Research in Developmental Disabilities 35 (2014) 2987–2992
Contents lists available at ScienceDirect
Research in Developmental Disabilities
Metabolomic (anthropometric and biochemical) indexes and metabolic syndrome in adolescents and young adults with intellectual disabilities Arnulfo Ramos-Jime´nez a,*, Rosa Patricia Herna´ndez-Torres b,1, Abraham Wall-Medrano a,1, Rafael Villalobos-Molina a,c,1 a Department of Health Sciences, Autonomous University of Ciudad Juarez, Anillo Envolvente del PRONAF y Estocolmo s/n, Ciudad Jua´rez 32310, Chihuahua, Mexico b School of Sciences of Physical Culture, Autonomous University of Chihuahua, Ciudad Jua´rez, Chihuahua, Mexico c Biomedicine Unit, School of Higher Studies Iztacala, National Autonomous University of Me´xico, Tlalnepantla, Mexico
A R T I C L E I N F O
A B S T R A C T
Article history: Received 21 June 2014 Accepted 23 July 2014 Available online
The aim of the present study was to describe the use of combination of international standardized anthropometric parameters, along with biochemical parameters (metabolomic indexes) to identify metabolic syndrome (MetS), in persons with intellectual disabilities. We conducted a cross-sectional study of 42 adolescents and young adults with intellectual disabilities (aged 13–30 years) who attend special schools in Ciudad Jua´rez, Chihuahua, Me´xico. The study included anthropometric (using the International Society for the Advancement of Kineanthropometry recommendations) and biochemical measures, and their combinations as metabolomic-indexes, that can significantly predict MetS occurrence in this vulnerable population. Waist circumference (WC) and relaxed arm circumference, both adjusted for height, have the highest correlation with MetS (R2 = 0.23– 0.47, p < 0.01). Besides body mass index (BMI) and WC we propose other indicators such as, skinfolds, hip circumference and relaxed arm circumference, all of them adjusted by height in order to better define the presence of MetS in persons with intellectual disabilities. ß 2014 Elsevier Ltd. All rights reserved.
Keywords: Obesity Arm circumference Skinfolds Cardiovascular risk Metabolic syndrome index
1. Introduction The metabolic syndrome (MetS) is a cluster of abnormalities like central obesity, dyslipidemia, hyperglycemia and hypertension (Alberti et al., 2009); it is a main risk factor for to develop type 2 diabetes (DM2) and cardiovascular diseases (CVD) (Gami et al., 2007; Mottillo, Filion, Genest, & Joseph, 2010). Global prevalence of the MetS is variable, for instance in Europe it is 28–78% (van Vliet-Ostaptchouk et al., 2014), in the US it is 23% (Beltra´n-Sa´nchez, Harhay, Harhay, & McElligott, 2013); while in Me´xico it is 25% (Escobedo et al., 2009; Me´ndez-Herna´ndez et al., 2009). Among people with a physical,
* Corresponding author at: Instituto de Ciencias Biome´dicas, Universidad Auto´noma de Ciudad Jua´rez. Anillo Envolvente del PRONAF y Estocolmo s/n, Ciudad Jua´rez 32310, Chihuahua, Mexico. Tel.: +52 656 688 1821; fax: +52 656 688 1800. E-mail addresses: [email protected], [email protected] (A. Ramos-Jime´nez), [email protected] (R.P. Herna´ndez-Torres), [email protected] (A. Wall-Medrano), [email protected] (R. Villalobos-Molina). 1 These authors contributed equally to this work. http://dx.doi.org/10.1016/j.ridd.2014.07.050 0891-4222/ß 2014 Elsevier Ltd. All rights reserved.
