Cross-sectional associations between adipose tissue depots and areal bone mineral density in the UK Biobank imaging study.

The relationship between obesity and osteoporosis is poorly understood. In this study, we assessed the association between adiposity and bone. The fat-bone relationship was dependent on sex, body mass index classification, and menopausal status. Results highlight the importance of accounting for direct measures of adiposity (beyond BMI) and menopause status. INTRODUCTION: Assess the relationship between direct measures of adiposity (total body fat mass, visceral adipose tissue, and abdominal subcutaneous adipose tissue) with the whole body and clinically relevant bone sites of the lumbar spine, and femoral neck areal bone mineral density (aBMD) in men and women. METHODS: This cross-sectional analysis was conducted utilizing de-identified data from the UK Biobank on participants (n = 3674) with available dual-energy X-ray absorptiometry (DXA) and magnetic resonance imaging (MRI) data. Sex-stratified multiple linear regression was used to assess the relationship between adiposity measures and aBMD outcomes, controlling for age, race, total body lean mass (DXA), height, BMI class, physical activity, smoking, menopausal status (women), and hormone use (women). RESULTS: In men, significant interactions were observed between measures of adiposity and BMI on aBMD for the whole body and lumbar spine. Interactions indicated a positive relationship between adiposity and aBMD in men classified as normal weight, but an inverse relationship in men with elevated BMI. In women, significant interactions between adiposity measures and menopausal status were observed primarily for the whole body and femoral neck aBMD bone outcomes which indicated a negative relationship between adiposity and aBMD in premenopausal women, but a positive relationship in postmenopausal women. CONCLUSION: Total body adiposity, abdominal subcutaneous adipose tissue, and visceral adipose tissue were all significantly associated with aBMD in both men and women. The strength and direction of association were dependent on sex, BMI classification, and menopausal status (women).

Association of objectively measured physical activity and bone health in children and adolescents: a systematic review and narrative synthesis.

The influence of day-to-day physical activity on bone in adolescence has not been well characterized. Forty articles were identified that assessed the relationship between accelerometry-derived physical activity and bone outcomes in adolescents. Physical activity was positively associated with bone strength in peri-pubertal males, with less consistent evidence in females. Physical activity (PA) is recommended to optimize bone development in childhood and adolescence; however, the influence of day-to-day PA on bone development is not well defined. The aim of this review was to describe the current evidence for objectively measured PA on bone outcomes in healthy children and adolescents. MEDLINE, Embase, Cochrane Library, Scopus, Web of Science, CINAHL, PsycInfo, and ClinicalTrials.gov were searched for relevant articles up to April 2020. Studies assessing the relationship between accelerometry-derived PA and bone outcomes in adolescents (6-18 years old) were included. Two reviewers independently screened studies for eligibility, extracted data, and rated study quality. Forty articles met inclusion criteria (25 cross-sectional, 15 longitudinal). There was significant heterogeneity in accelerometry methodology and bone outcomes measured. Studies in males indicated a significant, positive relationship between moderate to vigorous PA (MVPA) and bone outcomes at the hip and femur, particularly during the peri-pubertal years. The results for MVPA and bone outcomes in females were mixed. There was a paucity of longitudinal studies using pQCT and a lack of data regarding how light PA and/or impact activity influences bone outcomes. The current evidence suggests that objectively measured MVPA is positively associated with bone outcomes in children and adolescents, especially in males. However, inconsistencies in methodology make it difficult to determine the amount and type of PA that leads to favorable bone outcomes. Given that the majority of research has been conducted in Caucasian adolescents, further research is needed in minority populations.

Physical activity, sedentary time, and longitudinal bone strength in adolescent girls.

