Formula and scale for body surface area estimation in high-risk infants

Advances in medical technology and the health sciences have lead to a rapid increase in the prevalence and morbidity of high-risk infants with chronic or permanent sequels such as the birth of early preterm infants. A suitable formula is therefore needed for body surface area (BSA) estimation for high-risk infants to more accurately devise therapeutic regimes in clinical practice. A cohort study involving 5014 high-risk infants was conducted to develop a suitable formula for estimating BSA using four of the existing formulas in the literature. BSA of high-risk infants was calculated using the four BSA equations (Boyd-BSA, Dubois-BSA, Meban-BSA, Mosteller-BSA), from which a new calculation, Mean-BSA, was arithmetically derived as a reference BSA measure. Multiple-regression was performed using nonlinear least squares curve fitting corresponding to the trend line and the new equation, Neo-BSA, developed using Excel and SPSS 17.0. The Neo-BSA equation was constructed as follows: Neo-BSA = 5.520 x W(0.5526) x L(0.300). With the assumption of the least square root relation between weight and length, a BSA scale using only weight was fabricated specifically for clinical applications where weight is more available in high-risk infant populations than is length. The validity of Neo-BSA was evaluated against Meban-BSA, the best of the four equations for high-risk infants, as there is a similarity of subjects in the two studies. The other formulas revealed substantial variances in BSA compared to Neo-BSA. This study developed a new surface area equation, Neo-BSA, as the most suitable formula for BSA measurement of high-risk infants in modern-day societies, where an emerging population of newborns with shorten gestational ages are becoming more prevalent as a result of new advances in the health sciences and new development of reproductive technologies. In particular, a scale for 400-7000 g body weight babies derived from the Neo-BSA equation has the clinical advantage of using only weight as a measurement, since length is often not feasible as a measurement due to the newborn's body posture. Further studies are required to confirm our findings for the application of Neo-BSA and the BSA scale (based on weight) for various populations and ethnicities under different clinical conditions.     

How Big Is It Really? Assessing the Efficacy of Indirect Estimates of Body Size in Asian Elephants

Information on an organism’s body size is pivotal in understanding its life history and fitness, as well as helping inform conservation measures. However, for many species, particularly large-bodied wild animals, taking accurate body size measurements can be a challenge. Various means to estimate body size have been employed, from more direct methods such as using photogrammetry to obtain height or length measurements, to indirect prediction of weight using other body morphometrics or even the size of dung boli. It is often unclear how accurate these measures are because they cannot be compared to objective measures. Here, we investigate how well existing estimation equations predict the actual body weight of Asian elephants Elephas maximus, using body measurements (height, chest girth, length, foot circumference and neck circumference) taken directly from a large population of semi-captive animals in Myanmar (n = 404). We then define new and better fitting formulas to predict body weight in Myanmar elephants from these readily available measures. We also investigate whether the important parameters height and chest girth can be estimated from photographs (n = 151). Our results show considerable variation in the ability of existing estimation equations to predict weight, and that the equations proposed in this paper predict weight better in almost all circumstances. We also find that measurements from standardised photographs reflect body height and chest girth after applying minor adjustments. Our results have implications for size estimation of large wild animals in the field, as well as for management in captive settings.     

Determination of body surface area and formulas to estimate body surface area using the alginate method

The purpose of this study was to determine the body surface area (BSA) based on the alginate method, to derive formulae for estimating BSA, and to compare the error of the present formula to previous formulas obtained from other countries. We directly measured the entire body surface area of 34 males (20-60 years old, 158.5-187.5 cm in height, 48.5-103.1 kg in body weight) and 31 females (20-63 years old, 140.6-173.1 cm, 36.8-106.1 kg) using alginate. The measurements showed that the BSA had a mean of 18,339 cm(2) (15,416-22,753 cm(2)) for males, and 16,452 cm(2) (12,825-22,025 cm(2)) for females. Based on these measurements, a regression model to estimate BSA was derived: Estimated BSA (cm(2))=73.31 Height (cm)(0.725) x Weight (kg)(0.425) (r(2)=0.999). The mean error of the formula was -0.1%, and did not show any significant difference by gender or body shape. When applied to the datasets (n=506) composed of various races (Caucasians, Africans, and Asians), the mean error of the formula was 0.4% and was smaller than that of DuBois & DuBois's, Gehan & George's, and Mosteller's formulas when applied to the same datasets. The errors of the three previous formulas were also within 2%. Overall, formulas based on the DuBois exponent (Weight(0.425) Height (0.725)) did not show any tendency of overestimation or underestimation by body shape, but other BSA-formulae showed differences by body shape. The present BSA formula has shown good accuracy in Korean adults of all weight categories compared to traditional formulas.     

