Vincent Yau

Prenatal and neonatal peripheral blood mercury levels and autism spectrum disorders.

BACKGROUND Prenatal and early-life exposures to mercury have been hypothesized to be associated with increased risk of autism spectrum disorders (ASDs). OBJECTIVES This study investigated the association between ASDs and levels of total mercury measured in maternal serum from mid-pregnancy and infant blood shortly after birth. METHODS The study sample was drawn from the Early Markers for Autism (EMA) Study. Three groups of children who were born in Orange County, CA in 2000-2001 were identified: children with ASD (n=84), children with intellectual disability or developmental delay (DD) (n=49), and general population controls (GP) (n=159). Maternal serum specimens and newborn bloodspots were retrieved from the California Department of Public Health prenatal and newborn screening specimen archives. Blood mercury levels were measured in maternal serum samples using mass spectrometer and in infant bloodspots with a 213 nm laser. RESULTS Maternal serum and infant blood mercury levels were significantly correlated among all study groups (all correlations >0.38, p<0.01). Adjusted logistic regression models showed no significant associations between ASD and log transformed mercury levels in maternal serum samples (ASD vs. GP: OR [95% CI]=0.96 [0.49-1.90]; ASD vs. DD: OR [95% CI]=2.56 [0.89-7.39]). Results for mercury levels in newborn blood samples were similar (ASD vs. GP: OR [95% CI]=1.18 [0.71-1.95]; ASD vs. DD: OR [95% CI]=1.96 [0.75-5.14]). CONCLUSIONS Results indicate that levels of total mercury in serum collected from mothers during mid-pregnancy and from newborn bloodspots were not significantly associated with risk of ASD, though additional studies with greater sample size and covariate measurement are needed.

Health Services Utilization Among Children With and Without Autism Spectrum Disorders

Using data from multiple health systems (2009–2010) and the largest sample to date, this study compares health services use among youth with and without an autism spectrum disorder (ASD)—including preventive services not previously studied. To examine these differences, we estimated logistic and count data models, controlling for demographic characteristics, comorbid physical health, and mental health conditions. Results indicated that youth with an ASD had greater health care use in many categories, but were less likely to receive important preventive services including flu shots and other vaccinations. An improved understanding of the overall patterns of health care use among this population could enable health systems to facilitate the receipt of appropriate and effective health care.

Psychotropic Medication Use among Insured Children with Autism Spectrum Disorder

This study examined psychotropic medication use among 7901 children aged 1–17 with autism spectrum disorder (ASD) in five health systems, comparing to matched cohorts with no ASD. Nearly half (48.5 %) of children with ASD received psychotropics in the year observed; the most common classes were stimulants, alpha-agonists, or atomoxetine (30.2 %), antipsychotics (20.5 %), and antidepressants (17.8 %). Psychotropic treatment was far more prevalent among children with ASD, as compared to children with no ASD (7.7 % overall), even within strata defined by the presence or absence of other psychiatric diagnoses. The widespread use of psychotropics we observed, particularly given weak evidence supporting the effectiveness of these medications for most children with ASD, highlights challenges in ASD treatment and the need for greater investment in its evaluation.

Medical Conditions in the First Years of Life Associated with Future Diagnosis of ASD in Children

This study examines medical conditions diagnosed prior to the diagnosis of autism spectrum disorder (ASD). Using a matched case control design with 3911 ASD cases and 38,609 controls, we found that 38 out of 79 medical conditions were associated with increased ASD risk. Developmental delay, mental health, and neurology conditions had the strongest associations (ORs 2.0–23.3). Moderately strong associations were observed for nutrition, genetic, ear nose and throat, and sleep conditions (ORs 2.1–3.2). Using machine learning methods, we clustered children based on their medical conditions prior to ASD diagnosis and demonstrated ASD risk stratification. Our findings provide new evidence indicating that children with ASD have a disproportionate burden of certain medical conditions preceding ASD diagnosis.