The association between baseline physical activity and sedentary time with 2-year longitudinal bone strength was evaluated. The effect of physical activity on bone depended on maturity status. Sedentary time did not negatively impact bone outcomes, regardless of maturity. Maturity should be considered when developing exercise interventions to improve bone outcomes. INTRODUCTION: Physical activity during adolescence is important to obtain peak bone mass; however, adolescents are increasingly sedentary, potentially increasing risk for osteoporosis later in life. The aim of this study was to assess the association of physical activity and sedentary time with 2-year longitudinal bone outcomes in adolescent females (69% Hispanic/31% non-Hispanic). METHODS: Bone strength was assessed at the 66% tibia, 20% femur, and 66% radius of 9- to 12-year-old girls (n = 131) using peripheral quantitative computed tomography at baseline and 2-year follow-up. Physical activity and sedentary time were assessed via accelerometry. Linear regression analyses were used to assess whether baseline vigorous physical activity (VPA), moderate physical activity (MPA), light physical activity (LPA), or sedentary time predict longitudinal bone outcomes, adjusting for relevant confounders. RESULTS: Significant interactions were found between maturity offset and physical activity. In weight-bearing bones, significant interactions were primarily identified between VPA and maturity offset. Interactions indicated that VPA was associated with favorable bone outcomes at the tibia and femur in girls further past the age of PHV. However, this favorable effect was not observed in girls closer to the age of PHV. At the radius, interactions were primarily observed between LPA and maturity offset. Again, LPA was more beneficial for girls further past the age of PHV. Sedentary time did not significantly influence bone outcomes. CONCLUSION: The effects of physical activity on bone may be dependent on maturity. Therefore, physical activity interventions, with attention to maturity status, may be required to optimize bone strength in girls.

Estimation of visceral fat in 9- to 13-year-old girls using dual-energy X-ray absorptiometry (DXA) and anthropometry.

OBJECTIVES: Accumulation of visceral fat (VF) in children increases the risk of cardiovascular disease and type 2 diabetes, and measurement of VF in children using computed tomography and magnetic resonance imaging (MRI) is expensive. Dual-energy X-ray absorptiometry (DXA) may provide a low-cost alternative. This study aims to determine if DXA VF estimates can accurately estimate VF in young girls, determine if adding anthropometry would improve the estimate and determine if other DXA fat measures, with and without anthropometry, could be used to estimate VF in young girls. METHODS: Visceral fat was measured at lumbar intervertebral sites (L1-L2, L2-L3, L3-L4 and L4-L5) using 3.0T MRI on 32 young girls (mean age 11.3 ± 1.3 years). VF was estimated using the GE CoreScan application. Measurement of DXA android and total body fat was performed. Weight, height and waist circumference (WC) measurements were also obtained. RESULTS: Waist circumference and body mass index were both strongly correlated with MRI, although WC was the best anthropometric covariate. Per cent fat (%fat) variables had the strongest correlation and did best in regression models. DXA %VF (GE CoreScan) and DXA android %fat and total body %fat accounted for 65% to 74% of the variation in MRI VF. CONCLUSION: Waist circumference predicted MRI VF almost as well as DXA estimates in this population, and a combination of WC and DXA fat improves the predictability of VF. DXA VF estimate was improved by the addition of WC; however, DXA android %fat with WC was better at predicting MRI VF.

Use of iDXA spine scans to evaluate total and visceral abdominal fat.

OBJECTIVES: Abdominal fat may be a better predictor than body mass index (BMI) for risk of metabolically-related diseases, such as diabetes, cardiovascular disease, and some cancers. We sought to validate the percent fat reported on dual energy X-ray absorptiometry (DXA) regional spine scans (spine fat fraction, SFF) against abdominal fat obtained from total body scans using the iDXA machine (General Electric, Madison, WI), as previously done on the Prodigy model. METHODS: Total body scans and regional spine scans were completed on the same day (N = 50). In alignment with the Prodigy-based study, the following regions of interest (ROI) were assessed from total body scans and compared to the SFF from regional spine scans: total abdominal fat at (1) lumbar vertebrae L2-L4 and (2) L2-Iliac Crest (L2-IC); (3) total trunk fat; and (4) visceral fat in the android region. Separate linear regression models were used to predict each total body scan ROI from SFF; models were validated by bootstrapping. RESULTS: The sample was 84% female, a mean age of 38.5 ± 17.4 years, and mean BMI of 23.0 ± 3.8 kg/m2 . The SFF, adjusted for BMI, predicted L2-L4 and L2-IC total abdominal fat (%; Adj. R2 : 0.90) and total trunk fat (%; Adj. R2 : 0.88) well; visceral fat (%) adjusted R2 was 0.83. Linear regression models adjusted for additional participant characteristics resulted in similar adjusted R2 values. CONCLUSIONS: This replication of the strong correlation between SFF and abdominal fat measures on the iDXA in a new population confirms the previous Prodigy model findings and improves generalizability.

