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Does Waist Indicate Dyslipidemia better than BMI in Korean Adult Population?
Obesity is an independent and modifiable risk factor for cardiovascular disease, and known as a core of the metabolic syndrome. Obesity has been largely diagnosed based upon anthrompometric measurements like waist circumference (WC) and body mass index (BMI). We sought to determine associations betw...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
The Korean Academy of Medical Sciences
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808579/ https://www.ncbi.nlm.nih.gov/pubmed/15716594 http://dx.doi.org/10.3346/jkms.2005.20.1.7 |
Sumario: | Obesity is an independent and modifiable risk factor for cardiovascular disease, and known as a core of the metabolic syndrome. Obesity has been largely diagnosed based upon anthrompometric measurements like waist circumference (WC) and body mass index (BMI). We sought to determine associations between anthropometric measurements and dyslipidemia in a community adult sample composed of 1,032 community residents (356 men, 676 women) aged 50 yr and over in Namwon, Korea. Blood tests for lipid profiles, including total cholesterol (TC) and HDL cholesterol (HDL) were performed, and dyslipidemia was defined as TC/HDL greater than 4. Anthropometric measurements included WC, waist-to-height ratio (WHtR), waist-to-hip ratio, and BMI. All anthropometric measures were categorized into quartiles and evaluated for associations with dyslipidemia. TC/HDL showed the significant associations with the anthropometric measures, independently of potential confounders. In women, increases of obesity indexes by quartile analyses showed linear increases of odds ratios for dyslipidemia (p values <0.01 by trend test). In men, except BMI, same patterns of association were noted. WC and WHtR were significantly associated with dyslipidemia in Korean adult population. As a simple and non-invasive method for a detection of obesity and dyslipidemia, anthropometric measurements could be efficiently used in clinical and epidemiologic fields. |
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