Impact of Dietary Patterns on Metabolic Syndrome in Young Adults: A Cross-Sectional Study

Metabolic syndrome has become a significant public health concern. This study aims to investigate the impact of dietary patterns on metabolic syndrome in young adults and how physical activity modulates this effect. A cross-sectional study was conducted at a health management center in Tianjin, China, from September 2022 to March 2023. Participants aged 18-35 years were recruited using convenience sampling. Dietary intake was assessed using a validated food frequency questionnaire. Logistic regression models evaluated associations between these patterns and metabolic syndrome, adjusting for potential confounders. Among 442 participants, four dietary patterns were identified: Legume-Nut, Alcohol-Meat, Sugar-Processed, and Egg-Vegetable. The Legume-Nut dietary pattern was associated with a higher risk of metabolic syndrome (OR = 2.63, 95% CI: 1.08-6.37), while the Egg-Vegetable dietary pattern was associated with a lower risk (OR = 0.26, 95% CI: 0.10-0.70). No significant associations were found for the Sugar-Processed and Alcohol-Meat patterns. Subgroup analysis revealed that the Legume-Nut pattern increased the risk of metabolic syndrome among those with irregular physical activity, whereas the Egg-Vegetable pattern decreased the risk. These findings highlight the significant influence of dietary patterns on the risk of metabolic syndrome in young adults and the modifying effect of regular physical activity, underscoring the need for targeted dietary and lifestyle interventions to prevent metabolic syndrome in this population.

Authors

Institutions

Publication Details

Journal
Nutrients
Published
2024-08-29
DOI
https://doi.org/10.3390/nu16172890
Citations
13
Primary Topic
Diet, Metabolism, and Disease
Type
article
Field-Weighted Citation Impact
4.65

Funders

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

Impact of Dietary Patterns on Metabolic Syndrome in Young Adults: A Cross-Sectional Study

Xueying Xu, Jingwen Liu, Yuan He, Xiaoying Zang et al.
13 citations
Nutrients
Diet, Metabolism, and Disease
4.65
article

Impact of Dietary Patterns on Metabolic Syndrome in Young Adults: A Cross-Sectional Study

Xueying Xu, Jingwen Liu, Yuan He, Xiaoying Zang, Qingyun Lv, Huaping Zhang, Xiaonan Zhang, Yue Zhao, Hairong Chang, Wenfeng Lu, Yaqi Wang
article en
13 citations

Abstract

Metabolic syndrome has become a significant public health concern. This study aims to investigate the impact of dietary patterns on metabolic syndrome in young adults and how physical activity modulates this effect. A cross-sectional study was conducted at a health management center in Tianjin, China, from September 2022 to March 2023. Participants aged 18-35 years were recruited using convenience sampling. Dietary intake was assessed using a validated food frequency questionnaire. Logistic regression models evaluated associations between these patterns and metabolic syndrome, adjusting for potential confounders. Among 442 participants, four dietary patterns were identified: Legume-Nut, Alcohol-Meat, Sugar-Processed, and Egg-Vegetable. The Legume-Nut dietary pattern was associated with a higher risk of metabolic syndrome (OR = 2.63, 95% CI: 1.08-6.37), while the Egg-Vegetable dietary pattern was associated with a lower risk (OR = 0.26, 95% CI: 0.10-0.70). No significant associations were found for the Sugar-Processed and Alcohol-Meat patterns. Subgroup analysis revealed that the Legume-Nut pattern increased the risk of metabolic syndrome among those with irregular physical activity, whereas the Egg-Vegetable pattern decreased the risk. These findings highlight the significant influence of dietary patterns on the risk of metabolic syndrome in young adults and the modifying effect of regular physical activity, underscoring the need for targeted dietary and lifestyle interventions to prevent metabolic syndrome in this population.

NutrientsVol. 16(17)
Tianjin Medical University (CN)
National Natural Science Foundation of China, Humanities and Social Science Fund of Ministry of Education of China
Zero hunger
Openalex Percentile: Top 4%
Diet, Metabolism, and Disease
4.65
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.