Cohort Profile: The Dutch Perined-Lifelines birth cohort

English version

Autoři: Nastaran Salavati ^aff001; Marian K. Bakker ^aff001; Eline M. van der Beek ^aff003; JanJaap H. M. Erwich ^aff001
Působiště autorů: Department of Obstetrics and Gynecology, University Medical Centre of Groningen, University of Groningen, Groningen, The Netherlands ^aff001; Department of Genetics, EUROCAT Registration Northern Netherlands, University Medical Centre of Groningen, University of Groningen, Groningen, The Netherlands ^aff002; Department of Pediatrics, University Medical Centre of Groningen, University of Groningen, Groningen, The Netherlands ^aff003; Danone Nutricia Research, Utrecht, The Netherlands ^aff004
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0225973

Souhrn

Background

Maternal nutrition status (e.g. dietary/nutrient intake) during pregnancy has been associated with pregnancy outcomes including birth weight, infant survival and metabolic health of the offspring during later life. During the past few years, maternal dietary intake, at least three months before conception, has been shown to affect pregnancy outcomes also. However, literature investigating this link is still scarce. The studies that have looked at preconception dietary intake in relation to pregnancy outcome were either animal studies, had small sample sizes or focused on only selected macronutrient intake rather than complete (macro)nutrient composition or dietary intakes (e.g. food groups). Therefore, we aim to investigate the association between preconception diet and pregnancy outcomes in a linked birth cohort. The main objective of this manuscript is to describe the methodology of establishing this birth cohort and to describe both the characteristics of the study population included as well as the representativeness in terms of dietary intake.

Methods

We created the birth cohort by linking two existing databases; a large population-based cohort study in the Netherlands (The Lifelines Cohort study) and the Dutch national birth registry (Perined), through a ‘trusted third party’. The birth cohort contains information on maternal dietary intake during preconception as well as pregnancy outcomes.

Results and discussion

In the Lifelines Cohort study, 3,418 pregnancies were available for linking with Perined. In total, 2,368 pregnancies (86.9%) were linked with Perined, resulting in the birth cohort. With this linked cohort we are able to provide insights on the associations between dietary intake before conception and pregnancy outcomes. Such data could potentially improve nutritional care for women of childbearing age. Lifestyle changes in the period preceding pregnancy may be most effective in improving pregnancy outcomes. A focus on this window of opportunity may provide both sufficient time, as well as a period when women are potentially motivated to adopt health optimizing behaviours.

Klíčová slova:

Carbohydrates – Birth – Labor and delivery – Pregnancy – Cohort studies – Diet – Dutch people

Zdroje

1. Painter RC, Roseboom TJ, Bleker OP. Prenatal exposure to the Dutch famine and disease in later life: An overview. Reprod Toxicol. 2005;20: 345–352. doi: 10.1016/j.reprotox.2005.04.005 15893910

2. Vaag A, Brøns C, Gillberg L, Hansen NS, Hjort L, Arora GP, et al. Genetic, nongenetic and epigenetic risk determinants in developmental programming of type 2 diabetes. Acta Obstet Gynecol Scand. 2014;93: 1099–1108. doi: 10.1111/aogs.12494 25179736

3. WHO | World Health Statistics 2015. WHO. World Health Organization; 2016; Available: http://www.who.int/gho/publications/world_health_statistics/2015/en/

4. De-Regil LM, Fernández-Gaxiola AC, Dowswell T, Peña-Rosas JP. Effects and safety of periconceptional folate supplementation for preventing birth defects. De-Regil LM, editor. Cochrane database Syst Rev. Chichester, UK: John Wiley & Sons, Ltd; 2010; CD007950. doi: 10.1002/14651858.CD007950.pub2 20927767

5. Kind KL, Moore VM, Davies MJ. Diet around conception and during pregnancy—effects on fetal and neonatal outcomes. Reprod Biomed Online. 2006;12: 532–41. Available: http://www.ncbi.nlm.nih.gov/pubmed/16790095 doi: 10.1016/s1472-6483(10)61178-9 16790095

6. Williamson CS. Nutrition in pregnancy. Nutr Bull. Wiley/Blackwell (10.1111); 2006;31: 28–59. doi: 10.1111/j.1467-3010.2006.00541.x

7. De-Regil LM, Harding KB, Roche ML. Preconceptional Nutrition Interventions for Adolescent Girls and Adult Women: Global Guidelines and Gaps in Evidence and Policy with Emphasis on Micronutrients. J Nutr. 2016;146: 1461S–1470S. doi: 10.3945/jn.115.223487 27281812

8. Hanson MA, Bardsley A, De-Regil LM, Moore SE, Oken E, Poston L, et al. The International Federation of Gynecology and Obstetrics (FIGO) recommendations on adolescent, preconception, and maternal nutrition: "Think Nutrition First". Int J Gynaecol Obstet. 2015;131 Suppl 4: S213–53. doi: 10.1016/S0020-7292(15)30034-5

9. Inskip HM, Godfrey KM, Robinson SM, Law CM, Barker DJP, Cooper C, et al. Cohort profile: The Southampton Women’s Survey. Int J Epidemiol. Europe PMC Funders; 2006;35: 42–8. doi: 10.1093/ije/dyi202 16195252

