Assessing Body Composition among 3‐ to 8‐Year‐Old Children: Anthropometry,BIA, and DXA

Objective: To examine the inter‐relationships of body composition variables derived from simple anthropometry [BMI and skinfolds (SFs)], bioelectrical impedance analysis (BIA), and dual energy x‐ray (DXA) in young children. Research Methods and Procedures: Seventy‐five children (41 girls, 34 boys) 3 to 8 years of age were assessed for body composition by the following methods: BMI, SF thickness, BIA, and DXA. DXA served as the criterion measure. Predicted percentage body fat (%BF), fat‐free mass (FFM; kilograms), and fat mass (FM; kilograms) were derived from SF equations [Slaughter (SL)1 and SL2, Deurenberg (D) and Dezenberg] and BIA. Indices of truncal fatness were also determined from anthropometry. Results: Repeated measures ANOVA showed significant differences among the methods for %BF, FFM, and FM. All methods, except the D equation (p = 0.08), significantly underestimated measured %BF (p < 0.05). In general, correlations between the BMI and estimated %BF were moderate (r = 0.61 to 0.75). Estimated %BF from the SL2 also showed a high correlation with DXA %BF (r = 0.82). In contrast, estimated %BF derived from SFs showed a low correlation with estimated %BF derived from BIA (r = 0.38); likewise, the correlation between DXA %BF and BIA %BF was low (r = 0.30). Correlations among indicators of truncal fatness ranged from 0.43 to 0.98. Discussion: The results suggest that BIA has limited utility in estimating body composition, whereas BMI and SFs seem to be more useful in estimating body composition during the adiposity rebound. However, all methods significantly underestimated body fatness as determined by DXA, and, overall, the various methods and prediction equations are not interchangeable.     

Bioelectrical impedance underestimates total and truncal fatness in abdominally obese women

Objective: To compare estimates of total and truncal fatness from eight‐electrode bioelectrical impedance analysis equipment (BIA₈) with those from DXA in centrally obese women. The secondary aim was to examine BMI and waist circumference (WC) as proxy measures for percentage total body fat (%TBF) and truncal body fat percentage (tr%BF). Research Methods and Procedures: This was a cross‐sectional study of 136 women (age, 48.1 ± 7.7 years; BMI, 30.4 ± 2.9 kg/m²; %TBF_DXA, 46.0 ± 3.7%; WC, 104 ± 8 cm). Fatness was measured by DXA and Tanita BC‐418 equipment (Tanita Corp., Tokyo, Japan). Agreement among methods was assessed by Bland‐Altman plots, and regression analysis was used to evaluate anthropometric measures as proxies for total and abdominal fatness. Results: The percentage of overweight subjects was 41.9%, whereas 55.9% of the subjects were obese, as defined by BMI, and all subjects had a WC exceeding the World Health Organization cut‐off point for abdominal obesity. Compared with DXA, the BIA₈ equipment significantly underestimated total %BF (?5.0; ?3.6 to ?8.5 [mean; 95% confidence interval]), fat mass (?3.6; ?3.9 to ?3.2), and tr%BF (?8.5; ?9.1 to ?7.9). The discrepancies between the methods increased with increasing adiposity for both %TBF and tr%BF (both p < 0.001). Variation in BMI explained 28% of the variation in %TBF_DXA and 51% of %TBF_BIA8. Using WC as a proxy for truncal adiposity, it explained only 18% of tr%BF_DXA variance and 27% of tr%BF_BIA8 variance. The corresponding figures for truncal fat mass were 49% and 35%, respectively. No significant age effects were observed in any of the regressions. Discussion: BIA₈ underestimated both total and truncal fatness, compared with DXA, with higher dispersion for tr%BF than %TBF. The discrepancies increased with degree of adiposity, suggesting that the accuracy of BIA is negatively affected by obesity.     

