A. Andreoli

Effects of different sports on bone density and muscle mass in highly trained athletes

PURPOSE It is known that participating in sports can have a beneficial effect on bone mass. However, it is not well established which sport is more beneficial for increased bone mineral density (BMD) and appendicular muscle mass (AMM). This study investigated the effects of different high-intensity activities on BMD and AMM in highly trained athletes. MATERIALS AND METHODS Sixty-two male subjects aged 18--25 yr participated in the study. The sample included judo (J; N = 21), karate (K; N = 14), and water polo (W; N = 24) athletes who all competed at national and international level. Twelve age-matched nonathletic individuals served as the control group (C). All athletes exercised regularly for at least 3 h x d(-1), 6 d x wk(-1). Segmental, total BMD, and AMM were measured with a dual-energy x-ray (DXA) absorptiometry (Lunar Corp., Madison, WI). DXA analysis also includes bone mineral content (BMC) and fat and lean masses. RESULTS Total BMD(C) was significantly lower (mean +/- SD: 1.27 +/- 0.06 g x cm(-2), P < 0.05) than either judo or karate athletes (total BMD(J) (1.4 +/- 0.06 g x cm(-2)) and total BMD(K) (1.36 +/- 0.08 g x cm(-2))) but not different from the W athletes (total BMD(W) (1.31 +/- 0.09 g x cm(-2))). AMM was significantly lower in the C group compared with the three athletic groups (P < 0.05). Fat mass was higher in the W versus J and K athletes but not different from the C group (P < 0.05). CONCLUSIONS This cross-sectional study has shown that athletes, especially those engaged in high-impact sports, have significantly higher total BMD and AMM than controls. These results suggest that the type of sport activity may be an important factor in achieving a high peak bone mass and reducing osteoporosis risk.

The validity of predicted body fat percentage from body mass index and from impedance in samples of five European populations

Objectives: To test and compare the validity of a body mass index (BMI)-based prediction equation and an impedance-based prediction equation for body fat percentage among various European population groups.Design: Cross-sectional observational study.Settings: The study was performed in five different European centres: Maastricht and Wageningen (The Netherlands), Milan and Rome (Italy) and Tampere (Finland), where body composition studies are routinely performed.Subjects: A total of 234 females and 182 males, aged 18–70 y, BMI 17.0–41.9 kg/m2.Methods: The reference method for body fat percentage (BF%REF) was either dual-energy X-ray absorptiometry (DXA) or densitometry (underwater weighing). Body fat percentage (BF%) was also predicted from BMI, age and sex (BF%BMI) or with a hand-held impedance analyser that uses in addition to arm impedance weight, height, age and sex as predictors (BF%IMP).Results: The overall mean (±s.e.) bias (measured minus predicted) for BF%BMI was 0.2±0.3 (NS) and−0.7±0.3 (NS) in females and males, respectively. The bias of BF%IMP was 0.2±0.2 (NS) and 1.0±0.4 (P<0.01) for females and males, respectively. There were significant differences in biases among the centres. The biases were correlated with level of BF% and with age. After correction for differences in age and BF% between the centres the bias of BF%BMI was not significantly different from zero in each centre and was not different among the centres anymore. The bias of BF%IMP decreased after correction and was significant from zero and significant from the other centres only in males from Tampere. Generally, individual biases can be high, leading to a considerably misclassification of obesity. The individual misclassification was generally higher with the BMI-based prediction.Conclusions: The prediction formulas give generally good estimates of BF% on a group level in the five population samples, except for the males from Tampere. More comparative studies should be conducted to get better insight in the generalisation of prediction methods and formulas. Individual results and classifications have to be interpreted with caution.European Journal of Clinical Nutrition (2001) 55, 973–979

Review article: breath testing for human liver function assessment

Carbon‐labelled breath tests were proposed as tools for the evaluation of human liver function 30 years ago, but have never become part of clinical routine. One reason for this is the complex role of the liver in metabolic regulation, making it difficult to provide essential information for the management of patients with liver disease with a single test and to satisfy the hepatology community. As a result, a battery of breath tests have been developed. Depending on the test compound administered, different metabolic pathways (microsomal, cytosolic, mitochondrial) can be examined. Most available data come from microsomal function tests, whilst information about cytosolic and mitochondrial liver function is more limited. However, breath tests have shown promise in some studies, in particular to predict the outcome of patients with chronic liver disease or to monitor hepatic function after treatment. Whilst we await new substrates that can be used to measure liver function in a more valid manner, and large prospective studies to assess the usefulness of available test compounds, the aim of this review is to describe how far we have come in this controversial and unresolved issue.

