Optimal interpregnancy interval in autism spectrum disorder: A multi-national study of a modifiable risk factor

It is biologically plausible that risk of autism spectrum disorder (ASD) is elevated by both short and long interpregnancy intervals (IPI). We conducted a retrospective cohort study of singleton, non-nulliparous live births, 1998–2007 in Denmark, Finland, and Sweden (N = 925,523 births). Optimal IPI was defined as the IPI at which minimum risk was observed. Generalized additive models were used to estimate relative risks (RR) of ASD and 95% Confidence Intervals (CI). Population impact fractions (PIF) for ASD were estimated under scenarios for shifts in the IPI distribution. We observed that the association between ASD (N = 9302) and IPI was U-shaped for all countries. ASD risk was lowest (optimal IPI) at 35 months for all countries combined, and at 30, 33, and 39 months in Denmark, Finland, and Sweden, respectively. Fully adjusted RRs at IPIs of 6, 12, and 60 months were 1.41 (95% CI: 1.08, 1.85), 1.26 (95% CI: 1.02, 1.56), and 1.24 (95% CI: 0.98, 1.58) compared to an IPI of 35 months. Under the most conservative scenario PIFs ranged from 5% (95% CI: 1%–8%) in Denmark to 9% (95% CI: 6%–12%) in Sweden. The minimum ASD risk followed IPIs of 30–39 months across three countries. These results reflect both direct IPI effects and other, closely related social and biological pathways. If our results reflect biologically causal effects, increasing optimal IPIs and reducing their indications, such as unintended pregnancy and delayed age at first pregnancy has the potential to prevent a salient proportion of ASD cases. Lay Summary: Waiting 35 months to conceive again after giving birth resulted in the least risk of autism. Shorter and longer intervals resulted in risks that were up to 50% and 85% higher, respectively. About 5% to 9% of autism cases might be avoided by optimizing birth spacing

On composite marginal likelihoods

Clustered data, Computational efficiency, Composite likelihood, Genetics, Longitudinal data, Missing data, Pairwise likelihood, Pseudolikelihood, Spatial data, Statistical efficiency, Survival analysis, Time series,