Jesse L Parker1, Sarah L Appleton1,2, Yohannes Adama Melaku1, Angela L D'Rozario3,4, Gary A Wittert2,5, Sean A Martin2,5, Barbara Toson6, Peter G Catcheside1, Bastien Lechat1, Alison J Teare1, Robert J Adams1,2,7, Andrew Vakulin1,3. 1. Flinders Health and Medical Research Institute, Adelaide Institute for Sleep Health, Flinders University, Adelaide, South Australia, Australia. 2. South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia. 3. CIRUS, Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, University of Sydney, Sydney, New South Wales, Australia. 4. Faculty of Science, School of Psychology, The University of Sydney, Sydney, New South Wales, Australia. 5. Freemasons Centre for Male Health and Wellbeing, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia. 6. College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia. 7. Respiratory and Sleep Services, Southern Adelaide Local Health Network, Bedford Park, Adelaide, South Australia, Australia.
Abstract
STUDY OBJECTIVES: Sleep microarchitecture parameters determined by quantitative power spectral analysis of electroencephalograms have been proposed as potential brain-specific markers of cognitive dysfunction. However, data from community samples remain limited. This study examined cross-sectional associations between sleep microarchitecture and cognitive dysfunction in community-dwelling men. METHODS: Florey Adelaide Male Ageing Study participants (n = 477) underwent home-based polysomnography (2010-2011). All-night electroencephalogram recordings were processed using quantitative power spectral analysis following artifact exclusion. Cognitive testing (2007-2010) included the inspection time task, Trail-Making Tests A and B, and Fuld object memory evaluation. Complete case cognition, polysomnography, and covariate data were available in 366 men. Multivariable linear regression models controlling for demographic, biomedical, and behavioral confounders determined cross-sectional associations between sleep microarchitecture and cognitive dysfunction overall and by age-stratified subgroups. RESULTS: In the overall sample, worse Trail-Making Test A performance was associated with higher rapid eye movement (REM) theta and alpha and non-REM theta but lower delta power (all P < .05). In men ≥ 65 years, worse Trail-Making Test A performance was associated with lower non-REM delta but higher non-REM and REM theta and alpha power (all P < .05). Furthermore, in men ≥ 65 years, worse Trail-Making Test B performance was associated with lower REM delta but higher theta and alpha power (all P < .05). CONCLUSIONS: Sleep microarchitecture parameters may represent important brain-specific markers of cognitive dysfunction, particularly in older community-dwelling men. Therefore, this study extends the emerging community-based cohort literature on a potentially important link between sleep microarchitecture and cognitive dysfunction. The utility of sleep microarchitecture for predicting prospective cognitive dysfunction and decline warrants further investigation. CITATION: Parker JL, Appleton SL, Melaku YA, et al. The association between sleep microarchitecture and cognitive function in middle-aged and older men: a community-based cohort study. J Clin Sleep Med. 2022;18(6):1593-1608.
STUDY OBJECTIVES: Sleep microarchitecture parameters determined by quantitative power spectral analysis of electroencephalograms have been proposed as potential brain-specific markers of cognitive dysfunction. However, data from community samples remain limited. This study examined cross-sectional associations between sleep microarchitecture and cognitive dysfunction in community-dwelling men. METHODS: Florey Adelaide Male Ageing Study participants (n = 477) underwent home-based polysomnography (2010-2011). All-night electroencephalogram recordings were processed using quantitative power spectral analysis following artifact exclusion. Cognitive testing (2007-2010) included the inspection time task, Trail-Making Tests A and B, and Fuld object memory evaluation. Complete case cognition, polysomnography, and covariate data were available in 366 men. Multivariable linear regression models controlling for demographic, biomedical, and behavioral confounders determined cross-sectional associations between sleep microarchitecture and cognitive dysfunction overall and by age-stratified subgroups. RESULTS: In the overall sample, worse Trail-Making Test A performance was associated with higher rapid eye movement (REM) theta and alpha and non-REM theta but lower delta power (all P < .05). In men ≥ 65 years, worse Trail-Making Test A performance was associated with lower non-REM delta but higher non-REM and REM theta and alpha power (all P < .05). Furthermore, in men ≥ 65 years, worse Trail-Making Test B performance was associated with lower REM delta but higher theta and alpha power (all P < .05). CONCLUSIONS: Sleep microarchitecture parameters may represent important brain-specific markers of cognitive dysfunction, particularly in older community-dwelling men. Therefore, this study extends the emerging community-based cohort literature on a potentially important link between sleep microarchitecture and cognitive dysfunction. The utility of sleep microarchitecture for predicting prospective cognitive dysfunction and decline warrants further investigation. CITATION: Parker JL, Appleton SL, Melaku YA, et al. The association between sleep microarchitecture and cognitive function in middle-aged and older men: a community-based cohort study. J Clin Sleep Med. 2022;18(6):1593-1608.
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