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E-news ExclusiveThe Association Between Autism Spectrum Traits and Age-Related Spatial Working Memory Decline
However, due to historical changes to the diagnostic criteria for autism (eg, from a narrow to wide diagnostic criteria, historically being a predominantly male diagnosis), many people remain undiagnosed (Happé & Frith, 2020; Lai & Baren Cohen, 2015). For example, a study using United Kingdom health care records found that only 1 in 18,000 adults over the age of 50 had an autism diagnosis in 2018, suggesting that only one in nine autistic people in this age group are diagnosed (O’Nions et al, 2023). Additionally, due to these changes in diagnostic criteria and the high rates of underdiagnosis in older populations, we know little about the needs of autistic people as they age (Mason et al, 2022). Autism is often viewed as being part of a spectrum, where it exists at the end of a continuum of high to low autistic traits found in the general population (Constantino & Todd, 2003; Hoekstra et al, 2007). Additionally, these traits are found to have strong genetic overlap with diagnosed autism (Bralten et al, 2018). Furthermore, classifying autistic traits as natural human variations existing on a continuum, as opposed to medical deficits, also aligns with the neurodiversity perspective, which returns autonomy to the autistic community regarding their care and acknowledges not only differences but also strengths associated with autism (Kapp et al, 2013). As such, using a dimensional trait-based approach to study autism has become increasingly common, particularly in historically overlooked populations, for example, women/girls, and older people. The effectiveness of this approach is also strengthened by growing evidence that individuals with high autistic traits are often found to have similar social, health, and cognitive profiles to diagnosed autistic samples (Stewart et al, 2020, 2021, 2023). Taken together, studying autistic traits in older age is a convenient way to bridge two high-priority public health issues—understanding the needs of neurodivergent people, and understanding the needs of older people. A central issue in autism and aging research is whether older autistic and high autistic trait people are at risk of accelerated cognitive aging. Cross-sectional evidence has indicated that older autistic people often self-report that their cognitive abilities are declining (Klein et al, 2023; Stewart et al, 2018, 2024), but there is little cross-sectional evidence about objective cognitive performance changes. Cognitive decline is a key issue for society, given the growing prevalence of dementia (Nichols et al, 2022), which is a WHO public health priority. Factors implicated in age-related cognitive decline, such as a decrease in interference inhibition (Earles et al, 1997), information processing speed (Caplan & Waters, 2005), social participation (Lövdén et al, 2005), and an increase in depressive symptoms (Paterniti et al, 2002), are all elevated in autistic populations (Haigh et al, 2018; Hossain et al, 2020; Stewart et al, 2024; Tonizzi et al, 2022). Thus, understanding whether there are differences in how particular domains of cognition might change with age in autistic and high autistic trait groups compared with nonautistic and low autistic trait groups is a topic of great interest. Geurts and Vissers (2012) have proposed three hypotheses of how cognition may change in autistic populations: that autistic individuals show similar age-related changes to nonautistic people, that is parallel development; that autism may have a detrimental effect on age-related cognitive changes, that is, steeper decline (double jeopardy hypothesis); or that autism may have a protective effect on age-related cognitive changes (safeguard hypothesis). Furthermore, these patterns of change may be domain specific. Working memory (WM) is a particular area of interest in this regard since working memory differences have been widely documented across early life through to middle age and later life in autistic populations (Kercood et al, 2014; Steele et al, 2007; Stewart et al, 2018, 2023). While some cross-sectional studies comparing WM between older and younger autistic adults have suggested either a parallel (Geurts & Vissers, 2012) or a safeguarding effect (Lever et al, 2015) of autism on WM decline, these studies are limited as findings could be due to differences in groups. To properly test the three hypotheses relating autism to changes in WM with age, longitudinal within-group studies are needed, and the current study is the first (to our knowledge) to do this. Consequently, this study aimed to investigate whether higher autism spectrum traits (AST) in middle-aged/older adults predicted memberships of different trajectories of age-related changes in spatial working memory (SWM) compared with no AST. It was hypothesized that middle-aged/older adults would show age-related SWM decline independent of AST, but trajectories of age-related change may differ in those with higher AST compared with no AST. The full study is available at https://academic.oup.com/gerontologist/article/65/5/gnaf096/8071459?login=false. — Source: The Gerontologist |
