Association between pro-inflammatory diet and fecal incontinence: a large population-based study

In conclusion, this study not only elucidates the fundamental roles of pro-inflammatory diet in inducing intestinal inflammation and eventually in resulting FI, but also provides a FI risk prediction tool based on dietary factors, which may prove beneficial in the clinical diagnosis of FI.

Authors

Institutions

Publication Details

Journal
Frontiers in Nutrition
Published
2025-05-22
DOI
https://doi.org/10.3389/fnut.2025.1547406
Citations
3
Primary Topic
Pelvic floor disorders treatments
Type
article
Field-Weighted Citation Impact
5.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Association between pro-inflammatory diet and fecal incontinence: a large population-based study

Yanni Lv, Tingting Dong, Can Li, Zihan Liu et al.
3 citations
Frontiers in Nutrition
Pelvic floor disorders treatments
5.00
article

Association between pro-inflammatory diet and fecal incontinence: a large population-based study

Yanni Lv, Tingting Dong, Can Li, Zihan Liu, Haiyang Wang, LU Xing-fu, Tao Shen, Erkang Wu, Enyu Luan
article en
3 citations

Abstract

In conclusion, this study not only elucidates the fundamental roles of pro-inflammatory diet in inducing intestinal inflammation and eventually in resulting FI, but also provides a FI risk prediction tool based on dietary factors, which may prove beneficial in the clinical diagnosis of FI.

Frontiers in NutritionVol. 12
Anhui Normal University (CN)
Openalex Percentile: Top 5%
Pelvic floor disorders treatments
5.00
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.