Body adiposity index assess body fat with high accuracy in nondialyzed chronic kidney disease patients

Objective:

High body fat (BF) is an alarming condition that also affects nondialyzed chronic kidney disease (CKD) patients. Distinct methods are used to evaluate BF; however, in CKD population it remains unclear which one is more reliable showing high accuracy. Dual‐energy X‐ray absorptiometry (DXA), used as reference method to estimate adiposity, is expensive and time consuming to be applied in clinical settings. Recently, a new body adiposity index (BAI), that estimates BF from easily accessible measures, was validated in the general population. The aim of this study was to evaluate which simple and practical method, routinely used to estimate BF, shows the highest accuracy compared with DXA, in nondialyzed CKD patients.

Design and Methods:

In this cross‐sectional study BF was estimated by DXA, bioelectrical impedance analysis (BIA), anthropometry (ANTHRO), and BAI. Serum leptin levels were determined.

Results:

Studied patients (n = 134) were 55% males, 54% overweight/obese, and 64.9 ± 12.5 years old, with estimated glomerular filtration rate (eGFR) = 29.0 ± 12.7 ml/min. The correlation coefficient was higher between DXA vs. ANTHRO (r = 0.76) and BAI (r = 0.61) than with BIA (r = 0.57), after adjusting for gender, age, and eGFR (P < 0.0001). Therefore, the Lin's concordance correlation coefficient and Bland–Altman plots were performed to measure the accuracy (C_b) between DXA with both ANTHRO and BAI. A higher accuracy (C_b = 0.82) and lower mean difference (?3.4%) was observed for BAI than for ANTHRO (C_b = 0.61; ?8.4%). Leptin levels correlated (P < 0.0001) with DXA (r = 0.56) and BAI (r = 0.59).

Conclusions:

These findings suggest that BAI estimates BF with high accuracy in nondialyzed CKD patients and may be helpful in the treatment of this population with increased BF.

     

Skinfolds and coronary heart disease risk factors are more strongly associated with BMI than with the body adiposity index

Objective:

A recent, cross‐sectional analysis of adults found that the hip circumference divided by height^1.5 minus 18 (the body adiposity index, BAI) was strongly correlated (r = 0.79) with percent body fat determined by dual energy X‐ray absorptiometry. The BAI was proposed as a more accurate index of body fatness than BMI. We examined whether BAI was more strongly related, than was BMI and waist circumference, to skinfold thicknesses and levels of various risk factors for coronary heart disease.

Design and Methods:

Cross‐sectional analyses of adults (n = 14,263 for skinfold thickness; n=6291 for fasting lipid levels) in the National Health and Nutrition Examination Survey (NHANES) III, 1988‐1994.

Results:

As compared with BMI and waist circumference, we found that BAI was less strongly associated with the skinfold sum and with risk factor levels. For example, correlations with the skinfold sum were r = 0.79 (BMI) vs. r = 0.70 (BAI) among men, and r = 0.86 (BMI) vs. r = 0.79 (BAI) among women; p < 0.001 for the difference between each pair of correlations. An overall index of the 7 risk factors was also more strongly associated with BMI and waist circumference than BAI in analyses stratified by sex, race‐ethnicity and age. Multivariable analyses indicated that if BMI was known, BAI provided little additional information on risk factor levels.

Conclusions:

Based on the observed associations with risk factor levels and skinfold thicknesses, we conclude that BAI is unlikely to be a better index of adiposity than BMI.     

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.     

