Evidence mapPaperPMID 35329071Full record

ArticleInternational journal of environmental research and public health2022

Structural Equation Modelling for Predicting the Relative Contribution of Each Component in the Metabolic Syndrome Status Change.

José E Teixeira, José A Bragada, João P Bragada, Joana P Coelho, Isabel G Pinto, Luís P Reis, Paula O Fernandes, Jorge E Morais, Pedro M Magalhães

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Observational
  7. Article
  8. The Relationships between Physical Activity, Exercise, and Sport on the Immune System.International journal of environmental research and public health · 2022
    Article
  9. 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

9 authors at 2 institutions in 1 country.

José E TeixeiraResearch Centre in Sports Sciences, Health and Human Development (CIDESD), 5001-801 Vila Real, Portugal.ORCID 0000-0003-4612-3623
José A BragadaResearch Centre in Sports Sciences, Health and Human Development (CIDESD), 5001-801 Vila Real, Portugal.ORCID 0000-0001-7020-0583
João P BragadaNorth East Local Health Unit (ULSNE)-Health Care Unit of Santa Maria, 5301-852 Bragança, Portugal.ORCID 0000-0002-9413-221X
Joana P CoelhoNorth East Local Health Unit (ULSNE)-Health Care Unit of Santa Maria, 5301-852 Bragança, Portugal.ORCID 0000-0002-5967-9017
Isabel G PintoNorth East Local Health Unit (ULSNE)-Health Care Unit of Santa Maria, 5301-852 Bragança, Portugal.ORCID 0000-0001-7187-8580
Luís P ReisNorth East Local Health Unit (ULSNE)-Health Care Unit of Santa Maria, 5301-852 Bragança, Portugal.ORCID 0000-0003-0236-1654
Paula O FernandesApplied Management Research Unit (UNIAG), Instituto Politécnico de Bragança (IPB), 5300-253 Bragança, Portugal.ORCID 0000-0001-8714-4901
Jorge E MoraisResearch Centre in Sports Sciences, Health and Human Development (CIDESD), 5001-801 Vila Real, Portugal.ORCID 0000-0002-6885-0648
Pedro M MagalhãesDepartment of Sport Sciences, Instituto Politécnico de Bragança (IPB), 5300-253 Bragança, Portugal.ORCID 0000-0003-2492-1499
Polytechnic Institute of Bragança · PTUnidade Hospitalar de Bragança · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the factor weighting in the development of metabolic syndrome (MetS) may help to predict the progression for cardiovascular and metabolic diseases. Thus, the aim of this study was to develop a confirmatory model to describe and explain the direct and indirect effect of each component in MetS status change. A total of 3581 individuals diagnosed with MetS, aged 18−102 years, were selected between January 2019 and December 2020 from a community-representative sample of Portuguese adults in a north-eastern Portuguese region to test the model’s goodness of fit. A structural equation modelling (SEM) approach and a two-way ANOVA (age × body composition) were performed to compare the relative contribution of each MetS component using joint interim statement (JIS). Waist circumference (β = 0.189−0.373, p < 0.001), fasting glucose (β = 0.168−0.199, p < 0.001) and systolic blood pressure (β = 0.140−0.162, p < 0.001) had the highest direct effect on the change in MetS status in the overall population and concerning both sexes. Moreover, diastolic blood pressure (DBP), triglycerides (TG) and high-density lipoprotein cholesterol (HDL-c) had a low or non-significant effect. Additionally, an indirect effect was reported for age and body composition involving the change in MetS status. The findings may suggest that other components with higher specificity and sensitivity should be considered to empirically validate the harmonised definition of MetS. Current research provides the first multivariate model for predicting the relative contribution of each component in the MetS status change, specifically in Portuguese adults.

Indexed as

Metabolic SyndromeAdultBlood GlucoseBlood PressureFemaleHumansLatent Class AnalysisMaleRisk FactorsTriglyceridesWaist CircumferenceBlood GlucoseTriglyceridesmetabolic syndromemultilevel modellingpredictionprogressionpublic health

Identifiers

PMID35329071
PMCPMC8992136
OpenAlexW4220980685

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.