Estimating the Prevalence of Autism Spectrum Disorder in New South Wales, Australia: A Data Linkage Study of Three Routinely Collected Datasets

Routinely collected data help estimate the prevalence of autism spectrum disorder (ASD) in jurisdictions without active autism surveillance. We created a population-based cohort of 1,211,834 children born in 2002-2015 in New South Wales, Australia using data linkage. Children with ASD were identified in three datasets - disability services, hospital admissions, and ambulatory mental health data. The prevalence of ASD in the cohort was 1.3% by age 12 and prevalence at age 6 increased an average of 4.1% per year (95% Confidence Interval, 3.3%, 4.8%). Most children with ASD were identified in disability services data (87%), although data linkage identified 1,711 additional cases that were more likely female, older at first contact, and living in major cities and less disadvantaged areas.

Comparing Gastrointestinal Endoscopy Findings in Children with Autism, Developmental Delay, or Typical Development

OBJECTIVE

To compare endoscopic and histologic upper endoscopy (esophagogastroduodenoscopy [EGD]) findings in children with autism spectrum disorders (ASD) to age- and gender-matched controls with developmental delay (DD) or with typical development (TD).

METHODS

Retrospective, cross-sectional study of children undergoing EGD, identifying those diagnosed with ASD, and matching on age and gender to children with DD or TD in ratio of 1:1:2. Rates of EGD findings were compared between the 3 groups using χ² or Fisher exact test. Multivariable linear regression was performed to identify predictors of abnormal histology.

RESULTS

A total of 2104 patients were included (526 ASD; 526 DD; 1052 TD). Children with ASD had higher rates of abnormal esophageal histology (ASD 38.4%; DD 33.4%; TD 30.4%, P = .008), particularly esophagitis. In multivariable modeling, ASD diagnosis was an independent predictor of abnormal esophageal histology (OR [95% CI] 1.38 [1.09, 1.76]) compared with TD. Stomach findings did not differ among the groups. In the duodenum, histologic abnormalities were observed with lower frequency in ASD (ASD 17.0%; DD 20.1%; TD 24.2%, P = .005). In multivariable analysis, ASD diagnosis was not a significant predictor (OR 0.78 [0.56, 1.09]) of abnormal duodenal histology.

CONCLUSIONS

Children with ASD have higher rates of histologic esophagitis compared with age- and gender-matched DD and TD controls. ASD was a significant independent predictor of abnormal esophageal, but not, duodenal, histology. These results underscore the importance of EGD in children with ASD.

Psychotropic Medication Use in Children and Youth with Autism Enrolled in Medicaid

Children with autism frequently present with complex mental health diagnoses and psychotropic medications are often a component of comprehensive biopsychosocial treatment plans for these conditions. The purpose of this study is to provide rates and patterns of psychotropic medication use, and predictors thereof, in children and youth with autism enrolled in Medicaid across the US. This study examined national Medicaid claims from 2008 to 2016 of all children and youth with autism ages 0-21 years enrolled in Medicaid. Psychotropic medication use was examined across several child and youth characteristics, including age, co-occurring mental health conditions, sex, and race and ethnicity. About half of children and youth with autism enrolled in Medicaid had at least one psychotropic prescription in a year, a number that decreased slightly across the study period due to decreases in the prescription of antipsychotics. As new medications for autism or co-occurring conditions are developed and deployed, and as the understanding of the characteristics of the population of children with autism evolves, studying rates of medication usage helps to understand utilization patterns and differences in access to quality care.

Health conditions and service use of autistic women and men: A retrospective population-based case-control study

LAY ABSTRACT

This study used administrative data from Ontario, Canada to compare the health conditions and service use of autistic women and men with adults with other developmental disabilities and with adults without developmental disabilities. Autistic women and men were more likely to have physical and mental health conditions compared to adults without developmental disabilities. Rates of health conditions were similar or lower among autistic adults compared to adults with other developmental disabilities, except more autistic adults had psychiatric conditions. Autistic women and men used higher rates of psychiatric services compared to all other groups. When comparing autistic women with same aged autistic men, sex differences were found for specific physical (Crohn's disease/colitis, rheumatoid arthritis) and psychiatric conditions (psychotic disorders, non-psychotic disorders), as well differences in service use (emergency department visits, hospitalizations, family doctor and neurologist visits). These results further highlight the high health needs and service use of autistic women and men, as well as adults with other developmental disabilities. It is critical for future research to focus on mental health support for autistic adults and to better understand how to tailor supports to best serve autistic women.

Hospitalizations Among Children and Youth With Autism in the United States: Frequency, Characteristics, and Costs

National estimates of hospitalization diagnoses and costs were determined using the 2016 HCUP Kids' Inpatient Database. Children and youth with autism were hospitalized over 45,000 times at over $560 million in costs and 260,000 inpatient days. The most frequent principal diagnoses for hospitalizations of children and youth with autism were epilepsy, mental health conditions, pneumonia, asthma, and gastrointestinal disorders, which resulted in almost $200 million in costs and 150,000 inpatient days. Mental health diagnoses accounted for 24.8% of hospitalizations, an estimated $82 million in costs, and approximately 94,000 inpatient days. Children and youth with autism were more likely hospitalized for epilepsy, mental health diagnoses, and gastrointestinal disorders, and less likely for pneumonia and asthma compared to other children and youth.

Heterogeneity in Autism Spectrum Disorder Case-Finding Algorithms in United States Health Administrative Database Analyses

Strengthening systems of care to meet the needs of individuals with autism spectrum disorder (ASD) is of growing importance. Administrative data provide advantages for research and planning purposes, including large sample sizes and the ability to identify enrollment in insurance coverage and service utilization of individuals with ASD. Researchers have employed varying strategies to identify individuals with ASD in administrative data. Differences in these strategies can limit the comparability of results across studies. This review describes implications of the varying strategies that have been employed to identify individuals with ASD in US claims databases, with consideration of the strengths and limitations of each approach.

Medicaid Disruption Among Transition-Age Youth on the Autism Spectrum

Enrollment in Medicaid facilitates access to needed services among transition-age youth on the autism spectrum and youth with intellectual disability (ID). There are long-standing programs to ensure that individuals with ID remain enrolled as they age; similar programs for autistic youth are newer, not as widespread, and may not be as effective. We compared Medicaid disenrollment and re-enrollment between transition-age youth on the autism spectrum, youth with ID, and youth with both diagnoses using a national claims-based prospective cohort study from 2008 through 2012. Autistic youth were most likely to disenroll and least likely to re-enroll. Disenrollment peaked for all three groups at ages 19 and 21. Transition-age youth on the autism spectrum experience more disruptions in access to Medicaid-reimbursed services than youth with ID. More equitable Medicaid enrollment options for autistic individuals are needed to ensure their access to critical health care as they age.

