Body composition by the four-compartment model: validity of the BOD POD for assessing body fat in mexican elderly

Predictive equations for fat mass in older Hispanic adults with excess adiposity using the 4-compartment model as a reference method

BACKGROUND

Predictive equations are the best option for assessing fat mass in clinical practice due to their low cost and practicality. However, several factors, such as age, excess adiposity, and ethnicity can compromise the accuracy of the equations reported to date in the literature.

OBJECTIVE

To develop and validate two predictive equations for estimating fat mass: one based exclusively on anthropometric variables, the other combining anthropometric and bioelectrical impedance variables using the 4C model as the reference method.

SUBJECTS/METHODS

This is a cross-sectional study that included 386 Hispanic subjects aged ≥60 with excess adiposity. Fat mass and fat-free mass were measured by the 4C model as predictive variables. Age, sex, and certain anthropometric and bioelectrical impedance data were considered as potential predictor variables. To develop and to validate the equations, the multiple linear regression analysis, and cross-validation protocol were applied.

RESULTS

Equation 1 included weight, sex, and BMI as predictor variables, while equation 2 considered sex, weight, height squared/resistance, and resistance as predictor variables. R2 and RMSE values were ≥0.79 and ≤3.45, respectively, in both equations. The differences in estimates of fat mass by equations 1 and 2 were 0.34 kg and -0.25 kg, respectively, compared to the 4C model. This bias was not significant (p < 0.05).

CONCLUSIONS

The new predictive equations are reliable for estimating body composition and are interchangeable with the 4C model. Thus, they can be used in epidemiological and clinical studies, as well as in clinical practice, to estimate body composition in older Hispanic adults with excess adiposity.

Determination of Fat-Free Mass Density and its Components in Older Hispanic Adults by In Vivo Methods

The densitometry method estimates body composition based on cadaver reference values, mainly the fat-free mass density value of 1.100 g/cm³. However, several changes in fat-free mass components by aging, ethnicity, and excess adiposity could influence their density and affect body composition estimations. The present study aimed to compare the mean fat-free mass component values in older Hispanic adults to cadaver reference values. This cross-sectional study included a sample of 420 subjects aged ≥60 yr from northern Mexico. Fat-free mass was determined by the four-compartment model using air displacement plethysmography, the deuterium dilution technique, and dual-energy X-ray absorptiometry for body density, aqueous and mineral fractions of body weight, respectively. A 1-sample t test was used to compare the fat-free mass density and aqueous, mineral, and residue fractions of fat-free mass from subjects in the study to the assumed cadaver reference values. The mean fat-free mass density value for the total sample of older Hispanic adults (1.096 ± 0.011 g/cm³) was significantly (p < 0.001) lower than the assumed value of 1.100 g/cm³, except in obese older men. The mean aqueous fraction of fat-free mass (74.8 ± 3.3%) was higher than the assumed value of 73.8%, and the mean residue fraction of fat-free mass value was lower (18.3 ± 3.4%) than the reference value of 19.4%. Indeed, only the mean mineral fraction of fat-free mass value (6.8 ± 0.8%) was similar to the reference value. In the total sample, all characteristic mean fat-free mass values in these older Hispanic adults differed from cadaver reference values, except the mineral fraction of fat-free mass value.

Accuracy of body composition measurement techniques across the age span

This study investigated the acceptable accuracy of common body composition techniques compared with the reference 4-compartment (4C-R) model, which has not been investigated in a sample with diverse characteristics, including age and sex. Techniques included components of the 4C-R model [dual-energy X-ray absorptiometry, air displacement plethysmography, deuterium dilution (DD)] and surrogate compartment models, which utilised bioelectrical impedance spectroscopy (BIS) rather than DD. Men and women (sex = 1:1, 18-85 years, n = 90) completed body composition testing under best-practice guidance. For measurement of individuals, only the reference 3-compartment (3C-R) equation met acceptable error limits (<5% error among individuals) within the a priori cut-point (80%) for fat-free mass (FFM; CV = 0.52%) and fat mass (FM; CV = 1.61%). However, all investigated techniques reached equivalency to the 4C-R model for FFM on average (CV = 0.52-4.31%), but for FM only the 3C and 4C equations that included quantification of total body water (TBW) by DD or BIS reached equivalency overall (CV = 1.61-6.68%). Sex and age minimally influenced accuracy. Only the 3C-R or 4C-R equations are supported for acceptable individual accuracy for both FFM and FM. For group estimates any investigated technique could be used with acceptable accuracy for FFM; however, for FM, inclusion of TBW measurement within a compartment model is necessary. Novelty: Only the referent 3C and 4C models (including deuterium dilution) provide accurate body composition results that are acceptable for measurement of individuals in the general population. For group estimates of lean mass in the general population, compartments models that include TBW must be used for accurate measurement.

