Inverse relationship between dietary index for gut microbiota and cardiovascular-kidney-metabolic syndrome among the general adult population.

Cardiovascular-kidney-metabolic (CKM) syndrome is defined as the complex interaction of metabolic diseases such as metabolic syndrome (MS), chronic kidney disease (CKD), and cardiovascular disease (CVD). A study indicates that the CKM syndrome affects over 25% of the U.S. population, contributing to an increasing burden of disease on a global scale. The Dietary Index for Gut Microbiota (DI-GM) is an indicator used to assess the impact of diet on the health of the gut microbiota. The DI-GM has been demonstrated to be closely associated with a variety of diseases. However, it remains unclear whether the DI-GM can serve as a predictor for the CKM syndrome. This study aims to explore the association between the DI-GM and CKM syndrome. This study employed a cross-sectional research design utilizing publicly available data from the National Health and Nutrition Examination Survey (NHANES) for the years 2007-2016. After excluding participants with missing demographic data and age < 20, those with missing DI-GM and CKM data, and those with missing values for covariates, a total of 10,786 participants were selected from the NHANES database. Multivariable logistic regression evaluated DI-GM and CKM syndrome, adjusting for demographics and socioeconomic factors. Restricted cubic spline (RCS) regression assessed dose-response relationships. Subgroup analyses further explored the relationship between DI-GM and gender, age, marital status, race, education level, drinking, smoking, poverty-income ratio (PIR) and dietary inflammatory index (DII). Sensitivity analysis using random forest for missing data were performed. In this study, participants with CKM syndrome were significantly older than those without CKM syndrome (CKM: 48.81 ± 16.66 years vs. non-CKM: 34.28 ± 12.64 years, P < 0.001). The results from multivariate logistic regression analysis demonstrated a consistent negative association between DI-GM and CKM syndrome across the unadjusted model (OR = 0.91, 95% CI: 0.87-0.95, P < 0.001), Model 1 (OR = 0.88, 95% CI: 0.83-0.92, P < 0.001), Model 2 (OR = 0.88, 95% CI: 0.84-0.93, P < 0.001), and Model 3 (OR = 0.93, 95% CI: 0.88-0.99, P < 0.001).After adjusting for all confounders, participants with DI-GM ≥ 6 exhibited a 23% lower odds of CKM compared to those with DI-GM ≤ 3 (OR = 0.77, 95% CI: 0.59-0.99, P < 0.05). RCS analysis indicated a linear negative relationship between DI-GM and CKM (P = 0.071). Subgroup analyses suggested that the protective association between DI-GM and CKM prevalence was more pronounced in females (OR = 0.89, 95% CI: 0.84-0.95), non-Hispanic Whites (OR = 0.90, 95% CI: 0.84-0.96), participants with education above high school (OR = 0.93, 95% CI: 0.87-0.98), and high-income individuals (PIR ≥ 3) (OR = 0.90, 95% CI: 0.84-0.97). Significant heterogeneity (interaction P-value < 0.05) was observed in race (P = 0.027), education level (P = 0.008), and smoking (P = 0.017). Smoking has a significant effect on the association between DI-GM and CKM syndrome (P < 0.05), suggesting that smoking may weaken the protective effect of DI-GM against CKM. No significant interaction between DI-GM and DII (P = 0.451). All sensitivity analyses supported the inverse relationship between DI-GM and CKM syndrome. Our findings suggest that the DI-GM score was significantly negatively correlated with CKM syndrome. Specific subgroups (such as non-Hispanic Whites, individuals with higher education levels, and smokers) may modify the association between the DI-GM and CKM syndrome. These insights could inform more personalized dietary strategies for CKM prevention.