2988
A. Ramos-Jime´nez et al. / Research in Developmental Disabilities 35 (2014) 2987–2992
intellectual or sensory disability, some authors report high cardiovascular risks, prevalence of obesity (>12%), or values that triple the mean values of the general population (Froehlich-Grobe, Lee, & Washburn, 2013; Graham and Reid, 2000; Rimmer, Yamaki, Lowry, Wang, & Vogel, 2010). On the contrary, others reported healthy anthropometric and lipid profiles in people with autism and intellectual disability (Adelekan, Magge, Shults, Stallings, & Stettler, 2012; Moses et al., 2013); however, in northern Me´xico we have found 25% dyslipidemia among these people, similar to the general population (Ramos-Jime´nez, Wall-Medrano, & Herna´ndez-Torres, 2012). These data suggest that the MetS prevalence might be different, and it could be associated to existing social, economic, educative and cultural factors among the populations. On the other hand, anthropometric parameters known to be better associated to MetS and CVD prevalence are body mass index (BMI) and waist circumference (WC), where WC has been shown to be a better indicator (Klein et al., 2007); however, there are other anthropometric parameters less used but also associated to those illnesses, like skinfolds and endomorphy somatotype (Lele, 2007; Moreno et al., 2002). One of the reasons for that is a lack of a unique method for their measurement then results are not easily comparable, and this is even worse if the method is applied to subjects with disabilities. In this sense, the association between anthropometric parameters and metabolic ones in persons with intellectual disability is scarcely known. Moreover, due to the specific physical and genetics conditions of this illness, to alimentary, social, cultural and physical activity roles among these persons, those associations could be different to those found in the general population. To the best of our knowledge there are no studies, using international standardized anthropometric parameters, that determine the presence or not of MetS in intellectual disability subjects. Then, the aim of this study was to describe the best anthropometric parameters associated to MetS, along with its prevalence among these persons by using the International Society for the Advancement of Kineanthropometry (ISAK) scale/guidelines (Kevin and Olds, 1996). 2. Methods 2.1. Characteristics of the subjects Forty two individuals of both sexes (13–30 years-old) were invited to participate in the study; they showed different degree of mental disability like autism, cerebral paralysis, microcephalia, non-defined perinatal and genetic factors not related to Down syndrome. All the participants attended public schools for the social integration of persons with intellectual disability and for their multidisciplinary attention, in Ciudad Jua´rez, Chihuahua, Me´xico. The study protocol was a transversal and descriptive design, which was approved by the Ethics Committee of the Universidad Auto´noma de Ciudad Jua´rez, and by the participant schools’ authorities, we followed the declaration of Helsinki recommendations for human experimentation. Anthropometric, biochemical and blood pressure measurements were completed in two weeks. The diagnosis for the kind of intellectual disability was established by experienced psychiatrists in this kind of disorders, and given to the researchers via the schools’ authorities. 2.2. Anthropometric measurements The complete measurements were conducted under the recommendations of the ISAK (Kevin and Olds, 1996) and were performed by a trained anthropometrist, and validated by the ISAK. Body weight was obtained through a digital scale (Tanita mod. 682), the height with a portable stadiometer (Seca mod. 208), and the other measurements with an anthropometer (Centurion Kit, Vancouver, Canada). 2.3. Biochemical analysis Peripheral blood samples were withdrawn and collected in tubes with and without anticoagulant (EDTA) from each participant, in a resting condition. Glycemia, triacylglycerols (TAG), total cholesterol (TC), and cholesterol associated to high density lipoproteins (HDL-C), were determined by commercial enzymatic-colorimetric techniques. Interassay variation was lower than 2.3%. 2.4. Statistical analysis For a better description of the health status among the subjects, and to get a better correlation between anthropometric and biochemical parameters, the following metabolomic-anthropometric and metabolomic-biochemical indexes were created or obtained from reported studies: waist circumference/height (WC/H), waist circumference/hip (WC/Hip), body mass index waist circumference/height (BMI WC/H), WC Hip/H, body weight WC/H (BW WC/H), WC bicipital skinfold/H (WC BS/H), WC relaxed arm circumference/height (WC AC/H), TAG/HDL-C and TAG glucose (TyG). In order to normalize data distribution and parametric analysis, natural logarithms for the metabolomic indexes were obtained, except for WC/H, WC/Hip and WC AC/H; these three indexes already showed a normal distribution. Descriptive statistics and Pearson’s bivariate correlation between anthropometric and biochemical parameters, natural logarithm and metabolomic indexes are shown, as well as a regression analysis between a commonly used parameter to define overweight (WC) and the metabolomic indexes.