Effect of total body water estimates via bioimpedance on bod pod-based three-compartment body fat models

BACKGROUND/OBJECTIVES

Previous research has compared 2- and 3-compartment (2C and 3C, respectively) models against criterion 4-compartment (4C) models while utilizing the same body density (D_b) method for all measures. This design induces an inherent bias and obscures the added benefit of a 3C model over the simpler 2-compartment (2C) models.

PURPOSE

The purpose of this study was to determine the effect of total body water estimates via single-frequency (SF-BIA) and multi-frequency (MF-BIA) bioimpedance analysis on body fat estimates derived from air displacement plethysmography (ADP)-derived 3C models.

SUBJECTS/METHODS

A sample of 95 females and 82 males (n = 177) participated in this study. Underwater weighing, dual energy X-ray absorptiometry, and bioimpedance spectroscopy were used to calculate percent fat (%Fat) via a criterion 4C model (4C_CRITERION). %Fat was predicted via 3C_MFBIA (ADP and MF-BIA), 3C_SFBIA (ADP and SF-BIA), and a stand-alone 2-compartment (2C) model, based upon ADP, when using Siri and Brozek body density conversion formulas (2C_SIRI and 2C_BROZEK. respectively).

RESULTS

The standard error of estimate (SEE) was lowest for 3C_SFBIA when evaluated in females and males (2.72% and 2.31%, respectively) and highest for 2C_SIRI (3.98% and 3.84%, respectively). Similarly, the total error (TE) for females and males was lowest for 3C_SFBIA (3.21% and 2.67%, respectively) and highest for 2C_SIRI (4.58% and 4.48%, respectively) and 2C_BROZEK (4.65% and 4.33%, respectively).

CONCLUSIONS

Results suggest that SF-BIA and MF-BIA can improve the estimation of %Fat, beyond simpler 2C models, when integrated with ADP in a more advanced 3C model. Furthermore, the present study revealed that 3C_SFBIA was the best overall prediction model based upon TE values. The current study results support the integration of ADP and bioimpedance technology as part of a 3C model for the improvement of %Fat estimates over simpler 2C models.

The validation of contemporary body composition methods in various races and ethnicities

Few investigations have evaluated the validity of current body composition technology among racially and ethnically diverse populations. This study assessed the validity of common body composition methods in a multi-ethnic sample stratified by race and ethnicity. One hundred and ten individuals (55 % female, age: 26·5 (sd 6·9) years) identifying as Asian, African American/Black, Caucasian/White, Hispanic, Multi-racial and Native American were enrolled. Seven body composition models (dual-energy X-ray absorptiometry (DXA), air displacement plethysmography (ADP), two bioelectrical impedance devices (BIS, IB) and three multi-compartment models) were evaluated against a four-compartment criterion model by assessing total error (TE) and standard error of the estimate. For the total sample, measures of % fat and fat-free mass (FFM) from multi-compartment models were all excellent to ideal (% fat: TE = 0·94-2·37 %; FFM: TE = 0·72-1·78 kg) compared with the criterion. % fat measures were very good to excellent for DXA, ADP and IB (TE = 2·52-2·89 %) and fairly good for BIS (TE = 4·12 %). For FFM, single device estimates were good (BIS; TE = 3·12 kg) to ideal (DXA, ADP, IB; TE = 1·21-2·15 kg). Results did not vary meaningfully between each race and ethnicity, except BIS was not valid for African American/Black, Caucasian/White and Multi-racial participants for % fat (TE = 4·3-4·9 %). The multi-compartment models evaluated can be utilised in a multi-ethnic sample and in each individual race and ethnicity to obtain highly valid results for % fat and FFM. Estimates from DXA, ADP and IB were also valid. The BIS may demonstrate greater TE for all racial and ethnic cohorts and results should be interpreted cautiously.

