Evidence map›Paper›PMID 38088734›Full record

ArticleCadernos de saude publica2023

Patterns of metabolic syndrome and associated factors in women from the ELSA-Brasil: a latent class analysis approach.

Nila Mara Smith Galvão, Sheila Maria Alvim de Matos, Maria da Conceição Chagas de Almeida, Ligia Gabrielli, Sandhi Maria Barreto, Estela M L Aquino, Maria Inês Schmidt, Leila Denise Alves Ferreira Amorim

Open access · diamondAbstract read
In one paragraph

Article in Cadernos de saude publica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 3 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

8 authors at 5 institutions in 1 country.

Nila Mara Smith GalvãoUniversidade do Estado da Bahia, Salvador, Brasil.ORCID 0000-0002-3106-6366
Sheila Maria Alvim de MatosInstituto de Saúde Coletiva, Universidade Federal da Bahia, Salvador, Brasil.ORCID 0000-0003-2080-9213
Maria da Conceição Chagas de AlmeidaInstituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brasil.ORCID 0000-0002-4760-4157
Ligia GabrielliInstituto de Saúde Coletiva, Universidade Federal da Bahia, Salvador, Brasil.ORCID 0000-0002-5195-1979
Sandhi Maria BarretoFaculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brasil.ORCID 0000-0001-7383-7811
Estela M L AquinoInstituto de Saúde Coletiva, Universidade Federal da Bahia, Salvador, Brasil.ORCID 0000-0002-8204-1249
Maria Inês SchmidtFaculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil.ORCID 0000-0002-3837-0731
Leila Denise Alves Ferreira AmorimInstituto de Matemática e Estatística, Universidade Federal da Bahia, Salvador, Brasil.ORCID 0000-0002-1112-2332
Universidade Federal da Bahia · BRFundação Oswaldo Cruz · BRUniversidade do Estado da Bahia · BRUniversidade Federal de Minas Gerais · BRUniversidade Federal do Rio Grande do Sul · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to identify patterns of metabolic syndrome among women and estimate their prevalence and relationship with sociodemographic and biological characteristics. In total, 5,836 women were evaluated using baseline data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Patterns of metabolic syndrome were defined via latent class analysis, using the following metabolic abnormalities as indicators: abdominal obesity, hyperglycemia, hypertension, hypertriglyceridemia, and reduced HDL cholesterol. The relationship between these patterns and individual characteristics was assessed using latent class analysis with covariates. Three patterns of metabolic syndrome were identified: high metabolic expression, moderate metabolic expression, and low metabolic expression. The first two patterns represented most women (53.8%) in the study. Women with complete primary or secondary education and belonging to lower social classes were more likely to have higher metabolic expression. Black and mixed-race women were more likely to have moderate metabolic expression. Menopausal women aged 50 years and older were more often classified into patterns of greater health risk. This study addressed the heterogeneous nature of metabolic syndrome, identifying three distinct profiles for the syndrome among women. The combination of abdominal obesity, hyperglycemia, and hypertension represents the main metabolic profile found among ELSA-Brasil participants. Sociodemographic and biological factors were important predictors of patterns of metabolic syndrome.

Indexed as

HyperglycemiaHypertensionMetabolic SyndromeAdultAgedBrazilFemaleHumansLatent Class AnalysisLongitudinal StudiesMiddle AgedObesity, AbdominalRisk Factors

Identifiers

PMID38088734
PMCPMC10715568
OpenAlexW4389565041

What OpenQuestion 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 OpenQuestion graph.