Validation of BIA in Obese Children and Adolescents and Re‐evaluation in a Longitudinal Study

Decrease in fat mass (FM) is a one of the aims of pediatric obesity treatment; however, measurement techniques suitable for routine clinical assessment are lacking. The objective of this study was to validate whole‐body bioelectrical impedance analysis (BIA; TANITA BC‐418MA) against the three‐component (3C) model of body composition in obese children and adolescents, and to test the accuracy of our new equations in an independent sample studied longitudinally. A total of 77 white obese subjects (30 males) aged 5–22 years, BMI‐standard deviation score (SDS) 1.6–3.9, had measurements of weight, height (HT), body volume, total body water (TBW), and impedance (Z). FM and fat‐free mass (FFM) were calculated using the 3C model or predicted from TANITA. FFM was predicted from HT²/Z. This equation was then evaluated in 17 other obese children (5 males) aged 9–13 years. Compared to the 3C model, TANITA manufacturer's equations overestimated FFM by 2.7 kg (P < 0.001). We derived a new equation: FFM = ?2.211 + 1.115 (HT²/Z), with r² of 0.96, standard error of the estimate 2.3 kg. Use of this equation in the independent sample showed no significant bias in FM or FFM (mean bias 0.5 ± 2.4 kg; P = 0.4), and no significant bias in change in FM or FFM (mean bias 0.2 ± 1.8 kg; P = 0.7), accounting for 58% (P < 0.001) and 55% (P = 0.001) of the change in FM and FFM, respectively. Our derived BIA equation, shown to be reliable for longitudinal assessment in white obese children, will aid routine clinical monitoring of body composition in this population.     

Ethnic Differences in Subcutaneous Adiposity and Waist Girth in Children and Adolescents

The purpose of this study was to examine ethnic differences in adiposity as measured by sum of skinfolds (SKF) and waist circumference (WC) in children and adolescents, after statistical adjustment for the BMI and age. A cross sectional sample of 3,218 (55% white, 49% male) children and adolescents aged 5–18 years who participated in the Bogalusa Heart Study (1992–1994) were included in these analyses. Sex‐specific ANOVAs, adjusted for BMI and age, for each 2‐year age group compared measures of adiposity (SKF and WC) between ethnic groups. No significant differences in the proportions of children and adolescents who were overweight and obese by ethnicity or sex were found. Mean SKF in normal weight (P < 0.0001) and overweight (P < 0.0001) categories was higher for white than black children of both sexes. Across most age categories, white boys and girls had significantly higher SKF than black boys and girls, respectively (P ≤ 0.05). Across most age categories, white boys had significantly higher WC than black boys (P ≤ 0.05) with no difference in the girls, when adjusted for BMI and age. Measures of adiposity in childhood and adolescence were significantly higher in white children compared to black children, when adjusted for BMI and age. Throughout childhood and adolescence, white boys and girls had higher SKF and white boys had higher WC. Differences in adiposity between ethnic groups should be considered in disease risk assessment and stratification as they are observed even for a given BMI level.     

Are Ethnic and Gender Specific Equations Needed to Derive Fat Free Mass from Bioelectrical Impedance in Children of South Asian,Black African-Caribbean and White European Origin? Results of the Assessment of Body Composition in Children Study

Background

Bioelectrical 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.

Methods

Cross-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(height²/Z); C: FFM = linear combination(height²/Z+weight)}.

Results

Ethnicity 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.

Conclusions

Ethnic- 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.     

Racial/ethnic differences in body fatness among children and adolescents

Background: Although the BMI is widely used as a measure of adiposity, it is a measure of excess weight, and its association with body fatness may differ across racial or ethnic groups. Objective: To determine whether differences in body fatness between white, black, Hispanic, and Asian children vary by BMI‐for‐age, and whether the accuracy of overweight (BMI‐for‐age ≥ Centers for Disease Control and Prevention (CDC) 95th percentile) as an indicator of excess adiposity varies by race/ethnicity. Methods and Procedures: Total body dual‐energy X‐ray absorptiometry (DXA) provided estimates of %body fat among 1,104 healthy 5‐ to 18‐year‐olds. Results: At equivalent levels of BMI‐for‐age, black children had less (mean, 3%) body fatness than white children, and Asian girls had slightly higher (1%) levels of %body fat than white girls. These differences, however, varied by BMI‐for‐age, with the excess body fatness of Asians evident only among relatively thin children. The ability of overweight to identify girls with excess body fatness also varied by race/ethnicity. Of the girls with excess body fatness, 89% (24/27) of black girls, but only 50% (8/16) of Asian girls, were overweight (P = 0.03). Furthermore, the proportion of overweight girls who had excess body fatness varied from 62% (8/13) among Asians to 100% (13/13) among whites. Discussion: There are racial or ethnic differences in body fatness among children, but these differences vary by BMI‐for‐age. If race/ethnicity differences in body fatness among adults also vary by BMI, it may be difficult to develop race‐specific BMI cut points to identify equivalent levels of %body fat.     