Validity of Body-Composition Methods across Racial and Ethnic Populations

Multi-compartment body-composition models that divide the body into its multiple constituents are the criterion method for measuring body fat percentage, fat mass, and fat-free mass. However, 2- and 3-compartment body-composition devices such as air displacement plethysmography (ADP), DXA, and bioelectrical impedance devices [bioelectrical impedance analysis (BIA)] are more commonly used. Accurate measures depend on several assumptions, including constant hydration, body proportion, fat-free body density, and population characteristics. Investigations evaluating body composition in racial and ethnic minorities have observed differences in the aforementioned components between cohorts. Consequently, for racial/ethnic minority populations, estimates of body composition may not be valid. The purpose of this review was to comprehensively examine the validity of common body-composition devices in multi-ethnic samples (samples including >1 race/ethnicity) and in African-American, Hispanic, Asian, and Native American populations. Based on the literature, DXA produces valid results in multi-ethnic samples and ADP is valid for Hispanic and African American males when utilizing race-specific equations. However, for DXA and ADP, there is a need for validity investigations that include larger, more racially diverse samples, specifically including Hispanic/Latinx, Asian, Native American adults, and African-American females. Technology has advanced significantly since initial validity studies were conducted; therefore, conclusions are based on outdated models and software. For BIA, body-composition measures may be valid in a multi-ethnic sample, but the literature demonstrates disparate results between races/ethnicities. For BIA and ADP, the majority of studies have utilized DXA or hydrostatic weighing as the criterion to determine validity; additional studies utilizing a multi-compartment model criterion are essential to evaluate accuracy. Validity studies evaluating more recent technology in larger, more racially/ethnically diverse samples may improve our ability to select the appropriate method to accurately assess body composition in each racial/ethnic population.

Agreement between laboratory methods and the 4-compartment model in assessing fat mass in obese older Hispanic-American adults

BACKGROUND/OBJECTIVES

Densitometry (Siri's and Brožek's equations), hydrometry (by the deuterium dilution technique), and dual-energy X-ray absorptiometry (DXA) are three methods for estimating body composition. However, because they are all based on certain assumptions, they may not be applicable to aged and obese subjects due to changes in their body composition. Hence, the validity of these "laboratory methods" could be affected in obese older people. The main aim was to assess the agreement between densitometry, hydrometry, and DXA with the 4-compartment (4C) model to estimate fat mass (FM) in obese older Hispanic-American adults. As secondary goals, we explored whether the bias in densitometry and hydrometry results could be improved by modifying the assumptions regarding fat-free mass (FFM) density and hydration factor (HF) values, respectively. In the case of DXA, we explored the factors that contribute to bias.

SUBJECTS/METHODS

This is a cross-sectional study based on a sample of 171 obese subjects aged ≥60 years from 3 regions of northern Mexico. Body composition was assessed by the 4C model as the reference method and by all three laboratory methods. Agreement of the latter with the 4C model was probed by Bland and Altman analysis, a paired sample t-test, and simple linear regression analyses. In addition, the mean FFM density estimated in this sample, and HF values (published previously) of 0.737 and 0.753 for obese older Hispanic-American men and women, respectively, were considered as ethnic- and gender-specific values. These values were used to modify the densitometric and hydrometric equations in order to improve their bias. Finally, we tested whether the hydration status and indirect markers of adiposity are contributing factors to the bias of DXA using multiple linear regression analysis.

RESULTS

Siri's equation overestimated FM by 0.57 kg (p < 0.01), while Brožek's equation, hydrometry, and DXA underestimated it by 1.24 kg, 0.89 kg, and 0.79 kg (p < 0.01), respectively, compared to the 4C model. The bias in the densitometry and hydrometry results was eliminated by substituting the ethnic- and gender-specific values into the equations. Finally, we found that hip circumference contributes to the bias in DXA.

CONCLUSION

The densitometry, hydrometry, and DXA methods are not interchangeable with the 4C model for assessing fat mass in obese, older Hispanic-American adults. The lack of agreement could indicate that the assumptions of each method do not apply to this population.

The Effect of Gum Arabic (Acacia Senegal) on Cardiovascular Risk Factors and Gastrointestinal Symptoms in Adults at Risk of Metabolic Syndrome: A Randomized Clinical Trial

