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Associations of dietary energy density with body composition and cardiometabolic risk in children with overweight and obesity: role of energy density calculations, under-reporting energy intake and physical activity

  • Alejandro Gomez-Bruton (a1) (a2), Lide Arenaza (a3), Maria Medrano (a3), Jose Mora-Gonzalez (a4), Cristina Cadenas-Sanchez (a4), Jairo H. Migueles (a4), Victoria Muñoz-Hernández (a4), Elisa Merchan-Ramirez (a4), Wendy Daniela Martinez-Avila (a4), Jose Maldonado (a5) (a6), Maddi Oses (a3), Ignacio Tobalina (a7) (a8), Luis Gracia-Marco (a1) (a4), German Vicente-Rodriguez (a1) (a2), Francisco B. Ortega (a4) and Idoia Labayen (a3)...


This study examined (1) the association of dietary energy density from solid (EDS) and solid plus liquids (EDSL) with adiposity and cardiometabolic risk factors (CRF) in children with overweight and obesity, (2) the effect of under-reporting on the mentioned associations and (3) whether the association between ED and body composition and CRF is influenced by levels of physical activity. In a cross-sectional design, 208 overweight and obese children (8–12-year-old; 111 boys) completed two non-consecutive 24 h recalls. ED was calculated using two different approaches: EDS and EDSL. Under-reporters were determined with the Goldberg method. Body composition, anthropometry and fasting blood sample measurements were performed. Moderate to vigorous physical activity (MVPA) was registered with accelerometers (7-d-register). Linear regressions were performed to evaluate the association of ED with the previously mentioned variables. Neither EDS nor EDSL were associated with body composition or CRF. However, when under-reporters were excluded, EDS was positively associated with BMI (P=0·019), body fat percentage (P=0·005), abdominal fat (P=0·008) and fat mass index (P=0·018), while EDSL was positively associated with body fat percentage (P=0·008) and fat mass index (P=0·026). When stratifying the group according to physical activity recommendations, the aforementioned associations were only maintained for non-compliers. Cluster analysis showed that the low-ED and high-MVPA group presented the healthiest profile for all adiposity and CRF. These findings could partly explain inconsistencies in literature, as we found that different ED calculations entail distinct results. Physical activity levels and excluding under-reporters greatly influence the associations between ED and adiposity in children with overweight and obesity.


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*Corresponding author: A. Gomez-Bruton, email


