Pediatric Original Article | Published:

Does the FTO gene interact with the socioeconomic status on the obesity development among young European children? Results from the IDEFICS study

International Journal of Obesity volume 39, pages 16 (2015) | Download Citation

Abstract

Background:

Various twin studies revealed that the influence of genetic factors on psychological diseases or behaviour is more expressed in socioeconomically advantaged environments. Other studies predominantly show an inverse association between socioeconomic status (SES) and childhood obesity in Western developed countries. The aim of this study is to investigate whether the fat mass and obesity-associated (FTO) gene interacts with the SES on childhood obesity in a subsample (N=4406) of the IDEFICS (Identification and prevention of Dietary- and lifestyle-induced health EFfects In Children and infantS) cohort.

Methods:

A structural equation model (SEM) is applied with the latent constructs obesity, dietary intakes, physical activity and fitness habits, and parental SES to estimate the main effects of the latter three variables and a FTO polymorphism on childhood obesity. Further, a multiple group SEM is used to explore whether an interaction effect exists between the single nucleotide polymorphism rs9939609 within the FTO gene and SES.

Results:

Significant main effects are shown for physical activity and fitness (standardised β̂s = −0.113), SES (β̂s = −0.057) and the FTO homozygous AA risk genotype (β̂s = −0.177). The explained variance of obesity is ~9%. According to the multiple group approach of SEM, we see an interaction between SES and FTO with respect to their effect on childhood obesity (Δχ2=7.3, df=2, P=0.03).

Conclusion:

Children carrying the protective FTO genotype TT seem to be more protected by a favourable social environment regarding the development of obesity than children carrying the AT or AA genotype.

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References

  1. 1.

    , . Environmental contributions to the obesity epidemic. Science 1998; 280: 1371–1374.

  2. 2.

    , , , , . Socioeconomic status modifies heritability of IQ in young children. Psychol Sci 2003; 14: 623–628.

  3. 3.

    , , . Heritability for adolescent antisocial behavior differs with socioeconomic status: gene–environment interaction. J Child Psychol Psychiatry 2006; 47: 734–743.

  4. 4.

    , , , , , et al. Influence of maternal educational level on the association between the rs3809508 neuromedin B gene polymorphism and the risk of obesity in the HELENA study. Int J Obes 2010; 34: 478–486.

  5. 5.

    , , . Epidemiology of Obesity in Children and Adolescents – Prevalence and Etiology, chapter 26. Springer, 2011, pp 483–492.

  6. 6.

    , , , , , et al. IDEFICS Consortium. The IDEFICS cohort: design, characteristics and participation in the baseline survey. Int J Obes 2011; 35(Suppl 1): S3–S15.

  7. 7.

    , , , , , et al. IDEFICS Consortium. Prospective analysis of the association of a common variant of FTO (rs9939609) with adiposity in children: results of the IDEFICS study. PLoS One 2012; 7: e48876.

  8. 8.

    . Structural equation models with latent variables. John Wiley & Sons: New York, 1989.

  9. 9.

    , , , , , et al. IDEFICS Consortium Socioeconomic factors and childhood overweight in Europe: results from the multi-centre IDEFICS study. Pediatr Obes 2013; 8: 1–12.

  10. 10.

    , , , , . Calibration of two objective measures of physical activity for children. J Sports Sci 2008; 26: 1557–1565.

  11. 11.

    , , . Body mass index reference curves for the UK, 1990. Arch Dis Child 1995; 73: 25–29.

  12. 12.

    , , . British 1990 growth reference centiles for weight, height, body mass index and head circumference fitted by maximum penalized likelihood. Stat Med 1998; 17: 407–429.

  13. 13.

    , , , , , . Foot-to-foot bioelectrical impedance analysis: a valuable tool for the measurement of body composition in children. Int J Obes Relat Metab Disord 2001; 25: 273–278.

  14. 14.

    . Confirmatory factor analysis. Guilford: New York, 2006.

  15. 15.

    , , . Testing differences between nested covariance structure models: power analysis and null hypotheses. Psychol Methods 2006; 11: 19–35.

  16. 16.

    . Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equ Modeling 1999; 6: 1–55.

  17. 17.

    , , . Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes. Struct Equ Modeling 1999; 6: 56–83.

  18. 18.

    , , , , . Effect of environmental and genetic factors on education-associated disparities in weight and weight gain: a study of Finnish adult twins. Am J Clin Nutr 2004; 80: 815–822.

  19. 19.

    , . Unfavorable socioeconomic conditions in early life presage expression of proinflammatory phenotype in adolescence. Psychosom Med 2007; 69: 402–409.

  20. 20.

    , , , , , et al. Computational identification of gene–social environment interaction at the human IL6 locus. Proc Natl Acad Sci 2010; 107: 5681–5686.

  21. 21.

    , , , , , . Education reduces the effects of genetic susceptibilities to poor physical health. Int J Epidemiol 2010; 39: 406–414.

  22. 22.

    , , , , , et al. Lifestyle and socioeconomic-status modify the effects of ADRB2 and NOS3 on adiposity in European-American and African-American adolescents. Obesity 2011; 19: 595–603.

  23. 23.

    , , , , , et al. Éducation modulates the association of the FTO rs9939609 polymorphism with body mass index and obesity risk in the Mediterranean population. Nutr Metab Cardiovasc Dis 2012; 22: 651–658.

  24. 24.