Gum Arabic (GA) is a widely-used additive in food processing, but is also historically used in a number of traditional therapies. It has been shown to have a broad range of health benefits, particularly in improving important cardiovascular risk indicators. Metabolic syndrome and its associated cardiac outcomes are a significant burden on modern healthcare systems, and complementary interventions to aid in its management are required. We aimed to examine the effect of GA on those with, or at risk of, metabolic syndrome to identify an effect on improving important disease parameters related to cardiovascular outcomes. A single-blind, randomized, placebo-controlled trial was conducted to identify the effects of daily GA supplementation on metabolic and cardiovascular risk factors. A total of 80 participants were randomized to receive 20 g of GA daily (n = 40) or placebo (1 g pectin, n = 40) for 12 weeks. Key endpoints included body-anthropometric indices, diet and physical activity assessment, and blood chemistry (HbA1c, fasting glucose, and blood lipids). Of the 80 enrolled, 61 completed the study (intervention: 31, control: 30) with 19 dropping out due to poor treatment compliance. After 12 weeks, the participants receiving the GA showed significant decreases in systolic and diastolic blood pressure, fat-free body mass, energy and carbohydrate consumption, and fasting plasma glucose, as well as increased intake of dietary fiber. They also reported improvements in self-perceived bloating and quality of bowel movements, as well as a decreased appetite score following GA consumption. These results suggest that GA could be a safe and beneficial adjunct to other treatments for those with, or at risk of, metabolic syndrome.

Examining Race-Related Error in Two-Compartment Models of Body Composition Assessment: A Systematic Review and Meta-Analysis

BACKGROUND

The Brozek and Siri formulas estimate relative adiposity (%Fat) from total body density (D_b) using a 2-compartment (2C) model. Racial/ethnic differences in D_b have been reported, along with subsequent errors in estimated %Fat.

OBJECTIVE

The primary aim of this systematic review and meta-analysis was to examine potential race/ethnic differences in the accuracy of the Brozek and Siri 2C formulas using aggregate-level data.

METHODS

Peer-reviewed studies available in English that provided 2C and 4C estimates of %Fat were located using searches of the PubMed (n = 150), Scopus (n = 170), and Web of Science (n = 138) online electronic databases. Random-effects models were used to determine potential differences between racial groups using a mean ES and 95% confidence intervals.

RESULTS

The cumulative results from 78 effects indicate that the relative accuracy of the Brozek equation did not vary between racial groups (between group p = 0.053). In contrast, the Siri equation slightly underestimated %Fat for Asian adults (ES_WMD = -1.40%, 95%CI -2.33% to -0.46%; p = 0.004) and Black adults (ES_WMD = -1.10%, 95%CI -2.11% to -0.08%; p = 0.034), with no significant differences observed in Hispanic adults (ES_WMD = 0.64%, 95%CI -1.02% to 2.31%; p = 0.448) and White adults (ES_WMD = 0.08%, 95%CI -0.42% to 0.57%; p = 0.766) (between group p = 0.019).

CONCLUSION

Small, but statistically significant, error was found between racial groups when estimating %Fat using the 2C Siri equation when compared to 4C models. However, the observed error due to race/ethnicity appears to be of little clinical or practical significance when using either equation.

Fat-free mass characteristics vary based on sex, race, and weight status in US adults

Common body composition estimation techniques necessitate assumptions of uniform fat-free mass (FFM) characteristics, although variation due to sex, race, and body characteristics may occur. National Health and Nutrition Examination Survey data from 1999 to 2004, during which paired dual-energy x-ray absorptiometry (DXA) and bioimpedance spectroscopy assessments were performed, were used to estimate FFM characteristics in a sample of 4619 US adults. Calculated FFM characteristics included the density and water, bone mineral, and residual content of FFM. A rapid 4-component model was also produced using DXA and bioimpedance spectroscopy data. Study variables were compared across sex, race/ethnicity, body mass index (BMI), and age categories using multiple pairwise comparisons. A general linear model was used to estimate body composition after controlling for other variables. Statistical analyses accounted for 6-year sampling weights and complex sampling design of the National Health and Nutrition Examination Survey and were based on 5 multiply imputed datasets. Differences in FFM characteristics across sex, race, and BMI were observed, with notable dissimilarities between men and women for all outcome variables. In racial/ethnic comparisons, non-Hispanic blacks most commonly presented distinct FFM characteristics relative to other groups, including greater FFM density and proportion of bone mineral. Body composition errors between DXA and the 4-component model were significantly influenced by sex, age, race, and BMI. In conclusion, FFM characteristics, which are often assumed in body composition estimation methods, vary due to sex, race/ethnicity, and weight status. The variation of FFM characteristics in diverse populations should be considered when body composition is evaluated.

Fat-free mass characteristics of Hispanic adults: Comparisons with non-Hispanic Caucasians and cadaver reference values

BACKGROUND

A four-compartment (4C) model quantifies fat, water, mineral and residual. As such, 4C models are more accurate than two-compartment (2C) models based off cadaver reference values (RV), which necessitate assumptions regarding fat-free mass (FFM) characteristics. Nonetheless, research has yet to determine whether the FFM characteristics of Hispanics are similar to non-Hispanic Caucasians and RV.

