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Short Stature Is Related to High Body Fat Composition Despite Body Mass Index in a Mexican Population
Archives of Medical Research 34 (2003) 137–140
ORIGINAL ARTICLE
Short Stature Is Related to High Body Fat Composition Despite Body Mass Index in a Mexican Population* Juan Carlos López-Alvarenga,a Rebeca A. Montesinos-Cabrera,a Consuelo Velázquez-Alvab and Jorge González-Barrancoa a
Departamento de Endocrinología, Clínica de Obesidad, Instituto Nacional de Ciencias Médicas y de la Nutrición Salvador Zubirán, Mexico City, Mexico b Universidad Autónoma Metropolitana-Xochimilco, Mexico City, Mexico Received for publication April 22, 2002; accepted November 25, 2002 (02/074).
Background. Mexico has a high prevalence of short stature (SS) population; thus, body mass index (BMI) criteria for diagnosis of obesity should be different from that in a tall stature (TS) population. The aim of this study was to determine whether SS at the same BMI would have greater body fat mass than those with TS. Methods. We studied 116 individuals, 58 with SS (women 1.50 m and men 1.60 m) matched by gender, age (5 years), and BMI (2). Body fat was measured by bioelectrical impedance analysis. Results. Paired comparisons between matched subjects showed that SS have greater body fat percentage than TS ( 1.40%, p 0.04). Subjects with BMI 25 and SS showed higher difference ( 4.2%, p 0.004) in body fat percentage. Subjects with SS have more body fat percentage than TS. Conclusions. This finding supports the hypothesis that in SS population BMI for diagnosis of obesity must be re-evaluated; from these results, we propose that diagnosis of obesity in SS be from BMI of 25. © 2003 IMSS. Published by Elsevier Science Inc. Key Words: Body mass index, Short stature, Bioelectrical impedance analysis, Body fat, Mexico.
Introduction Body mass index (BMI) has been used as a main criterion for diagnosis of obesity. However, BMI is an indicator of heaviness rather than fatness; thus, the Index is unable to effectively distinguish body fat from fat-free mass. For instance, using bioelectrical impedance analysis (BIA), percentage of body fat was more closely related to serum lipids than BMI (1). Using dual-energy X-ray absorptiometry (DEXA) (2), women with higher BMI have more fat and lean mass than those with lower BMI, but men with higher BMI have more fat mass but similar lean mass compared to men with
Address reprint requests to: Juan Carlos López Alvarenga, M.Sc., M.D., Departamento de Endocrinología, Clínica de Obesidad, Instituto Nacional de Ciencias Médicas y de la Nutrición Salvador Zubirán, Vasco de Quiroga #15, Col. Sección XVI, Tlalpan, 14000 México, D.F., México. Phone and FAX: ( 52) (55) 5513-4507; E-mail: [email protected] *Presented as a poster at the 10th European Congress on Obesity, Antwerp, Belgium (2000).
lower BMI. BMI for children and adolescents demonstrated cautious interpretations due to wide confidence limits despite the same BMI (3). World Health Organization (WHO) criterion for diagnosis of obesity is BMI 30, but short stature (SS) individuals could be different from those of normal stature (NS). In some countries such as Mexico, SS individuals (women 1.50 m and men 1.60 m) have a prevalence of 29%. Moreover, for some specific areas such as the southeastern Mexican state of Yucatán (4), 58.3% of men have 1.64 m and 76.4% of women 1.51 m. The National Consensus for Obesity in Mexico (5) recommended BMI 27 for diagnosis of obesity. They hypothesized that persons with SS are misclassified by BMI and suggested that SS men (1.64 m) and women (1.51 m) would be considered obese if their BMI were 25. Bioelectrical impedance analysis (BIA) is a non-invasive measurement of body composition and additionally possesses many advantages over other methods in that it is inexpensive, simple, fast, safe, portable, easy-toperform, and requires minimal operator training (6).
