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The prevalence and profile of autism in individuals born preterm: a systematic review and meta-analysis
Catherine Laverty1, Andrew Surtees2,3, Rory O'Sullivan4
1School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK. cml704@student.bham.ac.uk.
Insights
Preterm birth is linked to higher autism rates. This meta-analysis found autism characteristics in 20% of preterm individuals using screening tools, and 6% using diagnostic assessments.
Area of Science:
- Neurodevelopmental disorders
- Perinatal medicine
- Developmental psychology
Background:
- Preterm birth (<37 weeks) is associated with adverse developmental outcomes.
- Preterm populations exhibit heightened rates of autism spectrum disorder (ASD).
- Prematurity may increase the risk of neurodevelopmental impairments.
Purpose of the Study:
- To synthesize existing literature on autism characteristics in preterm populations.
- To calculate pooled prevalence estimates for autism in individuals born preterm.
- To compare autism rates in preterm versus general populations.
Main Methods:
- A meta-analysis was conducted following PRISMA guidelines.
- Literature search across five databases until December 2020.
- Included 52 studies, categorized by assessment method (screening tools vs. diagnostic assessments).
Main Results:
- Pooled prevalence of autism characteristics was 20% (screening tools) and 6% (diagnostic assessments).
- Individuals born preterm had 3.3 times higher odds of an autism diagnosis compared to the general population.
- Analysis included 10,900 retrieved papers, with 52 selected for final analysis.
Conclusions:
- Autism characteristics are significantly more prevalent in preterm individuals than in the general population.
- Clinical monitoring and support are crucial for individuals born preterm.
- Findings underscore the neurodevelopmental impact of prematurity.
Introduction:
Preterm birth (<37 weeks) adversely affects development in behavioural, cognitive and mental health domains. Heightened rates of autism are identified in preterm populations, indicating that prematurity may confer an increased likelihood of adverse neurodevelopmental outcomes. The present meta-analysis aims to synthesise existing literature and calculate pooled prevalence estimates for rates of autism characteristics in preterm populations.
Methods:
Search terms were generated from inspection of relevant high-impact papers and a recent meta-analysis. Five databases were searched from database creation until December 2020 with PRISMA guidelines followed throughout.
Results:
10,900 papers were retrieved, with 52 papers included in the final analyses, further classified by assessment method (screening tools N=30, diagnostic assessment N=29). Pooled prevalence estimates for autism in preterm samples was 20% when using screening tools and 6% when using diagnostic assessments. The odds of an autism diagnosis were 3.3 times higher in individuals born preterm than in the general population.
Conclusions:
The pooled prevalence estimate of autism characteristics in individuals born preterm is considerably higher than in the general population. Findings highlight the clinical need to provide further monitoring and support for individuals born preterm.
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