Previous research examining toddler sleep problems has relied almost exclusively on variable-centered statistical approaches to analyze these data, which provide helpful information about the development of the average child. The current study examined whether person-centered trajectory analysis, a statistical technique that can identify subgroups of children who differ in their initial level and/or trajectory of sleep problems, has the potential to inform our understanding of toddler sleep problems and their development.
Families (N = 185) were assessed at 12, 24, 30, and 36 months of child age. Latent class growth analysis was used to test for subgroups that differed in their 24–36 month sleep problems. Subgroups were compared on child 36-month externalizing, internalizing, and total problem behaviors, and on 12 month maternal mental health, inter-parental conflict, and maternal parenting behaviors.
Results support a four-class solution, with “low, stable,” “low, increasing,” “high, increasing,” and “high decreasing” classes. The classes whose sleep problems persisted or worsened over time had worse behavioral problems than those whose symptoms improved or remained stably low. Additionally, 12 month maternal depression and global symptom severity, intimate partner violence, and maternal harsh-intrusive parenting behaviors discriminated between the classes that had similar levels of 24 month sleep disturbance but who had diverging trajectories over time.
This statistical approach appears to have the potential to increase understanding of sleep problem trajectories in the early years of life. Maternal mental health, intimate partner violence, and parenting behaviors may be clinically useful markers of risk for the persistence or development of toddler sleep problems.