0188-4409/03 $–see front matter. Copyright © 2003 IMSS. Published by Elsevier Science Inc. doi:10.1016/S0188-4409(03)00002-X
138
López-Alvarenga et al./ Archives of Medical Research 34 (2003) 137–140
The aim of this study was to explore the hypothesis concerning whether SS individuals are fatter than tall stature (TS) persons despite the same BMI. To our knowledge, this is the first study in Mexico concerning body fat percentage related to stature.
by paired Student t test; p 0.05 was accepted as statistically significant. Multiple lineal correlation was used to calculate partial coefficients. The Human Ethics Committee of the INCMNSZ approved this study in August 1999 and verbal consent was obtained from each participant.
Materials and Methods
Results
Students from the Metropolitan Autonomous University/ Xochimilco Campus and out-patients from the Obesity Clinic at the National Institute of Medical Sciences and Nutrition Salvador Zubirán (INCMNSZ), both in Mexico City, were invited to participate in this study. Standardized nutritionists were trained to rank weight and height. SS was defined as height for women 1.50 m and for men 1.60 m, while TS were women with 1.60 m and men 1.70 m. One standardized nutritionist performed measurements related to height (Holtain® stadiometer), weight, and waist-hip ratio. BMI was calculated by the following formula: BMI weight (kg)/height2 (m). BIA with Tanita BF305® was carried out to measure weight, water, body content of fat, and fat-free mass. All measurements were registered early in the morning with participants on overnight fast; each emptied their bladder prior to these measurements. Subjects were barefoot and wearing a bathing suit when measurements were taken. Values obtained were derived from prediction equations provided by the equipment manufacturer (7). BIA is a good predictor of estimated bioconductor volume and resistive impedance was corrected for stature (8). BIA measurements showed high correlation with hydrodensitometry (Velázquez C, unpublished data) superior to BMI as estimator of body fat (9). Previously, our group published a paper dealing with the reliability of this method (10). Subjects were matched by gender, BMI 2, and age 5 years, as it is known these variables can influence body composition. Data were expressed as mean and standard deviation (SD). Differences between matched data were tested
This study involved 116 subjects including 58 (39 females and 19 males) with SS matched with the remaining 58 subjects with TS. Average age for individuals with SS was 26.8 7.0 years and individuals with TS, 27.2 6.6 years (p 0.20). Table 1 shows paired comparisons. Differences in body fat percentage exhibited higher body fat content for all SS people. Those with BMI 25 showed greater differences between statures (4.2% favoring short stature) (Table 2). Stature and BMI showed significant correlation with body fat (partial coefficient of correlation r 0.36, p 0.001 and r 0.46, p 0.001, respectively) but waist-hip ratio had no relationship with body fat (partial coefficient of correlation r 0.17, p 0.12).
Discussion Results herein confirmed that subjects with SS had higher percentage of body fat than tall persons. The importance of this finding was possible misclassification according to stature in populations with high prevalence of individuals with SS. Matching-subject method is powerful for contrasting, in this particular case, body fat. Matching by BMI, gender, and age contributed to control of these potential cofounders, diminished variable dispersion, and allowed comparing two persons with same BMI but different stature. Moreover, identical BMI suggested similar physical activity, but we did not measure this variable. Kim et al. (11) demonstrated that young people have similar rates of limited physical ac-
Table 1. Paired differences between tall- and short-stature individuals for entire group Variables Females/males Age (years) BMI Waist circumference (cm) Hip circumference (cm) Waist/hip ratio Resistance ( ) Body fat (%) Body fat (kg) Fat-free mass (kg)
Tall stature
Short stature
Difference
p value
39/19
39/19
—
—
26.8 7.0 23.5 2.7 78.9 8.9 98.8 5.2 0.80 0.08 559.3 59.6 28.3 8.9 18.6 6.8 47.2 9.1
27.2 6.6 23.8 2.8 76.3 8.8 92.0 5.9 0.83 0.08 568.5 66.3 29.7 9.5 16.07 6.5 37.7 7.0
0.4
0.3 2.6 6.7
0.03
9.2
1.4 2.53 9.5
0.20 0.06 0.001 0.001 0.001 0.32 0.04 0.001 0.001
Minus sign ( ) in difference column is in favor of short stature. Data were expressed as mean SD. p value was calculated by paired t test.
