Cross-calibration of eight-polar bioelectrical impedance analysis versus dual-energy X-ray absorptiometry for the assessment of total and appendicular body composition in healthy subjects aged 21-82 years

AIM: To calibrate eight-polar bioelectrical impedance analysis (BIA) against dual-energy X-ray absorptiometry (DXA) for the assessment of total and appendicular body composition in healthy adults. RESEARCH DESIGN: A cross-sectional study was carried out. SUBJECTS: Sixty-eight females and 42 males aged 21-82 years participated in the study. METHODS: Whole-body fat-free mass (FFM) and appendicular lean tissue mass (LTM) were measured by DXA; resistance (R) of arms, trunk and legs was measured by eight-polar BIA at frequencies of 5, 50, 250 and 500 kHz; whole-body resistance was calculated as the sum R of arms, trunk and legs. RESULTS: The resistance index (RI), i.e. the height(2)/resistance ratio, was the best predictor of FFM and appendicular LTM. As compared with weight (Wt), RI at 500 kHz explained 35% more variance of FFM (vs 0.57), 45% more variance of LTM(arm) (vs 0.48) and 36% more variance of LTM(leg) (vs 0.50) (p < 0.0001 for all). The contribution of age to the unexplained variance of FFM and appendicular LTM was nil or negligible and the RI x sex interactions were either not significant or not important on practical grounds. The percent root mean square error of the estimate was 6% for FFM and 8% for LTM(arm) and LTM(leg). CONCLUSION: Eight-polar BIA offers accurate estimates of total and appendicular body composition. The attractive hypothesis that eight-polar BIA is influenced minimally by age and sex should be tested on larger samples including younger individuals.     

Cross-calibration of eight-polar bioelectrical impedance analysis versus dual-energy X-ray absorptiometry for the assessment of total and appendicular body composition in healthy subjects aged 21-82 years

Aim: To calibrate eight-polar bioelectrical impedance analysis (BIA) against dual-energy X-ray absorptiometry (DXA) for the assessment of total and appendicular body composition in healthy adults. Research design: A cross-sectional study was carried out. Subjects: Sixty-eight females and 42 males aged 21-82 years participated in the study. Methods: Whole-body fat-free mass (FFM) and appendicular lean tissue mass (LTM) were measured by DXA; resistance ( R ) of arms, trunk and legs was measured by eight-polar BIA at frequencies of 5, 50, 250 and 500 kHz; whole-body resistance was calculated as the sum R of arms, trunk and legs. Results: The resistance index (RI), i.e. the height 2 /resistance ratio, was the best predictor of FFM and appendicular LTM. As compared with weight (Wt), RI at 500 kHz explained 35% more variance of FFM ( vs 0.57), 45% more variance of LTM arm ( vs 0.48) and 36% more variance of LTM leg ( vs 0.50) ( p < 0.0001 for all). The contribution of age to the unexplained variance of FFM and appendicular LTM was nil or negligible and the RI &#50 sex interactions were either not significant or not important on practical grounds. The percent root mean square error of the estimate was 6% for FFM and 8% for LTM arm and LTM leg. Conclusion: Eight-polar BIA offers accurate estimates of total and appendicular body composition. The attractive hypothesis that eight-polar BIA is influenced minimally by age and sex should be tested on larger samples including younger individuals.     

Assessing the body composition of 6–17‐year‐old black and white girls in field studies

The purpose of the study was to develop ethnic‐specific equations for fat‐free mass (FFM) from selected anthropometric dimensions and bioelectrical impedance measures of resistance (R) and reactance (X_c) for use in the NHLBI Growth and Heath Study. Using dual‐energy X‐ray absorptiometry measures of body composition as the dependent variable and field measures of body composition by anthropometry and bioelectrical impedance as the explanatory variables, ethnic‐specific prediction equations were developed on a sample of girls representing a wide range of ages and BMI. The equations were cross‐validated using (1) the Prediction of Sum of Squares (PRESS) statistic and (2) an independent sample of 20 girls of each race from a study conducted at the National Institute of Child Health and Human Development (NICHD). Subjects were 65 White and 61 Black girls 6–17 years of age. The best race‐specific equations for FFM each explained 99% and 97% of the variance in the White and Black girls, respectively. Root mean square errors (RMSE) ranged from 1.14 to 1.95 kg. The equation for Black girls used Stature²/Resistance (R), weight, and reactance (X_c) as predictor variables; the equation for White girls used Stature²/R, weight, and triceps skinfold thickness. The results indicate that (1) equations to predict FFM in girls should be ethnic‐specific and that (2) accurate values for TBF and %BF can be calculated from the predicted FFM. Am. J. Hum. Biol. 13:249–254, 2001. © 2001 Wiley‐Liss, Inc.     

