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Journal of Perinatal Medicine

Official Journal of the World Association of Perinatal Medicine

Editor-in-Chief: Dudenhausen, Joachim W.

Editorial Board Member: / Bancalari, Eduardo / Greenough, Anne / Genc, Mehmet R. / Chervenak, Frank A. / Chappelle, Joseph / Bergmann, Renate L. / Bernardes, J.F. / Bevilacqua, G. / Blickstein, Isaac / Cabero Roura, Luis / Carbonell-Estrany, Xavier / Carrera, Jose M. / D`Addario, Vincenzo / D'Alton, MD, Mary E. / Dimitrou, G. / Grunebaum, Amos / Hentschel, Roland / Köpcke, W. / Kawabata, Ichiro / Keirse, M.J.M.C. / Kurjak M.D., Asim / Lee, Ben H. / Levene, Malcolm / Lockwood, Charles J. / Marsal, Karel / Makatsariya, Alexander / Nishida, Hiroshi / Papp, Zoltán / Pejaver, Ranjan Kumar / Pooh, Ritsuko K. / Romero, Roberto / Saugstad, Ola D. / Schenker, Joseph G. / Sen, Cihat / Seri, Istvan / Vetter, Klaus / Winn, Hung N. / Young, Bruce K. / Zimmermann, Roland

6 Issues per year

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5-year IMPACT FACTOR: 1.597

SCImago Journal Rank (SJR) 2014: 0.731
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Prenatal and perinatal risk factors for autism

Larry Burd / Robin Severud / Jacob Kerbeshian / Marilyn G. Klug

Citation Information: Journal of Perinatal Medicine. Volume 27, Issue 6, Pages 441–450, ISSN (Print) 0300-5577, DOI: 10.1515/JPM.1999.059, June 2005

Publication History

Published Online:


Aim: To identify pre- and perinatal risk factors for autism.

Method: Case control study. We matched names of patients from North Dakota who met DSM criteria for autism, a pervasive developmental disorder, and autisticdisorder with their birth certificates. Five matched controls were selected for each case.

Results: Univariate analysis of the 78 cases and 390 controls identified seven risk factors. Logistic modeling to control for confounding produced a five variable model. The model parameters were χ2 = 36.6 and p <0.001. The five variables in the model were decreased birth weight, low maternal education, later start of prenatal care, and having a previous termination of pregnancy. Increasing father's age was associated with increased risk of autism.

Conclusion: This methodology may provide an inexpensive method for clinics and public health providers to identify risk factors and to identify maternal characteristics of patients with mental illness and developmental disorders.

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