The relative body fat and anthropometric prediction of body density of South Australian females aged 17—35 years

Summary One hundred and thirty-five females were tested in order to: produce some normative percentage body fat (% BF) data on an Australian sample which represented a cross-section of physical activity patterns, cross-validate existing multiple regression equations which predict body density (BD) from anthropometric measurements, and if necessary develop population specific equations.Measurements were taken of 10 girths, 3 widths and 7 skinfolds. Body density was measured by underwater weighing with the residual volume (RV) being determined by helium dilution. The Siri equation was then used to convert BD to % BF. The % BF scores had an overall mean of 23.4 (range 10.8–49.2). The very active group (n=45) had a significantly lower (p<0.05) relative body fat (X=20.6% BF) than either the active (n=45; 23.5% BF) or sedentary groups (n=45; 26.2% BF). Previously published equations were found to have limited applicability to Australian subjects. A stepwise multiple regression was therefore used to develop the following equation (R = 0.893): BD(g·cm^–3) = 1.16957-0.06447 (log₁₀ triceps, subscapular, supraspinale, front thigh, abdominal and calf skinfolds in mm)-0.00081 (gluteal girth in cm)+ 0.0017 (forearm girth in cm) + 0.00606 (biepicondylar humerus breadth in cm). Only those predictors which resulted in a statistically significant increase inr (p0.05) were included. The standard error of estimate of 0.00568 g · cm^–3 was equivalent to 2.6% BF at the mean.This study was supported by a grant from the Menzies Foundation     

Bias and limits of agreement between hydrodensitometry, bioelectrical impedance and skinfold calipers measures of percentage body fat

Previous research has often used correlations as a statistical method to show agreement; however, this is not a valid use of the statistic. The purpose of this study was to investigate the bias and limits of agreement for three methods of estimating percentage body fat for 117 male and 114 female university athletes: hydrodensitometry (HYD), bioelectrical impedance (BIA) and skinfold calipers (SKF). The mean (SD) percentage body fat for males as assessed by HYD, BIA and SKF methods, respectively, were 13.2 (3.3)%, 14.1 (3.3)% and 13.0 (3.2)%. Female body fat measurements were 22.5 (3.9)%, 23.7 (4.3)% and 23.8 (4.2)%, respectively. Pearson product moment correlations for male and female body fat percentages between the three methods were high, ranging from 0.81 to 0.86 (P < 0.05). However, compared to the criterion measure of body fat percentage (HYD), the magnitude of agreement BIA and SKF revealed a different pattern. The mean absolute difference between HYD and BIA measurements of body fat for males was −0.8 (2.0)% fat, and between HYD and SKF was it was 0.2 (1.7)% fat. The mean absolute difference for females between HYD and BIA was −1.2 (2.5)%; for HYD and SKF it was −1.4 (2.2)%. Compared to the HYD measures for males and females, the BIA and SKF measures were as much as a 3.8% underestimation and a 6.2% overestimation of body fat. This study provides evidence that the strength of a correlation does not indicate agreement between two methods. In future, reliability and validity studies should examine the absolute differences between two variables and calculate limits of agreement around which a practitioner can appreciate the precision of the methodologies. Accepted: 26 August 1997     

The monitoring of the menstrual status of female athletes by salivary steroid determination and ultrasonography

Summary This study was designed to evaluate whether traditional plasma hormone determinations can be adequately replaced by measurements of salivary hormones. Eleven young sportswomen with menstrual irregularities attributed to strenuous physical exercise participated in this study. Mean body weight expressed as a percentage of ideal body weight was 92%, SD 4%. Their mean weekly training distance was 35 km, SD 15. Basal plasma endocrinological measurements revealed a hypo-oestrogenic status (mean plasma oestradiol values: 22pg-ml^–1, SD 8.8), and a deficient luteal phase (mean plasma progesterone: 2.9 ng · ml^–1, SD 2.1). Preexercise salivary sex steroids were low. Salivary progesterone levels were 39.3 pg · ml^–1, SD 9.5 (normal ranges in saliva: 25–60 pg· ml^–1), salivary oestrone (E₁) was 12.2 pg · ml^–1, SD 2.3 (normal ranges in saliva: 7.5–25 pg·ml^–1), and salivary oestradiol (E₂) < 1.9 pg · ml^–1, SD 1.1 (normally 1.0–10.0 pg · ml^–1). After a 21-km run, all salivary steroids appeared to increase. Mean salivary testosterone levels increased by 15.2% and salivary progesterone by 14.8%. Mean salivary oestrogens also increased (E₁: + 13.9%; E₂: +21.1%). These findings confirm the results of earlier studies which found higher post-exercise plasma sex steroid levels. Since salivary measurements are believed to reflect non-protein-bound, thus free steroid levels, the results obtained by these techniques may provide a more realistic picture of the hormonal effects of physical exercise. In future, more accurate, cost-effective and easier techniques for salivary measurements may offer additional advantages.     

