Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2018.

PROBLEM/CONDITION: Autism spectrum disorder (ASD). PERIOD COVERED: 2018. DESCRIPTION OF SYSTEM: The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts active surveillance of ASD. This report focuses on the prevalence and characteristics of ASD among children aged 8 years in 2018 whose parents or guardians lived in 11 ADDM Network sites in the United States (Arizona, Arkansas, California, Georgia, Maryland, Minnesota, Missouri, New Jersey, Tennessee, Utah, and Wisconsin). To ascertain ASD among children aged 8 years, ADDM Network staff review and abstract developmental evaluations and records from community medical and educational service providers. In 2018, children met the case definition if their records documented 1) an ASD diagnostic statement in an evaluation (diagnosis), 2) a special education classification of ASD (eligibility), or 3) an ASD International Classification of Diseases (ICD) code. RESULTS: For 2018, across all 11 ADDM sites, ASD prevalence per 1,000 children aged 8 years ranged from 16.5 in Missouri to 38.9 in California. The overall ASD prevalence was 23.0 per 1,000 (one in 44) children aged 8 years, and ASD was 4.2 times as prevalent among boys as among girls. Overall ASD prevalence was similar across racial and ethnic groups, except American Indian/Alaska Native children had higher ASD prevalence than non-Hispanic White (White) children (29.0 versus 21.2 per 1,000 children aged 8 years). At multiple sites, Hispanic children had lower ASD prevalence than White children (Arizona, Arkansas, Georgia, and Utah), and non-Hispanic Black (Black) children (Georgia and Minnesota). The associations between ASD prevalence and neighborhood-level median household income varied by site. Among the 5,058 children who met the ASD case definition, 75.8% had a diagnostic statement of ASD in an evaluation, 18.8% had an ASD special education classification or eligibility and no ASD diagnostic statement, and 5.4% had an ASD ICD code only. ASD prevalence per 1,000 children aged 8 years that was based exclusively on documented ASD diagnostic statements was 17.4 overall (range: 11.2 in Maryland to 29.9 in California). The median age of earliest known ASD diagnosis ranged from 36 months in California to 63 months in Minnesota. Among the 3,007 children with ASD and data on cognitive ability, 35.2% were classified as having an intelligence quotient (IQ) score ≤70. The percentages of children with ASD with IQ scores ≤70 were 49.8%, 33.1%, and 29.7% among Black, Hispanic, and White children, respectively. Overall, children with ASD and IQ scores ≤70 had earlier median ages of ASD diagnosis than children with ASD and IQ scores >70 (44 versus 53 months). INTERPRETATION: In 2018, one in 44 children aged 8 years was estimated to have ASD, and prevalence and median age of identification varied widely across sites. Whereas overall ASD prevalence was similar by race and ethnicity, at certain sites Hispanic children were less likely to be identified as having ASD than White or Black children. The higher proportion of Black children compared with White and Hispanic children classified as having intellectual disability was consistent with previous findings. PUBLIC HEALTH ACTION: The variability in ASD prevalence and community ASD identification practices among children with different racial, ethnic, and geographical characteristics highlights the importance of research into the causes of that variability and strategies to provide equitable access to developmental evaluations and services. These findings also underscore the need for enhanced infrastructure for diagnostic, treatment, and support services to meet the needs of all children.

Carers' perceptions of the impact of home telehealth monitoring on the provision of care and sustainability of use.

AIMS: This paper aims to report carers' perceptions of the impact of home telehealth on the provision of care and the sustainability of home telehealth use. METHOD: This paper is reporting on a sample of 15 carers who were involved in the telehealth arm of a larger controlled trial. RESULTS: Carers primarily believed that telehealth helped to provide better care. None of the carers had organised, or planned to organise, ongoing telehealth monitoring beyond the study. The main reason given for non-sustained usage was the belief that the person they cared for no longer required, or would benefit from, the monitoring. CONCLUSION: As the person being cared for was a frail older person with multiple chronic diseases and a history of recent hospitalisation, the non-sustained usage of home telehealth by carers raises questions about what is needed to ensure sustainability of use; this requires further investigation.

