Print version ISSN 1517-8692
Rev Bras Med Esporte vol.10 no.3 Niterói May/June 2004
Area de sección transversa del brazo: implicaciones técnicas y aplicaciones para avaliación de la composición corporal y de la fuerza dinámica máxima
Fernando A.M.S. Pompeu; Daniele Gabriel; Bianca Gama Pena; Pedro Ribeiro
Exercise Physiology Laboratory (LABOFISE) - Department of Biosciences and Physical Activity - Rio de Janeiro Federal University (UFRJ) - Rio de Janeiro
Arm muscular tissue and fat ring areas can be evaluated by anthropometric measures. The objective of this study was to investigate the application of one technique that infers these areas to estimate body adiposity and the maximal strength of upper limbs and trunk, as well as its objectivity. For that, a sample of 40 healthy men (25 ± 6 years; 72.6 ± 9.4 kg) was divided in two groups: VI (n = 30) internal validation and VE (n = 10) external validation. It was determined to VI the muscle area (AMB), fat absolute area (AGB) and fat percentile upper-arm area (APB) using the values of circumference and triceps skinfold, as well as the sum of seven and eight skinfold thickness (S8DC) and the maximal weight lifted in bench press (1-RM) by two evaluators separately (A and B). In VE only AMB and 1-RM were obtained. Multiple and simple regression analyses and Student t-test were applied (a < 0.05). The variance of S8DC was explained in 93% (EPE = 14.6 mm) from AGB and weight, the AMB explained in 66% (EPE = 9 kg) of the 1-RM variance by itself and there was no significant difference between the maximal weight measured and predicted in VE group. Satisfactory intraclass correlations between the evaluators to AMB (ICC = 0.99), AGB (ICC = 0.96) and ATB (ICC = 0.99) were also found. Therefore it may be concluded that the anthropometric technique that infers muscle and fat upper-arm areas can be used with good agreement between evaluators to estimate body adiposity and upper limbs and trunk strength.
Key words: Upper-arm muscle area. Upper-arm fat percentile area. Body adiposity. Limbs and trunk maximal strength. Bench press.
del tejido muscular (AMB) y del de grosor del brazo (AGB),
pueden ser estimadas por medidas antropométricas.
OBJETIVO: Investigar la validación de el error inter-testeo de la antropometría para inferencia del AMB y del AGB. Secundariamente, se estudió la previsión de la fuerza de los miembros superiores y del tronco a través de la AMB.
METODOS: Fueron voluntarios para este estudio 40 jóvenes masculinos (25 ± 6 años; 72,6 ± 9,4 kg), divididos aleatoriamente en los grupos de validación interna (VI, n = 30) y de validación externa (VE, n = 10). Se determinó para VI, a través de conceptos geométricos, el área total del brazo (ATB), AMB, AGB y el área porcentual de gordura de el brazo. La sumatoria de ocho pliegues cutáneos (SDC8) fue empleado como índice de la adiposidad corporal. La fuerza de los miembros superiores y del e tronco fue medida a través de la carga máxima alcanzada del ejercicio supino recto libre (1-RM). Las medidas antropométricas fueron realizadas por dos evaluadores independientes. Los datos fueron tratados por medio del análisis de regresión, con coeficiente de correlación intraclase (ICC) y el test t de Student apareado (a < 0,05).
RESULTADOS: La varianza de SDC8 puede ser explicada en un 93% (EPE = 14,6 mm) a partir de AGB y del peso corporal. La AMB se explico en 66,1% (EPE = 9 kg) a 1-RM. No se observó diferencia significativa, para el grupo VE, entre los valores medidos (84,2 ± 16,2 kg) y predecidos (78,4 ± 14,2 kg) de 1-RM. Se observó poca variación entre los evaluadores para AMB (ICC = 0,99), AGB (ICC = 0,96) y ATB (ICC = 0,99).
CONCLUSION: La antropometría puede ser empleada para la inferencia de la AMB y del AGB, con buena concordancia entre evaluadores, para estimar la adiposidad coporal y la fuerza de los miembros superiores del tronco.
Palabras-clave: Area muscular del brazo. Area percentual de grasa del brazo. Adiposidad corporal. Fuerza voluntaria máxima. Supino recto.
