Cargando…

Prevalence of the Metabolic Syndrome in Central and South American Immigrant Residents of the Washington, DC, Area

The objective of this study was to estimate the prevalence of Metabolic Syndrome (MetS) and its risk components and then compare differences in the risk components among low-income, uninsured Central and South American recent immigrants to the USA. This cross-sectional survey sampled 1,042 adult pat...

Descripción completa

Detalles Bibliográficos
Autores principales: Gill, Regina M., Khan, Saira A., Jackson, Robert T., Duane, Marguerite
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5514324/
https://www.ncbi.nlm.nih.gov/pubmed/28744376
http://dx.doi.org/10.1155/2017/9531964
Descripción
Sumario:The objective of this study was to estimate the prevalence of Metabolic Syndrome (MetS) and its risk components and then compare differences in the risk components among low-income, uninsured Central and South American recent immigrants to the USA. This cross-sectional survey sampled 1,042 adult patients from a medical clinic in metropolitan Washington, DC. The overall prevalence of the MetS was 26.9% estimated using the modified harmonized definition. The most common abnormal metabolic indicator for women was an elevated BMI ≥ 30 kg/m(2) (36.1%), while, for men, it was an elevated triglyceride level (46.5%). The risk of abnormal MetS indicators increased steadily with increasing BMI. The abnormal indicator combination identifying the most subjects with the MetS included the following: high triglycerides, low HDL cholesterol, and obesity. MetS rates were highest among subjects from El Salvador and Honduras, 31.3% and 28.0%, respectively, and lowest among subjects from Bolivia (21.7%). Dyslipidemia and high BMI increased the likelihood of having the MetS, which is consistent with studies on Mexican Americans in the San Antonio Heart Study and studies within Central and South American countries. This study adds new baseline epidemiological data for largely understudied, low-income, and mostly recent immigrant groups.