Association of Dynamics in Lean and Fat Mass Measures with Mortality in Frail Older Women.

OBJECTIVE: The relationship between body composition and mortality in frail older people is unclear. We used dual-x-ray absorptiometry (DXA) data to examine the association between dynamics in whole-body composition and appendicular (4 limbs) and central (trunk) compartments and all-cause mortality in frail older women. DESIGN: Prospective study with up to 19 years of follow up. SETTING: Community dwelling older (≥65) women. PARTICIPANTS: 876 frail older participants of the Women's Health Initiative Observational Study with a single measure of body composition and 581 participants with two measures. MEASUREMENTS: Frailty was determined using modified Fried's criteria. All-cause mortality hazard was modeled as a function of static (single-occasion) or dynamic changes (difference between two time points) in body composition using Cox regression. RESULTS: Analyses adjusted for age, ethnicity, income, smoking, cardiovascular disease, diabetes, stroke, number of frailty criteria and whole-body lean mass showed progressively decreased rates of mortality in women with higher appendicular fat mass (FM) (P for trend=0.01), higher trunk FM (P for trend=0.03) and higher whole-body FM (P for trend=0.01). The hazard rate ratio for participants with more than a 5% decline in FM between two time points was 1.91; 1.67 and 1.71 for appendicular, trunk and whole-body compartment respectively as compared to women with relatively stable adiposity (p<0.05 for all). Dynamics of more than 5% in lean mass were not associated with mortality. CONCLUSION: Low body fat or a pronounced decline in adiposity is associated with increased risks of mortality in frail older women. These results indicate a need to re-evaluate healthy weight in persons with frailty. .

Dual energy X-ray absorptiometry spine scans to determine abdominal fat in postmenopausal women.

Body composition may be a better predictor of chronic disease risk than body mass index (BMI) in older populations. OBJECTIVES: We sought to validate spine fat fraction (%) from dual energy X-ray absorptiometry (DXA) spine scans as a proxy for total abdominal fat. METHODS: Total body DXA scan abdominal fat regions of interest (ROI) that have been previously validated by magnetic resonance imaging were assessed among healthy, postmenopausal women who also had antero-posterior spine scans (n = 103). ROIs were (1) lumbar vertebrae L2-L4 and (2) L2-Iliac Crest (L2-IC), manually selected by two independent raters, and (3) trunk, auto-selected by DXA software. Intra-class correlation coefficients evaluated intra and inter-rater reliability on a random subset (N = 25). Linear regression models, validated by bootstrapping, assessed the relationship between spine fat fraction (%) and total abdominal fat (%) ROIs. RESULTS: Mean age, BMI, and total body fat were 66.1 ± 4.8 y, 25.8 ± 3.8 kg/m2 and 40.0 ± 6.6%, respectively. There were no significant differences within or between raters. Linear regression models adjusted for several participant and scan characteristics were equivalent to using only BMI and spine fat fraction. The model predicted L2-L4 (Adj. R2 : 0.83) and L2-IC (Adj. R2 : 0.84) abdominal fat (%) well; the adjusted R2 for trunk fat (%) was 0.78. Model validation demonstrated minimal over-fitting (Adj. R2 : 0.82, 0.83, and 0.77 for L2-L4, L2-IC, and trunk fat, respectively). CONCLUSIONS: The strong correlation between spine fat fraction and DXA abdominal fat measures make it suitable for further development in postmenopausal chronic disease risk prediction models. Am. J. Hum. Biol. 28:918-926, 2016. © 2016Wiley Periodicals, Inc.

High genetic risk individuals benefit less from resistance exercise intervention.