Bioimpedance for severe obesity: comparing research methods for total body water and resting energy expenditure

Objective: As the acceptance of surgical procedures for weight loss in morbid obesity is increasing, clinically useful baseline and follow‐up measures of total body water (TBW) and resting energy expenditure (REE) are important. Research methods such as deuterium (D²O) dilution and metabolic carts are problematic in the clinical setting. We compared bioimpedance analysis (BIA) predicted (Tanita TBF‐310) and measured TBW and REE. Methods and Procedures: Forty‐two paired presurgery studies were completed using BIA and D²O in patients with BMI (mean ± s.d.) 50.2 ± 8.8 kg/m² for TBW, and 30 patients with BMI 51.0 ± 13 kg/m² completed paired determinations of REE with metabolic carts and the Tanita balance with weight, height, sex, and age modifiers. Regression analysis and Bland‐Altman plots were applied. Results: When regression analysis was completed for TBW, regression line was consistent with the identity line “y = x.” The intercept was not different from 0 (95% confidence interval ?2.5 ± 7.0). The slope of the line was not different from 1.0 ± 0.1. The measured TBW 51.2 ± 10.1 l had a correlation with the predicted 49.5 ± 11.27 l of 0.92. There also was no significant difference (P = 0.33) between predicted (2,316 ± 559 kcal/day) and measured REE (2,383 ± 576 kcal/day);δ 66.7 ± 273 kcal/day. The two measures were highly correlated (r = 0.88) with no bias detected. Discussion: These observations support the use of the BIA system calibration in subjects with severe obesity. Without the use of complex, costly equipment and invasive procedures, BIA measurements can easily be obtained in clinical practice to monitor patient responses to treatment.     

The prevalence of obesity in ethnic admixture adults

Objective: To determine whether the prevalence of obesity in ethnic admixture adults varies systematically from the average of the prevalence estimates for the ethnic groups with whom they share a common ethnicity. Methods and Procedures: The sample included 215,000 adults who reported one or more ethnicities, height, weight, and other characteristics through a mailed survey. Results: The highest age‐adjusted prevalence of overweight (BMI ≥ 25) was in Hawaiian/Latino men (88%; n = 41) and black/Latina women (74.5%; n = 79), and highest obesity (BMI ≥ 30) rates were in Hawaiian/Latino men (53.7%; n = 41) and Hawaiian women (39.2%, n = 1,247). The prevalence estimates for most admixed groups were similar to or higher than the average of the prevalences for the ethnic groups with whom they shared common ethnicities. For instance, the prevalence of overweight/obesity in five ethnic admixtures—Asian/white, Hawaiian/white, Hawaiian/Asian, Latina/white, and Hawaiian/Asian/white ethnic admixtures—was significantly higher (P < 0.0001) than the average of the prevalence estimates for their component ethnic groups. Discussion: The identification of individuals who have a high‐risk ethnic admixture is important not only to the personal health and well‐being of such individuals, but could also be important to future efforts in order to control the epidemic of obesity in the United States.     