Global prevalence of autism: A systematic review update

Prevalence estimates of autism are essential for informing public policy, raising awareness, and developing research priorities. Using a systematic review, we synthesized estimates of the prevalence of autism worldwide. We examined factors accounting for variability in estimates and critically reviewed evidence relevant for hypotheses about biological or social determinants (viz., biological sex, sociodemographic status, ethnicity/race, and nativity) potentially modifying prevalence estimates of autism. We performed the search in November 2021 within Medline for studies estimating autism prevalence, published since our last systematic review in 2012. Data were extracted by two independent researchers. Since 2012, 99 estimates from 71 studies were published indicating a global autism prevalence that ranges within and across regions, with a median prevalence of 100/10,000 (range: 1.09/10,000 to 436.0/10,000). The median male‐to‐female ratio was 4.2. The median percentage of autism cases with co‐occurring intellectual disability was 33.0%. Estimates varied, likely reflecting complex and dynamic interactions between patterns of community awareness, service capacity, help seeking, and sociodemographic factors. A limitation of this review is that synthesizing methodological features precludes a quality appraisal of studies. Our findings reveal an increase in measured autism prevalence globally, reflecting the combined effects of multiple factors including the increase in community awareness and public health response globally, progress in case identification and definition, and an increase in community capacity. Hypotheses linking factors that increase the likelihood of developing autism with variations in prevalence will require research with large, representative samples and comparable autism diagnostic criteria and case‐finding methods in diverse world regions over time.

Health characteristics of reproductive-aged autistic women in Ontario: A population-based, cross-sectional study

LAY ABSTRACT

While an increasing number of girls and women are being identified with autism, we know little about reproductive-aged autistic women's health. This study used administrative data from Ontario, Canada, to compare the health of reproductive-aged autistic women with non-autistic women. Overall, reproductive-aged autistic women had poorer health compared with non-autistic women, including increased rates of material deprivation, chronic medical conditions, psychiatric conditions, history of assault, and use of potentially teratogenic medications (i.e. drugs that can be harmful to the development of an embryo or fetus). These findings suggest that there is a need for health interventions tailored to the needs of reproductive-aged autistic women.

Epilepsy in adulthood: Prevalence, incidence, and associated antiepileptic drug use in autistic adults in a state Medicaid system

LAY ABSTRACT

Epilepsy is more common in autistic children compared to children without autism, but we do not have good estimates of how many autistic adults have epilepsy. We used data from a full population of 7513 autistic adults who received Medicaid in Wisconsin to figure out the proportion of autistic adults who have epilepsy, as compared to 18,429 adults with intellectual disability. We also wanted to assess how often epilepsy is first diagnosed in adulthood. Finally, we wanted to see whether antiepileptic drugs are being used to treat epilepsy in autistic adults. We found that 34.6% of autistic adults with intellectual disability and 11.1% of autistic adults without intellectual disability had epilepsy, compared to 27.0% of adults with intellectual disability alone. Autistic women and autistic adults with intellectual disability were more likely than autistic men and autistic adults without intellectual disability to have both previous and new diagnoses of epilepsy. Finally, we found that antiepileptic medications are commonly prescribed to autistic people who do not have epilepsy potentially to treat mental health conditions or behavior problems, and that antiepileptic medications are not always prescribed to autistic people with epilepsy even though they are indicated as a first-line epilepsy treatment. The findings of this study highlight the need to effectively treat and prevent epilepsy in autistic adults.

Assessing the validity of administrative health data for the identification of children and youth with autism spectrum disorder in Ontario

Population‐level identification of children and youth with ASD is essential for surveillance and planning for required services. The objective of this study was to develop and validate an algorithm for the identification of children and youth with ASD using administrative health data. In this retrospective validation study, we linked an electronic medical record (EMR)‐based reference standard, consisting 10,000 individuals aged 1–24 years, including 112 confirmed ASD cases to Ontario administrative health data, for the testing of multiple case‐finding algorithms. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and corresponding 95% confidence intervals (CI) were calculated for each algorithm. The optimal algorithm was validated in three external cohorts representing family practice, education, and specialized clinical settings. The optimal algorithm included an ASD diagnostic code for a single hospital discharge or emergency department visit or outpatient surgery, or three ASD physician billing codes in 3 years. This algorithm's sensitivity was 50.0% (95%CI 40.7–88.7%), specificity 99.6% (99.4–99.7), PPV 56.6% (46.8–66.3), and NPV 99.4% (99.3–99.6). The results of this study illustrate limitations and need for cautious interpretation when using administrative health data alone for the identification of children and youth with ASD.

Lay Summary

We tested algorithms (set of rules) to identify young people with ASD using routinely collected administrative health data. Even the best algorithm misses more than half of those in Ontario with ASD. To understand this better, we tested how well the algorithm worked in different settings (family practice, education, and specialized clinics). The identification of individuals with ASD at a population level is essential for planning for support services and the allocation of resources. Autism Res 2021, 14: 1037–1045. © 2021 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals LLC.

Identifying Children and Youth With Autism Spectrum Disorder in Electronic Medical Records: Examining Health System Utilization and Comorbidities

Autism spectrum disorder (ASD) is a neurodevelopmental disorder requiring significant health and educational resources for affected individuals. A reference standard for ASD was generated from an existing population‐based cohort of 10,000 children and youth aged 1–24 years who were randomly selected for chart abstraction from 29,256 patients from 119 family physicians. We developed and validated an algorithm to identify children and youth with ASD within an electronic medical record system (N = 80,237, aged 1–24 years) in order to examine the prevalence of comorbidities and quantify health system utilization within the cohort. We identified 1,062 children and youth with ASD representing a prevalence of 1.32%. Compared to individuals without ASD, those with ASD had a higher prevalence of asthma, were more likely to visit a specialist, undergo surgery, and be hospitalized for psychiatric reasons. Children and youth with ASD in Ontario have complex health system needs, illustrated through a significant burden of comorbidities and increased health system utilization.

Lay Summary

Our paper generates population‐based estimates of health system use by children and youth with ASD, who have a higher burden of comorbidities than the general population. We developed a case‐finding algorithm and applied it in electronic medical records to create a cohort of children and youth with ASD, thereby generating an important resource to further study the health care needs of individuals with ASD.

Impact of Psychoactive Drug Use on Developing Obesity among Children and Adolescents with Autism Spectrum Diagnosis: A Nested Case-Control Study

BACKGROUND

Obesity in children on the autism spectrum (AS) is becoming a significant health concern. The purpose of this study was to identify the predictors of obesity in a cohort of AS youth and to assess the impact of psychoactive medication use while exploring the second-generation antipsychotics (SGAs) dose-response curve.

STUDY DESIGN

A nested case-control study was conducted using Quebec public administrative databases. Subjects with AS <18 years [≥2 diagnoses International Classification of Diseases: 9th revision (ICD-9): 299.X] were identified (January 1993 to May 2011). Cases were defined as subjects with an obesity diagnosis (ICD-9: 278.X) during the coverage period and matched to 10 controls for age, gender, and follow-up duration. Potential risk factors for obesity (sociodemographic characteristics, other neuropsychiatric conditions, and psychoactive drug use) were evaluated and analyzed using conditional logistic regression.

RESULTS

From a cohort of 5369 AS subjects, we identified 135 obesity cases. Among the different risk factors, only SGAs [rate ratio (RR): 1.04, 95% confidence interval (CI): 1.01-1.07] increased the probability of obesity in multivariate analysis. Exposure for ≥12 months increased significantly the likelihood of obesity (RR: 2.01, 95% CI: 1.18-3.42). Higher risk was observed with chlorpromazine-equivalent daily doses ≥100 mg (RR: 2.20, 95% CI: 1.00-4.84). Among SGA users, concomitant antidepressants (per 30-day exposure) slightly increased the probability (RR: 1.08, 95% CI: 1.01-1.15).

CONCLUSIONS

Longer and higher SGA exposure increased the risk of obesity, which has to be considered in relation to the paucity of evidence supporting long-term psychoactive medication use in AS children. Results highlight the need to promote optimal use and interventions to mitigate metabolic side effects of SGAs in this population.

