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Being born small-for-gestational-age is associated with an unfavourable dietary intake in Danish adolescent girls: findings from the Danish National Birth Cohort

Published online by Cambridge University Press:  13 November 2018

F. B. Kampmann*
Affiliation:
Centre for Foetal Programming, Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark Division for Diet, Disease Prevention and Toxicology, National Food Institute, Technical University of Denmark, Kgs. Lyngby, Denmark Department of Endocrinology – Diabetes and Metabolism, Rigshospitalet, Copenhagen, Denmark The Danish Diabetes Academy, Odense, Denmark
L. G. Grunnet
Affiliation:
Department of Endocrinology – Diabetes and Metabolism, Rigshospitalet, Copenhagen, Denmark The Danish Diabetes Academy, Odense, Denmark
T. I. Halldorsson
Affiliation:
Centre for Foetal Programming, Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark Unit for Nutrition Research, Landspitali University Hospital and Faculty of Food Science and Nutrition, University of Iceland, Reykjavik, Iceland
A. A. Bjerregaard
Affiliation:
Centre for Foetal Programming, Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
C. Granstrøm
Affiliation:
Centre for Foetal Programming, Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
S. M. Pires
Affiliation:
Division for Diet, Disease Prevention and Toxicology, National Food Institute, Technical University of Denmark, Kgs. Lyngby, Denmark
M. Strøm
Affiliation:
Centre for Foetal Programming, Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark Faculty of Natural and Health Sciences, University of the Faroe Islands, Torshavn, Faroe Islands
A. A. Vaag
Affiliation:
Department of Endocrinology – Diabetes and Metabolism, Rigshospitalet, Copenhagen, Denmark Cardiovascular and Metabolic Disease (CVMD) Translational Medicine Unit, Early Clinical Development, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden
I. Tetens
Affiliation:
Vitality – Centre for Good Older Lives, Department of Nutrition, Sports & Exercise, University of Copenhagen, Denmark
S. F. Olsen
Affiliation:
Centre for Foetal Programming, Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
*
Address of correspondence: F. B. Kampmann, DTU Food, Kemitorvet, Building 202, Kgs. Lyngby, Denmark. E-mail: [email protected]

Abstract

Individuals born small have an increased risk for developing type 2 diabetes. Altered food preferences in these subjects seem to play a role; however, limited evidence is available on the association between being born small-for-gestational-age (SGA) at term and food intake in adolescence. Alterations in leptin, ghrelin and dopamine levels are suggested mechanisms linking SGA with later food intake. From a large prospective Danish National Birth Cohort, we compared dietary intake of adolescents being born SGA with normal-for-gestational-age (NGA) adolescents. Intake of foods and nutrients was assessed by a validated food frequency questionnaire in a subsample of 15,607 14-year-old individuals born at term. SGA was defined by birth weight (BW) <10th percentile (n = 1470) and NGA as BW between 10 and 90th percentile (n = 14,137) according to sex and gestational age-specific BW standard curves. Girls born SGA had a 7% (95% CI: 3–12%, P = 0.002) higher intake of added sugar and a 2–8% lower intake of dietary fibre, vegetables, polyunsaturated fatty acids, and total n−6, compared with NGA girls (P < 0.05). Adjusting for parental socio-occupational status, maternal smoking and diet in pregnancy did not substantially change the differences in dietary intake, except from dietary fibre, which were no longer statistically significant. No significant differences in dietary intake between SGA and NGA boys were found. In summary, girls born SGA had an unfavourable dietary intake compared with NGA girls. These differences persisted after controlling for potential confounders, thus supporting a fetal programming effect on dietary intake in girls born SGA at term. However, residual confounding by other factors operating early in childhood cannot be excluded.

Type
Original Article
Copyright
© Cambridge University Press and the International Society for Developmental Origins of Health and Disease 2018 

