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.

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.

Validity of self-reported energy intake in lean and obese young women, using two nutrient databases, compared with total energy expenditure assessed by doubly labeled water.

OBJECTIVE: To compare self-reported total energy intake (TEI) estimated using two databases with total energy expenditure (TEE) measured by doubly labeled water in physically active lean and sedentary obese young women, and to compare reporting accuracy between the two subject groups. DESIGN: A cross-sectional study in which dietary intakes of women trained in diet-recording procedures were analyzed using the Minnesota Nutrition Data System (NDS; versions 2.4/6A/21, 2.6/6A/23 and 2.6/8.A/23) and Nutritionist III (N3; version 7.0) software. Reporting accuracy was determined by comparison of average TEI assessed by an 8 day estimated diet record with average TEE for the same period. RESULTS: Reported TEI differed from TEE for both groups irrespective of nutrient database (P<0.01). Measured TEE was 11.10+/-2.54 and 11.96+/-1.21 MJ for lean and obese subjects, respectively. Reported TEI, using either database, did not differ between groups. For lean women, TEI calculated by NDS was 7.66+/-1.73 MJ and by N3 was 8.44+/-1.59 MJ. Corresponding TEI for obese women were 7.46+/-2.17 MJ from NDS and 7.34+/-2.27 MJ from N3. Lean women under-reported by 23% (N3) and 30% (NDS), and obese women under-reported by 39% (N3) and 38% (NDS). Regardless of database, lean women reported higher carbohydrate intakes, and obese women reported higher total fat and individual fatty acid intakes. Higher energy intakes from mono- and polyunsaturated fatty acids were estimated by NDS than by N3 in both groups of women (P< or =0.05). CONCLUSIONS: Both physically active lean and sedentary obese women under-reported TEI regardless of database, although the magnitude of under-reporting may be influenced by the database for the lean women. SPONSORSHIP: USDA Hatch Project award (ARZT-136528-H-23-111) to LB Houtkooper and WH Howell.

Nutritional status of U.S. elite female heptathletes during training.

This study describes the body composition, dietary nutrient intake, dietary practices, and biochemical indices of iron status of elite female American heptathletes during training. Four-day diet records and dietary practice questionnaires were obtained from 19 female heptathletes (26 +/- 3 years) during the training season. Anthropometric measurements and fasting blood samples were obtained at the lowest phase of the training cycle. These athletes had a low body fat (13.8 +/- 2.7%) and high fat-free mass to height ratios (33.0 +/- 2.0 kg/m). Average nutrient intakes were > 67% of the reference intakes for all nutrients except vitamin E. Most dietary nutrient densities were higher than NHANES III nutrient densities for women 20-29 years old. More than 50% of the athletes took vitamin supplements and monitored their hydration status. Fifteen of the 17 athletes reported a normal menstrual cycle. Markers of biochemical iron status were all within the normal range. On average, these athletes were lean with high levels of fat free mass, adequate nutrient intakes, and normal biochemical indices of iron status. However, individual data reveals considerable variability within this group.

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

Estimation of body fat from anthropometry and bioelectrical impedance in Native American children.

OBJECTIVE: Obesity, as measured by body mass index, is highly prevalent in Native American children, yet there are no valid equations to estimate total body fatness for this population. This study was designed to develop equations to estimate percentage body fat from anthropometry and bioelectrical impedance as a critical part of Pathways, a multi-site study of primary prevention of obesity in Native American children. DESIGN: Percentage fat was estimated from deuterium oxide dilution in 98 Native American children (Pima/Maricopa, Tohono O'odham and White Mountain Apache tribes) between 8 and 11 y of age. The mean fat content (38.4%+/-8. 1%) was calculated assuming the water content of the fat-free body was 76%. Initial independent variables were height, weight, waist circumference, six skinfolds and whole-body resistance and reactance from bioelectrical impedance (BIA). RESULTS: Using all-possible-subsets regressions with the Mallows C (p) criterion, and with age and sex included in each regression model, waist circumference, calf and biceps skinfolds contributed least to the multiple regression analysis. The combination of weight, two skinfolds (any two out of the four best: triceps, suprailiac, subscapular and abdomen) and bioelectrical impedance variables provided excellent predictability. Equations without BIA variables yielded r2 almost as high as those with BIA variables. The recommended equation predicts percentage fat with a root mean square error=3.2% fat and an adjusted r2=0.840. CONCLUSION: The combination of anthropometry and BIA variables can be used to estimate total body fat in field studies of Native American children. The derived equation yields considerably higher percentage fat values than other skinfold equations in children.

