Prenatal smoking, alcohol and caffeine exposure and maternal-reported attention deficit hyperactivity disorder symptoms in childhood: triangulation of evidence using negative control and polygenic risk score analyses

Elis Haan*, Hannah M Sallis, Luisa Zuccolo, Jeremy Labrecque, Eivind Ystrom, Ted Reichborn-Kjennerud, Ole A Andreassen, Karoline Alexandra Havdahl, Marcus R Munafo

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

9 Citations (Scopus)
54 Downloads (Pure)


Background and aims: Studies have indicated that maternal prenatal substance use may be associated with offspring attention deficit hyperactivity disorder (ADHD) via intrauterine effects. We measured associations between prenatal smoking, alcohol and caffeine consumption with childhood ADHD symptoms accounting for shared familial factors.

Design: First, we used a negative control design comparing maternal and paternal substance use. Three models were used for negative control analyses: unadjusted (without confounders), adjusted (including confounders) and mutually adjusted (including confounders and partner's substance use). The results were meta-analysed across the cohorts. Secondly, we used polygenic risk scores (PRS) as proxies for exposures. Maternal PRS for smoking, alcohol and coffee consumption were regressed against ADHD symptoms. We triangulated the results across the two approaches to infer causality.

Setting: We used data from three longitudinal pregnancy cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC) in the United Kingdom, Generation R study (GenR) in the Netherlands and Norwegian Mother, Father and Child Cohort study (MoBa) in Norway.

Participants: Phenotype data available for children were: NALSPAC = 5455-7751; NGENR = 1537-3119; NMOBA = 28 053-42 206. Genotype data available for mothers was: NALSPAC = 7074; NMOBA = 14 583.

Measurements: A measure of offspring ADHD symptoms at age 7-8 years was derived by dichotomizing scores from questionnaires and parental self-reported prenatal substance use was measured at the second pregnancy trimester.

Findings: The pooled estimate for maternal prenatal substance use showed an association with total ADHD symptoms [odds ratio (OR)SMOKING = 1.11, 95% confidence interval (CI) = 1.00-1.23; ORALCOHOL = 1.27, 95% CI = 1.08-1.49; ORCAFFEINE = 1.05, 95% CI = 1.00-1.11], while not for fathers (ORSMOKING = 1.03, 95% CI = 0.95-1.13; ORALCOHOL = 0.83, 95% CI = 0.47-1.48; ORCAFFEINE = 1.02, 95% CI = 0.97-1.07). However, maternal associations did not persist in sensitivity analyses (substance use before pregnancy, adjustment for maternal ADHD symptoms in MoBa). The PRS analyses were inconclusive for an association in ALSPAC or MoBa.

Conclusions: There appears to be no causal intrauterine effect of maternal prenatal substance use on offspring attention deficit hyperactivity disorder symptoms.
Original languageEnglish
Number of pages14
Early online date17 Nov 2021
Publication statusE-pub ahead of print - 17 Nov 2021

Bibliographical note

Funding Information:
We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The UK Medical Research Council and Wellcome (Grant ref.: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. A comprehensive list of grants funding is available on the ALSPAC website ( ). GWAS data were generated by Sample Logistics and Genotyping Facilities at Wellcome Sanger Institute and LabCorp (Laboratory Corporation of America) using support from 23andMe. The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. We are grateful to all the participating families in Norway who take part in this on‐going cohort study. We thank the Norwegian Institute of Public Health (NIPH) for generating high‐quality genomic data. This research is part of the HARVEST collaboration, supported by the Research Council of Norway (NRC) (no. 229624). We also thank the NORMENT Centre for providing genotype data, funded by NRC (no. 223273), South East Norway Health Authority and KG Jebsen Stiftelsen. Further, we thank the Center for Diabetes Research, the University of Bergen for providing genotype data and performing quality control and imputation of the data funded by the ERC AdG project SELECTionPREDISPOSED, Stiftelsen Kristian Gerhard Jebsen, Trond Mohn Foundation, NRC, the Novo Nordisk Foundation, the University of Bergen and the Western Norway Health Authorities (Helse Vest). The general design of Generation R Study is made possible by financial support from the Erasmus Medical Center, Rotterdam, the Erasmus University Rotterdam, the Netherlands Organization for Health Research and Development (ZonMw), the Netherlands Organization for Scientific Research (NWO), the Ministry of Health, Welfare and Sport and the Ministry of Youth and Families. The Generation R Study is conducted by the Erasmus Medical Center in close collaboration with the School of Law and Faculty of Social Sciences of the Erasmus University Rotterdam, the Municipal Health Service Rotterdam area, Rotterdam, the Rotterdam Homecare Foundation, Rotterdam and the Stichting Trombosedienst and Artsenlaboratorium Rijnmond (STAR‐MDC), Rotterdam. We gratefully acknowledge the contribution of children and parents, general practitioners, hospitals, midwives and pharmacies in Rotterdam. The generation and management of GWAS genotype data for the Generation R Study were conducted at the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, the Netherlands. We would like to thank Karol Estrada, Dr Tobias A. Knoch, Anis Abuseiris, Luc V. de Zeeuw and Rob de Graaf for their help in creating GRIMP, BigGRID, MediGRID and Services@MediGRID/D‐Grid (funded by the German Bundesministerium fuer Forschung und Technology; grants 01 AK 803 A‐H, 01 IG 07015 G) for access to their grid computing resources. We thank Mila Jhamai, Manoushka Ganesh, Pascal Arp, Marijn Verkerk, Lizbeth Herrera and Marjolein Peters for their help in creating, managing and QC of the GWAS database; also, we thank Karol Estrada for their support in creation and analysis of imputed data, Sonja Swanson for her valuable ideas when designing the study and Claudia Kruithof for her contribution. This research was performed in the UK Medical Research Council Integrative Epidemiology Unit (grant number MC_UU_00011/7) and also supported by the National Institute for Health Research (NIHR) Bristol Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol. L.Z. was supported by a UK Medical Research Council fellowship (grant number G0902144). H.M.S. is supported by the European Research Council (Grant ref: 758813 MHINT). J.L. is supported by a Netherlands Organization of Scientific Research Replication Study Grant (401.18.067). The South‐Eastern Norway Regional Health Authority supported A.H. (no. 2018059 and no. 2020022). The Norwegian Research Council supported E.Y. (no. 262177 and no. 288083) (OAA, RCN no. 273291 and no. 223273), T.R.‐K. (no. 274611) and A.H. (no. 274611 and no. 288083). The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health and Social Care. This research was also conducted as part of the CAPICE (Childhood and Adolescence Psychopathology: unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe) project, funded by the European Union's Horizon 2020 research and innovation programme, Marie Sklodowska Curie Actions—MSCA‐ITN‐2016—Innovative Training Networks under grant agreement number 721567.

Publisher Copyright:
© 2021 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.


  • smoking
  • alcohol
  • caffeine
  • polygenic risk score
  • negative control
  • childhood ADHD
  • intrauterine effects
  • GenR
  • MoBa


Dive into the research topics of 'Prenatal smoking, alcohol and caffeine exposure and maternal-reported attention deficit hyperactivity disorder symptoms in childhood: triangulation of evidence using negative control and polygenic risk score analyses'. Together they form a unique fingerprint.

Cite this