Does previous participation in high-impact training result in residual bone gain in growing girls? One year follow-up of a 9-month jumping intervention.

The skeletal response to exercise and training on bone is exceptionally good during the growing years. However, it is not known whether the benefit of training on bone is maintained after the training. This 20-month follow-up study assessed the effect of a 9-month jumping intervention on bone gain and physical performance in 99 girls (mean age 12.5 +/- 1.5 years at the beginning of the study) one year after the end of the intervention. Both bone mineral content (BMC), by dual energy X-ray absorptiometry (DXA) at the lumbar spine and proximal femur, and physical performance parameters (standing long jump, leg extension strength, and shuttle run tests) were measured at baseline and at 20 months. A multivariate regression analysis was first used to determine the best predictors of the BMC accrual by time. Analysis showed that age at baseline and square of age, changes in height and weight, and pubertal development into Tanner stages 4 and 5 during the follow-up explained the majority of the BMC gain. Then, the effect of participation in the 9-month exercise intervention on BMC accrual and physical performance was analysed adding this variable (participation: yes/no) into the model. The regression analysis showed that the trainees (N = 50) had 4.9 % (95 % CI, 0.9 % to 8.8 %, p = 0.017) greater BMC increase in the lumbar spine than the controls (N = 49). The mean 20-month BMC increase in the lumbar spine was 28 % (SD 19) in the trainees compared to 22 % (12) increase in the controls. In the proximal femur, the trend was similar but the obtained 2 to 3 % higher BMC accrual in the trainees (compared to that in controls) were statistically insignificant. Among the performance variables, using the same model that best predicted the BMC accrual, the only statistically significant between-groups difference, in favour of the trainees, was the improvement in the standing long jump test (6.4 %, 95 % CI, 2.3 % to 10.4 %, p = 0.002). Improvements in the leg extension strength and shuttle run tests showed no between-groups difference. In conclusion, although the greatest proportion of bone mineral accrual in growing girls is attributable to growth, an additional bone gain achieved by jumping training is maintained at the lumbar spine at least a year after the end of the training.

Bone mineral density during reduction, maintenance and regain of body weight in premenopausal, obese women.

Weight loss may lead to bone loss but little is known about changes in bone mass during regain of reduced weight. We studied changes in bone mineral density (BMD) and bone mineral content (BMC) during voluntary weight reduction and partial regain. The study consisted of three phases: a 3 month weight reduction with very-low-energy diet (VLED), a 9 month randomized, controlled walking intervention period with two training groups (target energy expenditure 4.2 or 8.4 MJ/week) and a 24-month follow-up. The participants were premenopausal women with a mean body mass index of 34.0 (SD 3.6) kg/m2. Seventy-four of 85 subjects completed the whole study. Total body, lumbar spine, proximal femur and dominant radius BMD and BMC were measured with dual-energy X-ray absorptiometry (DXA). The mean weight loss during VLED was 13.2 (3.4) kg, accompanied by unchanged total body BMC and decreased lumbar, trochanteric and radial BMD (p < 0.05). During months 3-36, an average of 62% of the weight loss was regained, total body BMC decreased and trochanteric BMD increased (p < 0.05). At the end of the study, total body BMC and lumbar and femoral neck BMD were lower than initially (p < 0.05). Weight change throughout the study correlated significantly with the change in radial (r = 0.54), total body (r = 0.39) and trochanteric (r = 0.37) BMD. Exercise-group assignment had no effect on BMD at weight-bearing sites. In conclusion, the observed changes in BMD and BMC during weight reduction and its partial regain were clinically small and partly reversible. More studies are needed to clarify whether the observed weight changes in BMD and BMC are real or are artifacts arising from assumptions, inaccuracies and technical limitations of DXA.

Assessment of fat-mass loss during weight reduction in obese women.

