Maternal vaccination and preterm birth: using data mining as a screening tool



The main purpose of this study was to identify possible associations between medicines used in pregnancy and preterm deliveries using data mining as a screening tool.


Prospective cohort study.


We used data mining to identify possible correlates between preterm delivery and medicines used by 92,235 pregnant Danish women who took part in the Danish National Birth Cohort (DNBC). We then evaluated the association between one of the identified exposures (vaccination) and the risk for preterm birth by using logistic regression. The women were classified into groups according to their exposure to vaccination. The regression analyses were adjusted for the following covariates: parity, infant’s gender, maternal Body-Mass Index (BMI), age, smoking, drinking, job, number of inhabitants in the place of residence, infections, diabetes, high blood pressure and preeclampsia.

Main outcome measure

Preterm birth, a delivery occurring before the 259th day of gestation (i.e., less than 37 full weeks).


Data mining had indicated that maternal vaccination (among other factors) might be related to preterm birth. The following regression analysis showed that, the women who reported being vaccinated shortly before or during gestation had a slightly higher risk of giving preterm birth (O.R. = 1.14; 95% CI 1.04–1.25) as compared to the non-vaccinated group.


Whether the association between maternal vaccination and the risk for preterm birth found here is causal or not deserves further studies. Data mining, especially with additional refinements, may be a valuable and very efficient tool to screen large databases for relevant information which can be used in clinical and public health research.

This is a preview of subscription content, access via your institution.

Fig. 1


  1. 1.

    Yuksel B, Greenough A. Birth weight and hospital readmission of infants born prematurely. Arch Pediatr Adolesc Med 1994;148(4):384–8.

    PubMed  CAS  Google Scholar 

  2. 2.

    Berkowitz GS, Papiernik E. Epidemiology of preterm birth. Epidemiol Rev 1993;15(2):414–43.

    PubMed  CAS  Google Scholar 

  3. 3.

    Navas L, Wang E, de Carvalho V, Robinson J. Improved outcome of respiratory syncytial virus infection in a high-risk hospitalized population of Canadian children. Pediatric Investigators Collaborative Network on Infections in Canada. J Pediatr 1992;121(3):348–54.

    PubMed  CAS  Google Scholar 

  4. 4.

    Rasmussen S. Fødselsregisteret 2003. The Danish National Health Service 2003.

  5. 5.

    Sorensen HT, Nielsen GL, Olesen C, et al. Risk of malformations and other outcomes in children exposed to fluconazole in utero. Br J Clin Pharmacol 1999;48:234–8.

    PubMed  CAS  Article  Google Scholar 

  6. 6.

    Nielsen GL, Sorensen HT, Larsen H, Pedersen L. Risk of adverse birth outcome and miscarriage in pregnant users of non-steroidal anti-inflammatory medicines: population based observational study and case-control study. Br Med J 2001;322:266–70.

    CAS  Article  Google Scholar 

  7. 7.

    Olesen C, Thrane N, Nielsen GL, et al. A population-based prescription study of asthma medicines during pregnancy: changing the intensity of asthma therapy and perinatal outcomes. Respiration 2001;68:256–261.

    PubMed  CAS  Article  Google Scholar 

  8. 8.

    Thorp JM Jr, Hartmann KE, Berkman ND, Carey TS, Lohr KN, et al. Antibiotic therapy for the treatment of preterm labor: a review of the evidence. Am J Obstet Gynecol 2002;186(3):587–92.

    PubMed  CAS  Article  Google Scholar 

  9. 9.

    King JF, Flenady VJ, Papatsonis DN, Dekker GA, Carbonne B. Calcium channel blockers for inhibiting preterm labour (Cochrane Review). Cochrane Database Syst Rev CD002255;2003.

  10. 10.

    Bishop CM. Neural networks for pattern recognition. Oxford Univ. Press; 1995. 482 pp. ISBN 1-883157-00-5.

  11. 11.

    Goodwin LK, Iannacchione MA, Hammond WE, Crockett P, Maher S, Schlitz K. Data Mining Methods Find Demographic Predictors of Preterm Birth. Nurs Res. 2001;50(6):340–5.

