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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.