Percentage Fat in Overweight and Obese Children: Comparison of DXA and Air Displacement Plethysmography**

Objective: To compare percentage body fat (percentage fat) estimates from DXA and air displacement plethysmography (ADP) in overweight and obese children. Research Methods and Procedures: Sixty‐nine children (49 boys and 20 girls) 14.0 ± 1.65 years of age, with a BMI of 31.3 ± 5.6 kg/m² and a percentage fat (DXA) of 42.5 ± 8.4%, participated in the study. ADP body fat content was estimated from body density (D_b) using equations devised by Siri (ADP_Siri) and Lohman (ADP_Loh). Results: ADP estimates of percentage fat were highly correlated with those of DXA in both male and female subjects (r = 0.90 to 0.93, all p < 0.001; standard error of estimate = 2.50% to 3.39%). Compared with DXA estimates, ADP_Siri and ADP_Loh produced significantly (p < 0.01) lower estimates of mean body fat content in boys (?2.85% and ?4.64%, respectively) and girls (?2.95% and ?5.15%, respectively). Agreement between ADP and DXA methods was further examined using the total error and methods of Bland and Altman. Total error ranged from 4.46% to 6.38% in both male and female subjects. The 95% limits of agreement were relatively similar for all percentage fat estimates, ranging from ±6.73% to ±7.94%. Discussion: In this study, conversion of D_b using the Siri equation led to mean percentage fat estimates that agreed better with those determined by DXA compared with the Lohman equations. However, relatively high limits of agreement using either equation resulted in percentage fat estimates that were not interchangeable with percentage fat determined by DXA.     

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.     

Concordance of the recently published body adiposity index with measured body fat percent in European-American adults

The body adiposity index (BAI; hip circumference (cm)/height (m)(1.5) - 18) has recently been shown to demonstrate a stronger correlation with percentage body fat (%fat) than that between the BMI and %fat in Mexican-American adults. Here, we compare the concordance between %fat from dual-energy X-ray absorptiometry (DXA) and BAI, and between %fat and BMI, in European-American adults (n = 623). Agreement between BAI, BMI, and %fat was assessed using Lin's concordance coefficients (ρ(c)), where values <0.90 are considered poor. In the sample as a whole, the agreement between BAI and %fat (ρ(c) = 0.752) was far better than that between BMI and %fat (ρ(c) = 0.445) but was nonetheless relatively poor. There were large mean differences in %fat between the BAI and DXA %fat, particularly at lower levels of adiposity (<20%), and further the BAI overestimated %fat in males and underestimated %fat in females. Optimizing the BAI formula for our sample only marginally improved performance. Results of the present study show that BAI provides a better indicator of adiposity in European-American adults than does BMI, but does not provide valid estimates of %fat, particularly at lower levels of body fatness. Further research is warranted to investigate the predictive ability of BAI for various health outcomes.     

Compulsive buying: Relationship with body mass index

Objective:

Compulsive buying has historically been associated with various self‐regulatory disturbances, including eating pathology (e.g., binge eating). Therefore, a relationship between scores on a measure of compulsive buying, the Compulsive Buying Scale (CBS), and body mass index (BMI) in adulthood was hypothesized.

Design and Methods:

Using a self‐report survey methodology in a cross‐sectional consecutive sample of convenience of 373 obstetrics/gynecology patients, correlations between CBS scores and BMI, both generally and with regard to race were examined.

Results:

A modest general correlation between CBS scores and BMI (r = 0.17, P < 0.01) was found. However, when these data were examined by race, CBS scores and BMI were significantly related among Caucasian women (r = 0.25, P < 0.01), but not in African American women (r = 0.04, P = n.s.).

Conclusions:

Findings indicate that compulsive buying is associated with increasing BMI in adulthood, particularly among Caucasian women.     

A new method for body fat evaluation, body adiposity index, is useful in women with familial partial lipodystrophy

