Christine Fountain

Age of diagnosis for autism: individual and community factors across 10 birth cohorts

Background The incidence of autism rose dramatically between 1992 and 2001, while the age at which children were first diagnosed declined. During this period the size and composition of the autism caseload has changed, but little is known about whether the factors associated with the timing of diagnosis may also have shifted. Using a multilevel analysis strategy, the individual and community-level factors associated with age of diagnosis were modelled across 10 birth cohorts of California children. Methods Linked birth and administrative records on 17 185 children with diagnoses of autistic disorder born in California between 1992 and 2001 and enrolled with the California Department of Developmental Services (DDS) were analysed. Information on cases, their parents and their residential location were extracted from birth and DDS records. Zip codes of residence were matched to census data to create community-level measures. Multilevel linear models were estimated for each birth cohort, with individual-level effects for sex, race, parental characteristics, poverty status, birth order and symptom expression. At the community level measures of educational and economic composition, local autism prevalence and the presence of a child psychiatrist were included. Results Children with highly educated parents are diagnosed earlier, and this effect has strengthened over time. There is a persistent gap in the age of diagnosis between high and low socioeconomic status (SES) children that has shrunk but not disappeared over time. Conclusion Routine screening for autism in early childhood for all children, particularly those of low SES, is necessary to eliminate disparities in early intervention.

Six Developmental Trajectories Characterize Children With Autism

OBJECTIVE: The goal of this study was to describe the typical longitudinal developmental trajectories of social and communication functioning in children with autism and to determine the correlates of these trajectories. METHODS: Children with autism who were born in California from 1992 through 2001 and enrolled with the California Department of Developmental Services were identified. Subjects with <4 evaluations present in the database were excluded, resulting in a sample of 6975 children aged 2 to 14 years. Score sequences were constructed based on 9 evaluative items for social, communication, and repetitive behavior functioning. Typical trajectories were identified by using group-based latent trajectory modeling, and multinomial logistic regression models were used to determine the odds of classification within each trajectory varied by individual and family-level factors. RESULTS: Six typical patterns of social, communication, and repetitive behavior functioning were identified. These trajectories displayed significant heterogeneity in developmental pathways, and children whose symptoms were least severe at first diagnosis tended to improve more rapidly than those severely affected. One group of ∼10% of children experienced rapid gains, moving from severely affected to high functioning. Socioeconomic factors were correlated with trajectory outcomes; children with non-Hispanic, white, well-educated mothers were more likely to be high functioning, and minority children with less-educated mothers or intellectual disabilities were very unlikely to experience rapid gains. CONCLUSIONS: Children with autism have heterogeneous developmental pathways. One group of children evidenced remarkable developmental change over time. Understanding what drives these outcomes is thus critical.

Estimated Autism Risk and Older Reproductive Age

OBJECTIVES We sought to estimate the risk for autism associated with maternal and paternal age across successive birth cohorts. METHODS We linked birth records and autism diagnostic records from the California Department of Developmental Services for children born in California between 1992 and 2000 to calculate the risk associated with maternal and paternal age for each birth cohort as well as for the pooled data. RESULTS The categorical risks associated with maternal age over 40 years ranged from a high of 1.84 (95% confidence interval [CI] = 1.37, 2.47) to a low of 1.27 (95% CI = 0.95, 1.69). The risk associated with paternal age ranged from 1.29 (95% CI = 1.03, 1.6) to 1.71 (95% CI = 1.41, 2.08). CONCLUSIONS Pooling data across multiple birth cohorts inflates the risk associated with paternal age. Analyses that do not suffer from problems produced by pooling across birth cohorts demonstrated that advanced maternal age, rather than paternal age, may pose greater risk. Future research examining parental age as a risk factor must be careful to avoid the paradoxes that can arise from pooling data, particularly during periods of social demographic change.

Finding a Job in the Internet Age

Internet job searching offers an empirical setting in which to explore the trade-off between quality and quantity of information. As both firms and workers turn to the internet for unprecedented amounts of labor market information, it is unclear whether this makes the matching process more efficient. Using longitudinal data on two samples of unemployed job searchers in 1998 and 2000, I establish the rise of the internet as a job-search strategy and assess whether searching online increased the short-term probability of finding a job. Results suggest the internets contribution to an unemployed searchers information pool may afford a small advantage only to the extent that other job searchers are not using it, perhaps due to an inverse relationship between search and screening costs in a two-sided market.