Short Stature Is Related to High Body Fat Despite Body Mass Index
139
Table 2. Paired differences between tall- and short-stature individuals with BMI 25 Variables
Tall stature
Short stature
Difference
p value
Females/males Age (years) BMI Waist circumference (cm) Hip circumference (cm) Waist/hip Resistance ( ) Body fat (%) Body fat (kg) Fat-free mass (kg)
6/8 26.7 4.9 27.4 1.8 91.1 5.9 103.7 3.9 0.88 0.05 512.8 51.7 31.1 10.8 24.4 8.4 54.6 10.6
6/8 27.4 4.3 27.6 2.3 88.0 6.3 98.0 6.4 0.90 0.07 517.4 63.9 35.4 12.4 22.9 8.5 41.7 8.6
—
0.7
0.2 3.2 5.8
0.02
4.6
4.2 1.4 13.0
— 0.29 0.50 0.08 0.001 0.24 0.82 0.004 0.23 0.001
Minus sign ( ) in difference column is in favor of short stature. Data were expressed as mean SD. p value was calculated by paired t test.
tivity in adolescence, albeit exceedingly less than in elementary school. Surprisingly, there are very few studies in the literature that investigate this issue. Studies that reported short stature and limb lengths were associated with diabetes and coronary heart disease (12,13); these findings could be related to interrupted early growth. Children stunted due to chronic malnutrition have larger abdominal, head, and thoracic circumferences in relation to stature than non-stunted children (14). Tall persons have lower basal metabolic rate per unit of body weight than short people, probably due to diverse proportion of metabolically active internal organs (15). The most recent study is the only work that compared body composition by underwater weight between statures and without adjusting for BMI. The study focused on energy expenditure. Considering our entire group, modest differences in body fat content were found (1.4%); however, when we analyzed only individuals with BMI 25, they showed higher differences between groups (4.2%). This fact supported the idea that difference could rise as BMI increases, but we experienced a drop in statistical power. Our findings need to be corroborated by another methodology such as DEXA. SS persons have higher waist/hip ratio than taller persons, but we had no biochemical data to analyze the effect of this finding. We carried out gender-based analysis because subgroup statistics lose power and increase bias. Therefore, it would be desirable in the future to compare differences within and between genders using a complete design. Thus, SS persons are misinterpreted as without obesity if we consider only BMI criteria. Amount of fat mass could explain high frequency of diabetes, hyperlipidemia, or hypertension in these subjects. Different adiposity measures were related to metabolic changes such as LDL sizes (16) or functions related to immune system (17). Further research is needed to interpret these facts. We concluded that subjects with SS have higher body fat percentage than those with TS despite BMI. This finding supported the idea that BMI is inaccurate and a new cut-off point for diagnosis of obesity must be re-evaluated accord-
ing to height. We recommend that BMI of 25 or more be used in SS population for diagnosis of obesity.
Acknowledgments This study was carried out with grant no. 116515 from CONACyT (México) to JCLA.
References 1. Nagaya T, Yoshida H, Takahashi H, Matsuda Y, Kawai M. Body mass index (weight/height2) or percentage body fat by bioelectrical impedance analysis: which variable better reflects serum lipid profile? Int J Obes 1999;23:771–774. 2. Morabia A, Ross A, Curtin F, Pichard C, Slosman DO. Relation of BMI to a dual-energy X-ray absorptiometry measure of fatness. Br J Nutr 1999;82:49–55. 3. Pietrobelli A, Faith MS, Allison IDS, Gallagher D, Chiumello G, Heymsfield S. Body mass index as a measure of adiposity among children and adolescents: a validation study. J Pediatr 1998;132:204–210. 4. Vargas-Ancona L. Epidemiologia de la diabetes mellitus, intolerancia a la glucosa y factores de riesgo aterogónico en Yucatán, México. Rev Biomed 1994;5:151–159. 5. González-Barranco J, Lara-Gallegos JJ, Avila-Rosas A. Concepto, definición y diagnóstico. In: Vargas-Ancona L, Bastarrachea R, LaviadaMolina H, González-Barranco J, Avila-Rosas H, editors. Obesidad en México. México: FUNSALUD, UAY;1999. pp. 25–41. 6. Houtkooper BL, Lohman GT, Going BS, Howell HW. Why bioelectrical impedance analysis should be used for estimating adiposity. Am J Clin Nutr 1996;64(Suppl):436S–448S. 7. Body fat analyzer TBF-305 instruction manual. Tokyo, Japan: Tanita Corporation;1998. 8. Foster KR, Lukaski HC. Whole-body impedance—what does it measure? Am J Clin Nutr 1996;64(Suppl):388S–396S. 9. Roubenoff R. Applications of bioelectrical impedance analysis for body composition to epidemiologic studies. Am J Clin Nutr 1996;64(Suppl): 459S–462S. 10. Macías-M N, Velásquez C, López-Alvarenga JC, Brito-Córdova G, González-Barranco J. Reproducibility of bioimpedance between two observers: a student and an expert. Obes Res 1997;5(Suppl 1):68S. 11. Kim SY, Glynn NW, Kriska AM, Barton BA, Kronsberg SS, Daniels SR, Crawford PB, Sabry ZI, Liu K. Decline in physical activity in black girls and white during adolescence. N Engl J Med 2002;347: 709–715.