Body composition assessment by dual-energy X-ray absorptiometry (DXA)

Body composition (BC) assessment is indispensable to evaluate nutritional status and thus health, both at the population and individual level, and to assess the efficacy of primary and secondary preventive nutritional strategies. Changes in BC, including the regional distribution of body fat, largely occur during pubertal transition, with marked differences between genders. They may, however, also occur in the elderly, who experience significant changes in the ratio between body fat and muscle with aging. The development and implementation of more sophisticated techniques (e.g. BC assessment at the molecular and atomic levels) could provide a major contribution to determining BC at different levels. This review discusses the application of dual-energy X-ray absorptiometry (DXA) on BC determination, given that DXA has the potential to provide overall and regional assessment of BC in terms of fat, lean mass and bone. DXA is widely used in many clinical settings primarily diagnosis osteoporosis. This article describes the use of whole-body DXA in assessing BC in patients with chronic diseases (e.g. metabolic syndrome) as well as in different sport activities to evaluate the effects of exercise.RiassuntoLa valutazione della composizione corporea, da qui in avanti denominata con il termine anglosassone di body composition (BC), è un metodo essenziale per analizzare lo stato di salute in termini nutrizionali, sia a livello di popolazione sia a livello individuale, come pure per indagare l’efficacia delle strategie nutrizionali preventive primarie e secondarie. I cambiamenti della BC, inclusa la distribuzione distrettuale del grasso corporeo, avvengono in larga parte durante il periodo puberale e si diversificano in base al sesso. Questi tuttavia possono manifestarsi anche nel soggetto anziano, per il quale il trascorrere degli anni può causare significativi cambiamenti nel rapporto tra grasso corporeo e muscolo. Per misurare la composizione corporea esistono numerose tecniche; alcune semplici, ma con margini di errore ancora elevati, altre invece costose e sofisticate (come per esempio la valutazione a livello atomico e molecolare della BC) ma più affidabili nel rilevamento dei risultati a vari livelli. Questa revisione della letteratura riguarda l’applicazione della tecnica dual-Energy X-ray absorptiometry (DXA) per la determinazione della composizione corporea, in quanto tale metodica permette di misurare sia in maniera totale che segmentale, per singoli distretti, i vari componenti quali: massa grassa, massa magra e tessuto osseo. Attualmente la DXA è principalmente usata per fare diagnosi di osteoporosi e/o per controllare la risposta alla terapia farmacologia. In questo articolo verranno descritte le altre possibili indicazioni, tra cui lo studio della BC nei pazienti con sindromi metaboliche croniche e l’applicazione in condizioni fisiologiche, quali per esempio nello sportivo, per valutare l’effetto dell’esercizio fisico sulla massa corporea.

How fat is obese

Abstract.The aim of the study was a comparison between body fat measurements and body mass index. We analyzed the data of 890 subjects, 596 females and 294 males, ranging in age from 18 to 83 years, in body mass index (BMI) from 14 to 54 kg/m2, and in body fat percentage (BF%) from 4% to 57%. A considerable number of subjects, both males and females, could not be classified as obese based on their BMI alone. Such a misclassification is undesirable, especially in general practice, and it calls for diagnostic criteria other than the BMI alone to be used for obesity.

Measured and predicted resting metabolic rate in Italian males and females, aged 18-59 y.

Objectives: To determine the resting metabolic rate in a sample of the Italian population, and to evaluate the validity of predictive equations for resting metabolic rate (RMR) from the literature in normal and obese subjects.Design: Cross-sectional observational study.Settings: Department of Human Physiology and Nutrition, University ‘Tor Vergata’, Rome.Subjects: A total of 320 healthy subjects, 127 males and 193 females, aged 18–59 y.Methods: Weight, height and resting metabolic rate by indirect calorimetry were measured. Resting metabolic rate was also predicted using equations from the literature.Results: Resting metabolic rate (mean±s.d.) in normal weight subjects was 7983±1007 kJ/24 h (males) and 6127±907 kJ/24 h (females). Measured RMR and predicted RMR values using various equations from the literature were significantly different in males and females, except for the Harris–Benedict equation and the Schofield equations. Also, in overweight and obese subjects the prediction error was generally larger compared to normal-weight subjects for all formulas except for the Harris–Benedict and Schofield formulas. In overweight and obese males but not in females, RMR was lower than in normal-weight subjects after correcting for weight and age differences. Stepwise multiple regression of resting metabolic rate against weight, height and age in males and females did not reveal a prediction formula with a lower prediction error than the Harris–Benedict or Schofield formulas and thus was not further explored.Conclusions: The Harris–Benedict formula and the Schofield formula provide a valid estimation of resting metabolic rate at a group level in both normal-weight and overweight Italians. However, the individual error can be so high that for individual use a measured value has to be preferred over an estimated value.European Journal of Clinical Nutrition (2001) 55, 208–214

Predicting fat-free mass in children using bioimpedance analysis

Abstract.Body composition assessment is a useful procedure for the study of nutritional status and water distribution. In adults, it is a predictor of morbidity and mortality, since body fatness is associated with risk factors for cardiovascular disease. Bioelectric impedance analysis (BIA) is a simple, safe, and inexpensive method for assessment of body composition both in pediatric and adult subjects. The aim of our study was to validate the impedance index, ZI (H2/Z, height in cm2/impedance), as a predictor factor of fatfree mass (FFM) and fat mass (FM) in a sample (n=75) of normal children. Dual-energy X-ray absorptiometry (DXA) was chosen as reference method. Despite some minor bias, DXAis considerably less expensive and easier to administer in pediatric subjects than other established gold standard reference methods for assessing body composition. ZI values were highly correlated with FFM measured with DXA. The following equations were obtained from the regression analysis: (a) male subjects, FFMDXA=0.6375 (ZI)+5.9913, r2=0.897, p<0.0001; (b) female subjects, FFMDXA=0.7597 (ZI)+ 3.5853, r2=0.903, p<0.0001. These data support the notion that BIA alone can be used as a surrogate to measure FFM in a pediatric sample.