Assessment of fat-free mass from bioelectrical impedance analysis in obese women with Prader-Willi syndrome

Background: Fat-free mass (FFM) is lower in obese subjects with Prader-Willi syndrome (PWS) than in obese subjects without PWS. FFM prediction equations developed in non-PWS subjects may, thus, not work in PWS subjects.

Aim: To test whether the estimation of FFM from bioelectrical impedance analysis (BIA) in PWS subjects requires population-specific equations.

Methods: Using dual-energy X-ray absorptiometry, this study measured FFM in 27 PWS and 56 non-PWS obese women and evaluated its association with the impedance index at 50?kHz (ZI₅₀), i.e. the ratio between squared height and whole-body impedance at 50?kHz.

Results: At the same level of ZI₅₀, PWS women had a lower FFM than non-PWS women. However, when PWS-specific equations were used, FFM was accurately estimated at the population level. An equation employing a dummy variable coding for PWS status was able to explain 85% of the variance of FFM with a root mean squared error of 3.3?kg in the pooled sample (n?=?83).

Conclusion: Population-specific equations are needed to estimate FFM from BIA in obese PWS women.     

Validation of different bioimpedance analyzers for predicting cell mass against whole-body counting of potassium (40K) as a reference method.

This study compared two different tetrapolar bioimpedance (BIA) devices for estimating body cell mass (BCM), validated them against whole-body counting of (40)K (TBK method), and developed improved prediction equations for estimating BCM from BIA. In 50 healthy volunteers (age 23-65 years, BMI 18.6-27.7 kg/m(2)), BCM was estimated with the BIA devices Nutriguard-M (Data Input, Germany) and Soft-Tissue-Analyzer-STA (Akern, Italy) and by the TBK method. Methods were compared by the Bland-Altman procedure. New prediction equations for BCM were developed by multiple stepwise regression analysis based on a single BIA parallel model. The Akern device gives similar mean estimates of BCM compared to the Data Input device in males (33.5 vs. 33.3 kg, P = 0.789), but higher values in females (24.6 vs. 22.8 kg; P < 0.001). Both BIA devices overestimate mean BCM relative to the TBK method; in males by 5.0 kg (Data Input, P < 0.001) and 5.1 kg (Akern, P < 0.001); in females by 2.3 kg (Data Input, P < 0.001) and 4.1 kg (Akern, P < 0.001). Limits of agreement between BIA and TBK methods are for males +/-4.99 kg (Data Input) and +/-7.16 kg (Akern); for females, +/-4.69 kg (Data Input) and +/-4.12 kg (Akern). New equations were developed for estimating BCM for both BIA analyzers (Data Input, R(2) = 0.91, SEE = 1.46 kg; Akern, R(2) = 0.90, SEE = 1.48 kg). Since estimates of BCM by the present BIA devices do not differ in males, they might be interchangeable. This does not hold true for females. Because both BIA devices overestimate BCM, the newly developed device-specific equations which reduce bias and limits of agreement should be applied.     

Prediction of fat-free mass in black and white pre-adolescent and adolescent girls from anthropometry and impedance

