Association of a Diet Index for the Gut Microbiome With Hypertension and Obesity-Related Hypertension: A Cross-Sectional Analysis of NHANES 2007-2020.

Authors

Jingyi Zhang, Yubo Teng, Guocheng Xue, Shengwen Jiang, Boxiang Yang, Miao Zhang

Published in

The Journal of cardiovascular nursing. Jul 03, 2026. Epub Jul 03, 2026.

Abstract

Dietary patterns that support gut-microbiome diversity may influence hypertension, but phenotype-specific evidence is limited.
Assess associations of a diet index for the gut microbiome (DI-GM) with prevalent hypertension and obesity-related hypertension in U.S. adults.
The National Health and Nutrition Examination Survey 2007-2020 included 22,784 adults aged ≥20 years. Multivariable logistic models related DI-GM (continuous; quartiles) to outcomes; restricted cubic splines characterized dose-response. Effect modification was tested across demographic and clinical subgroups. Variable importance of DI-GM components was estimated using the Boruta algorithm. Discrimination was assessed by the area under the receiver operating characteristic curve.
Higher DI-GM was inversely associated with hypertension-per 1-unit higher DI-GM: odds ratio (OR) = 0.97 (95% confidence interval [CI], 0.96-0.99; P<.001)-and more strongly with obesity-related hypertension: OR = 0.95 (95% CI, 0.92-0.98; P<.01). Spline analyses suggested approximately linear inverse associations. There was no significant interaction between DI-GM and hypertension, as well as between DI-GM and obesity-related hypertension, in any of the subgroups. Refined grains, fermented dairy, and dietary fiber ranked highest for hypertension, while high-fat diet, processed meats, and avocados were most influential for obesity-related hypertension. The areas under the receiver operating characteristic curves were 0.695 for hypertension and 0.767 for obesity-related hypertension.
In this cross-sectional analysis, higher DI-GM was related to lower odds of hypertension, particularly obesity-related hypertension. Diet index for the gut microbiome may aid hypothesis generation and risk stratification for microbiome-supportive dietary guidance; causal inference is not possible. Prospective cohorts and randomized dietary interventions integrating microbiome profiling are needed.

PMID:
42391551
Bibliographic data and abstract were imported from PubMed on 03 Jul 2026.

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