Several valid and precise techniques(1,2) to infer body composition have been developed. These quantifications depend on complex and expensive laboratorial procedures. In face of these difficulties, the accurate study of body composition is yet infeasible or imprecise for a large number of professional from the sports area. The development of simpler, less expensive and precise techniques becomes necessary for field applications. One of the techniques may be the estimation of the fat tissue and the upper arm muscle mass. These inferences are based on anthropometric measures that enable both the resolution of problems related to body adiposity as well as problems related to muscular strength(2).
Himes et al.(3) suggested that the inference technique of tissue areas is effective for the prediction of the body fat absolute weight; however, this technique would be ineffective for the estimation of the body density and fat percentile. Until this moment, no similar study was performed with the Brazilian population. These studies are necessary, once the anthropometric inferences of the body composition are population-specific. Thus, doubts with regard to the employment validity of the fat percentile upper-arm area for the estimation of the body adiposity still remain.
The inference anthropometric technique of the muscular area and upper-arm fat proceeds from abstractions derived from calculations of concentric circle areas. However, as the arm is not a perfect cylinder, the fat distribution around it is not homogeneous. Thus, this technique may not be satisfactorily precise. Also considering that the variation between evaluators for the skinfold technique on the estimation of the body adiposity may exceed 200%(4), the validity and objectivity study of the arm tissue areas determination technique is relevant.
The accurate estimation of the upper-arm muscular area should present a good relation with the maximal voluntary strength (FVM)(5). For the measure of the FVM, the free bench press exercise may be employed. The maximal load lifted once (1-RM) in this exercise presents high correlation with the same test performed for other muscular groups of trunk and upper limbs(6). In the practical application field, the FVM indirect estimation may minimize the risks of articular and muscular lesions, besides other possible injuries during the performance of maximal load tests in muscular exercise gyms.
This study, therefore, had as objectives: a) to determine and to evaluate the relation between the upper-arm fat area (AGB) and other anthropometric variables such as the body adiposity (S8DC); b) to verify if the inclusion of the biceps skinfold thickness in the calculation of the AGB improves the relation of this area with body adiposity; c) to evaluate the relation between upper-arm muscular area (AMB) and trunk and upper limbs strength; and d) to assess the subjectivity of the technique on the inference of the upper-arm muscular area (AMB) and upper-arm fat area (AGB).
Forty healthy male individuals and students from the Physical Education course (EEFD/UFRJ) who had experience on counter-resistance exercises were volunteers in this study. These individuals were randomly divided into two groups namely: VI (n = 30), internal validation, and VE (n = 10), external validation. Each individual signed a consent form in which all procedures adopted as well as the possible risks were described.
Two independent evaluators (A and B) measured weight, height, skinfold thickness and the right arm circumference. The arm perimeter was measured at the mid point between the acromion and the olecranon, and the individuals remained at orthostatic position with the upper limb extended and relaxed. The chest, biceps, triceps, medium axillary, subscapular, suprailiac, abdominal, anterior crural and sural skinfold thickness were also measured, followed by standardization proposed by Pollock et al.(7). Weight and height were measured according to Gordon et al.(8). For the two last measures, a mechanical balance (FILIZOLA®, Br), for the arm circumference, a metallic measure tape (SANNY®, Br) and for the skinfolds, a skinfold caliper (LANGE®, USA) were used.
The body adiposity was estimated through the sum of skinfold thickness mentioned above. The biceps and triceps (S7DC) skinfolds were not employed in this calculation but only the triceps skinfold thickness (S8DC), when the two first were included in the calculation of the upper-arm segment area.
Calculation of the arm cross-section area (ATB) and its components
The calculation of ATB, AMB, AGB and APB, was based on procedures described by Frisancho(9,10), thus:
ATB = arm total cross-section (cm2)
C = arm circumference (cm)
The arm muscular area (AMB) is calculated as follows:
AMB = arm transversal muscular area (cm2)
C = arm perimeter (cm)
T = triceps skinfold (cm)
The arm fat area (AGB) was calculated as follows:
AGB = arm fat transversal area (cm2)
ATB = arm total transversal area (cm2)
AMB = arm muscular transversal area (cm2)
Finally, the arm fat percentile area (APB) was calculated as follows:
APB = arm fat percentile area (%)
AGB = arm fat transversal area (cm2)
ATB = arm total transversal area (cm2)
In this study, the sum of triceps and biceps skinfold measures were also applied for the determination of AMB. When this procedure was performed, these two measures were not applied in the sum of skinfold measures in order to represent the body adiposity.