Skeletal muscle properties and performance in elite female track athletes

Summary Selected biochemical and physiological properties of skeletal muscle were studied in light of performance capabilities in 24 elite female track athletes. The feasibility of quantifying end point histochemistry and relating oxidative staining density (reduced nicotinomide adenine dinucleotide diaphorase: NADH-D) to whole body maximal oxygen consumption ( max) was also investigated, while muscle fiber types, classified according to alkaline APTase stains, were studied and related to muscle oxidative capacity (succinate dehydrogenase: SDH), max and “in vivo” torque-velocity properties. Muscle biopsies were taken from the vastus lateralis of each subject and maximal knee extensor torques were recorded at 30‡ from full extension at four selected velocities. While results confirm earlier reports on skeletal muscle properties and performance it was concluded that end point histochemistry could be reliably quantified and that an “oxidative” stain such as NADH-D correlates extremely well with max (r=0.86,p<0.001) whereas correlations between %slow twitch fibres (alkaline ATPase stain) and max were lower (r=0.44,p<0.05). Additionally, as knee extension velocity increased from 0–1.7 rad·s⁻¹ angle specific extensor torque production did not decline as observed in vitro and pentathletes displayed significantly larger torques at all velocities when compared to the other athletes. These data confirm that while myofibrillar ATPase staining correlates with force-velocity properties of muscle, max is better correlated with quantified oxidative staining. Supported in part by a Public Health Service Biomedical Research Support Grant to UCLA, Public Health Service Grant 10423 and by the National Aeronautics and Space Administration (NASA)     

Anemia and iron status in young fertile non-professional female athletes

We evaluated the effects of regular physical exercise on anemia and iron status in young non-professional female athletes. A total of 191 healthy white Italian women (23.5 ± 4.68 years) were analyzed; 70 were non-professional athletes performing 11.1 ± 2.63 h week⁻¹ exercise and 121 were sedentary controls. Blood markers of anemia and iron status—hemoglobin (Hb), hematocrit (Hct), red blood cells (RBC), serum ferritin, iron, transferrin (Tf), transferrin saturation (TfS), soluble transferrin receptor (sTfR), and the sTfR/log ferritin ratio (sTfR-F index)—were evaluated. Anemia threshold was Hb < 120 g l^–1. Ferritin concentrations < 12 μg l^–1 were considered as iron deficiency (ID). Frequency of anemia (15.7 versus 10.7%, P = 0.32), ID (27.1 versus 29.8%, P = 0.70), and ID anemia (8.6 versus 5.8%, P = 0.46) was not different in athletes and controls. However, athletes were threefold more likely than controls (17.1 versus 5.8%) to have serum iron < 50 μg dl^–1 [odds ratio (OR) 3.37, P = 0.012]. Low-TfS (<15%) was found in 25.7% of athletes and in 13.2% of controls, OR 2.27, P = 0.030. Elevated-sTfR (>1.76 mg l^–1) was found in 24.3% of athletes and in 12.4% of controls, OR 2.27, P = 0.034. Regular non-professional sport activity does not cause an increased rate of anemia or of iron deficiency in fertile women. However, physical exercise has an impact on iron status as it reduces serum iron and transferrin saturation, and elevates sTfR. Nearly one fifth of recreational athletes have anemia and a third have iron deficit, these conditions can decrease their physical performance.     

Brozek two-compartment model under-estimates body fat in black female athletes.

