Longitudinal Association of Delta Activity at Sleep Onset with Cognitive and Affective Function in Community-Dwelling Older Adults

ICGP JUNIOR INVESTIGATOR AWARDEE

Longitudinal association of delta activity at sleep onset with cognitive and affective function in community-dwelling older adults

Makoto Kawai1, Sherry A. Beaudreau1,2,3, Christine E. Gould1,4, Nathan C. Hantke1,2, Isabelle Cotto1, Josh T. Jordan1,5, Rayna B. Hirst6 and Ruth O’Hara1,2,3

1Department of Psychiatry and Behavioral Sciences, Stanford University, School of Medicine, Stanford, CA, USA 2Sierra Paciﬁc Mental Illness Research Education and Clinical Centers, VA Palo Alto Health Care System, Palo Alto, CA, USA 3School of Psychology, University of Queensland, Brisbane, Australia 4Geriatric Research Education and Clinical Center, VA Palo Alto Health Care System, Palo Alto, CA, USA 5California School of Professional Psychology at Alliant, International University, San Francisco, CA, USA 6Palo Alto University, Palo Alto, CA, USA Correspondence to: M. Kawai, MD, E-mail: [email protected]

Objective: This investigation sought to determine whether delta activity at sleep onset (DASO) in the sleep electroencephalography of older adults represents normal variation or is associated with clinical pathology. To this end, we examined its longitudinal associations with cognitive and affective function in older adults without dementia. Methods: Participants were 153 community-dwelling older adults without dementia. We evaluated polysomnography (PSG), cognitive performance, and affective function at four time points: baseline, 12, 24, and 36 months. All participants completed PSG and measures of global cognition, delayed verbal memory, information processing speed, attention, inhibition, verbal naming, visuospatial ability, and measures of anxiety and depression. DASO was defined as sequences of rhythmic anterior delta activity on PSG in the transition from awake to sleep during the baseline assessment (Figure 1). Results: At the baseline, 83 women and 70 men, mean age 71.3 ± 0.6 years participated and 19.6% of participants exhibited DASO. Age, years of education, gender, and body mass index did not differ according to DASO status. Linear mixed modeling showed that the presence of DASO was actually associated with lower levels of anxiety and depression. Further, participants with DASO, versus those without DASO, exhibited a trend towards better cognitive performance over time, although none of these associations reached statistical significance. Conclusions: Whereas DASO was associated with better affective function, no significant association was found between DASO and cognitive change over time. These longitudinal findings support the view that the presence of DASO in healthy older adults represents normal variation rather than pathological aging. Copyright # 2016 John Wiley & Sons, Ltd.

Key words: delta activity at sleep onset; cognition; affective function History: Received 30 December 2015; Accepted 15 June 2016; Published online 23 August 2016 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/gps.4554

Introduction focal lesion (Accolla et al., 2011; Fariello et al., 1982; Watemberg et al., 2002). One complication in the liter- Frontal intermittent rhythmic delta activity (FIRDA), ature is that in the transition to sleep in older adults, now called rhythmic delta activity in newer terminol- rhythmic slow wave electroencephalography (EEG) ogy (Hirsch et al., 2013), in adults is usually considered activity may in fact reﬂect the intrusion of sleep-related an abnormal ﬁnding indicative of encephalopathy or a elements of the EEG into the waking state. As such, this

Copyright # 2016 John Wiley & Sons, Ltd. Int J Geriatr Psychiatry 2016; 31: 1124–1135 A longitudinal examination in community-dwelling older adults 1125

onset in the context of daytime napping. Daytime napping may vary substantially from patient to patient, not occurring at all in some, and this may account for the mixed findings observed. Further, these studies did not investigate the relationship of DASO to more in-depth cognitive testing. As many as 20% of healthy, community-dwelling older have cognitive impairments indicative of mild cognitive impairment (MCI), placing them at increased risk for the development of dementia. In the absence of more in-depth cognitive testing, it is unclear if the 16% presenting with DASO in the Katz and Horowitz Figure 1 Delta activity at sleep onset (DASO) (in circle) in transition investigation are individuals with poorer cognitive from awake to stage N1 sleep C3-A2, C4-A1 channels show delta range functioning, who are at risk for developing dementia. high-amplitude rhythmic activity in the middle of epoch. Paper speed: There is also substantial selection bias of subjects in- 10 s per page. EEG filter setting: High-frequency filter: 30 Hz. Low- volved in the studies utilizing hospital EEG laborato- frequency filter: 0.3 Hz. Notch filter: Off. ries. Thus, It is inevitable for these studies to include higher rate of encephalopathy or dementia. However, type of slow wave EEG activity may reflect more the in- we do not believe that those studies represent stability of wake sleep control that occurs with typical community-dwelling older adults. Now, we address aging rather than a pathological process per se (Bliwise, this issue by examining whether DASO that is 1993; Landolt et al., 1996). captured by nocturnal polysomnography (PSG) in We recently suggested that a distinction be made healthy, community-dwelling older adults is asso- between delta activity at sleep onset (DASO) and slow ciated with trajectories of poorer cognitive and affec- wave activity that does not occur in the context of tive function measures. Indeed, there has been a sleep onset (e.g., FIRDA) (Kawai et al., 2016). paucity of investigations focusing on these issues in Although not termed DASO, previous reports consis- recent years. tently show a higher prevalence of this type of activity There have been efforts to predict decline in cogni- in older adults (Katz and Horowitz, 1983; Shiohama tive function from EEG. Several reports showed et al., 1993; Stam, 2011; Zurek et al., 1985), with some temporal theta and delta activity to be correlated suggesting that it may represent normal variation with cognitive decline in patients with MCI or among older adults because it occurs within a normal Alzheimer’s disease (Jelic et al.,2000;Rossiniet al., EEG background (Katz and Horowitz, 1983). DASO is 2006; Sloan and Fenton, 1993). Increased theta characterized with the sequences of rhythmic, bilateral power in resting state quantitative EEG is correlated anterior slow activity in the delta range (mostly with decline in cognition in normal older and 1.5–2.5/s), duration varies between 2 and 10 s, and Alzheimer’s disease patients (Coben et al., 1985; the voltage output may be considerably high (Katz Prichep et al., 2006). On the other hand, in a and Horowitz, 1983; Stam, 2011). Gibbs and Gibbs cross-sectional study utilizing magnetoencephalogra- originally termed this pattern of EEG during sleep phy, Vlahou et al., reported slow frequency (0.5– onset as “anterior bradyrhythmia” (Gibbs and Gibbs, 6.5 Hz) activity in resting-state to be correlated with 1964; Stam, 2011). better executive functioning among healthy older in- Despite the view that DASO represents normal dividuals (Vlahou et al., 2014). variation, the clinical significance of DASO is still Using a cross-sectional design, our group recently uncertain. Some reports suggest that DASO may be found no significant associations between DASO and associated with a higher prevalence of altered mental several measures of cognition that included memory status based on accumulated EEG data (Shiohama and executive function (Kawai et al., 2016). We et al., 1993; Stam, 2011; Zurek et al., 1985). Katz and concluded that DASO most likely represents normal Horowitz, on the other hand, found DASO in 16% variation. However, the question still remains as to of healthy older adults, suggesting that it may repre- whether DASO captured by nocturnal PSG in sent a normal variant in this age range (Katz and healthy older individuals is in fact a harbinger of Horowitz, 1983). The difficulty is that the majority long-term decline in cognition, not evident upon of these studies were reported on EEGs, which were cross-sectional analyses. A longitudinal investigation not performed nocturnally, but which captured sleep is required to fully determine whether DASO