Maximal voluntary strength test
The equipments used for the test of a maximal repetition (1-RM) were: a bench with a bar support; other bench for feet support; a long-bar dumbbell (HBL) and free weights (WEIDER®, USA). The last two equipments were previously weighted with the objective of confirming the weight announced by the manufacturer. Prior to the beginning of tests, a specific warm-up in the region to be put in motion was performed. Later, the executions of some repetitions only with the bar were employed for the exercise recognition and corrections. The exercise requested consisted of lifting the HBL held up at the shoulders width with hands in pronation up to the xiphoid process and to elevate it once again up to the elbow complete extension. Three attempts were allowed for the determination of the maximal load, employing the two-minute interval for recovery between attempts.
The descriptive statistics with average and standard deviation and the Student t-test for independent samples were employed for the comparison between groups. For the VE group, the paired Student t-test was employed in order to compare the result of the 1-RM measured to the result predicted from the formula deduced for group VI. For the study of the objectivity of AMB, AGB and ATB and for the inclusion of the biceps skinfold in the method, the multiple and linear regression analysis and the calculation of the coefficient of the intraclass correlation (ICC) were employed. The level of significance adopted in this study was a < 0.05. The calculations for this study were performed with the SPSS for Windows® applicative.
No significant differences between the anthropometric variables and the load of 1-RM of groups VI and VE (tables 1 and 3) were observed. A matrix of correlation for the parameters studied in group VI was presented in table 2. The body adiposity, determined through the eight skinfold thickness, was explained in 84% by the arm fat area (figure 1). This prediction may be improved through the inclusion of the variable weight, what increased the determination correlation up to 88.2% (Eq. 5). The inclusion of other variable did not improve this model significantly.
Applying the equation above (Eq. 5) for data from group VE, non-significant differences were observed between values measured (104.1 ± 31.3 mm) and predicted (95.4 ± 18.7 mm).
The inclusion of the biceps skinfold (AGBTB) did not improve significantly (n = 30, r = 0.90, EPE = 16 mm, S7DC = 23.972 + 3.974AGBTB) the predicting power of the sum of seven skinfold thickness (S7DC). The data predicted for S7DC (106 ± 39 mm) from AGBTB were significantly higher; however, these values presented strong association (r = 0.99).
When data from all subjects (n = 40) measured by two evaluators (A and B) are compared to each other, a non-significant difference was observed for ATB (A = 73.3 ± 12.0 cm2 and B = 72.9 ± 11.8 cm2). This parameter presented good correlation between evaluators (ICC = 0.99, EPE = 3.20 cm2, y = 2.12 + 0.977x). However, a small but significant difference between evaluators for AMB (A = 57.7 ± 9.9 cm2 and B = 57.0 ± 10.3 cm2) was observed. This area (AMB) was also strongly associated between evaluators (ICC = 0.99, EPE = 2.11 cm2, y = 11.208 - 0.110x). Finally, the AGB was not different between evaluators (A = 15.5 ± 8.0 cm2 and B = 15.9 ± 7.2 cm2) and also presented correlated measures (ICC = 0.96, EPE = 8.01 cm2, y = 7.280 - 0.110x).
In figure 2, it is observed that the AMB presented good correlation with the load of 1-RM test in the free bench press exercise for group VI (r = 0.81). The application of the equation presented in this figure for data from group VE did not generate results significantly different between loads measured (84.2 ± 18.3 kg) and predicted (78.8 ± 14.2 kg). These measured and predicted values (1-RM) were well correlated (r = 0.80). The arm muscular area estimated with the inclusion of the biceps skinfold (AMBBT) was significantly smaller (52.7 ± 9.4 cm2). The data derived by both methods (AMB and AMBBT) presented strong correlation (r = 0,97). The predicting capacity of 1-RM from the application of AMBBT was not improved (r = 0.78, EPE = 10.0 kg, 1-RM = 13.488 + 1.293 AMBBT).
