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Longitudinal trends in and tracking of energy and nutrient intake over 20 years in a Dutch cohort of men and women between 13 and 33 years of age: The Amsterdam growth and health longitudinal study

Published online by Cambridge University Press:  09 March 2007

G. Bertheke Post ,
Wieke de Vente ,
Han C. G. Kemper  and
Jos W. R. Twisk
G. Bertheke Post
Affiliation:
Institute for Research in Extramural Medicine, Amsterdam Growth and Health Research Group, Faculty of Medicine, Vrije Universiteit, vd Boechorststraat 7, 1081 BT Amsterdam, The Netherlands
Wieke de Vente
Affiliation:
Institute for Research in Extramural Medicine, Amsterdam Growth and Health Research Group, Faculty of Medicine, Vrije Universiteit, vd Boechorststraat 7, 1081 BT Amsterdam, The Netherlands
Jos W. R. Twisk
Affiliation:
Institute for Research in Extramural Medicine, Amsterdam Growth and Health Research Group, Faculty of Medicine, Vrije Universiteit, vd Boechorststraat 7, 1081 BT Amsterdam, The Netherlands
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Abstract

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The purpose of the present study was to describe the longitudinal development of nutrient intake and to determine the stability of this intake from adolescence into adulthood. Longitudinal data of the Amsterdam Growth and Health Longitudinal Study were analysed; the dietary intake of 200 subjects (males and females) was repeatedly measured (eight times) over a period of 20 years, covering the age period of 13–33 years. Dietary intake was determined with the detailed crosscheck dietary history interview. With use of multivariate ANOVA for repeated measurements, trends in macro- and micronutrients over time and differences between genders were analysed. Furthermore, stability coefficients, corrected for time-dependent (biological age) and time-independent covariates (gender) were calculated, taking into account all the measurements. The results showed significant (P<0.001) time and gender effects for energy intake (kJ) and the following macronutrients: protein (g and % total energy supply), fat (g) and carbohydrate (g). Interaction effects between time and gender diminished when the macronutrients were calculated as a percentage of total energy intake. The micronutrients Ca, Fe and vitamins changed significantly (P<0.001) over time and showed an interaction effect with gender, with the exception of cholesterol intake (mg/MJ), which did not show an interaction effect of time and gender. The tracking of the nutrient intake showed relatively low but significant (P<0.05) stability coefficients for all macro- and micronutrients (0.28–0.52). In conclusion, dietary intake does change considerably over time, with the exception of polyunsaturated fat intake (% total energy supply) for both males and females and fat intake in females. Furthermore, stability coefficients for nutrients appeared to be low to moderate. Although these coefficients may be somewhat attenuated as a result of the relatively large measurement error of the dietary intake measurement, they suggest moderate stability of diet over time. These findings may imply that dietary intake is changeable and suggest that disease prevention measures can be implemented in adulthood.

Keywords

Age trendsTrackingDietary historyLongitudinal study
Type
Research Article
Information
British Journal of Nutrition , Volume 85 , Issue 3 , March 2001 , pp. 375 - 385
Copyright
Copyright © The Nutrition Society 2001

