The associations of dietary exposure to selected food additives with dietary patterns and overweight

Although food additive consumption did not exceed safety limits, its association with obesity highlights a potential public health concern. The findings advocate for dietary guidelines that consider the broader implications of ultra-processed products beyond caloric and nutrient content.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2026-02-25
DOI
https://doi.org/10.1371/journal.pone.0341825
Primary Topic
Consumer Attitudes and Food Labeling
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The associations of dietary exposure to selected food additives with dietary patterns and overweight

Sigal Tepper, Kerem Avital, Danit Rivkah Shahar, Sivan Ben-Avraham et al.
PLoS ONE
Consumer Attitudes and Food Labeling
article

The associations of dietary exposure to selected food additives with dietary patterns and overweight

Sigal Tepper, Kerem Avital, Danit Rivkah Shahar, Sivan Ben-Avraham, Irit Atary-Sheetryt
article en

Abstract

Although food additive consumption did not exceed safety limits, its association with obesity highlights a potential public health concern. The findings advocate for dietary guidelines that consider the broader implications of ultra-processed products beyond caloric and nutrient content.

PLoS ONEVol. 21(2)
Ben-Gurion University of the Negev (IL), Israel Ministry of Health (IL), Tel Hai Academic College (IL)
Zero hunger
Openalex Percentile: Top 47%
Consumer Attitudes and Food Labeling
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.