Why bioelectrical impedance analysis should be used for estimating adiposity.

The whole-body bioelectrical impedance analysis (BIA) approach for estimating adiposity and body fat is based on empirical relations established by many investigators. Properly used, this noninvasive body-composition assessment approach can quickly, easily, and relatively inexpensively provide accurate and reliable estimates of fat-free mass (FFM) and total body water (TBW) in healthy populations. The estimated FFM or TBW values are used to calculate absolute and relative body fat amounts. When different investigators follow the same standard BIA procedures and use the same population and criterion method, similar prediction equations and relatively small prediction errors have been reported for measurement of FFM and TBW (SEE: 1.7-3.0 for FFM and 0.23-1.5 kg for TBW). The BIA approach is most appropriate for estimating adiposity of groups in epidemiologic and field studies but has limited accuracy for estimating body composition in individuals. When used as a simple index (stature2/ resistance), BIA is more sensitive and specific for grading average adiposity in groups than some other anthropometric indexes such as the body mass index. Prediction equations based on BIA have been validated and cross-validated in children, youths, adults, and the elderly, in primarily white populations and, to a limited extent, in Asian, black, and Native American populations.

Assessment of body composition in youths and relationship to sport.

Body composition assessment techniques provide estimates of percent body fat (%BF), fat mass (FM), and fat-free mass (FFM) based on indirect assessment models and methods. Prediction equations for %BF developed using a two-component model based on adult body composition constants with overestimate %BF in youths, especially prepubescent youths. Body composition prediction equations that have been validated and cross-validated using multiple-component criterion models which include measurements of body density and the water and mineral components of FFM provide the most accurate means for assessment of body composition in youths. Use of appropriate prediction equations and proper measurement techniques, for either bioelectrical impedance or skinfolds, results in body composition estimates with standard errors of estimate (prediction errors) of 3 to 4% BF and 2.0 to 2.5 kg of FFM. Poor measurement technique and inappropriate prediction equations will result in much larger prediction errors.

Effects of resistance training on regional and total bone mineral density in premenopausal women: a randomized prospective study.

This study was designed to assess the effects of 18 months of resistance exercise on regional and total bone mineral density (BMD) and soft tissue lean mass (STL) in premenopausal women aged 28-39 randomly assigned to an exercise or control group. Twenty-two exercise and 34 control subjects completed the 18-month training study. All subjects were previously inactive and untrained women. Initial, 5-, 12- and 18-month assessments were made of total and regional BMD and total and regional STL using dual energy X-ray absorptiometry. All subjects consumed a 500 mg/day elemental calcium supplement throughout the study. Initial Ca intake without supplement averaged 1,023 mg/day in total sample. Serum levels of bone osteocalcin and dietary assessments using 12 randomly assigned days of diet records were also completed. Muscular strength was assessed from both 1 repetition maximum (RM) testing of 10 weightlifting exercises and by peak torque for hip abduction/adduction and knee extension/flexion. Training increased strength by 58.1% based on 1 RM testing and by 33.8% based on isokinetic testing at 18 months versus baseline. BMD increased significantly above baseline at the lumbar spine for the exercise group at 5 months (2.8%), 12 months (2.3%), and 18 months (1.9%) as compared with controls. Femur trochanter BMD increased significantly (p < 0.05) in the exercise group at 12 months (1.8%) and 18 months (2.0%) but not at 5 months (0.7%) as compared with controls. No changes in total BMD, arm BMD, or leg BMD were found. There was a 20% increase in BGP in the exercise group as compared with controls at 5 months and this difference was maintained throughout the study. For STL, significant increases for total, arm, and leg were found at 5, 12, and 18 months for the exercise group versus control ranging from 1-6% over baseline. These results support the use of strength training for increasing STL and muscular strength with smaller but significant regional increases in BMD in the premenopausal population.

Nutrients, body composition and exercise are related to change in bone mineral density in premenopausal women.