Copyright # 2016 John Wiley & Sons, Ltd. Int J Geriatr Psychiatry 2016; 31: 1124–1135 1126 M. Kawai et al. represents normal variation or is associated with cognitive battery indicative of dementia, any serious cognitive and affective dysfunction over time. To medical illness, or any Axis I disorder diagnosis, date, no longitudinal study has examined the ability currently or within the past 2 years based on the of DASO to predict cognitive decline or increased SCID-IV-TR. Participants were also excluded if they impairments in affective function over time. The were currently taking psychotropic medication, goal of our current study was to examine the short-acting anxiolytics, sedative hypnotics, medica- relationship of DASO at baseline to the trajectory tions with signiﬁcant cholinergic or anticholinergic of cognition and affect in a non-patient sample of side effects, or any FDA-approved medications for community-dwelling older adults. We hypothesized dementia. thatDASOwouldbeassociatedwithdeclineincog- nition and mood over time. Cognitive battery

Methods Participants completed an extensive cognitive battery, with measures sensitive to MCI in older adults A longitudinal study was performed on 153 (Petersen, 2004). For analytic purposes, to ensure that community-dwelling older adults who were enrolled the measures are independent and reduce those signif- in an investigation of sleep and cognitive function icantly correlated with each other, we conducted a recruited through advertisements and local senior principal component analysis, which identified four centers from 2005 to 2010 (National Institute of independent cognitive domains and associated assess- Health Grants MH 070886, AG 18784, and ments. We performed data reduction in cognitive AG17824). We previously published a cross-sectional domains utilizing principal component analysis in the study utilizing baseline data from the same cohort similar way employed in previous reports (Chapman (Kawai et al., 2016). In our study, 153 participants et al., 2010; Levin et al., 2013). The cognitive domains were evaluated at baseline. We evaluated PSG, cogni- examined included the following: (i) delayed verbal tive performance, and affective function at four time recall on Rey Auditory Verbal Learning Test 20-minute points: baseline, 12, 24, and 36 months. Ninety-five delay trial (RAVLT) (Lezak et al., 2004); (ii) informa- participants completed at least three assessment points tion processing speed and attention on the Stroop (including baseline evaluation). However, only 81 Color and Word Test (STRCW) (Golden et al., participants completed the 36-month evaluation. This 1978); (iii) verbal naming on the Boston Naming Test formed the rationale, in part, for the use of mixed (Kaplan et al., 1978); and (iv) visuospatial ability on the models which allow us to impute missing data. Four Judgment of Line Orientation (Benton et al., 1983). At participants dropped out due to death (not related to baseline, we asked all participants if they were color our study), 18 participants dropped out due to newly blind in order for them to perform the STRCW. One diagnosed sleep disorders (insomnia, OSA and RLS), participant was identified as a color blind and did not 10 participants developed medical illness, and two complete the STRCW, but all their remaining data participant developed dementia. The remaining sim- were included in the analysis. Prior work from our ply did not want to complete a fourth assessment, and other groups has consistently found lower perfor- due to the time involved. We were only unable to con- mance on measures of delayed recall to be associated tact two subjects. All participants provided informed with increased age (Blachstein and Vakil, 2016; Kawai consent in accordance with Stanford University IRB et al., 2016). Deficits in the other three cognitive do- regulations. An initial evaluation included demo- mains are common in older adults and are associated graphics, self-reported current and past medical status, with an increased risk of cognitive decline and onset the mini-mental state examination (MMSE) to screen of dementia (Drag and Bieliauskas, 2010). The MMSE for dementia (Folstein et al., 1975), and Structured was included as a brief mental status examination to Clinical Interview for DSM-IV-TR (SCID-IV-TR) quantify global cognitive functioning. The selected (First et al., 2002) to screen for Axis I psychiatric measures are valid and widely used with older popula- disorders. Participants had to meet the following tions (Benton et al., 1983; Golden, 1978; Kaplan et al., inclusion criteria: aged 50 years or older, able to give 1978; Lezak et al., 2004). Alternate forms were informed consent, and sufficient visual and auditory employed for the RAVLT as they were available for acuity for the cognitive testing. Individuals were these tests. Presentation of the alternate forms was excluded if they had a MMSE < 26, a diagnosis of counterbalanced across subjects as well as follow-up possible or probable dementia or a profile on the assessment time points.