As an ancillary project of the National Heart Lung and Blood Institute's Growth and Health Study (NGHS), data of 31 black girls and 38 white girls, 10–16 years of age, were used to develop equations to predict fat-free mass (FFM) from selected anthropometric dimensions and bioelectric impedance measures of resistance and reactance. Subjects were drawn from ongoing projects at the Children's Hospital Medical Center (CHMC) to obtain girls of both races from a wide range of body mass indices. FFM was estimated from measures of dual energy X-ray absorptiometry (DXA). The resulting equations had a root mean square error (RMSE) of 1.9 kg and a coefficient of variation (CV) of 4.9% for black girls using independent variables: stature divided by resistance squared (S²/R), thigh circumference, subscapular and suprailiac skinfold thicknesses. The corresponding values for white girls were 1.1 kg and 3.2% using independent variables: S²/R, arm circumference, weight, and reactance divided by resistance (R/R_c). In addition to cross-validating the ethnic-specific equations using PRESS statistics, the equation for white girls was also cross-validated using an independent sample of 35 girls from the Fels Longitudinal Study selected to match the CHMC sample. The cross-validation yielded a pure error of 2.4 kg FFM and a CV of 7%. The predicted values for FFM from the equations were used to calculate percentage of body fat in the CHMC sample and the pure errors for estimating percentage of body fat were 3% for blacks and 2% for whites. © 1993 Wiley-Liss, Inc.     

Lower-limb and whole-body tissue composition assessment in healthy active older women

AIM: The study evaluated, in active elderly women, the accuracy and bias of anthropometry and bioelectrical impedance analysis (BIA) for lower-limb and whole-body tissue composition measures using dual-energy X-ray absorptiometry (DXA) as the criterion method. METHODS: Nineteen individuals (66.1 +/- 4.2 years) participated in the study. Whole-body fat mass (FM) and fat-free mass (FFM) were measured by anthropometry, BIA and DXA. Lower-limb volume (LLV) and lower-limb FFM (LLFFM) were assessed by anthropometry and DXA. RESULTS: LLV and LLFFM were significantly overestimated by anthropometry vs. DXA (p < 0.05 and p < 0.001, respectively) but significant relationships were observed [coefficient of determination (R(2)) > 0.25, p < 0.05]. No significant difference was observed between FM(A) (where (A) stands for anthropometry) vs. FM(DXA) and FFM(A) vs. FFM(DXA) and significant relationships were observed [R(2) = 0.93, p < 0.001, coefficient of variation (CV) = 7.3%; and R(2) = 0.85, p < 0.001, CV = 4.4%, respectively]. No significant difference was observed between FM(BIA) and FM(DXA) and a significant relationship was observed (R(2) = 0.80, p < 0.001, CV = 11.6%). FFM was significantly underestimated by BIA vs. DXA (p < 0.01). CONCLUSIONS: In active elderly women, (i) compared with DXA, anthropometry overestimates LLV and LLFFM; (ii) anthropometry can be an accurate method for assessing whole-body composition; and (iii) despite a non-significant bias for the FM measurement, the BIA tends to overestimate FM and underestimate FFM.     

Age‐related pattern of body density and body composition in Japanese males and females, 11 and 18 years of age

The age‐related pattern of body density and body composition in Japanese males (n = 266) and females (n = 318), 11.00 to 18.99 years of age was studied. Body density (BD) as well as height, body weight, and seven skinfold thicknesses were measured. Percentage fat (%Fat) was calculated using the age‐ and sex‐specific equation of Lohman. Fat mass (FM), fat‐free mass (FFM), and the body mass index (BMI) were calculated. The trend for BD in males was lowest at 11 years (1.0530 g/ml) and increased to 1.0695 g/ml at 14 years, and then decreased slightly at 15 to 17 years. In female, BD decreased from 1.0530 g/ml at 13 years to 1.0424 g/ml at 17 years. Mean %Fat was highest in males at 11 years (15.8%), and lowest at 14 years (10.1%). The highest mean %Fat in females occurred at 16 years (22.8%), and the lowest at age 11 years (15.2%). Overall, only 6.8% of males and 3.1% of females were classified as obese. Between 11 and 18 years, FFM of males differed by 20.7 kg or 67.9%, whereas females showed a difference of only 10.8 kg or 34.7%. Consequently, age effects explained approximately 60% of the male variance of FFM but only 26% in females. Body density of each sex and age group in this study did not differ significantly from previous Japanese studies, and the pooled BD data for 1,457 Japanese including the present study are reported as a reference. Am. J. Hum. Biol. 14:327–337, 2002. © 2002 Wiley‐Liss, Inc.     