PS1-13: Variation in the Incidence and Prevalence of Autism from Multiple Health Systems: Findings from the Mental Health Research Network Autism Registry Study

Background/Aims Autism spectrum disorders (ASD) are characterized by impairments in social interaction and communication, as well as restricted, stereotyped interests and behaviors. A recent study found that approximately 1 in 88 children in the U.S. were diagnosed with an ASD and that prevalence varied widely among different demographic groups. The goals of this study were to obtain accurate prevalence and incidence statistics for ASD across several large, diverse health systems and to describe the variation of these statistics across demographic factors. Methods All members within the five participating health systems born between January 1, 1993 and December 31, 2008 with electronic claims, enrollment, or medical record information were included in the study. Information on member demographics and ASD subtypes were collected from earliest available records at each site through the end of December 31, 2010. Individuals with an ASD diagnosis from an ASD specialist or two or more ASD diagnoses from non-specialists were defined as valid cases. Results A preliminary examination of data from one site (N = 1,271,823) found 10,114 individuals <18 years ever diagnosed with an ASD. Of those 10,114 ASD cases, 8,085 met the validation criteria and were included in final analyses. Prevalence of all ASDs in children ≤8 years old was 1.1/1000 in 2001 (1 in 909 children) and increased steadily to 7.1/1000 in 2010 (1 in 141 children). Prevalence specifically for autistic disorder (AD), a more severe subtype, in children ≤8 years old was 0.3/1000 in 2001 and increased to 1.9/1000 in 2010. Similar secular increases were noted for incidence. Prevalence and incidence varied greatly among demographic groups. Prevalence of all ASDs in 2010 was 8.4/1000 among Whites, 7.1/1000 among Blacks, and 10.6/1000 among Asians. Prevalence of ASDs among females was lower than among males in all years (2010 males: 11.2/1000, 2010 females: 2.8/1000). Conclusions This study provides up-to-date prevalence and incidence information from a group of large, diverse, community-based settings. Incidence and prevalence differed across racial groups and sex status. Strong increasing trends in the diagnosis of ASDs in general, as well as the AD subtype, were observed.

Prenatal maternal serum concentrations of per- and polyfluoroalkyl substances in association with autism spectrum disorder and intellectual disability

Background: Emerging work has examined neurodevelopmental outcomes following prenatal exposure to per- and polyfluoroalkyl substances (PFAS), but few studies have assessed associations with autism spectrum disorder (ASD). Objectives: Our objective was to estimate associations of maternal prenatal PFAS concentrations with ASD and intellectual disability (ID) in children. Methods: Participants were from a population-based nested case–control study of children born from 2000 to 2003 in southern California, including children diagnosed with ASD (n=553), ID without autism (n=189), and general population (GP) controls (n=433). Concentrations of eight PFAS from stored maternal sera collected at 15–19 wk gestational age were quantified and compared among study groups. We used logistic regression to obtain adjusted odds ratios for the association between prenatal PFAS concentrations (parameterized continuously and as quartiles) and ASD versus GP controls, and separately for ID versus GP controls. Results: Geometric mean concentrations of most PFAS were lower in ASD and ID groups relative to GP controls. ASD was not significantly associated with prenatal concentrations of most PFAS, though significant inverse associations were found for perfluorooctanoate (PFOA) and perfluorooctane sulfonate (PFOS) [adjusted ORs for the highest vs. lowest quartiles 0.62 (95% CI: 0.41, 0.93) and 0.64 (95% CI: 0.43, 0.97), respectively]. Results for ID were similar. Conclusions: Results from this large case–control study with prospectively collected prenatal measurements do not support the hypothesis that prenatal exposure to PFAS is positively associated with ASD or ID. https://doi.org/10.1289/EHP1830

A4-1: Validating Electronic Health Record Demographic Data Using Self-reported Data from the Autism Registry Survey

