Response to “Association between the dietary index for gut microbiota and advanced cardiovascular‐kidney‐metabolic syndrome among United States adults: A cross‐sectional study”

We sincerely thank Dr Bruni et al for their thoughtful and constructive letter regarding our recent article, “Association between the dietary index for gut microbiota and advanced cardiovascular-kidney-metabolic syndrome among United States adults: A cross-sectional study.”1 We greatly appreciate their interest in our work and their valuable comments. First, we fully acknowledge the limitations of cross-sectional study design for causal inference and temporal interpretation.2 Based on the National Health and Nutrition Examination Survey (NHANES) data, a causal relationship between the dietary index for gut microbiota (DI-GM) and cardiovascular-kidney-metabolic (CKM) syndrome progression cannot be directly established; therefore, the article emphasizes that the findings reflect associations only. The possibility of reverse causation is also recognized, particularly in individuals with advanced CKM whose dietary patterns may have changed in response to their condition. To mitigate potential bias, we adjusted for multiple confounders and conducted stratified analyses, which showed that the association remained generally consistent across subgroups. Nevertheless, residual confounding and reverse causation cannot be entirely excluded, and prospective studies are warranted. Second, the reliability of dietary assessment warrants attention. The NHANES uses weighted repeated 24-h dietary recalls, which are widely applied in US nutrition epidemiology and offer good feasibility and standardization. Nevertheless, these assessments remain susceptible to recall bias and reporting errors, particularly among individuals with obesity, diabetes, or chronic diseases, who may systematically under-report or over-report certain foods.3 This limitation is common to studies using large public databases and underscores the need for future research to incorporate longer-term and more detailed dietary assessment tools, such as food frequency questionnaires, dietary records, or multiple timepoint measurements, to improve exposure accuracy. Third, the DI-GM in our study strictly followed the original construction method, with each dietary component scored based on sex-specific medians to account for differences between men and women in energy requirements, dietary intake, and gut microbiota composition.4 This approach avoids potential sex-related confounding that could arise from using overall medians and ensures standardization and comparability of DI-GM within each sex group. We acknowledge that this scoring method may somewhat reduce sensitivity to exposure gradients; however, in multivariable logistic regression models treating DI-GM as a continuous variable, the inverse association with advanced CKM remained significant and directionally consistent across models, with an odds ratio of 0.88, indicating that the association is not driven by the specific scoring method and demonstrates a certain degree of robustness. Finally, in the current study, DI-GM did not directly measure the gut microbiome. It reflects dietary patterns related to microbial features rather than the microbiome itself, and without concurrent metagenomic or metabolomic data, it is difficult to disentangle microbiota-mediated effects from those of overall healthier diet or lifestyle.5 Our study aimed to explore the overall association between gut microbiota–related dietary patterns and CKM progression from an epidemiological perspective, rather than to infer specific microbial pathways or causal mechanisms. Nevertheless, these findings provide important clues for future prospective cohort or intervention studies integrating fecal microbiome composition, microbial metabolites such as short-chain fatty acids and trimethylamine N-oxide, and detailed lifestyle assessments, which could help quantify the relative contributions of microbiota-mediated vs overall dietary and lifestyle effects on CKM risk.6 Overall, we greatly value the insightful feedback provided. Future prospective cohort and intervention studies, integrating multiomics data, may further clarify the predictive value and potential clinical use of DI-GM, thereby providing more actionable guidance for CKM risk stratification and lifestyle intervention strategies. None declared. Changzhou ‘14th Five-Year’ Health and Wellness High-level Talent Training Project : 2024CZBJ016.