Int. J. Environ. Res. Public Health 2012, 9 280 for first trimester exposure to O3 was for those pregnancies where the conception day happened during autumn, and this was the only season-specific O3 effect where the confidence interval included the null. Table 6. Season-specific ORs for preterm delivery and β-coefficients for gestational period (in weeks) per 10 µg/m3 increase in 1st trimester O3 concentration. Season C(9r5u%de COIR) A(d9j5u%steCdIO)aR Crude(s9l5o%pe CesIt)imates estiAmdajtuesste(9d5s%lopCeI) a Spring 1.10 (1.02, 1.18) 1.13 (1.05, 1.21) −0.06 (−0.09, −0.03) −0.07 (−0.10, −0.04) Summer 1.05 (0.99, 1.10) 1.13 (1.02, 1.26) −0.03 (−0.06, 0.00) −0.04 (−0.07, −0.02) Autumn 1.05 (0.96, 1.14) 1.07 (0.98, 1.16) −0.06 (−0.09, −0.02) −0.06 (−0.09, −0.03) Winter 1.15 (1.08, 1.21) 1.12 (1.04, 1.20) −0.07 (−0.10, −0.04) −0.06 (−0.09, −0.03) a Multiple pollutant model adjusted for maternal smoking, parity, sex of the child, first trimester temperature, first trimester relative humidity, first trimester NO2, a seasonal spline and long term cubic regression spline. High exposure to O3 during the first trimester was associated with a shorter duration of gestation, regardless of season of conception, although the association was weakest during summer (Table 5). 4. Discussion We found an association between first trimester O3 exposure and increased risk of preterm birth, which was consistent with descriptive data for the different years. We have studied the effects of temporal fluctuations in air pollution exposure between pregnancies. This approach gives us the ability to detect effects better for exposures that vary more strongly in time than in space. That is, this study is well suited to detect effects of O3, but not so well suited to detect the full effects from air pollutants with an additional within city variation, i.e., NO2. At this latitude, O3 levels are mainly dependent on the incoming air masses, and the local formation is very limited [21]. At the same time, the regional background concentrations of pollutants such as NO2 are low, and the fluctuations in concentrations are highly dependent on the dispersion of emissions from local traffic in the city. This means that periods of stagnation will increase exhaust levels everywhere in the city, though more in some streets and districts than in others. As such, there will have been some misclassification of NO2 exposures, which as non-differential typically would tend to produce attention in slopes and odds ratios. We use a few stations only for a quite large area. However, air pollution data from the same monitoring stations have for this population shown significant associations in time-series studies of daily mortality and hospitalisations in APHEA-2 and other studies, indicating their validity [22]. The Medical Birth Registry has existed in Sweden since 1973, is almost complete (99%) and of very high quality [23]. Because of this it is very unlikely that missing data has had any impact on the results of this study. One quality issue we observed with the Medical Birth Registry was the lack of information on smoking habits. In 7.4% of the births in this study we did not have information on smoking status. Possible explanations to these missing records are; unwillingness to respond to this question during the first antenatal care visit, failure to report information from antenatal care by the birthing centre or antenatal care started in a later stage of pregnancy. This is probably more common among women with social problems. There is of course the issue of migration. Exposure misclassification will occur for women who moved to the study area during gestation. However, although such movements may bias associations towards the null, we do not believe these migration