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.     

Is Body Mass Index a Measure of Adiposity in Elderly Women?

Objective: To evaluate the accuracy of body mass index (BMI) as a predictor of body fat in elderly women. Research Methods and Procedures: A total of 1423 women aged 67 ± 5 (mean ± SD, range: 60 to 88) years were consecutively enrolled into the study. Fat mass (FM) was measured using DXA. Results: BMI explained 72.9% of FM variance (p < 0.0001), with a root mean square error of estimate (RMSE) of 3.5 kg. After standardization of RMSE on the dependent variable as RMSE%, the prediction error equaled 15%. BMI explained 54.8% of FM% variance (p < 0.0001), with an RMSE of 4.1%, corresponding to an RMSE% of 11%. Discussion: The relatively high RMSE% of the FM and FM%‐BMI associations caution against the use of BMI as an adiposity index in individual elderly women. However, an error corresponding to 11% of FM% may be accepted for population studies of body fat in elderly women.     

Comparison of three bioelectrical impedance methods with DXA in overweight and obese men

Objective: To compare bioelectrical impedance analysis (BIA) of body composition using three different methods against DXA in overweight and obese men. Research Methods and Procedures: Forty‐three healthy overweight or obese men (ages 25 to 60 years; BMI, 28 to 43 kg/m²) underwent BIA assessment of body composition using the ImpediMed SFB7 (version 6; ImpediMed, Ltd., Eight Mile Plains, Queensland, Australia) in multifrequency mode (Imp‐MF) and DF50 single‐frequency mode (Imp‐SF) and the Tanita UltimateScale (Tanita Corp., Tokyo, Japan). Validity was assessed by comparison against DXA using linear regression and limits of agreement analysis. Results: All three BIA methods showed good relative agreement with DXA [Imp‐MF: fat mass (FM), r² = 0.81; fat‐free mass (FFM), r² = 0.81; percentage body fat (BF%), r² = 0.69; Imp‐SF: FM, r² = 0.65; FFM, r² = 0.76; BF%, r² = 0.40; Tanita: BF%, r² = 0.44; all p < 0.001]. Absolute agreement between DXA and Imp‐MF was poor, as indicated by a large bias and wide limits of agreement (bias, ±1.96 standard deviation; FM, ?6.6 ± 7.7 kg; FFM, 8.0 ± 7.1 kg; BF%, ?7.0 ± 6.6%). Imp‐SF and Tanita exhibited a smaller bias but wide limits of agreement (Imp‐SF: FM, ?1.1 ± 8.5 kg; FFM, 2.5 ± 7.9 kg; BF%, ?1.7 ± 7.3% Tanita: BF%, 1.2 ± 9.5%). Discussion: Compared with DXA, Imp‐MF produced large bias and wide limits of agreement, and its accuracy estimating body composition in overweight or obese men was poor. Imp‐SF and Tanita demonstrated little bias and may be useful for group comparisons, but their utility for assessment of body composition in individuals is limited.     

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.     

Validation of DXA Body Composition Estimates in Obese Men and Women

The aim of this study was to determine the accuracy of dual‐energy X‐ray absorptiometry (DXA)‐derived percentage fat estimates in obese adults by using four‐compartment (4C) values as criterion measures. Differences between methods were also investigated in relation to the influence of fat‐free mass (FFM) hydration and various anthropometric measurements. Six women and eight men (age 22–54 years, BMI 28.7–39.9 kg/m², 4C percent body fat (%BF) 31.3–52.6%) had relative body fat (%BF) determined via DXA and a 4C method that incorporated measures of body density (BD), total body water (TBW), and bone mineral mass (BMM) via underwater weighing, deuterium dilution, and DXA, respectively. Anthropometric measurements were also undertaken: height, waist and gluteal girth, and anterior‐posterior (A‐P) chest depth. Values for both methods were significantly correlated (r² = 0.894) and no significant difference (P = 0.57) was detected between the means (DXA = 41.1%BF, 4C = 41.5%BF). The slope and intercept for the regression line were not significantly different (P > 0.05) from 1 and 0, respectively. Although both methods were significantly correlated, intraindividual differences between the methods were sizable (4C‐DXA, range = ?3.04 to 4.01%BF) and significantly correlated with tissue thickness (chest depth) or most surrogates of tissue thickness (body mass, BMI, waist girth) but not FFM hydration and gluteal girth. DXA provided cross‐sectional %BF data for obese adults without bias. However, individual data are associated with large prediction errors (±4.2%BF). This error appears to be associated with tissue thickness indicating that the DXA device used may not be able to accurately account for beam hardening in obese cohorts.     