A quantitative trait locus for body fat on chromosome 1q43 in French Canadians: linkage and association studies

Objective: To explore a quantitative trait locus (QTL) on human chromosome 1q affecting BMI, adiposity, and fat‐free mass phenotypes in the Quebec Family Study cohort. Research Methods and Procedures: Non‐parametric sibpair and variance component linkage analyses and family‐based association studies were performed with a dense set of chromosome 1q43 microsatellites and single‐nucleotide polymorphism markers in 885 adult individuals. Results: Linkage was observed between marker D1S184 and BMI (p = 0.0004) and with body fat mass or percentage body fat (p ≤ 0.0003), but no linkage was detected with fat‐free mass. Furthermore, significant linkages (p < 0.0001) were achieved with subsamples of sibpairs at both ends of phenotype distributions. Association studies with quantitative transmission disequilibrium tests refined the linkage to a region overlapping the regulator of G‐protein signaling 7 (RGS7) gene and extending to immediate upstream gene loci. Discussion: The present study indicates that the QTL on chromosome 1q43 specifically affects total adiposity and provides a genetic mapping framework for the dissection of this adiposity locus.     

Comparison of body composition methods in obese African-American women

Objective : To compare the accuracy of percentage body fat (%BF) estimates between bioelectrical impedance analysis (BIA) and DXA in obese African‐American women. Research Methods and Procedures : Fifty‐five obese African‐American women (mean age, 45 years; mean BMI, 38; mean %BF, 48%) were studied. BF was assessed by both BIA (RJL Systems BIA 101Q; RJL Systems, Clinton Township, MI) and DXA (Hologic QDR‐2000 Bone Densitometer; Hologic Inc., Bedford, MA). Generalized and ethnicity‐ and obese‐specific equations were used to calculate %BF from the BIA. Bland‐Altman analyses were used to compare the agreement between the BIA and the DXA, with the DXA serving as the criterion measure. Results : Two of the generalized equations provided consistent estimates across the weight range in comparison with the DXA estimates, whereas most of the other equations increasingly underestimated %BF as BF increased. One of the generalized and one of the ethnicity‐specific equations had mean differences that were not significantly different from the DXA value. Discussion : The findings show that the Lukaski equation provided the most precise and accurate estimates of %BF in comparison with the QDR 2000 and provide preliminary support for the use of this equation for obese African‐American women.     

Physical Activity as a Predictor of Body Composition in American Indian Children

Objective: To examine physical activity in second grade American Indian children as a predictor of percentage body fat 3 years later. Research Methods and Procedures: Physical activity was assessed as average vector magnitude (AVM) counts from an accelerometer in 454 second grade children as part of the Pathways study. BMI was assessed, and skinfolds and bioelectrical impedance were used to estimate fat mass, fat‐free body mass, and percentage body fat in validated prediction equations. Associations were examined using mixed models regression controlling for baseline body composition. Results: In normal‐weight children, higher AVM counts were significantly associated with decreases in percentage body fat. Among overweight children, higher AVM counts were significantly associated with increases in BMI, fat mass, and fat‐free mass but not percentage body fat. Discussion: Higher physical activity levels in second grade were associated with lower levels of percentage body fat in fifth grade in normal‐weight but not in overweight children. BMI showed no association with physical activity among normal‐weight children, and increases in BMI were associated with increasing amounts of physical activity among overweight children. These findings emphasize the importance of valid body composition measures and may indicate important differences in associations between physical activity and adiposity in normal‐weight as compared with overweight children.     

Comparability of Resting Energy Expenditure in Nigerians and U.S. Blacks

Objective: To determine the influence of environmental factors on resting energy expenditure (REE) and its relationship to adiposity in two populations of West African origin, Nigerians and U.S. blacks. Research Methods and Procedures: REE and body composition were measured in a cross‐sectional sample of 89 Nigerian adults (39 women and 50 men), and 181 U.S. black adults (117 women and 65 men). Both groups represent randomly selected population samples. REE was measured by indirect calorimetry after an overnight fast in both sites using the same instrument. Body composition was estimated using bioelectrical impedance analysis (BIA) in 72 Nigerians and 156 U.S. participants. Multivariate regression analysis was used to determine the significant predictors of REE. The analyses were repeated in a set of 17 Nigerians and 28 U.S. blacks in whom body composition was measured using deuterium dilution. Results: U.S. black adults were significantly heavier and had both more fat‐free mass (FFM) and body fat than Nigerians. FFM was the only significant determinant of REE in both population groups, whether body composition was measured using BIA or deuterium dilution. The relationship between REE and body composition did not differ by site. There was no relationship between REE and adiposity. Discussion: Differences in current environmental settings did not impact REE. The differences observed in mean levels of body fat between Nigerians and U.S. blacks were not the result of differences in REE adjusted for body composition.     

