ArticleBMJ public health2026
Measuring reading and language skill in generation Scotland: Scottish Family Health Study.
Article in BMJ public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Introduction: Successful acquisition of language and literacy skills is essential to child development and is associated with positive socioeconomic and well-being outcomes later in life. Research into communication skills has primarily focused on early development and childhood. This is particularly the case for studies of genetic variation in reading and language skills, which rarely include older adults; the largest genome-wide association study to date includes participants only up to 26 years of age. We argue that reading-related traits remain stable across the adult lifespan and that including older adults offers a way to increase statistical power for gene discovery. Here, we describe newly available reading, spelling and oral-language-related measures in the Generation Scotland: Scottish Family Health Study (GS:SFHS). Methods: Phenotypic data in GS:SFHS were extended to include quantitative measures of reading, spelling and language-related measures as well as self-reported neurodevelopmental and psychiatric conditions. Participants also reported frequency of book reading in both childhood and adulthood. Multiple regression analyses were conducted to examine associations between reading-related measures and age and characterise their stability across the adult lifespan. Results: Reading-related data were collected for N=1595 GS:SFHS participants aged 29.5-76.9 years. Regression analyses indicated that reading and spelling performance were stable across the adult lifespan. In contrast, negative curvilinear effects of age Conclusions: These data provide a novel resource for investigating reading, spelling and language skills in adults. The opportunity to link these measures with the existing and future biomarker, cognitive and health record data within GS:SFHS offers a deeply phenotyped dataset with substantial potential for replication studies, meta-analyses and future genetic discovery.
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