No apparent progress in bioelectrical impedance accuracy: validation against metabolic risk and DXA

Bioelectrical impedance (BIA) is quick, easy, and safe when quantifying fat and lean tissue. New BIA models (Tanita BC-418 MA, abbreviated BIA(8)) can perform segmental body composition analysis, e.g., estimate %trunkal fatness (%TF). It is not known, however, whether new BIA models can detect metabolic risk factors (MRFs) better than older models (Tanita TBF-300, abbreviated BIA(4)). We therefore tested the correlation between MRF and percentage whole-body fat (%BF) from BIA(4) and BIA(8) and compared these with the correlation between MRF and dual-energy X-ray absorptiometry (DXA, used as gold standard), BMI and waist circumference (WC). The sample consisted of 136 abdominally obese (WC >or= 88 cm), middle-aged (30-60 years) women. MRF included fasting blood glucose and insulin; high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides; high sensitive C-reactive protein, plasminogen activator inhibitor-1 (PAI-1), and fibrinogen; and alanine transaminase (ALT) liver enzyme. We found that similar to DXA, but in contrast to BMI, neither %BF BIA(4) nor %BF BIA(8) correlated with blood lipids or ALT. In the segmental analysis of %TF, BIA(8) only correlated with inflammatory markers, but not insulin, blood lipids, or ALT liver enzyme (in contrast to WC and %TF DXA). %TF DXA was associated with homeostatic model assessment insulin resistance (HOMA-IR) independently of WC (P = 0.03), whereas %TF BIA(8) was not (P = 0.53). Receiver-operating characteristic (ROC) curves confirmed that %TF BIA(8) did not differ from chance in the detection of insulin resistance (P = 0.26). BIA estimates of fatness were, at best, weakly correlated with obesity-related risk factors in abdominally obese women, even the new eight-electrode model. Our data support the continued use of WC and BMI.     

Comparison of DXA and CT in the Assessment of Body Composition in Premenopausal Women With Obesity and Anorexia Nervosa

Accurate methods for assessing body composition in subjects with obesity and anorexia nervosa (AN) are important for determination of metabolic and cardiovascular risk factors and to monitor therapeutic interventions. The purpose of our study was to assess the accuracy of dual‐energy X‐ray absorptiometry (DXA) for measuring abdominal and thigh fat, and thigh muscle mass in premenopausal women with obesity, AN, and normal weight compared to computed tomography (CT). In addition, we wanted to assess the impact of hydration on DXA‐derived measures of body composition by using bioelectrical impedance analysis (BIA). We studied a total of 91 premenopausal women (34 obese, 39 with AN, and 18 lean controls). Our results demonstrate strong correlations between DXA‐ and CT‐derived body composition measurements in AN, obese, and lean controls (r = 0.77–0.95, P < 0.0001). After controlling for total body water (TBW), the correlation coefficients were comparable. DXA trunk fat correlated with CT visceral fat (r = 0.51–0.70, P < 0.0001). DXA underestimated trunk and thigh fat and overestimated thigh muscle mass and this error increased with increasing weight. Our study showed that DXA is a useful method for assessing body composition in premenopausal women within the phenotypic spectrum ranging from obesity to AN. However, it is important to recognize that DXA may not accurately assess body composition in markedly obese women. The level of hydration does not significantly affect most DXA body composition measurements, with the exceptions of thigh fat.     

