Factors Affecting the Timing of an Autism Spectrum Diagnosis

Sunday, 27 July 2014: 10:50 AM

Ashley Darcy Mahoney, PhD, NNP-BC
School of Nursing, Emory University, Atlanta, GA
Melinda Higgins, PhD
Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA
Bonnie Minter, MS, CPNP
Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA

Purpose:

The prevalence of children with autistic spectrum disorders (ASD) has increased over the past two decades. Over this same time period, the number of infants born preterm has also increased. Early diagnosis of ASD enables interventions that improve the functioning of children with ASD. To address the
question of whether late-preterm (LPT, 34-36 weeks) infants carry the same risk for ASD as full-term infants, this study explored possible relationships between gestational age and ASD diagnosis. Additionally, this study addressed how maternal education, race, age, marital status and neonatal factors collectively affect the timing of when a child is diagnosed with ASD, realizing that early diagnosis improves outcomes.

Methods:

A retrospective cohort analysis of 664 children was undertaken at the largest Autism research and treatment center in the country. The application of Bayes rule was used given that we do not have sufficient information about the joint probabilities related to prematurity and autism. Using the estimated gestational age proportions within ASD diagnosis, plus national estimates of ASD and prematurity, probabilities for ASD within a given gestational age were calculated. For all variables, comparisons were made between infants diagnosed with ASD and those not diagnosed with ASD using independent group t-tests, non-parametric tests, and chi-square tests. The final predictive logistic regression model selected used forward stepwise likelihood ratio variable selection to create the best ASD predictive model for timing of diagnosis.

Results:

 On average, the 664 children in this cohort were 38.1 (SD 3.3) weeks with 7.1% Early Preterm (EPT, <33 weeks) and 13.9% LPT. Sixty-one percent of the infants seen (406/664) were diagnosed with ASD. Forty-six percent were Caucasian and 34% were African American.  In comparison to full term infants, EPT infants were significantly more likely to be diagnosed with ASD (1.9 times higher risk (95% CI [1.3, 2.5] significant at α=.05). We observed an elevated prevalence of ASD among children born LPT (1.2 times higher risk (95% CI [0.9, 1.5] not significant at α=.05), the magnitude of the elevation was not statistically significant. Reviewing the hazard ratios, older, married parents were associated with a having a child diagnosed with ASD at a younger age. Male infants and African American infants had a higher probability of an earlier ASD diagnosis than female infants and Caucasian infants, respectively. No statistically significant difference of timing of ASD diagnosis was found in infants across gestational age groups.

Conclusion:

EPT infants were significantly more likely to be diagnosed with ASD as compared to their term counterparts. Our study identified a two-times greater risk among children born EPT. We observed an elevated prevalence of ASD among children born LPT, the magnitude of the elevation was not statistically significant. This study also demonstrates that children are more likely to have an earlier ASD diagnosis if their parents are older, if the child’s gender is male, and if the child’s parents are married. Early identification of risk factors offers an avenue for early diagnostic evaluation and referral.