Thyroid volume as measured by ultrasonography in patients With type 1 diabetes mellitus without thyroid dysfunction.

The aim of this cross-sectional study was to assess and compare thyroid volume and its derminants in a cohort of type 1 diabetes mellitus (DM1) and compare the results to a healthy control group. We studied 65 DM1 patients treated with an intensive insulin regimen and 65 matched controls. In all participants we evaluated weight, height, BMI, waist-hip ratio, body surface area and body composition variables determined by using a bioelectrical impedance analyser. Thyroid size was estimated by ultrasonography. We determined basal TSH, anti-thyroid antibodies and urinary iodine excretion. Body weight, height, BMI and body surface area were similar in DM1 patients and in controls. Fat-free mass was higher in both male and female DM1 patients than in controls (64.4 +/- 6.9 vs. 60.4 +/- 8.2 kg, p=0.03 and 48.3 +/- 5.7 vs. 45.4 +/- 6, p=0.04, respectively), and fat mass was lower in male DM1 patients than in controls (9.7 +/- 7 vs. 14.2 +/- 8.1 kg, p=0.01). Thyroid volume was greater in both male and female DM1 patients than in controls (11.12 +/- 2.87 vs. 9.63 +/- 2.27 ml, p=0.0001 and 9.5 +/- 2.3 vs. 7.7 +/- 2 ml, p=0.002, respectively). Urinary iodine excretion was similar in the two groups. In both DM1 patients and controls, thyroid volume correlated with weight, height, BMI, waist-hip ratio, body surface area, fat-free mass and the multivariate linear regression analysis with thyroid volume as the dependent variable showed that fat-free mass in either group was the only significant determinant of thyroid volume. We conclude that DM1 patients had larger thyroid volume compared with healthy controls with similar anthropometry; body composition is different in DM1 patients and that the anthropometric and body composition variables, especially fat-free mass and body surface area, predict thyroid volume either in DM1 patients or in healthy controls.     

Development of allometric relations for three mangrove species in South Florida for use in the Greater Everglades Ecosystem restoration

Mathematical relations that use easily measured variables to predict difficult-to-measure variables are important to resource managers. In this paper we develop allometric relations to predict total aboveground biomass and individual components of biomass (e.g., leaves, stems, branches) for three species of mangroves for Everglades National Park, Florida, USA. The Greater Everglades Ecosystem is currently the subject of a 7.8-billion-dollar restoration program sponsored by federal, state, and local agencies. Biomass and production of mangroves are being used as a measure of restoration success. A technique for rapid determination of biomass over large areas is required. We felled 32 mangrove trees and separated each plant into leaves, stems, branches, and for Rhizophora mangle L., prop roots. Wet weights were measured in the field and subsamples returned to the laboratory for determination of wet-to-dry weight conversion factors. The diameter at breast height (DBH) and stem height were also measured. Allometric equations were developed for each species for total biomass and components of biomass. We compared our equations with those from the same, or similar, species from elsewhere in the world. Our equations explained ≥93% of the variance in total dry weight using DBH. DBH is a better predictor of dry weight than is stem height and DBH is much easier to measure. Furthermore, our results indicate that there are biogeographic differences in allometric relations between regions. For a given DBH, stems of all three species have less mass in Florida than stems from elsewhere in the world.     