Relationship between Body Mass Index and Percent Body Fat in Vietnamese: Implications for the Diagnosis of Obesity

BackgroundThe burden of obesity in Vietnam has not been well defined because there is a lack of reference data for percent body fat (PBF) in Asians. This study sought to define the relationship between PBF and body mass index (BMI) in the Vietnamese population.MethodsThe study was designed as a comparative cross-sectional investigation that involved 1217 individuals of Vietnamese background (862 women) aged 20 years and older (average age 47 yr) who were randomly selected from the general population in Ho Chi Minh City. Lean mass (LM) and fat mass (FM) were measured by DXA (Hologic QDR 4500). PBF was derived as FM over body weight.ResultsBased on BMI ≥30, the prevalence of obesity was 1.1% and 1.3% for men and women, respectively. The prevalence of overweight and obesity combined (BMI ≥25) was ~24% and ~19% in men and women, respectively. Based on the quadratic relationship between BMI and PBF, the approximate PBF corresponding to the BMI threshold of 30 (obese) was 30.5 in men and 41 in women. Using the criteria of PBF >30 in men and PBF >40 in women, approximately 15% of men and women were considered obese.ConclusionThese data suggest that body mass index underestimates the prevalence of obesity. We suggest that a PBF >30 in men or PBF >40 in women is used as criteria for the diagnosis of obesity in Vietnamese adults. Using these criteria, 15% of Vietnamese adults in Ho Chi Minh City was considered obese.     

Dynamics of Change in Total and Regional Body Composition After Gastric Bypass in Obese Patients

Little is known on patterns of change over time in body composition, especially lean body mass (LBM), during massive weight loss after Roux‐en‐Y gastric bypass (RYGB) in obese patients. We performed sequential measurements of total and regional body composition in patients after RYGB, and we compared a subsample of patients after surgery to a nonsurgical control group of similar age and body fatness. We used dual‐energy X‐ray absorptiometry (DXA) before and at 3, 6, and 12 months after RYGB in 42 obese women (before surgery: age 39.5 ± 11.6 years; BMI 44.6 ± 6.1 kg/m²; mean ± s.d.) and in 48 control obese women referred for nonsurgical weight management, before weight loss. During 1‐year follow‐up after RYGB, there was a continuous decrease in body weight (?36.0 ± 12.5 kg at 1 year), total fat mass (FM) (?26.0 ± 9.1 kg), as well as in trunk and appendicular FM. In contrast, the decrease in total LBM (?9.8 ± 4.8 kg at 1 year), as well as in trunk and appendicular LBM, plateaued after 3–6 months. Rates of loss in weight, FM, and LBM were highest during the first 3‐month period after RYGB (6.4 ± 1.8, 4.1 ± 1.7, and 2.3 ± 1.2 kg/month, respectively), then decreased continuously for FM but plateaued for LBM. There was no evidence of a decrease in total, trunk, or appendicular LBM in weight‐reduced subjects compared to the control group. In conclusion, follow‐up of these obese women revealed a differential pattern of change in FM and LBM after RYGB. Despite an important loss in LBM, especially during the 3–6 months of initial period, LBM appears to be spared thereafter.     

Comparison of Methods to Assess Body Composition Changes during a Period of Weight Loss

Objective: To assess the accuracy of body composition measurements by air displacement plethysmography and bioelectrical impedance analysis (BIA) compared with DXA during weight loss. Research Methods and Procedures: Fifty‐six healthy but overweight participants, 34 women and 22 men (age, 52 ± 8.6 years; weight, 92.2 ± 11.6 kg; BMI, 33.3 ± 2.9 kg/m²) were studied in an outpatient setting before and after 6 months of weight loss (weight loss, 5.6 ± 5.5 kg). Subjects were excluded if they had initiated a new drug therapy within 30 days of randomization, were in a weight loss program, or took a weight loss drug within 90 days of randomization. Subjects were randomly assigned either to a self‐help program, consisting of two 20‐minute sessions with a nutritionist and provision of printed materials and other self‐help resources, or to attendance at meetings of a commercial program (Weight Watchers). Body composition was examined by each of the methods before and after weight loss. Results: BIA (42.4 ± 5.8%) underestimated percentage fat, whereas the BodPod (Siri = 51.7 ± 6.9%; Brozek = 48.5 ± 6.5%) overestimated percentage fat compared with DXA (46.1 ± 7.9%) before weight loss. Correlation coefficients for detecting changes in body composition between DXA and the other methods were relatively high, with Brozek Δfat mass (FM; r² = 0.63), Siri FM (r² = 0.65), tetrapolar BIA percentage fat (r² = 0.57), and Tanita FM (r² = 0.61) being the highest. Discussion: In conclusion, all of the methods were relatively accurate for assessing body composition compared with DXA, although there were biases. Furthermore, each of the methods was sensitive enough to detect changes with weight loss.     