A. Ramos-Jime´nez et al. / Research in Developmental Disabilities 35 (2014) 2987–2992
2989
Table 1 Physical and biochemical characteristics of subjects. Percentile 0–5
6–25
26–50
51–75
76–95
95–100
13.0 0.0 39.9 0.4 1.43 0.02 16.2 0.7
14.0 0.0 46.3 2.2 1.52 0.03 18.0 0.7
15.0 0.0 53.7 2.3 1.59 0.02 20.5 1.1
16.5 0.7 65.9 5.6 1.65 0.02 24.9 1.6
20.1 2.4 79.8 4.2 1.71 0.02 30.2 2.4
26.3 3.2 101.9 13.6 1.81 0.07 50.1 2.8
Bicipital Triceps Subescapularis Supraspinal Medial leg Sum of skinfolds
Skinfolds, mm 3.5 0.7 5.5 2.1 6.3 0.6 5.3 0.6 5.5 0.7 27.5 0.7
5.4 0.9 9.0 1.6 9.3 1.2 8.8 1.5 8.0 1.5 44.5 6.4
9.0 1.8 13.5 1.0 13.2 1.6 13.5 1.4 11.7 1.6 63.7 4.5
12.9 1.2 18.7 1.8 19.4 2.2 18.7 2.6 15.6 1.7 84.2 10.7
18.2 1.8 26.6 3.0 25.4 1.1 28.7 2.9 25.4 3.3 121.7 14.1
24.5 0.7 34.0 2.8 34.0 5.3 37.0 3.0 32.7 3.1 145.1 0.7
Waist Hip Arm
Circumference, cm 61.5 0.7 78.7 3.2 19.5 0.7
65.0 1.4 83.7 1.6 22.5 0.5
71.1 2.2 90.9 2.4 25.0 1.2
82.4 6.4 98.2 2.8 28.0 1.3
95.7 4.2 108.1 4.8 32.5 1.0
110.7 7.2 126.3 2.5 37.7 2.1
Glucose HDL-C Total Cholesterol Triacylglycerols
Biochemical, mg/dL 76.5 0.7 29.8 0.1 105.5 6.4 48.5 3.5
79.5 1.3 37.5 4.3 130.2 7.0 57.5 5.0
84.0 1.8 45.3 1.2 155.5 7.8 80.7 11.5
90.3 2.2 51.6 3.2 176.4 4.5 119.4 16.0
96.0 2.2 60.3 2.7 203.9 12.7 199.5 32.8
207.5 106.8 72.9 2.7 244.0 15.6 468.0 192.3
WC/H WC/Hip BMI WC/H WC Hip/H BW WC/H WC BS/H WC AC/H TAG/HDL-C TyG
Metabolomic indexes 38.2 0.9 40.2 1.1 0.65 0.07 0.75 0.02 6.9 0.1 7.1 0.1 8.0 0.0 8.2 0.0 7.4 0.1 7.6 0.1 4.7 0.3 5.4 0.1 6.7 0.1 6.8 0.1 0.27 0.10 0.07 0.08 7.56 0.1 7.78 0.08
44.2 1.2 0.79 0.01 7.3 0.1 8.3 0.1 7.8 0.1 6.0 0.2 7.0 0.1 0.47 0.24 8.13 0.16
51.0 3.4 0.85 0.02 7.6 0.1 8.5 0.1 8.1 0.1 6.5 0.1 7.3 0.1 0.96 0.24 8.55 0.12
59.3 3.6 0.91 0.03 8.0 0.1 8.7 0.1 8.4 0.1 6.9 0.2 7.5 0.1 1.56 0.19 9.14 0.31
69.1 2.2 1.01 0.05 8.4 0.1 9.1 0.1 8.8 0.2 7.4 0.1 7.8 0.1 2.59 0.31 10.34 0.16
Age (years) Weight (kg) Height (m) BMI (kg/m2)
Values are presented as mean SD. BMI, body mass index; WC, waist circumference; AC, arm circumference; H, height; BW, body weight; BS, biceps skinfold; TC, total cholesterol; HDL-C, cholesterol associated to high density lipoproteins; TAG, triacylglycerols; TyG, triacylglycerols glucose.
