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Nutrición Hospitalaria

versión On-line ISSN 1699-5198versión impresa ISSN 0212-1611

Nutr. Hosp. vol.30 no.5 Madrid nov. 2014

http://dx.doi.org/10.3305/nh.2014.30.5.7982 

ORIGINAL / Otros

 

Reference values for leptin, cortisol, insulin and glucose, among European adolescents and their association with adiposity: The HELENA Study

Valores de referencia para leptina, cortisol, insulina y glucosa entre los adolescentes europeos y su asociación con adiposidad: Estudio HELENA

 

 

Thabata Koester-Weber1, Jara Valtueña1, Christina Breidenassel1,2, Laurent Beghin3, Maria Piada4, Sara Moreno1, Inge Huybrechts5,6, Gonzalo Palacios1,7, Sonia Gómez-Martínez8, Ulrike Albers1, Stefaan de Henauw5, Guiseppe Maiani9, Anthony Kafatos4, Denes Molnar10, Michael Sjöstrom11, Kurt Widhalm12, Yannis Manios13, Luis A. Moreno14, Ascensión Marcos8, Manuel J. Castillo15, Peter Stehle2 y Marcela Gonzalez-Gross1,7

1ImFINE Research Group. Department of Health and Human Performance. Faculty of Physical Activity and Sport Sciences-INEF. Technical University of Madrid. Spain.
2Institut für Ernährungs und Lebensmittelwissenschaften Ernährungphysiologie. Rheinische Friedrich Wilhelms Universität, Germany.
3Faculté de Médecine, Université de Lille, France.
4Preventive Medicine and Nutrition Unit, School of Medicine, University of Crete, Heraklion, Crete, Greece.
5Department of Public Health, Ghent University, Ghent, Belgium.
6International Agency for Research on Cancer, Dietary Exposure Assessment group, Lyon, France.
7CIBERobn (Fisiopatología de la Obesidad y la Nutrición CB12/03/30038), Instituto de Salud Carlos III, Spain.
8Immunonutrition Research Group, Department of Metabolism and Nutrition, Institute of Food Science, Technology and Nutrition (ICTAN), Spanish National Research Council (CSIC), Madrid, Spain.
9Food & Nutrition Research Centre, Agricultural Research Council (CRA-NUT), Rome, Italy.
10Department of Pediatrics, University of Pécs, Pécs, József A. u. 7, 7623 Pécs, Hungary.
11Karolinska Institute, Sweden.
12Department of Pediatrics, Private Medical University, Strubergasse 21, 5020 Salzburg, Austria.
13Department of Nutrition & Dietetics, Harokopio University, 70, El Venizelou Ave, 176 71 Kallithea, Athens - Greece.
14Growth, Exercise, Nutrition and Development (GENUD) Research Group, Faculty of Health Sciences, University of Zaragoza, Domingo Miral sin, 50009 Zaragoza, Spain.
15Department of Medical Physiology, School of Medicine, University of Granada, Spain.

The HELENA study has taken place with the financial support of the European Community Sixth RTD Framework Programme (Contract FOOD-CT-2005-007034). This study was also supported by a grant from the Spanish Ministry of Science and Innovation AGL2007-29784-E.

Correspondence

 

 


ABSTRACT

Background and Objective: Adequate concentrations of leptin, cortisol, and insulin are important for a suitable metabolism and development during adolescence. These hormones jointly with glucose play a major role in fat metabolism and development of childhood obesity. Our main objective was to quantify biomarkers as leptin, cortisol, insulin and glucose status in European adolescents to contribute to establish reference ranges.
Methods: A representative sample of 927 adolescents (45% males, 14.9±1.2 years for the overall population) from ten European cities of the HELENA study was used to obtain fasting blood samples for these biomarkers. The percentile distributions were computed by sex and age and percentiles were associated with BMI classification.
Results: Serum leptin concentration in adolescents varied significantly according to BMI, sex and age (all p<0.001). Cortisol presented a tendency to increase with age, both for females and males, while insulin and glucose were stable with age. Leptin and insulin were highest in obese adolescents (p<0.001), whilst cortisol and glucose did not vary with BMI. Percentiles 5, 25, 50, 75 and 95, for hormones values were, respectively: 1.27, 4.06, 11.54, 26.70 and 65.33 ng/ml for leptin; 5.00, 8.11, 11.14, 15.00 and 24.51 μg/dl for cortisol and 3.65, 6.15, 8.52, 11.90 and 20.53 μlU/ml for insulin.
Conclusions: In adolescents, leptin, cortisol, insulin and glucose concentrations are differently affected by age, sex and BMI. Establishment of reference ranges (percentiles) of these biomarkers would be of great interest when pediatricians have to assess the trend of an adolescent to develop obesity years after.

