Key result
Higher dietary index for gut microbiota scores were significantly associated with a lower prevalence of metabolic syndrome, demonstrating a 26% reduction in the highest versus lowest quartile (OR 0.74).
Why the study?
The relationship between the dietary index for gut microbiota (DI-GM) and metabolic syndrome (MetS), as well as the potential mediating role of body mass index, remains unclear.
Does a higher dietary index for gut microbiota (DI-GM) score reduce the prevalence of metabolic syndrome in adults?
Cross-Sectional (n=21,100)
Does a higher dietary index for gut microbiota (DI-GM) score reduce the prevalence of metabolic syndrome in adults?
Odds Ratio: 0.74 (95% CI 0.63–0.87)
Absolute Event Rate: 19.81% vs 24.02%
p-value: p=<0.001
A higher dietary index for gut microbiota is significantly associated with a lower prevalence of metabolic syndrome, an effect that is largely mediated by body mass index.
Should not yet change MetS dietary counseling; leaves open whether DI-GM targeting reduces prevalence independently of BMI.
Background: Dietary patterns influence the onset of metabolic syndrome (MetS) through the modulation of intestinal microbiota. Nevertheless, the relationship between the dietary index for gut microbiota (DI-GM), a novel metric for evaluating the link between diet and microbiota well-being, and its correlation with MetS, as well as the potential mediating role of body mass index (BMI), remains unclear. Methods: This study examined information from 21,100 individuals participating in the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and 2020. The association of DI-GM with MetS was assessed using a weighted multivariate logistic regression model, and restricted cubic spline curves (RCS), subgroup analyses, and mediation analyses were performed. Results: A significant inverse correlation was observed between DI-GM score and the prevalence of MetS. The prevalence of MetS decreased by 8% (OR = 0.92, 95% CI: 0.89-0.95) for each unit of DI-GM. The prevalence of MetS was reduced by 26% in Q4 compared with Q1 (OR = 0.74, 95% CI: 0.63-0.87). RCS analysis further revealed a linear relationship between DI-GM and MetS prevalence. Subgroup analysis showed that the negative association between DI-GM and MetS was more significant in the exercise, non-smoking, and non-drinking population. Furthermore, BMI played a significant mediating role in the association, accounting for 52.71%. Conclusion: A notable negative correlation exists between DI-GM score and the prevalence of MetS. The promotion of a healthy lifestyle can strengthen this correlation, with BMI serving as a crucial mediating factor. This underscores the potential of dietary interventions that focus on gut microbiota in conjunction with weight management as targeted strategies for the prevention and management of MetS.
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Liu et al. (2025) conducted a cross-sectional in Metabolic syndrome (n=21,100). Dietary index for gut microbiota (DI-GM) vs. Lowest quartile (Q1) of DI-GM score was evaluated on Prevalence of metabolic syndrome (Q4 vs Q1) (OR 0.74, 95% CI 0.63-0.87, p=<0.001). Higher dietary index for gut microbiota scores were significantly associated with a lower prevalence of metabolic syndrome, demonstrating a 26% reduction in the highest versus lowest quartile (OR 0.74).
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