This study determined relationships among total energy intake, nutrient intake, body composition, exercise group status, and annual rates of change (slopes) in bone mineral density in 66 Caucasian premenopausal women (mean age, 34.4 +/- 2.7) taking calcium supplements. Body composition components measured by dual-energy X-ray absorptiometry included fat mass, soft tissue lean mass, and bone mineral density (g/cm2) of total body, spine (lumbar vertebrae 2-4), and three femur sites measured at baseline, 5, 12, and 18 mo. Nutrients were not significant variables in regression models predicting bone mineral density slopes (rates of change) at any femur site. The only significant variable in models predicting Ward's triangle bone mineral density slope was the initial fat mass and, for trochanter, exercise. Significant variables (P < 0.05) in models predicting total body bone mineral density slope included the initial fat mass and fat mass slope plus either vitamin A, carotene, fiber, magnesium, or phosphorus (R2 from 0.31 to 0.25) and fat mass slope plus sodium (R2 = 0.24). The significant variable in the model predicting L2-4 slope was energy intake (R2 = 0.17, P < 0.05). We conclude that nutrient intake, exercise, and body composition are related to bone mineral density rate of change and that relations among these variables vary by bone site.

Prediction of body composition in premenopausal females from dual-energy X-ray absorptiometry.

Four methods for predicting body composition were compared in premenopausal females (n = 100), 28-39 yr old, by using underwater weighing (UWW) as the criterion method. The four methods were dual energy X-ray absorptiometry (DEXA), skinfolds, bioelectrical impedance, and body mass index. The sample had a mean percent fat (%fat) of 29.7 +/- 6.8% (SD) by DEXA and 29.9 +/- 5.8% measured by UWW. DEXA yielded a standard error of estimate (SE) of 2.4% (r = 0.91) for the prediction of %fat from UWW. When %fat was estimated from other methods, larger SEs were obtained: 3.0% for skin-folds, 3.3% for body mass index, and 2.9% for bioelectrical impedance (height2/resistance) plus weight. Individual body density values derived from UWW were corrected for bone mineral variation. DEXA predicted the corrected body density with a lower SE (0.0040 vs. 0.0053 g/ml) than the original density values. We conclude that DEXA was a precise method and correlated highly with fat-free body weight and %fat from UWW in this homogeneous female sample.

Resistance exercise training is associated with decreases in serum low-density lipoprotein cholesterol levels in premenopausal women.

BACKGROUND: Aerobic exercise training is associated with reduced serum concentrations of triglycerides, increased concentrations of high-density lipoprotein cholesterol, and minimal changes in serum levels of total cholesterol or low-density lipoprotein cholesterol. There are few data on the effects of resistance exercise on blood lipid levels. METHODS: Premenopausal women were randomly assigned to a supervised resistance exercise training program (n = 46) or a control group (n = 42) for 5 months. Serum was analyzed for levels of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides. Body composition and dietary intake were also measured. RESULTS: The exercise group showed a 0.33 +/- 0.03-mmol/L (mean +/- SE) decrease in total cholesterol level and a 0.36 +/- 0.001-mmol/L decrease in low-density lipoprotein cholesterol level that was significantly different from the control group. No significant changes were noted in serum high-density lipoprotein cholesterol or triglyceride levels in either group. Changes in body composition showed no significant correlations with changes in total cholesterol or low-density lipoprotein cholesterol. There were no significant differences in nutrient intake between the groups. CONCLUSION: In healthy, premenopausal women, with normal baseline lipid profiles, 5 months of resistance exercise training was associated with significant decreases in serum total cholesterol and low-density lipoprotein cholesterol concentrations.

Food selection for endurance sports.

1) The body requires at least 40 nutrients that are classified into six groups: protein, carbohydrate, fat, vitamin, mineral, and water. These nutrients cannot be made in the body and so they must be supplied from solid or liquid foods. 2) Fat, carbohydrate, and protein contain energy that is measured in units called kilocalories. Alcohol also contains kilocalories, but is not a recommended energy source for endurance exercise. 3) Foods in endurance sports training programs should provide adequate fluids to prevent dehydration; energy intake that is high in carbohydrate, low in fat, adequate in protein, and that maintains desirable body weight and desirable proportions of fat and lean weight; and sufficient amounts of vitamins and minerals. 4) Six categories of food types form the fundamentals of good diets for endurance exercise training and include: fruits, vegetables, grains-legumes, lean meats, low-fat milk products, and fats-sweets. Vegetarian diets include all food type categories except meat and/or milk products. 5) Fat and carbohydrate content of foods in each food type category varies greatly because of how foods are prepared. 6) The Food Pyramid and Sports Food Swap are guides for selecting foods that provide recommended amounts of essential nutrients for endurance exercise. 7) Before, during, and after endurance exercise, food intake should include adequate amounts of easily digestible, high carbohydrate foods that are familiar and psychologically satisfying. 8) Easily digestible high carbohydrate liquid or solid foods should be eaten soon after exercise is stopped to maximize rates of glycogen replacement. 9) Dehydration can be prevented by adequate fluid intake before, during, and after exercise. 10) Any food plan should be tested before a competition to find out how well that plan works for an athlete.

