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Associations between Components of Metabolic Syndrome and Demographic, Nutritional, and Lifestyle Factors.
Lima, Layne Christina Benedito de Assis; Aquino, Séphora Louyse Silva; da Cunha, Aline Tuane Oliveira; Peixoto, Talita do Nascimento; Lima, Severina Carla Vieira Cunha; Sena-Evangelista, Karine Cavalcanti Maurício; Lima, Josivan Gomes; Pedrosa, Lucia Fátima Campos.
Afiliação
  • Lima LCBA; Postgraduate Program in Nutrition, Federal University of Rio Grande do Norte, Av. Salgado Filho, 3000-Lagoa Nova, Natal 59078970, RN, Brazil.
  • Aquino SLS; Postgraduate Program in Health Sciences, Federal University of Rio Grande do Norte, Av. Cordeiro de Farias s/n, Natal 59012-570, RN, Brazil.
  • da Cunha ATO; Collaborative Researcher in Postgraduate Program in Nutrition, Federal University of Rio Grande do Norte, Av. Salgado Filho, 3000-Lagoa Nova, Natal 59078970, Brazil.
  • Peixoto TDN; Postgraduate Program in Health Sciences, Federal University of Rio Grande do Norte, Av. Cordeiro de Farias s/n, Natal 59012-570, RN, Brazil.
  • Lima SCVC; Postgraduate Program in Nutrition, Federal University of Rio Grande do Norte, Av. Salgado Filho, 3000-Lagoa Nova, Natal 59078970, RN, Brazil.
  • Sena-Evangelista KCM; Department of Nutrition, Federal University of Rio Grande do Norte, Av. Salgado Filho, 3000-Lagoa Nova, Natal, RN 59078-970, Brazil.
  • Lima JG; Postgraduate Program in Nutrition, Federal University of Rio Grande do Norte, Av. Salgado Filho, 3000-Lagoa Nova, Natal 59078970, RN, Brazil.
  • Pedrosa LFC; Department of Nutrition, Federal University of Rio Grande do Norte, Av. Salgado Filho, 3000-Lagoa Nova, Natal, RN 59078-970, Brazil.
J Nutr Metab ; 2024: 8821212, 2024.
Article em En | MEDLINE | ID: mdl-38282753
ABSTRACT

Objectives:

To evaluate the associations between individuals with and without changes in components of metabolic syndrome (MetS) and demographic, nutritional, and lifestyle factors.

Methods:

A cross-sectional study was conducted with 224 individuals followed-up at a public hospital in Northeast Brazil. We used National Cholesterol Education Program-Adult Treatment Panel III (NCEP) criteria to diagnose MetS. We assessed components of MetS as dependent variables, while sex, age, food consumption, smoking, alcohol intake, physical activity, anthropometric parameters, and sleep hours were independent variables.

Results:

Comparing individuals with and without changes in components of MetS, the logistic regression models revealed that female sex was predictive of increased waist circumference and low HDL-c levels while advanced age was predictive of increased blood pressure and blood glucose levels. BMI emerged as a predictor for waist circumference and a protective factor for triglyceride levels. In addition, potassium intake, physical activity, and sleep duration were protective against decreased HDL-c, elevated triglyceride, and elevated blood pressure levels, respectively.

Conclusion:

This study demonstrated that sex, age, BMI, dietary potassium intake, physical activity, and hours of sleep are factors to be targeted in public health actions for prevention and treatment of MetS.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Nutr Metab Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Brasil

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Nutr Metab Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Brasil