Autism spectrum disorder/Takiwātanga: An Integrated Data Infrastructure-based approach to autism spectrum disorder research in New Zealand

New Zealand has few estimates of the prevalence of autism spectrum disorder and no national registry. The use of administrative data sources is expanding and could be useful in autism spectrum disorder research. However, the extent to which autism spectrum disorder can be captured in these data sources is unknown. In this study, we utilised three linked administrative health data sources from the Integrated Data Infrastructure to identify cases of autism spectrum disorder among New Zealand children and young people. We then investigated the extent to which a range of mental health, neurodevelopmental and related problems co-occur with autism spectrum disorder. In total, 9555 unique individuals aged 0–24 with autism spectrum disorder were identified. The identification rate for 8-year-olds was 1 in 102. Co-occurring mental health or related problems were noted in 68% of the autism spectrum disorder group. The most common co-occurring conditions were intellectual disability, disruptive behaviours and emotional problems. Although data from the Integrated Data Infrastructure may currently undercount cases of autism spectrum disorder, they could be useful for monitoring service and treatment-related trends, types of co-occurring conditions and for examining social outcomes. With further refinement, the Integrated Data Infrastructure could prove valuable for informing the national incidence and prevalence of autism spectrum disorder and the long-term effectiveness of clinical guidelines and interventions for this group.

Objective Estimates of Direct-Medical Costs Among Persons Aged 3 to 38 Years With and Without Research-Defined Autism Spectrum Disorder Ascertained During Childhood: A Population-Based Birth-Cohort Study

OBJECTIVES

Accurate estimates of autism spectrum disorder (ASD)-associated medical costs are essential for predicting future care needs, allocating resources, identifying best practices, and modeling cost-effectiveness. Most existing studies have either employed subjective cost data or ascertained ASD using self-reported or International Classification of Diseases-coded diagnoses. Such ascertainment is especially problematic for identifying milder ASD among older individuals never diagnosed with ASD.

METHODS

This 1976 through 2000 population-based birth-cohort study was set in Olmsted County, Minnesota. ASD cases and age- and sex-matched unaffected controls were identified by applying uniform operational research criteria for ASD (using the guidelines of the Diagnostic and Statistical Manual of Mental Disorders, fourth edition, text revision) after rigorous review of provider-linked medical and public, private, or home school records available for all members from birth to a maximum age of 21 years. Medical cost estimates for the 901 case-control pairs used line-item provider-linked billing data (including all payers) from 2003 through 2014 (ages 3-38 years). Outpatient pharmaceutical costs were unavailable. Temporal changes in diagnostic criteria, clinical practice, public awareness, and access were addressed by separating analyses into 5-year age group and 4-year calendar period cells. Unadjusted and adjusted (age and age plus co-occurring conditions) cost estimates were provided for cases, controls, and case-control differences. Additional factors (co-occurring conditions, percentage hospitalized, intellectual disability) were investigated using unadjusted descriptive analyses.

RESULTS

Cell sample sizes ranged from 93 to 402 for age groups 3 through 19 years and from 45 to 395 for age groups 20 through 38 years. Unadjusted, age-adjusted, and fully adjusted medical costs were significantly higher for cases versus controls in 100% of cells for age groups 3 through 19 years and in 50% (unadjusted), 38% (age adjusted), and 12% (fully adjusted) of cells for age groups 20 through 38 years.

CONCLUSIONS

These unique estimates can help inform the construction of cost-effectiveness models; decisions by payers, providers, and policy makers; and predictions of lifetime costs.

Identification of Pediatric Autism Spectrum Disorder Cases Using Health Administrative Data

Administrative data are frequently used to identify Autism Spectrum Disorder (ASD) cases in epidemiological studies. However, validation studies on this mode of case ascertainment have lacked access to high-quality clinical diagnostic data and have not followed published reporting guidelines. We report on the diagnostic accuracy of using readily available health administrative data for pediatric ASD case ascertainment. The validation cohort included almost all the ASD-positive children born in British Columbia, Canada from April 1, 2000 to December 31, 2009 and consisted of 8,670 children in total. 4,079 ASD-positive and 2,787 ASD-negative children were identified using Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview-Revised (ADI-R) assessments done through the British Columbia Autism Assessment Network (BCAAN). An additional 1,804 ADOS/ADI-R assessed ASD-positive children were identified using Ministry of Education records. This prospectively collected clinical data (the diagnostic gold standard) was then linked to each child's physician billing and hospital discharge data. The diagnostic accuracy of 11 algorithms that used the administrative data to assign ASD case status was assessed. For all algorithms, high positive predictive values (PPVs) were observed alongside low values for other measures of diagnostic accuracy illustrating that PPVs alone are not an adequate measure of diagnostic accuracy. We show that British Columbia's health administrative data cannot reliably be used to discriminate between children with ASD and children with other developmental disorders. Utilizing these data may result in misclassification bias. Methodologically sound, region-specific validation studies are needed to support the use of administrative data for ASD case ascertainment. Autism Res 2020, 13: 456-463. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Health administrative data are frequently used to identify Autism Spectrum Disorder (ASD) cases for research purposes. However, previous validation studies on this sort of case identification have lacked access to high-quality clinical diagnostic data and have not followed published reporting guidelines. We show that British Columbia's health administrative data cannot reliably be used to discriminate between children with ASD and children with other developmental disorders.

Estimating heritability and genetic correlations from large health datasets in the absence of genetic data

Typically, estimating genetic parameters, such as disease heritability and between-disease genetic correlations, demands large datasets containing all relevant phenotypic measures and detailed knowledge of family relationships or, alternatively, genotypic and phenotypic data for numerous unrelated individuals. Here, we suggest an alternative, efficient estimation approach through the construction of two disease metrics from large health datasets: temporal disease prevalence curves and low-dimensional disease embeddings. We present eleven thousand heritability estimates corresponding to five study types: twins, traditional family studies, health records-based family studies, single nucleotide polymorphisms, and polygenic risk scores. We also compute over six hundred thousand estimates of genetic, environmental and phenotypic correlations. Furthermore, we find that: (1) disease curve shapes cluster into five general patterns; (2) early-onset diseases tend to have lower prevalence than late-onset diseases (Spearman's ρ = 0.32, p < 10-16); and (3) the disease onset age and heritability are negatively correlated (ρ = -0.46, p < 10-16).

Is the Autism Boom Headed for Medicaid? Patterns in the Enrollment of Autistic Adults in Wisconsin Medicaid, 2008-2018

Our primary objective was to describe demographic characteristics and enrollment patterns in a unique 11-year full sample of adult Wisconsin Medicaid beneficiaries with identified autism spectrum disorder (ASD) or intellectual disability (ID). We obtained de-identified Medicaid claims data for adults with a recorded ASD or ID diagnosis aged 21 and older with any Medicaid fee-for-service claims between January 1, 2008 and December 31, 2018. We assessed enrollment, age, number of visits, and paid amount per year using generalized linear models with a random intercept for each beneficiary. We identified claims for 4,775 autistic adults without ID, 2,738 autistic adults with ID, 14,945 adults with ID, and 3,484 adults with Down syndrome. The age distribution of the diagnostic group with ASD diagnoses was right skewed with a majority of beneficiaries less than age 30. The ASD without ID diagnostic group had the least visits and paid amount per person per year compared to other groups. In each age category, the ASD with ID diagnostic group had the most paid amount per person per year compared to other groups. It is urgent that we identify the health and health service needs of autistic adults from young adulthood through old age. Our findings have implications for ensuring adequate health coverage across the lifespan and highlight the importance of a strong and accessible health care system for autistic people. Autism Res 2019, 12: 1541-1550. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Medicaid provides health insurance to disabled people who meet income requirements. We assessed patterns of enrollment and service use among autistic adults and adults with developmental disabilities in Wisconsin Medicaid. We found a consistent influx of new young autistic adults without intellectual disability into the Medicaid system, with fewer visits and lower paid amounts compared to other developmental disability groups. The changing population of autistic people using Medicaid has implications for providing health care to autistic adults in the future.