Background/Aims The use of administrative patient data via the electronic health record (EHR) is very important in research. It’s critical we have a sense of the validity and relative accuracy of key data in this widely available data source. The HMORN Virtual Data Warehouse (VDW) is an example of a large repository of administrative data used in numerous studies. The recent Mental Health Research Network (MHRN) Autism Spectrum Disorder (ASD) Registry Survey was hosted by four HMORN sites inviting Kaiser Permanente members to complete a Web-based questionnaire on behalf of their child identified as having an ASD diagnosis in the EHR. Methods In addition to an extensive battery of questions regarding ASD, the survey collected data on a number of demographic data elements also available in the VDW. These are: age, gender, race/ethnicity (child), income (household) and education (household adult). A total of 1155 adults responded to the ASD Registry Survey. These records were matched with demographic data from the VDW for the same child. Results Preliminary examination of race-ethnicity and gender data shows that there‘s a good to excellent level of agreement between the two sources when data are non-missing in both data sources. A total of 992 records had non-missing race/ethnicity data from both data sources. In 81.1% (805/992) of the cases, both data sources agreed (kappa = 0.68, CI = 0.64–0.72). The categories that had the highest level of agreement are White, Black, and Asian, while the Hispanic and multi-racial groupings had a comparatively much lower level of agreement (46.9%). For gender, level of agreement was very high (99.0%, 1118/1129, kappa = 0.97, CI = 0.95–0.99). Conclusions In this study, race in the electronic health record was a very accurate measure for major race categories but was far less accurate when reporting the emergent and important multi-racial category and Hispanic ethnicity. Gender had an excellent level of agreement between the two sources. Age, gender, and race-ethnicity are key covariates for many studies analyzing EHR data. Income and education can serve to illuminate socioeconomic factors very relevant to health care research. Having a sense of the validity and accuracy of these data is crucial to the research process.

PS1-14: Health-Related Quality of Life in Children with Autism Spectrum Disorders: Findings from the Mental Health Research Network Autism Registry Web Survey

Background/Aims Approximately 1 in 88 children in the U.S. is diagnosed with Autism Spectrum Disorder (ASD). ASD is a complex disorder characterized by impairment in social skills, communication, and cognitive and behavioral functioning. In order for policy makers and clinical managers to evaluate new approaches to treating and managing ASD, they need brief comprehensive outcome measures. One approach that could be useful in this context is measurement of health-related quality of life (HR-QOL), which provides a comprehensive picture of health status including an individual’s psychosocial, emotional, and physical wellbeing. This comprehensive approach is particularly important in conditions such as ASD that have multiple impacts on a person’s health. Few previous studies have examined HR-QOL in persons with ASD, and most of these studies have used small samples. The purpose of this analysis is to examine HR-QOL in a group of geographically- and racially/ethnically-diverse children with ASD who are enrolled in the Mental Health Research Network (MHRN) Autism Registry. Methods A Web-based survey of parents of children with ASD was implemented at four MHRN Autism Registry sites, including children’s HR-QOL, measured by the Pediatric Quality of Life Inventory (PedsQLTM). The PedsQLTM provides an overall score, as well as subscales for important domains including physical health, psychosocial health, emotional functioning, social functioning, and school functioning. Results To date, recruitment letters have been mailed to approximately 8800 parents and 800 surveys have been completed. Preliminary analyses of respondents indicate that HR-QOL is lower in children with ASD compared to national norms. We will present the final results from the survey, which will conclude in November 2012. The presentation will examine the overall scores, scores on subscales, and scores by subgroup (e.g., age, gender, race) and will compare these scores to national norms. Conclusions We successfully implemented a Web-based survey of parents of children with ASD across four MHRN sites. With 800 completed surveys (recruitment will continue through November 2012), this is the largest known population-based survey on children with ASD to date. The current study will help to confirm results from smaller samples and will allow for more refined analyses of subgroups.