scholarly journals Body fat estimates from bioelectrical impedance equations in cardiovascular risk assessment: The PREVEND cohort study

2019 ◽  
Vol 26 (9) ◽  
pp. 905-916 ◽  
Author(s):  
Oyuntugs Byambasukh ◽  
Michele F Eisenga ◽  
Ron T Gansevoort ◽  
Stephan JL Bakker ◽  
Eva Corpeleijn

Aims To investigate prospectively the association of body fat percentage (BF%) estimates using various equations from bioelectrical impedance analysis (BIA) with cardiovascular events, compared with body mass index (BMI) and waist circumference. Methods and results We used data of 34 BIA-BF%-equations that were used for estimation of BF% in 6486 (men = 3194, women = 3294) subjects. During a median follow-up of 8.3 years, 510 (7.9%) cardiovascular events (363 in men; 147 in women) occurred. In men, the crude hazard ratio (95% confidence interval) for BF% from the best predicting BIA-BF%-equation was 3.97 (3.30–4.78) against 2.13 (1.85–2.45) for BF% from the BIA device's BIA-BF%-equation, 1.34 (1.20–1.49) for BMI and 1.49 (1.40–1.73) for waist circumference per log-1-SD increase of all. In women, the hazard ratios for best predicting BIA-BF%-equation, BIA device estimation, BMI and waist circumference were 3.80 (2.85–4.99), 1.89 (1.57–2.28), 1.35 (1.21–1.51) and 1.52 (1.31–1.75), respectively. After adjustments for age, Framingham cardiovascular disease risk score and creatinine excretion – a marker of muscle mass – BF%s and BMI remained independently associated with cardiovascular events in both men and women, while waist circumference was independently associated with cardiovascular events in men, but not in women. According to discrimination ability (C-index) and additive predictive value (net reclassification index and integrated discrimination index) on obesity measures to the Framingham cardiovascular disease risk score, BF% was superior to BMI and waist circumference in both men and women. Conclusions BF% was independently associated with future cardiovascular events. Body fat estimates from the best-predicting BIA-BF%-equations can be a more predictive measurement in cardiovascular risk assessment than BMI or waist circumference.

2011 ◽  
Vol 22 (2) ◽  
pp. 162-169 ◽  
Author(s):  
Patrícia F. Pereira ◽  
Hiara M. S. Serrano ◽  
Gisele Q. Carvalho ◽  
Joel A. Lamounier ◽  
Maria do Carmo G. Peluzio ◽  
...  

AbstractBackground:Excessive body fat, mainly abdominal fat, is associated with higher cardiovascular risk. However, a fat localisation measurement that would be more indicative of risk in adolescents has not yet been established.Objective:This study was conducted in order to evaluate the correlation between body fat location measurements and cardiovascular disease risk factors in female adolescents.Materials and methods:A total of 113 girls – 38 eutrophic according to their body mass index but with a high percentage of body fat, 40 eutrophic with adequate body fat, and 35 with excessive weight – were evaluated using 15 anthropometrical measurements and 10 cardiovascular risk factors.Results:The central skinfold was the best measurement for predicting variables such as glycaemia and high-density lipoprotein; waist circumference for insulin and homeostasis model assessment; coronal diameter for total cholesterol and low-density lipoprotein; sagittal abdominal diameter for triglycerides and leptin; hip circumference for blood pressure; and the central/peripheral skinfold ratio for homocysteine. The correlation between the measurements and the number of risk factors showed that waist circumference and the waist/stature ratio produced the best results.Conclusions:The results suggest that the body fat distribution in adolescents is relevant in the development of cardiovascular risk factors. Simple measurements such as waist circumference and the waist/stature ratio were the best predictors of a risk of disease and they should therefore be associated with the body mass index in clinical practice in order to identify those adolescents at higher risk.


2012 ◽  
Vol 87 (5) ◽  
pp. 452-460 ◽  
Author(s):  
Tiago V. Barreira ◽  
Amanda E. Staiano ◽  
Deirdre M. Harrington ◽  
Steven B. Heymsfield ◽  
Steven R. Smith ◽  
...  

Nova ◽  
2015 ◽  
Vol 13 (24) ◽  
pp. 7 ◽  
Author(s):  
Leonardo Yunda ◽  
David Pacheco ◽  
Jorge Millan

<p>Developing a Web-based Fuzzy Inference Tool for cardiovascular risk assessment. The tool uses evidence-based medicine inference rules for membership classification. <strong>Methods</strong>. The system framework allows adding variables such as gender, age, weight, height, medication intake, and blood pressure, with various types of membership functions based on classification rules. <strong>Results</strong>. By inputting patient clinical data, the tool allows health professionals to obtain a prediction of cardiovascular risk. The tool can also be later used to predict other types of risks including cognitive and physical disease conditions.</p>


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