Effect of high contents of dietary animal-derived protein or carbohydrates on canine faecal microbiota

Background

Few equations have been developed in veterinary medicine compared to human medicine to predict body composition. The present study was done to evaluate the influence of weight loss on biometry (BIO), bioimpedance analysis (BIA) and ultrasonography (US) in cats, proposing equations to estimate fat (FM) and lean (LM) body mass, as compared to dual energy x-ray absorptiometry (DXA) as the referenced method. For this were used 16 gonadectomized obese cats (8 males and 8 females) in a weight loss program. DXA, BIO, BIA and US were performed in the obese state (T0; obese animals), after 10% of weight loss (T1) and after 20% of weight loss (T2). Stepwise regression was used to analyze the relationship between the dependent variables (FM, LM) determined by DXA and the independent variables obtained by BIO, BIA and US. The better models chosen were evaluated by a simple regression analysis and means predicted vs. determined by DXA were compared to verify the accuracy of the equations.

Results

The independent variables determined by BIO, BIA and US that best correlated (p?<?0.005) with the dependent variables (FM and LM) were BW (body weight), TC (thoracic circumference), PC (pelvic circumference), R (resistance) and SFLT (subcutaneous fat layer thickness). Using Mallows??Cp statistics, p value and r ² , 19 equations were selected (12 for FM, 7 for LM); however, only 7 equations accurately predicted FM and one LM of cats.

Conclusions

The equations with two variables are better to use because they are effective and will be an alternative method to estimate body composition in the clinical routine. For estimated lean mass the equations using body weight associated with biometrics measures can be proposed. For estimated fat mass the equations using body weight associated with bioimpedance analysis can be proposed.     

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.     

Body composition determinants of metabolic phenotypes of obesity in nonobese and obese postmenopausal women

Objective : Although obesity is typically associated with increased cardiovascular risk, a subset of obese individuals display a normal metabolic profile (“metabolically healthy obese,” MHO) and conversely, a subset of nonobese subjects present with obesity‐associated cardiometabolic abnormalities (“metabolically obese nonobese,” MONO). The aim of this cross‐sectional study was to identify the most important body composition determinants of metabolic phenotypes of obesity in nonobese and obese healthy postmenopausal women. Design and Methods : We studied a total of 150 postmenopausal women (age 54 ± 7 years, mean ± 1 SD). Based on a cardiometabolic risk score, nonobese (body mass index [BMI] ≤ 27) and obese women (BMI > 27) were classified into “metabolically healthy” and “unhealthy” phenotypes. Total and regional body composition was assessed with dual‐energy X‐ray absorptiometry (DXA). Results : In both obese and nonobese groups, the “unhealthy” phenotypes were characterized by frequent bodyweight fluctuations, higher biochemical markers of insulin resistance, hepatic steatosis and inflammation, and higher anthropometric and DXA‐derived indices of central adiposity, compared with “healthy” phenotypes. Indices of total adiposity, peripheral fat distribution and lean body mass were not significantly different between “healthy” and “unhealthy” phenotypes. Despite having increased fat mass, MHO women exhibited comparable cardiometabolic parameters with healthy nonobese, and better glucose and lipid levels than MONO. Two DXA‐derived indices, trunk‐to‐legs and abdominal‐to‐gluteofemoral fat ratio were the major independent determinants of the “unhealthy” phenotypes in our cohort. Conclusions : The “metabolically obese phenotype” is associated with bodyweight variability, multiple cardiometabolic abnormalities and an excess of central relative to peripheral fat in postmenopausal women. DXA‐derived centrality ratios can discriminate effectively between metabolic subtypes of obesity in menopause.     

