The study stands out in a crowded field for its methodological rigor. Much of the existing evidence linking sleep to cognitive ageing relies on cross-sectional snapshots, single crude measures of sleep, and broad global cognitive scores that lump together very different mental abilities. Marent and colleagues—working with Mitch J. Duncan of the University of Newcastle, Greet Cardon of Ghent University, Genevieve Albouy of the University of Utah, and Jannique van Uffelen of KU Leuven—deliberately broke from that template. They measured sleep both objectively and subjectively, assessed cognition with a validated computerized battery that yields separate domain scores, and used statistical models designed for repeated observations over time, allowing them to ask not only whether sleep and cognition were related but whether those relationships changed as the study unfolded.

The objective side of the sleep measurement came from seven days of wrist-worn accelerometry, processed with the open-source GGIR software pipeline that has become a standard in large-scale sleep research. From the raw acceleration data, the team derived two key parameters: device-measured sleep duration and sleep efficiency, the latter defined as the share of the sleep period spent genuinely asleep rather than awake. Sleep efficiency is a particularly interesting metric because it captures sleep continuity—how fragmented a night of sleep is—rather than simply how long a person remains in bed. Two people can each log eight hours of sleep opportunity, yet one may sleep soundly through the night while the other wakes repeatedly, and accelerometry can distinguish between them in a way that morning questionnaires often cannot.

Subjective sleep quality was captured with the Pittsburgh Sleep Quality Index, one of the most widely used self-report instruments in sleep science. The researchers also constructed a multidimensional sleep health score, an approach that reflects a growing consensus in the field, formalized in a 2025 American Heart Association scientific statement, that sleep should be evaluated as a constellation of dimensions—duration, continuity, timing, quality, and regularity—rather than as a single number. This composite combined device-measured and self-reported sleep dimensions into one index of overall sleep health, testing the idea that the whole sleep profile might matter more for the brain than any individual component.

Cognitive function, meanwhile, was assessed with the Cambridge Neuropsychological Test Automated Battery, or CANTAB, a computerized assessment platform administered at each of the three time points. Rather than reporting a single global cognition score, the researchers computed composite z-scores for four distinct domains: short-term memory, long-term memory, executive function, and processing speed. This domain-specific approach matters because cognitive ageing is not uniform. Different neural systems decline at different rates and respond differently to lifestyle factors, and a global score can mask a real association in one domain by diluting it across others. Executive function, in particular, is known to be among the earliest and most consequential casualties of unhealthy ageing, underpinning the daily planning and self-regulation that keep older adults independent.

The statistical core of the study was a series of linear mixed-effects models, which are well suited to longitudinal data because they can handle repeated measurements within the same individuals while treating sleep characteristics as time-varying predictors. In practical terms, the models asked whether, when a participant’s sleep efficiency was higher than their own typical level, their executive function was also better than their own typical level. The models were adjusted for a careful set of potential confounders: age, sex, educational level, living situation, and total physical activity—the last of which is important because physical activity influences both sleep and cognition and could otherwise masquerade as a sleep effect. The team also tested sleep-by-time interactions to determine whether any association strengthened or weakened across the two-year follow-up.

The results were, in a word, selective. Sleep duration showed no significant association with any of the four cognitive domains. Subjective sleep quality, as measured by the Pittsburgh index, was likewise unrelated to cognition. Even the multidimensional sleep health score—the most sophisticated sleep measure in the analysis—failed to predict performance in any domain. Only sleep efficiency rose to significance, and only for executive function: higher efficiency was associated with better executive performance. The researchers ran sensitivity analyses using wake after sleep onset, essentially the inverse of sleep efficiency, and observed a comparable pattern, lending confidence that the finding was not an artifact of how the variable was defined. Crucially, the sleep-by-time interactions were not significant, meaning the association between sleep efficiency and executive function remained stable across all three measurement waves rather than emerging or fading over time.

Why would sleep continuity matter for executive function when sleep duration and subjective quality do not? The authors’ finding aligns with a broader literature suggesting that fragmented sleep may be more disruptive to prefrontal-dependent processes than shortened sleep. Executive functions are exquisitely sensitive to the quality of prior-night sleep, and sleep fragmentation is known to blunt the slow-wave and spindle activity that supports overnight neural restoration. It is also plausible that the association is bidirectional: emerging evidence, including studies cited in the paper, indicates that preclinical cognitive decline can itself disturb sleep, so reduced sleep efficiency might be an early signal of brain change rather than a cause of it. The null findings for duration and subjective quality echo recent meta-analytic work showing weak and inconsistent links between those measures and cognition in healthy older adults, and they caution against overinterpreting the popular narrative that sleeping longer automatically protects the ageing brain.