The several methods proposed for the estimation of the body adiposity through anthropometric variables generally use diameters, circumferences, height of limbs and skinfold thickness. Despite the large number of anthropometric techniques for the study of the body composition, studies correlating specifically fat area of a segment with body adiposity for the Brazilian population were not found. It seems possible to expect a satisfactory predicting power of body adiposity from technique for the segment study, once the incidence of the gynoid fat distribution is prevalent in women and android in men. This hypothesis may be confirmed through results of the present study, which suggest with good external validity that the AGB combined with weight may be employed in the estimation of the body adiposity. The modification of this technique through the inclusion of the biceps skinfold thickness did not improve the relation mentioned above. The arm muscular area may also be employed for the estimation of the maximal voluntary strength. In the present work, a good external validity for the relation between the load of 1-RM in the free bench press exercise and the AMB was observed. The parameters of the arm fat and muscular areas may be estimated with satisfactory error between evaluators.
The proportion between body tissues is changed with the age(8,9,11). The subcutaneous fat tissue increases with the aging(12,14). Based on this phenomenon, in the second half of the 70th decade, Pollock et al.(15,16) suggested different equations for the prediction of the body density of women and men from different age ranges. In this procedure, the overestimation of the body density values of older individuals was corrected, including the age in years in the regression equation. Jackson et al.(17) and Guedes(18) performed the same correction in their methods and achieved excellent results for the estimation of the body density. More recently(19), a high accuracy on the estimation of the body adiposity was reported from the use of skinfold thickness compared to the method of neutron activation analysis and tritium dilution, when individuals were divided by age ranges. Therefore, it is expected that age plays a relevant role as independent variable. However, in the present study, age has not contributed to improve the relation between AGB and the sum of skinfold thickness. It is observed that the age distribution of subjects from this study was not gaussian, being a positive asymmetry distribution curve (figure 3). Such asymmetry may have reduced the importance of this criterion as predictor.
The estimation error of adiposity through the arm tissue areas method was close to error observed in studies of the body composition. For such comparison, due to the difference on the units adopted (g/mm3, %, kg or cm2), the EPE of the method was divided by the average of the group studied; this allowed announcing the EPE as average percentage. The EPE announced so was similar to EPE found in literature(16,20,21) for estimations of the body composition. Durnin and Womersley(22) and Baumgartner et al.(23) found indexes (EPE) of 22% and 25-30% of the average for the prediction of fat in men, employing the hydrostatic weighting and the bioelectrical impedance techniques, respectively.
Heymsfield et al.(24) studied the possibility of improving the inference technique of AGB, suggested by Frisancho(10,11) and Katch and Hortobagyi(25). Those authors demonstrated that half of the triceps skinfold underestimates the subcutaneous fat tissue radius when determined through computerized tomography. De Koning et al.(26) used the sum of the biceps and triceps skinfolds thickness to infer AMB and AGB determined by anthropometry and computerized tomography and found results similar to results from the first study(24). The last study(26) demonstrated that the area calculated through the anthropometric technique underestimated the measure through tomography. In face of such considerations, and considering the present results, the inclusion of the biceps skinfold measure seems not to improve the method.
The variance of the maximal voluntary strength of trunk and upper limbs was explained in 66% through AMB. Other studies also observed correlation between cross-section muscular area with 1-RM in men(27,28). In a study(25), a correlation of AMB for men and women was proposed, comparing values obtained through computerized tomography to values estimated through anthropometry. Such results are based on the hypothesis that the strength of a given muscle is proportional to its cross-sectional area(5,29,30). Thus, besides the technique error(31), it is likely that the involvement of other muscles in the exercise may have affected the FVM prediction. The specific tension values (TESP) observed in the present study (14.2 ± 1.7 N/cm2) were close to the variation proposed by Enoka(32) (16 - 30 N/cm2) for in situ experiments. The t-test applied between values measured and values predicted of group VE for both the body adiposity and the 1-RM indicates a good external validity. We may, therefore, use the equations expecting acceptable error ranges when individuals similar to those from this study are analyzed. The consideration of the humerus bone area may improve the relations found in the present study. However, the subtraction of 10.0 cm2 as bone area index, as proposed in the study adopted as reference(9,10), will increase the number of calculations with no alterations of regressions here observed.
