Skip to main content
SpringerLink
Log in

LC-PUFA enrichment in infant formula and neurodevelopment up to age 3.5 years in the French nationwide ELFE birth cohort

  • Original Contribution
  • Published:
European Journal of Nutrition Aims and scope Submit manuscript

Abstract

Purpose

For decades, consistent associations between breastfeeding and children’s neurodevelopment have been attributed to breastmilk content in long-chain polyunsaturated fatty acids (LC-PUFAs). However, the beneficial effect of LC-PUFA enrichment of infant formula on neurodevelopment remains controversial. This study examined the association of LC-PUFA enrichment of infant formulas with neurodevelopment up to age 3.5 years.

Methods

Analyses were based on 9372 children from the French nationwide ELFE birth cohort. Monthly from 2 to 10 months, parents declared their infant’s feeding mode, including breastfeeding and the name of the infant formula, which allowed for identifying formulas enriched in arachidonic (ARA), eicosapentaenoic (EPA) and/or docosahexaenoic (DHA) acids. Neurodevelopment was assessed at age 1 and 3.5 years with the Child Development Inventory (CDI-1 and CDI-3.5); at 2 years with the MacArthur-Bates Communicative Development Inventories (MB-2); and at 3.5 years with the Picture Similarities subtest of the British Ability Scale (BAS-3.5). Associations were assessed by linear regression adjusted for any breastfeeding duration and main confounding factors, including socioeconomic characteristics.

Results

One-third of formula-fed infants consumed LC-PUFA-enriched formulas. Most of these formulas were enriched in both DHA and ARA, and about 10% of infants consumed formula further enriched in EPA. LC-PUFA enrichment of infant formula was not associated with neurodevelopmental scores at age 1 (CDI-1, − 0.16 [− 0.39, 0.07]), age 2 (MB-2, 0.78 [− 0.33, 1.89]), or age 3.5 (CDI-3.5, − 0.05 [− 0.27, 0.17]; BAS-3.5, − 0.93 [− 2.85, 0.98]).

Conclusion

In the ELFE study, LC-PUFA enrichment of infant formula was not associated with neurodevelopmental scores up to 3.5 years.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Availability of data and material

The data underlying the findings cannot be made freely available for ethical and legal restrictions imposed because this study includes a substantial number of variables that together could be used to re-identify the participants based on a few key characteristics and then used to access other personal data. Therefore, the French ethics authority strictly forbids making these data freely available. However, they can be obtained upon request from the ELFE principal investigator. Readers may contact marie-aline.charles@inserm.fr to request the data. The code book and analytic code will be made available upon request pending application and approval.

References

  1. Victora CG, Bahl R, Barros AJ, Franca GV, Horton S, Krasevec J, Murch S, Sankar MJ, Walker N, Rollins NC, Lancet Breastfeeding Series G (2016) Breastfeeding in the 21st century: epidemiology, mechanisms, and lifelong effect. Lancet 387(10017):475–490. https://doi.org/10.1016/S0140-6736(15)01024-7

    Article  PubMed  Google Scholar 

  2. Horta BL, de Sousa BA, de Mola CL (2018) Breastfeeding and neurodevelopmental outcomes. Curr Opin Clin Nutr Metab Care 21(3):174–178. https://doi.org/10.1097/MCO.0000000000000453

    Article  PubMed  Google Scholar 

  3. Kramer MS, Aboud F, Mironova E, Vanilovich I, Platt RW, Matush L, Igumnov S, Fombonne E, Bogdanovich N, Ducruet T, Collet JP, Chalmers B, Hodnett E, Davidovsky S, Skugarevsky O, Trofimovich O, Kozlova L, Shapiro S, Promotion of Breastfeeding Intervention Trial Study G (2008) Breastfeeding and child cognitive development: new evidence from a large randomized trial. Arch Gen Psychiatry 65(5):578–584. https://doi.org/10.1001/archpsyc.65.5.578

    Article  PubMed  Google Scholar 

  4. Mortensen EL, Michaelsen KF, Sanders SA, Reinisch JM (2002) The association between duration of breastfeeding and adult intelligence. JAMA 287(18):2365–2371. https://doi.org/10.1001/jama.287.18.2365

