Home SVCC                                                  Area: English - Español - Português

Interaction Bmi - Fat Componet

Narváez A; Ximena; Narváez, P Galo

LABEMORF. Buenos Aires, Argentina

Introduction: Body Mass Index (BMI) is useful for monitoring of nutritional status and obesity degree.
Objectives: To propose the utilization of a cross-tab = interaction of BMI vs. the fat component (tricipital + sub scapular skinfolds) (SSk), for the rapid qualification of modifications the body composition, in adolescent and adult youths with moderate - high intensity training.
Methods: 15223 subjects between 16-29 years old. A) top-rank athletes 622 male (M) and 263 females (F), from 30 country and 33 Pan American (PA) sports; B) 315 M and 129 F white, black and yellow athletes, from South American, PA and world sports; C) 355 M and 245 F, adolescents of competitive sports; and D) adolescent with scholastic sports activity, (7630 M and 6564 F). By Quartiles technique 1) the continuous variables were transformed into discreet variables; and 2) the rectangularity of data was assumed. Furthermore, to normalize the Skwness of the BMI and SSk, them were transformed by natural logarithms (ln).
Results: The BMI was dependent in the group A) of the SSk, M x2= 284 p<0.000; F x2 = 90.4 p<0.000; and of the age M x2 = 43.3 p<0.000 and F x2 = 24.1 p<0.004.
Discussion: The results are similar for the groups B, C and D. However, were not found significant differences between races neither countries but between sports. This would be explained by the dependency found between BMI and Lean Body Mass (LBM).
Conclusions: The following table (Table 1A- B- C- D- E- F) considers by convention, normality zone between the percentiles 15 - 85. The values down of these centiles, are qualified, as sub valuation = low LBM-thinness-low body mass; and for above them, as over valuation = high LBM- obesity- over weight.


   The Body Mass Index, it is a simple but objective anthropometrics index of the nutritional status of the population. The following factor had a significant impact on BMI: the weigh-height in the intrauterine growth, the birth weight-height (5), the socioeconomic status, seasonal changes in food availability and demands on activity.

   It is relatively inexpensive, easy to collect and to analyze (3,4). The weight and the height from which is derived, (BMI Kg/m2 = weight/height2) is the classic and traditional classification of obesity, it has been applied almost of exclusive way in adult and with objections and limitations adolescent in growth and development ages and especially in population with sports activity (8,9).

   The objective of this work was proposed the utilization of a cross-table that represents the interaction among BMI and the the fat component (sum of triceps and sub scapular skinfold thicknesses) (SSk), for a fast qualification of the body composition, in adolescent and adult youths with moderate and high intensity training.

   15223 subject between 16-29 years. A) Top rank athletes 622 male (M) and 263 females (F),representative of 33 sports and 30 Pan American countries. B) 315 M and 129 F white, black and yellow athletes, representative of the South American, Pan American and world sports; C) 355 M and 245 F, competitive sports of not high performance (10); and D) 6730 M and 6564 F, adolescent with scholastic sports activity.

   To achieve a homogeneous treatment and to avoid the bias, were categorized the studied variables, through the transformation technique of continuous quantities into discreet. Were codified in four groups according to the statistical technique of Quartiles (I = 0-25; II = 26-50; III = 51-75; and IV 76 -100 centiles). This method permits to have equal number of cases in each quartil and to assume the rectangularity (1) The general model is shown what is in Table 1.

      To correct (to normalize) the Skwness of the BMI and SSk, we used natural logarithms-transformation.

   The statistic treatment was central trend measures, dispersion and percentile values. Was applied Kolmogorov - Smirnov test for to prove normal distribution of the samples and Mann-Whitney, Kruskal-Wallis to test that the samples were originating of the same populations. Table 2a, 2b, 2c, 2d.

   Through cross tables we calculated the dependency of the variables with x2 and the degree of association with the correlation coefficient (r of Pearson).

   The BMI was dependent in all the groups of SSk and of the age. Table 3a, 3b. It was found very significant correlations r = 0.69 p<0.001 between BMI (Kg/m2), and SSk (mm) in male; and r = 0.68 p<0.001 for women. In the group B was found significant dependency of the BMI vs SSk, age and Lean Body Mass (LBM), in male and women in the group of whites, and alone for LBM in the black race group.

   Furthermore, the country - sport factor, was made weakly significant, alone in male, when was added the fat factor.

   It is important to emphasize that the sub scapular skinfold, presents the highest level of differences p<0.001

   Tables of BMI of WHO (2) are validated data base, to qualify chronic energy deficiency, malnutrition and monitoring the changes in the nutritional status which are influenced by socioeconomic status, seasonal changes in the foods availability and demands of physical activity.

   It was recommended the BMI as base of the anthropometric indicators of the thinness and the overweight during the adolescence (Spurr and Cabbage) (13). It is considered that the weight for the age provides few information and it is even misleading in absence of the corresponding information on the height for the age. However, the traditional methods of combined employment of the height for the age and the weight for the age to evaluate the body mass, both are complicated and have paid off biased (Kramer) (7).