    , , , , , et al. First investigation of two obesity-related loci (TMEM18, FTO) concerning their association with educational level as well as income: the MONICA/KORA study. J Epidemiol Community Health 2011; 65: 174–176.

  25. 25.

    , , , , , et al. Low physical activity accentuates the effect of the FTO rs9939609 polymorphism on body fat accumulation. Diabetes 2008; 57: 95–101.

  26. 26.

    , , , , , et al. Physical activity attenuates the body mass index–increasing influence of genetic variation in the FTO gene. Am J Clin Nutr 2009; 90: 425–428.

  27. 27.

    , , , , , et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 2007; 316: 889–894.

  28. 28.

    , , , , , et al. Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits. PLoS Genet 2007; 3: e115.

  29. 29.

    , , , , . An obesity-associated FTO gene variant and increased energy intake in children. N Engl J Med 2008; 359: 2558–2566.

  30. 30.

    , , , , , et al. Impact of variation in the FTO gene on whole body fat distribution, ectopic fat, and weight loss. Obesity 2008; 16: 1969–1972.

  31. 31.

    , , , , , et al. Obesity genes identified in genome-wide association studies are associated with adiposity measures and potentially with nutrient-specific food preference. Am J Clin Nutr 2009; 90: 951–959.

  32. 32.

    , , , . The mouse Fused toes (Ft) mutation is the result of a 1.6-Mb deletion including the entire Iroquois B gene cluster. Mamm Genome 2002; 13: 186–188.

  33. 33.

    , , , , . Where to go with FTO? Trends Endocrinol Metab 2011; 22: 53–59.

  34. 34.

    , , , , , et al. Variation in FTO contributes to childhood obesity and severe adult obesity. Nat Genet 2007; 39: 724–726.

  35. 35.

    , , , , , et al. The obesity gene, FTO, is of ancient origin, up-regulated during food deprivation and expressed in neurons of feeding-related nuclei of the brain. Endocrinology 2008; 149: 2062–2071.

  36. 36.

    , . From GWAS to biology: lessons from FTO. Ann NY Acad Sci 2011; 1220: 162–171.

  37. 37.

    , . Is there a genetic contribution to cultural differences? Collectivism, individualism and genetic markers of social sensitivity. Soc Cogn Affect Neurosci 2010; 5: 203–211.

  38. 38.

    , . The global childhood obesity epidemic and the association between socio-economic status and childhood obesity. Int Rev Psychiatry 2012; 24: 176–188.

  39. 39.

    , , , , , . Television watching, energy intake, and obesity in US children: results from the third National Health and Nutrition Examination Survey, 1988-1994. Arch Pediatr Adolesc Med 2001; 155: 360–365.

  40. 40.

    , , , , , et al. IDEFICS Consortium Diet–obesity associations in children: approaches to counteract attenuation caused by misreporting. Public Health Nutr 2012; 16: 256–266.

  41. 41.

    . The evolution of human adiposity and obesity: where did it all go wrong? Dis Model Mech 2012; 5: 595–607.

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Acknowledgements

This work was done as part of the IDEFICS Study (www.idefics.eu). We gratefully acknowledge the financial support of the European Community within the Sixth RTD Framework Program Contract No. 016181 (FOOD). We thank the IDEFICS children and their parents for taking the time to participate in this extensive examination programme. We are grateful for the support provided by school boards, headmasters, teachers, school staff and communities, and for the effort of all study nurses and our data managers, especially Claudia Brünings-Kuppe and Birgit Reineke.

Author information

Author notes

    • R Foraita
    •  & F Günther

    These authors contributed equally to this work.

Affiliations

  1. Leibniz Institute for Prevention Research and Epidemiology—BIPS, Bremen, Germany

    • R Foraita
    • , F Günther
    • , K Bammann
    •  & I Pigeot
  2. Copenhagen Business School, Department of Intercultural Communication and Management, Frederiksberg, Denmark

    • W Gwozdz
    •  & L A Reisch
  3. Epidemiology & Population Genetics, Institute of Food Sciences—CNR, Avellino, Italy

    • P Russo
    • , F Lauria
    •  & A Siani
  4. Department of Chronic Diseases, National Institute for Health Development, Tallinn, Estonia

    • T Veidebaum
  5. Research and Education Institute of Child Health, Strovolos, Cyprus

    • M Tornaritis
  6. Department of Epidemiology and Prevention, IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli (IS)

    • L Iacoviello
  7. Department of Public Health, Ghent University, Ghent, Belgium

    • K Vyncke
  8. Research Foundation Flanders, Brussels, Belgium

    • K Vyncke
  9. University of Brighton, School of Sport and Service Management, Eastbourne, UK

    • Y Pitsiladis
  10. Department of Pediatrics, University of Gothenburg, Institution of clinical sciences, Gothenburg, Sweden

    • S Mårild
  11. Department of Pediatrics, University of Pécs, Pécs, Hungary

    • D Molnár
  12. University of Zaragoza, Growth, Exercise, Nutrition and Development (GENUD) Research Group, Zaragoza, Spain

    • L A Moreno
  13. University of Bremen, Institute of Public Health and Nursing Science (IPP), Bremen, Germany

    • K Bammann
  14. University of Bremen, Faculty 03: Mathematics/Computer Science, Bremen, Germany

    • I Pigeot

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Competing interests

The authors declare no conflict of interest.

Corresponding author

Correspondence to R Foraita.

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DOI

https://doi.org/10.1038/ijo.2014.156

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