The purpose of this study was to compare percentage body fat (%BF) values of black female athletes calculated using the Heymsfield four-compartment (4C), Brozek two-compartment (2C) and Schutte models. Eleven collegiate athletes underwent total body water (TBW) assessment, hydrostatic weighing (HW) and dual energy X-ray absorptiometry (DXA). Repeated-measures ANOVA determined that the 4C model yielded %BF values (16.2 +/- 1.5%) that were higher than the Brozek model (13.6 +/- 1.7%) but similar to the Schutte model (16.7 +/- 1.6%). The fat-free mass density of the athletes (1.109 +/- 0. 002 kg l-1) was significantly higher than the value 1.1 kg l-1 assumed by the 2C model. We conclude that in lean black female athletes, the Brozek 2C model under-estimates %BF, and that, if only HW is available, the Schutte model should be used to estimate %BF.     

Estimation of body density and lean body weight from body measurements at high altitude

Body density and other anthropometric data were obtained on 101 Indian soldiers who were continuously staying at high altitude (3920 m) for more than 10 months. Use was made of a human body volumeter, and body density was calculated from observed body weight and volume. Measurements were taken on the body using standard techniques. A stepwise linear regression analysis was performed to establish possible relationships of 36 body measurements with density and lean body weight. Thigh anterior, juxta-nipple skin folds and forearm and ankle circumferences were selected in the regression equation predicting body density. Multiple correlation coefficient (R) equal to 0.765 was obtained for this equation. For the predicted lean body weight, R equalled 0.930. The regression equations included body weight, thigh anterior and juxta-nipple skin fold thicknesses, and forearm circumference. Contribution of other body measurements in the regression of these parameters was not significant. The analysis also revealed that a new set of coefficients is required for the measurements included in the published regression equations.     

Human body surface area: measurement and prediction using three dimensional body scans

The development of three dimensional laser scanning technology and sophisticated graphics editing software have allowed an alternative and potentially more accurate determination of body surface area (BSA). Raw whole-body scans of 641 adults (395 men and 246 women) were obtained from the anthropometric data base of the Civilian American and European Surface Anthropometry Resource project. Following surface restoration of the scans (i.e. patching and smoothing), BSA was calculated. A representative subset of the entire sample population involving 12 men and 12 women (G24) was selected for detailed measurements of hand surface area (SA_hand) and ratios of surface area to volume (SA/VOL) of various body segments. Regression equations involving wrist circumference and arm length were used to predict SA_hand of the remaining population. The overall [mean (SD)] of BSA were 2.03 (0.19) and 1.73 (0.19) m² for men and women, respectively. Various prediction equations were tested and although most predicted the measured BSA reasonably closely, residual analysis revealed an overprediction with increasing body size in most cases. Separate non-linear regressions for each sex yielded the following best-fit equations (with root mean square errors of about 1.3%): BSA (cm<SUP>2</SUP>)=128.1·<I>m</I><SUP>0.44</SUP>·<I>h</I><SUP>0.60</SUP>for men and BSA=147.4·<I>m</I><SUP>0.47</SUP>·<I>h</I><SUP>0.55</SUP>for women, where m, body mass, is in kilograms and h, height, is in centimetres. The SA/VOL ratios of the various body segments were higher for the women compared to the men of G24, significantly for the head plus neck (by 7%), torso (19%), upper arms (15%), forearms (20%), hands (18%), and feet (11%). The SA/VOL for both sexes ranged from approximately 12·m^–1 for the pelvic region to 104–123·m^–1 for the hands, and shape differences were a factor for the torso and lower leg. Electronic Publication     

Predicting football players' dual-energy x-ray absorptiometry body composition using standard anthropometric measures

Context:

The recent increase in athlete size, particularly in football athletes of all levels, coupled with the increased health risk associated with obesity warrants continued monitoring of body composition from a health perspective in this population. Equations developed to predict percentage of body fat (%Fat) have been shown to be population specific and might not be accurate for football athletes.

Objective:

To develop multiple regression equations using standard anthropometric measurements to estimate dual-energy x-ray absorptiometry %Fat (DEXA%Fat) in collegiate football players.

Design:

Controlled laboratory study.

Patients and Other Participants:

One hundred fifty-seven National Collegiate Athletic Association Division IA football athletes (age  =  20 ± 1 years, height  =  185.6 ± 6.5 cm, mass  =  103.1 ± 20.4 kg, DEXA%Fat  =  19.5 ± 9.1%) participated.

