Prenatal and perinatal risk factors for autism

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 autistic disorder 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 chi(2) = 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.