   The reference data of the weight for the height have the advantage of the fact that they do not require the knowledge of the chronological age. However the relationship between the weight and the height changes much with the age (and probably with the maturity status) during the adolescence; consequently, with a given height , the corresponding weight to a particular percentile is not the same for all the ages, in such a way that the meaning of a given percentile of the weight for the height defers according to the age.

   For the same reasons, the relative weights calculated in the categories of the height during the adolescence are appropriate solely when are used in categories restricted to the age (Kramer) (7).

   The results of our study in adolescent, with significant physical activity, demonstrate that the BMI is affected by the fat component as principal factor, in each one of the four Quartiles in those which were divided the BMI and the SSk. Consequently, it is not a relationship escalated with the absolute values. The dependency is linear and very significant in all the range of the BMI as of the SSk scales.

   Our results failed to demostrate any influence of the "origin component" on the BMI, neither type of sport in male. However, in women the differences though moderate, were made present. We think that in this case, they were in evidence by the own characteristics of the sex female. The interaction found between BMI and SSk would be explained better in the women by greater fat quantity in the inferior limbs.

   It is certain that it is possible to find equal value of the BMI in subjects with different corporal composition. However it has been suggested that the BMI to other than its easy compute, independent of the height [Khosla & Lowe (5), Evans & Preceding (3), Florey (4), Smalley and col. (12)], is more sensitive to the changes of the energetic reserves of the fat that of the lean body mass (LBM). This is crucial to feed the idea to suggest the BMI, as an index of both energetic supply to the body, and the variations in the body composition, i.e., body fat and muscle mass than can occur at similar BMI values.

    On the other hand, the lean body mass was determinant factor in the differences of BMI for the males and women, demonstrating its strong dependency. (Table 3a, 3b). In spite of this, for male between BMI vs LBM we find significant correlations, r = 0.75 p<0.001. In women: BMI vs LBM r = 0.74 p<0.001. This demonstrates a high degree of reliability in the use of the BMI to qualify easy and roughly, the body composition in athletes. In other words a BMI increased in a athlete, is also indicative of a greater LBM and/or muscular mass.

   Other of the warn customarily referred, it is the application of the BMI in adolescent with high training levels. This group of subjects other than to be influenced by the rapid growth process, the physical training would modify significantly the body composition and the structure skeletal muscle.

   We study in the group A and B, the interaction of the BMI with all these factors in Pan American top rank athletes, where the training is over 12 bout by week. Furthermore, this group of 900 athletes of both sexes, was in competitive stage. We consider also the possibility that the factor "country of origin" (34 countries of the American continent) would have influence.

   In the group B, we eliminated the race factor, since in this group was not found differences in both sexes for the white races, black or yellow. Table 3a, 3b.

   The influence of the age in male was noticeable considering that the competition age is similar in all the subjects, except for sports gymnastics. The age range considerate in the group A is 22.4 ± 5.3 years old for women (n =263); and of 24.1 ± 4.2 in male (n =622); and for the group B is 21.602 ± 5.388 years old in women (n = 129); and 21.235 ± 4.233 in male (n = 315).

   In relationship to our but recent publication(11), we test the application of the allometric scaling of the BMI by the SSK, according to the following equations:

BMI / SSk 0.231 in Male; and BMI/ SSk 0.250 in women

   However, the age was a very significant discrimination factor in both sexes F = 5.26 p<0.001 in male; and F = 13.67 p<0.000 in women. Consequently we discarded this procedure, and we chosen the construction of a table of double entry.

   Thinking about giving to physician a tool but simple of using, was design a double entry cross-table, in which the percentiles 15 and 85 delimit the normality zone. Up above of the percentile 85 is established the overweight zone and by below of the percentile 15 the thinness zone. These criteria though arbitrational are based on the criterion of dispersion the median.

   The percentile tables often include the inter quartil range (IQR). It is known also as inter quartil deviation. It is half of the distance between the quartile Q1=25 and Q3=75. In a normal distribution, if from the median (P50), are carried to each side 1 IQR, is encompassed approximately 50 percent of the cases; and 4 IQR covers all the range of the distribution.

   If in any variable we calculate the IQR, we will see that its boundaries are close up the percentiles 15 downward and 85 upward. Of way practices, between these percentiles the limits of normality are fixed. Upward of this limit is considered over valuation and toward under, sub valuation.

   The steps to read the table of BMI, are to locate the age in the first column and in the two following strings, we can see the values of BMI in the first and SSk in the second. Of agreement to the value obtained in the measurement, we located one of the five columns, that correspond to the percentiles 5 - 15 - 50 - 85 - 95. As have been established by convention, the values of the normality, it will be between the centiles 15 - 85 and the values up above or below, it receive the qualifying from substandard or supranormal respectively.