Copyright # 2016 John Wiley & Sons, Ltd. Int J Geriatr Psychiatry 2016; 31: 1124–1135 A longitudinal examination in community-dwelling older adults 1127

Affective battery A board-certified clinical neurophysiologist (MK) performed additional visual analysis of EEG parameters In addition to the cognitive battery, participants to identify DASO. The neurophysiologist was blind to completed several self-report mood questionnaires to any clinical parameters. DASO was defined as follows: measure affect. The Geriatric Depression Scale (GDS) (1) Sequences of rhythmic, bilateral anterior slow (Yesavage et al., 1982) was employed to evaluate activity in the delta range (1–2.5 Hz) depressive symptoms. For evaluation for anxiety, the (2) Duration between 2 and 10 s with amplitude more Spielberger Anxiety/Trait (STAI) (Spielberger et al., than 50 μV 1983) and Beck Anxiety Inventory (Beck et al., 1988) (3) Occur within otherwise normal background were administered. activity in the transition period from awake to sleep (4) High-amplitude delta range activity in slow-wave sleep is excluded Polysomnography (PSG) and sleep questionnaires (5) Sleep transitions were defined as 30-s epochs scored either as (i) stage N1; (ii) stage W Unattended, overnight PSG (Safiro Ambulatory PSG intermixed with a short period of stage N1 sleep, System; Compumedics, Charlotte, NC) was performed with the latter characterized by slow eye on all participants. Participants went to bed and arose movement, disappearance of posterior dominant according to their normal schedule. The PSG was rhythm, and vertex sharp wave transients or applied as close as possible to the time they indicated EEG activity in the range of 4–7 Hz with slowing that they typically went to bed. However, in all cases of background frequencies by ≥ 1 Hz from those there was a period of wake recording both before the of stage W; or (iii) stage W adjacent to epochs of participant went to bed and after they awakened. The any sleep stages. standard recording montage included scalp electroencephalography electrodes (C3, C4, O1, O2, M1, and Even though DASO can occur multiple times M2) applied at positions according to the International during overnight PSG, data were categorized as a 10–20 System of Electrode Placement, chin and bila- binary parameter of “present” [DASO (+)] if DASO teral anterior tibialis electromyography, electro- occurred at least once and “absent” [DASO (À)] if oculography, electrocardiography, nasal pressure no DASO was found in the overnight PSG record. transducer and oral airflow (thermistor), abdominal and thoracic excursion (piezoelectric band), finger pulse oximetry, snoring sounds (microphone), and Statistical analysis body position. All data were scored for sleep staging and respiratory events by a registered PSG technolo- We employed linear mixed effects modeling (Laird gist and were reviewed by a diplomate of the Amer- and Ware, 1982; Meredith and Tisak, 1990; ican Board of Sleep Medicine following the Raudenbush and Bryk, 2002; Singer and Willett, American Academy of Sleep Medicine scoring man- 2003) to model trajectories of cognitive and affective ual (Berry et al., 2014). For slow wave sleep, stage function measurements, as well as PSG parameters 3 and stage 4 were distinguished (Rechtschaffen across the four time points. The linear mixed model and Kales, 1968). An apnea is defined as a “cessation enabled us to fully benefit from repeatedly measured or near complete cessation (>90% reduction) of air- parameters as it accommodates missing observations. flow for a minimum of 10 s,” ahypopneais“a In this procedure, all available cases, including the greater than 30% reduction of amplitude in airflow ones with missing measurements, are included in the as compared with baseline with a greater than 3% analyses. Missing data points were treated as missing oxygen desaturation,” and apnea hypopnea index at random on observed information using maximum represents “the number of apneas and hypopneas di- likelihood estimation (LIttle and Rubin, 2002). The in- vided by the number of hours of sleep” (Berry et al., clusion of every subject who completed at least one as- 2014). Sleep-related questionnaires, including the sessment allowed for conservation of power. We first Epworth Sleepiness Scale (Johns, 1991), the Pitts- estimated trajectories of change to determine whether burgh Sleep Quality Index (Buysse et al.,1989),the DASO (+) and (À) groups were associated with change Functional Outcomes of Sleep Questionnaire in cognition and/or affect over time. We finally (Weaver et al., 1997), and the Morningness- examined a model in which we included age at base- Eveningness Questionnaire (Horne and Ostberg, line, gender, and years of education as covariates and 1976) were also administered. included both DASO and a time × DASO interaction