Total lung capacity of baboons and humans determined by planimetry of radiographs.

Total lung capacity and radiographic lung area of 25 young and 7 aged baboons (Papio cynocephalus) and seven nonsmoking young adult men were measured. For all subjects, total lung capacity and radiographic lung area raised to the 3/2 power were shown to be highly correlated (r = 0.995). The regression equation for this relationship was total lung capacity (ml) = 78 + 0.234 x radiographic lung area (1.5) (cm2). A more useful regression equation for predicting values of total lung capacity was found to be log total lung capacity = -0.3819 + 1.4153 x log radiographic lung area (r = 0.993), because the standard error of estimate remains a constant percentage of Y values (+/- 12%). Total lung capacity and radiographic lung area were also highly correlated with height, weight and arm span of young baboons and men (r greater than 0.92), but the lungs of aged baboons were disproportionately larger.     

Specificity of training modalities on upper-body one repetition maximum performance: free weights vs. hammer strength equipment

The purpose of this study was to determine whether a relationship exists between 1-repetition maximum (1RM) performed on hammer strength (HS) machines compared to free weights (FWs) and also to develop regression equations that can accurately predict 1RM when switching from exercise modality to another. Thirty-one trained male subjects performed 1-RM lifts (1RM's) on 3 HS externally loaded machines and 3 comparable FW exercises. Subjects performed 2 1RM tests during each laboratory session, with at least 48-72 hours of recovery between each. One repetition maximum data were used to (a) determine the relationship between 1RM performed on HS vs. FW and (b) to develop regression equations that can accurately predict 1RM's when switching from 1 exercise modality to another. Statistics revealed significant differences (p < 0.05) between 1RM's performed on the HS equipment as compared to its corresponding (FW) exercise. For all exercises, 1RM's were significantly greater on the HS equipment. Regression equations were developed for all exercises, except when predicting the HS shoulder press and the HS preacher curls from their free weight counterparts, where no variables existed that could significantly predict their respective 1RM's. As 1 RMs were significantly greater when using the HS equipment compared to when using FWs, those transitioning from HS exercise to FW exercise should exercise caution.     

Longitudinal analysis of the dynamics and risk of coronary heart disease in the Framingham Study.

Statistical methods designed specifically for the analysis of chronic disease incidence and progression in longitudinal studies are presented. These method model the risk of acute phases of chronic disease separately from the temporal change in risk variables. This could be accomplished because, under a specific biological model of the disease mechanism, the problems of estimating the risk of an acute event and of predicting the change in risk variables are independent. Specifically, a quadratic equation relating risk variable values to chronic disease risk and a system of linear equations predicting future risk variable values from present values may beestimated separately. Taken together, they utilize the full information available in a longitudinal study on the temporal dimension of chronic disease progression. In addition, the model is found to possess a number of attractive statistical and theoretical properties. These methods are applied to longitudinal data from the Framingham Study on coronary heart disease (CHD) in males. A quadratic function relating the risk of a CHD event to selected risk variables (age, and the natural logarithms of serum cholesterol, uric acid, diastolic blood pressure and pulse pressure) was estimated from measurements made at four points equally spaced in time (two years) with a further morbidity follow-up at a fifth point. The risk function was found to predict CHD risk accurately. It showed that, apart from the linear effects of the risk variables, cohort effects, quadratic effects and interaction effects were important predictors of CHD risk. The linear regression equations used to predict future risk variable values showed that there was an intricate network of cross-temporal associations. Study of the two types of equations jointly show that putative risk variables could affect the risk of CHD incidence both directly, by being associated with higher levels of risk, and indirectly, by causing other risk variable values to change with time. The results led us to identify several different roles that risk variables might play in CHD incidence.     

