4.6 Article

Prenatal and Perinatal Factors and Risk of Multiple Sclerosis

Journal

EPIDEMIOLOGY
Volume 20, Issue 4, Pages 611-618

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/EDE.0b013e31819ed4b9

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Funding

  1. Training Program in Psychiatric Epidemiology and Biostatistics [T32 MH17119]
  2. National Research Service Award

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Background: A potential role of prenatal and perinatal exposures in autoimmunity has been hypothesized, but few studies have examined the relation between various prenatal and perinatal factors and the risk of multiple sclerosis (MS). Methods: The study population included participants in the Nurses' Health Studies-2 prospective cohorts that together comprise 238,381 female nurses, who self-reported exposure to prenatal and perinatal factors. In addition, 35,815 nurses' mothers participated by providing detailed information regarding experiences surrounding their daughter's birth. The following prenatal and perinatal factors were studied in relation to MS: fetal growth, birth season, preterm birth, mode of delivery, maternal weight gain, medical conditions, medication use, diethylstilbestrol exposure, prenatal health care, maternal activity level, maternal obstetric history, parental age, and prenatal and childhood passive smoke exposure. Results: The sample included 723 confirmed MS cases, including 383 with diagnosis after reporting prenatal and perinatal factors. Few associations were observed. These included an increased risk among women whose mothers reported late initiation of prenatal care (after the first trimester) (27 cases; rate ratio = 1.6 [95% confidence interval = 1.0-2.4]), diabetes during pregnancy (2 cases; 10 [2.5-42]), and maternal prepregnancy overweight/obesity (20 cases; 1.7 [1.0-2.7]). Results also suggested a possible increase in incident NIS risk among women with prenatal diethylstilbestrol exposure (9 cases; 1.8 [0.93-3.5]). Conclusions: This study provides modest support for a role of prenatal factors in MS risk. The results should be interpreted cautiously due to the limited statistical power, potential for exposure misclassification, and possibility of chance findings. (Epidemiology 2009;20: 611-618)

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