Processed Food Consumption and Sleep Quality in School-Aged Children: Insights from a Cross-Sectional Study

These findings underscore the importance of addressing dietary patterns on children's sleep quality. Future interventions should account for reducing NOVA 4 and sweet snack consumption in order to improve sleep quality.

Authors

Institutions

Publication Details

Journal
Nutrients
Published
2025-01-10
DOI
https://doi.org/10.3390/nu17020233
Citations
1
Primary Topic
Obesity, Physical Activity, Diet
Type
article
Field-Weighted Citation Impact
1.88

Funders

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

Processed Food Consumption and Sleep Quality in School-Aged Children: Insights from a Cross-Sectional Study

Rafaela Rosário, Cláudia Augusto, Ana Duarte, Patrícia Padrão et al.
1 citations
Nutrients
Obesity, Physical Activity, Diet
1.88
article

Processed Food Consumption and Sleep Quality in School-Aged Children: Insights from a Cross-Sectional Study

Rafaela Rosário, Cláudia Augusto, Ana Duarte, Patrícia Padrão, Pedro Moreira, María José Silva, Juliana Martins, M. Gomes
article en
1 citations

Abstract

These findings underscore the importance of addressing dietary patterns on children's sleep quality. Future interventions should account for reducing NOVA 4 and sweet snack consumption in order to improve sleep quality.

NutrientsVol. 17(2)
Universidade do Porto (PT), Escola Superior de Enfermagem de Coimbra (PT), University of Minho (PT)
Fundação para a Ciência e a Tecnologia
Zero hunger
Openalex Percentile: Top 20%
Obesity, Physical Activity, Diet
1.88
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.