References

Beal, VA (1967) The nutritional history in longitudinal research. Journal of the American Dietetic Association 51, 426–432.CrossRefGoogle ScholarPubMed
Black, AE, Goldberg, GR, Jebb, SA, Livingtone, MB, Cole, TJ & Prentice, AM (1991) Critical evaluation of energy intake data using fundamental principles of energy physiology: 2. Evaluating the results of published surveys. European Journal of Clinical Nutrition 45, 583–599.Google Scholar
Block, G, Patterson, B & Subar, A (1992) Fruit, vegetables, and cancer prevention: a review of the epidemiological evidence. Nutrition and Cancer 18, 1–29.CrossRefGoogle ScholarPubMed
de Castro, JM (1993) Genetic influences on daily intake and meal patterns of humans. Physiology and Behavior 53, 777–782.CrossRefGoogle ScholarPubMed
de Castro, JM (1993 b)) Independence of genetic influences on body size, daily intake, and meal patterns of humans. Physiology and Behavior 54, 633–639.Google Scholar
Fernyhough, LK, Horwath, CC, Campbell, AJ, Robertson, MC & Busby, WJ (1999) Changes in dietary intake during a 6-year follow-up of an older population. European Journal of Clinical Nutrition 53, 216–225.Google Scholar
Gebski, V, Leung, O, McNeil, D & Lunn, D (1992) SPIDA User Manual, version 6. Eastwood, NSW Australia: University of Macquaire.Google Scholar
Goldberg, GR, Black, AE, Jebb, SA, Cole, TJ, Murgatroyd, PR, Coward, WA & Prentice, AM (1991) Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify under-recording. European Journal of Clinical Nutrition 45, 569–581.Google Scholar
Goldbohm, RA, van't Veer, P, van den Brandt, PA, van't Hof, MA, Brants, HAM, Sturmans, F & Hermus, RJJ (1995) Reproducibility of a food frequency questionnaire and stability of dietary habits determined from five annually repeated measurements. European Journal of Clinical Nutrition 49, 420–429.Google Scholar
Heaney, RP, Davies, KM, Recker, RR & Packard, PT (1990) Long-term consistency of nutrient intakes in human. Journal of Nutrition 120, 869–875.Google Scholar
Jain, M, Howe, GR, Harrison, L & Miller, AB (1989) A study of repeatability of dietary data over a seven-year period. American Journal of Epidemiology 129, 422–429.Google Scholar
Jensen, OM, Wahrendorf, J, Rosenqvist, A & Geser, A (1984) The reliability of questionnaire-derived historical dietary information and temporal stability of food habits in individuals. American Journal of Epidemiology 120, 281–290.Google Scholar
Kelder, SH, Perry, CL, Klepp, K & Lytle, LL (1994) Longitudinal tracking of adolescent smoking, physical activity, and food choice behaviors. American Journal of Public Health 84, 1121–1126.Google Scholar
Kemper, HCG (1985) Growth, Health and Fitness of Teenagers: Longitudinal Research in International Perspective. Medicine and Sport Science Series no. 20 Basel and New York: Karger.Google Scholar
Kemper, HCG (1995) The Amsterdam Growth Study: A Longitudinal Analysis of Health, Fitness and Lifestyle. HKP Sport Science Monograph Series no, V.6 Champaign, IL: Human Kinetics.Google Scholar
Kemper, HCG, Snel, J, Verschuur, R & Storm-van Essen, L (1990) Tracking of health and risk indicators of cardiovascular diseases from teenager to adult: Amsterdam Growth and Health Study. Preventive Medicine 19, 642–655.Google Scholar
Kemper, HCG, Van Mechelen, W (1995) Methods and measurements used in the longitudinal study The Amsterdam Growth Study: A longitudinal analysis of health, fitness and lifestyle. HKP Sport Science Monograph Series no., v.6, pp. 39 [Kemper, HCG, editor]. Champaign, IL: Human Kinetics.Google Scholar
Kleinbaum, DG, Kupper, LL & Muller, KE (1988) Applied Regression Analysis and Other Multivariate Methods.Boston,MA: PWS-KENT Publishing Co.Google Scholar
Marr, JW (1971) Individual dietary surveys: purpose and methods. World Review of Nutrition and Dietetics 13, 105–164.Google Scholar
Netherlands Food and Nutrition Council (1992) Nederlandse Voedingsnormen 1989 (Dutch Food Norms 1989). 2nd ed. The Hague, The Netherlands: Voorlichtingsbureau voor de Voeding.Google Scholar
Nie, NH, Hull, CH, Jenkins, JG, Steinbrenner, K & Bent, DH (1983) SPSS: Statistical Packages for the Social Sciences.New York: McGraw-Hill.Google Scholar
Norris, J, Harnack, L, Carmichael, S, Pouane, T, Wakimoto, P & Block, G (1997) US trends in nutrient intake: the 1987 and 1992 national health interview surveys. American Journal of Public Health 87, 740–746.Google Scholar
Osler, M, Heitmann, BL & Schroll, M (1997) Ten year trends in the dietary habits of Danish men and women – cohort and cross-sectional data. European Journal of Clinical Nutrition 51, 535–541.Google Scholar
Popkin, BM, Haines, PS & Patterson, RE (1992) Dietary changes in older Americans, 1977–1987. American Journal of Clinical Nutrition 55, 823–830.CrossRefGoogle ScholarPubMed
Post, GB (1989) Nutrition in adolescence: a longitudinal study in dietary pattern from teenager to adult.PHD Thesis, Agricultural University Wageningen, The Netherlands.Google Scholar
Singer, MR, Moore, LL, Garrahie, EJ & Ellison, RC (1995) The tracking of nutrient intake in young children: The Framingham Children's study. American Journal of Public Health 85, 1673–1677.Google Scholar
Smith, SA, Campbell, DR, Elmer, PJ, Martini, MC, Slavin, JL & Potter, JD (1995) The University of Minnesota cancer prevention research unit vegetable and fruit classification scheme (United States). Cancer Causes and Control 6, 292–302.Google Scholar
Stein, AD, Shea, S, Basch, CE, Contento, IR & Zybert, P (1991) Variability and tracking of nutrient intakes of pre-school children based on multiple administrations of the 24-hour dietary recall. American Journal of Epidemiology 134, 1427–1437.Google Scholar
Stephan, A & Wald, N (1990) Trends in individual consumption of dietary fat in the United States, 1920–1984. American Journal of Clinical Nutrition 52, 457–469.Google Scholar
Stichting Nederlandse Voedingsstoffen bestand (1996) Nevo Tabel 1996 (Dutch Food Composition Table 1996). Den Haag, The Netherlands: Voorlichtingsbureau voor de Voeding.Google Scholar
Twisk, JWR, Kemper, HCG, Mellenbergh, GJ, van Mechelen, W & Post, GB (1996) Relation between the longitudinal development of lipoprotein levels and lifestyle parameters during adolescence and young adulthood. Annals of Epidemiology 6, 246–256.CrossRefGoogle ScholarPubMed
Twisk, JWR, Kemper, HCG, van Mechelen, W & Post, GB (1997) Tracking of risk factors for coronary heart disease over a 14-year period: A comparison between lifestyle and biological risk factors with data from the Amsterdam Growth and Health Study. American Journal of Epidemiology 145, 888–898.Google Scholar
Van #Staveren, WA, West, CE, Hoffmans, MDA, Bos, P, Kardinaal, AF, van Poppel, GA, Schipper, HJ, Hautvast, JG & Hayes, RB (1986) Comparison of contemporaneous and retrospective estimates of food consumption made by a dietary history method. American Journal of Epidemiology 123, 884–893.Google Scholar
Voedselconsumptiepeiling (1998) Zo eet Nederland 1996 (That's How the Dutch Eat 1996). Den Haag, The Netherlands: Voedingscentrum.Google Scholar
Westerterp, KR, verboeket-Van, deVenne, WPHG, Meijer, GAL, Ten HoorF, F, (1992) Self-reported intake as a measure for energy intake, a validation against doubly labelled water Obesity in Europe 91, pp. 17–22 [G, Ailhaud, B, Guy-Graud, M, Lafontau & D, Ricquier, editors]. London: John Libbey.Google Scholar