Relationship Between Basal Metabolic Rate,Gender, Age,and Body Composition in 8,780 White Obese Subjects

The objective of the present study was to explore the relationship between basal metabolic rate (BMR), gender, age, anthropometric characteristics, and body composition in severely obese white subjects. In total, 1,412 obese white children and adolescents (BMI > 97° percentile for gender and age) and 7,368 obese adults (BMI > 30 kg/m²) from 7 to 74 years were enrolled in this study. BMR was measured using an indirect calorimeter equipped with a canopy and fat free mass (FFM) were obtained using tetrapolar bioelectrical impedance analysis (BIA). Using analysis of covariance, we tested the effect of gender on the relationship between BMR, age, anthropometry, and body composition. In children and adolescents, the predictor × gender interaction was significant in all cases except for FFM × gender. In adults, all predictor × gender interactions were significant. A prediction equation based on body weight (BW), age, and gender had virtually the same accuracy of the one based on FFM, age, and gender to predict BMR in both children and adults (R²_adj = 0.59 and 0.60, respectively). In conclusion, gender was a significant determinant of BMR in children and adolescents but not in adults. Our results support the hypothesis that the age‐related decline in BMR is due to a reduction in FFM. Finally, anthropometric predictors of BMR are as accurate as body composition estimated by BIA.     

The relationship between insulin sensitivity and serum adiponectin levels in three population groups.

Reduced plasma adiponectin levels are associated with insulin resistance. Black South Africans, like African Americans, are more insulin-resistant than BMI-matched white subjects, as are Asian Indians. We investigated whether this interethnic variation in insulin resistance is due to differences in plasma adiponectin levels. Blood and anthropometric measurements were taken from black, white and Asian-Indian subjects. Serum adiponectin, lipids, glucose and insulin were measured; insulin sensitivity was calculated using HOMA. Black (HOMA = 2.62 +/- 0.99) and Asian-Indian subjects (HOMA = 3.41 +/- 2.85) were more insulin-resistant than BMI-matched white (HOMA = 1.76 +/- 0.63) subjects (p = 0.0001). Furthermore, the white subjects had higher adiponectin levels (8.11 +/- 4.39 microg/ml) compared to black (5.71 +/- 2.50 microg/ml) and Asian Indian (5.86 +/- 2.50 microg/ml) subjects (p = 0.003). When all ethnic groups were combined, multiple regression analysis demonstrated that serum adiponectin levels corrected for BMI and ethnicity did not correlate with HOMA, but did explain 10.0 % of the variance in HDL-cholesterol levels. Within each ethnic group, adiponectin only correlated inversely with HOMA in white subjects. Adiponectin may play a role in determining serum HDL-cholesterol levels, but ethnic variation in insulin sensitivity is not dependent on serum levels of this adipokine. The relationship between adiponectin and insulin resistance varies across ethnic groups.     

Potential effects of ethnicity in genetic and environmental sources of variability in the stature, mass, and body mass index of children

We examined sources of variability in stature, body mass, and body mass index (BMI) in families of black and white elementary schoolchildren from Philadelphia, Pennsylvania. The sample consisted of 445 black and 379 white children, 7-13 years old, and their parents (total n = 2016). The sample was distributed among 596 nuclear families, each representing an independent pedigree. Maximum-likelihood-based variance decomposition methods were used to simultaneously estimate ethnic group-specific effects of genes, sex, age by sex, and unmeasured environmental factors on stature, body mass, and BMI. Likelihood ratio tests were performed to assess the significance of h2 estimates and differences in sigma g and sigma e between black and white families. Genes account for moderate proportions of the phenotypic variance (h2) of these traits in black and white children. In black and white children, respectively, h2 estimates were 0.37 and 0.53 for stature, 0.37 and 0.31 for body mass, and 0.38 and 0.24 for BMI (p < 0.0005). Although the differences in h2 between ethnic groups were not significant (stature, p = 0.23; body mass, p = 0.49; BMI, p = 0.14), black children exhibited a significantly greater total residual phenotypic standard deviation (sigma e and sigma g) in body mass and BMI and a significantly greater sigma e for stature compared with white children. The larger residual phenotypic variance in the black sample is likely due to exposure to unmeasured environmental factors that are not accounted for in this model. Given that sigma g for stature is not significantly different between ethnic groups, the slightly lower estimates in black children are due to the increased contribution of the environment to the phenotypic variance in this trait.     