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References

Hales, CN, Barker, DJP. The thrifty phenotype hypothesis: Type 2 diabetes. Br Med Bull. 2001; 60, 520.CrossRefGoogle Scholar
Vaag, AA, Grunnet, LG, Arora, GP, Brøns, C. The thrifty phenotype hypothesis revisited. Diabetologia. 2012; 55, 20852088.CrossRefGoogle ScholarPubMed
Gluckman, PD, Hanson, MA, Cooper, C, Thornburg, KL. Effect of in utero and early-life conditions and adult health and disease. N Engl J Med. 2008; 359, 15231524, author reply 1524.CrossRefGoogle ScholarPubMed
Vaag, A, Brøns, C, Gillberg, L, et al. Genetic, nongenetic and epigenetic risk determinants in developmental programming of type 2 diabetes. Acta Obstet Gynecol Scand. 2014; 93, 10991108.CrossRefGoogle ScholarPubMed
Whincup, PH, Kaye, SJ, Owen, CG, et al. Birth weight and risk of type 2 diabetes: a systematic review. J Am Med Assoc. 2008; 300, 28862897.Google ScholarPubMed
Portella, AK, Kajantie, E, Hovi, P, et al. Effects of in utero conditions on adult feeding preferences. J Dev Orig Health Dis. 2012; 3, 140152.CrossRefGoogle ScholarPubMed
Molle, RD, Bischoff, A, Portella, A, Silveira, P. The fetal programming of food preferences: current clinical and experimental evidence. J Dev Orig Health Dis. 2015; 7, 19.Google Scholar
Barbieri, MA, Portella, AK, Silveira, PP, et al. Higher spontaneous carbohydrate intake in young women. Pediatr Res. 2009; 65, 215220.CrossRefGoogle ScholarPubMed
Crume, TL, Scherzinger, A, Stamm, E, et al. The long-term impact of intrauterine growth restriction in a diverse U.S. cohort of children: the EPOCH study. Obesity (Silver Spring). 2014; 22, 608615.CrossRefGoogle Scholar
Lussana, F, Painter, RC, Ocke, MC, et al. Prenatal exposure to the Dutch famine is associated with a preference for fatty foods and a more atherogenic lipid profile. Am J Clin Nutr. 2008; 88, 16481652.CrossRefGoogle Scholar
Stein, AD, Rundle, A, Wada, N, Goldbohm, RA, Lumey, LH. Associations of gestational exposure to famine with energy balance and macronutrient density of the diet at age 58 years differ according to the reference population used. J Nutr. 2009; 139, 15551561.CrossRefGoogle Scholar
Perälä, M-M, Männistö, S, Kaartinen, NE, et al. Body size at birth is associated with food and nutrient intake in adulthood. PLoS One. 2012; 7, e46139.CrossRefGoogle ScholarPubMed
Kaseva, N, Wehkalampi, K, Hemiö, K, et al. Diet and nutrient intake in young adults born preterm at very low birth weight. J Pediatr. 2013; 163, 4348.CrossRefGoogle ScholarPubMed
Bellinger, L, Lilley, C, Langley-Evans, SC. Prenatal exposure to a maternal low-protein diet programmes a preference for high-fat foods in the young adult rat. Br J Nutr. 2004; 92, 513520.CrossRefGoogle ScholarPubMed
Krechowec, SO, Vickers, MH, Breier, BH. Fetal programming of postnatal phenotype and obesity – experimental evidence from biomedical research. Proc New Zeal Soc Anim Prod. 2004; 64, 2429.Google Scholar
Ayres, C, Agranonik, M, Portella, AK, et al. Intrauterine growth restriction and the fetal programming of the hedonic response to sweet taste in newborn infants. Int J Pediatr. 2012; 2012, 657379.CrossRefGoogle ScholarPubMed
Malik, VS, Fung, TT, van Dam, RM, et al. Dietary patterns during adolescence and risk of type 2 diabetes in middle-aged women. Diabetes Care. 2012; 35, 1218.CrossRefGoogle ScholarPubMed
Naja, F, Hwalla, N, Itani, L, et al. A Western dietary pattern is associated with overweight and obesity in a national sample of Lebanese adolescents (13–19 years): a cross-sectional study. Br J Nutr. 2015; 114, 19091919.CrossRefGoogle Scholar
Wiium, N, Breivik, K, Wold, B. Growth trajectories of health behaviors from adolescence through young adulthood. Int J Environ Res Public Health. 2015; 12, 1371113729.CrossRefGoogle ScholarPubMed