Determination of intracellular water by multifrequency bioelectrical impedance.

Body composition was measured in 57 healthy males by 40K measurements and by multifrequency bioelectrical impedance. Intracellular resistance (Ricf) was calculated from the impedance values using the Cole-Cole model. From total body potassium, intracellular water (ICW) was calculated. In addition, in 14 subjects, total body water (TBW) and extracellular water (ECW) was measured using deuterium oxide dilution and bromide dilution, respectively. Prediction formulas from the literature from impedance at different frequencies were used to predict TBW and ECW, and ICW was calculated as the difference of predicted TBW and ECW. Predicted and measured values of TBW, ECW and ICW did not always show the same values as measured. Generally the ICW from potassium was well correlated with calculated ICW from impedance values, correlation coefficients varying from 0.68 to 0.79, depending on the used prediction formula. From the impedance index H2/Ricf, body weight and age, ICW from potassium was predicted with stepwise multiple regression. The prediction formula was ICW = 0.37065.H2/Ricf - 0.132.age + 0.105.weight + 12.2. The prediction error was 1.9 kg and the explained variance 0.69. The residuals of this prediction formula were dependent on the level of ICW as measured by potassium. The same phenomenon was observed when ICW was calculated as the difference of predicted TBW and ECW. The results show that multifrequency impedance is able to predict ICW, however, the prediction is influenced by body water distribution.

Fat-free mass by bioelectrical impedance vs dual-energy X-ray absorptiometry (DXA).

Body composition (BC) assessment is a useful tool for a careful evaluation of nutrition status. Bioelectrical impedance analysis (BIA) is a safe, low-cost and reliable method for BC assessment. For epidemiological and clinical research in children, paediatric-age specific formula for fat-free mass (FFM) prediction from BIA is needed. Thus, in 35 children (age 7.7-13.0 years) with different levels of body fatness (relative weight for age 70.6-133.8%), FFM was calculated from dual-energy X-ray absorptiometry (DXA). A regression equation from BIA and DXA data was elaborated. The impedance index (ZI = height2/bioelectrical impedance) was the strongest predictor of FFM, explaining 89% of its variance. However, the variance increased to 96% when body weight was added with ZI in the regression model. No variable, including sex and age, contributed to the prediction of FFM in the presence of ZI and body weight. The regression formula [FFM = 2.330 + 0.588 ZI (cm2/omega) + 0.211 Weight (kg) (r = 0.96, SEE = 1.0 kg)], allows a reliable prediction of FFM in children from body impedance values.

Whole body and regional body composition analysis by dual-energy X-ray absorptiometry in cirrhotic patients

Objectives: To compare whole body and regional (arms, legs and trunk) fat mass, fat-free mineral-free mass, bone mineral content and bone mineral density, measured by DXA, in cirrhotic patients and age, sex and BMI matched healthy volunteers.Design: Cross-sectional study.Setting: Two medical research institutions.Subjects: Twenty-two non ascitic cirrhotic patients and 16 age, sex and BMI matched healthy volunteers.Interventions: The Lunar DPX whole-body X-ray densitometer with Lunar software version 3.6z (Lunar Radiation Corp., Madison WI, USA) was used. Regional analysis was performed on the arms, legs, trunk and head.Results: Compared to controls, cirrhotic patients showed a significant reduction in percentage body fat. When differentiated by gender, however, the reduction in percentage body fat was evident in female cirrhotics only, particularly in the trunk. In male cirrhotic patients fat-free mineral-free mass was reduced in absolute terms in the whole body and the limbs. For both genders and in each body segment bone mineral content and density were reduced in cirrhotics compared to controls. In cirrhotic patients bone mineral density was significantly correlated to both fat-free, mineral-free mass (r=0.85; P<0.001) and to the Physical Activity Index (r=0.52; P<0.01).Conclusions: Two different patterns of soft tissue loss may be found in cirrhotic patients: in women lean tissue is maintained while fat stores are reduced, as in early starvation; in men lean tissue is reduced, as seen under conditions of stress. Moreover, factors influencing lean body mass, such as nutritional depletion and physical inactivity, may contribute to the reduction of bone density frequently observed in cirrhotic patients.Sponsorship: This work has been funded by the University of Rome, ‘La Sapienza’ research grant MURST 60%, 1995.