Copyright # 2016 John Wiley & Sons, Ltd. Int J Geriatr Psychiatry 2016; 31: 1124–1135 1128 M. Kawai et al. to determine whether trajectories of change differed period of observation. When we tested a model between DASO (+) and (À) groups. controlling for age, gender, and years of education as We analyzed Intraclass Correlation Coefficient to ex- fixed predictors, the DASO (+) group still exhibited amine the variability in DASO status from year to year. statistically significantly lower scores on the STAI, We also performed re-analysis with liner mixed model- but this was not the case for the GDS. It is also noted ing among 66 participants who completed all four points. that DASO status was highly consistent over time, with In exploratory analyses, we examined whether any an Intraclass Correlation Coefficient of 0.909 (95% CI other PSG parameters or the quantitative measures 0.859, 0.945), indicating very little variability in DASO of DASO (number of occurrences or duration) status from year to year. Thus, DASO status measured predicted cognitive measures. in each observation point was not involved as a time- IBM SPSS Statistics for Macintosh, Version 23.0, varying predictor in our model. Armonk, NY: IBM Corp., was used to perform all We also performed re-analysis with liner mixed statistical analyses. For these analyses, we applied modeling among 66 participants who completed all four alpha level set at 0.05. points. However, none of the parameter of cognitive or affective function variables reached statistical significance with time or baseline DASO status. Results Although current and recent Axis I disorders were excluded in the process of an in-person clinical Participants were 83 women and 70 men ranging from interview and were never included, 22 participants 52 to 90 years old, with a mean age of 71.3 ± (standard reported history of Axis I disorders based on our error: SE) 0.6 years. Mean and SE of years of education self-reported questionnaire. With binary measures of were 16.5 and 0.2 years. DASO was present in 30 history of Axis I disorders, we performed re-analysis. participants (19.6%) at baseline. Age, years of educa- We found no significant association on trajectory of tion, gender, and body mass index (BMI) were not any cognitive or affective measures. In the analyses of different in the DASO (+) and DASO (À) groups as affective measures, higher GDS score (p < 0.01) and determined by Mann–Whitney U-test and chi-squared higher STAI (p < 0.02) were associated with the test (Table 1). Sixty percent of DASO (+) and 52% of presence of history of Axis I disorders. Sleep parame- DASO (À) completed 36 months follow-up. We ters, including DASO status, were not associated with performed an analysis and found no significant diffe- history of Axis I disorders. The associations of DASO rence in drop out rate between the two groups. to cognitive and affective measures did not change The linear mixed model found no significant diffe- when covaried with history of Axis I disorders. rence between in DASO (+) and (À) groups in the In exploratory analyses, we examined whether any trajectory of cognitive decline on memory (RAVLT), other PSG parameters predicted cognitive decline executive functioning (STRCW), visuospatial ability (Table 4). DASO (+) group exhibited higher rates of (Judgment of Line Orientation), and naming (Boston Naming Test) (Table 2 and Figure 2). As it is shown in Table 1 Comparison of demographics between DASO (+) and (À) Figure 2, MMSE total score declined over time; how- groups with Mann–Whitney U-test for continuous variables and chi- ever, DASO was not significantly associated with the squared for gender trajectory of MMSE scores. p-value by In the analyses of affective measures, lower self- Mann–Whitney reported depressive symptoms (GDS) (p < 0.05) and U-test for age, lower trait anxiety (STAI) (p < 0.03) were associated years of education, and BMI, with DASO (+) status at baseline (Table 3 and chi-squared test Figure 3). Effect sizes and p-values for the differences DASO (+) DASO (À) for gender between DASO (+) and (À) groups in GDS, Beck Anxiety Inventory, and STAI were À0.33 (95% CI N 30 123 À À À À Age (years) 71.4 ± 1.4 71.3 ± 0.7 0.739 0.57, 0.09), p = 0.04; 0.19 (95% CI 0.42, Years of 16.3 ± 0.4 16.6 ± 0.3 0.608 À0.05), p = 0.17; and À0.40 (95% CI À0.64, À0.16), Education p = 0.02, respectively. None of these variables are Gender 08:10:00 PM 63:60 0.293 fi (Women : Men) statistically signi cant after Bonferroni correction for BMI 26.3 ± 0.7 27.1 ± 0.5 0.672 the adjustment of multiple testing. DASO did not show any effect on the trajectory of DASO: Delta activity at sleep onset. affective function measurements over the 36-month BMI: Body mass index.

Copyright # 2016 John Wiley & Sons, Ltd. Int J Geriatr Psychiatry 2016; 31: 1124–1135 A longitudinal examination in community-dwelling older adults 1129

stage 3 and 4 sleep than the DASO (À) group (p = 0.01 and 0.05 with effect sizes of 0.47 (95% CI 0.22, 0.73)

* 0.12 and 0.42 (95% CI 0.17, 0.68), respectively). No rela- 0.03

modeling tionship with DASO was observed for any other sleep

-value by linear mixed parameter. p In the DASO (+) group, DASO occurred in the est. ) at baseline. Repeated .0.05 0.06 0.96 0.84 ﬁ

À rst sleep onset in all 30 DASO (+) subjects. DASO À

r( (+) group and DASO (À) group did not differ on 0.01, 0.46 0.190.02, 0.440.15, 0.32 0.04* 0.12 0.72 0.94 0.06 0.97 0.23 0.96 0.46, 0.010.36, 0.11 0.15 0.31 0.98 0.50 0.53, À À À À À À their scores on any sleep-related questionnaires, including the Epworth Sleepiness Scale, Pittsburgh 0.22 0.12 0.29 À À À Sleep Quality Index, Functional Outcomes of Sleep Effect size (d) 95% CI D T D*T Questionnaire, and Morningness-Eveningness Ques- n tionnaire (Table 5). ) À Although we used a binary measure of DASO, in exploratory analysis, we examined the quantitative DASO (

Total measures of DASO (number of occurrences or dura- n tion). Using our continuous measure of DASO, we ﬁ (all points of observation) found no signi cant association with any of our

DASO (+) cognitive or affective measures. We included all DASO

n (+) participants (n = 30 at baseline). However, it is À

) important to note that DASO ( ) subjects were À ﬁ

nish 200 items. Lower scores mean better performance on these measures. excluded from this analysis by de nition as no subject ﬁ

