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SENSITIVITY AND SPECIFICITY OF ACCESSIBLE, LOW COST BUT LITTLE USE ANTHROPOMETRIC PREDICTORS TO IDENTIFY CARDIOVASCULAR RISK IN INDIGENOUS WOMEN IN SOCIALFOOD VULNERABILITY

Introduction: By 2030 it is estimated that more than 23 million people will die from Cardiovascular Disease (CVD). CVD impacts public-health by raising costs on family and health systems. In Mexico, CVD is the fourth cause of premature mortality in adults 34-44 years, the third in 45-54 years and th...

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Bibliographic Details
Published in:Annals of nutrition and metabolism 2020-01, Vol.76, p.178
Main Authors: Guzmán-Márquez, M C, Benítez-Arciniega, A D, Vizcarra-Bordi, I, Ochoa-Rivera, T
Format: Article
Language:English
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Summary:Introduction: By 2030 it is estimated that more than 23 million people will die from Cardiovascular Disease (CVD). CVD impacts public-health by raising costs on family and health systems. In Mexico, CVD is the fourth cause of premature mortality in adults 34-44 years, the third in 45-54 years and the first from 65. Framingham-Risk-Scale (FRS), is widely used by linking biochemical and clinical data to calculate CVD risk (CVDr), however the difficulty of having biochemical data, leads to the need to develop anthropometric tools with high-sensitivity and specificity to predict it, especially in vulnerable groups with restricted access to health services. Anthropometric indicators (AI) such as waistcircumference (WC), waist-height-index (WHI) and conicityindex (CoI) are proposed as accessible predictors to estimate CVDr. Receiver-Operating-Characteristics (ROC) curves, compare the predictive skill of diagnostic methods using graphical representation under the focus of balancing sensitivity and specificity as well as obtaining cut-off points that support the diagnosis. Objective: to assess predictive-capacity of three AI for the identification of CVDr in Matlatzinca women, who have high levels of poverty and social inequality, hindering their access to CVD biomarkers. Methods: Population-based cross-sectional study in 93 indigenous women. CVDr was estimated using FRS as reference method, comparing it with WC, CoI and WHI. ROCcurves were obtained identifying cut-off points, area under the curve, sensitivity and specificity for each anthropometric indicator. Results: Breakpoints and AUC for each AI were: WHI-0.63 (0.763), CoI-1.29 (0.756) and WC-91 (0.663). Conclusions: In this population, WHI presented greater power of discrimination, considering it the best predictor of CVD risk because of its high sensitivity.
ISSN:0250-6807
1421-9697