Main Outcome Measure(s):

Participants had the following measures: (1) body composition testing with dual-energy x-ray absorptiometry; (2) skinfold measurements in millimeters, including chest, triceps, subscapular, midaxillary, suprailiac, abdominal (SFAB), and thigh; and (3) standard circumference measurements in centimeters, including ankle, calf, thigh, hip (AHIP), waist, umbilical (AUMB), chest, wrist, forearm, arm, and neck. Regression analysis and fit statistics were used to determine the relationship between DEXA%Fat and each skinfold thickness, sum of all skinfold measures (SFSUM), and individual circumference measures.

Results:

Statistical analysis resulted in the development of 3 equations to predict DEXA%Fat: model 1, (0.178 • AHIP) + (0.097 • AUMB) + (0.089 • SFSUM) − 19.641; model 2, (0.193 • AHIP) + (0.133 • AUMB) + (0.371 • SFAB) − 23.0523; and model 3, (0.132 • SFSUM) + 3.530. The R² values were 0.94 for model 1, 0.93 for model 2, and 0.91 for model 3 (for all, P < .001).

Conclusions:

The equations developed provide an accurate way to assess DEXA%Fat in collegiate football players using standard anthropometric measures so athletic trainers and coaches can monitor these athletes at increased health risk due to increased size.     

Changes in body fat and muscle in manual workers at and after retirement

Summary The changes in body fat and muscle in 73 men retiring from manual work have been measured in a longitudinal anthropometric study. Body fat increased by about 3% and body muscle decreased by about 1% between measurements made just before retirement and again 1 year later. The decline in muscle was even greater in a subgroup of 22 men who reported that their activity was less after retirement: but a subgroup of 11 whose activity was said to have been greater after retirement showed an increase in body muscle. A sub-sample of 26 men were measured on five further annual occasions (Fig. 1). The initial increase in body fat was reversed, and fat measurements fell back significantly to or below the pre-retirement values. Body muscle, however, continued to decline steadily at the initial rate, and the ratio of thigh muscle area to body mass fell significantly in retirement in the group as a whole. The possible contributions of ageing and of changes in energy balance and physical activity to these findings are discussed. Supported by the Nuffield Foundation and the Medical Research Council     

Estimating body fat in NCAA Division I female athletes: a five-compartment model validation of laboratory methods

The purpose of the present study was to determine the validity of various laboratory methods for estimating percent body fat (%fat) in NCAA Division I college female athletes (n = 29; 20 ± 1 year). Body composition was assessed via hydrostatic weighing (HW), air displacement plethysmography (ADP), and dual-energy X-ray absorptiometry (DXA), and estimates of %fat derived using 4-compartment (C), 3C, and 2C models were compared to a criterion 5C model that included bone mineral content, body volume (BV), total body water, and soft tissue mineral. The Wang-4C and the Siri-3C models produced nearly identical values compared to the 5C model (r > 0.99, total error (TE) < 0.40%fat). For the remaining laboratory methods, constant error values (CE) ranged from −0.04%fat (HW-Siri) to −3.71%fat (DXA); r values ranged from 0.89 (ADP-Siri, ADP-Brozek) to 0.93 (DXA); standard error of estimate values ranged from 1.78%fat (DXA) to 2.19%fat (ADP-Siri, ADP-Brozek); and TE values ranged from 2.22%fat (HW-Brozek) to 4.90%fat (DXA). The limits of agreement for DXA (−10.10 to 2.68%fat) were the largest with a significant trend of −0.43 (P < 0.05). With the exception of DXA, all of the equations resulted in acceptable TE values (<3.08%fat). However, the results for individual estimates of %fat using the Brozek equation indicated that the 2C models that derived BV from ADP and HW overestimated (5.38, 3.65%) and underestimated (5.19, 4.88%) %fat, respectively. The acceptable TE values for both HW and ADP suggest that these methods are valid for estimating %fat in college female athletes; however, the Wang-4C and Siri-3C models should be used to identify individual estimates of %fat in this population.     