DASO ( in this group had any occurrences of DASO. n

Discussion DASO (+) dence interval; STRW, Stroop Word; STRC, Stroop Color; STRCW, Stroop Color and Word; ﬁ

n This study is the ﬁrst to examine the longitudinal

) effect of DASO based on nocturnal PSG on cognitive À and affective functions. As we previously reported DASO ( utilizing the same cohort, a notable percentage of

n participants in our study exhibited DASO (19.6%) at baseline (Kawai et al., 2016), similar to that observed in a daytime EEG study of community-dwelling older DASO (+) adults (16%) (Katz and Horowitz, 1983). With , number of subjects; CI, con n

N respect to our primary hypothesis, we found no )

À evidence of worsening cognitive or affective performance over time being associated with the DASO. DASO ( Indeed, the presence of DASO was signiﬁcantly asso- n ciated with lower levels of anxiety, but this association did not pass rigorous adjustment for multiple testing,

DASO (+) using Bonferroni correction, and needs to be tested in the future study. Although there was no signiﬁcant n association, overall trend towards better performance )

À in all cognitive measurements supports the view that the presence of DASO in healthy older adults repre- DASO ( sents normal variation rather than pathological aging. n Baseline 12 months 24 monthsAnother 36 months important ﬁnding of our study was that the presence of DASO was highly stable over time.

DASO (+) The lack of association of DASO with increasing Longitudinal data for all cognitive parameters analyzed with linear mixed modeling

0.05. cognitive or affective impairments over time, com-

< bined with the stability of DASO itself across the full p MMSERAVLT 29.3JLO ± 0.2BNT 8.7 30 ± 0.5 30 25.6 28.8 ± ± 0.7 0.1 56.6 ± 0.9 30 123 7.5 ± 30 0.4 24.8 29.4 ± ± 123 0.4 0.2 56.2 ± 0.4 121 18 8.7 121 ± 0.9 26.5 28.7 ± ± 0.7 0.2 18 18 57 84 ± 0.8 7.5 25.2 ± 18 28.4 ± 0.4 ± 0.4 0.3 83 84 56.3 19 ± 0.6 26.3 84 28.2 ± 8.1 ± 0.7 ± 0.4 0.9 19 56.6 75 ± 19 1.5 24.4 19 28.6 ± ± 0.6 0.4 7.3 ± 0.5 73 56.8 18 ± 0.8 74 24.4 74 28.2 ± ± 1 0.3 8.5 ± 56.9 1.1 64 ± 1.3 17 18 18 24.6 29 ± ± 0.5 0.1 56.1 7.8 ± ± 1 0.5 63 85 63 25.7 64 28.5 ± ± 0.4 0.1 8.5 84 56.8 ± 346 ± 0.4 0.6 85 24.8 85 ± 0.2 341 56.3 0.22 ± 7.5 0.3 ± 0.2 343 343 0.21 0.08 0.25 0.01, 0.49 0.38 0.38 0.66 STRCSTRCW 141.2 74.1 ± ± 7.5 2.4 29 29 147.5 ± 5.8 79.6 ± 1.9 121 121 128.4 ± 9.5 72.5 ± 17 3.1 138.1 18 ± 3.5 82 79 ± 130.3 3.1 ± 7.7 83 18 135.2 71.9 ± ± 3.6 3.1 72 18 133.6 ± 9.4 82 ± 18 5.3 134.2 74 ± 4.1 62 74.1 ± 3.7 134.5 ± 4.2 18 82 140.1 76 ± ± 2.5 2 337 62 73.3 ± 1.5 83 79.3 ± 1.6 340 STRW 48.1 ± 1.2 29 53.4 ± 1.1 121 50.2 ± 2 18 53.3 ± 1.4 83 50.3 ± 2 18 53.8 ± 1.9 74 50.3 ± 2 18 51.3 ± 1.3 63 49.5 ± 0.8 83 53.1 ± 0.7 341 cognitive parameters were analyzed as dependent variables. Scores on MMSE, RAVLT, JLO,Scores and on BNT Stroop represent Color, mean Word,* and and standard Color error and of Word items represent correct. mean Higher time scores and mean standard better error performance required on to these measures. MMSE, mini-mental state exam; RAVLT, Rey Auditory Verbal Learning Test Delayed Recall trial; JLO, Judgment of Line Orientation; BNT: Boston Naming T DASO, delta activity at sleep onset; D, DASO; T, time of observation; D*T, analyzed with DASO and time of observation together. Fixed factor: DASO (+) o

Table 2 span of this longitudinal study, increases the evidence

Figure 2 DASO, delta activity at sleep onset. Solid line, DASO; (À), Dashed line, DASO (+) group; STRW, Stroop Word; STRC, Stroop Color; STRCW, Stroop Color and Word; MMSE, Mini-Mental State Exam; RAVLT, Rey Auditory Verbal Learning Test; JLO, Judgment of Line Orientation; BNT, Boston Naming Test. Scores on Stroop Color, Word, and Color and Word represent mean time and standard error required to finish 200 items. Lower scores mean better performance on these measures. Scores on MMSE, RAVLT, Judgment of Line Orientation, and Boston Naming Test represent mean and standard error of items correct. Higher scores mean better performance on these measures base, suggesting that DASO is relatively common in In our longitudinal analyses, we also found that the healthy older adults. DASO (+) group exhibited better performance on the Our previously reported investigation of the Stroop reading condition with an effect size of À0.29 baseline data found a statistically significant difference (95% CI À0.53, À0.05). However, these associations in the reading condition of the Stroop test (Kawai et al., did not reach statistical significance. Unequivocally, 2016), with the presence of DASO associated with however, our findings do not support any long-term better performance on this simple reading task mea- negative impact of DASO on cognitive function in sure that captures speed of processing and vigilance. community-dwelling older adults without dementia.