10. Scholtens S, Smidt N, Swertz MA, Bakker SJL, Dotinga A, Vonk JM, et al. Cohort Profile: LifeLines, a three-generation cohort study and biobank. Int J Epidemiol. 2015;44: 1172–80. doi: 10.1093/ije/dyu229 25502107

11. Klijs B, Scholtens S, Mandemakers JJ, Snieder H, Stolk RP, Smidt N. Representativeness of the LifeLines Cohort Study. Ali RI, editor. PLoS One. 2015;10: e0137203. doi: 10.1371/journal.pone.0137203 26333164

12. Molag ML, de Vries JHM, Duif N, Ocké MC, Dagnelie PC, Goldbohm RA, et al. Selecting informative food items for compiling food-frequency questionnaires: comparison of procedures. Br J Nutr. 2010;104: 446–456. doi: 10.1017/S0007114510000401 20374682

13. Siebelink E, Geelen A, de Vries JHM. Self-reported energy intake by FFQ compared with actual energy intake to maintain body weight in 516 adults. Br J Nutr. 2011;106: 274–81. doi: 10.1017/S0007114511000067 21338536

14. Streppel MT, de Vries JHM, Meijboom S, Beekman M, de Craen AJM, Slagboom PE, et al. Relative validity of the food frequency questionnaire used to assess dietary intake in the Leiden Longevity Study. Nutr J. 2013;12: 75. doi: 10.1186/1475-2891-12-75 23758629

15. RIVM/Dutch Nutrition Centre; Bilthoven TN 2011. N-T. NEVO online | RIVM.

16. Black AE. 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. 2000;24: 1119–30. Available: http://www.ncbi.nlm.nih.gov/pubmed/11033980 doi: 10.1038/sj.ijo.0801376 11033980

17. Schofield WN. Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr. 1985;39 Suppl 1: 5–41. Available: http://www.ncbi.nlm.nih.gov/pubmed/4044297

18. Perined, Perinatal care in the Netherlands 2006–2016. Utrecht; 2018.

19. Perined. Perinatal Care in the Netherlands 2016. Utrecht; 2018.

20. Willett WC, Howe GR, Kushi LH. Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr. 1997;65: 1220S–1228S. doi: 10.1093/ajcn/65.4.1220S 9094926

21. Rhee JJ, Sampson L, Cho E, Hughes MD, Hu FB, Willett WC. Comparison of Methods to Account for Implausible Reporting of Energy Intake in Epidemiologic Studies. Am J Epidemiol. 2015;181: 225–233. doi: 10.1093/aje/kwu308 25656533

22. Vinke PC, Corpeleijn E, Dekker LH, Jacobs DR, Navis G, Kromhout D. Development of the food-based Lifelines Diet Score (LLDS) and its application in 129,369 Lifelines participants. Eur J Clin Nutr. 2018;72: 1111–1119. doi: 10.1038/s41430-018-0205-z 29895847

23. Gezondheidsraad. Voedingsnormen: energie, eiwitten, vetten en verteerbare koolhydraten. Gezondheidsraad. 2001; Available: https://www.mvo.nl/media/gezondheid/voedingsnormen_gr_2001.pdf

24. Wu G, Bazer FW, Cudd TA, Meininger CJ, Spencer TE. Maternal Nutrition and Fetal Development. J Nutr. 2004;134: 2169–2172. doi: 10.1093/jn/134.9.2169 15333699

25. Phelan S. Pregnancy: a "teachable moment" for weight control and obesity prevention. Am J Obstet Gynecol. 2010;202: 135.e1–8. doi: 10.1016/j.ajog.2009.06.008 19683692

26. Stephenson J, Heslehurst N, Hall J, Schoenaker DAJM, Hutchinson J, Cade JE, et al. Before the beginning: nutrition and lifestyle in the preconception period and its importance for future health. Lancet (London, England). 2018;391: 1830–1841. doi: 10.1016/S0140-6736(18)30311-8 29673873

27. van Elten TM, Karsten MDA, Geelen A, Gemke RJBJ, Groen H, Hoek A, et al. Preconception lifestyle intervention reduces long term energy intake in women with obesity and infertility: a randomised controlled trial. Int J Behav Nutr Phys Act. BioMed Central; 2019;16: 3. doi: 10.1186/s12966-018-0761-6 30621789

28. Altfeld S, Handler A, Burton D, Berman L. Wantedness of pregnancy and prenatal health behaviors. Women Health. 1997;26: 29–43. Available: http://www.ncbi.nlm.nih.gov/pubmed/9525267

29. McBride CM, Emmons KM, Lipkus IM. Understanding the potential of teachable moments: the case of smoking cessation. Health Educ Res. 2003;18: 156–70. Available: http://www.ncbi.nlm.nih.gov/pubmed/12729175 doi: 10.1093/her/18.2.156 12729175

