The incidence, risk factors and implications of type 1 diabetes: whole-of-population linked-data study of children in South Australia born from 1999-2013

Abstract

The aim of this doctoral thesis was to study the incidence, risk factors and outcomes of type 1 diabetes for children in South Australia, born from 1999-2013. The incidence of type 1 diabetes has doubled in the last four decades in many countries including Australia, and has substantial individual and economic consequences. Evidence from studies on type 1 diabetes aetiology and its implications is mixed. In this thesis, the linkage of multiple population-wide administrative data over 15 years, and use of rigorous epidemiological approaches has resulted in a better understanding of the risk factors and implications of type 1 diabetes. There are four studies in this doctoral thesis. In the first descriptive study, the incidence of type 1 diabetes was estimated by individual and area-level socioeconomic characteristics among children (aged ≤11 years) in South Australia, born from 2002-2013. Findings of the study showed that type 1 diabetes incidence rates differed depending on the measures of socioeconomic characteristics. Individual-level indicators showed higher type 1 diabetes incidence among more advantaged children, however, there was no clear area-level socioeconomic patterning of type 1 diabetes. Area-level measures of socioeconomic position are likely to have a greater risk of misclassification from true socioeconomic position, which suggests that the use of area-level measures may be misleading. Socioeconomic position is a major determinant of health and can modify the risk factors of type 1 diabetes. For example, as per hygiene hypothesis, the socioeconomically dis-advantaged children are less likely to have type 1 diabetes, which is supported by the findings of individual-level socioeconomic patterning of type1 diabetes in the first study. In addition, socioeconomically disadvantaged women are less likely to have a caesarean birth and more likely to smoke in pregnancy. I chose to study these two risk factors of type 1 diabetes because the evidence was inconsistent, and some studies had methodical limitations. Evidence about the effect of caesarean section on childhood type 1 diabetes is mixed; ranging from very small or no risk to 20-30% increased risk. A prevailing theory is that exposure to the gut and vaginal microbiota during a vaginal birth protects against type 1 diabetes. Therefore, in the second study, the impact of caesarean birth on childhood type 1 diabetes (aged ≤15 years) was estimated. This involved linking multiple administrative datasets of children in South Australia, born from 1999-2013. The question was extended to whether type 1 diabetes risk differed for children born by prelabour or intrapartum caesarean to further test the idea of microbiota exposure on type 1 diabetes. That is because children born by prelabour caesarean do not get exposure to maternal vaginal microbiota, and intrapartum caesarean births may have some exposure. Findings of the study obtained from Cox proportional hazard regression analysis showed a negligible 5% higher incidence (HR = 1.05, 95% CI 0.86-1.28) for caesarean births compared with normal vaginal delivery, with wide confidence intervals including the null. Contrary to the hypothesis of a higher type 1 diabetes risk for prelabor caesarean (because of non-exposure to maternal vaginal microbiota) type 1 diabetes risk for intrapartum caesarean was slightly higher (HR = 1.08, 95% CI 0.82-1.41) than prelabor caesarean (HR = 1.02, 95% CI 0.79-1.32). This negligible risk of type 1 diabetes for children who had caesarean birth, either prelabor or intrapartum, and the potential for unmeasured confounding suggested that birth method induced variation in neonatal microbiota might not be involved in modifying type 1 diabetes risk. Like caesarean section, maternal smoking in pregnancy is also a debated risk factor for childhood type 1 diabetes. Evidence about maternal smoking on childhood type 1 diabetes is inconsistent; studies have been small, and many did not adjust for important confounders or address missing data. In the third study of this doctoral thesis, the effect of maternal smoking in pregnancy on childhood type 1 diabetes was estimated using Cox proportional hazard regression analysis, once again by linking multiple administrative datasets of children in South Australia, born from 1999-2013. The analytical approach for this study ranged; from Cox proportional hazard analysis with adjustment for wide range of confounders using the SA ECDP linked data, involving multiple imputation for missing data; to conducting meta-analysis in order to get more precise estimate. But smoking is notoriously residually confounded, therefore, I made special efforts to investigate the possibility of residual confounding by using a negative control and E-value. The findings demonstrated that maternal smoking in pregnancy was associated with a 16% (HR 0.84, 95% CI 0.67, 1.08) lower childhood type 1 diabetes incidence, compared with unexposed children, which was also supported by the meta-analytic estimates of population-based cohort studies (HR 0.72, 95% CI 0.62, 0.82) and case-control studies (OR 0.71, 95% CI 0.55, 0.86). The negative control outcome and E-value analyses indicated the potential for residual confounding in the effect of maternal smoking on childhood type 1 diabetes. Triangulation of evidence from this study along with the results of similar population-based studies, suggested a small reduced risk of childhood type 1 diabetes for children exposed to maternal smoking in pregnancy. However, the mechanisms linking maternal smoking in pregnancy with childhood type 1 diabetes require further investigation. In the fourth study of this thesis, the impact of childhood type 1 diabetes on children’s educational outcomes in year/grade 5 at age ~10 were estimated, linking population-wide data of children in South Australia, born from 1999-2005. In this study, a doubly-robust analytical method called augmented inverse probability weighting (AIPW) was used to compute the average treatment effect of type 1 diabetes on children’s educational outcomes. AIPW gives an unbiased estimate if either the outcome model or the treatment model is correctly specified. The findings of this study demonstrated that children with type 1 diabetes are not disadvantaged in terms of educational outcomes in year 5, potentially reflecting improvement in type 1 diabetes management in Australia. In summary, the work in this doctoral thesis has demonstrated that type 1 diabetes incidence differed depending on the measure of socioeconomic position. The hygiene hypothesis was only supported by the individual-level socioeconomic pattering of type 1 diabetes incidence in South Australia. The involvement of birth method induced variation in neonatal microbiota in type 1 diabetes was not supported by the caesarean and childhood type 1 diabetes study. Despite the evidence of residual confounding in the estimate of maternal smoking in pregnancy on childhood type 1 diabetes, triangulation of the evidence suggested small reduced risk for children exposed to maternal smoking in pregnancy, but further research will be needed to understand the mechanism. The findings of similar educational outcomes for children with and without type 1 diabetes, highlighted the importance of improvements in diabetes management.