Growth and productivity assessment of Casuarina glauca Sieb. ex. Spreng on sodic soil sites

Casuarina glauca is an introduced tree species to India. It is one the few species that can grow successfully in salt effected sites. C. glauca was investigated for biomass production at highly sodic soil sites (pH 8.6-10.5); it was found to be promising in terms of growth and productivity. Average height of plants in an 8-yr-old trial of Casuarina glauca was 1033.3+/-270 cm, however diameter at breast height (dbh) remained at 8.59+/-2.0 cm with a basal area of 6.68+/-1.6 cm2 per plant. High plant survival and establishment (75%) indicate its potential for afforestation of degraded soil sites. Linear regression equations (Y=a+bx) were developed to predict biomass of standing stocks defining relationships between growth parameters (x) as independent variable and productivity (Y) as dependent variable. Both uni-factor equations based on one independent variable (height or diameter alone), and multifactors involving both height and diameter together (d2h) were derived to predict biomass of different plant components. Coefficient of correlation and regression coefficients were found to be highly significant (p<0.001) in all the equations irrespective of independent variable such as plant height, diameter or both (d2h). There were marginal differences in r2 value (0.78-0.8) among equations derived by using d2 or d2h as independent variables. Height alone had relatively poor functional correlation with yield (r2=0.45). Accordingly, uni-factor linear equations with diameter (d2) were used for computing stand biomass with reasonably good accuracy. At the age of 8 years, stand productivity was 68.2 t ha-1 (oven dry biomass) out of which relatively a very high proportion (80.3%) of biomass was allocated to stem wood (54.8 t ha-1). Both branch wood (8.4 t ha-1) and leaves (5 t ha-1) contributed marginally. Casuarina glauca can be recommended as a promising species for biomass production on sodic soil sites as is evident from its performance.     

Prediction of normal values for lactate threshold estimated by gas exchange in men and women

Lactate threshold (LT) is an index of exercise capacity and can be estimated from the gas exchange consequences of a metabolic acidosis (LT_GE). In recent years, it has emerged as a diagnostic tool in the evaluation of subjects with exercise limitation. The purpose of this study was to develop LT_GE prediction equations on a relatively large sample of adults and to cross-validate each equation. A total of 204 healthy, sedentary, nonsmoking subjects (103 men and 101 women), aged 20–70 years, underwent graded exercise testing on a cycle ergometer. The V-slope technique was used to detect LT_GE as the oxygen uptake (V˙O₂) at the breakpoint of the carbon dioxide output versus V˙O₂ relationship. Multiple linear regression was used to develop 12 equations with combinations of the following predictor variables: age, height, body mass, and fat-free mass. Eight of the equations are gender-specific and four are generalized with gender as a dummy variable. The equations were cross-validated using the predicted residual sum of squares (PRESS) method. The results demonstrate that the equations had relatively high multiple correlations (0.577–0.863) and low standard errors of the estimate (0.123–0.228 1 · min⁻¹). The PRESS method demonstrated that the equations are generalizable, i.e., can be used in future studies without a significant loss of accuracy. Since we tested only healthy, sedentary subjects, our equations can be used to predict the lower limit of normal for a given subject. Using individual data for healthy and diseased subjects from the literature, we found that our gender-specific equations rarely miscategorized subjects unless they were obese and mass was a predictor variable. We conclude that our equations provide accurate predictions of normal values for LT_GE and that they are generalizable to other subject populations. Accepted: 13 February 1997     

正常人左心室功能指标的参考值及其预计公式的初步研究报告*

目的: 当前评估左心室容量和功能仍常用正常值范围,个体化分析也仅使用体表面积进行校正。尚缺少个体化因素相关的大样本参考值和预计公式。方法: 本研究纳入美国加州洛杉矶县南湾地区1200名健康志愿者,其中男807女393,年龄20岁-94岁,心脏CT造影（CTA）,经过高精度三维成像技术处理,计算左心室容积在收缩和舒张过程中的连续动态变化,测定左心室（LV）容量和功能指标：舒张末期容积（EDV)、收缩末期容积(ESV)、每搏输出量(SV)、射血分数(EF)和心输出量(CO)。将以上指标与一般特征指标进行多因素相关分析,以探索正常人预计值计算公式。结果: 男性除LVEF小于女性外（P<0.001）,其余各指标均大于女性（P<0.001）。多元线性回归分析提示, 性别、年龄、身高和体质量均为EDV、ESV、SV的独立影响因子(P<0.001); 而CO仅受年龄、性别、体质量显著影响(P<0.001),但与身高无关(P>0.05)。CO的预测公式CO (L·min^-1)= 6.963+0.446(Male) -0.037×年龄(yr)+0.013×体质量(kg)。结论: 性别、年龄、身高、体质量均影响左心室容量和功能,建立预测值计算公式,对心血管疾病的无创评估和个体化精准医疗具有重要参考价值。     