Waist circumference correlates with metabolic syndrome indicators better than percentage fat

Objective : Percent fat is often considered the reference for establishing the magnitude of adipose tissue accumulation and the risk of excess adiposity. However, the increasing recognition of a strong link between central adiposity and metabolic disturbances led us to test whether waist circumference (WC) is more highly correlated with metabolic syndrome components than percent fat and other related anthropometric measures such as BMI. Research Methods and Procedures : BMI, WC, and percent fat, measured by DXA, were evaluated in 1010 healthy white and African‐American men and women [age, 48.3 ± 17.2 (standard deviation) years; BMI, 27.0 ± 5.3 kg/m²]. The associations of BMI, WC, and percent fat with age and laboratory‐adjusted health risk indicators (i.e., serum glucose, insulin, triglycerides, high‐density lipoprotein cholesterol, blood pressure) in each sex and ethnicity group were examined. Results : For 18 of 24 comparisons, the age‐ and laboratory‐adjusted correlations were lowest for percent fat and in 16 of 24 comparisons were highest for WC. Fifteen of the between‐method differences reached statistical significance. With health risk indicator as the dependent variable and anthropometric measures as the independent variable, the contribution of percent fat to the WC regression model was not statistically significant; in contrast, adding WC to the percent fat regression model did make a significant independent contribution for most health risk indicators. Discussion : WC had the strongest associations with health risk indicators, followed by BMI. Although percent fat is a useful measure of overall adiposity, health risks are best represented by the simply measured WC.     

Comparison of self-reported and measured BMI as correlates of disease markers in US adults

Objective: The purpose of this study is to evaluate the validity of BMI based on self‐reported data by comparison with technician‐measured BMI and biomarkers of adiposity. Research Methods and Procedures: We analyzed data from 10,639 National Health and Nutrition Education Study III participants ≥20 years of age to compare BMI calculated from self‐reported weight and height with BMI from technician‐measured values and body fatness estimated from bioelectrical impedance analysis in relation to systolic blood pressure, fasting blood levels of glucose, high‐density lipoprotein‐cholesterol, triglycerides, C‐reactive protein, and leptin. Results: BMI based on self‐reported data (25.07 kg/m²) was lower than BMI based on technician measurements (25.52 kg/m²) because of underreporting weight (?0.56 kg; 95% confidence interval, ?0.71, ?0.41) and overreporting height (0.76 cm; 95% confidence interval, 0.64, 0.88). However, the correlations between self‐reported and measured BMI values were very high (0.95 for whites, 0.93 for blacks, and 0.90 for Mexican Americans). In terms of biomarkers, self‐reported and measured BMI values were equally correlated with fasting blood glucose (r = 0.43), high‐density lipoprotein‐cholesterol (r = ?0.53), and systolic blood pressure (r = 0.54). Similar correlations were observed for both measures of BMI with plasma concentrations of triglycerides and leptin. These correlations did not differ appreciably by age, sex, ethnicity, or obesity status. Correlations for percentage body fat estimated through bioelectrical impedance analysis with these biomarkers were similar to those for BMI. Discussion: The accuracy of self‐reported BMI is sufficient for epidemiological studies using disease biomarkers, although inappropriate for precise measures of obesity prevalence.     

Height and Adiposity among Children

Objectives : Although BMI (kilograms per meter squared) is widely used as a surrogate measure of adiposity, it is moderately associated (r ～ 0.3) with height among children. We examined whether the resulting preferential classification of taller children as overweight, based on a BMI ≥95th percentile, is appropriate. Research Methods and Procedures : We assessed the cross‐sectional relation of height among 5‐ to 18‐year‐old subjects (n = 1180) to levels of BMI, the sum of 10 skinfold thicknesses, and percentage body fat as determined by DXA. Results : The prevalence of a BMI level ≥95th percentile was substantially higher among 5‐ to 11‐year‐old subjects who were relatively tall for their age than among shorter children. Among 5‐ to 8‐year‐old boys, for example, each SD increase in height‐for‐age was associated with a 4.6‐fold increase in the prevalence of overweight (p < 0.001). Height not only was associated with BMI but also showed similar correlations with the skinfold sum and with percentage body fat; furthermore, the magnitudes of these associations decreased with age. We also found that the association between percentage body fat and BMI (r = 0.85 to 0.90) was close to the maximum correlation that can be achieved by any weight‐height index. Discussion : The use of BMI, which preferentially classifies taller young children as overweight, is appropriate because height and adiposity are correlated before the age of 12 years.     