BMI is a widely used method to evaluate adiposity. However, it has several limitations, particularly an inability to differentiate lean from fat mass. A new method, body adiposity index (BAI), has been recently proposed as a new measurement capable to determine fat excess better than BMI. The aim of this study was to investigate BAI as a mean to evaluate adiposity in a group of women with familial partial lipodystrophy (FPLD) and compare it with BMI. Thirteen women with FLPD Dunnigan type (FPLD2) and 13 healthy volunteers matched by age and BMI were studied. Body fat content and distribution were analyzed by dual X-ray absorptiometry (DXA). Plasma leptin was also measured. BAI was significantly lower in FPLD2 in comparison to control group (24.6 ± 1.5 vs. 30.4 ± 4.3; P < 0.001) and presented a more significant correlation with total fat (%) (r = 0.71; P < 0.001) and fat Mass (g) (r = 0.80; P < 0.001) than BMI (r = 0.27; P = 0.17 for total fat and r = 0.52; P = 0.006 for fat mass). There was a correlation between leptin and BAI (r = 0.57; P = 0.01), [corrected] but not between leptin and BMI. In conclusion, BAI was able to catch differences in adiposity in a sample of FPLD2 patients. It also correlated better with leptin levels than BMI. Therefore, we provide further evidence that BAI may become a more reliable indicator of fat mass content than the currently available measurements.     

Body Composition at 6 months of Life: Comparison Of Air Displacement Plethysmography and Dual‐Energy X‐Ray Absorptiometry

Body composition assessment during infancy is important because it is a critical period for obesity risk development, thus valid tools are needed to accurately, precisely, and quickly determine both fat and fat‐free mass. The purpose of this study was to compare body composition estimates using dual‐energy x‐ray absorptiometry (DXA) and air displacement plethysmography (ADP) at 6 months old. We assessed the agreement between whole body composition using DXA and ADP in 84 full‐term average‐for‐gestational‐age boys and girls using DXA (Lunar iDXA v11–30.062; Infant whole body analysis enCore 2007 software, GE, Fairfield, CT) and ADP (Infant Body Composition System v3.1.0, COSMED USA, Concord, CA). Although the correlations between DXA and ADP for %fat (r = 0.925), absolute fat mass (r = 0.969), and absolute fat‐free mass (r = 0.945) were all significant, body composition estimates by DXA were greater for both %fat (31.1 ± 3.6% vs. 26.7 ± 4.7%; P < 0.001) and absolute fat mass (2,284 ± 449 vs. 1,921 ± 492 g; P < 0.001), and lower for fat‐free mass (5,022 ± 532 vs. 5,188 ± 508 g; P < 0.001) vs. ADP. Inter‐method differences in %fat decreased with increasing adiposity and differences in fat‐free mass decreased with increasing infant age. Estimates of body composition determined by DXA and ADP at 6 months of age were highly correlated, but did differ significantly. Additional work is required to identify the technical basis for these rather large inter‐method differences in infant body composition.     

Body composition of obese subjects by air displacement plethysmography: The influence of hydration

Objective: We investigated whether air displacement plethysmography (ADP) could detect small changes in body composition of obese subjects with alterations in hydration. Research Methods and Procedures: Ten obese subjects (mean BMI, 39.3 ± 2.8 kg/m²) entered the ADP chamber without and with oil (1, 2, or 4 liters), water (1, 2, or 4 liters), or mixed (1 liter oil + 1 liter water or 2 liters oil + 2 liters water) loads. Real and measured changes in body composition were compared by regression analysis and Bland‐Altman procedures. Results: The ADP‐measured changes in volume did not differ from the real values and were strongly correlated with them (r = 0.98). In all cases, loads of differing composition and similar volume led to different values of fat, fat‐free mass, and percentage fat. Water was detected as increased fat‐free mass only with loads of ≥2 liters, most of the water being falsely detected as increased fat mass. The observed changes were correlated with the real ones for fat mass (r = 0.68; p < 0.0001), fat‐free mass (r = 0.66; p < 0.0001), and percentage fat (r = 0.61; p < 0.0001), but fat mass changes were overestimated by ～1 kg, and fat‐free mass changes were underestimated by ～1 kg. This underestimation increased with the highest water loads, as shown by the Bland‐Altman plot (r = ?0.27; p < 0.05). Percentage fat changes were overestimated by 0.8% (p < 0.001); the magnitude of the error was correlated with the weight of the water load (r = 0.62; p < 0.0001). Discussion: ADP accurately measures changes in body volume, discriminating small changes in body composition. It overestimates changes in adiposity, as most of the increased hydration is detected as an enlarged fat mass.     