OBJECTIVES: Genetic factors have an important role in body mass index (BMI) variation, and also likely have a role in the weight loss and body composition response to physical activity/exercise. With the recent identification of BMI-associated genetic variants, it is possible to investigate the interaction of these genetic factors with exercise on body composition outcomes. METHODS: In a block-randomized clinical trial of resistance exercise among women (n=148), we examined whether the putative effect of exercise on weight and dual-energy x-ray absorptiometry-derived body composition measurements differs according to genetic risk for obesity. Approximately one-half of the sample was randomized to an intervention consisting of a supervised, intensive, resistance exercise program, lasting 1 year. Genetic risk for obesity was defined as a genetic risk score (GRS) comprised of 21 single-nucleotide polymorphisms (SNPs) known to be associated with BMI variation. We examined the interaction of exercise intervention and the GRS on anthropometric and body composition measurements after 1 year of the exercise intervention. RESULTS: We found statistically significant interactions for body weight (P=0.01), body fat (P=0.01), body fat % (P=0.02) and abdominal fat (P=0.02), whereby the putative effect of exercise is greater among those with a lower level of genetic risk for obesity. No single SNP appears to be a major driver of these interactions. CONCLUSIONS: The weight-loss response to resistance exercise, including changes in body composition, differs according to an individual's genetic risk for obesity.

Muscle density predicts changes in bone density and strength: a prospective study in girls.

OBJECTIVE: We sought to determine whether muscle density, an index of skeletal muscle fat content, was predictive of 2-year changes in weight-bearing bone parameters in young girls. METHODS: Two-year prospective data from 248 girls, aged 8-13 years at baseline. Peripheral quantitative computed tomography was used to measure changes in bone strength indices (bone strength index [BSI, mg(2)/mm(4)] and strength-strain index [SSIp, mm(3)]) and volumetric bone mineral density [vBMD, mg/cm(3)] at distal metaphyseal and diaphyseal regions of the femur and tibia, as well as calf and thigh muscle density (mg/cm(3)), and muscle cross-sectional area (MCSA, mm(2)), indices of skeletal muscle fat content and muscle force production, respectively. RESULTS: After controlling for potential confounders, greater gains in femur BSI (44%, P<0.002), total femur vBMD (114%, P<0.04) and femur trabecular vBMD (306%, P<0.002) occurred in girls in the lowest versus the highest groups of baseline thigh muscle density. Greater gains in tibial BSI (25%, P<0.03) and trabecular vBMD (190%, P<0.002) were also observed in the lowest versus the highest baseline calf muscle density groups. CONCLUSION: Baseline muscle density is a significant predictor of changes in bone density and bone strength in young girls during a period of rapid skeletal development.

Body size and pubertal development explain ethnic differences in structural geometry at the femur in Asian, Hispanic, and white early adolescent girls living in the U.S.

UNLABELLED: Variation in structural geometry is present in adulthood, but when this variation arises and what influences this variation prior to adulthood remains poorly understood. Ethnicity is commonly the focus of research of skeletal integrity and appears to explain some of the variation in quantification of bone tissue. However, why ethnicity explains variation in skeletal integrity is unclear. METHODS: Here we examine predictors of bone cross sectional area (CSA) and section modulus (Z), measured using dual-energy X-ray absorptiometry (DXA) and the Advanced Hip Analysis (AHA) program at the narrow neck of the femur in adolescent (9-14 years) girls (n=479) living in the United States who were classified as Asian, Hispanic, or white if the subject was 75% of a given group based on parental reported ethnicity. Protocols for measuring height and weight follow standardized procedures. Total body lean mass (LM) and total body fat mass (FM) were quantified in kilograms using DXA. Total dietary and total dairy calcium intakes from the previous month were estimated by the use of an electronic semi-quantitative food frequency questionnaire (eFFQ). Physical activity was estimated for the previous year by a validated self-administered modifiable activity questionnaire for adolescents with energy expenditure calculated from the metabolic equivalent (MET) values from the Compendium of Physical Activities. Multiple regression models were developed to predict CSA and Z. RESULTS: Age, time from menarche, total body lean mass (LM), total body fat mass (FM), height, total calcium, and total dairy calcium all shared a significant (p<0.05), positive relationship with CSA. Age, time from menarche, LM, FM, and height shared significant (p<0.05), positive relationships with Z. For both CSA and Z, LM was the most important covariate. Physical activity was not a significant predictor of geometry at the femoral neck (p≥0.339), even after removing LM as a covariate. After adjusting for covariates, ethnicity was not a significant predictor in regression models for CSA and Z. CONCLUSION: Variability in bone geometry at the narrow neck of the femur is best explained by body size and pubertal maturation. After controlling for these covariates there were no differences in bone geometry between ethnic groups.