Cohort effects explain the increase in autism diagnosis among children born from 1992 to 2003 in California

BACKGROUND The incidence and prevalence of autism have dramatically increased over the last 20 years. Decomposition of autism incidence rates into age, period and cohort effects disentangle underlying domains of causal factors linked to time trends. We estimate an age-period-cohort effect model for autism diagnostic incidence overall and by level of functioning. METHODS Data are drawn from sequential cohorts of all 6 501 262 individuals born in California from 1992 to 2003. Autism diagnoses from 1994 to 2005 were ascertained from the California Department of Development Services Client Development and Evaluation Report. RESULTS Compared with those born in 1992, each successively younger cohort has significantly higher odds of an autism diagnosis than the previous cohort, controlling for age and period effects. For example, individuals born in 2003 have 16.6 times the odds of an autism diagnosis compared with those born in 1992 [95% confidence interval (CI) 7.8-35.3]. The cohort effect observed in these data is stronger for high than for low-functioning children with an autism diagnosis. DISCUSSION Autism incidence in California exhibits a robust and linear positive cohort effect that is stronger among high-functioning children with an autism diagnosis. This finding indicates that the primary drivers of the increases in autism diagnoses must be factors that: (i) have increased linearly year-to-year; (ii) aggregate in birth cohorts; and (iii) are stronger among children with higher levels of functioning.

Association between assisted reproductive technology conception and autism in California, 1997-2007.

OBJECTIVES We assessed the association between assisted reproductive technology (ART) and diagnosed autistic disorder in a population-based sample of California births. METHODS We performed an observational cohort study using linked records from the California Birth Master Files for 1997 through 2007, the California Department of Developmental Services autism caseload for 1997 through 2011, and the Centers for Disease Control and Preventions National ART Surveillance System for live births in 1997 through 2007. Participants were all 5 926 251 live births, including 48 865 ART-originated infants and 32 922 cases of autism diagnosed by the Department of Developmental Services. We compared births originated using ART with births originated without ART for incidence of autism. RESULTS In the full population, the incidence of diagnosed autism was twice as high for ART as non-ART births. The association was diminished by excluding mothers unlikely to use ART; adjustment for demographic and adverse prenatal and perinatal outcomes reduced the association substantially, although statistical significance persisted for mothers aged 20 to 34 years. CONCLUSIONS The association between ART and autism is primarily explained by adverse prenatal and perinatal outcomes and multiple births.

Authors’ response to: Cohort effects explain the increase in autism diagnosis: an identifiability problem of the age-period-cohort model

doi: 10.1093/ije/dyu214 Advance Access Publication Date: 31 October 2014 Authors’ response to: Cohort effects explain the increase in autism diagnosis: an identifiability problem of the age-period-cohort model From Katherine M Keyes, Ezra Susser, Keely Cheslack-Postava, Christine Fountain, Kayuet Liu and Peter S Bearman* Department of Epidemiology, Columbia University, New York, New York State Psychiatric Institute and Paul F. Lazarsfeld Center for the Social Sciences, Columbia University, New York

KING ET AL. RESPOND

We appreciate interest in our article and are particularly grateful that Durkin et al. highlighted the importance of considering parameterization in research on parental age and autism. Making sense of parental age has always been complicated because homophily on age plays a significant role in partner selection. The decomposition presented in our article mitigates these statistical problems. As Durkin et al. noted, our decomposition utilizes a continuous parameterization of parental age. It also eliminates problems arising from multicollinearity and provides a means of assessing whether the effects of maternal and paternal age on autism risk are joint or independent. We hope that future work will pay greater attention to choice of parameterization, as parental age appears particularly sensitive to specification. The decomposition results prove more stable than the categorical results. Our analyses demonstrate that the instability of the categorical age results for autism could lead to erroneous conclusions in pooled data. For instance, in 1995 both the estimates from the maternal and paternal cohort analyses differed from the pooled estimate by more than 20%. In the pooled data there appears to be a critical crossover in the effect of maternal and paternal age in that year. In fact, the cohort data reveals a 44% difference in risk. Similarly, there is more than a 10% difference in risk between the pooled and cohort estimate for paternal age in 2000. Here, again, the risk associated with maternal age exceeds that of paternal age in the cohort data. The opposite appears to be the case in the analysis of the pooled data. What should one conclude from this? First, different analyses conducted at different points in time and with different analysis strategies can lead to different conclusions about risk factors. Second, analyses that do not suffer from the statistical fallacies produced by pooling categorical data demonstrate that maternal age, rather than paternal age, may pose greater risk. Are these differences meaningful? Given that individuals may make life choices on the basis of these reports, our sense is that they are. Durkin et al. are absolutely right about the need to be sensitive to model specification. We agree completely. We also think it critical to be attentive to temporality. Although this is true for all research, it appears to be particularly true for autism, because the size and the composition of the population with autism has changed over time.1