Cross-validation of anthropometric and bioelectrical resistance prediction equations for body composition in older people using the 4-compartment model as a criterion method

A new approach to quantify visceral fat via bioelectrical impedance analysis and ultrasound compared to MRI

BACKGROUND

Visceral adipose tissue (VAT) has been linked to systemic proinflammatory characteristics, and measuring it accurately usually requires sophisticated instruments. This study aimed to estimate VAT applying a simpler method that uses total subcutaneous fat and total body fat (BF) measurements.

METHOD

As part of our experimental approach, the subcutaneous fat mass (SFT) was measured via US (SFTtotal), and VAT was quantified by assessing MRI data. Both parameters were added to obtain total body fat (BFcalc). Those results were then compared to values obtained from a bioelectrical impedance analysis (BFBIA). Multiple regression analyses were employed to develop a simplified sex-specific equation for SFT, which was subsequently used in conjunction with BFBIA to determine VAT (VATEq).

RESULT

We observed excellent reliability between BFBIA and BFcalc, with no significant difference in body fat values (20.98 ± 8.36 kg vs. 21.08 ± 8.81 kg, p = 0.798, ICC 0.948). VATEq_female/male revealed excellent reliability when compared to VATMRI, and no significant difference appeared (women: 0.03 ± 0.66 kg with a 95% CI ranging from -1.26 kg to 1.32 kg, p = 0.815, ICC: 0.955.; men: -0.01 ± 0.85 kg with a 95% CI ranging from -1.69 kg to 1.66 kg, p = 0.925, ICC: 0.952).

CONCLUSION

Taking an experimental approach, VAT can be determined without MRI.

Predictive equations for fat mass in older Hispanic adults with excess adiposity using the 4-compartment model as a reference method

BACKGROUND

Predictive equations are the best option for assessing fat mass in clinical practice due to their low cost and practicality. However, several factors, such as age, excess adiposity, and ethnicity can compromise the accuracy of the equations reported to date in the literature.

OBJECTIVE

To develop and validate two predictive equations for estimating fat mass: one based exclusively on anthropometric variables, the other combining anthropometric and bioelectrical impedance variables using the 4C model as the reference method.

SUBJECTS/METHODS

This is a cross-sectional study that included 386 Hispanic subjects aged ≥60 with excess adiposity. Fat mass and fat-free mass were measured by the 4C model as predictive variables. Age, sex, and certain anthropometric and bioelectrical impedance data were considered as potential predictor variables. To develop and to validate the equations, the multiple linear regression analysis, and cross-validation protocol were applied.

RESULTS

Equation 1 included weight, sex, and BMI as predictor variables, while equation 2 considered sex, weight, height squared/resistance, and resistance as predictor variables. R2 and RMSE values were ≥0.79 and ≤3.45, respectively, in both equations. The differences in estimates of fat mass by equations 1 and 2 were 0.34 kg and -0.25 kg, respectively, compared to the 4C model. This bias was not significant (p < 0.05).

CONCLUSIONS

The new predictive equations are reliable for estimating body composition and are interchangeable with the 4C model. Thus, they can be used in epidemiological and clinical studies, as well as in clinical practice, to estimate body composition in older Hispanic adults with excess adiposity.

Equation Córdoba: A Simplified Method for Estimation of Body Fat (ECORE-BF)

BACKGROUND

Many methods for measuring body fat have been developed, but applications in clinical settings are limited. For this reason, researchers have tried to identify different formulas for its estimation but most of are hard to incorporate into daily work due to the variability in population and difficulty of use. The aim of this study was to develop and validate a new equation for the simplified estimation of body fat using the Clínica Universidad de Navarra - Body Adiposity Estimator (CUN-BAE) as a reference.

METHODS

This research was conducted in two phases. In the first, the new body fat estimation equation was developed. The developed equation was validated in the second phase. Pearson's linear correlation, raw and adjusted linear regressions, the intraclass correlation coefficient, and Bland-Altman graphs were used.

