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Plant-based diet quality and gut microbiota in relation to cardiometabolic risk in Korean adults

  • Ji-Hee Shin,
  • Eun-Ji Song,
  • Mi Young Lim,
  • Hye-Jo Choi,
  • Jihye Kim,
  • Young-Do Nam

摘要

Purpose

This study investigated the association between plant-based diet quality and gut microbiota and explored whether integrating microbiota profiles with dietary indices improved strength of association with selected cardiometabolic outcomes.

Methods

In this cross-sectional study, we analyzed cohort data collected from 2,388 Korean adults between 2017 and 2019. Dietary quality indices, including the overall plant-based diet index (PDI), healthful PDI (hPDI), and unhealthful PDI (uPDI), were derived from a food frequency questionnaire. Gut microbiota were profiled using 16S rRNA gene sequencing. Cardiometabolic risk factors included obesity, abdominal obesity, elevated fasting glucose, elevated triglycerides, low high-density lipoprotein cholesterol (HDL-C), and elevated blood pressure.

Results

A higher hPDI score was associated with reduced obesity risk (OR = 0.72; 95% CI, 0.57–0.91) and improved gut microbiota α-diversity. A higher uPDI score was associated with increased risk of elevated fasting glucose (OR = 1.23; 95% CI, 1.00–1.52) and low HDL-C levels (OR = 1.35; 95% CI, 1.07–1.70), and lower α-diversity. hPDI and uPDI scores were also associated with differences in gut microbial community structure. For obesity and elevated fasting glucose, models integrating plant-based diet indices with gut microbiome features showed higher area under the curve than dietary-only models. Genus-level analyses identified key bacterial genera associated with dietary scores and metabolic traits. The predictive performance for low HDL-C remained modest across models.

Conclusions

Plant-based diet quality was associated with gut microbiota composition and cardiometabolic health. Integrating gut microbiome features with dietary assessments provided greater explanatory value for obesity and elevated fasting glucose, although longitudinal studies are needed to clarify temporal relationships and causal pathways.