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1. Geiß, H, Parhofer, K & Schwandt, P (2001) Parameters of childhood obesity and their relationship to cardiovascular risk factors in healthy prepubescent children. Int J Obes 25, 830837.
2. Gibson, LY, Allen, KL, Davis, E, et al. (2017) The psychosocial burden of childhood overweight and obesity: evidence for persisting difficulties in boys and girls. Eur J Pediatr 176, 925933.
3. Taylor, ED, Theim, KR, Mirch, MC, et al. (2006) Orthopedic complications of overweight in children and adolescents. Pediatrics 117, 21672174.
4. Singh, AS, Mulder, C, Twisk, JWR, et al. (2008) Tracking of childhood overweight into adulthood: a systematic review of the literature. Obes Rev 9, 474488.
5. Schwingshackl, L, Hoffmann, G, Kalle-Uhlmann, T, et al. (2015) Fruit and vegetable consumption and changes in anthropometric variables in adult populations: a systematic review and meta-analysis of prospective cohort studies. PLOS ONE 10, e0140846.
6. Brauchla, M, Juan, W, Story, J, et al. (2012) Sources of dietary fiber and the association of fiber intake with childhood obesity risk (in 2–18 year olds) and diabetes risk of adolescents 12–18 year olds: NHANES 2003–2006. J Nutr Metab 2012, 736258.
7. Luger, M, Lafontan, M, Bes-Rastrollo, M, et al. (2017) Sugar-sweetened beverages and weight gain in children and adults: a systematic review from 2013 to 2015 and a comparison with previous studies. Obes Facts 10, 674693.
8. Rouhani, MH, Haghighatdoost, F, Surkan, PJ, et al. (2016) Associations between dietary energy density and obesity: a systematic review and meta-analysis of observational studies. Nutrition 32, 10371047.
9. Alexy, U, Sichert-Hellert, W, Kersting, M, et al. (2004) Pattern of long-term fat intake and BMI during childhood and adolescence – results of the DONALD study. Int J Obes 28, 12031209.
10. Alexy, U, Libuda, L, Mersmann, S, et al. (2011) Convenience foods in children’s diet and association with dietary quality and body weight status. Eur J Clin Nutr 65, 160166.
11. Ambrosini, GL, Emmett, PM, Northstone, K, et al. (2012) Identification of a dietary pattern prospectively associated with increased adiposity during childhood and adolescence. Int J Obes 36, 12991305.
12. Butte, NF, Cai, G, Cole, SA, et al. (2007) Metabolic and behavioral predictors of weight gain in Hispanic children: the Viva la Familia Study. Am J Clin Nutr 85, 14781485.
13. Günther, ALB, Stahl, LJ, Buyken, AE, et al. (2011) Association of dietary energy density in childhood with age and body fatness at the onset of the pubertal growth spurt. Br J Nutr 106, 345349.
14. Hebestreit, A, Börnhorst, C, Barba, G, et al. (2014) Associations between energy intake, daily food intake and energy density of foods and BMI z-score in 2–9-year-old European children. Eur J Nutr 53, 673681.
15. Donin, AS, Nightingale, CM, Owen, CG, et al. (2014) Dietary energy intake is associated with type 2 diabetes risk markers in children. Diabetes Care 37, 116123.
16. Skinner, AC, Perrin, EM, Moss, LA, et al. (2015) Cardiometabolic risks and severity of obesity in children and young adults. N Engl J Med 373, 13071317.
17. McCaffrey, TC, Rennie, KL, Kerr, MA, et al. (2008) Energy density of the diet and change in body fatness from childhood to adolescence; is there a relation? Am J Clin Nutr 87, 12301237.
18. Kral, TVE, Berkowitz, RI, Stunkard, AJ, et al. (2007) Dietary energy density increases during early childhood irrespective of familial predisposition to obesity: results from a prospective cohort study. Int J Obes 31, 10611067.
19. Vernarelli, JA, Mitchell, DC, Hartman, TJ, et al. (2011) Dietary energy density is associated with body weight status and vegetable intake in U.S. children. J Nutr 141, 22042210.
20. O’Sullivan, TA, Bremner, AP, Bremer, HK, et al. (2015) Dairy product consumption, dietary nutrient and energy density and associations with obesity in Australian adolescents. J Hum Nutr Diet 28, 452464.
21. Murakami, K, Miyake, Y, Sasaki, S, et al. (2012) An energy-dense diet is cross-sectionally associated with an increased risk of overweight in male children, but not in female children, male adolescents, or female adolescents in Japan: the Ryukyus Child Health Study. Nutr Res 32, 486494.
22. Shephard, RJ. (2003) Limits to the measurement of habitual physical activity by questionnaires – Commentary. Br J Sports Med 37, 197206.
23. Aburto, TC, Cantoral, A, Hernández-Barrera, L, et al. (2015) Usual dietary energy density distribution is positively associated with excess body weight in Mexican children. J Nutr 145, 15241530.
24. Gomes, D, Luque, V, Xhonneux, A, et al. (2017) A simple method for identification of misreporting of energy intake from infancy to school age: results from a longitudinal study. Clin Nutr 37, 10531060.
25. Murakami, K, Miyake, Y, Sasaki, S, et al. (2012) Characteristics of under- and over-reporters of energy intake among Japanese children and adolescents: the Ryukyus Child Health Study. Nutrition 28, 532538.
26. Cadenas-Sánchez, C, Mora-González, J, Migueles, JH, et al. (2016) An exercise-based randomized controlled trial on brain, cognition, physical health and mental health in overweight/obese children (ActiveBrains project): rationale, design and methods. Contemp Clin Trials 47, 315324.
27. Medrano, M, Maiz, E, Maldonado-Martín, S, et al. (2015) The effect of a multidisciplinary intervention program on hepatic adiposity in overweight-obese children: protocol of the EFIGRO study. Contemp Clin Trials 45, 346355.
28. Cole, TJ & Lostein, T (2012) Extended international (IOTF) body mass indez cut-offs for thiness, overweight and obesity. Pediatr Obes 7, 284294.