Prediction of Fatness by Standing 8‐Electrode Bioimpedance: A Multiethnic Adolescent Population

The objective of this study was to validate an 8‐electrode bioimpedance analysis (BIA₈) device (BC‐418; Tanita, Tokyo, Japan) for use in populations of European, Maori, Pacific Island, and Asian adolescents. Healthy adolescents (215 M, 216 F; 129 Pacific Island, 120 Asian, 91 Maori, and 91 European; age range 12–19 years) were recruited by purposive sampling of high schools in Auckland, New Zealand. Weight, height, sitting height, leg length, waist circumference, and whole‐body impedance were measured. Fat mass (FM) and fat‐free mass (FFM) derived from the BIA₈ manufacturer's equations were compared with measurements by dual‐energy X‐ray absorptiometry (DXA). DXA‐measured FFM was used as the reference to develop prediction equations based on impedance. A double cross‐validation technique was applied. BIA₈ underestimated FM by 2.06 kg (P < 0.0001) and percent body fat (%BF) by 2.84% (P < 0.0001), on average. However, BIA₈ tended to overestimate FM and %BF in lean and underestimate FM and %BF in fat individuals. Sex‐specific equations developed showed acceptable accuracy on cross‐validation. In the total sample, the best prediction equations were, for boys: FFM (kg) = 0.607 height (cm)²/impedance (Ω) + 1.542 age (y) + 0.220 height (cm) + 0.096 weight (kg) + 1.836 ethnicity (0 = European or Asian, 1 = Maori or Pacific) ? 47.547, R² = 0.93, standard error of estimate (SEE) = 3.09 kg; and, for girls: FFM (kg) = 0.531 height (cm)²/impedance (Ω) + 0.182 height (cm) + 0.096 weight (kg) + 1.562 ethnicity (0 = non‐Pacific, 1 = Pacific) ? 15.782, R² = 0.91, SEE = 2.19 kg. In conclusion, equations for fatness estimation using BIA₈ developed for our sample perform better than reliance on the manufacturer's estimates. The relationship between BIA and body composition in adolescents is ethnicity dependent.     

Body composition assessment in extreme obesity and after massive weight loss induced by gastric bypass surgery

Body composition methods were examined in 20 women [body mass index (BMI) 48.7 +/- 8.8 kg/m(2)] before and after weight loss [-44.8 +/- 14.6 (SD) kg] after gastric bypass (GBP) surgery. The reference method, a three-compartment (3C) model using body density by air displacement plethysmography and total body water (TBW) by H(2)18O dilution (3C-H(2)18O), showed a decrease in percent body fat (%BF) from 51.4 to 34.6%. Fat-free mass hydration was significantly higher than the reference value (0.738) in extreme obesity (0.756; P < 0.001) but not after weight reduction (0.747; P = 0.16). %BF by H(2)18O dilution and air displacement plethysmography differed significantly from %BF by 3C-H(2)18O in extreme obesity (P < 0.05) and 3C models using (2)H(2)O or bioelectrical impedance analysis (BIA) to determine TBW improved mean %BF estimates over most other methods at both time points. BIA results varied with the equation used, but BIA better predicted %BF than did BMI at both time points. All methods except BIA using the Segal equation were comparable to the reference method for determining changes over time. A simple 3C model utilizing air displacement plethysmography and BIA is useful for clinical evaluation in this population.     

Racial and ethnic differences in secular trends for childhood BMI, weight, and height

Objectives: The prevalence of childhood overweight in the United States has markedly increased over the last 30 years. We examined differences in the secular trends for BMI, weight, and height among white, black, and Mexican‐American children. Research Methods and Procedures: Analyses were based on nationally representative data collected from 2 to 17 year olds in four examinations (1971–1974 through 1999–2002). Results: Overall, black children experienced much larger secular increases in BMI, weight, and height than did white children. For example, over the 30‐year period, the prevalence of overweight increased ～3‐fold (4% to 13%) among 6‐ to 11‐year‐old white children but 5‐fold (4% to 20%) among black children. In most sex‐age groups, Mexican‐American children experienced increases in BMI and overweight that were between those experienced by blacks and whites. Race/ethnicity differences were less marked among 2 to 5 year olds, and in this age group, white children experienced the largest increase in overweight (from 4% to 9%). In 1999–2002, the prevalence of extreme BMI levels (≥99th percentile) reached 6% to 7% among black girls and Mexican‐American boys. Discussion: Because of the strong tracking of childhood BMI levels into adulthood, it is likely that the secular increases in childhood overweight will greatly increase the burden of adult disease. The further development of obesity interventions in different racial/ethnic groups should be emphasized.     

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.     

