IMPORTANCEEvidence from studies investigating the association of epidural analgesia use during labor and delivery with risk of autism spectrum disorder (ASD) in offspring is conflicting.OBJECTIVE To assess the association of maternal use of epidural analgesia during labor and delivery with ASD in offspring using a large population-based data set with clinical data on ASD case status. DESIGN, SETTING, AND PARTICIPANTSThis population-based retrospective cohort study included term singleton children born in British Columbia, Canada, between April 1, 2000, and December 31, 2014. Stillbirths and cesarean deliveries were excluded. Clinical ASD diagnostic data were obtained from the British Columbia Autism Assessment Network and the British Columbia Ministry of Education. All children were followed up until clinical diagnosis of ASD, death, or the study end date of December 31, 2016.EXPOSURES Use of epidural analgesia during labor and delivery. MAIN OUTCOMES AND MEASURESA clinical diagnosis of ASD made by pediatricians, psychiatrists, and psychologists with specialty training to assess ASD. Cox proportional hazards models were used to estimate the hazard ratio of epidural analgesia use and ASD. Models were adjusted for maternal sociodemographics; maternal conditions during pregnancy; labor, delivery, and antenatal care characteristics; infant sex; gestational age; and status of small or large for gestational age. A conditional logistic regression model matching women with 2 births or more and discordance in ASD status of the offspring also was performed. RESULTSOf the 388 254 children included in the cohort (49.8% female; mean gestational age, 39.2 [SD, 1.2] weeks; mean follow-up, 9.05 [SD, 4.3] years), 5192 were diagnosed with ASD (1.34%) and 111 480 (28.7%) were exposed to epidural analgesia. A diagnosis of ASD was made for 1710 children (1.53%) among the 111 480 deliveries exposed to epidural analgesia (94 157 women) vs a diagnosis of ASD in 3482 children (1.26%) among the 276 774 deliveries not exposed to epidural analgesia (192 510 women) (absolute risk difference, 0.28% [95% CI, 0.19%-0.36%]). The unadjusted hazard ratio was 1.32 (95% CI, 1.24-1.40) and the fully adjusted hazard ratio was 1.09 (95% CI, 1.00-1.15). There was no statistically significant association of epidural analgesia use during labor and delivery with ASD in the within-woman matched conditional logistic regression (839/1659 [50.6%] in the exposed group vs 1905/4587 [41.5%] in the unexposed group; fully adjusted hazard ratio, 1.07 [95% CI, 0.87-1.30]). CONCLUSIONS AND RELEVANCEIn this population-based study, maternal epidural analgesia use during labor and delivery was associated with a small increase in the risk of autism spectrum disorder in offspring that met the threshold for statistical significance. However, given the likelihood of residual confounding that may account for the results, these findings do not provide strong supporting evidence for this association.

IMPORTANCEThe etiology of autism spectrum disorder (ASD) is poorly understood, but prior studies suggest associations with airborne pollutants.OBJECTIVE To evaluate the association between prenatal exposures to airborne pollutants and ASD in a large population-based cohort. DESIGN, SETTING, AND PARTICIPANTSThis population-based cohort encompassed nearly all births in Metro Vancouver, British Columbia, Canada, from 2004 through 2009, with follow-up through 2014. Children were diagnosed with ASD using a standardized assessment with the Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule. Monthly mean exposures to particulate matter with a diameter less than 2.5 μm (PM 2.5 ), nitric oxide (NO), and nitrogen dioxide (NO 2 ) at the maternal residence during pregnancy were estimated with temporally adjusted, high-resolution land use regression models. The association between prenatal air pollution exposures and the odds of developing ASD was evaluated using logistic regression adjusted for child sex, birth month, birth year, maternal age, maternal birthplace, and neighborhood-level urbanicity and income band. Data analysis occurred from June 2016 to May 2018.EXPOSURES Mean monthly concentrations of ambient PM 2.5 , NO, and NO 2 at the maternal residence during pregnancy, calculated retrospectively using temporally adjusted, high-resolution land use regression models. MAIN OUTCOMES AND MEASURESAutism spectrum disorder diagnoses based on standardized assessment of the Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule. The hypothesis being tested was formulated during data collection. RESULTSIn a cohort of 132 256 births, 1307 children (1.0%) were diagnosed with ASD by the age of 5 years. The final sample size for the PM 2.5 -adjusted model was 129 439 children, and for NO and NO 2 , it was 129 436 children; of these, 1276 (1.0%) were diagnosed with ASD. Adjusted odds ratios for ASD per interquartile range (IQR) were not significant for exposure to PM 2.5 during pregnancy (1.04 [95% CI, 0.98-1.10] per 1.5 μg/m 3 increase [IQR] in PM 2.5 ) or NO 2 (1.06 [95% CI, 0.99-1.12] per 4.8 ppb [IQR] increase in NO 2 ) but the odds ratio was significant for NO (1.07 [95% CI, 1.01-1.13] per 10.7 ppb [IQR] increase in NO). Odds ratios for male children were 1.04 (95% CI, 0.98-1.10) for PM 2.5 ; 1.09 (95% CI, 1.02-1.15) for NO; and 1.07 (95% CI, 1.00-1.13) for NO 2 . For female children, they were for 1.03 (95% CI, 0.90-1.18) for PM 2.5 ; 0.98 (95% CI, 0.83-1.13) for NO; and 1.00 (95% CI, 0.86-1.16) for NO 2 .CONCLUSIONS AND RELEVANCE In a population-based birth cohort, we detected an association between exposure to NO and ASD but no significant association with PM 2.5 and NO 2 .