29. Moliner-Urdiales, D, Ruiz, JR, Vicente-Rodriguez, G, et al. (2011) Associations of muscular and cardiorespiratory fitness with total and central body fat in adolescents: the HELENA study. Br J Sports Med 45, 101108.
30. EFSA (2014) Guidance on the EU menu methodology. EFSA J 12, 3944.
31. Goldberg, GR, Black, AE, Jebb, SA, et al. (1991) Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify under-recording. Eur J Clin Nutr 45, 569581.
32. Black, AE (2000) Critical evaluation of energy intake using the Goldberg cut-off for energy intake: basal metabolic rate. A practical guide to its calculation, use and limitations. Int J Obes Relat Metab Disord 24, 11191130.
33. Lazzer, S, Patrizi, A, De Col, A, et al. (2014) Prediction of basal metabolic rate in obese children and adolescents considering pubertal stages and anthropometric characteristics or body composition. Eur J Clin Nutr 68, 695699.
34. Schofield, WN (1985) Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 39, Suppl. 1, 541.
35. Tooze, JA, Krebs-Smith, SM, Troiano, RP, et al. (2012) The accuracy of the Goldberg method for classifying misreporters of energy intake on a food frequency questionnaire and 24-h recalls: comparison with doubly labeled water. Eur J Clin Nutr 66, 569576.
36. Nyström, CD, Henriksson, P, Martínez-Vizcaíno, V, et al. (2017) Does cardiorespiratory fitness attenuate the adverse effects of severe/morbid obesity on cardiometabolic risk and insulin resistance in children? A pooled analysis. Diabetes Care 40, 15801587.
37. van Hees, VT, Fang, Z, Langford, J, et al. (2014) Autocalibration of accelerometer data for free-living physical activity assessment using local gravity and temperature: an evaluation on four continents. J Appl Physiol 117, 738744.
38. Migueles, JH, Cadenas-Sanchez, C, Ekelund, U, et al. (2017) Accelerometer data collection and processing criteria to assess physical activity and other outcomes: a systematic review and practical considerations. Sport Med 47, 18211845.
39. Van Hees, VT, Sabia, S, Anderson, KN, et al. (2015) A novel, open access method to assess sleep duration using a wrist-worn accelerometer. PLOS ONE 10, e0142533.
40. Hildebrand, M, Van Hees, VT, Hansen, BH, et al. (2014) Age group comparability of raw accelerometer output from wrist-and hip-worn monitors. Med Sci Sports Exerc 46, 18161824.
41. van Ansem, WJ, Schrijvers, CT, Rodenburg, G, et al. (2014) Maternal educational level and children’s healthy eating behaviour: role of the home food environment (cross-sectional results from the INPACT study). Int J Behav Nutr Phys Act 11, 113.
42. Tanner, JM & Whitehouse, RH (1976) Clinical longitudinal standards for height, weight, height velocity, weight velocity, and stages of puberty. Arch Dis Child 51, 170179.
43. World Health Organization (2010) Global Recommendations on Physical Activity for Health. Geneva: WHO.
44. Prokasky, A, Rudasill, K, Molfese, VJ, et al. (2017) Identifying child temperament types using cluster analysis in three samples. J Res Pers 67, 190201.
45. Sanson, A, Letcher, P, Smart, D, et al. (2009) Associations between early childhood temperament clusters and later psychosocial adjustment. Merrill Palmer Quart 55, 2654.
46. Eshghi, A, Haughton, D, Legrand, P, et al. (2011) Identifying groups: a comparison of methodology. J Data Sci 9, 271291.
47. Johnson, L, Wilks, DC, Lindroos, AK, et al. (2009) Reflections from a systematic review of dietary energy density and weight gain: is the inclusion of drinks valid? Obes Rev 10, 681692.
48. Yin, J, Xue, H, Chen, Y, et al. (2018) Dietary energy density is positively associated with body composition of adults in Southwest China. Public Health Nutr 21, 18271834.
49. DiMeglio, DP & Mattes, RD (2000) Liquid versus solid carbohydrate: effects on food intake and body weight. Int J Obes Relat Metab Disord 24, 794800.
50. Schröder, H, Mendez, MA, Gomez, SF, et al. (2013) Energy density, diet quality, and central body fat in a nationwide survey of young Spaniards. Nutrition 29, 13501355.
51. Günther, ALB, Stahl, LJ, Buyken, AE, et al. (2011) Association of dietary energy density in childhood with age and body fatness at the onset of the pubertal growth spurt. Br J Nutr 106, 345349.
52. Johnson, L, Mander, AP, Jones, LR, et al. (2008) A prospective analysis of dietary energy density at age 5 and 7 years and fatness at 9 years among UK children. Int J Obes 32, 586593.
53. Johnson, L, van Jaarsveld, CHM, Emmett, PM, et al. (2009) Dietary energy density affects fat mass in early adolescence and is not modified by FTO variants. PLoS ONE 4, e4594.
54. Appannah, G, Pot, GK, Huang, RC, et al. (2015) Identification of a dietary pattern associated with greater cardiometabolic risk in adolescence. Nutr Metab Cardiovasc Dis 25, 643650.
55. Hallal, PC, Andersen, LB, Bull, FC, et al. (2012) Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet 380, 247257.
56. Hoffmann, DA, Marx, JM, Burmeister, JM, et al. (2018) Friday night is pizza night: a comparison of children’s dietary intake and maternal perceptions and feeding goals on weekdays and weekends. Int J Environ Res Public Health 15, 720.
57. Kerr, A, Slater, GJ & Byrne, N (2017) Impact of food and fluid intake on technical and biological measurement error in body composition assessment methods in athletes. Br J Nutr 117, 591601.
58. Martinez-Vizcaino, V, Martinez, MS, Aguilar, FS, et al. (2010) Validity of a single-factor model underlying the metabolic syndrome in children: a confirmatory factor analysis. Diabetes Care 33, 13701372.
59. Alberti, KGMM, Eckel, RH, Grundy, SM, et al. (2009) Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 120, 16401645.



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