Prenatal antibiotics exposure and the risk of autism spectrum disorders: A population-based cohort study

Background

Prenatal antibiotic exposure induces changes in infants’ gut microbiota composition and is suggested as a possible contributor in the development of autism spectrum disorders (ASD). In this study, we examined the association between prenatal antibiotic exposure and the risk of ASD.

Methods

This was a population-based cohort study utilizing the Manitoba Population Research Data Repository. The cohort included 214 834 children born in Manitoba, Canada between April 1, 1998 and March 31, 2016. Exposure was defined as having filled one or more antibiotic prescription during pregnancy. The outcome was autism spectrum disorder diagnosis. Multivariable Cox proportional hazards regression was used to estimate the risk of developing ASD in the overall cohort and in a sibling cohort.

Results

Of all subjects, 80 750 (37.6%) were exposed to antibiotics prenatally. During follow-up, 2965 children received an ASD diagnosis. Compared to children who were not exposed to antibiotics prenatally, those who were exposed had a higher risk of ASD: (adjusted HR 1.10 [95% CI 1.01, 1.19]). The association was observed in those exposed to antibiotics in the second or third trimester (HR 1.11 [95% CI 1.01, 1.23] and 1.17 [95% CI 1.06, 1.30], respectively). In the siblings’ cohort, ASD risk estimate remained unchanged (adjusted HR 1.08 [95% CI 0.90, 1.30], although it was not statistically significant.

Conclusions

Prenatal antibiotic exposure is associated with a small increase in the risk of ASD. Given the potential of residual confounding beyond what it was controlled through our study design and because of possible confounding by indication, such a small risk increase in the population is not expected to be clinically significant.

Brief Report: Service Use and Associated Expenditures Among Adolescents with Autism Spectrum Disorder Transitioning to Adulthood

This study compared Medicaid service utilization and expenditures among adolescents with autism spectrum disorder (ASD) to adolescents with intellectual disability (ID) as they aged into adulthood. Medicaid Analytic eXtract (MAX) data was used to identify a national cohort. Winsorization was utilized to control for expenditure outliers. A greater proportion of adolescents with ASD utilized most services. Decreases in the use of key services, including psychiatric outpatient services, were observed for both groups. Changes in medical services, such as increases in inpatient and long term care services, among the ASD cohort suggest medical needs of adolescents with ASD change as they age. Information remains lacking on changing ASD symptom presentation during the transition to adolescence.

Early childhood antibiotics use and autism spectrum disorders: a population-based cohort study

Background

Changes in microbiota composition as a result of antibiotics use in early life has been proposed as a possible contributor in the aetiology of autism spectrum disorders (ASD). We aimed to examine the association between early life antibiotic exposure and risk of ASD.

Methods

This was a population-based cohort study which included all live births in Manitoba, Canada, between 1 April 1998 and 31 March 2016. We used administrative health data from the Manitoba Population Research Data Repository. Exposure was defined as having filled one or more antibiotic prescription during the first year of life. The main outcome was ASD diagnosis. Cox proportional hazards regression models were used to estimate the risk of developing ASD in the overall population and in a sibling cohort.

Results

Of all subjects in the cohort (n = 214 834), 94 024 (43.8%) filled an antibiotic prescription during the first year of life. During follow-up, 2965 children received an ASD diagnosis. Compared with children who did not use antibiotics during the first year of life, those who received antibiotics had a reduced risk of ASD [adjusted hazardz ratio (HR) 0.91, 95% confidence interval (CI) 0.84-0.99). Number of treatment courses and cumulative duration of antibiotic exposure were not associated with ASD. In the sibling-controlled analysis, early life antibiotic exposure was not associated with ASD (adjusted HR 1.03, 95% CI 0.86-1.23).

Conclusions

Our findings suggested no clinically significant association between early life antibiotics exposure and risk of autism spectrum disorders, and should provide reassurance to concerned prescribers and parents.

Health Concerns and Health Service Utilization in a Population Cohort of Young Adults with Autism Spectrum Disorder

Individuals with autism spectrum disorder (ASD) have many health needs that place demands on the health service sector. This study used administrative data to compare health profiles in young adults 18–24 years of age with ASD to peers with and without other developmental disability. Young adults with ASD were more likely to have almost all the examined clinical health issues and health service use indicators compared to peers without developmental disability. They were more likely to have at least one psychiatric diagnosis, and visit the family physician, pediatrician, psychiatrist, and emergency department for psychiatric reasons, compared to peers with other developmental disability. Planning for the mental health care of transition age adults with ASD is an important priority for health policy.

Transition-Age Medicaid Coverage for Adolescents With Autism and Adolescents With Intellectual Disability

Although the majority of adolescents with autism spectrum disorder (ASD) rely on healthcare coverage through Medicaid during their transition into adulthood, little is known about their continuing eligibility. This study used Medicaid Analytic Extract (MAX) data to examine Medicaid coverage in a national sample using a cohort of adolescents with ASD ( n = 4,179) and a like-aged cohort with intellectual disability (ID, n = 21,844) over 5 years using survival analysis and Cox regression models. More than 1 in 4 adolescents with ASD lost coverage and fewer than half subsequently regained it. They were more likely to disenroll than adolescents with ID. Similarities in overall patterns among the 2 groups suggest that the experience of adolescents with ASD was characteristic of more general aspects of behavioral health coverage and indicate the need for programmatic reforms.

Annual trends in prevalence and incidence of autism spectrum disorders in Manitoba preschoolers and toddlers: 2004-2015

OBJECTIVES

Autism spectrum disorders (ASD) are among the leading causes of disabilities in children. We examined the annual prevalence and incidence rate of ASD between 2004 and 2015 in children aged 1 to 5 years residing in Manitoba.

METHODS

A population-based study was conducted using the Manitoba Population Research Data Repository. The study included children aged 1 to 5 years residing in Manitoba between 2004 and 2015. Standard identification algorithm was used to identify ASD cases from hospital abstracts and medical claims. Annual prevalence and incidence rates were calculated for the overall population and then stratified according to sex, region, and socio-economic status (SES). Multivariable negative binomial regression models, adjusted for sex, region, and SES, were used to examine changes in prevalence and incidence over study years.

RESULTS

Among children aged 1 to 5 years, 1685 ASD cases were diagnosed between 2004 and 2015. The crude ASD prevalence increased from 0.46% in 2004 to 0.97% in 2015 (p = 0.002). The crude incidence rate increased from 0.16% in 2004 to 0.39% in 2015 (p = 0.002). The increase in ASD prevalence and incidence was observed in all subgroups based on sex, region, and SES. The adjusted negative binomial model showed an annual relative risk increase, since 2004, for both prevalence and incidence of 1.69 (95% CI 1.56-1.83) and 1.84 (95% CI 1.62-2.09), respectively.