Associations of physical activity duration, frequency, and load with volumetric BMD, geometry, and bone strength in young girls.

SUMMARY: More efficacious physical activity (PA) prescriptions for optimal bone development are needed. This study showed that PA duration, frequency, and load were all independently associated with bone parameters in young girls. Increased PA duration, frequency, and load are all important osteogenic stimuli that should be incorporated into future PA interventions. INTRODUCTION: This study evaluated the associations of physical activity (PA) duration, frequency, load, and their interaction (total PA score = duration × frequency × load) with volumetric bone mineral density, geometry, and indices of bone strength in young girls. METHODS: Four hundred sixty-five girls (aged 8-13 years) completed a past year physical activity questionnaire (PYPAQ) which inquires about the frequency (days per week) and duration (average minutes per session) of leisure-time PA and sports. Load (peak strain score) values were assigned to each activity based on ground reaction forces. Peripheral quantitative computed tomography was used to assess bone parameters at metaphyseal and diaphyseal sites of the femur and tibia of the non-dominant leg. RESULTS: Correlations across all skeletal sites between PA duration, frequency, load and periosteal circumference (PC), bone strength index (BSI), and strength-strain index (SSI) were significant (p ≤ 0.05), although low (0.10-0.17). A 2.7-3.7% greater PC across all skeletal sites was associated with a high compared to a low PYPAQ score. Also, a high PYPAQ score was associated with greater BSI (6.5-8.7%) at metaphyseal sites and SSI (7.5-8.1%) at diaphyseal sites of the femur and tibia. The effect of a low PYPAQ score on bone geometric parameters and strength was greater than a high PYPAQ score. CONCLUSIONS: PA duration, frequency, and load were all associated with bone geometry and strength, although their independent influences were modest and site specific. Low levels of PA may compromise bone development whereas high levels have only a small benefit over more average levels.

Ethnic differences in femur geometry in the women's health initiative observational study.

SUMMARY: Participants in the observational study of the Women's Health Initiative (WHI) were studied to determine if ethnic differences in femur geometry can help to explain differences in hip fracture rates. Structural differences in femurs of African and Mexican-American women appear to be consistent with lower rates of hip fractures vs. whites. INTRODUCTION: Ethnic origin has a major influence on hip fractures, but the underlying etiology is unknown. We evaluated ethnic differences in hip fracture rates among 159,579 postmenopausal participants in the WHI then compared femur bone mineral density (BMD) and geometry among a subset with dual X-ray absorptiometry (DXA) scans of the hip and total body. METHODS: The subset included 8,206 non-Hispanic whites, 1,476 African-American (AA), 704 Mexican-American (MA), and 130 Native Americans (NA). Femur geometry derived from hip DXA using hip-structure analysis (HSA) in whites was compared to minority groups after adjustment for age, height, weight, percent lean mass, neck-shaft angle and neck length, hormone use, chronic disease (e.g., diabetes, rheumatoid arthritis, cancer), bone active medications (e.g., corticosteroids, osteoporosis therapies), and clinical center. RESULTS: Both AA and MA women suffered hip fractures at half the rate of whites while NA appeared to be similar to whites. The structural advantage among AA appears to be due to a slightly narrower femur that requires more bone tissue to achieve similar or lower section moduli (SM) vs. whites. This also underlies their higher BMD (reduces region area) and lower buckling ratios (buckling susceptibility). Both MA and NA women had similar advantages vs. whites at the intertrochanter region where cross-sectional area and SM were higher but with no differences at the neck. NA and MA had smaller bending moments vs. whites acting in a fall on the hip (not significant in small NA sample). Buckling ratios of MA did not differ from whites at any region although NA had 4% lower values at the IT region. CONCLUSION: Differences in the geometry at the proximal femur are consistent with the lower hip fracture rates among AA and MA women compared to whites.

