Evidence map›Paper›PMID 35757250›Full record

ArticleFrontiers in nutrition2022

Anthropometric Indicators of Body Composition Associated With Lipid and Glycemic Profiles in Overweight Brazilian Children and Adolescents From 2008 to 2020.

Carlos Alberto Nogueira-de-Almeida, Fábio da Veiga Ued, Andrea Aparecida Contini, Edson Zangiacomi Martinez, Luiz Antonio Del Ciampo, Maria Eduarda Nogueira-de-Almeida, Ivan Savioli Ferraz, Raquel Farias Barreto Silva, Elza Daniel de Mello, Mauro Fisberg

Open access · goldAbstract read
In one paragraph

Article in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

10 authors at 4 institutions in 1 country.

Carlos Alberto Nogueira-de-AlmeidaMedical Department, Federal University of São Carlos, São Carlos, Brazil.
Fábio da Veiga UedNutrition Department, Faculty of Medicine of Ribeirão Preto, University of São Paulo, São Paulo, Brazil.
Andrea Aparecida ContiniMedical Department, Federal University of São Carlos, São Carlos, Brazil.
Edson Zangiacomi MartinezFaculty of Medicine of Ribeirão Preto, University of São Paulo, São Paulo, Brazil.
Luiz Antonio Del CiampoPediatric Department, Faculty of Medicine of Ribeirão Preto, University of São Paulo, São Paulo, Brazil.
Maria Eduarda Nogueira-de-AlmeidaNutrition Department, Faculty of Medicine of Ribeirão Preto, University of São Paulo, São Paulo, Brazil.
Ivan Savioli FerrazPediatric Department, Faculty of Medicine of Ribeirão Preto, University of São Paulo, São Paulo, Brazil.
Raquel Farias Barreto SilvaPediatric Department, Faculty of Medicine of Ribeirão Preto, University of São Paulo, São Paulo, Brazil.
Elza Daniel de MelloPediatrics Department, Federal University of Rio Grande Do Sul, Porto Alegre, Brazil.
Mauro FisbergPensi Institute, Hospital Infantil Sabará, José Luiz Egídio Setúbal Foundation, São Paulo, Brazil.
Universidade de São Paulo · BRUniversidade Federal de São Carlos · BRUniversidade Federal de São Paulo · BRUniversidade Federal do Rio Grande do Sul · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Anthropometric indicators have been used to predict health problems. The objective was to determine which indicators present better correlation with dyslipidemia, hyperglycemia and peripheral insulin resistance, as well as the cutoff points capable of predicting lipid and glycemic alterations in Brazilian children and adolescents. Methods: A cross-sectional study conducted with 568 overweight individuals, aged between 5 and 18 years, living in Southeast and South Brazilian regions, submitted to anthropometric and body composition evaluation by bioimpedance, in addition to fasting laboratory tests [total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), fasting glycemia, and homeostasis model assessment-insulin resistance (HOMA-IR)]. Pearson's correlation was used to evaluate the association between anthropometric indicators and serum biomarkers. The ROC curve with Youden's J index was used to suggest anthropometric cutoff points with better ability to predict or rule out lipid and glycemic changes. Results: Cutoff points obtained for the z-score of body mass index (BMI), waist circumference (WC), and waist circumference for height (WC/H) showed high specificity (52 to 87%) and low sensitivity (23 to 59%), indicating greater ability to exclude changes in HDL-c, TG, and HOMA-IR levels. Cutoff points suggested for BMI ranged from +1.86 to +2.20 z-score. WC cutoff points ranged from +1.29 to +1.72, and, for the WC/H index, from +1.21 to +1.25. It was suggested the use of the following cutoff points to rule out changes in HDL-c, TG, and HOMA-IR values in clinical practice: BMI < z-score +2 and WC/H < z-score +1.29. In body fat percentage (BFP) analyses, the cutoff point < of 34% may be able to rule out changes in HDL-c (specificity of 70%), while the cutoff point > 36.6% may be able to predict changes in the HOMA-IR index (sensitivity of 76%). Conclusion: It is not yet possible to state which anthropometric parameter has the best correlation with lipid and glycemic alterations in overweight children and adolescents. We suggest considering BMI, WC, and WC/H cutoff points together to rule out changes in HDL-c, TG, and HOMA-IR, and use the BFP cutoff point to predict changes in HOMA-IR.

Indexed as

anthropometrybody compositionglycemic profilelipid profilenutritional statusobesity

Identifiers

PMID35757250
PMCPMC9218630
OpenAlexW4285740508

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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 OpenQuestion graph.