Copyright # 2016 John Wiley & Sons, Ltd. Int J Geriatr Psychiatry 2016; 31: 1124–1135 A longitudinal examination in community-dwelling older adults 1131

Indeed, there was an overall signiﬁcant effect for DASO being associated with less self-reported depressive symptoms and lower trait anxiety. However, when

modeling we covaried with age, gender, and years of education, only the association of presence of DASO with lower -value by linear mixed p trait anxiety remained statistically signiﬁcant. This ﬁnding suggests less mental health distress among ) at baseline. All affective 0.09 0.04* 0.58 0.75 0.05 0.17 0.15 1.00 0.16 0.02* 0.96 0.46 À À À À those with DASO compared with those without DASO r( es on BAI and STAI represent 0.57, 0.42, 0.64, and is all the more striking given the observed trait like À À À stability of the presence of DASO over time. The mechanism explaining the relationship of 0.33 0.19 0.40 À À À

Effect size 95% CI D T D*T DASO to lower anxiety is unclear. In 22 participants reported with remote history of Axis I disorders, we n found no signiﬁcant association with trajectory of ) À any cognitive or affective function measures. In addition, DASO status was not associated with history DASO ( of Axis I disorders. The associations of DASO to n cognitive and affective measures did not change when covaried with history of Axis I disorders. However, It

DASO (+) is important to note that history of Axis I disorders

n may be underreported because the data entry depends

) on self-reported questionnaire and remote memory of À participants.

DASO ( One possibility is a direct protective effect of DASO.

n In healthy older adults, Anderson et al., reported that a higher rate of 0.5–1 Hz activity in frontal channel in nocturnal sleep correlated with better daytime execu- DASO (+) tive function (Anderson and Horne, 2003). This study n included delta activity in an all night study, not only in )

À slow wave sleep, which most likely includes DASO as well (Anderson and Horne, 2003). DASO ( Another possibility is that a positive effect of DASO n on anxiety may be the result of DASO’s association with better sleep quality and increased slow wave sleep. In our exploratory analyses, despite the fact that high- DASO (+) amplitude slow wave activity in N3 sleep was n ﬁ

) excluded in the de nition, there was a trend for DASO À

, number of subjects; GDS, Geriatric Depression Scale; BAI, Beck Anxiety Inventory; STAI, Spielberger Anxiety/Trait Scale: Trait to be associated with higher sleep efﬁciency (it did not n ﬁ

DASO ( reach statistical signi cance), and with longer N3 sleep, À

n which was statistically different from the DASO ( ) group (Table 4). There are several reports showing the correlation between maintenance of slow wave

DASO (+) sleep and better cognition (Kim et al., 2011; Lafortune

n et al., 2014). A recent study in older men by Song et al.,

) (2015) reported no correlation between slow wave À sleep and executive function (Trail Making Test Part

DASO ( B) or global cognition (MMSE), but the cognitive n

Baseline 12 months 24 monthsbattery 36 months in this investigation Total was not comprehensive and affective processes were not included. The effect of slow wave sleep on cognition remains controversial Longitudinal data for all affective parameters analyzed with linear mixed modeling DASO (+)

0.05. (Scullin, 2013; Scullin and Bliwise, 2015), but prior

< studies repeatedly show that decreased slow wave sleep p GDS 4.2 ± 0.7 30 5.7 ± 0.5 123 3.8 ± 1 18 5.7 ± 0.6 80 4.7 ± 1 19 6.3 ± 0.7 75 4.2 ± 0.9 18 5.9 ± 0.7 63 4.2 ± 0.4 85 5.9 ± 0.3 341 BAI 4.9 ± 0.9 29 6.4 ± 0.6 117 5.3 ± 1.5 18 5.4 ± 0.6 82 3.9 ± 1 19 5.1 ± 0.6 75 3.8 ± 1.2 18 4.6 ± 0.6 63 4.5 ± 0.5 84 5.5 ± 0.3 337 DASO, delta activity at sleep onset; D, DASO; T, time of observation; D*T, analyzed with DASO and time of observation together; Fixed factor, DASO (+) o parameters were analyzed as dependent variables. more anxiety. * anxiety. Scores on GDS, BAI, STAI test represent mean, and standard error of items correct. Higher scores on GDS mean higher severity of depression. Higher scor STAI 31.3 ± 1.1 30 35 ± 0.8 121 31.4 ± 1.7 18 34.4 ± 1.1 81 30.2 ± 1.4 19 34.2 ± 1.3 75 30 ± 1.8 18 34.6 ± 1.3 63 30.8 ± 0.7 85 34.6 ± 0.5 340

