Assessing children's EDB problems, maternal mental health, and parental perceptions may identify children at risk for bullying. Parent-child communication, meeting children's friends, and encouraging children academically were associated with lower bullying odds; these protective factors may be useful in designing preventive interventions.

The objective of this study is to estimate Hispanic/non-Hispanic (nH)-white health disparities and assess the extent to which disparities can be explained by immigrant status and household primary language. The 2007 National Survey of Children's Health was funded by the Maternal and Child Health Bureau, and conducted by Centers for Disease Control and Prevention's National Center for Health Statistics as a module of the State and Local Area Integrated Telephone Survey. We calculated disparities for various health indicators between Hispanic and nH-white children, and used logistic regression to adjust them for socio-economic and demographic characteristics, primary language spoken in the household, and the child's immigrant status. Controlling for language and immigrant status greatly reduces health disparities, although it does not completely eliminate all disparities showing poorer outcomes for Hispanic children. English-speaking and nonimmigrant Hispanic children are more similar to nH-white children than are Hispanic children in non-English speaking households or immigrant children. Hispanic/nH-white health disparities among children are largely driven by that portion of the Hispanic population that is either newly-arrived to this country or does not speak primarily English in the household.

Research Objective This study examines small area variations in readmission rates to assess whether higher readmission rate in an area is associated with higher clusters of patients with multiple chronic conditions. Study Design The study uses hospital discharge data of adult (18+) patients in 6 U.S. states for 2009 from the Healthcare Cost and Utilization Project of the Agency for Healthcare Research and Quality, linked to contextual and provider data from Health Resources and Services Administration. A multivariate cross sectional design at primary care service area (PCSA) level is used. Principal Findings Adjusting for area characteristics, the readmission rates were significantly higher in PCSAs having higher proportions of patients with 2–3 chronic conditions and those with 4+ chronic conditions, compared with areas with a higher concentration of patients with 0–1 chronic conditions. Conclusions Using small area analysis, the study shows that areas with higher concentration of patients with increased comorbid conditions are more likely to have higher readmission rates.

Autism spectrum disorder (ASD) diagnoses sometimes change due to misdiagnosis, maturation, or treatment. This study uses a probability-based national survey—the Survey of Pathways to Diagnosis and Services—to compare currently diagnosed (n=1420) and previously diagnosed (n=187) children aged 6–17 years based on retrospective parental reports of early concerns about their children’s development, responses to those concerns by doctors and other health care providers, the type of provider who made the first ASD diagnosis, and the ASD subtype diagnoses received (if any). Propensity score matching was used to control for differences between the groups on children’s current level of functioning and other current characteristics that may have been related to diagnosis loss. Approximately 13% of the children ever diagnosed with ASD were estimated to have lost the diagnosis, and parents of 74% of them believe it was changed due to new information. Previously diagnosed children were less likely to have parents with early concerns about verbal skills, nonverbal communication, learning, and unusual gestures or movements. They were also less likely to have been referred to and diagnosed by a specialist. Previously diagnosed children were less likely to have ever received a diagnosis of Asperger’s disorder or autistic disorder.

Multiple factors, including demographic characteristics and indicators of social disadvantage, distinguish children with probable developmental delay from those unlikely to have developmental delay. Fewer factors identify children with possible delay.