Changes in soft tissue composition are the primary predictors of 4-year bone mineral density changes in postmenopausal women.

UNLABELLED: Changes in body weight influence bone mineral density, but the role of body composition is not clear in postmenopausal women. Body weight and soft tissue composition predicted bone changes independent of calcium supplementation and exercise frequency, indicating that soft tissue composition should be measured in clinical trials. INTRODUCTION: The purpose of this study was to examine the relationship between changes in body weight and composition and changes in 4-year bone mineral density (BMD) after accounting for age, 4-year exercise frequency (EX), and 4-year calcium supplement intake (CA) in postmenopausal women with and without hormone therapy (HT). METHODS: Postmenopausal women (aged 40-65 years) either using HT (for 1-3.9 years) or not using HT (for > or =1 year) were recruited to the study. EX and CA was monitored throughout the study and 167 women completed 4 years. BMD and soft tissue composition measurements were made using dual-energy X-ray absorptiometry. Regression was used to predict 4-year BMD changes from EX, CA, age, baseline and 4-year changes in body weight and composition. HT users (n = 115, 55.3 +/- 4.3 years) and non-users (n = 52, 57.5 +/- 4.7 years) were analyzed separately. RESULTS: The models predicting regional BMD changes that included soft tissue composition changes explained the most variation compared with those with body weight or EX and CA alone. Larger amounts of variation in BMD changes were explained in the no HT group. CONCLUSION: Body composition changes are important positive predictors of BMD changes independent of EX and CA supplementation, but their contribution varies according to bone site and with HT use.

Comparison of the validity of anthropometric and bioelectric impedance equations to assess body composition in adolescent girls.

OBJECTIVE: The purpose of this study was to examine the validity of two anthropometric and four bioelectric impedance (BIA) equations to estimate body composition from dual-energy x-ray absorptiometry (DXA) in adolescent girls of various ethnicities. The rationale for this study was to develop a prediction equation for percent body fat in a multi-ethnic, representative sample of sixth to eighth grade girls. DESIGN: One-hundred and sixty-six girls (51 African-American, 45 non-Black Hispanic, 55 non-Hispanic Caucasian, 15 multi-ethnic) participated. Estimates of percent fat and fat-free mass (FFM) from six published BIA and anthropometric equations and the equation developed from this study were compared to body composition determined from DXA. An RJL Systems analyzer was used to measure BIA. Anthropometry included body weight, height, and triceps and calf skinfolds. RESULTS: Average (± SD) age, size and body composition was as follows: age, 12.1±1.2 yrs, body mass 52.7±15.9 kg, height, 154.6±8.1 cm; DXA percent fat, 27.9±10.4; fat mass (FM), 15.6±10.2 kg; and fat free mass (FFM) 35.7±6.8 kg. No ethnic differences were found in the relationships between estimated and DXA measured body composition, with the exception of the skinfold equation. The six equations explained on average 82% of the variance in percent fat, 94% of the variance in fat mass, and 88% in fat free mass. Bland-Altman analysis indicated that none of the equations performed satisfactorily in our sample. CONCLUSIONS: The BIA and anthropometric equations were significantly related to DXA body composition parameters, however none met the criteria for cross-validation.

Bone mineral and predictors of bone mass in white, Hispanic, and Asian early pubertal girls.

Differences in bone among racial/ethnic groups may be explained by differences in body size and shape. Previous studies have not completely explained differences among white, Asian, and Hispanic groups during growth. To determine racial/ethnic differences and predictors of bone mass in early pubertal girls, we measured bone mineral content (BMC) in white, Hispanic, and Asian sixth-grade girls across six states in the United States. We developed models for predicting BMC for the total-body, distal radius, total-hip, and lumbar spine for 748 subjects. For each of the bone sites, the corresponding area from dual-energy X-ray absorptiometry (DXA) was a strong predictor of BMC, with correlations ranging 0.78-0.98, confirming that larger subjects have more BMC. Anthropometric measures of bone area were nearly as effective as bone area from DXA at predicting BMC. For total-body, distal radius, lumbar spine, and total-hip BMC, racial/ethnic differences were explained by differences in bone area, sexual maturity, physical activity, and dairy calcium intake. Bone size explained most of the racial/ethnic differences in BMC, although behavioral indicators were also significant predictors of BMC.

