全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Anthropometric Indices Added the Predictive Ability of Iron Status in Prognosis of Atherosclerosis

DOI: 10.5681/hpp.2012.025

Keywords: Anthropometric , Iron , Atherosclerosis , Predictive Ability , IDI , NRI

Full-Text   Cite this paper   Add to My Lib

Abstract:

Background: Abnormal homeostasis of iron such as deficiency or overload is associated with the pathogenesis of cardiovascular disease (CVD). Another risk factor for CVD is obesity whose added predictive ability to iron status has been assessed by few study. This study aimed to eva-luate the effect of adding anthropometric indices to a model based on iron status as risk factors of CVD.Methods: This cross-sectional study included 140 adult women aged 18-50 years randomly se-lected from Sheikhorrais Clinic that is one of the Tabriz University sub-specialized clinics in 2011. Anthropometric indices, carotid intima-media thickness (CIMT) and body iron status were measured by standard protocol, non-invasive ultrasound and concentrations of serum iron, ferri-tin, TIBC (Total iron Binding Capacity) and complete blood cell counts (CBC), respectively. In-tegrated discriminatory improvement index (IDI) and net reclassification improvement index (NRI) were used as the measures of added predictive ability of anthropometric measures to the iron statues.Results: IDI (SE) after adding Waist Circumference (WC), Waist to Heap Ratio (WHR), Waist to Height Ratio (WHtR), Body Mass Index (BMI) and Body fat (%) to base model was 0.12 (0.028), 0.09 (0.026), 0.12 (0.028), 0.07 (0.022) and 0.10 (0.026) respectively. The NRI (SE) was 0.10 (0.065) for WC, 0.03 (0.058) for WHR, 0.07 (0.067) for WHtR, 0.05 (0.067) for BMI, and 0.08 (0.064) for Body fat.Conclusions: Anthropometric indices could significantly add to the predictive ability of the iron statues, with highest IDI when WC and WHtR were added to the base model. It suggests that by adding WC and WHtR to the iron status lead us to a more optimal model for predicting the ini-tial stage of atherosclerosis.

Full-Text

comments powered by Disqus

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133

WeChat 1538708413