Objectivity studies include the intra-evaluator error and the validity of the method. In the case of the present technique the intra-evaluator error seems to be similar to those observed in other investigations. Heymsfield et al.(24) obtained variation coefficients of 7.1% for AMB and 1.0% for the arm total area between two evaluators. Other authors also observed satisfactory results for intra-evaluator measures for arm circumference and triceps skinfold separately(30-33). However, a higher objectivity of AGB in relation to AMB is expected due to the smaller area occupied by the fat tissue. Thus, small differences observed in values of circumference and triceps skinfolds will be less evident in AGB than in AMB. The ATB may be determined with lower variation between evaluators, possibly due to the small sum of errors for the attainment of variables ATB, once the skinfold thickness is not employed in this calculation.
Finally, it has been concluded that the inference anthropometric technique of muscular and arm fat areas may be employed with reasonable agreement between evaluators for the estimation of the body adiposity and maximal voluntary strength of trunk and upper limbs.
The authors of this study express their acknowledgments to Hospital dos Servidores do Estado and to AACEA-HSE, represented by Dr. Aluysio S. Aderaldo Jr. for the significant contribution for the performance of this work.
All the authors declared there is not any potential conflict of interests regarding this article.
1. Forslund AH, Johansson AG, Sjodin A, Bryding G, Ljunghall L, Hambraeus L. Evaluation on modified multicompartment models to calculate body composition in healthy males. Am J Clin Nutr 1996;63:856-62. [ Links ]
2. Withers RT, LaForgia J, Pillans K, Shipp NJ, Chatterton BE, Schultz CG, Leaney F. Comparisons of two-, three-, and four-compartment models of body composition analysis in men and women. J Appl Physiol 1998;85:238-45. [ Links ]
3. Himes JH, Roche AF, Webb P. Fat areas as estimates of total body fat. Am J Clin Nutr 1980;33:2093-100. [ Links ]
4. McArdle WD, Katch FI, Katch VL. Exercise Physiology. 4th ed. Baltimore: Williams & Wilkins, 1996. [ Links ]
5. Åstrand PO, Rocahl K, Dahl HA, Strømme SB. Textbook of work physiology: Physiological bases of exercise. 4th ed. Champaign: Human Kinetics, 2003. [ Links ]
6. Jackson A, Watkins M, Patton RW. A factor analysis of twelve isotonic strength performances on universal gym. Med Sci Sports Exerc 1980;12:274-7. [ Links ]
7. Pollock ML, Wilmore J. Exercício na saúde e na doença. 2s ed. Rio de Janeiro: Medsi, 1986. [ Links ]
8. Gordon CC, Chumlea WC, Roche AF. Stature, recumbent length, and weight. In: Lohman TG, Roche AF, Martorell R, editors. Anthropometric standardization reference manual. Champaign: Human Kinetics, 1988;3-8. [ Links ]
9. Frisancho AR. Triceps skinfold and upper arm muscle areas for assessment of nutritional status. Am J Clin Nutr 1974;27:1052-8. [ Links ]
10. Frisancho AR. New norms of upper limb fat and muscle areas for assessment of nutritional status. Am J Clin Nutr 1981;34:2540-5. [ Links ]
11. Baumgartner RN, Heymsfield SB, Lichtman S, Wang J, Pierson RN. Body composition in elderly people: effect of criterion estimates on predictive equations. Am J Clin Nutr 1991;53:1345-53. [ Links ]
12. Willams DP, Going SB, Lohman TG, Hewitt MJ, Harber AE. Estimation of body fat from skinfold thickness in middle-aged and older men and women: a multiple component approach. American Journal of Human Biology 1992;4:595-605. [ Links ]
13. Clasey JL, Kanaley JA, Wideman L, Heymsfield SB, Teates CD, Gutgesell ME, Thorner MO, Hartman ML, Weltman A. Validity of methods of body composition assessment in young and older men and women. J Appl Physiol 1999;86: 728-38. [ Links ]
14. Baumgartner RN, Rhyne RL, Troup C, Wayne S, Gandy PJ. Appendicular skeletal muscle are assessed by magnetic resonance imaging in older people. Journal of Gerontology 1992;47:M67-72. [ Links ]