    PubMed  CAS  Article  Google Scholar 

  12. 12.

    Olsen J, Melbye M, Olsen SF, Sorensen TI, et al. The Danish national birth cohort—its background, structure and aim. Scand J Public Health 2001;29:300–7.

    PubMed  CAS  Article  Google Scholar 

  13. 13.

    Witten IH, Frank E. Data mining: practical machine learning tools with Java implementations. Morgan Kaufmann, 2000; 371 pp. ISBN 1-55860-552-5.

  14. 14.

    Kask K, Dechter R. A general scheme for automatic generation of search heuristics from specification dependencies. Artif Intell 2001;129:91–131.

    Article  Google Scholar 

  15. 15.

    Alberman E. Low birth weight and prematurity. In: Pless IB, editors. The epidemiology of childhood disorders. New York: Oxford; 1994. p. 49–65. 531 pp. ISBN 0195075161.

  16. 16.

    Bracken MB, editor. Perinatal epidemiology. New York, Oxford University Press; 1984; 550 pp. ISBN 0195033892.

  17. 17.

    Wallis DH, Chin JL, Sur DKC. Influenza vaccination in pregnancy: current practices in a suburban community. J AM Board Fam Pract 2004;17:287–91.

    PubMed  Google Scholar 

  18. 18.

    Bridges CB, Harper SA, Fukuda K, Uyeki TM, Cox NJ, Sigleton JA. Advisory Committee on Immunization Practices. Prevention and control of influenza. Recommendations of the Advisory Committee on Immunization Practices (ACIP). MMWR Recomm Rep., 2003;52(RR-8):1–34; quiz CE1–4.

  19. 19.

    Yeager DP, Toy EC, Baker III B. Influenza vaccination in pregnancy. Am J Perinatology 1999;16(6):283–6.

    CAS  Google Scholar 

  20. 20.

    Reddy PA, Gupta I, Ganguly NK, Hepatitis-B vaccination in pregnancy: safety and immunogenic response in mothers and antibody transfer to neonates. Asia-Oceania J Obstet Gynaecol 1994;20(4):361–365.

    PubMed  CAS  Google Scholar 

  21. 21.

    Ingardia CJ, Kelley L, Lerer T, Wax JR, Steinfeld JD. Correlation of maternal and fetal hepatitis B antibody titers following maternal vaccination in pregnancy. Am. J. of Perinatology 1999;16(3):129–32.

    CAS  Article  Google Scholar 

  22. 22.

    No authors listed. Hazards of vaccination in pregnancy. Medicine and therapeutics bulletin, 1973;11(4):13–5.

Download references


We would like to thank Mr. Kenn S. Nielsen for the excellent technical and data management support; to Mrs. Inger Kristine Meder for helping with the last details in the manuscript preparation; and to the managerial team of the Danish National Birth Cohort, which consisted of: Jørn Olsen (Chair), Mads Melbye, Anne Marie Nybo Andersen, Sjurdur F. Olsen, Thorkild I.A. Sørensen, and Peter Aaby. This study was approved by the Copenhagen Section of the Danish Central Scientific-Ethical Committee by protocol no. KF-01-471/94 and KF-01-012/97.

Funding: One of the authors, I. Orozova-Bekkevold was financially supported by the Danish Pharmacy Foundation (Project nr: J.77–2003). Financial support for the Danish National Birth Cohort was obtained from the Danish National Research Foundation, the March of Dimes Birth Defects Foundation, the European Union (QLK1-2000-00083), the Pharmacy Foundation, the Egmont Foundation, the Augustinus Foundation and the Health Foundation.

Author information



Corresponding author

Correspondence to Ivanka Orozova-Bekkevold.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Orozova-Bekkevold, I., Jensen, H., Stensballe, L. et al. Maternal vaccination and preterm birth: using data mining as a screening tool. Pharm World Sci 29, 205–212 (2007).

Download citation


  • Data mining
  • Danish National Birth Cohort
  • Denmark
  • Maternal vaccination
  • Preterm birth