140
López-Alvarenga et al./ Archives of Medical Research 34 (2003) 137–140
12. Han TS, Hooper JP, Morrison CE, Lean ME. Skeletal proportions and metabolic disorders in adults. Eur J Clin Nutr 1997;5:804–809. 13. Forsen T, Eriksson J, Qiao Q, Tervahauta M, Nissinen A, Tuomilehto J. Short stature and coronary heart disease: a 35-year follow-up of the Finnish cohorts of the Seven Countries Study. J Intern Med 2000;248: 326–332. 14. Post CL, Victors CG, Barros AJ. Low prevalence of body weight-forheight deficit: comparison of stunted and non-stunted Brazilian children. Rev Saude Publica 1999;33:575–585.
15. Cesni L, Toti E, Pastore G, Ferro-Luzzi A. The basal metabolic rate and energy cost of standardised walking of short and tall men. Eur J Clin Nutr 1998;52:441–446. 16. Rainwater DL, Mitchell BID, Comuzzle AG, Haffner SM. Relationship of low-density lipoprotein particle size and measures of adiposity. Int J Obes 1999;23:180–189. 17. Nieman DC, Henson DA, Nehlsen-Cannarella S, Ekkens M, Utter AC, Butterworth DE, Fagoaga OR. Influence of obesity on immune function. J Am Diet Assoc 1999;99:294–299.
ORIGINAL ARTICLE
Short Stature Is Related to High Body Fat Composition Despite Body Mass Index in a Mexican Population* Juan Carlos López-Alvarenga,a Rebeca A. Montesinos-Cabrera,a Consuelo Velázquez-Alvab and Jorge González-Barrancoa a
Departamento de Endocrinología, Clínica de Obesidad, Instituto Nacional de Ciencias Médicas y de la Nutrición Salvador Zubirán, Mexico City, Mexico b Universidad Autónoma Metropolitana-Xochimilco, Mexico City, Mexico Received for publication April 22, 2002; accepted November 25, 2002 (02/074).
Background. Mexico has a high prevalence of short stature (SS) population; thus, body mass index (BMI) criteria for diagnosis of obesity should be different from that in a tall stature (TS) population. The aim of this study was to determine whether SS at the same BMI would have greater body fat mass than those with TS. Methods. We studied 116 individuals, 58 with SS (women 1.50 m and men 1.60 m) matched by gender, age (5 years), and BMI (2). Body fat was measured by bioelectrical impedance analysis. Results. Paired comparisons between matched subjects showed that SS have greater body fat percentage than TS ( 1.40%, p 0.04). Subjects with BMI 25 and SS showed higher difference ( 4.2%, p 0.004) in body fat percentage. Subjects with SS have more body fat percentage than TS. Conclusions. This finding supports the hypothesis that in SS population BMI for diagnosis of obesity must be re-evaluated; from these results, we propose that diagnosis of obesity in SS be from BMI of 25. © 2003 IMSS. Published by Elsevier Science Inc. Key Words: Body mass index, Short stature, Bioelectrical impedance analysis, Body fat, Mexico.