Key words: Leptin. Cortisol. Insulin. Glucose. Adiposity and Adolescents.


RESUMEN

Objetivo: Concentraciones adecuadas de leptina, cortisol e insulina son importantes para un metabolismo normal durante la adolescencia, puesto que valores alterados de estas hormonas, junto con la glucosa, se asocian con el desarrollo de la obesidad infantil. Nuestro principal objetivo fue cuantificar estos marcadores en adolescentes europeos con el fin de establecer rangos de referencia.
Métodos: Muestras de sangre procedentes de 927 adolescentes en ayunas (14,9 ± 1,2 años, 45% varones, estudio HELENA), fueron analizadas para cuantificar la leptina, cortisol, insulina y glucosa. Las distribuciones de percentiles se determinaron teniendo en cuenta el sexo y la edad. También se estudió la asociación entre percentiles y la clasificación del IMC.
Resultados: La concentración de leptina en suero variaba significativamente con el IMC, el sexo y la edad (todos p<0,001). El cortisol presentó una tendencia a aumentar con la edad, tanto para varones como mujeres, mientras que la insulina y la glucosa eran estables con la edad. La leptina y la insulina fueron más altas en los adolescentes obesos (p <0,001), mientras que el cortisol y glucosa no variaron con el IMC. Los percentiles 5, 25, 50, 75 y 95, para los valores de hormonas fueron, respectivamente: 1.27, 4.06, 11.54, 26.70 y 65.33 ng/ml para la leptina; 5.00, 8.11, 11.14, 15.00 y 24.51 μg/dl para el cortisol y 3.65, 6.15, 8.52, 11.90 y 20.53 μlU/ml de insulina.
Conclusiones: En los adolescentes, las concentraciones de referencia de leptina, cortisol, insulina y glucosa se ven afectados de manera diferente según la edad, el sexo y el IMC.

Palabras clave: Leptina. Cortisol. Insulina. Glucosa. Adiposidad y adolescentes.


 

Introduction

Since leptin was identified in 1994, hormones participating in energy homeostasis control have gained on importance, especially regarding the current obesity epidemic1. Nowadays it is known that adipocytes produce a number of substances and hormones apart from leptin, which interfere in energetic balance, as an example adiponectin, that acts cooperatively with insulin for glucose uptake2.

Besides the substances produced by adipocytes, other components of the endocrine system could be associated with adiposity and organic homeostasis. Cortisol, synthesized by the adrenal cortex, for example, could influence leptin levels due to the possible leptin secretion reduction under stress conditions. In fact, high serum cortisol levels in the morning have been associated with metabolic syndrome in overweight and obese children and adolescents3. Available evidences suggest that leptin has inhibitory role on insulin secretion and serum leptin concentration has been proposed as an important predictor of insulin resistance and other metabolic risks irrespective of obesity levels in adults4. All three (leptin, insulin and cortisol) are implicated in fatty acids metabolism and inflammation. Several studies have demonstrated a quantitative relation between higher concentrations of these hormones and the development of obesity as well as their complications2.

Generally, values of leptin, cortisol, insulin and glucose could be altered in the pediatric population with overweight and their comorbidities. However, reference values for healthy population are limited, hindering to answer questions such as: Is BMI associated with values of cortisol, glucose and insulin in healthy adolescents, as demonstrated for leptin? Do these substances vary with sex and age? Could reference curves be created in order to help assessment of adolescents in clinical practice? In this way, the main objective of the present study was to describe leptin, cortisol, insulin and glucose status in adolescents, contributing to establish reference values, which nowadays are not available for this population.