A cross‐sectional study of osteocalcin and body fat measures among obese adolescents

Osteocalcin (OCN), a marker of osteoblast activity, has been implicated in the regulation of energy metabolism by the skeleton and thus may affect body fat measures.

Objective:

To examine the relationships of OCN to body fat measures and whether they vary according to markers of energy and vitamin D metabolism.

Design and Methods:

Data were obtained from 58 obese adolescents aged 13‐17.9 years (38 females, 8 black or African‐American). Total fat mass (FM) [dual X‐ray absorptiometry (DXA)] and visceral adipose tissue (VAT) [computerized axial tomography (CT)] were calculated. Blood tests included leptin, OCN, 25‐hydroxyvitamin D [25(OH)D], parathyroid hormone (PTH), thyroid function tests, and triglycerides. Markers of glucose metabolism were obtained from fasting and OGTT samples.

Results and Conclusions:

Adolescents with 25(OH)D <20 ng mL^?1 were considered deficient (n = 17/58); none had high PTH (PTH ≥ 65 pg mL^?1). OCN was associated with lower VAT (?84.27 ± 33.89 mm²) and BMI (?0.10 ± 0.05 kg m^?2), not FM (P = 0.597) in a core model including age, sex, race, geographic latitude, summer, height z‐score, and tanner stage. Adding 25(OH)D deficiency and PTH attenuated the inverse association of OCN to VAT. There was a significant interaction of OCN and 25(OH)D deficiency on FM (0.37 ± 0.18 kg, P = 0.041) and BMI (0.28 ± 0.10 kg m^?2, P = 0.007) in this adjusted model, which was further explained by leptin. Adding A1C to the core model modified the relationship of OCN to VAT (?93.08 ± 35.05 mm², P = 0.011), which was further explained by HOMA‐IR. In summary, these findings provide initial evidence for a relationship between OCN and body fat measures that is dependent on energy metabolism and vitamin D status among obese adolescents.

     

Gestational and early life influences on infant body composition at 1 year

Excess weight gain during both pre‐ and postnatal life increases risk for obesity in later life. Although a number of gestational and early life contributors to this effect have been identified, there is a dearth of research to examine whether gestational factors and weight gain velocity in infancy exert independent effects on subsequent body composition and fat distribution.

Objective:

To test the hypothesis that birth weight, as a proxy of prenatal weight gain, and rate of weight gain before 6 months would be associated with total and truncal adiposity at 12 months of age.

Design and Methods:

Healthy, term infants (N = 47) were enrolled in the study and rate of weight gain (g/day) was assessed at 0‐3 months, 3‐6 months, and 6‐12 months.

Results:

Total and regional body composition were measured by dual‐energy X‐ray absorptiometry (DXA) at 12 months. Stepwise linear regression modeling indicated that lean mass at 12 months, after adjusting for child length, was predicted by rate of weight gain during each discrete period of infancy (P < 0.05), and by maternal pre‐pregnancy BMI (P < 0.05). Total fat mass at 12 months was predicted by rate of weight gain during each discrete period (P < 0.01), and by older maternal age at delivery (P < 0.05). Trunk fat mass at 12 months, after adjusting for leg fat mass, was predicted by rate of weight gain from 0‐3 months and 3‐6 months (P < 0.05).

Conclusion:

Results suggest that growth during early infancy may be a critical predictor of subsequent body composition and truncal fat distribution.     