Visceral adiposity is associated with serum retinol binding protein-4 levels in healthy women

Objective: Retinol binding protein‐4 (RBP4) has been reported to impair insulin sensitivity throughout the body. We investigated the relationship between serum RBP4 levels and adiposity indices as well as metabolic risk variables. Research Methods and Procedure: We recruited a total of 102 healthy women 21 to 67 years old. We assessed body composition by computed tomography and divided the study population into four groups based on body weight and visceral fat area (non‐obese without visceral adiposity, non‐obese with visceral adiposity, obese without visceral adiposity, and obese with visceral adiposity). Serum RBP4 levels were measured by radioimmunoassay. Results: Despite similar levels of total body fat, non‐obese women had lower systolic blood pressure, total cholesterol, triglyceride (TG), low‐density lipoprotein (LDL)‐cholesterol levels, insulin resistance indices, and RBP4 levels than non‐obese women with visceral adiposity and had higher high‐density lipoprotein‐cholesterol levels. Similarly, obese women without visceral adiposity had lower blood pressure, total cholesterol, TG levels, insulin resistance indices, and RBP4 levels than obese women with visceral adiposity. In addition, despite having increased body fat, obese women without visceral adiposity had lower TGs, insulin resistance indices, and serum RBP4 levels than non‐obese women with visceral adiposity. By step‐wise multiple regression analysis, visceral fat areas and LDL‐cholesterol levels independently affected RBP4 levels. Discussion: We determined that serum RBP4 levels are independently associated with visceral fat and LDL‐cholesterol levels. These results suggest that, irrespective of body weight, visceral obesity is an independent predictor of serum RBP4 levels, and RBP4 may represent a link between visceral obesity and cardiovascular disease.     

Impact of Obesity and Body Fat Distribution on Cardiovascular Risk Factors in Hong Kong Chinese

Objective: Body fat distribution has been reported to differentially contribute to the development of cardiovascular risk. We report the relative associations between general and central obesity and risk factors in 2893 Chinese subjects recruited from the Hong Kong population. Research Methods and Procedures: Anthropometric parameters [waist circumference (WC) and BMI], surrogate measures of insulin resistance (fasting plasma glucose and insulin, oral glucose tolerance test, 2 hours glucose and insulin), fasting lipids (total, low‐density lipoprotein‐cholesterol, high‐density lipoprotein‐cholesterol, and triglycerides) and systolic and diastolic blood pressure were measured. General obesity was classified as BMI ≥25.0 kg/m² and central obesity as a WC ≥80 or ≥90 cm in women and men, respectively. Results: A total of 39.2% of the population was found to be obese. Obesity per se increased the levels of the risk factors, but central adiposity contributed to a greater extent to adverse high‐density lipoprotein‐cholesterol, triglyceride, and insulin resistance levels. There was a continuous relationship between increasing obesity, both general and central, and cardiovascular risk, with lowest risk associated with the lowest indices of obesity. In the 1759 nonobese subjects divided into quartiles of BMI or WC, the levels of the cardiovascular risk factors still significantly increased with increasing quartiles of adiposity. Discussion: Central adiposity appears to contribute to a greater extent than general adiposity to the development of cardiovascular risk in this population. The relationship between obesity parameters and risk is a continuum, with risk factors significantly increasing even at levels usually considered nonobese. These observations support the proposed redefinition of overweight and obesity in Asian populations using lower cut‐off points.     

The Relationship of Childhood Adiposity to Parent Body Mass Index and Eating Behavior

Objective: To better understand risk factors for the development of obesity in early childhood, we examined the association between children's adiposity and their parents' eating behavior and body mass index (BMI). Research Methods and Procedures: Parents of 85 white children 36 months of age (49 boys and 36 girls) completed the Three‐Factor Eating Questionnaire measuring three dimensions of parent eating behavior: disinhibited eating, cognitive restraint of eating, and susceptibility to hunger. Parent BMI (kg/m²) was calculated using self‐reported height and weight. The children's percentage body fat was assessed by dual energy X‐ray absorptiometry analysis. Results: Twenty‐six percent of parents were obese (BMI ≥ 30 kg/m²). Both maternal and paternal BMI were associated with higher scores for disinhibition (r = 0.69 and r = 0.68, p < 0.001), and maternal BMI was also associated with higher scores for hunger (r = 0.51, p < 0.001). There were no significant relationships between children's percentage body fat and parent eating scores, and the correlation between children's percentage body fat and parent BMI was significant only between mothers and daughters (r = 0.35, p = 0.04). Obese parents were no more likely to have a child who was fatter (upper quintile of percentage body fat for gender). Discussion: Among 36 month‐old white children, parent eating behavior was related to parent BMI, but not to children's adiposity. There was only a weak relationship between parent BMI and child adiposity. Despite the aggregation of adiposity within families due to shared genes and environments, children may not express differences in susceptibility to obesity by 3 years of age.     