The influence of anthropometric factors on postural balance: the relationship between body composition and posturographic measurements in young adults

OBJECTIVE:

The aim of the present study was to evaluate the influence of anthropometric characteristics and gender on postural balance in adults. One hundred individuals were examined (50 males, 50 females; age range 20-40 years).

METHODS:

The following body composition measurements were collected (using bone densitometry measurements): fat percentage (% fat), tissue (g), fat (g), lean mass (g), bone mineral content (g), and bone mineral density (g/cm²). In addition, the following anthropometric measurements were collected: body mass (kg), height (cm), length of the trunk-cephalic region (cm), length of the lower limbs (cm) and length of the upper limbs (cm). The following indices were calculated: body mass index (kg/m²), waist-hip ratio and the support base (cm²). Also, a postural balance test was performed using posturography variables with open and closed eyes.

RESULTS:

The analysis revealed poor correlations between postural balance and the anthropometric variables. A multiple linear regression analysis demonstrated that the whole group (female and male) height explained 12% of the medial-lateral displacement, 10% of the speed of oscillation, and 11% of the displacement area. The length of the trunk-cephalic length explained 6% of the displacement in the anteroposterior direction. With eyes closed, the support base and height explained 18% of the medial displacement, and the lateral height explained 10% of the displacement speed and 5% of the scroll area.

CONCLUSION:

Measured using posturography, the postural balance was only slightly influenced by the anthropometric variables, both with open and closed eyes. Height was the anthropometric variable that most influenced postural balance, both in the whole group and separately for each gender. Postural balance was more influenced by anthropometric factors in males than females.     

Physiological and metabolic effects of a 25 km race in female athletes

Summary Nine female athletes were examined before and after a 25 km race (German championship). Their average running speed was 3.89 m/s. Postexercise weight loss was 1.60±0.58 kg or 2.87% of body weight, the mean rectal temperature increased by 1.04±0.52 C to 38.4±0.54 C. Leucocytes, but no other blood parameters (hemoglobin, hematocrit, erythrocytes, MCV) showed a marked rise after the race. Blood lactate rose from 1.86±0.34 to 4.97±1.19 mmol/l but hypoglycemia was not present in any of the athletes at the end of exercise. After the run serum enzymes showed lower increases than those observed in men for the same exercise duration. Serum sodium, chloride and potassium showed similar increases, inorganic phosphate higher increments than found in men. The comparatively high rise in free glycerol suggested a marked mobilization of lipid substrate, whereas the increment in serum of free fatty acids was lower than in male subjects after similar athletic events.A lowering of neuromuscular excitability (m. vastus medialis quadricipitis) was found after the race but the changes were significant only for the fibers responding to longer durations of stimuli (0.3–30 ms).     

Validity of anthropometric percent fat prediction equations for use with pregnant women

The purpose of this investigation was to determine the validity of five different skinfold prediction equation for use in forecasting the percent body fat of pregnant women. Twenty-one pregnant women underwent hydrostatic and skinfold thickness determinations of percent body fat at 6–10, 16, and 28 weeks of gestation. The correlations between hydrostatic and anthropometric determinations of percent body fat were high during the three test periods (r= .78 to r = .89). The slopes of the line of best fit between the criterion (hydrostatic weighing) and predicted variable (prediction equation) decreased across pregnancy. The anthropometric prediction equations tended to overestimate percent body fat changes in comparison to the hydrostatically determined percent body fat changes. Skinfold thickness measurements can be used as a prepregnancy aid in determining recommended weight gain during pregnancy and as a measure of subcutaneous fat status during pregnancy. However, anthropometric prediction equations should not be used during the later stages of pregnancy to estimate percent fat or percent fat changes.     

Optimal treatment of replicate measurements in anthropometric studies

Background: Anthropometric studies often include replicates of each measurement to decrease error. The optimal method to combine these measurements is uncertain.

Aim: To identify the optimal method to combine replicate measures for analysis.

Methods: The authors carried out 10?000 Monte Carlo simulations to explore the effect of six approaches to combine replicate measurements in a hypothetical two-group intervention study (n?=?100 per arm) in which the outcome, infant length at age 1 year, was measured two or three times. One group had a true value with a normal distribution N (mean?=?76, SD?=?2.4?cm). Statistical power was estimated to detect a 1?cm difference between the groups, based on a t-test.