The Relationship of Ethnicity,Socioeconomic Factors,and Overweight in U.S. Adolescents

Objective: To examine the extent to which race/ethnic differences in income and education account for sex‐specific disparities in overweight prevalence in white, African American, Hispanic, and Asian U.S. teens. Research Methods and Procedures: We used nationally representative data collected from 13,113 U.S. adolescents enrolled in the National Longitudinal Study of Adolescent Health. Logistic regression models were used to examine the relationship of family income and parental education to overweight prevalence (body mass index ≥ 85th percentile of age and sex‐specific cutoff points from the 2000 Centers for Disease Control and Prevention/National Center for Health Statistics growth charts). In addition, we used coefficients from our logistic regression models to project the effects on overweight prevalence of equalizing the socioeconomic status (SES) differences between race/ethnic groups. Results: Keeping adolescents in their same environments and changing only family income and parental education had a limited effect on the disparities in overweight prevalence. Ethnicity‐SES‐overweight differences were greater among females than males. Given that overweight prevalence decreased with increasing SES among white females and remained elevated and even increased among higher SES African‐American females, African‐American/white disparity in overweight prevalence increased at the highest SES. Conversely, disparity was lessened at the highest SES for white, Hispanic, and Asian females. Among males, disparity was lowest at the average SES level. Discussion: One cannot automatically assume that the benefits of increased SES found among white adults will transfer to other gender‐age‐ethnic groups. Our findings suggest that efforts to reduce overweight disparities between ethnic groups must look beyond income and education and focus on other factors, such as environmental, contextual, biological, and sociocultural factors.     

ESTIMATION OF TOTAL BODY WATER IN HARBOR SEALS: HOW USEFUL IS BIOELECTRICAL IMPEDANCE ANALYSIS?

We evaluated bioelectrical impedance analysis (BIA) as a means of rapidly and inexpensively estimating total body water (TBW) of harbor seals ( Phoca vitulina ). Deuterium oxide dilution was used to estimate TBW in 17 adult females and 16 of their pups between birth and late lactation. Isotope dilution was also used to determine TBW in 12 adult males early and 10 of these males late in the breeding season. At the same time, resistance ( Rs ) and reactance ( Xc ) measurements were taken using a tetrapolar, impedance plethysmograph (Model 101 A, RJL Systems). Seals were sedated with diazepam prior to taking BIA measurements. Within-day duplicate Rs measurements on pups and adults, taken 2-240 min apart, differed by an average of 3.0%± 1.4% ( n = 42, CV = 102%). Movement of the seal during BIA measurements caused variability in both Rs and Xc values. BIA measurements were generally poor predictors of TBW. Rs was significantly correlated with TBW in pups only ( Rs = 0.93, P = 0.001, n = 11). Bioelectrical conductor volume (length2/ Rs ) was significantly correlated with TBW only in adult females ( Rs = 0.63, P = 0.02, n = 14). We conclude that BIA is not a reliable method of estimating TBW in wild harbor seals.     

Assessing body composition with DXA and bioimpedance: effects of obesity, physical activity, and age

Objective: This study evaluated to what extent dual‐energy X‐ray absorptiometry (DXA) and two types of bioimpedance analysis (BIA) yield similar results for body fat mass (FM) in men and women with different levels of obesity and physical activity (PA). Methods and Procedures: The study population consisted of 37–81‐year‐old Finnish people (82 men and 86 women). FM% was estimated using DXA (GE Lunar Prodigy) and two BIA devices (InBody (720) and Tanita BC 418 MA). Subjects were divided into normal, overweight, and obese groups on the basis of clinical cutoff points of BMI, and into low PA (LPA) and high PA (HPA) groups. Agreement between the devices was calculated by using the Bland–Altman analysis. Results: Compared to DXA, both BIA devices provided on average 2–6% lower values for FM% in normal BMI men, in women in all BMI categories, and in both genders in both HPA and LPA groups. In obese men, the differences were smaller. The two BIA devices provided similar means for groups. Differences between the two BIA devices with increasing FM% were a result of the InBody (720) not including age in their algorithm for estimating body composition. Discussion: BIA methods provided systematically lower values for FM than DXA. However, the differences depend on gender and body weight status pointing out the importance of considering these when identifying people with excess FM.     

