Evidence map›Paper›PMID 31018842›Full record

ArticleBMC pediatrics2019

Comparison of various anthropometric indices in predicting abdominal obesity in Chinese children: a cross-sectional study.

Gengdong Chen, Huanchang Yan, Yuting Hao, Shiksha Shrestha, Jue Wang, Yan Li, Yuanhuan Wei, Jialiang Pan, Zheqing Zhang

Open access · goldAbstract read
In one paragraph

Article in BMC pediatrics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
8.7field-weighted citation impact, top 2% 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

14 citing papers in PubMed, 51 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Gengdong ChenFoshan Institute of Fetal Medicine, Department of Obstetrics, Southern Medical University Affiliated Maternal & Child Health Hospital of Foshan, Foshan, 528000, Guangdong, China.
Huanchang YanDepartment of Nutrition and Food Hygiene, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China.
Yuting HaoDepartment of Nutrition and Food Hygiene, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China.
Shiksha ShresthaDepartment of Nutrition and Food Hygiene, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China.
Jue WangDepartment of Nutrition and Food Hygiene, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China.
Yan LiDepartment of Nutrition and Food Hygiene, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China.
Yuanhuan WeiDepartment of Nutrition and Food Hygiene, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China.
Jialiang PanDepartment of Hygiene Detection Center, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China. panjialiang707@163.com.
Zheqing ZhangDepartment of Nutrition and Food Hygiene, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, 510515, China. zzqaa501@smu.edu.cn.ORCID 0000-0001-8386-0361
Southern Medical University · CNFoshan Maternity and Child Health Care Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFormer evidence regarding reference values of abdominal fat percentage (AFP) and optimal anthropometric indicators in predicting abdominal obesity measured by dual-energy X-ray absorptiometry (DXA) scan in Chinese children were scarce.

methodsA total of 452 Chinese children aged 6-9 years were included in this cross-sectional study. Abdominal fat and lean mass were measured by a DXA scan, and AFP were calculated. Anthropometric indicators including body mass index (BMI), chest circumference (CC), waist circumference (WC) and hip circumference (HC) were measured, waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) was also calculated.

resultsBy defining abdominal obesity as those with an AFP ≥ 85th percentile, the cutoffs values are 24.80, 30.29, 31.58, 31.86% in boys, and 25.02, 30.32, 31.66, 31.79% in girls, for children aged 6, 7, 8, and 9 years old, respectively. All anthropometric indicators were independently and positively associated with AFP (P all < 0.01). In girls, BMI was found to be the optimal predictors of childhood abdominal obesity. The values of area under curves (AUCs) were significantly higher (P all < 0.05) than other anthropometric indicators, except for WHtR (AUCs value: 0.886). However, in boys, WHtR instead of BMI, provided the largest AUCs value (0.922) in predicting abdominal obesity, followed by BMI ((AUCs value: 0.913).

conclusionThis study provides reference values of AFP measured by DXA in Chinese children aged 6-9 years. BMI and WHtR tend to be the optimal anthropometric indicators in predicting abdominal obesity in Chinese girls and boys, respectively.

Indexed as

Body Mass IndexWaist CircumferenceAbsorptiometry, PhotonAnthropometryArea Under CurveChildChinaCross-Sectional StudiesFemaleHumansIncidenceMaleObesity, AbdominalPediatric ObesityPredictive Value of TestsRisk AssessmentAbdominal obesityAnthropometric indicatorsChildrenChineseFat percentage

Identifiers

PMID31018842
PMCPMC6482578
OpenAlexW2945377351

What OpenQuestion holds

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LicenceCC BY
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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.