Table 3 is consistently correlated with higher levels of

Figure 3 DASO: delta activity at sleep onset GDS, Geriatric Depression Scale; BAI, Beck Anxiety Inventory; STAI, Spielberger Anxiety/Trait Scale: Trait anxiety. Scores on GDS, BAI, STAI test represent mean, and standard error of items correct. Higher scores on GDS mean higher severity of depression. Higher scores on BAI and STAI represent higher anxiety depression and anxiety symptoms (Armitage et al., of the 2007 American Academy of Sleep Medicine 2000; Borbely et al., 1984; Reynolds et al., 1983; Rosa manual (Berry et al., 2014). The lack of frontal et al., 1983). electrodes did not limit our ability to detect DASO, Previous studies reported that sleep manipulations, because, as it is shown in Figure 1, the amplitude is like sleep deprivation, affect mood in the older aults usually high enough to present in the central (Reynolds et al., 1986; Reynolds et al., 1987. However, electrodes, and the prevalence in our study is equiva- this remains to be tested, and sleep manipulation may lent to (even higher than) the one in a previous study indeed provide a valuable way to test both the stability performed with standard EEG recording (Katz and of DASO, and its association with cognition and affect Horowitz, 1983). Despite these limitations, this is by over time. For FIRDA, previous studies have re- far the largest study to date examining the longitudinal peatedly reported a relationship with pathological relationship of DASO to cognitive and affective func- mechanisms, either from a structural or functional tion among community-dwelling, healthy older adults abnormality (Stam and Pritchard, 1999; Watemberg in a US sample. Moreover, this study employed a full et al., 2002). For DASO, the clinical significance has objective neuropsychological test battery and PSG. been more controversial. Based on the data of patients Indeed, because we utilized nocturnal PSG, the evaluated in hospitals, correlation of DASO with brain time allowed for recording sleep is much longer than dysfunction has been reported (Klass and Brenner, what typically occurs in the daytime outpatient clinical 1995; Shiohama et al., 1993; Stam, 2011; Zurek et al., neurophysiology laboratory. Thus, the PSG may have 1985). Although these studies are not representative facilitated more detailed analyses of EEG changes of healthy community-dwelling older adults, the fact occurring in brief wake-to-sleep transitions, which that DASO has been reported repeatedly in older may occur often in the course of a routine overnight adults and in patients with structural lesions suggests PSG in an older adult. This situation may be particularly that age-related brain changes could generate DASO relevant for characterizing the nuances of EEGs of older (Gibbs and Gibbs, 1964; Klass and Brenner, 1995; humans, as the aging process is associated with in- Shiohama et al., 1993; Stam, 2011; Zurek et al., 1985). creased fluidity in such state transitions. The Katz and Horowitz investigation reported that Overall, the lack of association of DASO with long- DASO was present in 16% of normal older adults term trajectory of declining cognitive or affective without focal slow wave activity in baseline wake function in our study suggests that its presence in recording, and in line with the findings of our own healthy older adults at least represents normal varia- study, suggested that DASO thus represents a normal tion in PSG findings at sleep onset. The observed trait phenomenon (Katz and Horowitz 1983). like stability of DASO over time and its association Our study has several limitations, including the lack with reduced trait anxiety further suggest that the of baseline full montage EEG, the use of one rater presence of DASO may even represent a marker of responsible for determining absence or the presence cognitive and affective protection. Thus, we believe of DASO and the lack of frontal EEG electrodes due long-term effect of DASO to the trajectory of cognitive to utilizing traditional PSG montage before the issue and affective function is important for clinicians or

Copyright # 2016 John Wiley & Sons, Ltd. Int J Geriatr Psychiatry 2016; 31: 1124–1135 Copyright ogtdnleaiaini omnt-wligodradults older community-dwelling in examination longitudinal A Table 4 Longitudinal data for PSG parameters analyzed with linear mixed modeling

p-value by linear mixed Baseline 12 months 24 months 36 months Total modeling #

n À n n À n n À n n À n n À n

06Jh ie os Ltd. Sons, & Wiley John 2016 DASO (+) DASO ( ) DASO (+) DASO ( ) DASO (+) DASO ( ) DASO (+) DASO ( ) DASO (+) DASO ( ) Effect size 95% CI D T D*T

