Aims/hypothesis Evidence of an association between maternal smoking during pregnancy (prenatal smoking) and childhood type 1 diabetes is mixed. Previous studies have been small and potentially biased due to unmeasured confounding. The objectives of this study were to estimate the association between prenatal smoking and childhood type 1 diabetes, assess residual confounding with a negative control design and an E-value analysis, and summarise published effect estimates from a meta-analysis. Methods This whole-of-population study (births from 1999 to 2013, participants aged ≤15 years) used de-identified linked administrative data from the South Australian Early Childhood Data Project. Type 1 diabetes was diagnosed in 557 children (ICD, tenth edition, Australian Modification [ICD-10-AM] codes: E10, E101-E109) during hospitalisation (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014). Families not given financial assistance for school fees was a negative control outcome. Adjusted Cox proportional HRs were calculated. Analyses were conducted on complete-case (n = 264,542, type 1 diabetes = 442) and imputed (n = 286,058, type 1 diabetes = 557) data. A random-effects meta-analysis was used to summarise the effects of prenatal smoking on type 1 diabetes. Results Compared with non-smokers, children exposed to maternal smoking only in the first or second half of pregnancy had a 6% higher type 1 diabetes incidence (adjusted HR 1.06 [95% CI 0.73, 1.55]). Type 1 diabetes incidence was 24% lower (adjusted HR 0.76 [95% CI 0.58, 0.99]) among children exposed to consistent prenatal smoking, and 16% lower for exposure to any maternal smoking in pregnancy (adjusted HR 0.84 [95% CI 0.67, 1.08]), compared with the unexposed group. Meta-analytic estimates showed 28-29% lower risk of type 1 diabetes among children exposed to prenatal smoking compared with those not exposed. The negative control outcome analysis indicated residual confounding in the prenatal smoking and type 1 diabetes association. E-value analysis indicated that unmeasured confounding associated with prenatal smoking and childhood type 1 diabetes, with a HR of 1.67, could negate the observed effect. Conclusions/interpretation Our best estimate from the study is that maternal smoking in pregnancy was associated with 16% lower childhood type 1 diabetes incidence, and some of this effect was due to residual confounding.

Background: Despite an increase in the prevalence of sleep problems, few studies have investigated changes in the prescribing of drugs often used for managing insomnia. Aim: To explore changes in the pattern of benzodiazepine (BZD), z-drugs (zolpidem, zopiclone) and non-BZD prescriptions. Design and Setting: Open cohort study including 1,773,525 patients (55,903,294 consultations) regularly attending 404 Australian general practices from 2011-2018 (MedicineInsight). Method: Prescription rates per 1,000 consultations, the proportion of repeat prescriptions above recommendations, and the proportion of prescriptions for patients with a recent recorded insomnia diagnosis (i.e. within 2 years) were analysed using adjusted regression models. Results: Rates of BZD, z-drugs and non-BZD prescriptions were 56.6, 4.4 and 15.5/1,000 consultations in 2011 and 41.8, 3.5 and 21.5/1000 consultations in 2018, respectively. Temazepam represented 25.3% of the prescriptions and diazepam 21.9%. All BZD and zolpidem prescriptions declined from 2011-2018 [annual change varying from -1.4% to -10.8%], while non-BZD and zopiclone prescriptions increased in the same period [annual change: +5.0% to +22.6%]. Repeat prescriptions above recommendations remained below 10% for most medications, except melatonin (64.5%), zolpidem (63.3%), zopiclone (31.4%) and alprazolam (13.3%). In 2018, almost 50% of z-drugs and melatonin prescriptions were for patients with insomnia. There was 3.2%-5.9% annual increase in the proportion of prescriptions associated with a recently recorded insomnia diagnosis. Conclusion: Overall, BZD prescriptions in Australia declined from 2011-2018. However, the prescription of some of these drugs increased for patients with a recently recorded insomnia diagnosis. This is concerning because of potential adverse effects and risk of dependence.

Background: Challenges with type 1 diabetes (T1D) blood glucose management and illness-related school absences potentially influence children's educational outcomes. However, evidence about the impact of T1D on children's education is mixed. The objectives were to estimate the effects of T1D on children's educational outcomes, and compare time since T1D diagnosis (recent diagnosis [≤2 years] and 3 to 10 years long exposure) on educational outcomes. Methods: This whole-of-population study used de-identified, administrative linkeddata from the South Australian Early Childhood Data Project. T1D was identified from hospital ICD-10-AM diagnosis codes (E10, ranging E101 to E109), from 2001 to 2014. Educational outcomes were measured in grade 5 by the National Assessment Program-Literacy and Numeracy (NAPLAN, 2008-2015) for children born from 1999 to 2005. Analyses were conducted using augmented inverse probability of treatment weighting. Multiple imputations was used to impute missing data. Results: Among 61 445 children born in South Australia who had undertaken NAPLAN assessments, 162 had T1D. There were negligible differences in the educational outcomes of children with and without T1D, and between recently diagnosed and those with longer exposure. For example, the mean reading score was 482.8 ± 78.9 for children with T1D and 475.5 ± 74.3 for other children. The average treatment effect of 6.8 (95% CI-6.3-19.9) reflected one-tenth of a SD difference in the mean reading score of children with and without T1D. Conclusion: Children with T1D performed similarly on literacy and numeracy in grade 5 (age 10-years) compared to children without T1D. This could be due to effective T1D management. K E Y W O R D S augmented inverse probability weighting, childhood, educational outcomes, linked-data, type 1 diabetes 1 | INTRODUCTION Children with Type 1 diabetes (T1D) are dependent on exogenous insulin their entire lives due to the immune-mediated destruction of their insulin-producing pancreatic beta cells. In the last few decades,