14 Obstetrics and Gynecology International Table 9: The eﬀect of adjustment for some maternal characteristics on the eﬀect of tricyclic antidepressants (TCAs) on the occurrence of infant cardiac defect and on the eﬀect of antidepressants on preterm birth. Variables adjusted for None (=crude) Year of delivery Year of delivery and maternal age Year of delivery and maternal age and parity Year of delivery and maternal age and smoking Year of delivery and maternal age and smoking and BMI Cardiac defects after TCA OR 95% CI 1.64 1.14–2.36 1.75 1.22–2.52 1.74 1.21–2.50 1.74 1.21–2.50 1.72 1.19–2.49 1.68 1.15–2.45 <37 weeks after antidepressants OR 95% CI 1.60 1.50–1.72 1.60 1.44–1.77 1.58 1.40–1.79 1.54 1.37–1.77 1.44 1.23–1.69 1.42 1.32–1.52 Table 10: Eﬀect of stepwise adjustment for maternal characteristics in the analysis of the risk for drug-treated ADHD in infants conceived by IVF [34]. Variables adjusted for None (=crude) Year of delivery Year of delivery, maternal age, parity, smoking and country of birth Year of delivery, maternal age, parity, smoking, country of birth, and BMI Year of delivery, maternal age, parity, smoking, country of birth, and education Year of delivery, maternal age, parity, smoking, country of birth, and education, with exclusion of non-cohabiting women OR 0.71 0.77 0.91 0.95 1.14 1.18 95% CI 0.62–0.81 0.68–0.87 0.81–1.05 0.83–1.08 0.99–1.31 1.05–1.36 intervals will be adequate. When very strong eﬀects are seen of maternal age, notably in the lower or upper end of the age range, more exact maternal age adjustments, for example, based on one-year intervals, may be needed. Examples are the steeply increasing risk for a Down infant birth with high maternal age and a steeply increasing risk for an infant with gastroschisis with low maternal age. In both these examples, the regression between age and outcome is nonlinear, that is why a linear regression analysis may underestimate maternal age as a risk factor. If maternal smoking appears as a risk factor, adjustment for any smoking may be insuﬃcient and so may a crude division into <10 and ≥10 cigarettes per day. In the latter group will be included both women who smoke 10 cigarettes per day and women who smoke 20 or more cigarettes per day, and the proportion of these groups may well vary between women who have used for instance psychoactive drugs and women who have not used such drugs. If the adjustment for smoking results in a reduction of the risk estimate, one should consider the possibility that the remaining estimate may be too high due to crude information on smoking. A similar eﬀect can occur at adjustment for BMI, if only crude groups are used. An adjustment for the use of any other drug than the drug under study may in a similar way be insuﬃcient if the patterns of drug use diﬀer. A substantial percentage of women using antidepressants also use sedatives while adjustment for any other drug use will ineﬀectively adjust for the possible eﬀect of the sedatives. 3.9. The Eﬀect of Adjusting for Confounding on Risk Estimates. The eﬀects of confounders on outcome vary according to the nature of exposure and outcome. The most important eﬀects should be expected in analyses of drugs which are used at diﬀerent rates in diﬀerent groups of women, for instance, diﬀerent age groups. The confounding variables must, however, also aﬀect outcome in order to be relevant. Most variables studied in Table 2 had only moderate eﬀect on the risk for any relatively severe malformation, that is why the eﬀect of the clear diﬀerences in the use of antidepressants in early pregnancy will be weak. In Table 9 it is also seen that the stepwise adjustment for some of these variables does not markedly change the risk estimate for a cardiac malformation after maternal use of a tricyclic antidepressant in early pregnancy: the estimates vary around 1.6 and 1.7, and the crude estimate is close to the estimate after adjustment for year of delivery, maternal age, parity, smoking in early pregnancy, and prepregnancy BMI. The table also shows similar stepwise adjustments for risk estimates of preterm birth after maternal use of antidepressants, and here the adjustment reduces the excess risk with nearly one-third, from 60% increased risk to 42% increased risk, and the strongest eﬀects are seen from maternal smoking and obesity. In special circumtances, the signiﬁcance of confounding becomes very important. One example is a recent study on the risk for infants conceived after IVF to develop drug- treated ADHD [38]. A summary is given in Table 10. The crude OR indicates a statistically signiﬁcant protective eﬀect, that IVF children have a lower risk for this condition than other children. As in all studies of long-term eﬀect, year of delivery can be an important confounder if exposure rate (in this case use of IVF) increases during the observation period while the follow-up time of the children decreases. Adjustment for year of delivery increases the OR but it is still signiﬁcantly below 1.0. Adjustment for some maternal