Evidence mapPaperPMID 30864629Full record

ArticleArchives of endocrinology and metabolism2019

Anthropometric measurements as a potential non-invasive alternative for the diagnosis of metabolic syndrome in adolescents.

Silmara Salete de Barros Silva Mastroeni, Marco Fabio Mastroeni, John Paul Ekwaru, Solmaz Setayeshgar, Paul J Veugelers, Muryel de Carvalho Gonçalves, Patrícia Helen de Carvalho Rondó

Abstract read
In one paragraph

Article in Archives of endocrinology and metabolism, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
field-weighted citation impact
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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. Observational
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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

7 authors.

Silmara Salete de Barros Silva MastroeniDepartamento de Educação Física, Universidade da Região de Joinville (Univille), Joinville, SC, Brasil.
Marco Fabio MastroeniPopulation Health Intervention Research Unit, School of Public Health, University of Alberta, Edmonton, Alberta, Canada.
John Paul EkwaruPopulation Health Intervention Research Unit, School of Public Health, University of Alberta, Edmonton, Alberta, Canada.
Solmaz SetayeshgarPopulation Health Intervention Research Unit, School of Public Health, University of Alberta, Edmonton, Alberta, Canada.
Paul J VeugelersPopulation Health Intervention Research Unit, School of Public Health, University of Alberta, Edmonton, Alberta, Canada.
Muryel de Carvalho GonçalvesDepartamento de Ciências Biológicas, Universidade da Região de Joinville (Univille), Joinville, SC, Brasil.
Patrícia Helen de Carvalho RondóDepartamento de Nutrição, Faculdade de Saúde Pública, Universidade de São Paulo (FSP-USP), São Paulo, SP, Brasil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo identify which anthropometric measurement would be the best predictor of metabolic syndrome (MetS) in Brazilian adolescents. SUBJECTS AND

methodsCross-sectional study conducted on 222 adolescents (15-17 years) from a city in southern Brazil. Anthropometric, physical activity, blood pressure and biochemical parameters were investigated. MetS criteria were transformed into a continuous variable (MetS score). Linear regression analyses were performed to assess the associations of BMI, hip circumference, neck circumference (NC), triceps skinfold, subscapular skinfold and body fat percentage with MetS score. ROC curves were constructed to determine the cutoff for each anthropometric measurement.

resultsThe prevalence of MetS was 7.2%. Each anthropometric measurement was significantly (p < 0.001) associated with MetS score. After adjusting for potential confounding variables (age, sex, physical activity, and maternal education), the standardized coefficients of NC and body fat percentage appeared to have the strongest association (beta = 0.69 standard deviation) with MetS score. The regression of BMI provided the best model fit (adjusted R2 = 0.31). BMI predicted MetS with high sensitivity (100.0%) and specificity (86.4%).

conclusionsOur results suggest that BMI and NC are effective screening tools for MetS in adolescents. The early diagnosis of MetS combined with targeted lifestyle interventions in adolescence may help reduce the burden of cardiovascular diseases and diabetes in adulthood.

Indexed as

Body Mass IndexWaist CircumferenceAdolescentBlood PressureCross-Sectional StudiesFemaleHumansMaleMetabolic SyndromePrevalenceRisk FactorsSensitivity and Specificity

Identifiers

PMID30864629
PMCPMC10118845

What Socratic holds

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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 Socratic graph.