Multicompartment model of body composition assessment in Chinese-American adults

Using hydrodensitometry, dual energy x-ray absorptiometry, and deuterium dilution techniques, multiple compartment body composition assessment was performed on 29 adult Chinese-American men (n = 11) and women (n = 18). The purpose of the investigation was to determine if significant differences exist in the estimation of percentage of body fat (%BF) and fat-free mass (FFM), based on 2-, 3-, and 4-compartment models of body composition. Height, weight, and the body mass index (BMI) for the men were 170 cm, 63 kg, and 22 kg/m²; for the women, values were 161 cm, 59 kg, and 23 kg/m², respectively. Estimated values for %BF from density alone and density adjusted for TBW were not significantly different for either the men or women (20.5% vs. 18.8%) and (28.2% vs. 27.4%). However, %BF estimated from the 4-compartment model of density, TBW and BMC resulted in significantly lower values for both groups, 17.5% for men and 26.8% for women. The lack of a significant difference in %BF between density only and density adjusted for TBW indicates that TBW was within the accepted constancy value associated with hydrodensitometry. When density was adjusted for variation in both TBW and BMC, a significant decline occurred in the estimate of %BF for men, but not for women. The average TBW to FFM ratio was 0.75., 0.74, and 0.73 when using FFM values from 2-, 3-, and 4-compartment models, respectively. The average BMC to FFM ratio from two-, three-, and four-compartment estimates of FFM were 0.054, 0.053, and 0.052 for the men and 0.060, 0.059, and 0.059 for the women. The results suggest that Chinese-American men and women have similar TBW/FFM ratios, but the BMC/FFM ratio is higher in women than men. Am. J. Hum. Biol. 9:21–27 © 1997 Wiley-Liss, Inc.

1 This article is a US Government work and, as such, is in the public domain in the United States of America.

     

Effect of body size and gender in overarm throwing performance

The purpose of this study was to examine the relationship between maximum isometric strength, anthropometry and maximum velocity in overarm throwing for male and female experienced handball players. Twenty male and 20 female handball players were tested. The mean ball velocity was 23.2 m s^–1 and 19.1 m s^–1 for male and female handball players, respectively. For males and females, similar correlations were found between maximal isometric strength and throwing velocity (men, r=0.43, P=0.056; women, r=0.49, P=0.027). Univariate analysis of variance between isometric strength and throwing velocity for men and women showed no significant effect of gender (F _2,36=0.116, P=0.89). Body size had a strong positive effect on the throwing performance and isometric strength. Throwing velocity appeared to be affected by gender when size was expressed by mass or height (P<0.001). However, this dependence was completely explained by size differences when expressed as fat-free body mass (FFM). For strength, no gender effect was found at all, i.e. all gender differences were explained by size differences, irrespective on how this was expressed. The finding that strength and velocity show a gender independent relationship strengthens the notion that gender difference is based on difference in muscle bulk. We conclude that FFM, as an approximation for skeletal muscle mass, is the best measure to express body size when related to physical performance.     

Age‐related pattern of body density and body composition of Japanese men and women 18–59 years of age

Age‐related patterns of body size and composition were studied in a cross‐sectional sample of Japanese adults 18–59 years of age. Height, weight, the body mass index (BMI), body density (BD), percentage body fat (%Fat), fat mass (FM), fat‐free mass (FFM), and the sum of seven skinfold thicknesses (SF) of 288 men and 552 women were considered. Body density was measured by underwater weighing densitometry. Mean values of height, weight, BMI, BD, %Fat, FM, FFM, and SF of males were 169.0 cm, 65.3 kg, 22.8 kg/m², 1.0600 g/ml, 17.0%, 11.4 kg, 53.9 kg, and 95.0 mm, respectively, while corresponding values for females were 157.4 cm, 52.9 kg, 21.4 kg/m², 1.0420 g/ml, 24.4%, 13.1 kg, 39.7 kg, and 128.2 mm, respectively. Height, BD, and FFM correlated negatively with age in both sexes, while weight, BMI, %Fat, FM, and SF correlated positively with age. The highest BD and the lowest %Fat were observed in males ages 20 to <25 years (G20) and in females 25 to <30 years (G25). The lowest BD and highest %Fat were observed in G50 in both sexes. Correlations among parameters of body size and composition were stable with age in each sex. Height correlated negatively with BMI and %Fat in females, but not in males. In males, FM started to increase between G20 and G25 and continued to increase until G50, while SF and BMI remained stable during this period. In females, FM accumulation started around 30 years of age and continued until G50 and was accompanied by increases in SF and BMI. Am. J. Hum. Biol. 14:743–752, 2002. © 2002 Wiley‐Liss, Inc.     