AIM

The aim of this analysis was to compare the FFM characteristics of Hispanics to non-Hispanic Caucasians and cadaver RV.

METHODS

Data from 2 separate research centers were pooled to create a sample of 100 and 119 Hispanic males and females (age: 18-54 yrs; BMI: 16.46-42.27 kg/m²), respectively, and 47 and 55 non-Hispanic Caucasian males and females (age: 18-54 yrs; BMI: 16.00-36.67 kg/m²), respectively (n = 331). A 4C model was determined using bioimpedance analysis for hydration, dual energy X-ray absorptiometry for mineral, and air displacement plethysmography for body density (4C-ADP). FFM was calculated via the 4C-ADP and FFM characteristics (i.e., density [D_FFM], water [TBW:FFM], bone mineral [Mo:FFM], and residual [R:FFM]) were compared between sexes and ethnicities using a one-way ANOVA and against RV via a one sample t-test.

RESULTS

In Hispanics, all FFM characteristics significantly differed from cadaver RV (all p < 0.05). In contrast, D_FFM and TBW:FFM of non-Hispanic Caucasians were similar to cadaver RV for both sexes (all p > 0.05). Moreover, the R:FFM of non-Hispanic Caucasian females did not differ from cadaver RV (p = 0.403) whereas all other comparisons were significantly different (all p < 0.05). Sex comparisons within Hispanic participants revealed FFM characteristics were similar between males and females other than Mo:FFM (p < 0.001) whereas all FFM characteristics were similar between non-Hispanic Caucasian males and females (all p > 0.05). All of the ethnicity comparisons within males were statistically significant (all p < 0.05). Moreover, ethnicity comparisons within females were statistically significant for all comparisons other than Mo:FFM (p = 0.258).

CONCLUSION

The observed differences in FFM characteristics of Hispanics as compared to non-Hispanics Caucasians and reference values indicate that allied health professionals should employ appropriate caution when estimating body composition via 2C models in Hispanic populations.

High Hydration Factor in Older Hispanic-American Adults: Possible Implications for Accurate Body Composition Estimates

Age- and obesity-related body composition changes could influence the hydration factor (HF) and, as a result, body composition estimates derived from hydrometry. The aim of the present study was to compare the HF in older Hispanic-American adults to some published values. This cross-sectional study included a sample of 412 subjects, men and women, aged ≥60 years from northern Mexico. HF values were calculated based on the ratio of total body water-using the deuterium dilution technique-to fat-free mass, derived from the four-compartment model. The mean HF value for the total sample (0.748 ± 0.034) was statistically (p ≤ 0.01) higher than the traditionally assumed value of 0.732 derived from chemical analysis, the "grand mean'' value of 0.725 derived from in vivo methods, and the 0.734 value calculated for older French adults via the three-compartment model. The HF of the older women did not differ across the fat mass index categories, but in men the obese group was lower than the normal and excess fat groups. The hydration factor calculated for the total sample of older Hispanic-American people is higher than the HF values reported in the literature. Therefore, the indiscriminate use of these assumed values could produce inaccurate body composition estimates in older Hispanic-American people.

Meal-based enhancement of protein quality and quantity during weight loss in obese older adults with mobility limitations: rationale and design for the MEASUR-UP trial

Obese older adults with even modest functional limitations are at a disadvantage for maintaining their independence into late life. However, there is no established intervention for obesity in older individuals. The Measuring Eating, Activity, and Strength: Understanding the Response - Using Protein (MEASUR-UP) trial is a randomized controlled pilot study of obese women and men aged ≥60 years with mild to moderate functional impairments. Changes in body composition (lean and fat mass) and function (Short Physical Performance Battery) in an enhanced protein weight reduction (Protein) arm will be compared to those in a traditional weight loss (Control) arm. The Protein intervention is based on evidence that older adults achieve optimal rates of muscle protein synthesis when consuming about 25-30 g of high quality protein per meal; these participants will consume ~30 g of animal protein at each meal via a combination of provided protein (beef) servings and diet counseling. This trial will provide information on the feasibility and efficacy of enhancing protein quantity and quality in the context of a weight reduction regimen and determine the impact of this intervention on body weight, functional status, and lean muscle mass. We hypothesize that the enhancement of protein quantity and quality in the Protein arm will result in better outcomes for function and/or lean muscle mass than in the Control arm. Ultimately, we hope our findings will help identify a safe weight loss approach that can delay or prevent late life disability by changing the trajectory of age-associated functional impairment associated with obesity.