Methods for assessing body fat mass (FM) loss were compared in 32 obese (body mass index [BMI], 29 to 41 kg/m2) premenopausal women before and after a weight loss of 13.0 +/- 3.4 kg (mean +/- SD). A four-component (4C) model was used as the criterion. The other methods were as follows: three-component models (body density with total body water [3W] or bone minerals [3M]), underwater weighing, dual-energy x-ray absorptiometry ([DXA] XR-26, software 2.5.2; Norland, Ft Atkinson, WI), bioelectric impedance analysis (BIA) with an obese-specific equation [Segal et al), skinfolds (Durnin and Womersley), and an equation with BMI (Deurenberg et al). The 3W model (bias +/- SD, 0.5 +/- 0.4 kg), XR-26 (0.6 +/- 2.1 kg), and BMI equation (-0.3 +/- 2.1 kg) gave practically unbiased mean estimations of fat loss. All other methods underestimated fat loss by at least 1.6 kg (range of bias, -2.7 to -1.6 kg). The small bias (0.7 +/- 1.0 kg) between underwater weighing and model 4C before weight reduction indicates that the two-component assumptions were valid in premenopausal, weight-stable obese women. However, particularly the water fraction of the fat-free body component (4C model) was increased after weight reduction (before, 72.9% +/- 1.4%; after, 75.7% +/- 2.2%), making both underwater weighing and the 3M model uncertain for assessment of body composition changes. A general tendency for overestimating FM was seen before and more clearly after weight reduction. However, most methods underestimated fat loss, apparently because of unexpected changes in hydration of the fat-free body component.

Body composition assessment in lean and normal-weight young women.

Using percentage body fat (BF%) from a three-compartment (3C) model (body density from underwater weighing (UWW) and bone-mineral mass from dual-energy X-ray absorptiometry (DXA) as a criterion, we studied the accuracy of UWW, DXA, two skinfold equations, and two bioimpedance (BIA) equations. Thirty-four women (aged 16-20 years) with BF% 13.5-31.1 volunteered. UWW underestimated BF% by -0.5 BF% (95% CI: -1.0; -0.02), whereas DXA overestimated it by 7.3 BF% (95% CI 5.8; 8.8). Skinfolds underestimated and BIA overpredicted BF%. The differences between 3C and UWW, skinfolds (Durnin & Womersley, 1974) and BIA (Deurenberg et al. 1990) were dependent (range of r values: -0.63 to -0.79; P < 0.0001) on BF%, causing an overestimation of lean subjects' (UWW, BIA) or an underestimation of normal-weight subjects' (UWW, skinfolds) BF%. The 3C model and UWW gave comparable body-composition results for healthy young women with BF% of approximately 20-25. Based on a significant mean difference from the 3C model, and a large standard error of the estimate, we do not regard DXA as superior to skinfolds or BIA to assess BF%.

Resting metabolic rate and energy intake in female gymnasts, figure-skaters and soccer players.

We examined the hypothesis that lean female athletes, as compared to other female athletes and controls, have a greater deficit between reported energy intake (EI) and estimated energy expenditure (EE), and a reduction in resting energy expenditure adjusted to fat free and fat masses (REEADJ). The subjects were 12 gymnasts and figure-skaters (lean athletes), 12 soccer players (normal-weight athletes) and 10 normal-weight, untrained, controls. Body composition was calculated from a 3-compartment model (underwater weighing and dual energy x-ray absorptiometry). REE was assessed by indirect calorimetry. Physical activity and EI were estimated from 7-day records. EE was calculated using activity records and REE. REEADJ was similar in all groups (p > 0.05). EI was 8.29 (SD 1.84), 7.04 (SD 2.23) and 8.95 (SD 1.68) MJ.d-1 in controls, gymnasts and soccer players, respectively (p = 0.06). In gymnasts, reported EI was 3.19 (SD 2.63) MJ.d-1 lower than estimated EE. EI minus EE in controls was -0.18 (SD 1.80; different from gymnasts, p < 0.01) MJ.d-1, and in soccer players -0.47 (SD 1.89; different from gymnasts, p < 0.05) MJ.d-1. Low reported energy intake in gymnasts might reflect their attitudes on diet and body image.