The influence of anthropometric factors on postural balance: the relationship between body composition and posturographic measurements in young adults

OBJECTIVE:

The aim of the present study was to evaluate the influence of anthropometric characteristics and gender on postural balance in adults. One hundred individuals were examined (50 males, 50 females; age range 20-40 years).

METHODS:

The following body composition measurements were collected (using bone densitometry measurements): fat percentage (% fat), tissue (g), fat (g), lean mass (g), bone mineral content (g), and bone mineral density (g/cm²). In addition, the following anthropometric measurements were collected: body mass (kg), height (cm), length of the trunk-cephalic region (cm), length of the lower limbs (cm) and length of the upper limbs (cm). The following indices were calculated: body mass index (kg/m²), waist-hip ratio and the support base (cm²). Also, a postural balance test was performed using posturography variables with open and closed eyes.

RESULTS:

The analysis revealed poor correlations between postural balance and the anthropometric variables. A multiple linear regression analysis demonstrated that the whole group (female and male) height explained 12% of the medial-lateral displacement, 10% of the speed of oscillation, and 11% of the displacement area. The length of the trunk-cephalic length explained 6% of the displacement in the anteroposterior direction. With eyes closed, the support base and height explained 18% of the medial displacement, and the lateral height explained 10% of the displacement speed and 5% of the scroll area.

CONCLUSION:

Measured using posturography, the postural balance was only slightly influenced by the anthropometric variables, both with open and closed eyes. Height was the anthropometric variable that most influenced postural balance, both in the whole group and separately for each gender. Postural balance was more influenced by anthropometric factors in males than females.     

Development and validation of two equations estimating body composition for overweight and obese postmenopausal women

Objective

The aim of this study was to develop and validate two equations that best predict body composition of overweight and obese postmenopausal women.

Methods

Bioelectrical impedance analyses (BIAs) and anthropometric data such as circumferences and skinfolds were incorporated in the development of these two equations, respectively, while dual energy X-ray absorptiometry (DXA) was used as the reference method. A total number of 196 overweight and obese Greek postmenopausal women were used (131 subjects to develop the equations, and 65 to validate them).

Results

The BIA equation was: (FFM) = 38.475 + 0.207 × Wt − 0.092 × Rz/Ht² + 0.291 × Xc/Ht² (R² = 0.800, p < 0.0001) and the anthropometry equation was FM = −31.913 + 0.333 × GC + 0.840 × body mass index (BMI) + 0.064 × (biceps + triceps skinfold) (R² = 0.835, p < 0.0001). Both equations were found to result in unbiased estimates. Regarding reliability, BIA equation was found to be more reliable compared to existing ones when applied to this population. Additionally, BIA equation was more reliable compared to the anthropometric equation (±3.12642 kg vs. ±5.2342 kg limits of agreement, respectively).

Conclusion

These conclude that the equations developed in the current study are more reliable than the existing ones in the literature, and could be applied for assessing body composition in clinical practice and research.     

A comparison of dual energy X-ray absorptiometry and bioelectrical impedance analysis to measure total and segmental body composition in healthy young adults

The aim of this study was to investigate the accuracy of BIA in the measurement of total body composition and regional fat and the fat free mass in the healthy young adults. Four hundred and three healthy young adults (167 women and 236 men) aged 18–29 years were recruited from the Mid-West region of Ireland. Multi frequency, eight-polar bioelectrical impedance analysis (BIA) and dual energy X-ray absorptiometry (DXA) were used to measure the total body and segmental (arm, leg and trunk) fat mass and the fat free mass. BIA was found to underestimate the percentage total body fat in men and women (p < 0.001). This underestimate increased in men with >24.6% body fat and women with >32% body fat (p < 0.001). Fat tissue mass in the trunk segment was overestimated by 2.1 kg (p < 0.001) in men and underestimated by 0.4 kg (p < 0.001) in women. BIA was also found to underestimate the fat free mass in the appendages by 1.0 kg (p < 0.001) in men and 0.9 kg (p < 0.001) in women. Compared to dual energy X-ray absorptiometry, bioelectrical impedance analysis underestimates the total body fat mass and overestimates fat free mass in healthy young adults. BIA should, therefore, be used with caution in the measurement of total body composition in women and men with >25% total body fat. Though statistically significant, the small difference (~ 4%) between the methods indicates that the BIA may be used interchangeably with DXA in the measurement of appendicular fat free mass in healthy young adults.     