Body surface area prediction in normal-weight and obese patients

None of the equations frequently used to predict body surface area (BSA) has been validated for obese patients. We applied the principles of body size scaling to derive an improved equation predicting BSA solely from a patient's weight. Forty-five patients weighing from 51.3 to 248.6 kg had their height and weight measured on a calibrated scale and their BSA calculated by a geometric method. Data were combined with a large series of published BSA estimates. BSA prediction with the commonly used Du Bois equation underestimated BSA in obese patients by as much as 20%. The equation we derived to relate BSA to body weight was a power function: BSA (m(2)) = 0.1173 x Wt (kg)(0.6466). Below 10 kg, this equation deviated significantly from the BSA vs. body weight curve, necessitating a different set of coefficients: BSA (m(2)) = 0.1037 x Wt (kg)(0.6724). Covariance of height and weight for patients weighing <80 kg reduced the Du Bois BSA-predicting equation to a power function, explaining why it provides good BSA predictions for normal-size patients but fails with obesity.     

Prediction of body density using A-mode ultrasonoscope in Japanese physical education major college students

The purpose of the present study was to examine the distribution of subcutaneous fat and to derive several equations to predict body density (BD) using an amplitude modulation type of ultrasonoscope (A-mode ultrasonoscope, FUKUDA FT-100). Subjects were 188 male physical education major college students ranging in age from 18 to 24 years. Fifty subjects who were randomly selected out of the 188 subjects were measured for BD by the underwater weighing technique and were used to derive the equation for estimating the BD. Four points (scapular, triceps, suprailiac, and thigh) of subcutaneous fat which had been commonly selected, height, and weight were measured. The four measurements of fat for the 188 subjects indicated rather small means and small standard deviations respectively. Furthermore, histograms of those measurements tended to show a significant skewness for low values and deviated from the normal probability curve (p less than 0.01). Regarding the means, they were almost all the same except for suprailiac measurements. Suprailiac measurements showed more large values and were distributed rather more widely than the other measurements. Derivations of the multiple regression equations from anthropometric measurements were made using the Wherry-Doolittle test selection method (Clarke & Clarke, 1972). Four measurements (triceps, suprailiac, height, and weight) were selected by the Wherry-Doolittle method.     

Ideal body shape in young Japanese women and assessment of excessive leanness based on allometry

The present study is aimed to clarify the degree of leanness desired by contemporary young Japanese women using questionnaires and to use allometry to define the body weight boundary between the excessively lean and the others for a given height. Questionnaires on ideal body shape were distributed to female college students living in Akita and the suburbs of Tokyo. Data for 578 respondents, aged 18 to 21 years-old, were analyzed. The questionnaire asked the subjects to report their current and ideal body shape and to make a qualitative self-assessment of their weight. On average, the perceived ideal weight was 5.2 kg lower than the current weight. The results also revealed that young women have a tendency to misunderstand their body shape and to regard themselves as heavier than they really were. Meanwhile, we defined leanness as a state of insufficient lean body mass (LBM, kg) in relation to height (Ht, cm). Allometric equation of LBM on Ht and the standard error of estimate (SEE) were calculated as LBM=3.87 x 10(-3) x Ht(1.826) and 1.09, respectively. The LBM boundary between the excessively lean and the others was determined using these values according to a statistical procedure comparing normal and abnormal values. The corresponding total body weight was estimated from the boundary LBM in the literature. Subsequently the body weight boundary for each height was tabulated in order to make young women reconsider weight control. The subjects were asked to assess the body weight boundary for their own height. The boundary values were found to be consistent with the sense of the subjects.     