 

Subjects and Methods

Subjects, recruitment and study design

The HELENA-CSS (Healthy Lifestyle in Europe by Nutrition in Adolescence) study is a multi-centre cross-sectional study on lifestyle and nutrition among adolescents, from 10 European cities from nine different countries: Athens and Heraklion (Greece), Dortmund (Germany), Ghent (Belgium), Lille (France), Pecs (Hungary), Rome (Italy), Stockholm (Sweden), Vienna (Austria), and Zaragoza (Spain). Inclusion criteria were: being 12.5-17.5 years old, not participating simultaneously in another clinical trial and free of any acute infection earlier occurring than one week before inclusion5. Participants were recruited by a multi-stage random cluster sampling procedure, using schools as primary sampling units and classes as secondary sampling units. The sample size was calculated according to stratified random sampling with proportional affixation to the size of the strata (SEX and AGE) and minimum variance under Neyman allocation. A confidence level of 95% and a minimum of ± 0.3 error for body mass index (BMI) were chosen. On city level, diversity of the sample with respect to cultural and socio-economic aspects was achieved by performing a random proportional distribution of all schools taking into account the site (district/zone of the city) and the type of school (public or private). The complete description of the design and implementation of the study has been described elsewhere6. The study has been performed following the ethical guidelines of the Declaration of Helsinki 1964 (revision of Edinburgh 2000), Convention of Oviedo (1997), the Good Clinical Practice, and the legislation about clinical research in humans in each of the participating countries. Informed written consent was obtained from all participants and parents or guardians7.

Anthropometric measurements

Adolescents' height and weight were measured by trained researchers in a standardized way. The weight was recorded to the nearest 0.1kg, using an electronic scale (Type SECA 861, UK). The height was recorded to the nearest 0.1 cm, using a telescopic height measuring instrument (Type SECA 225, UK). The complete description of the anthropometric measurements of the study has been described elsewhere6. The Body Mass Index (BMI) of the adolescents was calculated from their measured height and weight (BMI = weight divided by height squared, [kg/m2]). The sample was classified in underweight, normal weight, overweight and obese, according to the international gender and age-specific BMI cut-off points proposed by Cole et al8. These points have been established for children and adolescents aged from 2 to < 18 years old separately for males and females. These cut-off values are based on percentiles of adults (>18 years) considering BMI <18.5 Kg/m2 for underweight, >25 Kg/m2 for overweight and 30kg/m2 for obesity8.

Tanner Stage was used for the description of adolescents' pubertal maturity. For the determination of Tanner Stage, physical examination was performed by a physician aiming to classify the adolescents into one of the five stages of pubertal maturity defined by Tanner et al.9.

Specimen collection and biochemical analyses

Blood sampling was randomly performed in one third of the recruited adolescents due to the low variability of biochemical markers. For this study was considered a subsample of 927 adolescents (421 males and 506 females) who completed the blood sampling for leptin, cortisol, insulin and glucose, with a mean age of 14.9 ±1.2 years. Fasting blood samples were collected by venipuncture at school between eight and ten o'clock in the morning between November 2006 and October 2007, during the whole academic year, excluding summer period. The complete sampling protocol has been published elsewhere10.

Leptin, cortisol, insulin and glucose assessment

For the measurements of glucose, leptin and cortisol blood was collected in serum tubes and centrifugated at 3500 rpm for 15 min. For insulin, heparin plasma was collected, put immediately on ice and centrifugated at 3500rpm for 15 min. The heparin plasma samples were transported under cooled conditions to the Central Laboratory in Bonn (Germany) and frozen at -80 oC. Insulin was analysed at the Nutrition and Food Science laboratory from the University of Bonn by immunoassay (Immulite 2000, DPC Biermann GmbH, Bad Nauheim, Germany). Serum aliquots were transported at stable room temperature and frozen at -80oC afterwards. Glucose was measured enzymatically on the Dimension RxL clinical chemistry system (Dade Behring, Schwalbach, Germany) in fresh serum samples at the University of Bonn. Samples of leptin and cortisol were analysed at the Biochemical Laboratory of the Faculty of Physical Activity and Sport Sciences (INEF) UPM, Madrid (Registered Lab number 242, Red de Laboratorios de la Comunidad de Madrid). Concentration of serum leptin (ng/mL) was measured using the RayBio® Human Leptin ELISA (Enzyme-Linked Immunosorbent Assay) kit. The sensitivity of leptin assay was less than 6 pg/mL, with intra and inter-assay coefficients of variation of <10% and <12%. To determine cortisol, a fluorescence polarisation enzymoassay in the AxSYM analyser was used (Abbott Diagnostics, Illinois, U.S.A.).