Association between measured BMI and self-perceived body size in Mexican adults

Aim: The study examined the association between perceived body size (through self-selection of Stunkard's body shape silhouettes) and measured body mass index (BMI) in Mexican Mestiso adult men and women, and determined the BMI values that corresponded to each silhouette.

Subjects: A sample of 1092 men and 1247 women, apparently healthy, aged 20–69, was studied.

Methods: Participants were asked to identify the silhouette that most accurately represented his/her body size. Weight and height were measured in duplicate to calculate BMI. A simple linear regression analysis was used to adjust BMI values to silhouette categories by gender. Areas under the receiver operating characteristic curves (AUC) were calculated to assess accuracy.

Results: Gender-specific BMI values for each silhouette were obtained. Correlation coefficients between silhouette ratings and BMI were 0.702 in males and 0.766 in females. Overweight ranged from silhouette 4 to 6 and obesity from silhouette 6 to 9, in both men and women. In the regression models, 49.3% of BMI variance in males and 58.7% in females were explained statistically by silhouette self-selection. AUC were higher than 0.8 for overweight and obesity in males and females.

Conclusions: Both male and female models had a good fit, indicating that BMI can be associated with body shape silhouettes. Silhouettes can be useful for defining overweight and obesity in settings such as schools or worksites, or where scales and stadiometers might not be available. They can also be used to provide health advice to the public.     

Changes in regional body composition explain increases in energy expenditure in elite junior basketball players over the season

We aimed to analyze the association between changes in total and regional fat (FM) and fat-free mass (FFM) over a season with resting (REE) and total energy expenditure (TEE) in elite basketball players. At the beginning of the pre-season and at the final of the competitive period, measures of total and regional FM, FFM, lean soft tissue (LST), and bone mineral estimated by DXA and REE by indirect calorimetry were obtained in eight males and nine females of the Portuguese basketball team (16-17 years). TEE was assessed by doubly labeled water. Handgrip and a vertical-jumping were used to assess strength and power. Changes were expressed as a percentage from the baseline values. Resting energy expenditure and TEE increased by 13.2 ± 12.6 and 13.3 ± 12.7% (p < 0.01), respectively. Increases in FFM (3.6 ± 2.2%) and reductions in relative FM (-4.0 ± 6.6%) were observed (p < 0.01). The strength and power increased by 14.4 ± 9.9 and 9.8 ± 10.6%, respectively (p < 0.001). Alone, FFM and arms LST differences explained 25 and 23% of the total variance in REE alteration. These variables remained associated after adjusting for gender and baseline values (β = 0.536, p = 0.042; and β = 2.023, p = 0.016, respectively). Over the season, the REE increase was explained by changes in FFM. The increase in REE along with the strength and power improvement may suggest that a qualitative change in the metabolic active tissues occurred. Furthermore, these findings highlight the regional LST contribution, specifically located at the upper limbs, as a key component for the higher REE occurred over the season in junior basketball players.     

Genomics of body fat percentage may contribute to sex bias in anorexia nervosa

Anorexia nervosa (AN) occurs nine times more often in females than in males. Although environmental factors likely play a role, the reasons for this imbalanced sex ratio remain unresolved. AN displays high genetic correlations with anthropometric and metabolic traits. Given sex differences in body composition, we investigated the possible metabolic underpinnings of female propensity for AN. We conducted sex‐specific GWAS in a healthy and medication‐free subsample of the UK Biobank (n = 155,961), identifying 77 genome‐wide significant loci associated with body fat percentage (BF%) and 174 with fat‐free mass (FFM). Partitioned heritability analysis showed an enrichment for central nervous tissue‐associated genes for BF%, which was more prominent in females than males. Genetic correlations of BF% and FFM with the largest GWAS of AN by the Psychiatric Genomics Consortium were estimated to explore shared genomics. The genetic correlations of BF%_male and BF%_female with AN differed significantly from each other (p < .0001, δ = ?0.17), suggesting that the female preponderance in AN may, in part, be explained by sex‐specific anthropometric and metabolic genetic factors increasing liability to AN.     

