Estimated Prevalence of Asthma in US Children With Developmental Disabilities

Abstract

IMPORTANCE The prevalence of asthma in US children with various developmental disabilities and delays is unclear, including how estimates vary by ethnic group. OBJECTIVE To report asthma prevalence estimates by various disability categories and developmental delays in a diverse sample of the US pediatric population. DESIGN, SETTING, AND PARTICIPANTS This population-based cross-sectional study encompassed a total of 71 811 families with children or adolescents aged 0 to 17 years (hereinafter referred to as children) who participated in the

Paediatric asthma and non‐allergic comorbidities: A review of current risk and proposed mechanisms

“…Regarding asthma and ASD, two of four studies found positive associations, 80,89 one found a null association 90 and another reported a negative association 91 . These last two studies were both clinically based samples of children recruited from hospital clinics, whereas the studies with positive associations used general populations.…”

“…These last two studies were both clinically based samples of children recruited from hospital clinics, whereas the studies with positive associations used general populations. Of note, the largest study on ASD and asthma comorbidity from the National Survey of Children's Health in the USA ( n = 71,084) found the risk for ASD was OR 1.68 (95% CI 1.07, 2.63) for children with asthma aged 0–17 years 80 …”

5-year risk of “adult-onset” chronic diseases during childhood and adolescent transitioning for individuals with cerebral palsy

“…For example, asthma was part of the criteria to define COPD. While COPD is not well studied in children with cerebral palsy, asthma is present among children and recently shown to be more prevalent among children with vs without cerebral palsy ( Xie et al, 2020 ). The selection of outcomes is not comprehensive, but it does provide novel evidence across many relevant physiologic systems, which is positioned to inform on the broader medical complexity present among children with cerebral palsy.…”

E-Cigarette Use in Young Adult Never Cigarette Smokers with Disabilities: Results from the Behavioral Risk Factor Surveillance System Survey

“…Furthermore, this ML approach may be used to select confounders for models as the dimensionality of the data increases. The LASSO algorithm was able to select some factors associated with disabilities such as asthma, HIV risky behavior, depression disorder, skipping medical care in the past 12 months due to cost and poor mental and physical health in the past 30 days [60][61][62][63]. Additionally, the LASSO algorithm was also able to select factors that were associated with e-cigarette use [2,27].…”