Basal metabolic rate of Brazilians living in the Southwestern United States.

Estimation of energy requirements relies on adequate values of basal metabolic rate (BMR). Prediction equations recommended for international use have been shown to overestimate BMR in populations living in the tropics. We have previously shown the inadequacy of these equations in samples of Brazilians living in tropical and temperate regions of the country. We sought to investigate whether BMR could adequately be estimated by prediction equations in a sample of Brazilians living in a different setting: the Sonoran desert of the Southwestern USA. BMR was measured under standard conditions in 33 subjects (14 men). Mean bias (estimated-measured) varied from 404.4 to 708.6 kJ day(-1) in women and 566.8 to 1122.8 kJ day(-1) in men, representing 8.5-15 and 8.9-17.6% overestimation, respectively, using the Schofield equations. Bland and Altman analyses showed large, relevant limits of agreement. The results using the recommended equations for the American population (IOM, 2005) were only 2% different from the Schofield equations. The Harris and Benedict equations yielded higher overestimations (15.0 and 16.8% for women and men, respectively) and the Henry and Rees equations also overestimated BMR (8.5 and 8.9%) even though they were developed for populations from the tropics, although to a lesser degree. It is concluded that the equations currently recommended for international use are not appropriate for Brazilians living in the Southwestern USA.

Comparison of two bioelectrical impedance analysis instruments for determining body composition in adolescent girls.

The purpose of this study was to compare fat-free mass (FFM) and percent body fat determined by two bio-electrical impedance analysis (BIA) instruments against criterion estimates determined by dual-energy x-ray absorptiometry (DXA) in a multi-racial/ethnic sample of adolescent girls. BIA was assessed in 151 girls (n=51 African-American; n=45 Hispanic; n=55 Caucasian; age 12.2 +/- 1.2 yr) using the RJL Quantum II and the American Weights and Measures Body-Comp Scale (BCS). Percent body fat determined by BIA was significantly related to that determined by DXA (R(2)=0.87, SEE=2.8% for RJL vs DXA, P<0.0001; R(2)=0.71, SEE=4.4% for BCS vs DXA, P<0.0001). The agreement between DXA and BIA for FFM was also significant (R(2)=0.91, SEE=0.03 kg for RJL, P <0.0001; R(2)=0.79, SEE=0.04 kg for BCS, P <0.0001). The BCS overestimated FFM by 2.7 kg (P<0.0001) and underestimated percent body fat by over 4% (P<0.001). There were no differences in percent body fat between DXA and the RJL, and although the RJL significantly overestimated FFM, the absolute difference was <1 kg. Within each ethnic group, the RJL instrument more closely estimated FFM and percent body fat than did the BCS. Although both BIA instruments compared favorably with DXA, the RJL had better stability and accuracy than the BCS, for both the total sample and for the three ethnic groups. Considering its relatively low cost and minimal time required for technical training, BIA is a useful and appropriate technique for assessing body composition in adolescent girls.

Validation of bioelectrical impedance analysis (BIA) for estimation of body composition in Black, White and Hispanic adolescent girls.

AIM: Equations for estimating % fat mass (%BF) and fat-free mass (FFM) from bioelectrical impedance analysis (BIA) that work in adolescent girls from different racial/ethnic backgrounds are not available. We investigated whether race/ethnicity influences estimation of body composition in adolescent girls. PRINCIPAL PROCEDURES: Prediction equations were developed for estimating FFM and %BF from BIA in 166 girls, 10-15 years old, consisting of 51 Black (B), 45 non-Black Hispanic (H), 55 non-Hispanic White (W) and 15 mixed (M) race/ethnicity girls, using dual energy x-ray absorptiometry (DXA) as the criterion method. FINDINGS: Black girls had similar %BF compared to other groups, yet were heavier per unit of height according to body mass index (BMI: kg.m(-2)) due to significantly greater FFM. BIA resistance index, age, weight and race/ethnicity were all significant predictors of FFM (R(2) = 0.92, SEE = 1.81 kg). Standardized regression coefficients showed resistance index (0.63) and weight (0.34) were the most important predictors of FFM. Errors in %BF (~2%) and FFM (~1.0 kg) were greater when race/ethnicity was not included in the equation, particularly in Black girls. We conclude the BIA-composition relationship in adolescent girls is influenced by race, and consequently have developed new BIA equations for adolescent girls for predicting FFM and %BF.