Development of anthropometry-based equations for the estimation of the total body water in Koreans

For developing race-specific anthropometry-based total body water (TBW) equations, we measured TBW using bioelectrical impedance analysis (TBW(BIA)) in 2,943 healthy Korean adults. Among them, 2,223 were used as a reference group. Two equations (TBW(K1) and TBW(K2)) were developed based on age, sex, height, and body weight. The adjusted R2 was 0.908 for TBW(K1) and 0.910 for TBW(K2). The remaining 720 subjects were used for the validation of our results. Watson (TBW(W)) and Hume-Weyers (TBW(H)) formulas were also used. In men, TBW(BIA) showed the highest correlation with TBW(H), followed by TBW(K1), TBW(K2) and TBW(W). TBW(K1) and TBW(K2) showed the lower root mean square errors (RMSE) and mean prediction errors (ME) than TBW(W) and TBW(H). On the Bland-Altman plot, the correlations between the differences and means were smaller for TBW(K2) than for TBW(K1). On the contrary, TBW(BIA) showed the highest correlation with TBW(W), followed by TBW(K2), TBW(K1), and TBW(H) in females. RMSE was smallest in TBW(W), followed by TBW(K2), TBW(K1) and TBW(H). ME was closest to zero for TBW(K2), followed by TBW(K1), TBW(W) and TBW(H). The correlation coefficients between the means and differences were highest in TBW(W), and lowest in TBW(K2). In conclusion, TBW(K2) provides better accuracy with a smaller bias than the TBW(W) or TBW(H) in males. TBW(K2) shows a similar accuracy, but with a smaller bias than TBW(W) in females.     

Resting energy expenditure and body composition in rural Sarawaki adults

The resting energy expenditure (REE) of 43 men and 41 nonpregnant women aged 18–42, of the Iban tribe in rural Sarawak, was measured using the Oxylog and analyzed in relation to fat mass (FM) and fat-free mass (FFM) derived from measurements of skinfold thickness, to estimates of the specific energy expenditure of the FFM, and to microclimatic variables. Measured REEs exceeded values predicted from FFM by 9–22%, but were consistent with the metabolic rates expected of Western adolescents of comparable body size and composition. In both sexes, body fat content significantly influenced REE after accounting for nonlinear effects of variation in FFM. This is consistent with reported high adipocyte metabolic rates in obese Westerners, and with the hypothesis that Iban may possess a relatively large capacity for fat mobilization and storage. Therefore, in some populations, terms representing both FM and FFM should be included in equations describing REE. These findings are consistent with postulated evolutionary advantages of efficiency in regulation of energy turnover. © 1993 Wiley-Liss, Inc.     

Gender differences in heritability of depressive symptoms in the elderly

BACKGROUND: The present study aimed to investigate the relative importance of genetic and environmental influences on depressive symptoms in the elderly. METHOD: Depressive symptoms were assessed through the Center for Epidemiological Studies-Depression (CES-D) scale. The CES-D scale was administered to 959 twin pairs (123 female MZs, 90 male MZs, 207 same-sex female DZs, 109 same-sex male DZs and 430 opposite-sex DZs) aged 50 years or older (mean age 72 years). A dichotomous depressed state variable was constructed based on CES-D cut-offs and self-reported use of antidepressant medication. Structural equation models were fitted to the data to dissect genetic and environmental variance components. RESULTS: The sex-specific heritability estimates for depressive symptoms were 14% for males and 29% for females and 23% when constrained to be equal for men and women. The prevalence of clinically significant depressive symptoms was 16% for men and 24% for women. Heritability estimates for the dichotomous depressed state measure were 7% for males and 49% for females in the full model and 33% when constrained to be equal. CONCLUSION: Our results suggest that depressive symptoms in the elderly are moderately heritable, with a higher heritability for women than men, although differences in heritability estimates were not statistically significant.