15. Pollock ML, Laughridge E, Coleman B, Linnerud AC, Jackson A. Prediction of body density in young and middle-aged women. J Appl Physiol 1975;38:745-9. [ Links ]
16. Pollock ML, Hickman T, Kendrick Z, Jackson A, Linnerud AC, Dawson G. Prediction of body density in young and middle-aged men. J Appl Physiol 1976;40:300-4. [ Links ]
17. Jackson AS, Pollock ML. Generalized equations for predicting body density of men. Br J Nutr 1978;40:497-504. [ Links ]
18. Guedes DP. Composição corporal: princípios, técnicas e aplicações. 2a ed. Londrina: APEF, 1994. [ Links ]
19. Beddoe AH, Samat SB. Body fat prediction from skinfold anthropometry referenced to a new gold standard: in vivo neutron activation analysis and tritium dilution. Physiol Meas 1997;19:393-403. [ Links ]
20. Jackson AS, Pollock MS, Graves JE, Mahar MT. Reliability and validity of bioelectrical impedance in determining body composition. J Appl Physiol 1988;64:529-34. [ Links ]
21. Lean M, Hans TS, Deurenberg P. Predicting body composition by anthropometric measurements. Am J Clin Nutr 1996;63:4-14. [ Links ]
22. Durnin JV, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. Br J Nutr 1974;32:77-97. [ Links ]
23. Baumgartner RN, Chumlea CW, Roche AF. Estimation of body composition from bioelectric impedance of body segments. Am J Clin Nutr 1989;50:221-6. [ Links ]
24. Heymsfield SB, McManus C, Smith J, Stevens V, Nixon DW. Anthropometric measurements of muscle mass: revised equations for calculating bone-free arm muscle area. Am J Clin Nutr 1982;36:680-90. [ Links ]
25. Katch FI, Hortobagyi T. Validity of surface anthropometry to estimate upper-arm muscularity, including changes with body mass loss. Am J Clin Nutr 1990;52:591-5. [ Links ]
26. De Koning FL, Binkhorst RA, Kauer JMG, Thijssen HOM. Accuracy of an anthropometric estimate of the muscle and bone area in a transversal cross-section of the arm. Int J Sports Med 1986;7:246-9. [ Links ]
27. Mayhew JL, Piper FC, Ware JS. Anthropometric correlates with strength performance among resistance trained athletes. J Sports Med Phys Fitness 1993;33:159-65. [ Links ]
28. Mayhew JL, Piper FC, Ware JS. Relationships of anthropometric dimensions to strength performance in resistance trained athletes. Journal of Physical Education and Sport Science 1993;5:7-16. [ Links ]
29. Schantz P, Randall-Fox E, Hutchison W, Tydén, Åstrand PO. Muscle fibre type distribution, muscle cross-sectional area and maximal voluntary strength in humans. Acta Physiol Scand 1983;117:219-26. [ Links ]
30. Kasarskis EJ, Berryman S, English T, Nyland J, Vanderlees T, Schneider A, Berger R, McClain C. The use of upper extremity anthropometrics in the clinical assessment of patients with amyotrophic lateral sclerosis. Muscle Nerve 1997;20:330-5. [ Links ]
31. Forbes GB, Brown MR, Griffiths HJ. Arm muscle plus bone area: anthropometry and CAT scan compared. Am J Clin Nutr 1988;47:929-31. [ Links ]
32. Enoka RM. Bases neuromecânicas da cinesiologia. 2a ed. São Paulo: Manole, 2000. [ Links ]
33. Mueller WH, Malina RM. Relative reliability of circumferences and skinfolds as measures of body fat distribution. Am J Phys Anthropol 1987;72:437-9. [ Links ]
34. Ferrario M, Carpenter MA, Chambless LE. Reliability of body fat distribution measurements. The ARIC study baseline cohort results. International Journal of Obesity 1995;19:449-57. [ Links ]
35. Benefice E, Malina R. Body size, body composition and motor performances of mild-to-moderately undernourished Senegalese children. Ann Hum Biol 1996;23:307-21. [ Links ]
36. Klipstein-Grobush K, Georg T, Boeing H. Interviewer variability in anthropometric measurements and estimates of body composition. Int J Epidemiol 1997;26(Supl1):S174-80. [ Links ]
Fernando A.M.S. Pompeu
Av. Brigadeiro Trompowski, 212, Cidade Universitária, Ilha do Fundão
21941-590 Rio de Janeiro, RJ
Fax: (21) 2562-6801
Received in 11/11/03. 2nd version received in 26/4/04. Approved in 30/4/04