A review of psychosocial pre-treatment predictors of weight control.

Prompted by the large heterogeneity of individual results in obesity treatment, many studies have attempted to predict weight outcomes from information collected from participants before they start the programme. Identifying significant predictors of weight loss outcomes is central to improving treatments for obesity, as it could help professionals focus efforts on those most likely to benefit, suggest supplementary or alternative treatments for those less likely to succeed, and help in matching individuals to different treatments. To date, however, research efforts have resulted in weak predictive models with limited practical usefulness. The two primary goals of this article are to review the best individual-level psychosocial pre-treatment predictors of short- and long-term (1 year or more) weight loss and to identify research needs and propose directions for further work in this area. Results from original studies published since 1995 show that few previous weight loss attempts and an autonomous, self-motivated cognitive style are the best prospective predictors of successful weight management. In the more obese samples, higher initial body mass index (BMI) may also be correlated with larger absolute weight losses. Several variables, including binge eating, eating disinhibition and restraint, and depression/mood clearly do not predict treatment outcomes, when assessed before treatment. Importantly, for a considerable number of psychosocial constructs (e.g. eating self-efficacy, body image, self-esteem, outcome expectancies, weight-specific quality of life and several variables related to exercise), evidence is suggestive but inconsistent or too scant for an informed conclusion to be drawn. Results are discussed in the context of past and present conceptual and methodological limitations, and several future research directions are described.

Pretreatment predictors of attrition and successful weight management in women.

OBJECTIVE: This study analyzed baseline behavioral and psychosocial differences between successful and nonsuccessful participants in a behavioral weight management program. Success was defined by commonly used health-related criteria (5% weight loss). Noncompletion was also used as a marker of a failed attempt at weight control. SUBJECTS: A total of 158 healthy overweight and obese women (age, 48.0+/-4.5 y; BMI, 31.0+/-3.8 kg/m(2); body fat, 44.5+/-5.3%). INTERVENTION: Subjects participated in a 16-week lifestyle weight loss program consisting of group-based behavior therapy to improve diet and increase physical activity, and were followed for 1 y after treatment. METHODS: At baseline, all women completed a comprehensive behavioral and psychosocial battery assessing dieting/weight history, dietary intake and eating behaviors, exercise, self-efficacy, outcome evaluations, body image, and other variables considered relevant for weight management. Participants who maintained a weight loss of 5% or more at 16 months (or 10% or more of initial fat mass) were classified as successful. Nonsuccessful participants were those who dropped out and completers who had not lost weight at follow-up. RESULTS: Of all participants, 30% (n=47) did not complete initial treatment and/or missed follow-up assessments (noncompleters). Noncompletion was independently associated with more previous weight loss attempts, poorer quality of life, more stringent weight outcome evaluations, and lower reported carbohydrate intake at baseline. In logistic regression, completion status was predicted correctly in 84% of all cases (chi(2)=45.5, P<0.001), using baseline information only. Additional predictors of attrition were initial weight, exercise minutes, fiber intake, binge eating, psychological health, and body image. A large variation in weight loss/maintenance results was observed (range: 37.2 kg for 16-month weight change). Independent baseline predictors of success at 16 months were more moderate weight outcome evaluations, lower level of previous dieting, higher exercise self-efficacy, and smaller waist-to-hip ratio. Success status at follow-up was predicted correctly in 74% of all starting cases (chi(2)=33.6, P<0.001). CONCLUSION: Psychosocial and behavioral variables (eg, dieting history, dietary intake, outcome evaluations, exercise self-efficacy, and quality of life) may be useful as pretreatment predictors of success level and/or attrition in previously overweight and mildly obese women who volunteer for behavioral weight control programs. These factors can be used in developing readiness profiles for weight management, a potentially important tool to address the issue of low success/completion rates in the current management of obesity.