Validation of Bioelectrical Impedance Analysis in Adolescents Across Different Ethnic Groups

Adolescent obesity is difficult to assess in multi‐ethnic populations using BMI, due to variability in the BMI–fatness relationship. We aimed to describe body composition (BC), and to validate leg–leg bioelectrical impedance analysis (BIA), in adolescents from different ethnic groups using deuterium (D₂O) as the reference method. Measurements were made of weight, height, total body water (TBW), and BIA (TANITA TBF‐300) in 110 white, 170 Asian, and 102 black adolescents aged 11–15 years. TBW was converted to lean mass (LM) using assumed hydration of lean tissue. General linear models were used to compare BC by D₂O between the ethnic groups. BC values from D₂O were compared with TANITA values, and used to generate ethnic‐specific prediction equations in the whole sample, and also in equation‐generation (group 1) and cross‐validation (group 2) subsamples. Ethnic variability in BMI did not reflect variability in adiposity. Asians had less LM than white and black adolescents, and less fat mass (FM) than white girls. TANITA in‐built equations did not predict BC accurately across ethnic groups, with significant bias in white and Asian males, and Asian and black females. The new equation generated from the entire sample removes ethnic‐specific mean biases. The group 1 equation showed no significant bias in any ethnic group when tested in group 2. We found significant variability in BC between ethnic groups that was not reflected by BMI. Manufacturers' equations are unsuitable for predicting BC in multi‐ethnic populations, and our new equations are recommended.     

Relationship of visceral adiposity to cardiovascular disease risk factors in black and white teens

Objective: We tested the hypothesis that visceral adiposity, compared with general adiposity, would explain more of the variance in cardiovascular disease (CVD) risk factors. Research Method and Procedures: Subjects were 464 adolescents (238 black and 205 girls). Adiposity measures included visceral adipose tissue (VAT; magnetic resonance imaging), percent body fat (%BF; DXA), BMI, and waist girth (anthropometry). CVD risk factors were fasting insulin, fibrinogen, total to high‐density lipoprotein‐cholesterol ratio, triglycerides (TGs), systolic blood pressure, and left ventricular mass indexed to height^2.7. Results: After adjustment for age, race, and sex, all adiposity indices explained significant proportions of the variance in all of the CVD risk factors; %BF tended to explain more variance than VAT. Regression models that included both %BF and VAT found that both indices explained independent proportions of the variance only for total to high‐density lipoprotein‐cholesterol ratio. For TGs, the model that included both %BF and VAT found that only VAT was significant. For systolic blood pressure and left ventricular mass indexed to height^2.7, anthropometric measures explained more of the variance than VAT and %BF. Discussion: The hypothesis that visceral adiposity would explain more variance in CVD risk than general adiposity was not supported in this relatively large sample of black and white adolescents. Only for TGs did it seem that VAT was more influential than %BF. Perhaps the deleterious effect of visceral adiposity becomes greater later in life as it increases in proportion to general adiposity.     

Bioelectrical impedance vs. four-compartment model to assess body fat change in overweight adults