The study’s limitations are worth keeping in view. The sample of 233 adults, while well characterized, was relatively healthy and community-dwelling, mean age 68.3 years, and two years of follow-up may be too short to capture the slow accumulation of sleep-related risk for dementia. Accelerometry, for all its objectivity, estimates sleep from movement and cannot stage sleep or detect the micro-architecture that polysomnography reveals. And as the authors note, observational associations—however carefully adjusted—cannot establish causation. Still, the stability of the sleep efficiency–executive function link across repeated observations, in a design that combined objective and subjective measurement with domain-specific cognitive testing, makes this one of the more informative contributions to a debate that matters to millions of ageing adults.

For the public, the takeaway is refreshingly modest and actionable. Rather than fixating on hitting a magic number of hours, the evidence points toward protecting the continuity of sleep—minimizing the night-time awakenings that erode efficiency—as the sleep dimension most plausibly connected to the executive brain in later life. For researchers, the study is a call to move beyond global cognition scores and single sleep metrics toward multidimensional, longitudinal designs that can isolate which features of sleep, if any, genuinely shape how we think as we age. The full dataset’s GGIR processing code has been made publicly available, and the authors report no competing interests, with the work supported in part by the Research Foundation – Flanders and Australian National Health and Medical Research Council funding.

Subject of Research: Longitudinal associations between multidimensional sleep measures and domain-specific cognitive function in older adults

Article Title: Associations between multidimensional sleep measures and domain-specific cognitive function across repeated observations in adults aged 55 years and older

Article References: Marent, P.-J., Duncan, M. J., Cardon, G., Albouy, G., & van Uffelen, J. (2026). Associations between multidimensional sleep measures and domain-specific cognitive function across repeated observations in adults aged 55 years and older. GeroScience. https://doi.org/10.1007/s11357-026-02518-y

Image Credits: AI Generated

DOI: 10.1007/s11357-026-02518-y

Keywords: sleep efficiency, executive function, cognitive ageing, actigraphy, sleep health, older adults, CANTAB, sleep duration, sleep quality, longitudinal study, GeroScience, accelerometry

The study, conducted as part of the PASOCA project (Physical Activity and Sleep for Optimal Cognitive Ageing), followed 233 cognitively healthy, community-dwelling adults aged 55 and above in Flanders, Belgium, across three annual assessment points over two years. Participants, whose average age at baseline was 68.3 years and just over half of whom were women, wore a wrist-worn tri-axial accelerometer (an ActiGraph wGT3X-BT) for seven consecutive days at each time point. The raw accelerometer data were processed with the open-source GGIR software package, which autocalibrated the device signals, detected non-wear periods, identified sustained inactivity bouts to estimate sleep, and classified time into sedentary behaviour, light physical activity and moderate-to-vigorous physical activity using established Hildebrand cut-points based on the ENMO metric. This device-based approach avoided the recall biases that plague self-reported questionnaires and captured all three behaviours continuously across the full day.

Cognitive function, meanwhile, was assessed with the Cambridge Neuropsychological Test Automated Battery (CANTAB), a validated computerised testing platform administered on an iPad. Six tasks—including Delayed Match to Sample, Verbal Recognition Memory, Paired Associates Learning, Spatial Working Memory, One Touch Stockings of Cambridge and the Multitasking Test—yielded standardised composite scores for four distinct domains: short-term memory, long-term memory, executive function and processing speed. The researchers anchored their domain definitions in the Cattell-Horn-Carroll-Miyake cognitive framework, and all z-scores were computed relative to baseline performance, allowing consistent tracking of change over time.

What makes this study methodologically distinctive is its compositional data analysis (CoDA) framework. Because there are only 24 hours in a day, time spent in physical activity, sedentary behaviour and sleep is inherently co-dependent: more of one necessarily means less of another. Traditional regression approaches that treat these behaviours as independent variables suffer from multicollinearity and can produce misleading results. The CoDA framework circumvents this by normalising the behaviours to a 24-hour total and transforming them into isometric log-ratio (ILR) coordinates through a sequential binary partitioning strategy—first contrasting sleep with waking behaviours, then sedentary behaviour against physical activity, and finally light activity against moderate-to-vigorous activity. These ILR coordinates were then entered as time-varying predictors in linear mixed-effects models with random intercepts, capturing the nested structure of repeated measurements within individuals.

The modelling strategy was deliberately conservative. Missing data from participant attrition were addressed through multiple imputation by fully conditional specification, generating 20 imputed datasets whose estimates were pooled using Rubin’s rule. Covariates were grouped into predefined blocks—sociodemographic factors (age, sex, education, living arrangement), health-related variables (body mass index, hearing impairment, number of prescribed medications) and behavioural indicators (smoking, alcohol use)—and hierarchical models were compared with the D1 multivariate Wald test, allowing each cognitive outcome to retain only the covariates that genuinely improved model fit. This guarded against overadjustment bias while accounting for the well-documented influences of education, social isolation and health status on late-life cognition.