Statistical analysis

Cortisol, insulin, leptin showed non-normal distribution while glucose presented a normal distribution and the residuals showed a satisfactory pattern. Descriptive statistics were performed and values are shown as mean, standard deviation, percentile, median, minimum and maximum. The differences between sex, age groups and BMI groups were analysed using one-way ANOVA. All the analyses were adjusted by means of a weighting factor to balance the sample according to the age and sex distribution of the theoretical sample, to guarantee representation of each of the stratified groups. The Pearson's correlation was performed to evaluate the correlation between BMI, and hormones concentrations. To provide percentile value curves for European adolescents, leptin, cortisol, insulin and glucose data were analysed by maximum penalised likelihood using the least mean square statistical method for boys and girls separately. Smoothed centile charts using the least mean square method were derived. This estimates the measurement centiles in terms of three age-sex-specific cubic spline curves: the L curve (Box-Cox power to remove skewness), M curve (median) and S curve (CV). For the construction of the percentile curves, data were imported into the LMS ChartMaker software (version 2.3; by Tim Cole and Huiqi Pan, HarlowHealthcare, South Shields, Tyne and Wear, UK) and the L, M and S curves were estimated. The rest of the data were analysed using SPSS version 18.0 (SPSS Inc., Chicago, IL, USA). Statistical significance was set at p<0.05.

 

Results

General descriptive characteristics from the study sample, including mean leptin, cortisol, insulin and glucose concentrations are presented in table I. Significant differences between genders were only observed in mean leptin values, females had higher values than males (p<0.001). Most of the adolescents had normal weight (72.7%; 674/927), 5.9% (55/927) underweight, 16.9% (157/927) overweight and 4.4% (41/927) obesity. Most adolescents (70%) were classified as Tanner stages 4 or 5, but there were no gender differences.

For leptin, Cortisol, insulin and glucose concentrations, percentile distribution by age and gender are shown in tables II, III, IV, V and smoothed centile curves (P5, P25, P50, P75, P95), studied by age and gender are presented in figure 1.

In males, leptin concentrations show a decreasing tendency with increasing age. On the other hand, females have no variation in leptin concentrations by age. For both gender a significant increasing cortisol concentration was observed with increasing age (table III). Otherwise, insulin values decrease by increasing age in females and males (Table IV). As presented in table V, glucose concentration was quite stable, with an increasing tendency in both mean and median values with age.

Associations between leptin, cortisol, insulin and glucose values and BMI.

Figure 2 shows the hormonal values and glucose concentration according to the BMI classifications: underweight, normal weight, overweight and obese. Leptin shows a significant progressive and linear increase according to BMI, being both positively correlated (p<0.001). According to the multivariate comparison model, with Bonferroni correction, the leptin levels for each BMI classification were significantly different (p<0.001). The highest leptin levels were observed in obese adolescents. Similar to leptin, insulin concentrations presented a progressively increasing concentration according to BMI, being both positively correlated (p<0.001). Insulin values for obese adolescents were significantly higher, from those classified as overweight, normal weight and underweight (p<0.001).

For both males and females a positive correlation between leptin and insulin was observed (r=0.409 and 0.304; p<0.001). Cortisol and glucose showed no variation of the levels according to BMI classification, but a positive correlation was observed between glucose and cortisol for males (r=0.293; p<0.001). Glucose presented a positive correlation with insulin in both gender (p<0.001).

 

Discussion

To the best of our knowledge, the data obtained in the framework of the HELENA study are the first descriptive values for establishing leptin, cortisol, insulin and glucose levels in apparently healthy European adolescents.

Our results showed that serum leptin concentration in adolescents varied significantly according to BMI, sex and age. The scientific interest on leptin concentrations in adolescents and pre-pubertal population has been increasing since the relation of high leptin values with an increased risk of insulin resistance is known11,12. In pediatric studies,higher values in obese subjects are related to inflammation and possibly to the metabolic syndrome13. Our results revealed a positive correlation between leptin concentration and BMI in both sexes. Leptin values among boys did not show significant variation with age; on the other hand, among girls, leptinemia increases according to increasing age as described earlier14. Cross-sectional studies have shown the presence of a significant sexual dimorphism in circulating leptin concentrations during puberty with higher values in girls independently of BMI, which is comparable with data found in our study 12,15,16,17,18,19,20. However, it should be taken into account that during puberty boys and girls have different changes in body composition, which also influence leptin levels18. Estradiol has a stimulatory effect on leptin concentration in females, while testosterone has a suppressive effect21. Furthermore, some studies22,23 showed a persistent gender difference in leptin concentrations even after adjustment for differences in testosterone, estradiol and percentage of fat mass in a group of children and adolescents. Findings of this study indicate that other metabolic or hormonal sex-related variables could probably influence leptin production23.

