Multimethod training increases portion-size estimation accuracy.
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Adult↗
Biomedical subjects
L B Houtkooper
Publications and source records attributed to L B Houtkooper.
Why bioelectrical impedance analysis should be used for estimating adiposity.
The whole-body bioelectrical impedance analysis (BIA) approach for estimating adiposity and body fat is based on empirical relations established by many investigators. Properly used, this noninvasive body-composition assessment approach can quickly, easily, and relatively inexpensively provide accurate and reliable estimates of fat-free mass (FFM) and total body water (TBW) in healthy populations. The estimated FFM or TBW values are used to calculate absolute and relative body fat amounts. When different investigators follow the same standard BIA procedures and use the same population and criterion method, similar prediction equations and relatively small prediction errors have been reported for measurement of FFM and TBW (SEE: 1.7-3.0 for FFM and 0.23-1.5 kg for TBW). The BIA approach is most appropriate for estimating adiposity of groups in epidemiologic and field studies but has limited accuracy for estimating body composition in individuals. When used as a simple index (stature2/ resistance), BIA is more sensitive and specific for grading average adiposity in groups than some other anthropometric indexes such as the body mass index. Prediction equations based on BIA have been validated and cross-validated in children, youths, adults, and the elderly, in primarily white populations and, to a limited extent, in Asian, black, and Native American populations.
Adipose Tissue↗
Assessment of body composition in youths and relationship to sport.
Body composition assessment techniques provide estimates of percent body fat (%BF), fat mass (FM), and fat-free mass (FFM) based on indirect assessment models and methods. Prediction equations for %BF developed using a two-component model based on adult body composition constants with overestimate %BF in youths, especially prepubescent youths. Body composition prediction equations that have been validated and cross-validated using multiple-component criterion models which include measurements of body density and the water and mineral components of FFM provide the most accurate means for assessment of body composition in youths. Use of appropriate prediction equations and proper measurement techniques, for either bioelectrical impedance or skinfolds, results in body composition estimates with standard errors of estimate (prediction errors) of 3 to 4% BF and 2.0 to 2.5 kg of FFM. Poor measurement technique and inappropriate prediction equations will result in much larger prediction errors.
Adipose Tissue↗
Nutrients, body composition and exercise are related to change in bone mineral density in premenopausal women.
This study determined relationships among total energy intake, nutrient intake, body composition, exercise group status, and annual rates of change (slopes) in bone mineral density in 66 Caucasian premenopausal women (mean age, 34.4 +/- 2.7) taking calcium supplements. Body composition components measured by dual-energy X-ray absorptiometry included fat mass, soft tissue lean mass, and bone mineral density (g/cm2) of total body, spine (lumbar vertebrae 2-4), and three femur sites measured at baseline, 5, 12, and 18 mo. Nutrients were not significant variables in regression models predicting bone mineral density slopes (rates of change) at any femur site. The only significant variable in models predicting Ward's triangle bone mineral density slope was the initial fat mass and, for trochanter, exercise. Significant variables (P < 0.05) in models predicting total body bone mineral density slope included the initial fat mass and fat mass slope plus either vitamin A, carotene, fiber, magnesium, or phosphorus (R2 from 0.31 to 0.25) and fat mass slope plus sodium (R2 = 0.24). The significant variable in the model predicting L2-4 slope was energy intake (R2 = 0.17, P < 0.05). We conclude that nutrient intake, exercise, and body composition are related to bone mineral density rate of change and that relations among these variables vary by bone site.
Absorptiometry, Photon↗
Resistance exercise training is associated with decreases in serum low-density lipoprotein cholesterol levels in premenopausal women.
