Intake of dietary branched-chain amino acids reduces odds of metabolic syndrome: a cross-sectional study on the PERSIAN Kavar cohort study

We observed a significant inverse association between dietary BCAA intake and MetS, hyperglycemia, and hypertriglyceridemia, regardless of confounding factors.

Authors

Institutions

Publication Details

Journal
Frontiers in Nutrition
Published
2024-10-17
DOI
https://doi.org/10.3389/fnut.2024.1403937
Citations
1
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
0.23

Funders

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

Intake of dietary branched-chain amino acids reduces odds of metabolic syndrome: a cross-sectional study on the PERSIAN Kavar cohort study

Ali Reza Safarpour, Mohammad Reza Fattahi, Sara Shojaei‐Zarghani, Zahra Mansourabadi
1 citations
Frontiers in Nutrition
Metabolomics and Mass Spectrometry Studies
0.23
article

Intake of dietary branched-chain amino acids reduces odds of metabolic syndrome: a cross-sectional study on the PERSIAN Kavar cohort study

Ali Reza Safarpour, Mohammad Reza Fattahi, Sara Shojaei‐Zarghani, Zahra Mansourabadi
article en
1 citations

Abstract

We observed a significant inverse association between dietary BCAA intake and MetS, hyperglycemia, and hypertriglyceridemia, regardless of confounding factors.

Frontiers in NutritionVol. 11
Shiraz University of Medical Sciences (IR)
Ministry of Health and Medical Education, Shiraz University of Medical Sciences, Shiraz University
Openalex Percentile: Top 42%
Metabolomics and Mass Spectrometry Studies
0.23
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.