RESULTS

The variables that best adjusted the body fat percentage were age, sex, and the Napierian logarithm of Body Mass Index (LnBMI), forming the Equation Córdoba for Estimation of Body Fat (ECORE-BF) model. In its validation, the model presented correlation values of 0.994, an intraclass correlation coefficient of 0.960, with the Bland-Altman graph indicating means differences of 1.82 with respect to the estimation with the CUN-BAE. Nevertheless, although the aim was to simplify the CUN-BAE, the main limitation of this study is that a gold standard, such as air displacement plethysmography (ADP) or dual-energy X-ray absorptiometry (DXA), was not used.

CONCLUSIONS

The proposed equation (ECORE-BF) simplified the CUN-BAE and provided a precise method, respecting the principle of parsimony, for the calculation of body fat.

The concurrent validity between leptin, BMI and skin folds during pregnancy and the year after

Background:

From a public health perspective it is important to know which of the currently used methods to estimate changes in maternal body fat during pregnancy and the year thereafter is the most adequate.

Objectives:

To evaluate the concurrent validity between leptin and surrogates of fat measures: body mass index (BMI) and the sum of four skin folds.

Design:

Data from the New Life(style) intervention study were analysed as a cohort study.

Setting:

Midwife practices in The Netherlands.

Population:

Healthy pregnant nulliparous women.

Methods:

Anthropometric measurements were done and blood was collected at 15, 25 and 35 weeks of pregnancy and at 6, 26 and 52 weeks after delivery. Data were used if at least 4 out of the 6 measurements were available, leaving 87 women in the analyses. Spearman's correlation coefficients between leptin and BMI and between leptin and the sum of skin folds were calculated for each time point and for the changes between the time points.

Results:

Correlations between leptin and BMI varied from 0.69 to 0.81. Correlations between leptin and the sum of skin folds were comparable, varying between 0.65 and 0.81.

Correlations between changes in leptin and changes in BMI and the sum of skin folds, respectively, were much lower compared with cross-sectional correlations.

Conclusion:

Because of the high correlation among the three methods and because of the overlapping intervals, all methods seem to be equally adequate to estimate changes in maternal body fat during pregnancy and the year thereafter.

Prediction of fat-free mass by bioelectrical impedance analysis in older adults from developing countries: a cross-validation study using the deuterium dilution method

OBJECTIVE

Several limitations of published bioelectrical impedance analysis (BIA) equations have been reported. The aims were to develop in a multiethnic, elderly population a new prediction equation and cross-validate it along with some published BIA equations for estimating fat-free mass using deuterium oxide dilution as the reference method.

DESIGN AND SETTING

Cross-sectional study of elderly from five developing countries.

METHODS

Total body water (TBW) measured by deuterium dilution was used to determine fat-free mass (FFM) in 383 subjects. Anthropometric and BIA variables were also measured. Only 377 subjects were included for the analysis, randomly divided into development and cross-validation groups after stratified by gender. Stepwise model selection was used to generate the model and Bland Altman analysis was used to test agreement.

RESULTS

FFM = 2.95 - 3.89 (Gender) + 0.514 (Ht2/Z) + 0.090 (Waist) + 0.156 (Body weight). The model fit parameters were an R2, total F-Ratio, and the SEE of 0.88, 314.3, and 3.3, respectively. None of the published BIA equations met the criteria for agreement. The new BIA equation underestimated FFM by just 0.3 kg in the cross-validation sample. The mean of the difference between FFM by TBW and the new BIA equation were not significantly different; 95% of the differences were between the limits of agreement of -6.3 to 6.9 kg of FFM. There was no significant association between the mean of the differences and their averages (r= 0.008 and p= 0.2).

CONCLUSIONS

This new BIA equation offers a valid option compared with some of the current published BIA equations to estimate FFM in elderly subjects from five developing countries.