Screening for physical inactivity in general practice - a test of diagnostic accuracy.

BACKGROUND: It is unclear what is the best method of accurately identifying physically inactive patients in general practice. This study aimed to compare the performance of different methods of assessing patient physical activity levels in general practice. OBJECTIVE: Thirteen general practitioners were randomly allocated to perform either their usual assessment, or this with a Lifescripts tool, on consecutive patients. The authors measured patients' physical activity by accelerometer over 1 week, including steps per day, then calculated agreement, kappa specificity, sensitivity, positive and negative predictive value (PV) and ROC characteristics for each assessment method (GPs' usual assessment, Lifescripts tool and steps per day) against the reference standard of accelerometer classification. RESULTS: Data from 29 patients was included. Agreement between subjective assessments was highest for GPs' usual assessment (agreement 73%; kappa 0.47; p=0.03), which also gave the highest area under the ROC curve (0.75, 95% CI: 0.52-0.98). However, this still had low specificity (67%) and positive PV (63%). Using a cut-off of 7500 steps/day maximised the area under the ROC curve at 0.91 (95% CI: 0.82-1.00), 19.2% greater than GPs' usual assessment. CONCLUSION: Measuring steps per day may be a feasible and more effective way to screen for physically inactive patients than self report. A large scale study to confirm these results is necessary.

Cardiometabolic risk in younger and older adults across an index of ambulatory activity.

BACKGROUND: Pedometers are increasingly being used to assess population levels of physical activity and as motivational tools for individuals to increase their physical activity. To maximize their utility, a framework for classifying pedometer-determined activity into meaningful health-related categories is needed. PURPOSE: This study investigated whether a pedometer step index proposed by Tudor-Locke and Bassett can effectively group younger and older adults according to cardiometabolic health status. METHODS: Analyses (conducted in 2008) used cross-sectional data from the Childhood Determinants of Adult Health study (1793 adults aged 26-36 years; collected 2004-2006) and from the Tasmanian Older Adult Cohort study (1014 adults aged 50-80 years; collected 2002-2006). Participants wore a pedometer for 7 days and the prevalence of cardiometabolic health indicators, including the metabolic syndrome, elevated Pathobiological Determinants of Atherosclerosis in Youth risk scores, and elevated Framingham risk scores, was examined across the following step categories: sedentary (< 5000); low-active (5000-7499); somewhat active (7500-9999); active (10,000-12,499); and high-active (> or = 12,500). RESULTS: With the exception of younger men, individuals achieving > or = 5000 steps had a substantially lower prevalence of adverse cardiometabolic health indicators than those obtaining fewer steps. Differences in the prevalence of adverse indicators were generally modest across higher steps-per-day categories. However, younger men and women in the high-active category had a substantially lower prevalence of some adverse health indicators. CONCLUSIONS: In general, the proposed index for classifying pedometer activity effectively distinguishes cardiometabolic health risk. Pedometers may be a useful tool for objectively identifying inactive individuals at greatest risk for poor cardiometabolic health.

Inpatient hospital service utilization of the uninsured in Nebraska: policy implications for addressing uncompensated care.

In order better to inform policymakers about financing uncompensated hospital care through appropriate allocation of resources among Nebraska communities, this study used seven years (1996-2002) of county-level data from multiple sources to examine the relationship between population economic factors and the hospital inpatient care use by uninsured patients. The generalized estimating equation (GEE) regression analysis showed that, at the county level, the population uninsurance rate and other economic factors (e.g., per capita income, the percentage of population receiving welfare) are statistically significant predictors of average hospital self-pay inpatient charge per resident. Residents in the three western regions of the state also incurred statistically higher per-resident hospital self-pay inpatient charges than did their counterparts in the three eastern regions. State policymakers in Nebraska can use our study results to allocate resources on the basis of community economic characteristics and geographic location, to help reduce the financial burden of caring for the uninsured to safety net hospitals. The study may have a wide application to other states examining the same policy issues. The model used in this study can be easily created for other states, as the required data are readily available.