Objective: The Tanita TBF‐305 body fat analyzer is marketed for home and clinical use and is based on the principles of leg‐to‐leg bioelectrical impedance analysis (BIA). Few studies have investigated the ability of leg‐to‐leg BIA to detect change in percentage fat mass (%FM) over time. Our objective was to determine the ability of leg‐to‐leg BIA vs. the four‐compartment (4C) model to detect small changes in %FM in overweight adults. Research Methods and Procedures: Thirty‐eight overweight adults (BMI, 25.0 to 29.9 kg/m²; age, 18 to 44 years; 31 women) participated in a 6‐month, randomized, double‐blind, placebo‐controlled study of a nutritional supplement. Body composition was measured at 0 and 6 months using the Tanita TBF‐305 body fat analyzer [using equations derived by the manufacturer (%FM_T‐Man) and by Jebb et al. (%FM_T‐Jebb)] and the 4C model (%FM_4C). Results: Subjects in the experimental group lost 0.9%FM_4C (p = 0.03), a loss that did not reach significance using leg‐to‐leg BIA (0.6%FM_T‐Man, p = 0.151; 0.6%FM_T‐Jebb, p = 0.144). We observed large standard deviations (SDs) in the mean difference in %FM between the 4C model and the Tanita_Manufacturer (2.5%) and Tanita_Jebb (2.2%). Ten subjects fell outside ±1 SD of the mean differences at 0 and 6 months; those individuals were younger and shorter than those within ±1 SD. Discussion: Leg‐to‐leg BIA performed reasonably well in predicting decreases in %FM in this group of overweight adults but resulted in wide SDs vs. %FM_4C in individuals. Cross‐sectional determinations of %FM of overweight individuals using leg‐to‐leg BIA should be interpreted with caution.     

The relationship between anthropometric indexes of adiposity and vascular function in the FATE cohort

Objective:

Numerous indexes of adiposity have been proposed and are currently in use in clinical practice and research. However, the correlation of these indexes with measures of vascular health remain poorly defined. This study investigated which measure of adiposity is most strongly associated with endothelial function.

Design and Methods:

Data from the Firefighters And Their Endothelium (FATE) study was used. The relationships between three measures of vascular function: flow‐mediated dilation (FMD), hyperemic velocity time integral (VTI), and hyperemic shear stress (HSS), and five measures of adiposity: BMI, waist circumference (WC), waist‐to‐hip ratio (WHR), waist‐to‐height ratio (WHtR), and body adiposity index (BAI) were tested. Univariate comparisons were made, and subsequently models adjusted for traditional risk factors were constructed.

Results:

A total of 1,462 male firefighters (mean age 49 ± 9) without cardiovascular disease comprised the study population. No measure of adiposity correlated with FMD; all five measures of adiposity were negatively correlated with VTI and HSS (P values <0.0001), with WHtR most strongly correlated with VTI, and WC most strongly correlated with HSS (both P < 0.05). In models including all five measures of obesity simultaneously, BMI, WC, and WHtR were all predictive of HSS (all P values <0.05), and BMI and WHR were both predictive of VTI (P values <0.05).

Conclusions:

Anthropometric measures of adiposity may help refine estimations of atherosclerotic burden. BMI was most consistently associated with endothelial dysfunction, but measures of adiposity that reflect distribution of mass were additive.     

A Prospective Study of Adiposity and All‐Cause Mortality: The Malmö Diet and Cancer Study

Objective: This study aims to examine the association between various measures of adiposity and all‐cause mortality in Swedish middle‐aged and older men and women and, additionally, to describe the influences of age and sex on these associations. Research Methods and Procedures: A prospective analysis was performed in a cohort of 10,902 men and 16,814 women ages 45 to 73 years who participated in the Malmö Diet and Cancer Study in Sweden. Baseline examinations took place between 1991 and 1996, and 982 deaths were documented during an average follow‐up of 5.7 years. All‐cause mortality was related to the following variables measured at baseline: body mass index (BMI), percentage of body fat, lean body mass (LBM), and waist‐to‐hip ratio (WHR), with adjustment for age and selected covariates. Body composition data were derived from bioelectrical impedance analysis. Results: The association between percentage of body fat and mortality was modified by age, particularly in women. For instance, fatness was associated with excess mortality in the younger women but with reduced mortality in the older women. Weaker associations were seen for BMI than for percentage of body fat in both sexes. Placement in the top quintiles of waist‐to‐hip ratio, independent of overall body fat, was a stronger predictor of mortality in women than in men. The observed associations could not be explained by bias from early death or antecedent disease. Discussion: The findings reveal sex and age differences for the effects of adiposity and WHR on mortality and indicate the importance of considering direct measures of adiposity, as opposed to BMI, when describing obesity‐related mortality risks.     

Concordance of BAI and BMI with DXA in the Newfoundland Population

Background:

Body adiposity index (BAI), indirect method proposed to predict adiposity, was developed using Mexican Americans and very little data are available regarding its validation in Caucasian populations to date.

