Socioeconomic disparities and difficulties to access to healthcare services among Canadian children with neurodevelopmental disorders and disabilities.

OBJECTIVES: The aims of this study were to identify the associations of levels of severity of neurodevelopmental disorders and disabilities (NDD/D) in children with their household socioeconomic status (SES) and their frequency of visits to a healthcare provider, and to examine how the severity of disability varied with these determinants among NDD/D subgroups, in order to inform possible social policy changes and to improve access to the healthcare system. METHODS: Data from the 2006 Participation and Activity Limitation Survey on children aged 5-14 years, collected by Statistics Canada, were analyzed (n=7,072 and weighted n=340,340). Children with NDD/D constituted those with impairments in motor, speech, neurosensory, and psychological functioning, as well as those who had issues with learning/cognition and social interactions. The weighted sample size for this group was n=111,630 (total sample size for children with limitations: n=174,810). We used logistic regression to assess the associations of household SES and frequency of visits to a healthcare provider with disability level. We included NDD/D subgroups as interaction terms in the model. Multiple correspondence analysis (MCA) was conducted to develop a profile of disability level. RESULTS: After-tax low income, family assistance, out-of-pocket expenses, needing but not receiving health services from a social worker, condition of the dwelling, and residential location were associated with the severity of NDD/D. Using MCA, 2 disability profiles could be identified based on access to healthcare, household income status, and condition of the dwelling. CONCLUSIONS: More social interventions are needed to reduce difficulties in accessing healthcare and to diminish the socially determined health inequalities faced by children with NDD/D.

Classification of upper limb disability levels of children with spastic unilateral cerebral palsy using K-means algorithm.

Treatment for cerebral palsy depends upon the severity of the child's condition and requires knowledge about upper limb disability. The aim of this study was to develop a systematic quantitative classification method of the upper limb disability levels for children with spastic unilateral cerebral palsy based on upper limb movements and muscle activation. Thirteen children with spastic unilateral cerebral palsy and six typically developing children participated in this study. Patients were matched on age and manual ability classification system levels I to III. Twenty-three kinematic and electromyographic variables were collected from two tasks. Discriminative analysis and K-means clustering algorithm were applied using 23 kinematic and EMG variables of each participant. Among the 23 kinematic and electromyographic variables, only two variables containing the most relevant information for the prediction of the four levels of severity of spastic unilateral cerebral palsy, which are fixed by manual ability classification system, were identified by discriminant analysis: (1) the Falconer index (CAI E ) which represents the ratio of biceps to triceps brachii activity during extension and (2) the maximal angle extension (θ Extension,max). A good correlation (Kendall Rank correlation coefficient = -0.53, p = 0.01) was found between levels fixed by manual ability classification system and the obtained classes. These findings suggest that the cost and effort needed to assess and characterize the disability level of a child can be further reduced.