathogenesis.Metabolic–BMI phenotype is an important predictor of GC risk. Identifying high-risk individuals—particularly males and postmenopausal females with metabolic abnormalities—may enhance prevention and screening strategies.