Objective:

The study objectives were to validate the BAI with dual‐energy X‐ray absorptiometry (DXA) body fat percentage (%BF), taking into consideration the gender and adiposity status.

Design and Methods:

A total of 2,601 subjects (Male 662, Female 1939) from our Complex Diseases in the Newfoundland population: Environment and Genetics (CODING) study participated in this investigation. Pearson correlations, with the entire cohort along with men and women separately, were used to compare the correlation of both BAI and BMI with %BF. Additionally, the concordance between BAI and BMI with %BF were also performed among normal‐weight (NW), overweight (OW), and obese (OB) groups. Adiposity status was determined by the Bray Criteria according to DXA %BF.

Results:

BAI performs better than BMI in our Caucasian population by: (1) reflecting the gender difference in total %BF between women and men, (2) correlating better with DXA %BF than BMI when women and men are combined, and (3) performing better in NW and OW subjects for both the sexes. However, BAI performs less effectively than BMI in OB men and women.

Conclusion:

In summary, the BAI method is a better estimate of adiposity than BMI in non‐OB subjects in our Caucasian population. A measurement sensitive to the changes in adiposity for both men and women is suggested to be incorporated into the present BAI equation to increase accuracy.     

Effect of Glucose Tolerance Status on PAI‐1 Plasma Levels in Overweight and Obese Subjects

Objective: The aim of our study was to examine whether plasminogen activator inhibitor‐1 (PAI‐1) plasma levels varied as a function of differences in glucose tolerance status independently of body fatness, body‐fat distribution, and insulin sensitivity. Research Methods and Procedures: Plasma PAI‐1 antigen levels, along with insulin resistance [measured by homeostatic model assessment (HOMA_IR)], central fat accumulation, body composition, blood pressure, and fasting concentrations of glucose, insulin, and lipids, were measured in 229 overweight and obese [body mass index (BMI) ≥25 kg/m²) subjects with normal glucose tolerance (NGT) and in 44 age‐ and BMI‐matched subjects with impaired glucose tolerance (IGT). Results: Plasma PAI‐1 antigen levels were significantly higher in IGT than in NGT subjects. Log PAI‐1 was positively correlated with BMI, HOMA_IR, and log insulin, and inversely associated with high‐density lipoprotein‐cholesterol both in IGT and in NGT individuals. On the other hand, log PAI‐1 was positively correlated with waist circumference, fat mass (FM), fat‐free mass, systolic and diastolic blood pressure, and log triglycerides only in the NGT group. After multivariate analyses, the strongest determinants of PAI‐1 levels were BMI, FM, waist circumference, and high‐density lipoprotein cholesterol in the NGT group and only HOMA_IR in the IGT cohort. Discussion: This study demonstrates that PAI‐1 concentrations are higher in IGT than in NGT subjects. Furthermore, we suggest that the influences of total adiposity, central fat, and insulin resistance, main determinants of PAI‐1 concentrations, are different according to the degree of glucose tolerance.     

Relationships between direct and indirect measures of central and total adiposity in children: What are we measuring?

Objective: The relationship between central and total fat measured by anthropometry, dual energy X‐ray absorptiometry, and magnetic resonance imaging (MRI) with each other and systolic blood pressure (SBP) was examined. Design and Methods: Participants of the Avon Longitudinal Study of Parents and Children were examined at ages 9, 11, 13, and 15 years (n = 3,796‐6,567). MRI was available on a subset of children at 11 (n = 156) and 13 (n = 95). Results: Body mass index (BMI) and waist circumference (WC) were highly correlated (r = 0.84‐0.91, across ages), and total body fat mass (TBFM) and trunk fat mass (TFM) were very strongly correlated (r ≥ 0.98). Among boys, BMI vs. WC explained a similar degree of variation in TBFM and TFM (41‐71% vs. 43‐76%, across age and overweight groups); in girls, BMI accounted for 62‐73% variance and WC 47‐69%. Adiposity measures were generally similarly correlated with SBP within age groups. Further, the relationship between intra‐abdominal adipose tissue (IAAT) volume and adiposity measures did not vary greatly at 11 (0.65‐0.67) and 13 (0.64‐0.67). Conclusions: BMI and WC contain a large amount of overlapping information as evidenced by their high correlation and similarly sized associations with fat mass, SBP, and IAAT. This suggests that WC may be an inadequate marker of central adiposity during childhood.