   Is desirable that the values of BMI and SSk be in agreement on the same centil. However will be given situations in which the values are located in different column. In this case the suggestion is that first will be appointed the percentile or location zone of the BMI and then that of the SSk. Case A: male of 16 year old with BMI = 23 and SSk = 19 mm. Is interpreted as BMI within the normality zone (percentiles 15-85) but with indicative SSk of excess of fat. Case B male of 17 year old with scholastic sports activity: BMI = 28 and SSk = 15 mm. Can be considered it as subject with significant increase of the component skeletal muscle and low fat component, possibly due to training process. Finely, the interpretation will be established by the experience and good judgement of the physician.

   We have presented evidence of the usefulness of the BMI in critical periods of age, label by the growth and development process; this is in adolescent with moderate and top-level of sports activity and competition. Furthermore, was discarded the racial effect and of the "country of origin".

   We not intended to replace the usefulness of internationally standardized specific indicators, for the evaluation of the development skeletal muscle. However, we insisted on discarding prejudices and limitations in the utilization of the BMI, especially being frequently used in the daily practice.

   The incorporation of the SSk added in average a 35% of precision, according to the quadratic regression that smooth the curve of BMI vs SSk in all the groups.

   We recommend the utilization of the cross tables suggested in this work, but at condition that the measurement of sub scapular and triceps skinfold thicknesses are included. We will be in possession of a fast, easy and very reliable tool of measure. Moreover, the incorporation of the SSk, adding approximately in average,35% of precision.

   Finally, we have included in this work a small dynamic table (Figure 1) accomplished in Excel of MS Office. Its utilization that in fact it is very simple, helped the interpretation and qualification by age and sex, of the subject sportsman - patient in the doctor's office. (Contact mail: xime@unctef.edu.ar)


1. Blackith, R. E. and Reyment. Multivariate morphometrics. Academic Press. London, 1971.

2. El Estado Físico: Uso e Interpretación de la Antropometría. Informe de un Comité de Expertos de la OMS. 854. Organización Mundial de la Salud. Ginebra, 1995.

3. Evans, J. G. & Prior, I. A. M. Indices of obesity derived from height and weight in two Polynesian population. Brit. J. Prev. Soc. Med. 23: 56-60, 1969.

4. Florey, C. D. V. The use and interpretation of ponderal index and other weight-height ratio in epidemiological studies. J. Chr. Dis. 23: 93-103,1970.

5. Khosla, T. & Lowe, C.R. Indices of obesity derived from body weight and height. Brit. J. Prev. Soc. Med. 21: 122-128,1967.

6. Klebanoff MA, Yip R. Influence of maternal birth weight on rate of fetal growth and duration of gestation. Journal of Pediatrics,1988,82:828-834.

7. Kramer MS. Determinants of low birth weight: methodological assessment and meta-analysis. Bulletin of the World Health Organization- Bulletin de l'Organisation Mondiale de la Santé,1987,65:663-737.

8. Malina, R.M.; and Bouchard C. "Growth, Maturation and Physical Activity". Human Kinetics Publishers, Inc. H. IL,1991.

9. Martorell R. Child growth retardation: a discussion of its causes and of its relationship to health. En: Blaxter KL, Waterlow JC, eds. Nutritional adaptation in man. Londres, John Libbey, 1985: 13-30.

10. Narváez P, GE; D'Angelo, C; Zabala, R. Physical Fitness in Children and Adolescents from differing Socioeconomic Strata, in: Human Growth, Physical Fitness and Nutrition. Medicine And Sports Science. Shephard RJ, Parízková J (ed): Basel, Karger,1991; Vol. (31), pp 80-89.

11. Sanagua, J O; Narváez, PGE; Rasmussen, R; Acosta,G. The Left Ventricular Hipertrophy in Power Trainig Athletes? Allometric Scaling Other Vision. Medicine and Science in Sports and Excersice. Vol 33:5 Supplement. 2001.

12. Smalley, K. J., Knerr, A. N., Kendrick, Z. V. , Colliver, J.A. & Owen, O.E. Reassessment of body mass indices. AMER. J. Clic. Nutri. 52: 405-408,1990.

13. Spurr GB, Barac-Nieto M, Maksud MG. Productivity and maximal oxygen consumption in sugar cane cutters. American journal of clinical nutrition, 1977, 30:316-321.



Your questions, contributions and commentaries will be answered
by the authors in the Prevention and Epidemiology list.
Please fill in the form (in Spanish, Portuguese or English) and press the "Send" button.

or commentary
Name and Surname:
E-Mail address:


2nd Virtual Congress of Cardiology

Dr. Florencio Garófalo
Steering Committee
Dr. Raúl Bretal
Scientific Committee
Dr. Armando Pacher
Technical Committee - CETIFAC

Copyright© 1999-2001 Argentine Federation of Cardiology
All rights reserved


This company contributed to the Congress: