Evidence map›Paper›PMID 39726532›Full record

ArticleFrontiers in pediatrics2024

Cross-sectional and prospective associations between children's eating behavior and visceral fat area and trunk fat mass.

Youxin Wang, Fangjing Shen, Pingping Zhang, Miao Xu, Danqi Qiu, Hui Wang, Li Li

Abstract read
In one paragraph

Article in Frontiers in pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Youxin Wang *Department of Endocrinology and Metabolism, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Fangjing Shen *Department of Endocrinology and Metabolism, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Pingping ZhangNingbo Center for Healthy Lifestyle Research, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Miao XuDepartment of Endocrinology and Metabolism, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Danqi QiuDepartment of Endocrinology and Metabolism, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Hui WangDepartment of Maternal and Child Health, School of Public Health, Peking University, Beijing, China.
Li LiDepartment of Endocrinology and Metabolism, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Understanding children's eating behaviors is crucial for elucidating the etiology of childhood obesity. However, the relationship between these behaviors and abdominal fat accumulation remains poorly understood. This study aims to investigate this association in primary school children. Methods: This study included 1,475 children aged 8-10 years in Ningbo, China. Body composition was measured both at baseline (September 2022) and after 9 months of follow-up (June 2023). Primary caregivers completed the Children's Eating Behavior Questionnaire (CEBQ). A mixed-effects linear model was applied to analyze the relationships between children's eating behaviors and body composition. Results: Greater visceral fat area (VFA) was associated with greater slowness in eating [β = 0.25 (0.02, 0.49)], greater food responsiveness [β = 0.29 (0.14, 0.43)], increased emotional undereating [β = 0.35 (0.17, 0.54)], and more emotional overeating [β = 0.21 (0.02, 0.39)]. Children with greater trunk fat mass (TrFM) tended to have greater food responsiveness [β = 0.02 (0.01, 0.03)] and greater enjoyment of food [β = 0.01 (0.00, 0.03)], increased emotional undereating [β = 0.02 (0.01, 0.03)] and emotional overeating [β = 0.02 (0.00, 0.03)]. Prospectively, positive correlations were observed between VFA and food responsiveness [β = 0.18 (0.02, 0.35)], as were emotional undereating [β = 0.31 (0.10, 0.52)] and emotional overeating [β = 0.24 (0.03, 0.46)]. Similarly, TrFM was positively correlated with food responsiveness [β = 0.02 (0.00, 0.03)], enjoyment of food [β = 0.02 (0.00, 0.04)], emotional undereating [β = 0.02 (0.01, 0.04)] and emotional overeating [β = 0.02 (0.01, 0.04)]. Conclusions: Our findings suggest that eating behaviors are significantly associated with abdominal fat accumulation in primary school children. Addressing specific eating behaviors may be crucial in mitigating abdominal fat and its related health risks.

Indexed as

abdominal fatchildreneating behaviorsobesityoverweight

Identifiers

PMID39726532
PMCPMC11669656

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.