Bioelectrical impedance estimation of fat-free body mass in children and youth: a cross-validation study.

The purposes of this study were to develop and cross-validate the "best" prediction equations for estimating fat-free body mass (FFB) from bioelectrical impedance in children and youth. Predictor variables included height2/resistance (RI) and RI with anthropometric data. FFB was determined from body density (underwater weighing) and body water (deuterium dilution) (FFB-DW) and from age-corrected density equations, which account for variations in FFB water and bone content. Prediction equations were developed using multiple regression analyses in the validation sample (n = 94) and cross-validated in three other samples (n = 131). R2 and standard error of the estimate (SEE) values ranged from 0.80 to 0.95 and 1.3 to 3.7 kg, respectively. The four samples were then combined to develop a recommended equation for estimating FFB from three regression models. R2 and SEE values and coefficients of variation from these regression equations ranged from 0.91 to 0.95, 2.1 to 2.9 kg, and 5.1 to 7.0%, respectively. As a result of all cross-validation analyses, we recommend the equation FFB-DW = 0.61 RI + 0.25 body weight + 1.31, with a SEE of 2.1 kg and adjusted R2 of 0.95. This study demonstrated that RI with body weight can predict FFB with good accuracy in Whites 10-19 yr old.

Fat-free mass in children and young adults predicted from bioelectric impedance and anthropometric variables.

Fat-free mass (FFM) values calculated from densitometry by using a multicomponent model were significantly (p less than 0.05) larger than those from the Siri two-component model (465 males, 441 females), especially in children and females. The multicomponent model assumes the density of FFM varies by age and sex because of differences in its constituents. With FFM values from the multicomponent model as the dependent variable and impedance and anthropometry as the independent variables, prediction equations were derived by all possible subsets of regression (140 males, 110 females). These equations had RMSEs of 2.2-2.3 kg and CVs of 5.0-5.8%. Cross-validation results were excellent for young adults but less satisfactory for children for whom a different calf skinfold had been measured. The selected equations are applicable to healthy white individuals aged 7-25 y.

Validity of bioelectric impedance for body composition assessment in children.

Whole-body bioelectrical impedance analysis (BIA) was evaluated for its reliability and accuracy in estimating body composition in children. The hypothesis that the index, body height2 divided by resistance (RI), can accurately predict fat-free body mass (FFB) and percent fat (%FAT) in children was tested on 94 caucasian children 10-14 yr old. Criterion variables were FFB and %FAT estimated using multicomponent equations developed for children. BIA measurements (resistance and reactance) were found to be reliable. Prediction accuracy (standard error of the estimate, SEE) for FFB from RI alone was 2.6 kg and for %FAT from RI and body weight was 4.2%. For RI, anthropometric variables and reactance, the SEE improved to 1.9 kg FFB. For RI and anthropometric variables, the SEE was 3.3% FAT. For anthropometric variables alone, the SEE's were 2.1 kg FFB and 3.2% FAT. Adult FFB and %FAT prediction equations cross-validated with this sample resulted in SEE's similar to those for adult samples. We conclude that RI together with anthropometry is a reliable and an acceptably accurate method of estimating FFB mass and %FAT in children.

Adolescent self-assessment of sexual maturation. Effects of fatness classification and actual sexual maturation stage.

Accuracy of self-assessed staging of sexual maturation was studied on 96 adolescents (49 boys and 47 girls) to validate previous studies and evaluate the effects of an adolescent's fatness level and actual sexual maturation stage on their ability to assess their level of sexual maturation. Correlation between the adolescents' self-assessments and physician assessments was moderately high (Kendall's tau-b = 0.65-0.82). Boys tended to overestimate, while girls underestimated their level of sexual maturation. Differences between physician and subject ratings by fatness classification or by actual sexual maturation stage was not significant. This study supports previous studies showing that adolescents can accurately assess their own stage of sexual maturation regardless of their fatness classification or actual sexual maturation stage.