Hyperinsulinemia is associated with the loss of appendicular skeletal muscle mass at 4.6 year follow-up in older men and women

BACKGROUND & AIMS

Homeostasis model assessment as a marker of insulin resistance has been associated with the pronounced loss of appendicular skeletal muscle mass in older adults. In the present study, we hypothesized that hyperinsulinemia as an early predictor of insulin resistance may be associated with the loss of appendicular skeletal muscle mass (ASM).

METHODS

This is a cohort study that included 147 well-functioning older men and women subjects who were followed for a period of 4.6 ± 1.8 years. Lean tissue in arm and legs, or ASM, was derived from dual-energy X-ray absorptiometry at baseline with follow-up measurements to obtain the relative change. Hyperinsulinemia was defined empirically at the 75th percentile.

RESULTS

The relative change in ASM was negative and significant throughout the quartiles of fasting insulin levels (p ≤ 0.05); however, the loss of ASM was more pronounced in the later quartiles (-0.7 kg) compared with the relative change in Q1 and Q2 (-0.5 kg and -0.3 kg). The unadjusted analysis indicates a significant association between hyperinsulinemia and the loss of ASM (β = -0.28, 95% CI-0.57-0.009, p = 0.05), an association that remained significant after adjusting for several covariates.

CONCLUSION

Hyperinsulinemia as an early marker of insulin resistance was associated with the loss of ASM in a cohort study of community-dwelling older men and women subjects without other chronic health conditions. The use of fasting insulin levels >8.4 μU/mL may help clinicians identify individuals in the geriatric population who are at a high risk of loss of appendicular skeletal muscle mass.

Association between insulin resistance and low relative appendicular skeletal muscle mass: evidence from a cohort study in community-dwelling older men and women participants

BACKGROUND

It has been hypothesized that insulin resistance plays a role in the development of the loss of skeletal muscle; however, no cohort studies on insulin resistance and low relative appendicular skeletal muscle mass (ASM) have been published to date. Thus, we examined whether insulin resistance is associated with low relative ASM after a 4.6-year follow-up period among apparently healthy older men and women participants.

METHODS

This is a combined retrospective-prospective cohort study, which includes 147 community-dwelling older men and women participants. ASM was measured by dual-energy x-ray absorptiometry at baseline and follow-up. Participants with a relative change in ASM below the sex-specific 15th value were classified as the low relative ASM group. Homeostatic model assessment was used to quantify insulin resistance. Logistic regression calculated odds ratios and 95% confidence intervals for development of low relative ASM, adjusted for covariates.

RESULTS

The loss of ASM in the low relative ASM and normal groups was -1.8kg and -0.35kg, respectively (p ≤ .05). The low relative ASM group was older and had higher insulin and homeostatic model assessment of insulin resistance values at baseline. The risk of developing low relative ASM at 4.6-year follow-up was 2.9 times higher (95% CI, 1.00-7.8; p = .04) among the participants with homeostatic model assessment of insulin resistance levels more than 2.3. After adjusting for age, the risk increased to 3.9 times higher (95% CI, 1.3-11.5; p = .03).

CONCLUSION

Insulin resistance was associated with low relative ASM at 4.6-year follow-up after accounting for several covariates in a cohort of apparently healthy, well-functioning young older men and women.

Comparison of body composition assessment methods in breast cancer survivors

PURPOSE/OBJECTIVES

To examine and compare the reliability of four body composition methods commonly used in assessing breast cancer survivors.

DESIGN

Cross-sectional.

SETTING

A rehabilitation facility at a university-based comprehensive cancer center in the southeastern United States.

SAMPLE

14 breast cancer survivors aged 40-71 years.

METHODS

Body fat (BF) percentage was estimated via bioelectric impedance analysis (BIA), air displacement plethysmography (ADP), and skinfold thickness (SKF) using both three- and seven-site algorithms, where reliability of the methods was evaluated by conducting two tests for each method (test 1 and test 2), one immediately after the other. An analysis of variance was used to compare the results of BF percentage among the four methods. Intraclass correlation coefficient (ICC) was used to test the reliability of each method.

MAIN RESEARCH VARIABLE

BF percentage.