Validation of submaximal prediction equations for the 1 repetition maximum bench press test on a group of collegiate football players

The purpose of the study was to determine the accuracy of 11 prediction equations in estimating the 1 repetition maximum (1 RM) bench press from repetitions completed by collegiate football players (N = 69) using 225 lb. The demographic variables race, age, height, weight, fat-free weight, and percent body fat were measured to determine whether these variables increased the accuracy of the prediction equations; race was the most frequently selected variable in the regression analyses. The validity of the prediction equations was dependent upon the number of repetitions performed, i.e., validity was higher when fewer repetitions were completed. Explained variability of 1 RM was slightly higher for all 11 equations when demographic variables were included. A new prediction equation was also developed using the number of repetitions performed and the demographic variables height and fat-free weight.     

Determination of esophageal probe insertion length based on standing and sitting height

The present study derives simple formulas for the prediction of optimal insertion length of an esophageal temperature-sensitive probe from the measurements of either standing or sitting height. The formulas assume that the optimal site for an esophageal temperature probe is in the region of the esophagus bounded by the left ventricle and aorta, corresponding to the level of the eighth and ninth thoracic vertebrae (T8 and T9, respectively). An esophageal probe was constructed of polyethylene tubing containing 1-cm segments of alternating radiopaque and nonradiopaque tubing in the distal 20 cm of the probe. The probe was inserted through a nostril into the esophagus of 20 subjects (12 males and 8 females) of various heights (range 163-194.6 cm) and weights (range 52.2-100.8 kg), and lateral chest radiograms were obtained for determination of the insertion length of the probe (L) required to situate the probe in the retrocardiac esophagus. Analysis of the radiograms demonstrated that, at the level of the intervertebral disc between T8 and T9, the probe was below the tracheal bifurcation and close to the left ventricle. The distance from the nasal flare to this level showed a good correlation with the subject's stretched stature (r2 = 0.71) and sitting height (r2 = 0.86). The following equations were derived to predict the placement of the esophageal probe at the T8/T9 level based on standing height: L (CM) = 0.228 x (standing height) - 0.194, and sitting height: L (cm) = 0.479 x (sitting height) - 4.44.     

Prediction of body composition in habitually active middle-aged men.

In 45 physically active men (ages 35-67 yr) who underwent hydrostatic weighing to determine body composition, multiple regression equations were developed for the prediction of body density (D), lean body weight (LBW), fat body weight (FBW), and % fat using selected anthropometric measurements. The prediction accuracy for these parameters using several previously generated anthropometric regression equations was also determined. With equations developed from the present data a substantially higher correlation was obtained between measured and predicted LBW (r = 0.95) than between measured and predicted D (r = 0.85), FBW (r = 0.88), or % fat (r = 0.84). When previously developed equations were applied to the present sample, correlations between measured and predicted values were considerably lower (4-42%) than in the original studies; this reduction was least in the case of LBW. Analysis of previous data indicated that in selected populations total body weight can account for a relatively large fraction of the variance in LBW. LBW may be estimated quite accurately (r greater than or equal to 0.90) in physically active men with one of several regression equations which include total body weight as an independent variable.     

Prediction of body density in young and middle-aged women.

The purpose of this investigation was to predict body density of young and middle-aged women and to determine if the use of a greater variety of variables, particularly those for fat in the bust and hip regions, increases the predictability of body density. Body density determined by the hydrostatic technique (dependent variable) was obtained from 83 volunteer young women and 60 middle-aged women ranging from 18 to 22 and 33 to 50 yr of age, respectively. Independent variables included 8 skinfold, 13 girth, and 7 diameter measures; age; height; weight; and bra and cup sizes. Mean body density for young women was 1.043 g/ml (SD plus or minus 0.014) and percent fat, 24.8 (SD plus or minus 6.4); 1.031 g/ml (SD plus or minus 0.015) and 29.8% (SD plus or minus 6.7) for middle aged subjects. Percent fat was calculated by the formula of Siri. Factor analysis was used to examine the dimensions measured by the independent variables as a function of age. A multiple regression model was used to develop predictions of body density from the independent variables. The best combination of four variables for predicting body density was skinfold thigh, skinfold suprailiac, cup size, skinfold suprailiac, girth waist, and skinfold thigh (R = 0.89) for middle-aged women. The data showed that the highest predictons were found by using combinations of skinfold, girth, and diameter variables; cup size also supported the need for different regression equations for different age groups.     