To evaluate reference values related to glucose, we used the normal ranges for fasting glucose classified by Di Bonito et al.24. These authors performed a classification in order to evaluate the association between fasting plasma glucose and cardio metabolic risk factors. Their classifications for normal ranges of glucose are: low normal (≤82 mg/dl), mid-normal (83-88 mg/dl), and high-normal (89-99 mg/dl). The values expressed by these authors were considered in our evaluation since children and adolescents with high-normal glucose presented a higher risk of insulin resistance, hypertension, elevated white blood cell values than those with low normal glycemic, independent of BMI24. In this sense, the interpretation for the glucose values distribution in percentiles of the present study indicates that the adolescents up to the 50th percentile are in the normal range for both sexes. The 75th percentile values can also be considered as normal, but are in the upper limit of normality, where the presence of a cardiovascular risk may be associated. In our study, glucose concentrations were not influenced by BMI and age.

According to Helene et al.25 these parameters added to insulin and lipid profile evaluation can be used to monitor cardiovascular risk. Insulin values were positively correlated with BMI in both sexes. Rizzo et al.26 showed in their study that adolescents with overweight, obesity and extreme obesity, had high average values of insulin, 13.27 ± 9.9 μlU/ml; 14.08 ± 7.64 /<μlU/ ml and 16.13 ± 8.07 μlU/ml. If we compare the distribution of insulin values found in our sample group with those from Rizzo et al (2013), above the 75th percentile similar values were observed in overweight adolescents, while above the 90th percentile values are similar to those observed in extremely obese adolescents.

Cortisol is considered the stress hormone and the stress values can be influenced by several biological conditions, including increased body weight. The weight excess associated with insulin resistance and the metabolic syndrome in children and adolescents are sufficient to cause metabolic stress and an elevation of cortisol levels. In our study, we found no association between cortisol levels and BMI; however, in the study published by Reinehr and Andler27, the weight loss of obese children and adolescents promoted a reduction in cortisol levels and insulin resistance. But some studies showed a large association between elevated serum cortisol and metabolic syndrome3,28. Cortisol concentration presented a tendency to increase with age for both sexes.

Due to our results, we suggest that in clinical practice, leptin may be considered a marker for the onset of puberty29, and should be related to inflammatory parameters. A more complex assessment should be preferred to the determination of solely fasting glucose in order to prevent cardiovascular disease and diabetes. Thus, for adolescents above the percentile 75 for glucose (>than 95 mg/dl), a complementary evaluation, for assessment of global health status should be considered. Regarding insulin, adolescents with percentile equal to or higher than 75th percentile (>11.90 μlU/ ml) should have a broader evaluation. Children with cortisol equal or above the 75th percentile (>15.0 μg/ dl) should also receive a complementary assessment related to the factors involved in the metabolic syndrome and other precursors of stress. Smoothed centile curves could be used in clinical practice as possible reference values.

The HELENA study has several strengths. The sampling procedure and the strict standardization of the fieldwork among the countries involved in the study avoided to a great extent confounding bias due to inconsistent protocols and different laboratory methods, which makes comparing results from isolated studies difficult. The main contribution of the present data is, for the fi Th time, to give a global overview of adolescent leptin, cortisol, insulin and glucose status in Europe. In the absence of reference values and specific cutoff points for this age group, percentile distributions as presented can be used in clinics and further research. The HELENA study performed in European adolescents aged 12.5 - 17.5 from ten different countries has given a unique opportunity to analyze hormonal concentrations in a large sample with a standardized methodology. The analysis of adiponectin was foreseen in the HELENA study, but unfortunately data were finally not available and could be considered a limitation in the context of the present study.