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.     

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.     

Comparison of the Classification of Obesity by BMI vs. Dual‐energy X‐ray Absorptiometry in the Newfoundland Population

Although BMI is the most widely used measure of obesity, debate still exists on how accurately BMI defines obesity. In this study, adiposity status defined by BMI and dual‐energy X‐ray absorptiometry (DXA) was compared in a large population to evaluate the accuracy of BMI. A total of 1,691 adult volunteers from Newfoundland and Labrador participated in the study. BMI and body fat percentage (%BF) were measured for all subjects following a 12‐h fasting period. Subjects were categorized as underweight (UW), normal weight (NW), overweight (OW), or obese (OB) based on BMI and %BF criteria. Differences between the two methods were compared within gender and by age‐groups. According to BMI criteria, 1.2% of women were classified as UW, 44.2% as NW, 34.2% as OW, and 20.3% as OB. When women were classified according to %BF criteria, 2.2% were UW, 29.6% were NW, 30.9% were OW, and 37.1% were OB. The overall discrepancy between the two methods for women was substantial at 34.7% (14.6% for NW and 16.8% for OB, P < 0.001). In men, the overall discrepancy was 35.2% between BMI and DXA (17.6% for OW and 13.5% for OB, P < 0.001). Misclassification by BMI was dependent on age, gender, and adiposity status. In conclusion, BMI misclassified adiposity status in approximately one‐third of women and men compared with DXA. Caution should be taken when BMI is used in clinical and scientific research as well as clinical practice.     

Similarity in Percent Body Fat Between White and Vietnamese Women: Implication for a Universal Definition of Obesity

It has been widely assumed that for a given BMI, Asians have higher percent body fat (PBF) than whites, and that the BMI threshold for defining obesity in Asians should be lower than the threshold for whites. This study sought to test this assumption by comparing the PBF between US white and Vietnamese women. The study was designed as a comparative cross‐sectional investigation. In the first study, 210 Vietnamese women ages between 50 and 85 were randomly selected from various districts in Ho Chi Minh City (Vietnam). In the second study, 419 women of the same age range were randomly selected from the Rancho Bernardo Study (San Diego, CA). In both studies, lean mass (LM) and fat mass (FM) were measured by dual‐energy X‐ray absorptiometry (DXA) (QDR 4500; Hologic). PBF was derived as FM over body weight. Compared with Vietnamese women, white women had much more FM (24.8 ± 8.1 kg vs. 18.8 ± 4.9 kg; P < 0.0001) and greater PBF (36.4 ± 6.5% vs. 35.0 ± 6.2%; P = 0.012). However, there was no significant difference in PBF between the two groups after matching for BMI (35.1 ± 6.2% vs. 35.0 ± 5.7%; P = 0.87) or for age and BMI (35.6 ± 5.1% vs. 35.8 ± 5.9%; P = 0.79). Using the criteria of BMI ≥30, 19% of US white women and 5% of Vietnamese women were classified as obese. Approximately 54% of US white women and 53% of Vietnamese women had their PBF >35% (P = 0.80). Although white women had greater BMI, body weight, and FM than Vietnamese women, their PBF was virtually identical. Further research is required to derive a more appropriate BMI threshold for defining obesity for Asian women.     

Does Isolated Unilateral Hip or Knee Osteoarthritis Lead to Adverse Changes in Extremity Composition?