Introduction Body mass index (BMI) has been used as a main criterion for diagnosis of obesity. However, BMI is an indicator of heaviness rather than fatness; thus, the Index is unable to effectively distinguish body fat from fat-free mass. For instance, using bioelectrical impedance analysis (BIA), percentage of body fat was more closely related to serum lipids than BMI (1). Using dual-energy X-ray absorptiometry (DEXA) (2), women with higher BMI have more fat and lean mass than those with lower BMI, but men with higher BMI have more fat mass but similar lean mass compared to men with
Address reprint requests to: Juan Carlos López Alvarenga, M.Sc., M.D., Departamento de Endocrinología, Clínica de Obesidad, Instituto Nacional de Ciencias Médicas y de la Nutrición Salvador Zubirán, Vasco de Quiroga #15, Col. Sección XVI, Tlalpan, 14000 México, D.F., México. Phone and FAX: ( 52) (55) 5513-4507; E-mail: [email protected] *Presented as a poster at the 10th European Congress on Obesity, Antwerp, Belgium (2000).
lower BMI. BMI for children and adolescents demonstrated cautious interpretations due to wide confidence limits despite the same BMI (3). World Health Organization (WHO) criterion for diagnosis of obesity is BMI 30, but short stature (SS) individuals could be different from those of normal stature (NS). In some countries such as Mexico, SS individuals (women 1.50 m and men 1.60 m) have a prevalence of 29%. Moreover, for some specific areas such as the southeastern Mexican state of Yucatán (4), 58.3% of men have 1.64 m and 76.4% of women 1.51 m. The National Consensus for Obesity in Mexico (5) recommended BMI 27 for diagnosis of obesity. They hypothesized that persons with SS are misclassified by BMI and suggested that SS men (1.64 m) and women (1.51 m) would be considered obese if their BMI were 25. Bioelectrical impedance analysis (BIA) is a non-invasive measurement of body composition and additionally possesses many advantages over other methods in that it is inexpensive, simple, fast, safe, portable, easy-toperform, and requires minimal operator training (6).
0188-4409/03 $–see front matter. Copyright © 2003 IMSS. Published by Elsevier Science Inc. doi:10.1016/S0188-4409(03)00002-X
138
López-Alvarenga et al./ Archives of Medical Research 34 (2003) 137–140
The aim of this study was to explore the hypothesis concerning whether SS individuals are fatter than tall stature (TS) persons despite the same BMI. To our knowledge, this is the first study in Mexico concerning body fat percentage related to stature.
by paired Student t test; p 0.05 was accepted as statistically significant. Multiple lineal correlation was used to calculate partial coefficients. The Human Ethics Committee of the INCMNSZ approved this study in August 1999 and verbal consent was obtained from each participant.
Materials and Methods
Results
Students from the Metropolitan Autonomous University/ Xochimilco Campus and out-patients from the Obesity Clinic at the National Institute of Medical Sciences and Nutrition Salvador Zubirán (INCMNSZ), both in Mexico City, were invited to participate in this study. Standardized nutritionists were trained to rank weight and height. SS was defined as height for women 1.50 m and for men 1.60 m, while TS were women with 1.60 m and men 1.70 m. One standardized nutritionist performed measurements related to height (Holtain® stadiometer), weight, and waist-hip ratio. BMI was calculated by the following formula: BMI weight (kg)/height2 (m). BIA with Tanita BF305® was carried out to measure weight, water, body content of fat, and fat-free mass. All measurements were registered early in the morning with participants on overnight fast; each emptied their bladder prior to these measurements. Subjects were barefoot and wearing a bathing suit when measurements were taken. Values obtained were derived from prediction equations provided by the equipment manufacturer (7). BIA is a good predictor of estimated bioconductor volume and resistive impedance was corrected for stature (8). BIA measurements showed high correlation with hydrodensitometry (Velázquez C, unpublished data) superior to BMI as estimator of body fat (9). Previously, our group published a paper dealing with the reliability of this method (10). Subjects were matched by gender, BMI 2, and age 5 years, as it is known these variables can influence body composition. Data were expressed as mean and standard deviation (SD). Differences between matched data were tested
This study involved 116 subjects including 58 (39 females and 19 males) with SS matched with the remaining 58 subjects with TS. Average age for individuals with SS was 26.8 7.0 years and individuals with TS, 27.2 6.6 years (p 0.20). Table 1 shows paired comparisons. Differences in body fat percentage exhibited higher body fat content for all SS people. Those with BMI 25 showed greater differences between statures (4.2% favoring short stature) (Table 2). Stature and BMI showed significant correlation with body fat (partial coefficient of correlation r 0.36, p 0.001 and r 0.46, p 0.001, respectively) but waist-hip ratio had no relationship with body fat (partial coefficient of correlation r 0.17, p 0.12).