FINDINGS

Significant differences in BF percentage were observed between BIA and all other methods (three-site SKF, p<0.001; seven-site SKF, p<0.001; ADP, p=0.002). No significant differences (p>0.05) in BF percentage between three-site SKF, seven-site SKF, and ADP were observed. ICCs between test 1 and test 2 for each method were BIA=1, ADP=0.98, three-site SKF=0.99, and seven-site SKF=0.94.

CONCLUSIONS

ADP and both SKF methods produce similar estimates of BF percentage in all participants, whereas BIA overestimated BF percentage relative to the other measures. Caution is recommended when using BIA as the body composition method for breast cancer survivors who have completed treatment but are still undergoing adjuvant hormonal therapy.

IMPLICATIONS FOR NURSING

Measurements of body composition can be implemented very easily as part of usual care and should serve as an objective outcome measure for interventions designed to promote healthy behaviors among breast cancer survivors.

Scalable office-based health care

The goal of health care is to provide high-quality care at an affordable cost for its patients. However, the population it serves has changed dramatically since the popularization of hospital-based health care. With available new technology, alternative health care delivery methods can be designed and tested. This study examines scalable office-based health care for small business, where health care is delivered to the office floor. This delivery was tested in 18 individuals at a small business in Minneapolis, Minnesota. The goal was to deliver modular health care and mitigate conditions such as diabetes, hyperlipidaemia, obesity, sedentariness and metabolic disease. The modular health care system was welcomed by employees - 70% of those eligible enrolled. The findings showed that the modular health care deliverable was feasible and effective. The data demonstrated significant improvements in weight loss, fat loss and blood variables for at risk participants. This study leaves room for improvement and further innovation. Expansion to include offerings such as physicals, diabetes management, smoking cessation and prenatal treatment would improve its utility. Future studies could include testing the adaptability of delivery method, as it should adapt to reach rural and under-served populations.

Assessment of age and sex by means of DXA bone densitometry: application in forensic anthropology

Today we are witnessing a genuine revolution in diagnostic imaging techniques. Dual X-ray absorptiometry (DEXA) quantifies bone mineral density (BMD) and bone mineral content (BMC). This technique has rarely been used in Forensic Anthropology, although its practical application has been demonstrated by various authors. In this article, we look into the conduct of bone mineral density in the femoral neck, the trochanter, the intertrochanter, the proximal femur and Ward's triangle, in relation to anthropometric age and sex parameters. The research was carried out on 70 persons - 38 men and 32 women - and the results obtained show significant correlations between bone mineral density measurements and anthropometric values. The research demonstrates bone mineral density to be a useful technique for sex and age data in forensic anthropology, particularly in the measurements observed in the Ward's triangle area.

Prediction of fat-free mass by bioelectrical impedance analysis in older adults from developing countries: a cross-validation study using the deuterium dilution method

OBJECTIVE

Several limitations of published bioelectrical impedance analysis (BIA) equations have been reported. The aims were to develop in a multiethnic, elderly population a new prediction equation and cross-validate it along with some published BIA equations for estimating fat-free mass using deuterium oxide dilution as the reference method.

DESIGN AND SETTING

Cross-sectional study of elderly from five developing countries.

METHODS

Total body water (TBW) measured by deuterium dilution was used to determine fat-free mass (FFM) in 383 subjects. Anthropometric and BIA variables were also measured. Only 377 subjects were included for the analysis, randomly divided into development and cross-validation groups after stratified by gender. Stepwise model selection was used to generate the model and Bland Altman analysis was used to test agreement.

RESULTS

FFM = 2.95 - 3.89 (Gender) + 0.514 (Ht2/Z) + 0.090 (Waist) + 0.156 (Body weight). The model fit parameters were an R2, total F-Ratio, and the SEE of 0.88, 314.3, and 3.3, respectively. None of the published BIA equations met the criteria for agreement. The new BIA equation underestimated FFM by just 0.3 kg in the cross-validation sample. The mean of the difference between FFM by TBW and the new BIA equation were not significantly different; 95% of the differences were between the limits of agreement of -6.3 to 6.9 kg of FFM. There was no significant association between the mean of the differences and their averages (r= 0.008 and p= 0.2).

CONCLUSIONS

This new BIA equation offers a valid option compared with some of the current published BIA equations to estimate FFM in elderly subjects from five developing countries.

Body composition analysis techniques in the aged adult: indications and limitations

PURPOSE OF REVIEW

Body composition analysis allows division of the body into different compartments on the basis of differing physical properties. A variety of techniques are available for measuring body composition. This review describes the changes that occur with increasing age, their significance and also the limitations of available body composition analysis techniques when applied to the elderly.

RECENT FINDINGS

Studies have shown the development of changes in body composition with ageing that have important consequences for health. Alterations in body fat content and particularly body fat distribution are associated with adverse metabolic effects and increased cardiovascular risk. Reduced skeletal muscle mass and strength (sarcopenia) are common in the elderly with important effects on function and outcome. A range of techniques are available for measuring body composition. However, changes in body composition with ageing, particularly altered composition of the constituents of fat-free mass, and changes in fat distribution, may lead to measurement errors with standard body composition assessment methodology.

SUMMARY

Measurement of body composition provides information of importance to health and function. Techniques used for assessment should be those unaffected by age-related changes in body composition, or those that have been adapted or validated in this age group. Particular roles of these techniques in the elderly include screening or surveillance of those at risk of malnutrition, and monitoring a range of chronic illnesses that are prevalent in older individuals.

Body fat measurement by bioelectrical impedance and air displacement plethysmography: a cross-validation study to design bioelectrical impedance equations in Mexican adults

BACKGROUND

The study of body composition in specific populations by techniques such as bio-impedance analysis (BIA) requires validation based on standard reference methods. The aim of this study was to develop and cross-validate a predictive equation for bioelectrical impedance using air displacement plethysmography (ADP) as standard method to measure body composition in Mexican adult men and women.

METHODS

This study included 155 male and female subjects from northern Mexico, 20-50 years of age, from low, middle, and upper income levels. Body composition was measured by ADP. Body weight (BW, kg) and height (Ht, cm) were obtained by standard anthropometric techniques. Resistance, R (ohms) and reactance, Xc (ohms) were also measured. A random-split method was used to obtain two samples: one was used to derive the equation by the "all possible regressions" procedure and was cross-validated in the other sample to test predicted versus measured values of fat-free mass (FFM).

RESULTS AND DISCUSSION

The final model was: FFM (kg) = 0.7374 * (Ht2 /R) + 0.1763 * (BW) - 0.1773 * (Age) + 0.1198 * (Xc) - 2.4658. R2 was 0.97; the square root of the mean square error (SRMSE) was 1.99 kg, and the pure error (PE) was 2.96. There was no difference between FFM predicted by the new equation (48.57 +/- 10.9 kg) and that measured by ADP (48.43 +/- 11.3 kg). The new equation did not differ from the line of identity, had a high R2 and a low SRMSE, and showed no significant bias (0.87 +/- 2.84 kg).

CONCLUSION

The new bioelectrical impedance equation based on the two-compartment model (2C) was accurate, precise, and free of bias. This equation can be used to assess body composition and nutritional status in populations similar in anthropometric and physical characteristics to this sample.

Evaluation of air-displacement plethysmography and bioelectrical impedance analysis vs dual-energy X-ray absorptiometry for the assessment of fat-free mass in elderly subjects

OBJECTIVE

To evaluate air-displacement plethysmography (ADP) and bioelectrical impedance analysis (BIA) vs dual-energy X-ray absorptiometry (DXA) for the assessment of fat-free mass (FFM) in healthy elderly subjects.

SUBJECTS

Forty-two women and twenty-six men aged 60-84 years.

METHODS

FFM was measured by DXA and ADP. Body impedance (Z) was measured by four-polar BIA and the impedance index (ZI) was calculated as stature(2)/Z. Selection of predictors (gender, age, weight and ZI at 5, 50 and 100 kHz) for BIA algorithms was carried out using bootstrapped stepwise linear regression on 1000 samples of 68 subjects. Limits of agreement were used as measures of interchangeability of ADP and BIA with DXA.

RESULTS

The limits of agreement of ADP vs DXA were -11.0 to 2.4 kg in males and -4.8 to 2.2 kg in females. Gender, weight and ZI(100) were selected as predictors of FFM by bootstrapped stepwise linear regression. In males, ZI(100) (-12.2 to 12.2 kg) was much less accurate than weight (-6.0 to 6.0 kg) at predicting FFM and their combination did not improve the estimate (-6.0 to 6.0 kg). In females, ZI(100) (-6.8 to 6.8 kg) was less accurate than weight (-5.6 to 5.6 kg) at predicting FFM and their combination improved the estimate only slightly (-5.0 to 5.0 kg).

CONCLUSIONS

In healthy elderly subjects, (1) ADP and DXA are not interchangeable for the assessment of FFM, especially in males; and (2) ZI(100) is not superior to weight for the prediction of FFM and their combination is of little advantage and only in females.