3. Results Demographic, physical and biochemical characteristics of the studied population are shown in Table 1; as observed, BMI, WC and BW increased with age to abnormal values. According to the WHO (1998) and the NCEP ATP III criteria (2002), to determine overweight and obesity, we found that 25% of the subjects show overweight (BMI 25 30 kg/m2), and 5% show obesity (BMI 30 kg/m2 or WC 102 cm) (Table 1). Regarding the somatotype, the average is endo-mesomorphy, i.e., subjects are round with dominant adiposity (endomorphy 5–6.5 units) and regular muscle mass (mesomorphy 3– 4.5 units). According to their metabolic profile, 5% showed hyperglycemia (110 mg/dL), 25% low HDL-C (
Contents lists available at ScienceDirect
Research in Developmental Disabilities
Metabolomic (anthropometric and biochemical) indexes and metabolic syndrome in adolescents and young adults with intellectual disabilities Arnulfo Ramos-Jime´nez a,*, Rosa Patricia Herna´ndez-Torres b,1, Abraham Wall-Medrano a,1, Rafael Villalobos-Molina a,c,1 a Department of Health Sciences, Autonomous University of Ciudad Juarez, Anillo Envolvente del PRONAF y Estocolmo s/n, Ciudad Jua´rez 32310, Chihuahua, Mexico b School of Sciences of Physical Culture, Autonomous University of Chihuahua, Ciudad Jua´rez, Chihuahua, Mexico c Biomedicine Unit, School of Higher Studies Iztacala, National Autonomous University of Me´xico, Tlalnepantla, Mexico
A R T I C L E I N F O
A B S T R A C T
Article history: Received 21 June 2014 Accepted 23 July 2014 Available online
The aim of the present study was to describe the use of combination of international standardized anthropometric parameters, along with biochemical parameters (metabolomic indexes) to identify metabolic syndrome (MetS), in persons with intellectual disabilities. We conducted a cross-sectional study of 42 adolescents and young adults with intellectual disabilities (aged 13–30 years) who attend special schools in Ciudad Jua´rez, Chihuahua, Me´xico. The study included anthropometric (using the International Society for the Advancement of Kineanthropometry recommendations) and biochemical measures, and their combinations as metabolomic-indexes, that can significantly predict MetS occurrence in this vulnerable population. Waist circumference (WC) and relaxed arm circumference, both adjusted for height, have the highest correlation with MetS (R2 = 0.23– 0.47, p < 0.01). Besides body mass index (BMI) and WC we propose other indicators such as, skinfolds, hip circumference and relaxed arm circumference, all of them adjusted by height in order to better define the presence of MetS in persons with intellectual disabilities. ß 2014 Elsevier Ltd. All rights reserved.
Keywords: Obesity Arm circumference Skinfolds Cardiovascular risk Metabolic syndrome index
1. Introduction The metabolic syndrome (MetS) is a cluster of abnormalities like central obesity, dyslipidemia, hyperglycemia and hypertension (Alberti et al., 2009); it is a main risk factor for to develop type 2 diabetes (DM2) and cardiovascular diseases (CVD) (Gami et al., 2007; Mottillo, Filion, Genest, & Joseph, 2010). Global prevalence of the MetS is variable, for instance in Europe it is 28–78% (van Vliet-Ostaptchouk et al., 2014), in the US it is 23% (Beltra´n-Sa´nchez, Harhay, Harhay, & McElligott, 2013); while in Me´xico it is 25% (Escobedo et al., 2009; Me´ndez-Herna´ndez et al., 2009). Among people with a physical,
* Corresponding author at: Instituto de Ciencias Biome´dicas, Universidad Auto´noma de Ciudad Jua´rez. Anillo Envolvente del PRONAF y Estocolmo s/n, Ciudad Jua´rez 32310, Chihuahua, Mexico. Tel.: +52 656 688 1821; fax: +52 656 688 1800. E-mail addresses: [email protected], [email protected] (A. Ramos-Jime´nez), [email protected] (R.P. Herna´ndez-Torres), [email protected] (A. Wall-Medrano), [email protected] (R. Villalobos-Molina). 1 These authors contributed equally to this work. http://dx.doi.org/10.1016/j.ridd.2014.07.050 0891-4222/ß 2014 Elsevier Ltd. All rights reserved.