Discussion Results herein confirmed that subjects with SS had higher percentage of body fat than tall persons. The importance of this finding was possible misclassification according to stature in populations with high prevalence of individuals with SS. Matching-subject method is powerful for contrasting, in this particular case, body fat. Matching by BMI, gender, and age contributed to control of these potential cofounders, diminished variable dispersion, and allowed comparing two persons with same BMI but different stature. Moreover, identical BMI suggested similar physical activity, but we did not measure this variable. Kim et al. (11) demonstrated that young people have similar rates of limited physical ac-
Table 1. Paired differences between tall- and short-stature individuals for entire group Variables Females/males Age (years) BMI Waist circumference (cm) Hip circumference (cm) Waist/hip ratio Resistance ( ) Body fat (%) Body fat (kg) Fat-free mass (kg)
Tall stature
Short stature
Difference
p value
39/19
39/19
—
—
26.8 7.0 23.5 2.7 78.9 8.9 98.8 5.2 0.80 0.08 559.3 59.6 28.3 8.9 18.6 6.8 47.2 9.1
27.2 6.6 23.8 2.8 76.3 8.8 92.0 5.9 0.83 0.08 568.5 66.3 29.7 9.5 16.07 6.5 37.7 7.0
0.4
0.3 2.6 6.7
0.03
9.2
1.4 2.53 9.5
0.20 0.06 0.001 0.001 0.001 0.32 0.04 0.001 0.001
Minus sign ( ) in difference column is in favor of short stature. Data were expressed as mean SD. p value was calculated by paired t test.
Short Stature Is Related to High Body Fat Despite Body Mass Index
139
Table 2. Paired differences between tall- and short-stature individuals with BMI 25 Variables
Tall stature
Short stature
Difference
p value
Females/males Age (years) BMI Waist circumference (cm) Hip circumference (cm) Waist/hip Resistance ( ) Body fat (%) Body fat (kg) Fat-free mass (kg)
6/8 26.7 4.9 27.4 1.8 91.1 5.9 103.7 3.9 0.88 0.05 512.8 51.7 31.1 10.8 24.4 8.4 54.6 10.6
6/8 27.4 4.3 27.6 2.3 88.0 6.3 98.0 6.4 0.90 0.07 517.4 63.9 35.4 12.4 22.9 8.5 41.7 8.6
—
0.7
0.2 3.2 5.8
0.02
4.6
4.2 1.4 13.0
— 0.29 0.50 0.08 0.001 0.24 0.82 0.004 0.23 0.001
Minus sign ( ) in difference column is in favor of short stature. Data were expressed as mean SD. p value was calculated by paired t test.
tivity in adolescence, albeit exceedingly less than in elementary school. Surprisingly, there are very few studies in the literature that investigate this issue. Studies that reported short stature and limb lengths were associated with diabetes and coronary heart disease (12,13); these findings could be related to interrupted early growth. Children stunted due to chronic malnutrition have larger abdominal, head, and thoracic circumferences in relation to stature than non-stunted children (14). Tall persons have lower basal metabolic rate per unit of body weight than short people, probably due to diverse proportion of metabolically active internal organs (15). The most recent study is the only work that compared body composition by underwater weight between statures and without adjusting for BMI. The study focused on energy expenditure. Considering our entire group, modest differences in body fat content were found (1.4%); however, when we analyzed only individuals with BMI 25, they showed higher differences between groups (4.2%). This fact supported the idea that difference could rise as BMI increases, but we experienced a drop in statistical power. Our findings need to be corroborated by another methodology such as DEXA. SS persons have higher waist/hip ratio than taller persons, but we had no biochemical data to analyze the effect of this finding. We carried out gender-based analysis because subgroup statistics lose power and increase bias. Therefore, it would be desirable in the future to compare differences within and between genders using a complete design. Thus, SS persons are misinterpreted as without obesity if we consider only BMI criteria. Amount of fat mass could explain high frequency of diabetes, hyperlipidemia, or hypertension in these subjects. Different adiposity measures were related to metabolic changes such as LDL sizes (16) or functions related to immune system (17). Further research is needed to interpret these facts. We concluded that subjects with SS have higher body fat percentage than those with TS despite BMI. This finding supported the idea that BMI is inaccurate and a new cut-off point for diagnosis of obesity must be re-evaluated accord-
ing to height. We recommend that BMI of 25 or more be used in SS population for diagnosis of obesity.