BACKGROUND: Aerobic exercise training is associated with reduced serum concentrations of triglycerides, increased concentrations of high-density lipoprotein cholesterol, and minimal changes in serum levels of total cholesterol or low-density lipoprotein cholesterol. There are few data on the effects of resistance exercise on blood lipid levels. METHODS: Premenopausal women were randomly assigned to a supervised resistance exercise training program (n = 46) or a control group (n = 42) for 5 months. Serum was analyzed for levels of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides. Body composition and dietary intake were also measured. RESULTS: The exercise group showed a 0.33 +/- 0.03-mmol/L (mean +/- SE) decrease in total cholesterol level and a 0.36 +/- 0.001-mmol/L decrease in low-density lipoprotein cholesterol level that was significantly different from the control group. No significant changes were noted in serum high-density lipoprotein cholesterol or triglyceride levels in either group. Changes in body composition showed no significant correlations with changes in total cholesterol or low-density lipoprotein cholesterol. There were no significant differences in nutrient intake between the groups. CONCLUSION: In healthy, premenopausal women, with normal baseline lipid profiles, 5 months of resistance exercise training was associated with significant decreases in serum total cholesterol and low-density lipoprotein cholesterol concentrations.
Adult↗
Prediction of body composition in premenopausal females from dual-energy X-ray absorptiometry.
Four methods for predicting body composition were compared in premenopausal females (n = 100), 28-39 yr old, by using underwater weighing (UWW) as the criterion method. The four methods were dual energy X-ray absorptiometry (DEXA), skinfolds, bioelectrical impedance, and body mass index. The sample had a mean percent fat (%fat) of 29.7 +/- 6.8% (SD) by DEXA and 29.9 +/- 5.8% measured by UWW. DEXA yielded a standard error of estimate (SE) of 2.4% (r = 0.91) for the prediction of %fat from UWW. When %fat was estimated from other methods, larger SEs were obtained: 3.0% for skin-folds, 3.3% for body mass index, and 2.9% for bioelectrical impedance (height2/resistance) plus weight. Individual body density values derived from UWW were corrected for bone mineral variation. DEXA predicted the corrected body density with a lower SE (0.0040 vs. 0.0053 g/ml) than the original density values. We conclude that DEXA was a precise method and correlated highly with fat-free body weight and %fat from UWW in this homogeneous female sample.
Absorptiometry, Photon↗
Bioelectrical impedance estimation of fat-free body mass in children and youth: a cross-validation study.
The purposes of this study were to develop and cross-validate the "best" prediction equations for estimating fat-free body mass (FFB) from bioelectrical impedance in children and youth. Predictor variables included height2/resistance (RI) and RI with anthropometric data. FFB was determined from body density (underwater weighing) and body water (deuterium dilution) (FFB-DW) and from age-corrected density equations, which account for variations in FFB water and bone content. Prediction equations were developed using multiple regression analyses in the validation sample (n = 94) and cross-validated in three other samples (n = 131). R2 and standard error of the estimate (SEE) values ranged from 0.80 to 0.95 and 1.3 to 3.7 kg, respectively. The four samples were then combined to develop a recommended equation for estimating FFB from three regression models. R2 and SEE values and coefficients of variation from these regression equations ranged from 0.91 to 0.95, 2.1 to 2.9 kg, and 5.1 to 7.0%, respectively. As a result of all cross-validation analyses, we recommend the equation FFB-DW = 0.61 RI + 0.25 body weight + 1.31, with a SEE of 2.1 kg and adjusted R2 of 0.95. This study demonstrated that RI with body weight can predict FFB with good accuracy in Whites 10-19 yr old.
Adipose Tissue↗
Validity of bioelectric impedance for body composition assessment in children.
Whole-body bioelectrical impedance analysis (BIA) was evaluated for its reliability and accuracy in estimating body composition in children. The hypothesis that the index, body height2 divided by resistance (RI), can accurately predict fat-free body mass (FFB) and percent fat (%FAT) in children was tested on 94 caucasian children 10-14 yr old. Criterion variables were FFB and %FAT estimated using multicomponent equations developed for children. BIA measurements (resistance and reactance) were found to be reliable. Prediction accuracy (standard error of the estimate, SEE) for FFB from RI alone was 2.6 kg and for %FAT from RI and body weight was 4.2%. For RI, anthropometric variables and reactance, the SEE improved to 1.9 kg FFB. For RI and anthropometric variables, the SEE was 3.3% FAT. For anthropometric variables alone, the SEE's were 2.1 kg FFB and 3.2% FAT. Adult FFB and %FAT prediction equations cross-validated with this sample resulted in SEE's similar to those for adult samples. We conclude that RI together with anthropometry is a reliable and an acceptably accurate method of estimating FFB mass and %FAT in children.
Adipose Tissue↗