30. Barker M, Dombrowski SU, Colbourn T, Fall CHD, Kriznik NM, Lawrence WT, et al. Intervention strategies to improve nutrition and health behaviours before conception. Lancet (London, England). Europe PMC Funders; 2018;391: 1853–1864. doi: 10.1016/S0140-6736(18)30313-1 29673875

31. Ramakrishnan U, Grant F, Goldenberg T, Zongrone A, Martorell R. Effect of women’s nutrition before and during early pregnancy on maternal and infant outcomes: a systematic review. Paediatr Perinat Epidemiol. 2012;26 Suppl 1: 285–301. doi: 10.1111/j.1365-3016.2012.01281.x 22742616

32. Zhang C, Schulze MB, Solomon CG, Hu FB. A prospective study of dietary patterns, meat intake and the risk of gestational diabetes mellitus. Diabetologia. 2006;49: 2604–2613. doi: 10.1007/s00125-006-0422-1 16957814

33. Tobias DK, Zhang C, Chavarro J, Bowers K, Rich-Edwards J, Rosner B, et al. Prepregnancy adherence to dietary patterns and lower risk of gestational diabetes mellitus. Am J Clin Nutr. 2012;96: 289–295. doi: 10.3945/ajcn.111.028266 22760563

34. Bao W, Bowers K, Tobias DK, Olsen SF, Chavarro J, Vaag A, et al. Prepregnancy low-carbohydrate dietary pattern and risk of gestational diabetes mellitus: a prospective cohort study. Am J Clin Nutr. American Society for Nutrition; 2014;99: 1378–84. doi: 10.3945/ajcn.113.082966 24717341

35. Harding KB, Peña-Rosas JP, Webster AC, Yap CM, Payne BA, Ota E, et al. Iodine supplementation for women during the preconception, pregnancy and postpartum period. Cochrane Database Syst Rev. 2017;3: CD011761. doi: 10.1002/14651858.CD011761.pub2 28260263

36. Schoenaker DA, Soedamah-Muthu SS, Callaway LK, Mishra GD. Prepregnancy dietary patterns and risk of developing hypertensive disorders of pregnancy: results from the Australian Longitudinal Study on Women’s Health. Am J Clin Nutr. 2015;102: 94–101. doi: 10.3945/ajcn.114.102475 26040639

37. Schoenaker DA, Soedamah-Muthu SS, Mishra GD. Quantifying the mediating effect of body mass index on the relation between a Mediterranean diet and development of maternal pregnancy complications: the Australian Longitudinal Study on Women’s Health. Am J Clin Nutr. 2016;104: 638–645. doi: 10.3945/ajcn.116.133884 27465377

38. Gresham E, Collins CE, Mishra GD, Byles JE, Hure AJ. Diet quality before or during pregnancy and the relationship with pregnancy and birth outcomes: the Australian Longitudinal Study on Women’s Health. Public Health Nutr. 2016;19: 2975–2983. doi: 10.1017/S1368980016001245 27238757

39. Harron K, Wade A, Gilbert R, Muller-Pebody B, Goldstein H. Evaluating bias due to data linkage error in electronic healthcare records. BMC Med Res Methodol. 2014;14: 36. doi: 10.1186/1471-2288-14-36 24597489

40. Benchimol EI, Smeeth L, Guttmann A, Harron K, Moher D, Petersen I, et al. The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement. PLOS Med. Public Library of Science; 2015;12: e1001885. doi: 10.1371/journal.pmed.1001885 26440803

41. Van Rossum CTM, Fransen HP, Verkaik-Kloosterman J, Buurma-Rethans EJM, Ocké MC. Dutch National Food Consumption Survey 2007–2010 [Internet]. 2007. Available: www.rivm.nl/vcp/

42. Van Rossum C, Buurma-Rethans EJM. Vennemann F, Beukers M, Brants H, De Boer E, et al. The diet of the Dutch: Results of the first two years of the Dutch National Food Consumption Survey 2012–2016. [Internet]. Bilthoven; 2016. Available: https://www.rivm.nl/bibliotheek/rapporten/2016-0082.pdf

43. Sluik D, Geelen A, de Vries JHM, Eussen SJPM, Brants HAM, Meijboom S, et al. A national FFQ for the Netherlands (the FFQ-NL 1.0): validation of a comprehensive FFQ for adults. Br J Nutr. 2016;116: 913–923. doi: 10.1017/S0007114516002749 27452894

44. Willett WC. Nutritional epidemiology (3rd edition). Oxford University Press; 2013.

45. King JC. A Summary of Pathways or Mechanisms Linking Preconception Maternal Nutrition with Birth Outcomes. J Nutr. 2016;146: 1437S–1444S. doi: 10.3945/jn.115.223479 27281808

46. Ananth C V., Ananth C V., Vintzileos AM. Epidemiology of preterm birth and its clinical subtypes. J Matern Neonatal Med. 2006;19: 773–782. doi: 10.1080/14767050600965882 17190687

47. Villar J, Papageorghiou AT, Knight HE, Gravett MG, Iams J, Waller SA, et al. The preterm birth syndrome: a prototype phenotypic classification. Am J Obstet Gynecol. 2012;206: 119–123. doi: 10.1016/j.ajog.2011.10.866 22177191