SleepLat (min) 35.2 ± 8.7 30 31.4 ± 3.4 122 20 ± 6.4 18 34.6 ± 5.1 70 32.5 ± 13.9 13 25.1 ± 5.4 61 20 ± 10.3 13 24.4 ± 7.1 50 28.4 ± 4.9 74 29.7 ± 2.4 303 À0.03 À0.29, 0.22 0.808 0.566 0.513 TST (min) 352.6 30 343.1 ± 7.5 122 355.9 ± 19.3 18 349.2 ± 10.6 70 356.6 ± 17.3 13 337.7 ± 11.3 61 352.4 ± 17.2 13 336.7 ± 11.6 50 354.1 ± 8.1 74 342.4 ± 4.9 303 0.14 À0.11, 0.40 0.275 0.897 0.941 ± 12.9 WASO (min) 95.1 30 126 ± 7.2 122 112.6 ± 22.9 18 118 ± 8.1 70 118.7 ± 16.5 13 121.5 ± 9 61 90.7 ± 16.9 13 123.9 ± 10.9 50 102.7 ± 8.3 74 122.9 ± 4.3 303 À0.27 À0.53, À0.02 0.085 0.891 0.438 ± 11.5 REM (min) 12.9 ± 1 30 13.4 ± 0.6 122 15 ± 1.4 18 12.2 ± 0.7 70 12.6 ± 1.5 13 14.8 ± 0.8 61 14.4 ± 1.5 13 11.7 ± 1 50 13.6 ± 0.6 74 13.1 ± 0.4 303 0.08 À0.17, 0.33 0.564 0.986 0.019* stage1 (min) 15.3 ± 1.5 30 17.5 ± 1 122 10.8 ± 1.3 18 13.9 ± 0.8 70 11.9 ± 1.7 13 11.6 ± 0.8 61 8.4 ± 1 13 11.6 ± 0.9 50 12.4 ± 0.8 74 14.5 ± 0.5 303 À0.24 À0.50, 0.01 0.524 0.00* 0.505 stage2 (min) 69.7 ± 1.7 30 68.1 ± 1 122 71.2 ± 2.3 18 73.6 ± 0.9 70 73.5 ± 1.8 13 71.3 ± 1.6 61 75.5 ± 1.5 13 76.1 ± 1 50 71.7 ± 1 74 71.3 ± 0.6 303 0.04 À0.21, 0.29 0.851 0.00* 0.322 stage3 (min) 1.3 ± 0.5 30 0.9 ± 0.2 122 2.2 ± 0.8 18 0.2 ± 0.1 70 2 ± 1.5 13 0.7 ± 0.3 61 1.7 ± 0.8 13 0.6 ± 0.2 50 1.7 ± 0.4 74 0.6 ± 0.1 303 0.47 0.22, 0.73 0.01* 0.915 0.228 stage4 (min) 0.9 ± 0.5 30 0.2 ± 0.1 122 0.8 ± 0.5 18 0.1 ± 0.1 70 0 ± 0 13 0 ± 0 61 0 ± 0 13 0 ± 0 50 0.6 ± 0.2 74 0.1 ± 0 303 0.42 0.17, 0.68 0.05* 0.01* 0.102 arousal (events/h) 2.4 ± 0.7 30 1.8 ± 0.3 122 0.7 ± 0.4 18 0.4 ± 0.1 70 0.6 ± 0.4 13 0.9 ± 0.3 61 0.1 ± 0.1 13 0.1 ± 0.1 50 1.3 ± 0.3 74 1 ± 0.1 303 0.12 À0.13, 0.38 0.277 0.00* 0.876 spontarI (events/h) 2.3 ± 0.6 30 1.5 ± 0.3 122 0.7 ± 0.4 18 0.4 ± 0.1 70 0.6 ± 0.4 13 0.7 ± 0.2 61 0 ± 0 13 0 ± 0 50 1.2 ± 0.3 74 0.8 ± 0.1 303 0.18 À0.06, 0.44 0.138 0.00* 0.886 SE (%) 75.6 ± 2.2 30 68.4 ± 1.4 122 73.4 ± 3.7 18 69.8 ± 1.8 69 70.4 ± 2.9 13 69 ± 2.1 61 73.5 ± 5 13 70.6 ± 2.3 50 73.8 ± 1.6 74 69.2 ± 0.9 302 0.3 0.04, 0.55 0.115 0.862 0.694 AHI (events/h) 32.2 ± 3.6 30 32.1 ± 2 122 24.4 ± 5.2 18 23.3 ± 2.5 70 21.4 ± 4.4 13 22.9 ± 2.4 61 22.5 ± 10.5 13 24.1 ± 4.8 50 26.7 ± 2.8 74 26.9 ± 1.4 303 À0.008 À0.26, 0.24 0.72 0.01* 0.99 AI (events/h) 23 ± 3.8 30 22.1 ± 1.8 122 22.6 ± 5.1 18 20.6 ± 2.4 70 16.5 ± 3.7 13 16.3 ± 2.2 61 17.3 ± 9.8 13 18.1 ± 4.8 50 20.8 ± 2.7 74 19.9 ± 1.3 303 0.03 À0.21, 0.29 0.56 0.34 0.99 HI (events/h) 9.2 ± 1.4 30 10 ± 1.1 122 1.7 ± 0.4 18 2.7 ± 0.7 70 4.8 ± 1.6 13 6.6 ± 0.8 61 5.2 ± 2 13 5.9 ± 1.5 50 5.9 ± 0.8 74 6.9 ± 0.6 303 À0.1 À0.35, 0.14 0.491 0.00* 0.995 minSpO2(%) 80.9 ± 3 30 79.3 ± 1.8 121 79.5 ± 4.7 18 81.3 ± 2.1 70 84.8 ± 1 13 81.7 ± 2.5 60 77.6 ± 7.2 12 83.3 ± 1.9 49 80.7 ± 2 73 80.9 ± 1.1 300 À0.01 À0.26, 0.24 0.819 0.817 0.673

DASO: delta activity at sleep onset. Numbers in left two columns represent mean and standard error of PSG parameters and scores on sleep related questionnaires. Multiple regression analyses were performed with DASO, Age, Gender and BMI as independent variables. SleepLat, sleep latency; TST, total sleep time; WASO, wake after sleep onset; REM, rapid eye movement sleep; SE, sleep efﬁciency; AHI, apnea hypopnea index; AI, apnea index; HI, hypopnea index; spontarI, spontaneous arousal index; minSpO2, minimum Oxygen saturation measured by pulse oximetry. *p < 0.05.

Table 5 Longitudinal data for all sleep related questionnaires analyzed with linear mixed modeling

p-value by linear Baseline 12 months 24 months 36 months Total mixed modeling n eit Psychiatry Geriatr J Int Effect DASO (+) n DASO (À) n DASO (+) n DASO (À) n DASO (+) n DASO (À) n DASO (+) n DASO (À) n DASO (+) n DASO (À) n size 95% CI D T D*T

ESS 6.8 ± 0.7 30 7.6 ± 0.4 117 7.5 ± 0.9 17 7.4 ± 0.5 75 6.5 ± 1 19 7.7 ± 0.6 66 7.3 ± 1 17 8 ± 0.6 62 7 ± 0.4 83 7.6 ± 0.2 320 À0.13 À0.38, 0.10 0.79 0.91 0.67 PSQI 6.8 ± 0.7 30 7.1 ± 0.4 118 6.5 ± 0.8 17 6.5 ± 0.4 74 7.6 ± 1 18 6.7 ± 0.5 67 6.7 ± 1 17 6.5 ± 0.6 60 6.9 ± 0.4 82 6.7 ± 0.2 319 0.05 À0.19, 0.29 0.96 0.85 0.87 FOSQ 18.8 ± 0.9 30 17.8 ± 0.2 116 17.9 ± 0.5 17 18 ± 0.2 75 18 ± 0.4 19 18.9 ± 1.2 64 18.1 ± 0.5 17 18.7 ± 1.2 53 18.3 ± 0.4 83 18.2 ± 0.3 308 0.02 À0.22, 0.26 0.84 0.97 0.68 MEQ 58.5 ± 2 30 58.3 ± 0.8 116 55.1 ± 2.4 17 58.1 ± 1.1 72 59.8 ± 2.5 19 58.5 ± 1.1 68 58.1 ± 3.3 16 57.5 ± 1.3 61 58 ± 1.2 82 58.1 ± 0.5 317 À0.01 À0.25, 0.23 0.80 0.29 0.37

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