After 1 or 2 previous cesarean births, risks for adverse outcomes between planned vaginal and cesarean birth are reduced among women with a prior vaginal birth. Our data offer women and their health care providers the opportunity to consider risk profiles separately for women who have and have not had a prior vaginal delivery.

BackgroundThe aim of this study was to assess the cost-effectiveness of administering magnesium sulphate to patients in whom preterm birth at < 32+0 weeks gestation is either imminent or threatened for the purpose of fetal neuroprotection.MethodsMultiple decision tree models and probabilistic sensitivity analyses were used to compare the administration of magnesium sulphate with the alternative of no treatment. Two separate cost perspectives were utilized in this series of analyses: a health system and a societal perspective. In addition, two separate measures of effectiveness were utilized: cases of cerebral palsy (CP) averted and quality-adjusted life years (QALYs).ResultsFrom a health system and a societal perspective, respectively, a savings of $2,242 and $112,602 is obtained for each QALY gained and a savings of $30,942 and $1,554,198 is obtained for each case of CP averted when magnesium sulphate is administered to patients in whom preterm birth is imminent. From a health system perspective and a societal perspective, respectively, a cost of $2,083 is incurred and a savings of $108,277 is obtained for each QALY gained and a cost of $28,755 is incurred and a savings of $1,494,500 is obtained for each case of CP averted when magnesium sulphate is administered to patients in whom preterm birth is threatened.ConclusionsAdministration of magnesium sulphate to patients in whom preterm birth is imminent is a dominant (i.e. cost-effective) strategy, no matter what cost perspective or measure of effectiveness is used. Administration of magnesium sulphate to patients in whom preterm birth is threatened is a dominant strategy from a societal perspective and is very likely to be cost-effective from a health system perspective.

Administrative data are frequently used to identify Autism Spectrum Disorder (ASD) cases in epidemiological studies. However, validation studies on this mode of case ascertainment have lacked access to high‐quality clinical diagnostic data and have not followed published reporting guidelines. We report on the diagnostic accuracy of using readily available health administrative data for pediatric ASD case ascertainment. The validation cohort included almost all the ASD‐positive children born in British Columbia, Canada from April 1, 2000 to December 31, 2009 and consisted of 8,670 children in total. 4,079 ASD‐positive and 2,787 ASD‐negative children were identified using Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview‐Revised (ADI‐R) assessments done through the British Columbia Autism Assessment Network (BCAAN). An additional 1,804 ADOS/ADI‐R assessed ASD‐positive children were identified using Ministry of Education records. This prospectively collected clinical data (the diagnostic gold standard) was then linked to each child's physician billing and hospital discharge data. The diagnostic accuracy of 11 algorithms that used the administrative data to assign ASD case status was assessed. For all algorithms, high positive predictive values (PPVs) were observed alongside low values for other measures of diagnostic accuracy illustrating that PPVs alone are not an adequate measure of diagnostic accuracy. We show that British Columbia's health administrative data cannot reliably be used to discriminate between children with ASD and children with other developmental disorders. Utilizing these data may result in misclassification bias. Methodologically sound, region‐specific validation studies are needed to support the use of administrative data for ASD case ascertainment. Autism Res 2020, 13: 456–463. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. Lay Summary Health administrative data are frequently used to identify Autism Spectrum Disorder (ASD) cases for research purposes. However, previous validation studies on this sort of case identification have lacked access to high‐quality clinical diagnostic data and have not followed published reporting guidelines. We show that British Columbia's health administrative data cannot reliably be used to discriminate between children with ASD and children with other developmental disorders.