Anthropometric parameter that best predict metabolic syndrome in postmenopausal women.
DOI:
https://doi.org/10.3329/jssmc.v14i2.73170Keywords:
Anthropometric, Menopause, Metabolic syndrome, Postmenopausal womenAbstract
Background: The use of anthropometric parameter is one of the new and low-cost diagnostic methods of detection of metabolic syndrome.
Aims and objectives: The objective of the present study was to examine the predictive power of many anthropometric parameters as an accurate predictor for MS in postmenopausal women.
Material and Methods: This cross sectional study involved 199 postmenopausal women. Six anthropometric parameters : Waist circumference (WC), body mass index (BMI), waist-to-height ratio (WHtR), waist to hip ratio (WHR), lipid accumulation product (LAP) and visceral adiposity index (VAI) were measured and calculated. Metabolic syndrome (MS) was defined according to the criteria of NCEP-ATP III. The women were devided into two groups based on presence or absence of metabolic syndrome. Comparisons of clinical and metabolic characteristics were performed between the groups. To analyze the correlation of anthropometric parameters with MS Spearmann test was used. The cut-off points, area under the curve (AUC), sensitivity and specificity of parameters were determined using Receiver Operating Characteristic Curve (ROC).
Results: The prevalence of MS in postmenopausal women was 74.4%. Visceral adiposity index (VAI), Lipid accumulation product (LAP), waist circumference (WC), Body mass index (BMI) and waist to height ratio (WHtR) were significantly higher in women with MS. Among the anthropometric parameters assessed mainly VAI and LAP showed a significant correlation with the majority of MS criteria. Through ROC curves VAI, LAP and WC presented higher AUC being the cut- off points followed :0.85, 0.83 and 0.75 respectively. This study has shown the postmenopausal women had a high prevalence of MS and VAI and LAP regarded as most sensitive and specific predictors for MS in post menopausal women.
J Shaheed Suhrawardy Med Coll 2022; 14(2): 18-24
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