Reference values of pulmonary diffusing capacity for nitric oxide in an adult population.

Our objective was to create reference values for single-breath DLNO based on a sample of non-smoking healthy males and females using a short breath-hold time. The sample included 130 individuals varied in age (18-85 yr), height (149-190 cm), and weight (49.4-102.6 kg). The subjects performed single-breath-hold maneuvers at rest inhaling 41 +/- 6 ppm NO and a standard diffusion mixture. The breath-hold time was 5.5 +/ -0.6 s. Multiple linear regression with backward elimination of the independent variables age, weight, gender, and either measured lung volume (called alveolar volume or VA) or height revealed specific prediction equations for DLNO. Inserting VA instead of height into the regression equation determined how much of an abnormality of DLNO was due to gas exchange versus low lung volume. The predicted DLNO adjusted for lung volume (ml/min/mmHg) = DLNO = 73.1 + 17.26 x (VA)+17.56 x (gender) - 1.0 x (age). The predicted DLNO unadjusted for lung volume (ml/min/mmHg) = -20.1 + 1.167 x (height)+31.81 x (gender) - 1.21 x (age). For gender, 1 = males, 0 = females; VA = liters; height = cm. Age, gender and VA (lung volume) were the best predictors of DLNO and DLCO. Weight was not a good independent predictor of DLNO or DLCO. When normalizing for height and age, women have 650 ml lower forced vital capacity, 660 ml lower VA, and a 6 and 32 ml/min/mmHg lower DLCO and DLNO, respectively, compared to men. Normalizing for lung volume and age, women have, on average, a 3.2 and 18 ml/min/mmHg lower DLCO and DLNO, respectively, compared to men.     

New insights into body composition assessment in obese women.

During treatment of patients with non-insulin-dependent diabetes mellitus, there may be marked body weight loss. Therefore, body composition should be monitored to check for a decrease in fat mass alone, without an excessive decrease of both fat-free mass and total body water. Accordingly, it is useful to monitor the hydration of these patients. One method that allows us to check the status of body hydration is the multifrequency bioelectric impedance analysis (MFBIA). It makes use of formulas that estimate total body water on the basis of the concept that the human body may be approximated to a cylinder of length equal to body height. In normal subjects body water estimates are sufficiently accurate, but in obese subjects the true hydration status may be overestimated. In this report, we describe the accuracy of mathematical models previously described in the literature, and correct for the overestimation of total body water in obese subjects by means of a new equation based on a new model. The coefficients for each model have been recalculated by the weighing of our sample in order to test the accuracy of estimates obtained with the equations. This new model includes both body volume and two impedances at appropriate frequencies useful for identifying two terms strictly related to extra- and intra-cellular water. The new formulas do not include body weight, but they include the body volume, a parameter more closely related to the biophysical reference model. Fifty-five overweight females, body mass index ranging from 26.8 to 50.2 kg/m2, were enrolled in the study. The proposed equations, taking advantage of two impedance values at appropriate frequencies, better predict total body water in obese women. This was particularly evident when the results obtained with the multifrequency bioelectric impedance analysis and deuterium isotopic oxide dilution method were compared. Although this last method is considered the "gold standard," it is not suitable for use in routine clinical practice. In conclusion, evaluation of total body composition by means of bioelectric impedance analysis might be included in programs for the prevention of non-insulin-dependent diabetes and for monitoring weight loss during overt pathology.