CONCLUSION

During the period from 2004 to 2015, both prevalence and incidence rates of diagnosed ASD in preschoolers and toddlers residing in Manitoba increased significantly.

Developmental functioning and symptom severity influence age of diagnosis in Canadian preschool children with autism

Background

Early diagnosis of autism spectrum disorder (ASD) is essential in most Canadian jurisdictions to access interventions that improve long-term child outcomes. Our main objective was to identify factors associated with timing of ASD diagnosis in five provinces across Canada.

Methods

Factors influencing age of diagnosis were assessed in the analyses of an inception cohort of children diagnosed with ASD between ages 2 and 5 years. We examined bivariate associations and using a series of multiple variable regression models, evaluated the unique contributions of developmental functioning, ASD symptoms and demographic variables. Children with known genetic abnormalities, or severe sensory or motor impairments interfering with assessment were excluded.

Results

Participants were 421 children (84.6% boys). The mean age of diagnosis was 38.2 months (SD=8.7), an average of 19 months after parents identified initial concerns. Factors associated with later diagnosis included more advanced language and cognitive skills, and higher levels of restricted repetitive behaviour symptoms. Child sex and family demographics were not associated with age of diagnosis. In regression analyses, language and cognitive skills accounted for 6.8% of variance in age of diagnosis and ASD symptoms contributed an additional 5.5%. Provincial site accounted for 4.0% of variance in age of diagnosis, independent of developmental skills and ASD symptoms.

Interpretation

Diagnosis of ASD occurred, on average, 19 months after parents' initial concerns. Language and cognitive skills, symptom severity and provincial site accounted for variation in age of ASD diagnosis in this Canadian cohort. Variable presentation across the developmental continuum must be considered in planning assessment services to ensure timely ASD diagnosis so that outcomes can be improved. Policy and practice leadership is also needed to reduce interprovincial variability.

Prevalence and Correlates of Autism Spectrum Disorders in Quebec: Prévalence et corrélats des troubles du spectre de l'autisme au Québec

OBJECTIVE

To estimate the prevalence, comorbidities, and service use of people with autism spectrum disorders (ASDs) based on data from Quebec Integrated Chronic Diseases Surveillance System (QICDSS).

METHODS

We included all residents up to age 24 eligible for health plan coverage who were in Quebec for at least 1 day from January 1, 1996, to March 31, 2015. To be considered as having an ASD, an individual had to have had at least 1 physician claim or hospital discharge abstract from 2000 to 2015 indicating one of the following ASD diagnosis codes: ICD-9 codes 299.0 to 299.9 or their ICD-10 equivalents.

RESULTS

The QICDSS shows that the prevalence of ASD has risen steadily over the past decade to approximately 1.2% ( n = 16,940) of children and youths aged 1 to 17 years in 2014 to 2015. The same prevalence was obtained using Ministry of Education data. Common medical comorbidities included congenital abnormalities of the nervous system, particularly in the first year of life. Psychiatric comorbidity was much more highly prevalent, especially common mental disorders like anxiety and attention-deficit/hyperactivity disorder. Children and youths with ASDs made on average 2.3 medical visits per year compared with 0.2 in the general population. Between 18 and 24 years old, the mental health needs of individuals with ASDs were met less by medical specialists and more by general practitioners.

CONCLUSION

Information derived from this database could support and monitor development of better medical services coordination and shared care to meet the continuous and changing needs of patients and families over time.

Validating an administrative data-based case definition for identifying children and youth with autism spectrum disorder for surveillance purposes

OBJECTIVES

To evaluate the sensitivity and positive predictive value (PPV) of administrative health and education data for identifying cases of autism spectrum disorder (ASD) in Manitoba, and to recommend a surveillance case definition.

METHODS

Four service providers abstracted information on children who had been clinically diagnosed with ASD ("sensitivity cohort"). That information was linked to Manitoba's administrative health and education data and records were extracted into the study dataset. Records were also included for children who had an administrative diagnosis of ASD but who were not part of the sensitivity cohort. Study packages were mailed to the parents of the latter group in order to verify their diagnostic status. The sensitivity and PPV of various case definitions were calculated.

RESULTS

Among the 1728 service provider-reported cases, 1532 had an administrative diagnosis of ASD. A total of 2414 children had an administrative diagnosis, of whom 882 were not part of the sensitivity cohort. The response to the mail-out was very poor (&lt;3%). Accordingly, we calculated minimum PPVs. Our recommended surveillance case definitions are ≥1 physician claim (ICD-9-CM 299) or ≥1 "ASD" special education record (2-5 years of age), and ≥2 physician claims or ≥1 "ASD" special education record (6-14 years of age). The sensitivity ranged from 80% (95% CI: 77-83) to 88% (95% CI: 83-91) and the minimum PPV from 70% (95% CI: 67-73) to 78% (95% CI: 75-81) for these definitions.

CONCLUSION

This work advances the goal of establishing a cost-effective national surveillance system for ASD.

Needles in the haystack: Using open-text fields to identify persons with intellectual and developmental disabilities in administrative home care data

BACKGROUND

Use of administrative health data to study populations of interest is becoming more common. Identifying individuals with intellectual and developmental disabilities (IDD) in existing databases can be challenging due to inconsistent definitions and terminologies of IDD over time and across sectors, and the inability to rely on etiologies of IDD as they are frequently unknown.

AIMS

To identify diagnoses related to IDD in an administrative database and create a cohort of persons with IDD.

METHODS

Open-text diagnostic entries related to IDD were identified in an Ontario home care database (2003-2015) and coded as being either acceptable (e.g. Down syndrome) or ambiguous (e.g. intellectually challenged). The cognitive and functional skills of the resulting groups were compared using logistic regressions and standardized differences, and their age distributions were compared to that of the general home care population.

RESULTS

Just under 1% of the home care population had a diagnostic entry related to IDD. Ambiguous terms were most commonly used (61%), and this group tended to be older and less impaired than the group with more acceptable terms used to describe their IDD.

CONCLUSIONS

Open-text diagnostic variables in administrative health records can be used to identify and study individuals with IDD.

IMPLICATIONS

Future work is needed to educate assessors on the importance of using standard, accepted terminology when recording diagnoses related to IDD.

Prenatal exposure to fever is associated with autism spectrum disorder in the boston birth cohort

Autism spectrum disorder (ASD) is phenotypically and etiologically heterogeneous, with evidence for genetic and environmental contributions to disease risk. Research has focused on the prenatal period as a time where environmental exposures are likely to influence risk for ASD. Epidemiological studies have shown significant associations between prenatal exposure to maternal immune activation (MIA), caused by infections and fever, and ASD. However, due to differences in study design and exposure measurements no consistent patterns have emerged revealing specific times or type of MIA exposure that are most important to ASD risk. No prior studies have examined prenatal MIA exposure and ASD risk in an under-represented minority population of African ancestry. To overcome these limitations, we estimated the association between prenatal exposure to fever and maternal infections and ASD in a prospective birth cohort of an understudied minority population in a city in the United States. No association was found between prenatal exposure to genitourinary infections or flu and the risk of ASD in a nested sample of 116 ASD cases and 988 typically developing controls in crude or adjusted analyses. Prenatal exposure to fever was associated with increased ASD risk (aOR 2.02 [1.04-3.92]) after adjustment for educational attainment, marital status, race, child sex, maternal age, birth year, gestational age, and maternal smoking. This effect may be specific to fever during the third trimester (aOR 2.70 [1.00-7.29]). Our findings provide a focus for future research efforts and ASD prevention strategies across diverse populations. Autism Res 2017, 10: 1878-1890. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

LAY SUMMARY

We looked at whether activation of the immune system during pregnancy increases the chance a child will develop ASD. We examined 116 children with ASD and 988 children without ASD that came from a predominantly low income, urban, minority population. We found that having the flu or genitourinary tract infections during pregnancy is not related to the child being diagnosed with ASD. However, we did find children were at increased risk for ASD when their mothers had a fever during pregnancy.