Validation of bioelectrical impedance for the prediction of fat-free mass in brazilian elderly subjects

Aging involves both nutritional and physiological changes, reducing fat-free mass (FFM) and increasing body fat, both of which are associated with physical weakness, unfitness and morbidity among the elderly. This study was undertaken to analyze the cross-validity of bioelectrical impedance equations for the prediction of fat-free mass (FFM) in elderly Brazilians. A cross-sectional population-based study, was performed in Florianópolis, Santa Catarina, Brazil, 2006. The study sample comprised 60 men and 120 women, aged 60 to 81. The dual energy X-ray absorptiometry (DEXA) served as gold standard. Predicted %BF and FFM were obtained from various anthropometric equations and bioelectric impedance. The cross-validation criteria suggested by Lohman and Bland-Altman plots of differences against the mean were used. The body mass index of the sample ranged from 18.4 to 39.3 kg/m². Mean percent body fat was 23.1 ± 5.8% in men and 37.3 ± 6.9% in women (range: 6 to 51.4%). In men, the equations of Kyle et al. (2001), Dey et al. (2003) and Sun et al. (2003) did not differ significantly from the DEXA measurement, with a constant error (CE) of 0.7 to 2.5 kg. In contrast, among women only the equations of Kyle et al. (2001) and Dey et al. (2003) were found to be valid (CE: 0.3 to 2.7 kg). The bioelectrical impedance equations validated in this study can be used in the Brazilian elderly population.

Skinfold prediction equation for athletes developed using a four-component model

INTRODUCTION

Skinfold (SKF) equations exist to predict percent body fat (%BF) in athletes; however, none have been derived from multicomponent model reference measures.

PURPOSE

To develop and cross-validate a %BF prediction equation based on SKF in athletes using a four-component model as the reference measure.

METHODS

Subjects were 132 collegiate athletes (20.7 +/- 2.0 yr; 78 males: 28 black, 50 white; 54 females: 10 black, 44 white). Four-component model estimates of %BF (%BF4C) included measures of total body water from deuterium dilution, bone mineral by dual- energy x-ray absorptiometry (DXA), and body density by densitometry using underwater weighing. SKF measures included subscapular, triceps, chest, midaxillary, suprailiac, abdominal, and thigh sites (7SKF). A prediction equation was developed on 102 athletes using 7SKF, race, and gender as predictor variables. Cross-validation was performed on a representative holdout sample of 30 athletes.

RESULTS

The equation cross-validated well (slope and intercept both not different (P > 0.05) from the line of identity (LOI); r(YY') = 0.85, total error (TE) = 3.76%BF) and was better than the existing athlete SKF equations (intercept and slope both different from LOI (P < 0.01); r(YY') = 0.76, TE = 4.51%BF). Notably, a prediction equation developed using 3SKF sites (abdomen, thigh, and triceps) produced a similar accuracy (intercept and slope both not different from LOI (P > 0.05); r(YY') = 0.85, TE = 3.66%BF).

CONCLUSIONS

The new 7SKF equation improved on SKF equations developed using densitometry. The final equation based on the whole sample was %BF' = 10.566 + 0.12077*(7SKF) - 8.057*(gender) - 2.545*(race). Moreover, a 3SKF equation was comparable in accuracy to the 7SKF equation: BF' = 8.997 + 0.24658*(3SKF) - 6.343*(gender) - 1.998*(race).

Anthropometric assessment of 10-y changes in body composition in the elderly

BACKGROUND

An increased central distribution of fat with advancing age is associated with chronic metabolic and cardiovascular abnormalities. Little is known about the magnitude or pattern of fat distribution and its association with healthy aging.

OBJECTIVE

This study describes approximately 10-y changes in body composition at 11 anthropometric sites in elderly persons and the metabolic and physical activity factors associated with these changes.

DESIGN

Skinfold thicknesses, girths, body fat by hydrodensitometry, physical activity by questionnaire, and metabolic variables were examined twice, 9.4 +/- 1.4 y apart, in 54 men and 75 women aged 60.4 +/- 7.8 y at baseline.