Gender‐ethnic Disparity in BMI and Waist Circumference Distribution Shifts in US Adults

While obesity has been increasing in the United States, little is known about the variation in recent BMI and waist circumference (WC) distribution shifts across socio‐demographic groups. We assessed shifts in BMI and WC distributions and compared between‐group differences over the past decade, and projected future BMI and WC distributions and prevalence of obesity and central obesity using National Health and Nutrition Examination Survey (NHANES) 1988–1994 and 1999–2004 data. BMI/WC distributional shifts overall and in percentiles were compared across groups. Average yearly shift was calculated and used for projecting future distributions and prevalence. Both BMI and WC increased more in their uppermost percentile distribution, though BMI shift declined toward the uppermost percentiles among women. Heavier Americans gained more adiposity over the past decade. Ethnic (non‐Hispanic (NH) white vs. black) disparities in mean BMI and WC became wider. Over the survey period, mean BMI increased by 1.3 units vs. 1.8 units among men and women, whereas WC, by 4.2 cm vs. 4.8 cm. Young adults had the largest increase. Shift in women's WC was stable between the 25th and 75th percentiles, but gained pace at higher WC, while women's BMI and men's BMI and WC shifts increased linearly. NH black women had the largest shifts and would have central obesity and obesity prevalence of 90.8 and 70.7% by 2020. Shifts in BMI and WC distribution varied across age‐, gender‐, and ethnic groups. Future rise in the obesity and central obesity prevalence rates are expected, but would vary by demographic groups.     

The Relationship Between Body Image Discrepancy and Body Mass Index Across Ethnic Groups

Objective: This study sought to examine at what body mass index (BMI) body image discrepancy (BD) was reported in a community sample of 389 white, Hispanic, and black women. In addition, we assessed the trajectory of the BMI–BD relationship as BMI increases by ethnic group. Research Methods and Procedures: All participants were assessed on height and weight and completed the Figure Rating Scale. Results: We found no difference in the proportion of women in each ethnic group reporting BD. However, white women experienced BD at a lower BMI level (BMI = 24.6), and below the criterion for overweight (BMI = 25). In contrast, black and Hispanic women did not report BD until they were overweight (BMIs of 29.2 and 28.5, respectively). Compared with black and white women, Hispanic women registered increases in BD at smaller increases in BMI. Discussion: These findings could have unhealthful implications for weight control behavior. The results encourage a closer look at ethnicity and BD, and their relationship to obesity and weight control.     

Comparison of bioelectrical impedance and BMI in predicting obesity-related medical conditions

Objective : To determine the relative validity of specific bioelectrical impedance analysis (BIA) prediction equations and BMI as predictors of physiologically relevant general adiposity. Research Methods and Procedures : Subjects were >12, 000 men and women from the Third National Health and Nutrition Examination Survey population. We examined the correlations between BMI and percentage body fat based on 51 different predictive equations, blood pressure, and blood levels of glucose, high‐density lipoprotein cholesterol, and triglycerides, which are known to reflect adiposity, while controlling for other determinants of these physiological measures. Results : BMI consistently had one of the highest correlations across biological markers, and no BIA‐based measure was superior. Percent body fat estimated from BIA was minimally predictive of the physiological markers independent of BMI. Discussion : These results suggest that BIA is not superior to BMI as a predictor of overall adiposity in a general population.     

Adiposity is not equal in a multi-race/ethnic adolescent population: NHANES 1999-2004

BMI is the preferred measure of adiposity in adolescents. Recent evidence suggests that in adults the relationship between BMI and adiposity can vary by age and race/ethnicity. We investigated the relationship between BMI and percent body fat (%BF) in a large multi-ethnic, nationally representative sample of US adolescents (National Health and Nutrition Examination Survey, NHANES, 1999-2004). BMI was calculated; %BF was derived from dual-energy X-ray absorptiometry data and compared to BMI among adolescents from three groups: non-Hispanic white (NHW), non-Hispanic black (NHB), and Mexican-American (MA). Fractional polynomials were used to model a new equation to estimate %BF from a given BMI. MA boys weighed significantly less than either NHW or NHB boys, while only NHB girls weighed significantly more than the other girls. Among the boys there were no differences in mean BMI, whereas %BF differed significantly between all three groups. For the girls, both BMI and %BF differed significantly the groups with MA girls having the highest %BF. The significant correlates for modeling %BF from BMI included gender, age, race/ethnicity, weight, [formula in text]: the final model explained 79% of the variance in %BF. NHB adolescents had significantly lower %BF for BMI and MA had higher than NHW. Our results indicate that BMI may not be an equivalent measure of %BF in a multi-ethnic population of US adolescents.