 

Conclusion

The reference curves established for leptin, cortisol, insulin and glucose, performed in the present study could be used in clinical practice and extrapolated to adolescents from other parts of the world, with similar ethnical background. In adolescents, not only BMI is associated with leptin, but also sex and age. Depending on the aim of the study, current data can contribute to elucidate which parameter should be included in further studies. This paper could contribute to public health offering data in apparently healthy adolescents.

 

Disclosure

The content of this paper reflects only the author's view and the rest of HELENA Study members are not responsible for it. The writing group takes sole responsibility for the content of this article.

 

Acknowledgements

We gratefully acknowledge all participating children and adolescents, and their parents and teachers for their collaboration. We also acknowledge all the members involved in the field work for their efforts and great enthusiasm. Many thanks to Petra Pickert, Rosa Torres and Anke Carstensen for their contribution to laboratory work.

 

Conflict of interests

None.

 

Helena Study Group

Co-ordinator: Luis A. Moreno.

Core Group members: Luis A. Moreno, Fréderic Gottrand, Stefaan De Henauw, Marcela González-Gross, Chantal Gilbert.

Steering Committee: Anthony Kafatos (President), Luis A. Moreno, Christian Libersa, Stefaan De Henauw, Jackie Sáchez, Fréderic Gottrand, Mathilde Kesting, Michael Sjostrom, Dénes Molnár, Marcela González-Gross, Jean Dallongeville, Chantal Gilbert, Gunnar Hall, Lea Maes, Luca Scalfi.

Project Manager: Pilar Meléndez.

1. Universidad de Zaragoza (Spain): Luis A. Moreno, Jesús Fleta, José A. Casajús, Gerardo Rodríguez, Concepción Tomás, María I. Mesana, Germán Vicente-Rodríguez, Adoración Villarroya, Carlos M. Gil, Ignacio Ara, Juan Revenga, Carmen Lachen, Juan Fernández Alvira, Gloria Bueno, Aurora Lázaro, Olga Bueno, Juan F. León, Jesús Ma Garagorri, Manuel Bueno, Juan Pablo Rey López, Iris Iglesia, Paula Velasco, Silvia Bel.

2. Consejo Superior de Investigaciones Científicas (Spain): Ascensión Marcos, Julia Wärnberg, Esther Nova, Sonia Gómez, Esperanza Ligia Díaz, Javier Romeo, Ana Veses, Mari Angeles Puertollano, Belén Zapatera, Tamara Pozo.

3. Université de Lille 2 (France): Laurent Beghin, Christian Libersa, Frédéric Gottrand, Catalina Iliescu, Juliana Von Berlepsch.

4. Research Institute of Child Nutrition Dortmund, Rheinische Friedrich-Wilhelms-Universität Bonn (Germany): Mathilde Kersting, Wolfgang Sichert-Hellert, Ellen Koeppen.

5. Pécsi Tudományegyetem (University of Pécs) (Hungary): Dénes Molnar, Eva Erhardt, Katalin Csernus, Katalin Török, Szilvia Bokor, Mrs. Angster, Enikö Nagy, Orsolya Kovács, Judit Repásy.

6. University of Crete School of Medicine (Greece): Anthony Kafatos, Caroline Codrington, María Plada, Angeliki Papadaki, Katerina Sarri, Anna Viskadourou, Christos Hatzis, Michael Kiriakakis, George Tsibinos, Constantine Vardavas Manolis Sbokos, Eva Protoyeraki, Maria Fasoulaki.

7. Institut für Ernährungs- und Lebensmittelwissenschaften -Ernährungphysiologie. Rheinische Friedrich Wilhelms Universität (Germany): Peter Stehle, Klaus Pietrzik, Marcela González-Gross, Christina Breidenassel, Andre Spinneker, Jasmin Al-Tahan, Miriam Segoviano, Anke Berchtold, Christine Bierschbach, Erika Blatzheim, Adelheid Schuch, Petra Pickert.

8. University of Granada (Spain): Manuel J. Castillo, Ángel Gutiérrez, Francisco B. Ortega, Jonatan R Ruiz, Enrique G. Artero, Vanesa Espafía-Romero, David Jiménez-Pavón, Palma Chillón, Magdalena Cuenca-Garcia.