Pedersen, AN, Christensen, T, Matthiessen, J, et al. Dietary Habits in Denmark 2011–2013. Main Results. 2015. National Food Institute, Technical University of Denmark: Søborg, Denmark.Google Scholar
Westenhoefer, J. Age and gender dependent profile of food choice. Forum Nutr. 2005; 57, 4451.CrossRefGoogle Scholar
Salvy, S, Elmo, A, Nitecki, LA, Kluczynski, MA, Roemmich, JN. Influence of parents and friends on children’s and adolescents’ food intake and food selection 1–3. Am Soc Nutr. 2011; 93, 8792.Google Scholar
Olsen, J, Melbye, M, Olsen, SF, et al. The Danish National Birth Cohort – its background, structure and aim. Scand J Public Health. 2001; 29, 300307.CrossRefGoogle ScholarPubMed
Nordic Nutrition Recommendations 2012. Integrating nutrition and physical activity, 2014.Google Scholar
Knudsen, LB, Olsen, J. The Danish Medical Birth Registry. Dan Med Bull. 1998; 45, 320323.Google ScholarPubMed
Bjerregaard, AA, Halldorsson, TI, Kampmann, FB, Olsen, SF, Tetens, I. Relative validity of a web-based food frequency questionnaire for Danish adolescents. Nutr J. 2018; 17, 9.CrossRefGoogle ScholarPubMed
Bjerregaard, AA, Tetens, I, Olsen, SF, Halldorsson, TI. Reproducibility of a web-based FFQ for 13- to 15-year-old Danish adolescents. J Nutr Sci. 2016; 5, e5.CrossRefGoogle ScholarPubMed
Ygil, KH. Mål, vaegt og portionsstørrelser (Dimensions, Weight and Portion sizes of Foods), 2013.Google Scholar
Lauritsen, J. FoodCalc, 2014. Available at: http://www.ibt.ku.dk/jesper/foodcalc/ Google Scholar
Data, Danish Food Composition, 2015. Retrieved 1 May 2015 from http://www.foodcomp.dk Google Scholar
Hauner, H, Bechthold, A, Boeing, H, et al. Evidence-based guideline of the German Nutrition Society: carbohydrate intake and prevention of nutrition-related diseases. Ann Nutr Metab. 2012; 60, 158.CrossRefGoogle ScholarPubMed
Ye, EQ, Chacko, SA, Chou, EL, Kugizaki, M, Liu, S. Greater whole-grain intake is associated with lower risk of type 2 diabetes, cardiovascular disease, and weight gain. J Nutr. 2013; 142, 13.Google Scholar
Mann, JI, De Leeuw, I, Hermansen, K, et al. Evidence-based nutritional approaches to the treatment and prevention of diabetes mellitus. Nutr Metab Cardiovasc Dis. 2004; 14, 373394.CrossRefGoogle ScholarPubMed
Sylvia, H, Hamdy, O, Mohan, V, Hu, B. Prevention and management of type 2 diabetes: dietary components and nutritional strategies. Lancet. 2014; 383, 19992007.Google Scholar
Schwingshackl, L, Hoffmann, G, Lampousi, A-M, et al. Food groups and risk of type 2 diabetes mellitus: a systematic review and meta-analysis of prospective studies. Eur J Epidemiol. 2017; 32, 363375.CrossRefGoogle ScholarPubMed
Malik, VS, Popkin, BM, Bray, GA, et al. Sugar-sweetened beverages and risk of metabolic syndrome and type 2 diabetes a meta-analysis. Diabetes Care. 2010; 33, 24772483.CrossRefGoogle ScholarPubMed
Pan, A, Sun, Q, Bernstein, AM, et al. Red meat consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta-analysis. Am J Clin Nutr. 2011; 94, 10881096.CrossRefGoogle ScholarPubMed
Riediger, ND, Shooshtari, S, Moghadasian, MH. The influence of sociodemographic factors on patterns of fruit and vegetable consumption in Canadian adolescents. J Am Diet Assoc. 2007; 107, 15111518.CrossRefGoogle ScholarPubMed
Räisänen, S, Gissler, M, Sankilampi, U, et al. Contribution of socioeconomic status to the risk of small for gestational age infants – a population-based study of 1,390,165 singleton live births in Finland. Int J Equity Health. 2013; 12, 28.CrossRefGoogle ScholarPubMed
Phung, H, Bauman, A, Nguyen, TV, et al. Risk factors for low birth weight in a socio-economically disadvantaged population: parity, marital status, ethnicity and cigarette smoking. Eur J Endocrinol. 2017; 18, 235243.Google Scholar