Regional Body Composition: Cross‐calibration of DXA Scanners—QDR4500W and Discovery Wi

Differences exist in body composition assessed by dual‐energy X‐ray absorptiometers (DXAs) between devices produced by different manufacturers and different models from the same manufacturer. Cross‐calibration is needed to allow body composition results to be compared in multicenter trials or when scanners are replaced. The aim was to determine reproducibility and extent of agreement between two fan‐beam DXA scanners (QDR4500W, Discovery Wi) for body composition of regional sites. The sample was: 39 women 50.6 ± 9.6 years old with BMI 26.8 ± 5.5 kg/m², body fat 33 ± 7%. Four whole body scans (two on each device) were performed over 3 weeks. Major variables were fat mass, nonosseous lean mass, and bone mineral content (BMC) for the truncal and appendicular regions. Extent of agreement was assessed using Bland and Altman plots. Both devices demonstrated good precision with mean test–retest differences close to zero for fat mass, nonosseous lean mass, and BMC of the truncal and appendicular regions. Evaluation of interdevice agreement revealed significant differences for truncal and appendicular BMC, nonosseous lean mass, and fat mass. The greatest interdevice difference was for truncal fat mass (0.69 ± 0.60 kg). Differences in truncal and appendicular fat mass increased in magnitude at higher mean values. Furthermore, differences in truncal and appendicular fat mass were strongly related to BMI (R = ?0.61, R = ?0.55, respectively). In conclusion, in vivo cross‐calibration is important to ensure comparability of regional body composition data between scanners, especially for truncal fat mass and for subjects with higher BMI.     

Obesity and body fat classification in the metabolic syndrome: Impact on cardiometabolic risk metabotype

Objective:

Obesity is a key factor in the development of the metabolic syndrome (MetS), which is associated with increased cardiometabolic risk. We investigated whether obesity classification by BMI and body fat percentage (BF%) influences cardiometabolic profile and dietary responsiveness in 486 MetS subjects (LIPGENE dietary intervention study).

Design and Methods:

Anthropometric measures, markers of inflammation and glucose metabolism, lipid profiles, adhesion molecules, and hemostatic factors were determined at baseline and after 12 weeks of four dietary interventions (high saturated fat (SFA), high monounsaturated fat (MUFA), and two low fat high complex carbohydrate (LFHCC) diets, one supplemented with long chain n‐3 polyunsaturated fatty acids (LC n‐3 PUFAs)).

Results:

About 39 and 87% of subjects classified as normal and overweight by BMI were obese according to their BF%. Individuals classified as obese by BMI (≥30 kg/m²) and BF% (≥25% (men) and ≥35% (women)) (OO, n = 284) had larger waist and hip measurements, higher BMI and were heavier (P < 0.001) than those classified as nonobese by BMI but obese by BF% (NOO, n = 92). OO individuals displayed a more proinflammatory (higher C reactive protein (CRP) and leptin), prothrombotic (higher plasminogen activator inhibitor‐1 (PAI‐1)), proatherogenic (higher leptin/adiponectin ratio) and more insulin resistant (higher HOMA‐IR) metabolic profile relative to the NOO group (P < 0.001). Interestingly, tumor necrosis factor‐α (TNF‐α) concentrations were lower post‐intervention in NOO individuals compared with OO subjects (P < 0.001).

Conclusions:

In conclusion, assessing BF% and BMI as part of a metabotype may help to identify individuals at greater cardiometabolic risk than BMI alone.     

Relationship between the percentage of body fat and surrogate indices of fatness in male and female Polish active and sedentary students

Background

Limited data have indicated that body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR) and waist to height ratio (WHtR) of athletes and young adults provide misleading results concerning body fat content. This study was aimed at the evaluation of the relationship between different surrogate indices of fatness (BMI, WC, WHR, WHtR and body adiposity index (BAI)) with the percentage of body fat in Polish students with respect to their sex and physical activity.

Methods

A total of 272 students volunteered to participate in the study. Of these students, 177 physical education students (90 males and 87 females) were accepted as active (physical activity of 7 to 9 hours/week); and 95 students of other specializations (49 males and 46 females) were accepted as sedentary (physical activity of 1.5 hours/week). Weight, height, waist and hip circumferences were measured, and BMI, WHR, WHtR and BAI were calculated. Body fat percentage was assessed using four skinfold measurements.