BackgroundWhile muscle atrophy is a function of normal aging, loss of muscle in the setting of hip and knee osteoarthritis (OA) has been observed using radiographic studies. There is limited data available regarding changes in extremity composition using bioimpedance (BIA). The purpose of this study was to assess the changes in extremity composition in patients with isolated, unilateral hip or knee OA using BIA.MethodsPatients presenting to our institution’s adult reconstruction clinic from February 2020 to April 2021 were retrospectively reviewed to identify those with isolated, unilateral hip and knee OA. The InBody 770 Body Composition Analyzer (InBody USA, Cerritos, California) was used to perform a complete body composition assessment, per protocol. Lean extremity mass (LEM), fat mass (FM), intracellular water (ICW), extremity body water (EBW = ICW + extracellular water (ECW)) and phase angle (PA) were determined. Differences between the affected (OA) and unaffected (no OA) extremities were compared using t-tests.Results38 patients had isolated hip OA. The mean age was 60.8 (±11.7) years, mean BMI was 31.7 (±6.8) kg/m2, and 39.5% were female. LEM, FM, EBW, ICW, and PA were significantly decreased in the hip OA extremity (LEM: 20.0 vs. 20.4 kg, p=0.0008, FM: 8.8 vs. 8.9 kg, p=0.0049, EBW: 15.7 vs 16.0, p=0.0011, ICW: 9.5 vs. 9.7 L, p=0.0004, PA: 4.5 vs 4.9º, p<0.0001). There were 25 patients with isolated knee OA. Mean age was 62.8 (±11.3) years, mean BMI was 33.6 (±6.9) kg/m2, and 52.0% were female. FM and PA were significantly lower in the knee OA extremity (11.3 vs 11.4 kg, p=0.0291, 4.5 vs 4.9º, p<0.0001). There were no significant differences in LEM, EBW, and ICW between the knee OA extremity and the unaffected extremity.ConclusionPatients with isolated, unilateral hip OA had decreased LEM, FM, EBW, and ICW in the affected extremity. Both unilateral hip and knee OA was associated with decreased PA, suggestive of greater underlying dysfunction in muscle or cellular performance. Further study is needed to better define when these abnormalities develop, how they progress over time, and the impact of targeted interventions in reversing these changes. Level of Evidence: III     

Usefulness of Anthropometry and DXA in Predicting Intra‐abdominal Fat in Obese Men and Women

Objective: To investigate the usefulness of anthropometry and DXA in predicting intra‐abdominal fat (IAF) in obese men and women. Research Methods and Procedures: Observational, cross sectional study of 22 women and 18 men with a body mass index of 30 or above. IAF from 20 cm above and 10 cm below the L4 to L5 intervertebral disc was measured by magnetic resonance imaging (MRI) as a reference method. Central abdominal fat was measured from the upper border of L2 to the lower border of L4 by DXA. Waist and hip circumferences were also measured. Results: In obese women DXA, waist circumference and waist‐hip ratio were equally well correlated with IAF (r = 0.74, 0.75, and 0.70, respectively). In obese men DXA was moderately correlated with IAF measured by MRI (r = 0.46), whereas waist circumference and waist‐hip ratio were not significantly correlated with IAF. Discussion: The prediction of IAF in obese subjects was highly dependent on sex more than in non‐obese persons. Anthropometry and DXA were equally useful in obese women, whereas anthropometry had no predictive power and DXA was the only acceptable predictor of IAF in obese men.     

The relationship of waist circumference and BMI to visceral, subcutaneous, and total body fat: sex and race differences

The purpose of this study was to examine sex and race differences in the relationship between anthropometric measurements and adiposity in white and African-American (AA) adults. Visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) areas were measured with computed tomography (CT). Fat mass (FM) was measured with dual-energy-X-ray absorptiometry (DXA). Correlation coefficients were used to assess the relationship of waist circumference (WC) and BMI to VAT, SAT, and FM within sex-by-race groups. General linear models were used to compare relationships between WC or BMI, and adiposity across sex and race, within age groups (18-39 and 40-64 years). The sample included 1,667 adults (men: 489 white; 120 AA; women: 666 white, 392 AA). WC and BMI correlations were highest for FM and SAT compared to VAT. Women had higher FM levels than men regardless of WC, but the sex difference in FM was attenuated in younger AA adults with a high BMI. For a given level of WC or BMI, women had higher levels of SAT than men; however, significant interactions indicated that the relationship was not consistent across all levels of BMI and WC. Sex and race differences in VAT varied significantly with WC and BMI. In general, white adults had higher levels of VAT than AA adults at higher levels of BMI and WC. Sex differences, and in some instances race differences, in the relationships between anthropometry and fat-specific depots demonstrate that these characteristics need to be considered when predicting adiposity from WC or BMI.