Causal effect of kimchi intake on HDL-cholesterol levels in middle aged Korean men: a two-sample Mendelian randomization analysis

This study provides evidence for a causal effect of kimchi consumption in preventing decreases in HDL-C levels among middle-aged Korean men. These findings support kimchi as a sex-specific dietary intervention for cardiovascular health.

Authors

Institutions

Publication Details

Journal
Genes & Nutrition
Published
2025-11-05
DOI
https://doi.org/10.1186/s12263-025-00785-6
Primary Topic
Phytoestrogen effects and research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Causal effect of kimchi intake on HDL-cholesterol levels in middle aged Korean men: a two-sample Mendelian randomization analysis

Seong‐Hee Ko, Dayeon Shin, Judy Cha
Genes & Nutrition
Phytoestrogen effects and research
article

Causal effect of kimchi intake on HDL-cholesterol levels in middle aged Korean men: a two-sample Mendelian randomization analysis

Seong‐Hee Ko, Dayeon Shin, Judy Cha
article en

Abstract

This study provides evidence for a causal effect of kimchi consumption in preventing decreases in HDL-C levels among middle-aged Korean men. These findings support kimchi as a sex-specific dietary intervention for cardiovascular health.

Genes & NutritionVol. 20(1)
Inha University (KR)
Korea Disease Control and Prevention Agency, National Research Foundation, National Research Foundation of Korea, Ministry of Science and ICT, South Korea
Openalex Percentile: Top 54%
Phytoestrogen effects and research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.