    Article  PubMed  Google Scholar 

  5. Belfort MB, Rifas-Shiman SL, Kleinman KP, Guthrie LB, Bellinger DC, Taveras EM, Gillman MW, Oken E (2013) Infant feeding and childhood cognition at ages 3 and 7 years: Effects of breastfeeding duration and exclusivity. JAMA Pediatr 167(9):836–844. https://doi.org/10.1001/jamapediatrics.2013.455

    Article  PubMed  PubMed Central  Google Scholar 

  6. Bernard JY, Armand M, Peyre H, Garcia C, Forhan A, De Agostini M, Charles MA, Heude B, Eden Mother-Child Cohort Study Group (2017) Breastfeeding, polyunsaturated fatty acid levels in colostrum and child intelligence quotient at age 5–6 years. J Pediatr 183:43–50. https://doi.org/10.1016/j.jpeds.2016.12.039

    Article  CAS  PubMed  Google Scholar 

  7. Tozzi AE, Bisiacchi P, Tarantino V, Chiarotti F, D’Elia L, De Mei B, Romano M, Gesualdo F, Salmaso S (2012) Effect of duration of breastfeeding on neuropsychological development at 10 to 12 years of age in a cohort of healthy children. Dev Med Child Neurol 54(9):843–848. https://doi.org/10.1111/j.1469-8749.2012.04319.x

    Article  PubMed  Google Scholar 

  8. Sanchez-Hernandez S, Esteban-Munoz A, Gimenez-Martinez R, Aguilar-Cordero MJ, Miralles-Buraglia B, Olalla-Herrera M (2019) A Comparison of changes in the fatty acid profile of human milk of spanish lactating women during the first month of lactation using gas chromatography-mass spectrometry. A comparison with infant formulas. Nutrients. https://doi.org/10.3390/nu11123055

    Article  PubMed  PubMed Central  Google Scholar 

  9. Shulkin M, Pimpin L, Bellinger D, Kranz S, Fawzi W, Duggan C, Mozaffarian D (2018) N-3 fatty acid supplementation in mothers, preterm infants, and term infants and childhood psychomotor and visual development: a systematic review and meta-analysis. J Nutr 148(3):409–418. https://doi.org/10.1093/jn/nxx031

    Article  PubMed  PubMed Central  Google Scholar 

  10. Moon K, Rao SC, Schulzke SM, Patole SK, Simmer K (2016) Longchain polyunsaturated fatty acid supplementation in preterm infants. Cochrane Database Syst Rev. https://doi.org/10.1002/14651858.CD000375.pub5

    Article  PubMed  PubMed Central  Google Scholar 

  11. European Food Safety Authority (2014) Scientific opinion on the essential composition of infant and follow-on formulae. EFSA J. https://doi.org/10.2903/j.efsa.2014.3760

    Article  Google Scholar 

  12. Koletzko B, Bergmann K, Brenna JT, Calder PC, Campoy C, Clandinin MT, Colombo J, Daly M, Decsi T, Demmelmair H, Domellof M, FidlerMis N, Gonzalez-Casanova I, van Goudoever JB, Hadjipanayis A, Hernell O, Lapillonne A, Mader S, Martin CR, Matthaus V, Ramakrishan U, Smuts CM, Strain SJJ, Tanjung C, Tounian P, Carlson SE (2020) Should formula for infants provide arachidonic acid along with DHA? A position paper of the European academy of paediatrics and the child health foundation. Am J Clin Nutr 111(1):10–16. https://doi.org/10.1093/ajcn/nqz252

    Article  PubMed  Google Scholar 

  13. Crawford MA, Wang Y, Forsyth S, Brenna JT (2015) The European food safety authority recommendation for polyunsaturated fatty acid composition of infant formula overrules breast milk, puts infants at risk, and should be revised. Prostaglandins Leukot Essent Fatty Acids 102–103:1–3. https://doi.org/10.1016/j.plefa.2015.07.005

    Article  CAS  PubMed  Google Scholar 

  14. Jiao J, Li Q, Chu J, Zeng W, Yang M, Zhu S (2014) Effect of n-3 PUFA supplementation on cognitive function throughout the life span from infancy to old age: a systematic review and meta-analysis of randomized controlled trials. Am J Clin Nutr 100(6):1422–1436. https://doi.org/10.3945/ajcn.114.095315

    Article  CAS  PubMed  Google Scholar 

  15. Jasani B, Simmer K, Patole SK, Rao SC (2017) Long chain polyunsaturated fatty acid supplementation in infants born at term. Cochrane Database Syst Rev. https://doi.org/10.1002/14651858.CD000376.pub4

    Article  PubMed  PubMed Central  Google Scholar 

  16. Verfuerden ML, Dib S, Jerrim J, Fewtrell M, Gilbert RE (2020) Effect of long-chain polyunsaturated fatty acids in infant formula on long-term cognitive function in childhood: a systematic review and meta-analysis of randomised controlled trials. PLoS ONE 15(11):e0241800. https://doi.org/10.1371/journal.pone.0241800

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Charles MA, Thierry X, Lanoe JL, Bois C, Dufourg MN, Popa R, Cheminat M, Zaros C, Geay B (2020) Cohort Profile: the French national cohort of children (ELFE): birth to 5 years. Int J Epidemiol 49(2):368–369j. https://doi.org/10.1093/ije/dyz227

    Article  PubMed  Google Scholar 

  18. de Lauzon-Guillain B, Davisse-Paturet C, Lioret S, Ksiazek E, Bois C, Dufourg MN, Bournez M, Nicklaus S, Wagner S, Charles MA (2018) Use of infant formula in the ELFE study: the association with social and health-related factors. Matern Child Nutr. https://doi.org/10.1111/mcn.12477

    Article  PubMed  Google Scholar 

  19. Wagner S, Kersuzan C, Gojard S, Tichit C, Nicklaus S, Thierry X, Charles MA, Lioret S, de Lauzon-Guillain B (2019) Breastfeeding initiation and duration in France: the importance of intergenerational and previous maternal breastfeeding experiences—results from the nationwide ELFE study. Midwifery 69:67–75. https://doi.org/10.1016/j.midw.2018.10.020

    Article  PubMed  Google Scholar 

  20. Duyme M, Zorman M, Tervo R, Capron C (2011) French norms and validation of the child development inventory (CDI): inventaire du developpement de l’enfant (IDE). Clin Pediatr (Phila) 50(7):636–647. https://doi.org/10.1177/0009922811398390

    Article  Google Scholar 

  21. Ireton H, Glascoe FP (1995) Assessing children’s development using parents’ reports. The child development inventory. Clin Pediatr (Phila) 34(5):248–255. https://doi.org/10.1177/000992289503400504

    Article  CAS  Google Scholar 

  22. Kern S, Langue J, Zesiger P, Bovet F (2010) Adaptations françaises des versions courtes des inventaires du développement communicatif de MacArthur-Bates. ANAE Approche neuropsychologique des apprentissages chez l’enfant 22(107–108):217–228

    Google Scholar 

  23. Elliott CD, Smith P, McCulloch K (1996) British ability scales second edition (BAS II): administration and scoring manual. NFER-Nelson, London

    Google Scholar 

  24. Kadawathagedara M, Ahluwalia N, Dufourg MN, Forhan A, Charles MA, Lioret S, de Lauzon-Guillain B (2021) Diet during pregnancy: Influence of social characteristics and migration in the ELFE cohort. Matern Child Nutr. https://doi.org/10.1111/mcn.13140

    Article  PubMed  PubMed Central  Google Scholar 

  25. Mamelle N, Munoz F, Grandjean H (1996) Fetal growth from the AUDIPOG study. I. Establishment of reference curves. J Gynécologie Obstétrique Biol Reprod 25(1):61–70

    CAS  Google Scholar 

  26. Juillard H (2015) Weighting of Elfe survey data at time 0. pandora.vjf.inserm.fr/public/

  27. Blondel B, Lelong N, Kermarrec M, Goffinet F, National Coordination Group of the National Perinatal Surveys (2012) Trends in perinatal health in France from 1995 to 2010. Results from the French national perinatal surveys. J Gynecol Obstet Biol Reprod (Paris) 41(4):e1–e15. https://doi.org/10.1016/j.jgyn.2012.04.014

