Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Byambasukh O

PROVIDER: S-EPMC6545622 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Byambasukh Oyuntugs O Eisenga Michele F MF Gansevoort Ron T RT Bakker Stephan Jl SJ Corpeleijn Eva E

European journal of preventive cardiology 20190221 9

<h4>Aims</h4>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.<h4>Methods and results</h4>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) ...[more]

PMID: 30791699

Similar Datasets

Project description:Dual-energy X-ray absorptiometry (DXA) has been considered a reference method for measuring body fat percentage (BF%) in children and adolescents with an excess of adiposity. However, given that the DXA technique is impractical for routine field use, there is a need to investigate other methods that can accurately determine BF%. We studied the accuracy of bioelectrical impedance analysis (BIA) technology, including foot-to-foot and hand-to-foot impedance, and Slaughter skinfold-thickness equations in the measurement of BF%, compared with DXA, in a population of Latin American children and adolescents with an excess of adiposity. A total of 127 children and adolescents (11?17 years of age; 70% girls) from the HEPAFIT (Exercise Training and Hepatic Metabolism in Overweight/Obese Adolescent) study were included in the present work. BF% was measured on the same day using two BIA analysers (Seca® 206, Allers Hamburg, Germany and Model Tanita® BC-418®, TANITA Corporation, Sportlife Tokyo, Japan), skinfold measurements (Slaughter equation), and DXA (Hologic Horizon DXA System®, Quirugil, Bogotá, Columbia). Agreement between measurements was analysed using t-tests, Bland?Altman plots, and Lin's concordance correlation coefficient (?c). There was a significant correlation between DXA and the other BF% measurement methods (r > 0.430). According to paired t-tests, in both sexes, BF% assessed by BIA analysers or Slaughter equations differ from BF% assessed by DXA (p < 0.001). The lower and upper limits of the differences compared with DXA were 6.3?22.9, 2.2?2.8, and -3.2?21.3 (95% CI) in boys and 2.3?14.8, 2.4?20.1, and 3.9?18.3 (95% CI) in girls for Seca® mBCA, Tanita® BC 420MA, and Slaughter equations, respectively. Concordance was poor between DXA and the other methods of measuring BF% (?c < 0.5). BIA analysers and Slaughter equations underestimated BF% measurements compared to DXA, so they are not interchangeable methods for assessing BF% in Latin American children and adolescents with excess of adiposity.

Project description:BackgroundBioelectrical impedance analysis (BIA) is a potentially valuable method for assessing lean mass and body fat levels in children from different ethnic groups. We examined the need for ethnic- and gender-specific equations for estimating fat free mass (FFM) from BIA in children from different ethnic groups and examined their effects on the assessment of ethnic differences in body fat.MethodsCross-sectional study of children aged 8-10 years in London Primary schools including 325 South Asians, 250 black African-Caribbeans and 289 white Europeans with measurements of height, weight and arm-leg impedance (Z; Bodystat 1500). Total body water was estimated from deuterium dilution and converted to FFM. Multilevel models were used to derive three types of equation {A: FFM?=?linear combination(height+weight+Z); B: FFM?=?linear combination(height(2)/Z); C: FFM?=?linear combination(height(2)/Z+weight)}.ResultsEthnicity and gender were important predictors of FFM and improved model fit in all equations. The models of best fit were ethnicity and gender specific versions of equation A, followed by equation C; these provided accurate assessments of ethnic differences in FFM and FM. In contrast, the use of generic equations led to underestimation of both the negative South Asian-white European FFM difference and the positive black African-Caribbean-white European FFM difference (by 0.53 kg and by 0.73 kg respectively for equation A). The use of generic equations underestimated the positive South Asian-white European difference in fat mass (FM) and overestimated the positive black African-Caribbean-white European difference in FM (by 4.7% and 10.1% respectively for equation A). Consistent results were observed when the equations were applied to a large external data set.ConclusionsEthnic- and gender-specific equations for predicting FFM from BIA provide better estimates of ethnic differences in FFM and FM in children, while generic equations can misrepresent these ethnic differences.

Project description:BACKGROUND: The measurements of body mass index (BMI) and percentage of body fat are used in many clinical situations. However, special tools are required to measure body fat. Many formulas are proposed for estimation but these use constant coefficients of age. Age spectrum might affect the predicted value of the body composition due to body component alterations, and the coefficient of age for body fat prediction might produce inconsistent results. The objective of this study was to identify variations of BMI and body fat across the age spectrum as well as compare results between BMI predicted body fat and bioelectrical impedance results on age. METHODS: Healthy volunteers were recruited for this study. Body fat was measured by bioelectrical impedance. The age spectrum was divided into three groups (younger: 18-39.9; middle: 40-59.9; and older: ≥60 years). Comparison of body composition covariates including fat mass (FM), fat free mass (FFM), percentage FM (PFM), percentage FFM (PFFM), FM index (FMI) and FFM index (FFMI) in each weight status and age spectrum were analyzed. Multivariable linear regression coefficients were calculated. Coefficient alterations among age groups were tested to confirm the effect of the age spectrum on body composition covariates. Measured PFM and calculated PFM from previous formulas were compared in each quarter of the age spectrum. RESULTS: A total of 2324 volunteers were included in this study. The overall body composition and weight status, average body weight, height, BMI, FM, FFM, and its derivatives were significantly different among age groups. The coefficient of age altered the PFM differently between younger, middle, and older groups (0.07; P = 0.02 vs 0.13; P < 0.01 vs 0.26; P < 0.01; respectively). All coefficients of age alterations in all FM- and FFM-derived variables between each age spectrum were tested, demonstrating a significant difference between the younger (<60 years) and older (≥60 years) age groups, except the PFFM to BMI ratio (difference of PFM and FMI [95% confidence interval]: 17.8 [12.8-22.8], P < 0.01; and 4.58 [3.4-5.8], P < 0.01; respectively). The comparison between measured PFM and calculated PFM demonstrated a significant difference with increments of age. CONCLUSION: The relationship between body FM and BMI varies on the age spectrum. A calculated formula in older people might be distorted with the utilization of constant coefficients.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets