European Journal of Epidemiology

, Volume 32, Issue 9, pp 751–764 | Cite as

Association of light-to-moderate alcohol drinking in pregnancy with preterm birth and birth weight: elucidating bias by pooling data from nine European cohorts

  • Katrine Strandberg-LarsenEmail author
  • Gry Poulsen
  • Bodil Hammer Bech
  • Leda Chatzi
  • Sylvaine Cordier
  • Maria Teresa Grønning Dale
  • Marieta Fernandez
  • Tine Brink Henriksen
  • Vincent WV Jaddoe
  • Manolis Kogevinas
  • Claudia J. Kruithof
  • Morten Søndergaard Lindhard
  • Per Magnus
  • Ellen Aagaard Nohr
  • Lorenzo Richiardi
  • Clara L. Rodriguez-Bernal
  • Florence Rouget
  • Franca Rusconi
  • Martine Vrijheid
  • Anne-Marie Nybo Andersen


Women who drink light-to-moderately during pregnancy have been observed to have lower risk of unfavourable pregnancy outcomes than abstainers. This has been suggested to be a result of bias. In a pooled sample, including 193 747 live-born singletons from nine European cohorts, we examined the associations between light-to-moderate drinking and preterm birth, birth weight, and small-for-gestational age in term born children (term SGA). To address potential sources of bias, we compared the associations from the total sample with a sub-sample restricted to first-time pregnant women who conceived within six months of trying, and examined whether the associations varied across calendar time. In the total sample, drinking up to around six drinks per week as compared to abstaining was associated with lower risk of preterm birth, whereas no significant associations were found for birth weight or term SGA. Drinking six or more drinks per week was associated with lower birth weight and higher risk of term SGA, but no increased risk of preterm birth. The analyses restricted to women without reproductive experience revealed similar results. Before 2000 approximately half of pregnant women drank alcohol. This decreased to 39% in 2000–2004, and 14% in 2005–2011. Before 2000, every additional drink was associated with reduced mean birth weight, whereas in 2005–2011, the mean birth weight increased with increasing intake. The period-specific associations between low-to-moderate drinking and birth weight, which also were observed for term SGA, are indicative of bias. It is impossible to distinguish if the bias is attributable to unmeasured confounding, which change over time or cohort heterogeneity.


Alcohol Birth weight Cohort study Confounding Preterm birth Small for gestational age 



The authors would like to thank the CHICOS consortium and the study coordination groups, participants and funders of the participating birth cohort studies: the Aarhus Birth Cohort (ABC), the Danish National Birth Cohort (DNBC), the Generation R cohort (GenR), the INMA study, Healthy Habits for two (HHf2), The Norwegian Mother and Child Cohort (MoBa), the Nascita e INFanzia: gli Effetti dell’Ambiente study (NINFEA), the endocrine disruptors: longitudinal study on pathologies of pregnancy, infertility and childhood study (PELAGIE) and Mother Child Cohort in Crete (RHEA). The MoBa data used is from the 6th version.


This work was supported by the European Commission FP7 Programme [Health –F2-2009-241604], University of Copenhagen, and KSL was funded by the Danish Council for Independent Research I Medical Sciences (grant identifier number: 09-066049).

Author contributions

KSL, GP and AMNA designed the study. GP and KSL analysed data and drafted the paper. All authors contributed to the analysis plan and data interpretation and critically revised the paper. Authors participated in two workshops during spring 2012 at which the analysis plan and data interpretation were discussed.

Supplementary material

10654_2017_323_MOESM1_ESM.docx (16 kb)
Supplementary material 1 (DOCX 15 kb)


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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  • Katrine Strandberg-Larsen
    • 1
    Email author
  • Gry Poulsen
    • 1
  • Bodil Hammer Bech
    • 2
  • Leda Chatzi
    • 3
  • Sylvaine Cordier
    • 4
  • Maria Teresa Grønning Dale
    • 5
    • 6
  • Marieta Fernandez
    • 7
  • Tine Brink Henriksen
    • 8
  • Vincent WV Jaddoe
    • 9
    • 10
    • 11
  • Manolis Kogevinas
    • 12
  • Claudia J. Kruithof
    • 9
    • 10
  • Morten Søndergaard Lindhard
    • 8
  • Per Magnus
    • 5
  • Ellen Aagaard Nohr
    • 13
  • Lorenzo Richiardi
    • 14
  • Clara L. Rodriguez-Bernal
    • 15
    • 16
    • 17
  • Florence Rouget
    • 4
  • Franca Rusconi
    • 18
  • Martine Vrijheid
    • 12
    • 19
    • 20
  • Anne-Marie Nybo Andersen
    • 1
  1. 1.Section for Social Medicine, Department of Public HealthUniversity of CopenhagenCopenhagen KDenmark
  2. 2.Department of Public Health, Section for EpidemiologyAarhus UniversityAarhusDenmark
  3. 3.Department of Social Medicine, Faculty of MedicineUniversity of CreteRethimnoGreece
  4. 4.National Institute of Health and Medical Research (INSERM), U1085-IRSETUniversity of RennesRennesFrance
  5. 5.Norwegian Institute of Public HealthOsloNorway
  6. 6.Department of PsychologyUniversity of OsloOsloNorway
  7. 7.University of GranadaGranadaSpain
  8. 8.Department of Pediatrics, Perinatal Epidemiology Research UnitAarhus University HospitalAarhusDenmark
  9. 9.The Generation R Study Group, Erasmus MCUniversity Medical Center RotterdamRotterdamThe Netherlands
  10. 10.Department of EpidemiologyErasmus MC, University Medical Center RotterdamRotterdamThe Netherlands
  11. 11.Department of PediatricsErasmus MC, University Medical Center RotterdamRotterdamThe Netherlands
  12. 12.ISGlobal Centre for Research in Environmental Epidemiology (CREAL)BarcelonaSpain
  13. 13.Research Unit for Gynaecology and Obstetrics, Institute of Clinical ResearchUniversity of Southern DenmarkOdense MDenmark
  14. 14.Cancer Epidemiology Unit, Department of Medical SciencesUniversity of Turin and CPO-PiemonteTurinItaly
  15. 15.FISABIO—Universitat Jaume I—Universitat de València Joint Research Unit of Epidemiology and Environmental HealthValènciaSpain
  16. 16.Health Services Research Area, FISABIO Salud Pública.ValenciaValenciaSpain
  17. 17.Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC)TenerifeSpain
  18. 18.Unit of EpidemiologyMeyer Children’s University HospitalFlorenceItaly
  19. 19.University Pompeu FabraBarcelonaSpain
  20. 20.CIBER Epidemiología y Salud Pública (CIBERESP)MadridSpain

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