2988
A. Ramos-Jime´nez et al. / Research in Developmental Disabilities 35 (2014) 2987–2992
intellectual or sensory disability, some authors report high cardiovascular risks, prevalence of obesity (>12%), or values that triple the mean values of the general population (Froehlich-Grobe, Lee, & Washburn, 2013; Graham and Reid, 2000; Rimmer, Yamaki, Lowry, Wang, & Vogel, 2010). On the contrary, others reported healthy anthropometric and lipid profiles in people with autism and intellectual disability (Adelekan, Magge, Shults, Stallings, & Stettler, 2012; Moses et al., 2013); however, in northern Me´xico we have found 25% dyslipidemia among these people, similar to the general population (Ramos-Jime´nez, Wall-Medrano, & Herna´ndez-Torres, 2012). These data suggest that the MetS prevalence might be different, and it could be associated to existing social, economic, educative and cultural factors among the populations. On the other hand, anthropometric parameters known to be better associated to MetS and CVD prevalence are body mass index (BMI) and waist circumference (WC), where WC has been shown to be a better indicator (Klein et al., 2007); however, there are other anthropometric parameters less used but also associated to those illnesses, like skinfolds and endomorphy somatotype (Lele, 2007; Moreno et al., 2002). One of the reasons for that is a lack of a unique method for their measurement then results are not easily comparable, and this is even worse if the method is applied to subjects with disabilities. In this sense, the association between anthropometric parameters and metabolic ones in persons with intellectual disability is scarcely known. Moreover, due to the specific physical and genetics conditions of this illness, to alimentary, social, cultural and physical activity roles among these persons, those associations could be different to those found in the general population. To the best of our knowledge there are no studies, using international standardized anthropometric parameters, that determine the presence or not of MetS in intellectual disability subjects. Then, the aim of this study was to describe the best anthropometric parameters associated to MetS, along with its prevalence among these persons by using the International Society for the Advancement of Kineanthropometry (ISAK) scale/guidelines (Kevin and Olds, 1996). 2. Methods 2.1. Characteristics of the subjects Forty two individuals of both sexes (13–30 years-old) were invited to participate in the study; they showed different degree of mental disability like autism, cerebral paralysis, microcephalia, non-defined perinatal and genetic factors not related to Down syndrome. All the participants attended public schools for the social integration of persons with intellectual disability and for their multidisciplinary attention, in Ciudad Jua´rez, Chihuahua, Me´xico. The study protocol was a transversal and descriptive design, which was approved by the Ethics Committee of the Universidad Auto´noma de Ciudad Jua´rez, and by the participant schools’ authorities, we followed the declaration of Helsinki recommendations for human experimentation. Anthropometric, biochemical and blood pressure measurements were completed in two weeks. The diagnosis for the kind of intellectual disability was established by experienced psychiatrists in this kind of disorders, and given to the researchers via the schools’ authorities. 2.2. Anthropometric measurements The complete measurements were conducted under the recommendations of the ISAK (Kevin and Olds, 1996) and were performed by a trained anthropometrist, and validated by the ISAK. Body weight was obtained through a digital scale (Tanita mod. 682), the height with a portable stadiometer (Seca mod. 208), and the other measurements with an anthropometer (Centurion Kit, Vancouver, Canada). 2.3. Biochemical analysis Peripheral blood samples were withdrawn and collected in tubes with and without anticoagulant (EDTA) from each participant, in a resting condition. Glycemia, triacylglycerols (TAG), total cholesterol (TC), and cholesterol associated to high density lipoproteins (HDL-C), were determined by commercial enzymatic-colorimetric techniques. Interassay variation was lower than 2.3%. 2.4. Statistical analysis For a better description of the health status among the subjects, and to get a better correlation between anthropometric and biochemical parameters, the following metabolomic-anthropometric and metabolomic-biochemical indexes were created or obtained from reported studies: waist circumference/height (WC/H), waist circumference/hip (WC/Hip), body mass index waist circumference/height (BMI WC/H), WC Hip/H, body weight WC/H (BW WC/H), WC bicipital skinfold/H (WC BS/H), WC relaxed arm circumference/height (WC AC/H), TAG/HDL-C and TAG glucose (TyG). In order to normalize data distribution and parametric analysis, natural logarithms for the metabolomic indexes were obtained, except for WC/H, WC/Hip and WC AC/H; these three indexes already showed a normal distribution. Descriptive statistics and Pearson’s bivariate correlation between anthropometric and biochemical parameters, natural logarithm and metabolomic indexes are shown, as well as a regression analysis between a commonly used parameter to define overweight (WC) and the metabolomic indexes.
A. Ramos-Jime´nez et al. / Research in Developmental Disabilities 35 (2014) 2987–2992
2989
Table 1 Physical and biochemical characteristics of subjects. Percentile 0–5
6–25
26–50
51–75
76–95
95–100
13.0 0.0 39.9 0.4 1.43 0.02 16.2 0.7
14.0 0.0 46.3 2.2 1.52 0.03 18.0 0.7
15.0 0.0 53.7 2.3 1.59 0.02 20.5 1.1
16.5 0.7 65.9 5.6 1.65 0.02 24.9 1.6
20.1 2.4 79.8 4.2 1.71 0.02 30.2 2.4
26.3 3.2 101.9 13.6 1.81 0.07 50.1 2.8
Bicipital Triceps Subescapularis Supraspinal Medial leg Sum of skinfolds
Skinfolds, mm 3.5 0.7 5.5 2.1 6.3 0.6 5.3 0.6 5.5 0.7 27.5 0.7
5.4 0.9 9.0 1.6 9.3 1.2 8.8 1.5 8.0 1.5 44.5 6.4
9.0 1.8 13.5 1.0 13.2 1.6 13.5 1.4 11.7 1.6 63.7 4.5
12.9 1.2 18.7 1.8 19.4 2.2 18.7 2.6 15.6 1.7 84.2 10.7
18.2 1.8 26.6 3.0 25.4 1.1 28.7 2.9 25.4 3.3 121.7 14.1
24.5 0.7 34.0 2.8 34.0 5.3 37.0 3.0 32.7 3.1 145.1 0.7
Waist Hip Arm
Circumference, cm 61.5 0.7 78.7 3.2 19.5 0.7
65.0 1.4 83.7 1.6 22.5 0.5
71.1 2.2 90.9 2.4 25.0 1.2
82.4 6.4 98.2 2.8 28.0 1.3
95.7 4.2 108.1 4.8 32.5 1.0
110.7 7.2 126.3 2.5 37.7 2.1
Glucose HDL-C Total Cholesterol Triacylglycerols
Biochemical, mg/dL 76.5 0.7 29.8 0.1 105.5 6.4 48.5 3.5
79.5 1.3 37.5 4.3 130.2 7.0 57.5 5.0
84.0 1.8 45.3 1.2 155.5 7.8 80.7 11.5
90.3 2.2 51.6 3.2 176.4 4.5 119.4 16.0
96.0 2.2 60.3 2.7 203.9 12.7 199.5 32.8
207.5 106.8 72.9 2.7 244.0 15.6 468.0 192.3
WC/H WC/Hip BMI WC/H WC Hip/H BW WC/H WC BS/H WC AC/H TAG/HDL-C TyG
Metabolomic indexes 38.2 0.9 40.2 1.1 0.65 0.07 0.75 0.02 6.9 0.1 7.1 0.1 8.0 0.0 8.2 0.0 7.4 0.1 7.6 0.1 4.7 0.3 5.4 0.1 6.7 0.1 6.8 0.1 0.27 0.10 0.07 0.08 7.56 0.1 7.78 0.08
44.2 1.2 0.79 0.01 7.3 0.1 8.3 0.1 7.8 0.1 6.0 0.2 7.0 0.1 0.47 0.24 8.13 0.16
51.0 3.4 0.85 0.02 7.6 0.1 8.5 0.1 8.1 0.1 6.5 0.1 7.3 0.1 0.96 0.24 8.55 0.12
59.3 3.6 0.91 0.03 8.0 0.1 8.7 0.1 8.4 0.1 6.9 0.2 7.5 0.1 1.56 0.19 9.14 0.31
69.1 2.2 1.01 0.05 8.4 0.1 9.1 0.1 8.8 0.2 7.4 0.1 7.8 0.1 2.59 0.31 10.34 0.16
Age (years) Weight (kg) Height (m) BMI (kg/m2)
Values are presented as mean SD. BMI, body mass index; WC, waist circumference; AC, arm circumference; H, height; BW, body weight; BS, biceps skinfold; TC, total cholesterol; HDL-C, cholesterol associated to high density lipoproteins; TAG, triacylglycerols; TyG, triacylglycerols glucose.
3. Results Demographic, physical and biochemical characteristics of the studied population are shown in Table 1; as observed, BMI, WC and BW increased with age to abnormal values. According to the WHO (1998) and the NCEP ATP III criteria (2002), to determine overweight and obesity, we found that 25% of the subjects show overweight (BMI 25 30 kg/m2), and 5% show obesity (BMI 30 kg/m2 or WC 102 cm) (Table 1). Regarding the somatotype, the average is endo-mesomorphy, i.e., subjects are round with dominant adiposity (endomorphy 5–6.5 units) and regular muscle mass (mesomorphy 3– 4.5 units). According to their metabolic profile, 5% showed hyperglycemia (110 mg/dL), 25% low HDL-C (