Results: Under a realistic scenario with a measurement error distribution N (0, 0.8), highest power was reached by use of the mean and the median of pairwise averages. However, when a portion of the data (≥2%) were contaminated by greater error (e.g. due to data entry), the median of three measurements outperformed all other methods while the mean had the lowest performance.

Conclusion: Obtaining three rather than two measures and using the median of the three replicates is a safe and robust approach to combine participants’ raw data values for use in subsequent analyses.     

Significance of the contribution of aerobic and anaerobic components to several distance running performances in female athletes

Summary To assess the most important determinant for successful distance running (800 m, 1500 m and 3000 m events) in female athletes, measurements of several anaerobic indices were made (peak power, mean power) using the Wingate anaerobic test (WAnT), and aerobic indices such as oxygen uptake or running velocity (v) at lactate threshold (LT), , or v at onset of blood lactate accumulation (OBLA), running economy (RE), and maximal oxygen uptake were determined using the incremental treadmill test. The RE was represented by a value measured at 240 m · min^–1 of a standard treadmill velocity. A stepwise multiple regression analysis (SAS stepwise procedure) combined the best features of forward inclusion and backward elimination to determine the most important factors in predicting the performance of running these distances as dependent variables. The stepwise procedure showed that the blood lactate variables such as LT and/or OBLA are highly correlated with, and contributed to predicting performance running 800 m-3000 m, whereas the anaerobic component was related only to running 800 m. In conclusion, blood lactate variables account for a large part of the variation in distance running performance in female as in male runners. The component of the anaerobic system which can be measured by the WAnT was shown to contribute to performance in running 800 m, but not in longer distances.     

在校女大学生脂肪和肌肉对仰卧起坐能力的影响

目的 探讨在校女大学生肌肉及脂肪分布规律对仰卧起坐能力的影响。 方法 随机抽取广西某高校非体育专业女大学生1560名,用生物电阻抗体成分仪测量躯体肌肉及脂肪等成分。按《国家学生体质健康标准》进行身高、体重及仰卧起坐测试。将仰卧起坐分数分成4组：<60分、60～69分、70～79分、≥80分。运用SPSS 22.0统计学软件分析数据。 结果 不同仰卧起坐分数段的女大学生体脂率、总脂肪量、躯干脂肪量、躯干脂肪率、内脏脂肪面积、内脏脂肪量、皮下脂肪量差异有统计学意义（F分别为3.414、2.914、2.881、3.347、3.064、3.235、2.766,均 P<0.05）,即60~69分组最高,≥80分组最低。而各分数段的总肌肉量、躯干肌肉量差异无统计学意义。矫正年龄、身高及体重因素后,除内脏脂肪面积及内脏脂肪量外,其余脂肪参数与仰卧起坐分数的相关性有统计学意义,成负相关关系(r<0, P<0.05)。全身肌肉量、躯干肌肉量与仰卧起坐分数成正相关关系,有统计学意义(r>0,P<0.05),且与其他参数相比,躯干肌肉量与仰卧起坐相关系数最大。 结论 脂肪与肌肉的分布对仰卧起坐能力影响有差异,女大学生仰卧起坐能力受皮下脂肪及躯干肌肉影响较大,而与内脏脂肪无关。     

The relation of menarcheal age to anthropometric profiles in Korean girls

The aim of this study was to represent the trend of early menarche and to assess the association of age at menarche with anthropometric profiles of Korean children and adolescents. A cross sectional survey was conducted with 13,371 girls aged 10 to 18 yr, recruited nationwide from April, 2005 to March, 2006. Height, weight and waist circumference of the subjects were measured; and the subjects self-reported their ages at menarche. We found that the menarcheal girls were taller (P<0.05 for the girls between 10 and 14 yr) and heavier (P<0.05 for the girls between 10 and 18 yr) than non-menarcheal ones. Menarcheal girls also showed higher body mass index (BMI), and greater waist circumference than non-menarcheal ones. Significant differences were represented according to the age at menarche in terms of BMI, waist circumference, % body fat mass, waist hip ratio and neck circumference as well as height and weight (P<0.05). In conclusion, girls who matured early were taller and heavier in early adolescence than those who matured later.