RESULTS

Subcutaneous fat declined (-17.2%; P < 0.001), whereas total fat mass increased (7.2%; P < 0.05). Waist and hip circumference changes were the best anthropometric predictors of total fat mass change (r(2) = 0.40-0.65, P < 0.0001). Thigh girth change was more strongly associated with fat-free mass change (r(2) = 0.22, P < 0.01) than with fat mass change (r(2) = 0.07, P < 0.05) in women. An increase in physical activity was associated with an attenuation of thigh girth decline in men and women (F ratio = 5.13, P < 0.007). Traditional metabolic markers of visceral adiposity (triacylglycerol, glucose, and total cholesterol) were not significantly related to the change in waist circumference.

CONCLUSIONS

Skinfold thicknesses cannot be used to assess changes in body fat mass because of age-related fat redistribution. Higher levels of physical activity can attenuate the decline in appendicular lean tissue expected over 10 y. Waist and thigh girths, rather than skinfold thicknesses, should be considered for use in longitudinal studies in the elderly because the changes in these girths capture increased abdominal adiposity and sarcopenia, respectively.

Development and validation of skinfold-thickness prediction equations with a 4-compartment model

BACKGROUND

Skinfold-thickness measurements are commonly obtained for the indirect assessment of body composition.

OBJECTIVE

We developed new skinfold-thickness equations by using a 4-compartment model as the reference. Additionally, we compared our new equations with the Durnin and Womersley and Jackson and Pollock skinfold-thickness equations to evaluate each equation's validity and precision.

DESIGN

Data from 681 healthy, white adults were used. Percentage body fat (%BF) values were calculated by using the 4-compartment model. The cohort was then divided into validation and cross-validation groups. Equations were developed by using regression analyses and the 4-compartment model. All equations were then tested by using the cross-validation group. Tests for accuracy included mean differences, R(2), and Bland-Altman plots. Precision was evaluated by comparing root mean squared errors.

RESULTS

Our new equations' estimated means for %BF in men and women (22.7% and 32.6%, respectively) were closest to the corresponding 4-compartment values (22.8% and 32.8%). The Durnin and Womersley equation means in men and women (20.0% and 31.0%, respectively) and the Jackson and Pollock mean in women (26.2%) underestimated %BF. All equations showed a tendency toward underestimation in subjects with higher %BF. Bland-Altman plots showed limited agreement between Durnin and Wormersley, Jackson and Pollock, and the 4-compartment model. Precision was similar among all the equations.

CONCLUSIONS

We developed accurate and precise skinfold-thickness equations by using a 4-compartment model as the method of reference. Additionally, we found that the skinfold-thickness equations frequently used by clinicians and practitioners underestimate %BF.

Hormonal and physiological correlates of energy expenditure and substrate oxidation in middle-aged, premenopausal women

An understanding of the hormonal and physiological correlates of energy expenditure and substrate oxidation in middle-aged women will increase our knowledge of factors that promote changes in energy balance and adiposity. We measured resting and postprandial energy expenditure and substrate oxidation in 59 middle-aged, premenopausal women (mean+/-sD age, 47+/-2 yr) to examine the hormonal and physiological correlates of energy and substrate metabolism. Energy expenditure and substrate oxidation were measured at rest using indirect calorimetry and urinary nitrogen excretion and for 180 min after the ingestion of a liquid meal (10 kcal/kg fat-free mass; 410+/-44 Cal). Fasting hormone levels were measured by RIA, glucose tolerance was determined by a 75-g oral glucose tolerance test, body composition was measured by dual energy x-ray absorptiometry, and peak aerobic capacity was determined by a treadmill test. Using stepwise regression analysis, we found that resting energy expenditure was predicted by fat-free mass and serum leptin concentration (r2 = 66%; P < 0.01), fat oxidation was predicted by resting energy expenditure (r2 = 17%; P < 0.01), and carbohydrate oxidation was predicted by serum leptin and appendicular skeletal muscle mass (r2 = 21%;P < 0.01). Novariables were related to postprandial energy expenditure or substrate oxidation. We conclude that in middle-aged, premenopausal women, variation in resting energy expenditure and substrate oxidation is primarily explained by fat-free mass and serum leptin levels. Thus, changes in metabolically active tissue mass or leptin concentration may partially contribute to changes in resting energy expenditure or substrate oxidation in middle-aged women.