Evidence map›Paper›PMID 32231225›Full record

ArticleEuropean journal of clinical nutrition2020

Healthy breakfast habits and changes in obesity-related cardiometabolic markers in children: a longitudinal analysis.

Xianwen Shang, Yanping Li, Haiquan Xu, Qian Zhang, Xiaoqi Hu, Ailing Liu, Songming Du, Tingyu Li, Hongwei Guo, Ying Li and 4 more

Abstract read
PubMed Publisher
In one paragraph

Article in European journal of clinical nutrition, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 9 institutions in 3 countries.

Xianwen ShangNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Yanping LiDepartment of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.ORCID http://orcid.org/0000-0002-0412-2748
Haiquan XuInstitute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing, China.
Qian ZhangNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Xiaoqi HuNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Ailing LiuNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Songming DuNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing, China.
Tingyu Li *Chongqing Children's Hospital, Chongqing, China.
Hongwei Guo *School of Public Health, Fudan University, Shanghai, China.
Ying Li *Harbin Medical University, Harbin, China.
Guifa Xu *Department of Public Health, Shandong University, Jinan, China.
Weijia Liu *Guangzhou Center for Disease Control and Prevention, Guangzhou, China.
Jun Ma *Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China.
Guansheng MaDepartment of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing, China. mags@bjmu.edu.cn.
Chinese Center For Disease Control and Prevention · CNHarvard University · USPeking University · CNChildren's Hospital of Chongqing Medical University · CNFudan University · CNGuangzhou Center for Disease Control and Prevention · CNMinistry of Agriculture and Rural Affairs · CNShandong University · CNThe Royal Melbourne Hospital · AU

Funding

Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 2008BAI58B05
6 · The paper itself

Abstract

backgroundData on the association of breakfast habits and changes in cardiometabolic markers in children are limited.

methodsIn total, 6964 children aged 6-13 years from Beijing, Shanghai, Chongqing, Jinan, Harbin, and Guangzhou were included in the final analysis. Daily consumption, consumption of ≥3 food groups, and at-home consumption were defined as healthy breakfast habits. Blood pressure, % fat mass, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides, glucose, and 50-m × 8 shuttle run were measured at baseline (May 2009) and follow-up (May 2010). Clustered cardiometabolic risk score (CCRS) was computed by summing Z scores of five components: % fat mass, systolic blood pressure, glucose, TC to HDL-C ratio, and triglyceride.

resultsChildren who ate breakfast daily had a higher decrease in TC to HDL-C ratio and a higher increase in HDL-C compared with breakfast skippers (both P values < 0.05). There was an inverse association of the number of food groups consumed at breakfast with the change in CCRS (P trend = 0.005). At-home breakfast consumption was associated with a lower increase in BMI, LDL-C, TC to HDL-C ratio, fasting glucose, and 50-m × 8 shuttle run and a higher increase in HDL-C (all P values < 0.05). Children with two or three healthy breakfast habits had a lower increase in CCRS, LDL-C, TC to HDL-C ratio, glucose, and a higher increase in HDL-C compared with those with none or one (all P values < 0.05).

conclusionsHealthy breakfast habits might help minimize the cardiometabolic risk factors in children.

Indexed as

BreakfastCardiovascular DiseasesChildChinaCholesterol, HDLHabitsHumansObesityRisk FactorsTriglyceridesCholesterol, HDLTriglycerides

Identifiers

PMID32231225
OpenAlexW3013062807

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.