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.

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.

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.

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.

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.

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.

Effects of exercise training on bone remodeling, insulin-like growth factors, and bone mineral density in postmenopausal women with and without hormone replacement therapy.

The purpose of this study was to determine the effects of 12 months of weight bearing and resistance exercise on bone mineral density (BMD) and bone remodeling (bone formation and bone resorption) in 2 groups of postmenopausal women either with or without hormone replacement therapy (HRT). Secondary aims were to characterize the changes in insulin-like growth factors-1 and -2 (IGF-1 and -2) and IGF binding protein 3 (IGFBP3) in response to exercise training. Women who were 3-10 years postmenopausal (aged 40-65 years) were included in the study. Women in the HRT and no HRT groups were randomized into the exercise intervention, resulting in four groups: (1) women not taking HRT, not exercising; (2) those taking HRT, not exercising; (3) those exercising, not taking HRT; and (4) women exercising, taking HRT. The number of subjects per group after 1 year was 27, 21, 25, and 17, respectively. HRT increased BMD at most sites whereas the combination of exercise and HRT produced increases in BMD greater than either treatment alone. Exercise training alone resulted in modest site-specific increases in BMD. Bone remodeling was suppressed in the groups taking HRT regardless of exercise status. The bone remodeling response to exercise training in women not taking HRT was not significantly different from those not exercising. However, the direction of change suggests an elevation in bone remodeling in response to exercise training, a phenomenon usually associated with bone loss. No training-induced differences in IGF-1, IGF-2, IGF-l:IGF-2 (IGF-1 : IGF-2), and IGFBP3 were detected.

Comparison of methods for assessing body-composition changes over 1 y in postmenopausal women.

BACKGROUND: Advances in dual-energy X-ray absorptiometry (DXA) software algorithms have improved the accuracy of this method for body-composition measurement. OBJECTIVE: Our objective was to compare the utility of DXA, underwater weighing (UWW), and a multicomponent model (MC) for assessing changes in body composition. DESIGN: : Previously sedentary women aged 40-66 y were randomly assigned to exercise training (ET; n = 36) and no exercise training (NT; n = 40). ET subjects exercised 3 d/wk; NT subjects remained sedentary. Changes in body mass, fat mass, and fat-free mass over 1 y were assessed by the 3 methods. RESULTS: Correlations among methods were significant and large (0.73-0.97). Body weight did not change significantly in either group. In the ET group, fat-free mass increased significantly as assessed by DXA (0.7 +/- 1.0 kg) but changes assessed by MC and UWW were not significant. Changes in fat mass and percentage body fat in the ET group were not significant. SDs for changes in fat mass and percentage body fat, respectively, from DXA were 2.5 kg and 2.7%; for MC, 5.5 kg and 7.1%; and for UWW, 4.4 kg and 5.8%. In the NT group, changes in fat-free mass, fat mass, and percentage body fat were significant (P