Development of a Machine Learning Algorithm for the Surveillance of Autism Spectrum Disorder

The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts population-based surveillance of autism spectrum disorder (ASD) among 8-year old children in multiple US sites. To classify ASD, trained clinicians review developmental evaluations collected from multiple health and education sources to determine whether the child meets the ASD surveillance case criteria. The number of evaluations collected has dramatically increased since the year 2000, challenging the resources and timeliness of the surveillance system. We developed and evaluated a machine learning approach to classify case status in ADDM using words and phrases contained in children's developmental evaluations. We trained a random forest classifier using data from the 2008 Georgia ADDM site which included 1,162 children with 5,396 evaluations (601 children met ADDM ASD criteria using standard ADDM methods). The classifier used the words and phrases from the evaluations to predict ASD case status. We evaluated its performance on the 2010 Georgia ADDM surveillance data (1,450 children with 9,811 evaluations; 754 children met ADDM ASD criteria). We also estimated ASD prevalence using predictions from the classification algorithm. Overall, the machine learning approach predicted ASD case statuses that were 86.5% concordant with the clinician-determined case statuses (84.0% sensitivity, 89.4% predictive value positive). The area under the resulting receiver-operating characteristic curve was 0.932. Algorithm-derived ASD "prevalence" was 1.46% compared to the published (clinician-determined) estimate of 1.55%. Using only the text contained in developmental evaluations, a machine learning algorithm was able to discriminate between children that do and do not meet ASD surveillance criteria at one surveillance site.

Prescription Drug Use and Polypharmacy Among Medicaid-Enrolled Adults with Autism: A Retrospective Cross-Sectional Analysis

Background

A lack of gold standard treatment for autism spectrum disorders (ASD), no clear ASD management guidelines, and lack of evidence-based pharmacological interventions other than aripiprazole and risperidone elevate the risk of off-label prescribing and adverse effects among individuals with ASD, more so among adults.

Objective

The aim of this study was to identify and compare the types of prescription drug use, rates of polypharmacy, and characteristics associated with polypharmacy among adults with and without ASD in a retrospective cross-sectional analysis of a three-state Medicaid Analytic eXtract database (2000–2008).

Methods

Adults aged 22–64 years with ASD (ICD9-CM code: 299.xx) were propensity score-matched to ‘no ASD’ controls by age, sex, and race. General polypharmacy (≥6 unique classes of prescription drugs in a year) and psychotropic polypharmacy (≥3 unique prescription drug classes of psychotropic medications within a 90-day period) were the main study outcomes. Chi-square tests for rates, t tests for mean number of claims, and multivariate logistic regressions for likelihood of prescription drug use and polypharmacy were run.

Results

Annually, almost 75% of adults with ASD had >20 prescription drug claims compared with 33% of adults without ASD. Around 85% of adults with ASD used at least one psychotropic drug class compared with 42% of adults without ASD. Highly common psychotropics were antipsychotics (66%_ASD vs 20%_noASD), anticonvulsants (59%_ASD vs 20%_noASD), and anxiolytics/hypnotics/sedatives (21%_ASD vs 11%_noASD). Other than psychotropics, many adults with ASD used medical prescription drugs such as antimicrobials (47%), dermatologic agents (48%), respiratory agents (38%), gastrointestinal agents (31%), alternative medications (25%), antiparkinsonian agents (22.6%), antihyperlipidemics/statins (7.3%), and immunologics (2.0%). Rates of general (48%_ASD vs 32%_noASD) and psychotropic polypharmacy (19%_ASD vs 6%_noASD) were significantly higher in the ASD group.

Conclusion

Prescription drug use and polypharmacy rates among adults with ASD are substantially higher than those in an age-, sex-, and race-matched cohort of adults without ASD. Adults with ASD frequently use therapeutic treatments other than psychotropics. Healthcare providers, who usually report low confidence in treating patients with ASD, should play an active role in constant monitoring of prescription drug use patterns and patient response to interventions. Prescribers and caregivers are encouraged to make decisions after weighing the benefits and risks associated with a pharmacological treatment. Further investigations into the common use of any alternative treatments that can affect a patient’s response to core treatments should also be conducted.

Electronic supplementary material

The online version of this article (doi:10.1007/s40801-016-0096-z) contains supplementary material, which is available to authorized users.

Increased Risk of Autism Spectrum Disorders in Children Born to Women With Systemic Lupus Erythematosus: Results From a Large Population-Based Cohort

OBJECTIVE

In utero exposure to maternal antibodies and cytokines are potential risk factors for autism spectrum disorders (ASDs). The aim of this study was to determine whether children born to mothers with systemic lupus erythematosus (SLE) have an increased risk of ASD compared to children born to mothers without SLE.

METHODS

The study population was derived from the Offspring of SLE Mothers Registry (OSLER), a large population-based cohort identified through healthcare databases in Quebec (1989-2009) comprising all women who had ≥1 hospitalization for a delivery (stillbirth or live birth) after SLE diagnosis. As general population controls, a randomly selected group of women without SLE was matched ≥4:1 to the mothers with SLE for age and year of delivery. Children born live to mothers with SLE and those born live to matched controls were identified, and a recorded diagnosis of ASD was ascertained for each child. Multivariate analyses were performed to adjust for parents' demographic characteristics, sex, birth order of the child, maternal comorbidities, and obstetric complications.

RESULTS

In total, 509 women with SLE had 719 children, and 5,824 matched controls had 8,493 children. Children born to women with SLE were more frequently found to have a diagnosis of ASD compared to controls (frequency of recorded ASDs 1.4% [95% confidence interval (95% CI) 0.8-2.5] versus 0.6% [95% CI 0.5-0.8]), a difference of 0.8% (95% CI 0.1-1.9). The mean age at ASD diagnosis was younger in offspring of SLE mothers (mean 3.8 years, 95% CI 1.8-5.8) compared to offspring of controls (mean 5.7 years, 95% CI 4.9-6.5). In primary multivariate analysis, SLE offspring had a substantially increased risk of ASD compared to controls (odds ratio 2.19, 95% CI 1.09-4.39).

CONCLUSION

Compared to children from the general population, children born to women with SLE have an increased risk of ASD, although, in absolute terms, it represents a rare outcome. These hypothesis-generating data provide direction for additional studies of maternal autoimmunity and ASD risk.

Incidence and cohort prevalence for autism spectrum disorders in the Avalon Peninsula, Newfoundland and Labrador

BACKGROUND

Recent studies have reported increased prevalence for autism spectrum disorders in a number of geographical locations. Our objective was to determine the incidence and 1-year cohort prevalence for autism spectrum disorders in children less than 15 years of age and living in the Avalon Peninsula at the time of diagnosis.

METHODS

Retrospective and prospective data were obtained from the Janeway Children's Health and Rehabilitation Centre (St. John's), including the identification and specific diagnosis for all children assessed for autism spectrum disorder from 2006 to 2010. Additional clinic data were reviewed to update the data until the end of 2013.

