Only primiparous women were included in order to avoid the confounding effects of factors associated with subsequent deliveries. There www.selleckchem.com/products/BAY-73-4506.html are limitations that should be considered. The external validity is reduced to facilities with similar socioeconomic and demographic characteristics and healthcare systems with comparable standards. The drawback is obvious given the large size of the study and the numbers of healthcare units involved so the criteria for diagnosis (ICD codes) to define outcomes may not be uniform across the study population, but the variation is most likely not related to maternal age. The MBR contains a large

body of information concerning the mother and child, which made it possible to adjust the results for confounding factors. At the same time this is a limitation as only the data available in the register could be used for adjustments. The register lacks information on ethnicity and socioeconomic status. Our effort was to evaluate obstetric and neonatal outcomes in different maternal age groups compared with women aged 25–29 overall. The only stratifications made were for year of birth, maternal BMI and smoking in early pregnancy. The data on year of birth showed that there is variability in the existence

of obstetric and neonatal diagnoses during the observation period. This may be due to true changes but may also be a result of changes in recording, including the expanding use of computerised medical records. It was therefore necessary to adjust for year of birth. Maternal BMI, maternal smoking and gestational age (for some relevant outcomes) were included in the adjusted analyses based on their well-known association with maternal and fetal outcome.26 27 Putative confounders and intermediaries were not identified with statistical analysis. To demonstrate causality between

the different outcomes evaluated in the analyses and maternal age a great number of putative intermediaries could have been considered such as the use of fertility treatment, fetal size, gestational weight gain, etc, but that was not the purpose of the study. There may be other variables (which are not intermediaries) but we have not been able to identify them. The proportion of missing data concerning the included confounders could have affected the results. The youngest age group had the highest frequency Dacomitinib of missing data on BMI (20.7%) and smoking (7.7%) compared with the reference group (13.1% and 4.9%, respectively). The distribution of BMI in the youngest age group was almost equal to the other maternal age groups. One explanation for a higher proportion of missing data in the youngest age group could be later detection of their pregnancies and attendance to the antenatal care, and questions concerning exposure in early pregnancy were not raised. Gestational age could be calculated for more than 99% of individuals in this study with only minimal variations between maternal age groups.