Mennella, JA, Jagnow, CP, Beauchamp, GK. Prenatal and postnatal flavor learning by human infants. Pediatrics. 2001; 107, e88e88.CrossRefGoogle ScholarPubMed
Silveira, PP, Agranonik, M, Faras, H, et al. Preliminary evidence for an impulsivity-based thrifty eating phenotype. Pediatr Res. 2012; 71, 293298.CrossRefGoogle ScholarPubMed
Shultis, WA, Leary, SD, Ness, AR, et al. Does birth weight predict childhood diet in the Avon longitudinal study of parents and children? J Epidemiol Community Health. 2005; 59, 955960.CrossRefGoogle ScholarPubMed
Stafford, M, Lucas, A. Possible association between low birth weight and later heart disease needs to be investigated further. BMJ. 1998; 316, 12471248.CrossRefGoogle Scholar
Epel, E, Lapidus, R, McEwen, B, Brownell, K. Stress may add bite to appetite in women: a laboratory study of stress-induced cortisol and eating behavior. Psychoneuroendocrinology. 2001; 26, 3749.CrossRefGoogle ScholarPubMed
Montano, M, Wang, M, vom Saal, F. Sex differences in plasma corticosterone in mouse fetuses are mediated by differential placental transport from the mother and eliminated by maternal adrenalectomy or stress. J Reprod Fertil. 1993; 99, 283290.CrossRefGoogle ScholarPubMed
Block, T, El-Osta, A. Epigenetic programming, early life nutrition and the risk of metabolic disease. Atherosclerosis. 2017; 266, 3140.CrossRefGoogle ScholarPubMed
Salas-Salvad, J, Martinez-González, M, Bulló, M, Ros, E. The role of diet in the prevention of type 2 diabetes. Nutr Metab Cardiovasc Dis. 2011; 21, 3248.CrossRefGoogle Scholar
Te Morenga, L, Mallard, S, Mann, J. Dietary sugars and body weight: systematic review and meta-analyses of randomised controlled trials and cohort studies. BMJ. 2012; 346, e7492.CrossRefGoogle ScholarPubMed
Hjort, L, Jørgensen, SW, Gillberg, L, et al. 36 h fasting of young men influences adipose tissue DNA methylation of LEP and ADIPOQ in a birth weight-dependent manner. Clin Epigenetics. 2017; 9, 40.CrossRefGoogle Scholar
Phillips, DIW, Fall, CHD, Cooper, C, et al. Size at birth and plasma leptin concentrations in adult life. Int J Obes. 1999; 23, 10251029.CrossRefGoogle ScholarPubMed
Jornayvaz, FR, Vollenweider, P, Bochud, M, et al. Low birth weight leads to obesity, diabetes and increased leptin levels in adults: the CoLaus study. Cardiovasc Diabetol. 2016; 15, 73.CrossRefGoogle ScholarPubMed
Shigemura, N, Ohta, R, Kusakabe, Y, et al. Leptin modulates behavioral responses to sweet substances by influencing peripheral taste structures. Endocrinology. 2004; 145, 839847.CrossRefGoogle ScholarPubMed
Umabiki, M, Tsuzaki, K, Kotani, K, et al. The improvement of sweet taste sensitivity with decrease in serum leptin levels during weight loss in obese females. Tohoku J Exp Med. 2010; 220, 267271.CrossRefGoogle ScholarPubMed
Navarro-Allende, A, Khataan, N, El-Sohemy, A. Impact of genetic and environmental determinants of taste with food preferences in older adults. J Nutr Elder. 2008; 27, 267276.CrossRefGoogle ScholarPubMed
Livingstone, MB, Robson, P. Measurement of dietary intake in children. Nut Proc Soc. 2000; 59, 279293.CrossRefGoogle ScholarPubMed
Birch, L, Arbor, A, Savage, JS, Ventura, A. From infancy to adolescence. Can J Diet Pr Res. 2009; 68, 111.Google Scholar
Ayres, C, Silveira, PP, Barbieri, MA, et al. Exposure to maternal smoking during fetal life affects food preferences in adulthood independent of the effects of intrauterine growth restriction. J. Dev. Orig. Health Dis. 2011; 2, 162167.CrossRefGoogle ScholarPubMed
Li, Y, Ley, SH, Tobias, DK, et al. Birth weight and later life adherence to unhealthy lifestyles in predicting type 2 diabetes: prospective cohort study. BMJ. 2015; 351, h3672.CrossRefGoogle ScholarPubMed
Biró, G, Hulshof, KFAM, Ovesen, L, Amorim Cruz, JA. Selection of methodology to assess food intake. Eur J Clin Nutr. 2002; 56(Suppl 2), S25S32.CrossRefGoogle ScholarPubMed