RESULTS

From 2006 to 2010, 272 children had a diagnosis of autism spectrum disorder, averaging 54 new cases per year. The incidence of new cases increased from 10.1 to 16.7 cases per 10 000 per year from 2006 to 2010. At the end of 2013, the prevalence among children born in 2006 was 1 case of autism spectrum disorder per 46 children or 215.77 per 10 000.

INTERPRETATION

We found higher rates of autism spectrum disorder than previously reported for this population. The prevalence in this region is also high when compared with other global populations. The high rate of diagnosis supports the need for a provincial autism spectrum disorder registry and further research on autism spectrum disorder within this population.

Validation of administrative health data for the pediatric population: a scoping review

BACKGROUND

The purpose of this research was to perform a scoping review of published literature on the validity of administrative health data for ascertaining health conditions in the pediatric population (≤20 years).

METHODS

A comprehensive search of OVID Medline (1946 - present), CINAHL (1937 - present) and EMBASE (1947 - present) was conducted. Characteristics of validation studies that were abstracted included the study population, health condition, topic of the validation (e.g., single diagnosis code versus case-finding algorithm), administrative and validation data sources. Inter-rater agreement was measured using Cohen's κ. Extracted data were analyzed using descriptive statistics.

RESULTS

A total of 37 articles met the study inclusion criteria. Cohen's κ for study inclusion/exclusion and data abstraction was 0.88 and 0.97, respectively. Most studies validated administrative data from the USA (43.2%) and Canada (24.3%), and focused on inpatient records (67.6%). Case-finding algorithms (56.7%) were more frequently validated than diagnoses codes alone (37.8%). Five conditions were validated in more than one study: diabetes mellitus, inflammatory bowel disease, asthma, rotavirus infection, and tuberculosis.

CONCLUSIONS

This scoping review identified a number of gaps in the validation of administrative health data for pediatric populations, including limited investigation of outpatient populations and older pediatric age groups.

Does a claims diagnosis of autism mean a true case?

The purpose of this study was to validate autism spectrum disorder cases identified through claims-based case identification algorithms against a clinical review of medical charts. Charts were reviewed for 432 children who fell into one of the three following groups: (a) more than or equal to two claims with an autism spectrum disorder diagnosis code (n = 182), (b) one claim with an autism spectrum disorder diagnosis code (n = 190), and (c) those who had no claims for autism spectrum disorder but had claims for other developmental or neurological conditions (n = 60). The algorithm-based diagnoses were compared with documented autism spectrum disorders in the medical charts. The algorithm requiring more than or equal to two claims for autism spectrum disorder generated a positive predictive value of 87.4%, which suggests that such an algorithm is a valid means to identify true autism spectrum disorder cases in claims data.

Using administrative health data to identify individuals with intellectual and developmental disabilities: a comparison of algorithms

BACKGROUND

Individuals with intellectual and developmental disabilities (IDD) experience high rates of physical and mental health problems; yet their health care is often inadequate. Information about their characteristics and health services needs is critical for planning efficient and equitable services. A logical source of such information is administrative health data; however, it can be difficult to identify cases with IDD in these data. The purpose of this study is to evaluate three algorithms for case finding of IDD in health administrative data.

METHODS

The three algorithms were created following existing approaches in the literature which ranged between maximising sensitivity versus balancing sensitivity and specificity. The broad algorithm required only one IDD service contact across all available data and time periods, the intermediate algorithm added the restriction of a minimum of two physician visits while the narrow algorithm added a further restriction that the time period be limited to 2006 onward. The resulting three cohorts were compared according to socio-demographic and clinical characteristics. Comparisons on different subgroups for a hypothetical population of 50,000 individuals with IDD were also carried out: this information may be relevant for planning specialised treatment or support programmes.

RESULTS

The prevalence rates of IDD per 100 were 0.80, 0.52 and 0.18 for the broad, intermediate and narrow algorithms, respectively. Except for 'percentage with psychiatric co-morbidity', the three cohorts had similar characteristics (standardised differences < 0.1). More stringent thresholds increased the percentage of psychiatric co-morbidity and decreased the percentages of women and urban residents in the identified cohorts (standardised differences = 0.12 to 0.46). More concretely, using the narrow algorithm to indirectly estimate the number of individuals with IDD, a practice not uncommon in planning and policy development, classified nearly 7000 more individuals with psychiatric co-morbidities than using the intermediate algorithm.

CONCLUSIONS

The prevalence rate produced by the intermediate algorithm most closely approximated the reported literature rate suggesting the value of imposing a two-physician visit minimum but not restricting the time period covered. While the statistical differences among the algorithms were generally minor, differences in the numbers of individuals in specific population subgroups may be important particularly if they have specific service needs. Health administrative data can be useful for broad-based service planning for individuals with IDD and for population level comparisons around their access and quality of care.

Gestational age at birth and risk of autism spectrum disorders in Alberta, Canada

OBJECTIVE

To examine the association between autism spectrum disorders (ASD) and each completed week of gestation using a graphical method of presenting results at all possible categorizations of gestational age (GA).

STUDY DESIGN

The risk of ASD in a total of 218110 singleton live births with complete data from Alberta, Canada between 1998 and 2004 was examined through linkage to health insurance records. The relative risk of developing ASD according to the 21 dichotomizations of shorter gestation (GA ≤ 23 weeks vs >23 weeks to ≤ 43 weeks vs >43 weeks, in 1-week increments) was calculated using log-binomial regression and adjusted for fetal sex, socioeconomic status, and birth year.

RESULTS

We observed a gradual increased risk of ASD with shorter gestation. Cutoffs only between 29 and 40 weeks clearly denoted an elevated risk of developing ASD compared with longer gestation, and the risk increased with earlier GA cutoff. The results were not affected by sex or measures of fetal growth.

CONCLUSION

Our data confirm the role of shortened gestation in ASD risk. We warn against the use of prespecified or a data-driven GA cutoff, however; instead, we recommend systematically examining all plausible cutoffs for GA to avoid overstating the homogeneity of risk in children on either side of a given cutoff, as well as to increase the comparability of studies.

Validation of administrative data sources for endoscopy utilization in colorectal cancer diagnosis

Background

Validation of administrative data is important to assess potential sources of bias in outcome evaluation and to prevent dissemination of misleading or inaccurate information. The purpose of the study was to determine the completeness and accuracy of endoscopy data in several administrative data sources in the year prior to colorectal cancer diagnosis as part of a larger project focused on evaluating the quality of pre-diagnostic care.

Methods

Primary and secondary data sources for endoscopy were collected from the Alberta Cancer Registry, cancer medical charts and three different administrative data sources. 1672 randomly sampled patients diagnosed with invasive colorectal cancer in years 2000–2005 in Alberta, Canada were included. A retrospective validation study of administrative data for endoscopy in the year prior to colorectal cancer diagnosis was conducted. A gold standard dataset was created by combining all the datasets. Number and percent identified, agreement and percent unique to a given data source were calculated and compared across each dataset and to the gold standard with respect to identifying all patients who underwent endoscopy and all endoscopies received by those patients.

Results

The combined administrative data and physician billing data identified as high or higher percentage of patients who had one or more endoscopy (84% and 78%, respectively) and total endoscopy procedures (89% and 81%, respectively) than the chart review (78% for both).

Conclusions

Endoscopy data has a high level of completeness and accuracy in physician billing data alone. Combined with hospital in/outpatient data it is more complete than chart review alone.

