Clinical, socio-demographic, and parental correlates of early autism traits in a community cohort

Abstract

Importance: Autism traits typically emerge between the ages of 1 and 2. It is not known if experiences which increase the likelihood of childhood autism are related to early trait emergence, or if other exposures are more important. Identifying factors linked to toddler autism traits may improve our understanding of the mechanisms underlying atypical neurodevelopment. Objective: To characterise the association between 18-month autism traits and clinical, socio-demographic, and parental factors. Design: This is a cohort study of toddlers (n=536). Clinical, socio-demographic, and parental information was collected at birth (gestational age at birth, sex, maternal body mass index, age, parental education level, parental first language, parental history of neurodevelopmental disorders) and at 18 months (parent cohabiting status, two measures of social deprivation, three measures of maternal parenting style, and a measure of maternal postnatal depression). General neurodevelopment was assessed with the Bayley Scales of Infant and Toddler Development, 3rd Edition (BSID-III), and autism traits were assessed using the Quantitative Checklist for Autism in Toddlers (Q-CHAT). Multivariable models were used to identify associations between variables and Q-CHAT. A model including BSID-III was used to identify factors associated with Q-CHAT independent of general neurodevelopment. Models were also evaluated addressing variable collinearity with principal component analysis (PCA). Setting: Single centre (London, UK). Participants: Sub-sample from the developing Human Connectome Project (dHCP). Results: A multivariable model explained 20% of Q-CHAT variance, with four individually significant variables (two measures of parenting style and two measures of socio-economic deprivation). After adding general neurodevelopment into the model 37% of Q-CHAT variance was explained, with three individually significant variables (two measures of parenting style and one measure of language development). After addressing variable collinearity with PCA, experience of early life adversity was positively correlated with Q-CHAT score via a single principal component, independently of general neurodevelopment. Neither sex nor family history of autism were associated with Q-CHAT score. Conclusions and Relevance: Our findings question whether potential autism diagnoses are being missed in more socially deprived groups, or if there are unidentified factors influencing the likelihood of transitioning from early traits at age 18 months to a clinical autism diagnosis in childhood.

Neonatal brain dynamic functional connectivity in term and preterm infants and its association with early childhood neurodevelopment

“…However, multiples studies have shown that family psychosocial and socio-demographic factors have a significant impact on brain development in childhood; with factors such as maternal stress, depression, low education, maternal immigration status, maternal age greater than 35 years, paternal age over 38 years and low household income all being linked to poorer developmental outcomes [87][88][89][90][91] . Thus, further studies could benefit from evaluating links between these wider socio-demographic markers and brain dynamics in early childhood 92 .…”

Neonatal brain dynamic functional connectivity in term and preterm infants and its association with early childhood neurodevelopment

“…However, multiples studies have shown that family psychosocial and socio-demographic factors have a significant impact on brain development in childhood; with factors such as maternal stress, depression, low education, maternal immigration status, maternal age greater than 35 years, paternal age over 38 years and low household income all being linked to poorer developmental outcomes (Deave et al, 2008; Dollaghan et al, 1999; Gale-Grant et al, 2020; Glover and O’Connor, 2002; Leonard et al, 2011; Rice et al, 2010; To et al, 2004). Thus, further studies could benefit from evaluating links between these wider socio-demographic markers and brain dynamics in early childhood (Gale-Grant et al, 2022).…”