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Record W2984914227 · doi:10.1080/03630242.2019.1688445

Metabolic syndrome (MetS) and associated factors in middle-aged women: a cross-sectional study in Northeast Brazil

2019· article· en· W2984914227 on OpenAlexaff
Mayle Andrade Moreira, Afshin Vafaei, Saionara Maria Aires da Câmara, Rafaela Andrade do Nascimento, Maria Socorro Medeiros de Morais, Maria das Graças Almeida, Álvaro Campos Cavalcanti Maciel

Bibliographic record

VenueWomen & Health · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsQueen's University
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsMedicinePoisson regressionMetabolic syndromeBody mass indexDemographyObesityAnthropometryCross-sectional studyConfidence intervalNational Cholesterol Education ProgramOdds ratioGerontologyPopulationWaistEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

We determined the prevalence of Metabolic Syndrome (MetS) and associated factors in 419 women (aged 40 to 65 years) in Northeast Brazil in a cross-sectional study conducted from April to November 2013. We defined MetS using the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III) criteria. Socio-demographic variables, reproductive factors, lifestyle factors, anthropometrics, body composition, quality of life, and physical performance were assessed for their associations. We constructed multivariate Poisson regression models to estimate prevalence rate ratios (PRR) and 95% confidence intervals (CI). We identified 275 (65.6%) cases of MetS. The three most prevalent indicators were obesity (73.5%), reduced high-density lipoprotein level (63.0%), and elevated blood pressure (60.9%). In the final adjusted model, black race (PR 1.30, 95% CI: 1.07-1.57), lower grip strength/body mass index (PR 1.31, 95% CI: 1.15-1.50), and low estradiol levels (PR 1.17, 95% CI: 1.00-1.35) were associated with MetS. MetS is a long-term threat to the health of middle-aged women and a potential public health burden. These results may help in developing health promotion strategies to prevent morbidity and mortality associated with MetS in this vulnerable population.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.286
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2019
Admission routes1
Has abstractyes

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