The headline finding is striking in its specificity: time-use composition was significantly associated with executive function (p = 0.005) but showed no significant relationship with short-term memory, long-term memory or processing speed. Crucially, the interaction between time-use composition and time was not statistically significant, meaning the association between daily behaviours and executive function remained stable across the entire two-year follow-up. This is the first study to establish such stability using repeated device-based measurements, addressing a major gap left by prior cross-sectional work that could only snapshot a single moment in the ageing process.

Exploratory post-hoc compositional isotemporal substitution analyses then probed which behaviour was driving the executive function association. These simulations hypothetically reallocated time in five-minute increments, up to 30 minutes, between pairs of behaviours while holding all else constant. The results pointed unambiguously to moderate-to-vigorous physical activity (MVPA) as the primary driver. Shifting 30 minutes from light activity to MVPA was associated with estimated executive function gains of 0.11 standard deviations at baseline and 0.17 at the first follow-up, with similar directional patterns at the second. Reallocating 30 minutes from sleep to MVPA produced smaller but still significant gains at baseline and follow-up 1, while shifts from sedentary behaviour to MVPA showed a similar but weaker pattern. Conversely, moving time away from MVPA—in any direction—was consistently associated with lower executive function, including a significant drop of 0.19 standard deviations when 30 minutes of MVPA was replaced with light activity at follow-up 1.

One unexpected nuance deserves attention: hypothetically shifting time from light activity to sedentary behaviour was also associated with modestly higher executive function scores at baseline and follow-up 1. The authors caution against overinterpreting this, but suggest that the cognitive context of sedentary activities—reading, social interaction, computer-based tasks—may partially explain it, echoing prior evidence that cognitively engaging sedentary behaviours differ from passive screen time. It reinforces a growing argument in the field that the quality and context of behaviours matter, not just their raw durations. At the same time, the researchers stress that nothing here diminishes sleep’s established importance for brain health; because MVPA occupied only about 4–5% of the day in this cohort, even small absolute reallocations represent a large proportional increase in vigorous activity, and trimming light activity or sitting time rather than sleep may be the more realistic route for most older adults.

Why would vigorous movement, in particular, benefit the brain’s executive machinery? The study’s discussion draws on established neurobiological mechanisms from the physical activity literature. Higher-intensity exercise stimulates the release of brain-derived neurotrophic factor (BDNF), insulin-like growth factor 1 (IGF-1) and vascular endothelial growth factor (VEGF), molecules that support angiogenesis and neurogenesis. It also increases lactate production, which can serve as an auxiliary energy source for the brain, while reducing pro-inflammatory cytokines such as tumour necrosis factor-alpha and oxidative stress. Structural brain changes have been documented in response to aerobic training as well—most famously, a 12-month moderate-intensity aerobic exercise programme produced significant hippocampal volume increases in adults aged 55 to 80. The present study did not measure these biomarkers directly, so the mechanistic chain remains inferential, but the behavioural-to-cognitive link it documents is consistent with this biological framework.

The authors are candid about their study’s limitations. The two-year follow-up may be too short to capture meaningful cognitive decline in a sample of healthy, highly educated volunteers—a classic healthy-volunteer bias that limits generalisability. Cognitive scores improved over time in short-term memory and executive function, a pattern most plausibly attributable to practice effects from repeated testing, which ranged from 0.01 to 0.20 standard deviations and fell within the ‘optimal’ range documented in longitudinal cognitive research. The GGIR algorithm classifies inactivity but cannot distinguish standing from sitting, and the study did not capture behavioural context or sleep quality. Still, the longitudinal design, device-based measurement across all 24 hours, compositional statistical framework and multi-domain cognitive battery represent a substantial methodological advance. The message for ageing populations is actionable: protecting or increasing moderate-to-vigorous physical activity—ideally by trading in sedentary or light-activity time rather than sleep—may help safeguard the executive functions that underpin independence, planning and quality of life in later years. Future interventional studies must now test whether deliberately restructuring the 24-hour day can produce those cognitive benefits in practice.

Subject of Research: Longitudinal associations between 24-hour movement behaviours and cognitive function in cognitively healthy adults aged 55 and above

Article Title: Longitudinal associations between 24-hour movement behaviours and cognitive function in adults aged 55 and above

Article References: Marent, P.-J., Cardon, G., Albouy, G., & van Uffelen, J. (2026). Longitudinal associations between 24-hour movement behaviours and cognitive function in adults aged 55 and above. Journal of Activity, Sedentary and Sleep Behaviors, 5(1), Article 9. https://doi.org/10.1186/s44167-026-00100-7

Image Credits: AI Generated

DOI: 10.1186/s44167-026-00100-7

Keywords: physical activity, sedentary behaviour, sleep, cognitive ageing, executive function, moderate-to-vigorous physical activity, compositional data analysis, accelerometry, CANTAB, memory, processing speed, healthy ageing