The role of prenatal, obstetric and neonatal factors in the development of autism

We conducted a linked database cohort study of infants born between 1990 and 2002 in Nova Scotia, Canada. Diagnoses of autism were identified from administrative databases with relevant diagnostic information to 2005. A factor representing genetic susceptibility was defined as having an affected sibling or a mother with a history of a psychiatric or neurologic condition. Among 129,733 children, there were 924 children with an autism diagnosis. The results suggest that among those with low genetic susceptibility, some maternal and obstetric factors may have an independent role in autism etiology whereas among genetically susceptible children, these factors appear to play a lesser role. The role of pre-pregnancy obesity and excessive weight gain during pregnancy on autism risk require further investigation.

Chronic disease risks in young adults with autism spectrum disorder: forewarned is forearmed

An emerging, cost-effective method to examine prevalent and future health risks of persons with disabilities is electronic health record (EHR) analysis. As an example, a case-control EHR analysis of adults with autism spectrum disorder receiving primary care through the Cleveland Clinic from 2005 to 2008 identified 108 adults with autism spectrum disorder. In this cohort, rates of chronic disease included 34.9% for obesity, 31.5% for hyperlipidemia, and 19.4% for hypertension. Compared with a control cohort of patients from the same health system matched for age, sex, race, and health insurance status, adults with autism spectrum disorder were more likely to be diagnosed with hyperlipidemia (odds ratio  =  2.0, confidence interval  =  1.2-3.4, p  =  .012). Without intervention, adults with autism spectrum disorder appear to be at significant risk for developing diabetes, coronary heart disease, and cancer by midlife.

Factors affecting the age at diagnosis of autism spectrum disorders in Nova Scotia, Canada

While early diagnosis of autism spectrum disorders (ASD) is essential for ensuring timely access to early intervention services, there is limited existing literature investigating factors that delay this diagnosis. This population-based cohort study explored the age at which children in Nova Scotia, Canada, are diagnosed with ASDs and the factors associated with this age. Children diagnosed with an ASD between January 1992 and December 2005 were identified from a cohort of live births in the province between 1990 and 2002. Demographic and clinical variables were extracted from population-based perinatal and administrative health databases and evaluated as predictors of age at ASD diagnosis. Of 122,759 live births, 884 cases of ASDs were identified during the study period. The median age at diagnosis within the cohort was 4.6 years. In adjusted linear regression analysis, a one year increase in maternal age at delivery was associated with a 0.06 decrease in age at ASD diagnosis (p= .0007). Children who were residents of Halifax County received their diagnoses 0.52 years later than residents of other counties (p= .0054). A diagnosis of attention-deficit/hyperactivity disorder (ADHD) was associated with a 1.29-year increase in age at diagnosis (p< .0001). These results suggest that potential exists for improving early detection of ASDs in the province. Future research in this field has the potential to contribute to our understanding of the causal pathways linking the demographic and clinical variables we have identified and the age at diagnosis of ASDs.

Autism spectrum disorders and fetal hypoxia in a population-based cohort: accounting for missing exposures via Estimation-Maximization algorithm

BACKGROUND

Autism spectrum disorders (ASD) are associated with complications of pregnancy that implicate fetal hypoxia (FH); the excess of ASD in male gender is poorly understood. We tested the hypothesis that risk of ASD is related to fetal hypoxia and investigated whether this effect is greater among males.

METHODS

Provincial delivery records (PDR) identified the cohort of all 218,890 singleton live births in the province of Alberta, Canada, between 01-01-98 and 12-31-04. These were followed-up for ASD via ICD-9 diagnostic codes assigned by physician billing until 03-31-08. Maternal and obstetric risk factors, including FH determined from blood tests of acidity (pH), were extracted from PDR. The binary FH status was missing in approximately half of subjects. Assuming that characteristics of mothers and pregnancies would be correlated with FH, we used an Estimation-Maximization algorithm to estimate HF-ASD association, allowing for both missing-at-random (MAR) and specific not-missing-at-random (NMAR) mechanisms.

RESULTS

Data indicated that there was excess risk of ASD among males who were hypoxic at birth, not materially affected by adjustment for potential confounding due to birth year and socio-economic status: OR 1.13, 95%CI: 0.96, 1.33 (MAR assumption). Limiting analysis to full-term males, the adjusted OR under specific NMAR assumptions spanned 95%CI of 1.0 to 1.6.

CONCLUSION

Our results are consistent with a weak effect of fetal hypoxia on risk of ASD among males. E-M algorithm is an efficient and flexible tool for modeling missing data in the studied setting.

Health care expenditures for children with autism spectrum disorders in Medicaid

OBJECTIVE

To study trends in health care expenditures associated with autism spectrum disorders (ASDs) in state Medicaid programs.

METHOD

Using Medicaid data from 42 states from 2000 to 2003, patients aged 17 years and under who were continuously enrolled in fee-for-service Medicaid were studied. Patients with claims related to autistic disorder (autism) were identified, as were patients with claims for any ASD other than autism. Total expenditures per treated patient consisted of Medicaid reimbursements from inpatient, outpatient, and long-term care and prescription drugs. Inflation-adjusted expenditures were compared over time and with expenditures associated with other mental health disorders.

RESULTS

A total of 2,184,677 children were diagnosed with some type of mental disorder during the study period. Of these children, 69,542 had an ASD, with 49,921 having autism and the rest having another ASD. Mean total health care expenditures per child with ASD were $22,079 in 2000 (in 2003 US dollars), and rose by 3.1% to $22,772 in 2003. The treated prevalence of autism per 10,000 covered lives rose by 32.2% from 40.6 to 53.6, the highest rate of increase among all mental disorders. Total health care expenditures for ASDs per 10,000 covered lives grew by 32.8% from $1,270,435 in 2000 (in 2003 dollars) to $1,686,938 in 2003.

CONCLUSIONS

Medicaid-reimbursed health care expenditures for ASD were quite substantial. Although the per patient expenditures grew slightly over time, the large increase in treated prevalence caused a considerable rise in total ASD-associated health care expenditures.

Contributions of the environment and environmentally vulnerable physiology to autism spectrum disorders

PURPOSE OF REVIEW

This review presents a rationale and evidence for contributions of environmental influences and environmentally vulnerable physiology to autism spectrum disorders (ASDs).

RECENT FINDINGS

Recent studies suggest a substantial increase in ASD prevalence above earlier Centers for Disease Control figures of one in 150, only partly explicable by data artifacts, underscoring the possibility of environmental contributors to increased prevalence. Some gene variants in ASD confer altered vulnerability to environmental stressors and exposures. De-novo mutations and advanced parental age as a risk factor for ASD also suggest a role for environment. Systemic and central nervous system pathophysiology, including oxidative stress, neuroinflammation, and mitochondrial dysfunction can be consistent with a role for environmental influence (e.g. from air pollution, organophosphates, heavy metals) in ASD, and some of the underlying biochemical disturbances (such as abnormalities in glutathione, a critical antioxidant and detoxifier) can be reversed by targeted nutritional interventions. Dietary factors and food contaminants may contribute risk. Improvement and loss of diagnosis in some with ASD suggest brain circuitry amenable to environmental modulation.

SUMMARY

Prevalence, genetic, exposure, and pathophysiological evidence all suggest a role for environmental factors in the inception and lifelong modulation of ASD. This supports the need for seeking targets for early and ongoing medical prevention and treatment of ASD.