The possibility of confounding due to differences between vaccinated and unvaccinated individuals included in observational studies of influenza immunization is well recognized [12] . The most significant type of confounding in influenza studies is due to a higher likelihood of individuals with high functional capacity (i.e., healthier The primary adjusted models were based on the approach of identifying covariates that produce adjusted ORs of 1 during the pre-influenza period and included the following covariates: gestational age for first antenatal visit, maternal diabetes (gestational and/or non-gestational), multivitamin use in pregnancy, history of alcohol use during pregnancy, education less than 12th grade, and mother married. b In the secondary adjusted models, the covariates included gestational age at first antenatal visit, maternal age less than 19 y, maternal age more than 35 y, multiple births, maternal medical risk factors, labor/delivery complications, birth defects, maternal diabetes (gestational and/or non-gestational), hypertension (treated or untreated), mother insured, multivitamin use in pregnancy, history of smoking during pregnancy, history of alcohol use during pregnancy, black race, education less than 12th grade, mother's marital status, and maternal weight before pregnancy. The ORs for association between the different covariates and receipt of influenza vaccine were computed using logistic regression. c Ratio of the odds of prematurity in newborns of mothers who received influenza vaccine during pregnancy compared to mothers who did not receive the vaccine by intensity of influenza activity, e.g., in the analysis of all seasons/periods, the (unadjusted) odds of prematurity were 25% lower among the infants of mothers who received the influenza vaccine during pregnancy than among infants whose mothers who did not receive the vaccine. doi:10.1371/journal.pmed.1000441.t002 Table 3 . ORs of being SGA by maternal influenza vaccine status (ORs,1 imply a protective association of the vaccine). The primary adjusted models were based on the approach of identifying covariates that produce adjusted ORs of 1 during the pre-influenza period and included the following covariates: gestational age for first antenatal visit, maternal diabetes (gestational and/or non-gestational), multivitamin use in pregnancy, history of alcohol use during pregnancy, education less than 12th grade, and mother married. b In the secondary adjusted models, the covariates included gestational age at first antenatal visit, maternal age less than 19 y, maternal age more than 35 y, multiple births, maternal medical risk factors, labor/delivery complications, birth defects, maternal diabetes (gestational and/or non-gestational), hypertension (treated or untreated), mother insured, multivitamin use in pregnancy, history of smoking during pregnancy, history of alcohol use during pregnancy, black race, education less than 12th grade, mother's marital status, and maternal weight before pregnancy. The ORs for association between the different covariates and receipt of influenza vaccine were computed using logistic regression. c Ratio of the odds of being SGA among newborns of mothers who received influenza vaccine during pregnancy compared to those born to mothers who did not receive the vaccine by intensity of influenza activity, e.g., in the analysis of all seasons/periods, the (unadjusted) odds of being SGA were 84% lower among the newborns of mothers who received influenza vaccine during pregnancy than among infants whose mothers who did not receive the vaccine. doi:10.1371/journal.pmed.1000441.t003 individuals) to get vaccinated-a phenomenon often known as the ''healthy user effect.'' However, most observational studies where significant confounding has been documented were conducted in the elderly and included a relatively nonspecific end point of all-cause mortality. It is reasonable to assume that, compared to older individuals, women of reproductive age may be less likely to have significant functional limitation even in the presence of co-morbidities. Therefore, influenza vaccine studies in this age group may be less likely to suffer from bias due to the healthy user effect. Moreover, we found no statistically significant difference between the vaccinated women and the unvaccinated women in terms of gestational age at which they sought antenatal care. On the other hand, the possibility of other confounders cannot be discounted in studies involving pregnant women. In order to address confounding, we used the pre-influenza period (i.e., the season where vaccine was available but there was minimal circulation of influenza virus) as the ''control'' period. The use of the pre-influenza period for selecting confounders from a broad set of covariates is an approach suggested by Nelson et al. [12] and Jackson et al. [11] that takes advantage of the seasonality of influenza circulation. The associations observed in our study were robust to adjustment for confounders identified using this approach (and the more traditional approach)-supporting the validity of our findings. Influenza virus, particularly seasonal influenza virus, rarely crosses the placenta [3, 17, 18] . However, the effect of infection on prematurity is thought be at least partially mediated through inflammatory pathways [5, 6] . Increase in pro-inflammatory cytokines (e.g., IL-1, IL-6 and TNF-a) and reduction in antiinflammatory cytokines (e.g., IL-10) have been linked to preterm labor [6, 19, 20] . IL-1 stimulates the amnion and the decidua to produce prostaglandins and can stimulate myometrial contractions [20] . Prostaglandins are known to play an important role in the initiation and progression of labor [21] . Moreover, in animal models, administration of IL-1 results in preterm birth [20] . Similarly, TNF-a induces the amnion, the decidua, and the myometrium to produce prostaglandins, and administration of TNF-a to pregnant animals can induce preterm labor [19, 22] . Recent studies have shown that influenza virus infection induces gene expression of pro-inflammatory cytokines including IL-1b, IL-6, TNF-a, interferon (IFN)-b, IFN-a, and granulocyte macrophage colony-stimulating factor (GM-CSF) [19] .