9. Istituto Nazionale di Ricerca per gli Alimenti e la Nutrizione (Italy): Davide Arcella, Elena Azzini, Emma Barrison, Noemi Bevilacqua, Pasquale Buonocore, Giovina Catasta, Laura Censi, Donatella Ciarapica, Paola D'Acapito, Marika Ferrari, Myriam Galfo, Cinzia Le Donne, Catherine Leclercq, Giuseppe Maiani, Beatrice Mauro, Lorenza Mistura, Antonella Pasquali, Raffaela Piccinelli, Angela Polito, Raffaella Spada, Stefania Sette, Maria Zaccaria.

10. University of Napoli "Federico II" Dept of Food Science (Italy): Luca Scalfi, Paola Vitaglione, Concetta Montagnese.

11. Ghent University (Belgium): Ilse De Bourdeaudhuij, Stefaan De Henauw, Tineke De Vriendt, Lea Maes, Christophe Matthys, Carine Vereecken, Mieke de Maeyer, Charlene Ottevaere, Inge Huybrechts.

12. Medical University of Vienna (Austria): Kurt Widhalm, Katharina Phillipp, Sabine Dietrich.

13. Harokopio University (Greece): Yannis Manios, Eva Grammatikaki, Zoi Bouloubasi, Tina Louisa Cook, Sofia Eleutheriou, Orsalia Consta, George Moschonis, Ioanna Katsaroli, George Kraniou, Stalo Papoutsou, Despoina Keke, Ioanna Petraki, Elena Bellou, Sofia Tanagra, Kostalenia Kallianoti, Dionysia Argyropoulou, Katerina Kondaki, Stamatoula Tsikrika, Christos Karaiskos.

14. Institut Pasteur de Lille (France): Jean Dallongeville, Aline Meirhaeghe.

15. Karolinska Institutet (Sweden): Michael Sjöstrom, Patrick Bergman, María Hagströmer, Lena Hallström, Märten Hallberg, Eric Poortvliet, Julia Wärnberg, Nico Rizzo, Linda Beckman, Anita Hurtig Wennlöf, Emma Patterson, Lydia Kwak, Lars Cernerud, Per Tillgren, Stefaan Sörensen.

16. Asociación de Investigación de la Industria Agroalimentaria (Spain): Jackie Sánchez-Molero, Elena Picó, Maite Navarro, Blanca Viadel, José Enrique Carreres, Gema Merino, Rosa Sanjuán, María Lorente, María José Sánchez, Sara Castellò.

17. Campden & Chorleywood Food Research Association (United Kingdom): Chantal Gilbert, Sarah Thomas, Elaine Allchurch, Peter Burguess.

18. SIK - Institutet foer Livsmedel och Bioteknik (Sweden): Gunnar Hall, Annika Astrom, Anna Sverkén, Agneta Broberg.

19. Meurice Recherche & Development asbl (Belgium) : Annick Masson, Claire Lehoux, Pascal Brabant, Philippe Pate, Laurence Fontaine.

20. Campden & Chorleywood Food Development Institute (Hungary): Andras Sebok, Tunde Kuti, Adrienn Hegyi.

21. Productos Aditivos SA (Spain): Cristina Maldonado, Ana Llorente.

22. Cárnicas Serrano SL (Spain): Emilio García.

23. Cederroth International AB (Sweden): Holger von Fircks, Marianne Lilja Hallberg, Maria Messerer.

24. Lantmännen Food R&D (Sweden): Mats Larsson, Helena Fredriksson, Viola Adamsson, Ingmar Börjesson.

25. European Food Information Council (Belgium): Laura Fernández, Laura Smillie, Josephine Wills.

26. Universidad Politécnica de Madrid (Spain): Marcela González-Gross, Jara Valtueña, Raquel Pedrero, Gonzalo Palacios, Agustín Meléndez, Pedro J. Benito, Juan José Gómez Lorente, David Cañada, Alejandro Urzanqui, Juan Carlos Ortiz, Francisco Fuentes, David Jiménez-Pavón, Ulrike Albers, Rosa María Torres, Paloma Navarro.

 

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Correspondence:
Gonzalo Palacios.
ImFINE Research Group
Departamento de Salud y Rendimiento Humano.
Facultad de CC de la Actividad Física y del Deporte-INEF.
Universidad Politécnica de Madrid.
c/ Martín Fierro 7, E-28040 Madrid.
E-mail: gonzalo.palacios@upm.es

Recibido: 21-VIII-2014.
Aceptado: 15-IX-2014.