Acknowledgments This study was carried out with grant no. 116515 from CONACyT (México) to JCLA.
References 1. Nagaya T, Yoshida H, Takahashi H, Matsuda Y, Kawai M. Body mass index (weight/height2) or percentage body fat by bioelectrical impedance analysis: which variable better reflects serum lipid profile? Int J Obes 1999;23:771–774. 2. Morabia A, Ross A, Curtin F, Pichard C, Slosman DO. Relation of BMI to a dual-energy X-ray absorptiometry measure of fatness. Br J Nutr 1999;82:49–55. 3. Pietrobelli A, Faith MS, Allison IDS, Gallagher D, Chiumello G, Heymsfield S. Body mass index as a measure of adiposity among children and adolescents: a validation study. J Pediatr 1998;132:204–210. 4. Vargas-Ancona L. Epidemiologia de la diabetes mellitus, intolerancia a la glucosa y factores de riesgo aterogónico en Yucatán, México. Rev Biomed 1994;5:151–159. 5. González-Barranco J, Lara-Gallegos JJ, Avila-Rosas A. Concepto, definición y diagnóstico. In: Vargas-Ancona L, Bastarrachea R, LaviadaMolina H, González-Barranco J, Avila-Rosas H, editors. Obesidad en México. México: FUNSALUD, UAY;1999. pp. 25–41. 6. Houtkooper BL, Lohman GT, Going BS, Howell HW. Why bioelectrical impedance analysis should be used for estimating adiposity. Am J Clin Nutr 1996;64(Suppl):436S–448S. 7. Body fat analyzer TBF-305 instruction manual. Tokyo, Japan: Tanita Corporation;1998. 8. Foster KR, Lukaski HC. Whole-body impedance—what does it measure? Am J Clin Nutr 1996;64(Suppl):388S–396S. 9. Roubenoff R. Applications of bioelectrical impedance analysis for body composition to epidemiologic studies. Am J Clin Nutr 1996;64(Suppl): 459S–462S. 10. Macías-M N, Velásquez C, López-Alvarenga JC, Brito-Córdova G, González-Barranco J. Reproducibility of bioimpedance between two observers: a student and an expert. Obes Res 1997;5(Suppl 1):68S. 11. Kim SY, Glynn NW, Kriska AM, Barton BA, Kronsberg SS, Daniels SR, Crawford PB, Sabry ZI, Liu K. Decline in physical activity in black girls and white during adolescence. N Engl J Med 2002;347: 709–715.
140
López-Alvarenga et al./ Archives of Medical Research 34 (2003) 137–140
12. Han TS, Hooper JP, Morrison CE, Lean ME. Skeletal proportions and metabolic disorders in adults. Eur J Clin Nutr 1997;5:804–809. 13. Forsen T, Eriksson J, Qiao Q, Tervahauta M, Nissinen A, Tuomilehto J. Short stature and coronary heart disease: a 35-year follow-up of the Finnish cohorts of the Seven Countries Study. J Intern Med 2000;248: 326–332. 14. Post CL, Victors CG, Barros AJ. Low prevalence of body weight-forheight deficit: comparison of stunted and non-stunted Brazilian children. Rev Saude Publica 1999;33:575–585.
15. Cesni L, Toti E, Pastore G, Ferro-Luzzi A. The basal metabolic rate and energy cost of standardised walking of short and tall men. Eur J Clin Nutr 1998;52:441–446. 16. Rainwater DL, Mitchell BID, Comuzzle AG, Haffner SM. Relationship of low-density lipoprotein particle size and measures of adiposity. Int J Obes 1999;23:180–189. 17. Nieman DC, Henson DA, Nehlsen-Cannarella S, Ekkens M, Utter AC, Butterworth DE, Fagoaga OR. Influence of obesity on immune function. J Am Diet Assoc 1999;99:294–299.