    Article  CAS  Google Scholar 

  28. Ferguson KD, McCann M, Katikireddi SV, Thomson H, Green MJ, Smith DJ, Lewsey JD (2020) Evidence synthesis for constructing directed acyclic graphs (ESC-DAGs): a novel and systematic method for building directed acyclic graphs. Int J Epidemiol 49(1):322–329. https://doi.org/10.1093/ije/dyz150

    Article  PubMed  Google Scholar 

  29. Shrier I, Platt RW (2008) Reducing bias through directed acyclic graphs. BMC Med Res Methodol 8:70. https://doi.org/10.1186/1471-2288-8-70

    Article  PubMed  PubMed Central  Google Scholar 

  30. Nagin DS, Odgers CL (2010) Group-based trajectory modeling in clinical research. Annu Rev Clin Psychol 6:109–138. https://doi.org/10.1146/annurev.clinpsy.121208.131413

    Article  PubMed  Google Scholar 

  31. Horta BL, Loret de Mola C, Victora CG (2015) Breastfeeding and intelligence: a systematic review and meta-analysis. Acta Paediatr 104(467):14–19. https://doi.org/10.1111/apa.13139

    Article  PubMed  Google Scholar 

  32. Drover JR, Felius J, Hoffman DR, Castaneda YS, Garfield S, Wheaton DH, Birch EE (2012) A randomized trial of DHA intake during infancy: school readiness and receptive vocabulary at 2–3.5 years of age. Early Hum Dev 88(11):885–891. https://doi.org/10.1016/j.earlhumdev.2012.07.007

    Article  CAS  PubMed  Google Scholar 

  33. Carlson SE, Ford AJ, Werkman SH, Peeples JM, Koo WW (1996) Visual acuity and fatty acid status of term infants fed human milk and formulas with and without docosahexaenoate and arachidonate from egg yolk lecithin. Pediatr Res 39(5):882–888. https://doi.org/10.1203/00006450-199605000-00024

    Article  CAS  PubMed  Google Scholar 

  34. Voigt RG, Jensen CL, Fraley JK, Rozelle JC, Brown FR 3rd, Heird WC (2002) Relationship between omega3 long-chain polyunsaturated fatty acid status during early infancy and neurodevelopmental status at 1 year of age. J Hum Nutr Diet 15(2):111–120. https://doi.org/10.1046/j.1365-277x.2002.00341.x

    Article  CAS  PubMed  Google Scholar 

  35. de Jong C, Kikkert HK, Fidler V, Hadders-Algra M (2012) Effects of long-chain polyunsaturated fatty acid supplementation of infant formula on cognition and behaviour at 9 years of age. Dev Med Child Neurol 54(12):1102–1108. https://doi.org/10.1111/j.1469-8749.2012.04444.x

    Article  PubMed  Google Scholar 

  36. Garwolinska D, Namiesnik J, Kot-Wasik A, Hewelt-Belka W (2018) Chemistry of human breast milk-a comprehensive review of the composition and role of milk metabolites in child development. J Agric Food Chem 66(45):11881–11896. https://doi.org/10.1021/acs.jafc.8b04031

    Article  CAS  PubMed  Google Scholar 

  37. Innis SM (2011) Dietary triacylglycerol structure and its role in infant nutrition. Adv Nutr 2(3):275–283. https://doi.org/10.3945/an.111.000448

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Lind T, Johansson U, Ohlund I, Lindberg L, Lonnerdal B, Tennefors C, Hernell O (2019) Study protocol: optimized complementary feeding study (OTIS): a randomized controlled trial of the impact of a protein-reduced complementary diet based on Nordic foods. BMC Public Health 19(1):134. https://doi.org/10.1186/s12889-019-6466-1