Results

Classification of fatness according to the BMI and the percentage of body fat have indicated that BMI overestimates fatness in lean subjects (active men and women, sedentary men), but underestimates body fat in obese subjects (sedentary women). In all groups, BMI, WHR, WHtR and BAI were significantly correlated with the percentage of body fat (with the exception of WHR and hip circumference in active and sedentary women, respectively). However, coefficients of determination not exceeding 50% and Lin’s concordance correlation coefficients lower than 0.9 indicated no relationship between measured and calculated body fat.

Conclusion

The findings in the present study support the concept that irrespective of physical activity and sex none of the calculated indices of fatness are useful in the determination of body fat in young adults. Thus, it seems that easily calculated indices may contribute to distorted body image and unhealthy dietary habits observed in many young adults in Western countries, but also in female athletes.     

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.     

Obesity is underestimated using body mass index and waist-hip ratio in long-term adult survivors of childhood cancer

Objective

Obesity, represented by high body mass index (BMI), is a major complication after treatment for childhood cancer. However, it has been shown that high total fat percentage and low lean body mass are more reliable predictors of cardiovascular morbidity. In this study longitudinal changes of BMI and body composition, as well as the value of BMI and waist-hip ratio representing obesity, were evaluated in adult childhood cancer survivors.

Methods

Data from 410 survivors who had visited the late effects clinic twice were analyzed. Median follow-up time was 16 years (interquartile range 11–21) and time between visits was 3.2 years (2.9–3.6). BMI was measured and body composition was assessed by dual X-ray absorptiometry (DXA, Lunar Prodigy; available twice in 182 survivors). Data were compared with healthy Dutch references and calculated as standard deviation scores (SDS). BMI, waist-hip ratio and total fat percentage were evaluated cross-sectionally in 422 survivors, in who at least one DXA scan was assessed.

Results

BMI was significantly higher in women, without significant change over time. In men BMI changed significantly with time (ΔSDS = 0.19, P<0.001). Percentage fat was significantly higher than references in all survivors, with the highest SDS after cranial radiotherapy (CRT) (mean SDS 1.73 in men, 1.48 in women, P<0.001). Only in men, increase in total fat percentage was significantly higher than references (ΔSDS = 0.22, P<0.001). Using total fat percentage as the gold standard, 65% of female and 42% of male survivors were misclassified as non-obese using BMI. Misclassification of obesity using waist-hip ratio was 40% in women and 24% in men.

Conclusions

Sixteen years after treatment for childhood cancer, the increase in BMI and total fat percentage was significantly greater than expected, especially after CRT. This is important as we could show that obesity was grossly underestimated using BMI and waist-hip ratio.     

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.     

Association between body mass index and muscularity in healthy older Japanese women and men

Background

Body mass index (BMI), expressed as the ratio of body mass to height squared (kg/m²), involves not only fat but also lean mass. The present study aimed to clarify how BMI is associated with total muscle mass (TMM) in older Japanese women and men.

Findings

Using a B-mode ultrasound apparatus, muscle thickness was measured at nine sites (forearm, upper arm anterior and posterior, thigh anterior and posterior, lower leg anterior and posterior, abdomen, and subscapular) for 346 women (BMI 16.40 to 33.11 kg/m²) and 286 men (BMI 16.86 to 31.18 kg/m²) aged 60.0 to 79.5 yrs. TMM was estimated using the product of the sum of the muscle thicknesses at the nine sites with height as an independent variable. For both sexes, the estimated TMM relative to height squared was significantly correlated with BMI (r = 0.688, P<0.0001 for women; r = 0.696, P<0.0001 for men), but the percentage of the estimated TMM in body mass was not.

Conclusion

These results indicate that, for older Japanese women and men, BMI is a simple and convenient index for assessing total muscularity.