    Article  PubMed  PubMed Central  Google Scholar 

  39. Jacobson JL, Jacobson SW, Muckle G, Kaplan-Estrin M, Ayotte P, Dewailly E (2008) Beneficial effects of a polyunsaturated fatty acid on infant development: evidence from the inuit of arctic Quebec. J Pediatr 152(3):356–364. https://doi.org/10.1016/j.jpeds.2007.07.008

    Article  CAS  PubMed  Google Scholar 

  40. Middleton P, Gomersall JC, Gould JF, Shepherd E, Olsen SF, Makrides M (2018) Omega-3 fatty acid addition during pregnancy. Cochrane Database Syst Rev. https://doi.org/10.1002/14651858.CD003402.pub3

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank the scientific coordinators (B Geay, H Léridon, C Bois, MN Dufourg, JL Lanoé, X Thierry, C Zaros), IT and data managers, statisticians (T Simeon, A Candea, S de Visme), administrative and family communication staff, and study technicians (C Guevel, M Zoubiri, L Gravier, I, Milan, R Popa) of the ELFE coordination team as well as the families that gave their time for the study.

Funding

The present study is part of the InfaDiet project, funded by an ANR grant (InfaDiet project, Grant No.: ANR-19-CE36-0008). The ELFE study is a joint project between the French Institute for Demographic Studies (INED) and the National Institute of Health and Medical Research (INSERM), in partnership with the French blood transfusion service (Etablissement français du sang [EFS]), Santé publique France, the National Institute for Statistics and Economic Studies (INSEE), the Direction générale de la santé (DGS, part of the Ministry of Health and Social Affairs), the Direction générale de la prévention des risques (DGPR, Ministry for the Environment), the Direction de la recherche, des études, de l’évaluation et des statistiques (DREES, Ministry of Health and Social Affairs), the Département des études, de la prospective et des statistiques (DEPS, Ministry of Culture), and the Caisse nationale des allocations familiales (CNAF), with the support of the Ministry of Higher Education and Research and the Institut national de la jeunesse et de l’éducation populaire (INJEP). Via the RECONAI platform, it receives a government grant managed by the National Research Agency under the “Investissements d'avenir” programme (ANR-11-EQPX-0038, ANR-19-COHO-0001). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Author notes

  1. Blandine de Lauzon-Guillain and Jonathan Y. Bernard contributed equally to this work.

Authors and Affiliations

  1. Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), Inserm, INRAE, 75004, Paris, France

    Pauline Martinot, Moufidath Adjibade, Marion Taine, Camille Davisse-Paturet, Sandrine Lioret, Marie-Aline Charles, Blandine de Lauzon-Guillain & Jonathan Y. Bernard

  2. Unité mixte Inserm-Ined-EFS ELFE, Ined, 93322, Aubervilliers, France

    Marie-Aline Charles

  3. Agency for Science, Technology and Research (A*STAR), Singapore Institute for Clinical Sciences (SICS), Singapore, Singapore

    Jonathan Y. Bernard

Authors
  1. Pauline Martinot
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Moufidath Adjibade
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marion Taine
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Camille Davisse-Paturet
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sandrine Lioret
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Marie-Aline Charles
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Blandine de Lauzon-Guillain
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jonathan Y. Bernard
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Blandine de Lauzon-Guillain.

Ethics declarations

Conflict of interest

The authors declare no competing financial interest.

Ethical approval

The ELFE study received approvals from the Advisory Committee for the Processing of Information for Health Research (Comité Consultatif sur le Traitement des Informations pour la Recherche en Santé: CCTIRS) and National Data Protection Authority (Commission National Informatique et Libertés: CNIL) and the National Council for Statistical Information (CNIS).

Consent to participate

Participating mothers had to provide written consent for their own and their child’s participation. Fathers gave signed consent for the child’s participation if present at inclusion or were informed about their rights to oppose it.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 44 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Martinot, P., Adjibade, M., Taine, M. et al. LC-PUFA enrichment in infant formula and neurodevelopment up to age 3.5 years in the French nationwide ELFE birth cohort. Eur J Nutr 61, 2979–2991 (2022). https://doi.org/10.1007/s00394-022-02863-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00394-022-02863-6

Keywords

Search

Navigation